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ely-eye/bench/sets/code.jsonl
T
ZacharyZhang-NY 77219c930b Add third-party benchmark suite frozen at 50,789 sources / 5,308 queries 
Ground truth comes only from third-party annotations (MMLongBench-Doc
evidence_page_ids, VisRAG qrels, ScreenSpot-v2 bboxes, Video-MME QA,
LongMemEval answer_session_ids, CodeSearchNet func_path+func_name) and
from document structure; no model judgement is used anywhere.

- bench/corpus/manifest.jsonl: 28 sources with url, retrieved_at, sha256,
  annotation_source, license, files[]; verified by bench.manifest_check
- bench/sets/{pdf,image,ui_screenshot,video,code,conversation}.{jsonl} plus
  corpus indexes and a manifest that freezes every file's sha256
- 2,928 answerable + 2,380 unanswerable queries over 854 holders; every
  query carries scope {holder, scenario, as_of} for transactive routing
- bench/validate_sets.py fails on missing gold, holder mismatch between
  gold and query, gold observed after as_of, and manifest digest drift
2026-10-06 12:05:43 -04:00

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{"answer": "csn:20tab/twentytab-treeeditor:treeeditor/admin.py:TreeEditor._collect_editable_booleans#20240", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "treeeditor/admin.py", "symbol": "TreeEditor._collect_editable_booleans"}, "source_id": "csn:20tab/twentytab-treeeditor:treeeditor/admin.py:TreeEditor._collect_editable_booleans#20240"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/20tab/twentytab-treeeditor/blob/f89d459b1348961880cd488df95690e68529f96b/treeeditor/admin.py#L215-L240", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:20tab-twentytab-treeeditor:TreeEditor._collect_editable_booleans-b65951cde5", "question": "Collect all fields marked as editable booleans. We do not\n want the user to be able to edit arbitrary fields by crafting\n an AJAX request by hand.", "scope": {"holder": "20tab-twentytab-treeeditor", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:20tab/twentytab-treeeditor:treeeditor/admin.py:TreeEditor.has_delete_permission#20244", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "treeeditor/admin.py", "symbol": "TreeEditor.has_delete_permission"}, "source_id": "csn:20tab/twentytab-treeeditor:treeeditor/admin.py:TreeEditor.has_delete_permission#20244"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/20tab/twentytab-treeeditor/blob/f89d459b1348961880cd488df95690e68529f96b/treeeditor/admin.py#L363-L374", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:20tab-twentytab-treeeditor:TreeEditor.has_delete_permission-ca0cf22fa4", "question": "Implement a lookup for object level permissions. Basically the same as\n ModelAdmin.has_delete_permission, but also passes the obj parameter in.", "scope": {"holder": "20tab-twentytab-treeeditor", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:3DLIRIOUS/MeshLabXML:meshlabxml/mlx.py:FilterScript.add_layer#6360", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "meshlabxml/mlx.py", "symbol": "FilterScript.add_layer"}, "source_id": "csn:3DLIRIOUS/MeshLabXML:meshlabxml/mlx.py:FilterScript.add_layer#6360"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/3DLIRIOUS/MeshLabXML/blob/177cce21e92baca500f56a932d66bd9a33257af8/meshlabxml/mlx.py#L181-L191", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:3DLIRIOUS-MeshLabXML:FilterScript.add_layer-6d01968d4e", "question": "Add new mesh layer to the end of the stack\n\n Args:\n label (str): new label for the mesh layer\n change_layer (bool): change to the newly created layer", "scope": {"holder": "3DLIRIOUS-MeshLabXML", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:3DLIRIOUS/MeshLabXML:meshlabxml/compute.py:measure_geometry#6387", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "meshlabxml/compute.py", "symbol": "measure_geometry"}, "source_id": "csn:3DLIRIOUS/MeshLabXML:meshlabxml/compute.py:measure_geometry#6387"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/3DLIRIOUS/MeshLabXML/blob/177cce21e92baca500f56a932d66bd9a33257af8/meshlabxml/compute.py#L117-L143", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:3DLIRIOUS-MeshLabXML:measure_geometry-ec89a54ba7", "question": "Compute a set of geometric measures of a mesh/pointcloud.\n\n Bounding box extents and diagonal, principal axis, thin shell barycenter\n (mesh only), vertex barycenter and quality-weighted barycenter (pointcloud\n only), surface area (mesh only), volume (closed mesh) and Inertia tensor\n Matrix (closed mesh).\n\n Args:\n script: the mlx.FilterScript object or script filename to write\n the filter to.\n\n Layer stack:\n No impacts\n\n MeshLab versions:\n 2016.12\n 1.3.4BETA\n\n Bugs:\n Bounding box extents not computed correctly for some volumes", "scope": {"holder": "3DLIRIOUS-MeshLabXML", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:4degrees/riffle:setup.py:BuildResources.finalize_options#15487", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "setup.py", "symbol": "BuildResources.finalize_options"}, "source_id": "csn:4degrees/riffle:setup.py:BuildResources.finalize_options#15487"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/4degrees/riffle/blob/e5a0d908df8c93ff1ee7abdda8875fd1667df53d/setup.py#L48-L51", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:4degrees-riffle:BuildResources.finalize_options-d0399ca77d", "question": "Finalize options to be used.", "scope": {"holder": "4degrees-riffle", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:4degrees/riffle:source/riffle/browser.py:FilesystemBrowser._onNavigate#15483", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "source/riffle/browser.py", "symbol": "FilesystemBrowser._onNavigate"}, "source_id": "csn:4degrees/riffle:source/riffle/browser.py:FilesystemBrowser._onNavigate#15483"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/4degrees/riffle/blob/e5a0d908df8c93ff1ee7abdda8875fd1667df53d/source/riffle/browser.py#L146-L151", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:4degrees-riffle:FilesystemBrowser._onNavigate-3b6ef681ea", "question": "Handle selection of path segment.", "scope": {"holder": "4degrees-riffle", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:5j9/wikitextparser:wikitextparser/_wikitext.py:SubWikiText.ancestors#7911", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "wikitextparser/_wikitext.py", "symbol": "SubWikiText.ancestors"}, "source_id": "csn:5j9/wikitextparser:wikitextparser/_wikitext.py:SubWikiText.ancestors#7911"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/5j9/wikitextparser/blob/1347425814361d7955342c53212edbb27f0ff4b5/wikitextparser/_wikitext.py#L1065-L1088", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:5j9-wikitextparser:SubWikiText.ancestors-a2cb35e759", "question": "Return the ancestors of the current node.\n\n :param type_: the type of the desired ancestors as a string.\n Currently the following types are supported: {Template,\n ParserFunction, WikiLink, Comment, Parameter, ExtensionTag}.\n The default is None and means all the ancestors of any type above.", "scope": {"holder": "5j9-wikitextparser", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:5j9/wikitextparser:wikitextparser/_wikitext.py:WikiText._pp_type_to_spans#7897", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "wikitextparser/_wikitext.py", "symbol": "WikiText._pp_type_to_spans"}, "source_id": "csn:5j9/wikitextparser:wikitextparser/_wikitext.py:WikiText._pp_type_to_spans#7897"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/5j9/wikitextparser/blob/1347425814361d7955342c53212edbb27f0ff4b5/wikitextparser/_wikitext.py#L481-L494", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:5j9-wikitextparser:WikiText._pp_type_to_spans-b5c66d196f", "question": "Create the arguments for the parse function used in pformat method.\n\n Only return sub-spans and change the them to fit the new scope, i.e\n self.string.", "scope": {"holder": "5j9-wikitextparser", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:5monkeys/django-bananas:bananas/admin/api/mixins.py:BananasAPI.get_view_name#12384", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "bananas/admin/api/mixins.py", "symbol": "BananasAPI.get_view_name"}, "source_id": "csn:5monkeys/django-bananas:bananas/admin/api/mixins.py:BananasAPI.get_view_name#12384"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/5monkeys/django-bananas/blob/cfd318c737f6c4580036c13d2acf32bca96654bf/bananas/admin/api/mixins.py#L90-L116", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:5monkeys-django-bananas:BananasAPI.get_view_name-a09ab63a5e", "question": "Get or generate human readable view name.\n Extended version from DRF to support usage from both class and instance.", "scope": {"holder": "5monkeys-django-bananas", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:5monkeys/django-bananas:bananas/url.py:get_engine#12390", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "bananas/url.py", "symbol": "get_engine"}, "source_id": "csn:5monkeys/django-bananas:bananas/url.py:get_engine#12390"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/5monkeys/django-bananas/blob/cfd318c737f6c4580036c13d2acf32bca96654bf/bananas/url.py#L92-L134", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:5monkeys-django-bananas:get_engine-19ff20a9db", "question": "Perform a lookup in _ENGINE_MAPPING using engine_string.\n\n :param scheme: '+'-separated string Maximum of 2 parts,\n i.e \"postgres+psycopg\" is OK, \"postgres+psycopg2+postgis\" is NOT OK.\n :return: Engine string", "scope": {"holder": "5monkeys-django-bananas", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:AartGoossens/goldencheetahlib:goldencheetahlib/client.py:GoldenCheetahClient._get_request#19503", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "goldencheetahlib/client.py", "symbol": "GoldenCheetahClient._get_request"}, "source_id": "csn:AartGoossens/goldencheetahlib:goldencheetahlib/client.py:GoldenCheetahClient._get_request#19503"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/AartGoossens/goldencheetahlib/blob/ebe57de7d94280674c8440a81f53ac02f0b4eb43/goldencheetahlib/client.py#L155-L181", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:AartGoossens-goldencheetahlib:GoldenCheetahClient._get_request-4adc3e6124", "question": "Do actual GET request to GC REST API\n Also validates responses.\n\n Keyword arguments:\n endpoint -- full endpoint for GET request", "scope": {"holder": "AartGoossens-goldencheetahlib", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:AartGoossens/goldencheetahlib:goldencheetahlib/client.py:GoldenCheetahClient._request_activity_list#19499", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "goldencheetahlib/client.py", "symbol": "GoldenCheetahClient._request_activity_list"}, "source_id": "csn:AartGoossens/goldencheetahlib:goldencheetahlib/client.py:GoldenCheetahClient._request_activity_list#19499"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/AartGoossens/goldencheetahlib/blob/ebe57de7d94280674c8440a81f53ac02f0b4eb43/goldencheetahlib/client.py#L85-L110", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:AartGoossens-goldencheetahlib:GoldenCheetahClient._request_activity_list-a30b2174ef", "question": "Actually do the request for activity list\n This call is slow and therefore this method is memory cached.\n\n Keyword arguments:\n athlete -- Full name of athlete", "scope": {"holder": "AartGoossens-goldencheetahlib", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:AkihikoITOH/capybara:capybara/virtualenv/lib/python2.7/site-packages/pip/_vendor/_markerlib/markers.py:ASTWhitelist.visit#15862", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "capybara/virtualenv/lib/python2.7/site-packages/pip/_vendor/_markerlib/markers.py", "symbol": "ASTWhitelist.visit"}, "source_id": "csn:AkihikoITOH/capybara:capybara/virtualenv/lib/python2.7/site-packages/pip/_vendor/_markerlib/markers.py:ASTWhitelist.visit#15862"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/AkihikoITOH/capybara/blob/e86c2173ea386654f4ae061148e8fbe3f25e715c/capybara/virtualenv/lib/python2.7/site-packages/pip/_vendor/_markerlib/markers.py#L70-L76", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:AkihikoITOH-capybara:ASTWhitelist.visit-d73207e9cb", "question": "Ensure statement only contains allowed nodes.", "scope": {"holder": "AkihikoITOH-capybara", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:AkihikoITOH/capybara:capybara/virtualenv/lib/python2.7/site-packages/pip/vcs/__init__.py:VersionControl.run_command#16187", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "capybara/virtualenv/lib/python2.7/site-packages/pip/vcs/__init__.py", "symbol": "VersionControl.run_command"}, "source_id": "csn:AkihikoITOH/capybara:capybara/virtualenv/lib/python2.7/site-packages/pip/vcs/__init__.py:VersionControl.run_command#16187"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/AkihikoITOH/capybara/blob/e86c2173ea386654f4ae061148e8fbe3f25e715c/capybara/virtualenv/lib/python2.7/site-packages/pip/vcs/__init__.py#L301-L321", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:AkihikoITOH-capybara:VersionControl.run_command-d456583f2b", "question": "Run a VCS subcommand\n This is simply a wrapper around call_subprocess that adds the VCS\n command name, and checks that the VCS is available", "scope": {"holder": "AkihikoITOH-capybara", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:Alignak-monitoring-contrib/alignak-backend-client:alignak_backend_client/client.py:Backend.decode#14960", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "alignak_backend_client/client.py", "symbol": "Backend.decode"}, "source_id": "csn:Alignak-monitoring-contrib/alignak-backend-client:alignak_backend_client/client.py:Backend.decode#14960"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Alignak-monitoring-contrib/alignak-backend-client/blob/1e21f6ce703e66984d1f9b20fe7866460ab50b39/alignak_backend_client/client.py#L199-L221", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Alignak-monitoring-contrib-alignak-backend-client:Backend.decode-f283cc66b1", "question": "Decodes and returns the response as JSON (dict) or raise BackendException\n :param response: requests.response object\n :return: dict", "scope": {"holder": "Alignak-monitoring-contrib-alignak-backend-client", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:Alignak-monitoring-contrib/alignak-backend-client:alignak_backend_client/client.py:Backend.set_token#14961", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "alignak_backend_client/client.py", "symbol": "Backend.set_token"}, "source_id": "csn:Alignak-monitoring-contrib/alignak-backend-client:alignak_backend_client/client.py:Backend.set_token#14961"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Alignak-monitoring-contrib/alignak-backend-client/blob/1e21f6ce703e66984d1f9b20fe7866460ab50b39/alignak_backend_client/client.py#L223-L238", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Alignak-monitoring-contrib-alignak-backend-client:Backend.set_token-e117ab4734", "question": "Set token in authentification for next requests\n :param token: str. token to set in auth. If None, reinit auth", "scope": {"holder": "Alignak-monitoring-contrib-alignak-backend-client", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:AnthonyMRios/pymetamap:pymetamap/SubprocessBackend.py:SubprocessBackend.extract_concepts#9010", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pymetamap/SubprocessBackend.py", "symbol": "SubprocessBackend.extract_concepts"}, "source_id": "csn:AnthonyMRios/pymetamap:pymetamap/SubprocessBackend.py:SubprocessBackend.extract_concepts#9010"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/AnthonyMRios/pymetamap/blob/01f35802ad13f2eb7dff033e66e5445e8f5bc039/pymetamap/SubprocessBackend.py#L27-L175", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:AnthonyMRios-pymetamap:SubprocessBackend.extract_concepts-2ae2558c37", "question": "extract_concepts takes a list of sentences and ids(optional)\n then returns a list of Concept objects extracted via\n MetaMap.\n\n Supported Options:\n Composite Phrase -Q\n Word Sense Disambiguation -y\n use strict model -A\n use relaxed model -C\n allow large N -l\n allow overmatches -o\n allow concept gaps -g\n term processing -z\n No Derivational Variants -d\n All Derivational Variants -D\n Ignore Word Order -i\n Allow Acronym Variants -a\n Unique Acronym Variants -u\n Prefer Multiple Concepts -Y\n Ignore Stop Phrases -K\n Compute All Mappings -b\n MM Data Version -V\n Exclude Sources -e\n Restrict to Sources -R\n Restrict to Semantic Types -J\n Exclude Semantic Types -k\n \n\n For information about the available options visit\n http://metamap.nlm.nih.gov/.\n\n Note: If an error is encountered the process will be closed\n and whatever was processed, if anything, will be\n returned along with the error found.", "scope": {"holder": "AnthonyMRios-pymetamap", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:AnthonyMRios/pymetamap:pymetamap/SubprocessBackendLite.py:SubprocessBackendLite.extract_concepts#9011", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pymetamap/SubprocessBackendLite.py", "symbol": "SubprocessBackendLite.extract_concepts"}, "source_id": "csn:AnthonyMRios/pymetamap:pymetamap/SubprocessBackendLite.py:SubprocessBackendLite.extract_concepts#9011"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/AnthonyMRios/pymetamap/blob/01f35802ad13f2eb7dff033e66e5445e8f5bc039/pymetamap/SubprocessBackendLite.py#L27-L115", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:AnthonyMRios-pymetamap:SubprocessBackendLite.extract_concepts-d754c27ab1", "question": "extract_concepts takes a list of sentences and ids(optional)\n then returns a list of Concept objects extracted via\n MetaMapLite.\n\n Supported Options:\n Restrict to Semantic Types --restrict_to_sts\n Restrict to Sources --restrict_to_sources\n\n For information about the available options visit\n http://metamap.nlm.nih.gov/.\n\n Note: If an error is encountered the process will be closed\n and whatever was processed, if anything, will be\n returned along with the error found.", "scope": {"holder": "AnthonyMRios-pymetamap", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:Azure/Azure-MachineLearning-ClientLibrary-Python:azureml/__init__.py:Datasets.add_from_dataframe#7275", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "azureml/__init__.py", "symbol": "Datasets.add_from_dataframe"}, "source_id": "csn:Azure/Azure-MachineLearning-ClientLibrary-Python:azureml/__init__.py:Datasets.add_from_dataframe#7275"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Azure/Azure-MachineLearning-ClientLibrary-Python/blob/d1211b289747671898eb063013e0dc53d3c80acd/azureml/__init__.py#L465-L507", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Azure-Azure-MachineLearning-ClientLibrary-Python:Datasets.add_from_dataframe-838a58a2f2", "question": "Serialize the specified DataFrame and upload it as a new dataset.\n\n Parameters\n ----------\n dataframe : pandas.DataFrame\n Data to serialize.\n data_type_id : str\n Format to serialize to.\n Supported formats are:\n 'PlainText'\n 'GenericCSV'\n 'GenericTSV'\n 'GenericCSVNoHeader'\n 'GenericTSVNoHeader'\n See the azureml.DataTypeIds class for constants.\n name : str\n Name for the new dataset.\n description : str\n Description for the new dataset.\n\n Returns\n -------\n SourceDataset\n Dataset that was just created.\n Use open(), read_as_binary(), read_as_text() or to_dataframe() on\n the dataset object to get its contents as a stream, bytes, str or\n pandas DataFrame.", "scope": {"holder": "Azure-Azure-MachineLearning-ClientLibrary-Python", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:Azure/Azure-MachineLearning-ClientLibrary-Python:azureml/http.py:_RestClient.get_datasets#7283", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "azureml/http.py", "symbol": "_RestClient.get_datasets"}, "source_id": "csn:Azure/Azure-MachineLearning-ClientLibrary-Python:azureml/http.py:_RestClient.get_datasets#7283"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Azure/Azure-MachineLearning-ClientLibrary-Python/blob/d1211b289747671898eb063013e0dc53d3c80acd/azureml/http.py#L70-L73", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Azure-Azure-MachineLearning-ClientLibrary-Python:_RestClient.get_datasets-a426b60d85", "question": "Runs HTTP GET request to retrieve the list of datasets.", "scope": {"holder": "Azure-Azure-MachineLearning-ClientLibrary-Python", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:Azure/azure-sdk-for-python:azure-mgmt-alertsmanagement/azure/mgmt/alertsmanagement/operations/alerts_operations.py:AlertsOperations.get_all#2443", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "azure-mgmt-alertsmanagement/azure/mgmt/alertsmanagement/operations/alerts_operations.py", "symbol": "AlertsOperations.get_all"}, "source_id": "csn:Azure/azure-sdk-for-python:azure-mgmt-alertsmanagement/azure/mgmt/alertsmanagement/operations/alerts_operations.py:AlertsOperations.get_all#2443"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Azure/azure-sdk-for-python/blob/d7306fde32f60a293a7567678692bdad31e4b667/azure-mgmt-alertsmanagement/azure/mgmt/alertsmanagement/operations/alerts_operations.py#L39-L210", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Azure-azure-sdk-for-python:AlertsOperations.get_all-258f141cc1", "question": "List all the existing alerts, where the results can be selective by\n passing multiple filter parameters including time range and sorted on\n specific fields. .\n\n :param target_resource: Filter by target resource( which is full ARM\n ID) Default value is select all.\n :type target_resource: str\n :param target_resource_type: Filter by target resource type. Default\n value is select all.\n :type target_resource_type: str\n :param target_resource_group: Filter by target resource group name.\n Default value is select all.\n :type target_resource_group: str\n :param monitor_service: Filter by monitor service which is the source\n of the alert instance. Default value is select all. Possible values\n include: 'Application Insights', 'ActivityLog Administrative',\n 'ActivityLog Security', 'ActivityLog Recommendation', 'ActivityLog\n Policy', 'ActivityLog Autoscale', 'Log Analytics', 'Nagios',\n 'Platform', 'SCOM', 'ServiceHealth', 'SmartDetector', 'VM Insights',\n 'Zabbix'\n :type monitor_service: str or\n ~azure.mgmt.alertsmanagement.models.MonitorService\n :param monitor_condition: Filter by monitor condition which is the\n state of the monitor(alertRule) at monitor service. Default value is\n to select all. Possible values include: 'Fired', 'Resolved'\n :type monitor_condition: str or\n ~azure.mgmt.alertsmanagement.models.MonitorCondition\n :param severity: Filter by severity. Defaut value is select all.\n Possible values include: 'Sev0', 'Sev1', 'Sev2', 'Sev3', 'Sev4'\n :type severity: str or ~azure.mgmt.alertsmanagement.models.Severity\n :param alert_state: Filter by state of the alert instance. Default\n value is to select all. Possible values include: 'New',\n 'Acknowledged', 'Closed'\n :type alert_state: str or\n ~azure.mgmt.alertsmanagement.models.AlertState\n :param alert_rule: Filter by alert rule(monitor) which fired alert\n instance. Default value is to select all.\n :type alert_rule: str\n :param smart_group_id: Filter the alerts list by the Smart Group Id.\n Default value is none.\n :type smart_group_id: str\n :param include_context: Include context which has data contextual to\n the monitor service. Default value is false'\n :type include_context: bool\n :param include_egress_config: Include egress config which would be\n used for displaying the content in portal. Default value is 'false'.\n :type include_egress_config: bool\n :param page_count: Determines number of alerts returned per page in\n response. Permissible value is between 1 to 250. When the\n \"includeContent\" filter is selected, maximum value allowed is 25.\n Default value is 25.\n :type page_count: int\n :param sort_by: Sort the query results by input field, Default value\n is 'lastModifiedDateTime'. Possible values include: 'name',\n 'severity', 'alertState', 'monitorCondition', 'targetResource',\n 'targetResourceName', 'targetResourceGroup', 'targetResourceType',\n 'startDateTime', 'lastModifiedDateTime'\n :type sort_by: str or\n ~azure.mgmt.alertsmanagement.models.AlertsSortByFields\n :param sort_order: Sort the query results order in either ascending or\n descending. Default value is 'desc' for time fields and 'asc' for\n others. Possible values include: 'asc', 'desc'\n :type sort_order: str\n :param select: This filter allows to selection of the fields(comma\n seperated) which would be part of the the essential section. This\n would allow to project only the required fields rather than getting\n entire content. Default is to fetch all the fields in the essentials\n section.\n :type select: str\n :param time_range: Filter by time range by below listed values.\n Default value is 1 day. Possible values include: '1h', '1d', '7d',\n '30d'\n :type time_range: str or ~azure.mgmt.alertsmanagement.models.TimeRange\n :param custom_time_range: Filter by custom time range in the format\n <start-time>/<end-time> where time is in (ISO-8601 format)'.\n Permissible values is within 30 days from query time. Either\n timeRange or customTimeRange could be used but not both. Default is\n none.\n :type custom_time_range: str\n :param dict custom_headers: headers that will be added to the request\n :param bool raw: returns the direct response alongside the\n deserialized response\n :param operation_config: :ref:`Operation configuration\n overrides<msrest:optionsforoperations>`.\n :return: An iterator like instance of Alert\n :rtype:\n ~azure.mgmt.alertsmanagement.models.AlertPaged[~azure.mgmt.alertsmanagement.models.Alert]\n :raises:\n :class:`ErrorResponseException<azure.mgmt.alertsmanagement.models.ErrorResponseException>`", "scope": {"holder": "Azure-azure-sdk-for-python", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:Azure/azure-sdk-for-python:azure-servicebus/azure/servicebus/control_client/servicebusservice.py:ServiceBusService.with_filter#2710", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "azure-servicebus/azure/servicebus/control_client/servicebusservice.py", "symbol": "ServiceBusService.with_filter"}, "source_id": "csn:Azure/azure-sdk-for-python:azure-servicebus/azure/servicebus/control_client/servicebusservice.py:ServiceBusService.with_filter#2710"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Azure/azure-sdk-for-python/blob/d7306fde32f60a293a7567678692bdad31e4b667/azure-servicebus/azure/servicebus/control_client/servicebusservice.py#L182-L201", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Azure-azure-sdk-for-python:ServiceBusService.with_filter-8200cbb233", "question": "Returns a new service which will process requests with the specified\n filter. Filtering operations can include logging, automatic retrying,\n etc... The filter is a lambda which receives the HTTPRequest and\n another lambda. The filter can perform any pre-processing on the\n request, pass it off to the next lambda, and then perform any\n post-processing on the response.", "scope": {"holder": "Azure-azure-sdk-for-python", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:BD2KGenomics/toil-lib:src/toil_lib/abstractPipelineWrapper.py:AbstractPipelineWrapper.__get_empty_config#15688", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "src/toil_lib/abstractPipelineWrapper.py", "symbol": "AbstractPipelineWrapper.__get_empty_config"}, "source_id": "csn:BD2KGenomics/toil-lib:src/toil_lib/abstractPipelineWrapper.py:AbstractPipelineWrapper.__get_empty_config#15688"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/BD2KGenomics/toil-lib/blob/022a615fc3dc98fc1aaa7bfd232409962ca44fbd/src/toil_lib/abstractPipelineWrapper.py#L123-L132", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:BD2KGenomics-toil-lib:AbstractPipelineWrapper.__get_empty_config-68bffcf2f5", "question": "Returns the config file contents as a string. The config file is generated and then deleted.", "scope": {"holder": "BD2KGenomics-toil-lib", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:BD2KGenomics/toil-lib:src/toil_lib/tools/variant_manipulation.py:gatk_select_variants#15736", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "src/toil_lib/tools/variant_manipulation.py", "symbol": "gatk_select_variants"}, "source_id": "csn:BD2KGenomics/toil-lib:src/toil_lib/tools/variant_manipulation.py:gatk_select_variants#15736"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/BD2KGenomics/toil-lib/blob/022a615fc3dc98fc1aaa7bfd232409962ca44fbd/src/toil_lib/tools/variant_manipulation.py#L7-L44", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:BD2KGenomics-toil-lib:gatk_select_variants-e9c7ecf3de", "question": "Isolates a particular variant type from a VCF file using GATK SelectVariants\n\n :param JobFunctionWrappingJob job: passed automatically by Toil\n :param str mode: variant type (i.e. SNP or INDEL)\n :param str vcf_id: FileStoreID for input VCF file\n :param str ref_fasta: FileStoreID for reference genome fasta\n :param str ref_fai: FileStoreID for reference genome index file\n :param str ref_dict: FileStoreID for reference genome sequence dictionary file\n :return: FileStoreID for filtered VCF\n :rtype: str", "scope": {"holder": "BD2KGenomics-toil-lib", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:BlueDragonX/detach:detach.py:Detach._close_fd#15517", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "detach.py", "symbol": "Detach._close_fd"}, "source_id": "csn:BlueDragonX/detach:detach.py:Detach._close_fd#15517"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/BlueDragonX/detach/blob/e2e5a1076e19f508baf3ffb2b586a75934fbae28/detach.py#L50-L57", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:BlueDragonX-detach:Detach._close_fd-f10b509847", "question": "Close a file descriptor if it is open.", "scope": {"holder": "BlueDragonX-detach", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:BlueDragonX/detach:detach.py:Detach._close_open_fds#15518", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "detach.py", "symbol": "Detach._close_open_fds"}, "source_id": "csn:BlueDragonX/detach:detach.py:Detach._close_open_fds#15518"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/BlueDragonX/detach/blob/e2e5a1076e19f508baf3ffb2b586a75934fbae28/detach.py#L59-L64", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:BlueDragonX-detach:Detach._close_open_fds-d32fd2eb91", "question": "Close open file descriptors.", "scope": {"holder": "BlueDragonX-detach", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:CITGuru/PyInquirer:PyInquirer/color_print.py:_print_token_factory#6173", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "PyInquirer/color_print.py", "symbol": "_print_token_factory"}, "source_id": "csn:CITGuru/PyInquirer:PyInquirer/color_print.py:_print_token_factory#6173"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/CITGuru/PyInquirer/blob/10d53723b36ebc7bba311457ec4afd9747a5c777/PyInquirer/color_print.py#L10-L27", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:CITGuru-PyInquirer:_print_token_factory-163ec15cd2", "question": "Internal helper to provide color names.", "scope": {"holder": "CITGuru-PyInquirer", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:CLARIAH/iribaker:iribaker/__init__.py:to_iri#15619", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "iribaker/__init__.py", "symbol": "to_iri"}, "source_id": "csn:CLARIAH/iribaker:iribaker/__init__.py:to_iri#15619"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/CLARIAH/iribaker/blob/47d2e8e95472353769962fde7626881f53429379/iribaker/__init__.py#L17-L81", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:CLARIAH-iribaker:to_iri-573c50f2b2", "question": "Safely quotes an IRI in a way that is resilient to unicode and incorrect\n arguments (checks for RFC 3987 compliance and falls back to percent encoding)", "scope": {"holder": "CLARIAH-iribaker", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:Chilipp/sphinx-nbexamples:sphinx_nbexamples/__init__.py:Gallery.process_directories#14846", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "sphinx_nbexamples/__init__.py", "symbol": "Gallery.process_directories"}, "source_id": "csn:Chilipp/sphinx-nbexamples:sphinx_nbexamples/__init__.py:Gallery.process_directories#14846"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Chilipp/sphinx-nbexamples/blob/08e0319ff3c70f8a931dfa8890caf48add4d0470/sphinx_nbexamples/__init__.py#L778-L784", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Chilipp-sphinx-nbexamples:Gallery.process_directories-95c4e3c0cb", "question": "Create the rst files from the input directories in the\n :attr:`in_dir` attribute", "scope": {"holder": "Chilipp-sphinx-nbexamples", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:Chilipp/sphinx-nbexamples:sphinx_nbexamples/__init__.py:NotebookProcessor.data_download#14840", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "sphinx_nbexamples/__init__.py", "symbol": "NotebookProcessor.data_download"}, "source_id": "csn:Chilipp/sphinx-nbexamples:sphinx_nbexamples/__init__.py:NotebookProcessor.data_download#14840"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Chilipp/sphinx-nbexamples/blob/08e0319ff3c70f8a931dfa8890caf48add4d0470/sphinx_nbexamples/__init__.py#L486-L492", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Chilipp-sphinx-nbexamples:NotebookProcessor.data_download-8fa730d769", "question": "Create the rst string to download supplementary data", "scope": {"holder": "Chilipp-sphinx-nbexamples", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:ChrisBeaumont/soupy:soupy.py:Collection.dictzip#11946", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "soupy.py", "symbol": "Collection.dictzip"}, "source_id": "csn:ChrisBeaumont/soupy:soupy.py:Collection.dictzip#11946"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/ChrisBeaumont/soupy/blob/795f2f61f711f574d5218fc8a3375d02bda1104f/soupy.py#L708-L723", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:ChrisBeaumont-soupy:Collection.dictzip-4c69966839", "question": "Turn this collection into a Scalar(dict), by zipping keys and items.\n\n Parameters:\n\n keys: list or Collection of NavigableStrings\n The keys of the dictionary\n\n Examples:\n\n >>> c = Collection([Scalar(1), Scalar(2)])\n >>> c.dictzip(['a', 'b']).val() == {'a': 1, 'b': 2}\n True", "scope": {"holder": "ChrisBeaumont-soupy", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:ChrisBeaumont/soupy:soupy.py:Node.find_next_sibling#11948", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "soupy.py", "symbol": "Node.find_next_sibling"}, "source_id": "csn:ChrisBeaumont/soupy:soupy.py:Node.find_next_sibling#11948"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/ChrisBeaumont/soupy/blob/795f2f61f711f574d5218fc8a3375d02bda1104f/soupy.py#L1018-L1023", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:ChrisBeaumont-soupy:Node.find_next_sibling-f11143d934", "question": "Like :meth:`find`, but searches through :attr:`next_siblings`", "scope": {"holder": "ChrisBeaumont-soupy", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:CiscoDevNet/webexteamssdk:webexteamssdk/api/access_tokens.py:AccessTokensAPI.get#8285", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "webexteamssdk/api/access_tokens.py", "symbol": "AccessTokensAPI.get"}, "source_id": "csn:CiscoDevNet/webexteamssdk:webexteamssdk/api/access_tokens.py:AccessTokensAPI.get#8285"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/CiscoDevNet/webexteamssdk/blob/6fc2cc3557e080ba4b2a380664cb2a0532ae45cd/webexteamssdk/api/access_tokens.py#L104-L148", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:CiscoDevNet-webexteamssdk:AccessTokensAPI.get-267a9746b6", "question": "Exchange an Authorization Code for an Access Token.\n\n Exchange an Authorization Code for an Access Token that can be used to\n invoke the APIs.\n\n Args:\n client_id(basestring): Provided when you created your integration.\n client_secret(basestring): Provided when you created your\n integration.\n code(basestring): The Authorization Code provided by the user\n OAuth process.\n redirect_uri(basestring): The redirect URI used in the user OAuth\n process.\n\n Returns:\n AccessToken: An AccessToken object with the access token provided\n by the Webex Teams cloud.\n\n Raises:\n TypeError: If the parameter types are incorrect.\n ApiError: If the Webex Teams cloud returns an error.", "scope": {"holder": "CiscoDevNet-webexteamssdk", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:CiscoDevNet/webexteamssdk:webexteamssdk/api/team_memberships.py:TeamMembershipsAPI.delete#8230", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "webexteamssdk/api/team_memberships.py", "symbol": "TeamMembershipsAPI.delete"}, "source_id": "csn:CiscoDevNet/webexteamssdk:webexteamssdk/api/team_memberships.py:TeamMembershipsAPI.delete#8230"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/CiscoDevNet/webexteamssdk/blob/6fc2cc3557e080ba4b2a380664cb2a0532ae45cd/webexteamssdk/api/team_memberships.py#L221-L235", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:CiscoDevNet-webexteamssdk:TeamMembershipsAPI.delete-0f9de9b3ca", "question": "Delete a team membership, by ID.\n\n Args:\n membershipId(basestring): The team membership ID.\n\n Raises:\n TypeError: If the parameter types are incorrect.\n ApiError: If the Webex Teams cloud returns an error.", "scope": {"holder": "CiscoDevNet-webexteamssdk", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:Clinical-Genomics/scout:scout/adapter/mongo/acmg.py:ACMGHandler.get_evaluations#11657", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "scout/adapter/mongo/acmg.py", "symbol": "ACMGHandler.get_evaluations"}, "source_id": "csn:Clinical-Genomics/scout:scout/adapter/mongo/acmg.py:ACMGHandler.get_evaluations#11657"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Clinical-Genomics/scout/blob/90a551e2e1653a319e654c2405c2866f93d0ebb9/scout/adapter/mongo/acmg.py#L89-L100", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Clinical-Genomics-scout:ACMGHandler.get_evaluations-1c00a0693a", "question": "Return all evaluations for a certain variant.\n\n Args:\n variant_obj (dict): variant dict from the database\n\n Returns:\n pymongo.cursor: database cursor", "scope": {"holder": "Clinical-Genomics-scout", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:Clinical-Genomics/scout:scout/parse/matchmaker.py:genomic_features#11364", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "scout/parse/matchmaker.py", "symbol": "genomic_features"}, "source_id": "csn:Clinical-Genomics/scout:scout/parse/matchmaker.py:genomic_features#11364"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Clinical-Genomics/scout/blob/90a551e2e1653a319e654c2405c2866f93d0ebb9/scout/parse/matchmaker.py#L59-L139", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Clinical-Genomics-scout:genomic_features-3f938397ee", "question": "Extract and parse matchmaker-like genomic features from pinned variants\n of a patient\n Args:\n store(MongoAdapter) : connection to the database\n case_obj(dict): a scout case object\n sample_name(str): sample display name\n genes_only(bool): if True only gene names will be included in genomic features\n\n Returns:\n g_features(list): a list of genomic feature objects that looks like this:\n [\n {\n \"gene\": {\n \"id\": \"LIMS2\"\n },\n \"variant\": {\n \"alternateBases\": \"C\",\n \"assembly\": \"GRCh37\",\n \"end\": 128412081,\n \"referenceBases\": \"G\",\n \"referenceName\": \"2\",\n \"start\": 128412080\n },\n \"zygosity\": 1\n },\n ....\n ]", "scope": {"holder": "Clinical-Genomics-scout", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:ContinuumIO/pycosat:examples/sudoku.py:solve#10437", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "examples/sudoku.py", "symbol": "solve"}, "source_id": "csn:ContinuumIO/pycosat:examples/sudoku.py:solve#10437"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/ContinuumIO/pycosat/blob/b38fd85b6f4dcc18efd6027e96e5785104f53bb0/examples/sudoku.py#L64-L91", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:ContinuumIO-pycosat:solve-45aaf4c893", "question": "solve a Sudoku grid inplace", "scope": {"holder": "ContinuumIO-pycosat", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:ContinuumIO/pycosat:examples/sudoku.py:sudoku_clauses#10436", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "examples/sudoku.py", "symbol": "sudoku_clauses"}, "source_id": "csn:ContinuumIO/pycosat:examples/sudoku.py:sudoku_clauses#10436"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/ContinuumIO/pycosat/blob/b38fd85b6f4dcc18efd6027e96e5785104f53bb0/examples/sudoku.py#L24-L61", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:ContinuumIO-pycosat:sudoku_clauses-9b02fbecc9", "question": "Create the (11745) Sudoku clauses, and return them as a list.\n Note that these clauses are *independent* of the particular\n Sudoku puzzle at hand.", "scope": {"holder": "ContinuumIO-pycosat", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:Crypto-toolbox/btfxwss:btfxwss/client.py:BtfxWss.authenticate#8409", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "btfxwss/client.py", "symbol": "BtfxWss.authenticate"}, "source_id": "csn:Crypto-toolbox/btfxwss:btfxwss/client.py:BtfxWss.authenticate#8409"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Crypto-toolbox/btfxwss/blob/16827fa6aacb2c0e289aa852bf61a18df6905835/btfxwss/client.py#L326-L334", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Crypto-toolbox-btfxwss:BtfxWss.authenticate-b0dd13b34c", "question": "Authenticate with the Bitfinex API.\n\n :return:", "scope": {"holder": "Crypto-toolbox-btfxwss", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:Crypto-toolbox/btfxwss:btfxwss/queue_processor.py:QueueProcessor._handle_trades#8394", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "btfxwss/queue_processor.py", "symbol": "QueueProcessor._handle_trades"}, "source_id": "csn:Crypto-toolbox/btfxwss:btfxwss/queue_processor.py:QueueProcessor._handle_trades#8394"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Crypto-toolbox/btfxwss/blob/16827fa6aacb2c0e289aa852bf61a18df6905835/btfxwss/queue_processor.py#L310-L322", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Crypto-toolbox-btfxwss:QueueProcessor._handle_trades-226d7ce83a", "question": "Files trades in self._trades[chan_id].\n\n :param dtype:\n :param data:\n :param ts:\n :return:", "scope": {"holder": "Crypto-toolbox-btfxwss", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:Danielhiversen/PyXiaomiGateway:xiaomi_gateway/__init__.py:XiaomiGateway.get_from_hub#5386", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "xiaomi_gateway/__init__.py", "symbol": "XiaomiGateway.get_from_hub"}, "source_id": "csn:Danielhiversen/PyXiaomiGateway:xiaomi_gateway/__init__.py:XiaomiGateway.get_from_hub#5386"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Danielhiversen/PyXiaomiGateway/blob/21b38ab972d67402f2124dba02101ddfd8d9e0b4/xiaomi_gateway/__init__.py#L379-L384", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Danielhiversen-PyXiaomiGateway:XiaomiGateway.get_from_hub-bf88a27e71", "question": "Get data from gateway", "scope": {"holder": "Danielhiversen-PyXiaomiGateway", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:Danielhiversen/PyXiaomiGateway:xiaomi_gateway/__init__.py:XiaomiGateway.write_to_hub#5385", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "xiaomi_gateway/__init__.py", "symbol": "XiaomiGateway.write_to_hub"}, "source_id": "csn:Danielhiversen/PyXiaomiGateway:xiaomi_gateway/__init__.py:XiaomiGateway.write_to_hub#5385"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Danielhiversen/PyXiaomiGateway/blob/21b38ab972d67402f2124dba02101ddfd8d9e0b4/xiaomi_gateway/__init__.py#L330-L377", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Danielhiversen-PyXiaomiGateway:XiaomiGateway.write_to_hub-0749ded7c5", "question": "Send data to gateway to turn on / off device", "scope": {"holder": "Danielhiversen-PyXiaomiGateway", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:Dirrot/python-cryptocoincharts-api:CryptoCoinChartsApi/CryptoCoinChartsApi.py:API._getdata#19261", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "CryptoCoinChartsApi/CryptoCoinChartsApi.py", "symbol": "API._getdata"}, "source_id": "csn:Dirrot/python-cryptocoincharts-api:CryptoCoinChartsApi/CryptoCoinChartsApi.py:API._getdata#19261"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Dirrot/python-cryptocoincharts-api/blob/8bf7a35c1032847aaea322b304014cd52853c273/CryptoCoinChartsApi/CryptoCoinChartsApi.py#L98-L117", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Dirrot-python-cryptocoincharts-api:API._getdata-0d0af356c7", "question": "Wrapper method", "scope": {"holder": "Dirrot-python-cryptocoincharts-api", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:Dirrot/python-cryptocoincharts-api:CryptoCoinChartsApi/CryptoCoinChartsApi.py:API.tradingpair#19259", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "CryptoCoinChartsApi/CryptoCoinChartsApi.py", "symbol": "API.tradingpair"}, "source_id": "csn:Dirrot/python-cryptocoincharts-api:CryptoCoinChartsApi/CryptoCoinChartsApi.py:API.tradingpair#19259"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Dirrot/python-cryptocoincharts-api/blob/8bf7a35c1032847aaea322b304014cd52853c273/CryptoCoinChartsApi/CryptoCoinChartsApi.py#L44-L65", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Dirrot-python-cryptocoincharts-api:API.tradingpair-d8ea6d052c", "question": "Use this function to query price and volume data for ONE trading pair.\n A list with all coin currencies can be found by using the listcoins method.\n A example pair: currency1_currency2 = \"doge_btc\" \n Usage: http://api.cryptocoincharts.info/tradingPair/[currency1_currency2]", "scope": {"holder": "Dirrot-python-cryptocoincharts-api", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:DiscordBotList/DBL-Python-Library:dbl/client.py:Client.close#7432", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "dbl/client.py", "symbol": "Client.close"}, "source_id": "csn:DiscordBotList/DBL-Python-Library:dbl/client.py:Client.close#7432"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/DiscordBotList/DBL-Python-Library/blob/c1461ae0acc644cdeedef8fd6b5e36f76d81c1aa/dbl/client.py#L351-L359", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:DiscordBotList-DBL-Python-Library:Client.close-80f7d55540", "question": "This function is a coroutine.\n\n Closes all connections.", "scope": {"holder": "DiscordBotList-DBL-Python-Library", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:DiscordBotList/DBL-Python-Library:dbl/client.py:Client.get_widget_small#7431", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "dbl/client.py", "symbol": "Client.get_widget_small"}, "source_id": "csn:DiscordBotList/DBL-Python-Library:dbl/client.py:Client.get_widget_small#7431"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/DiscordBotList/DBL-Python-Library/blob/c1461ae0acc644cdeedef8fd6b5e36f76d81c1aa/dbl/client.py#L330-L349", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:DiscordBotList-DBL-Python-Library:Client.get_widget_small-9b8ab5ab63", "question": "This function is a coroutine.\n\n Generates the default small widget.\n\n Parameters\n ==========\n\n bot_id: int\n The bot_id of the bot you wish to make a widget for.\n\n Returns\n =======\n\n URL of the widget: str", "scope": {"holder": "DiscordBotList-DBL-Python-Library", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:EpistasisLab/scikit-mdr:mdr/continuous_mdr.py:ContinuousMDR.fit#13176", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "mdr/continuous_mdr.py", "symbol": "ContinuousMDR.fit"}, "source_id": "csn:EpistasisLab/scikit-mdr:mdr/continuous_mdr.py:ContinuousMDR.fit#13176"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/EpistasisLab/scikit-mdr/blob/768565deb10467d04a960d27e000ab38b7aa8a62/mdr/continuous_mdr.py#L57-L93", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:EpistasisLab-scikit-mdr:ContinuousMDR.fit-c13b97b5d4", "question": "Constructs the Continuous MDR feature map from the provided training data.\n\n Parameters\n ----------\n features: array-like {n_samples, n_features}\n Feature matrix\n targets: array-like {n_samples}\n List of target values for prediction\n\n Returns\n -------\n self: A copy of the fitted model", "scope": {"holder": "EpistasisLab-scikit-mdr", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:EpistasisLab/scikit-mdr:mdr/utils/utils.py:conditional_entropy#13182", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "mdr/utils/utils.py", "symbol": "conditional_entropy"}, "source_id": "csn:EpistasisLab/scikit-mdr:mdr/utils/utils.py:conditional_entropy#13182"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/EpistasisLab/scikit-mdr/blob/768565deb10467d04a960d27e000ab38b7aa8a62/mdr/utils/utils.py#L68-L86", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:EpistasisLab-scikit-mdr:conditional_entropy-63aec33569", "question": "Calculates the conditional entropy, H(X|Y), in the given base\n\n Parameters\n ----------\n X: array-like (# samples)\n An array of values for which to compute the conditional entropy\n Y: array-like (# samples)\n An array of values for which to compute the conditional entropy\n base: integer (default: 2)\n The base in which to calculate conditional entropy\n\n Returns\n ----------\n conditional_entropy: float\n The conditional entropy calculated according to the equation H(X|Y) = H(X,Y) - H(Y)", "scope": {"holder": "EpistasisLab-scikit-mdr", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:Erotemic/progiter:setup.py:parse_description#12079", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "setup.py", "symbol": "parse_description"}, "source_id": "csn:Erotemic/progiter:setup.py:parse_description#12079"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Erotemic/progiter/blob/24f1ad15d79f76cccef7b5811d341ab33b72bf1e/setup.py#L71-L104", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Erotemic-progiter:parse_description-3fccbb0f21", "question": "Parse the description in the README file\n\n CommandLine:\n python -c \"import setup; print(setup.parse_description())\"", "scope": {"holder": "Erotemic-progiter", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:Erotemic/xdoctest:make_rtd.py:modify_conf#12249", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "make_rtd.py", "symbol": "modify_conf"}, "source_id": "csn:Erotemic/xdoctest:make_rtd.py:modify_conf#12249"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Erotemic/xdoctest/blob/1c85209498bcf3791c919985b3d1904ec2339768/make_rtd.py#L42-L65", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Erotemic-xdoctest:modify_conf-3cdbdd2a0e", "question": "pip install redbaron", "scope": {"holder": "Erotemic-xdoctest", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:GGiecold/Density_Sampling:Density_Sampling.py:density_sampling#15575", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "Density_Sampling.py", "symbol": "density_sampling"}, "source_id": "csn:GGiecold/Density_Sampling:Density_Sampling.py:density_sampling#15575"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/GGiecold/Density_Sampling/blob/8c8e6c63a97fecf958238e12947e5e6542b64102/Density_Sampling.py#L212-L323", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:GGiecold-Density_Sampling:density_sampling-d2c268f1ca", "question": "The i-th sample point of the data-set 'data' is selected by density sampling\n with a probability given by:\n \n | 0 if outlier_density > LD[i];\n P(keep the i-th data-point) = | 1 if outlier_density <= LD[i] <= target_density;\n | target_density / LD[i] if LD[i] > target_density.\n \n Here 'LD[i]' denotes the local density of the i-th sample point of the data-set, \n whereas 'outlier_density' and 'target_density' are computed as particular percentiles\n of that distribution of local densities.\n \n Parameters\n ----------\n data : array of shape (n_samples, n_features)\n The data-set, a fraction of whose sample points will be extracted\n by density sampling.\n \n local_densities : array of shape (n_samples,), optional (default = None)\n The i-th entry of this vector corresponds to the local density of the i-th sample\n point in the order of the rows of 'data'.\n \n metric : string, optional (default = 'manhattan')\n The distance metric used to determine the nearest-neighbor to each data-point.\n The DistanceMetric class defined in scikit-learn's library lists all available\n metrics.\n \n kernel_mult : float, optional (default = 2.0)\n The kernel multiplier, which determine (in terms of the median of the distribution\n of distances among nearest neighbors) the extent of the regions centered\n around each sample point to consider for the computation of the local density\n associated to that particular sample point.\n \n outlier_percentile : float, optional (default = 0.01)\n Specify the outlier density as a percentile of the distribution of local densities.\n \n target_percentile : float, optional (default = 0.05)\n Specifiy the target density as a percentile of the distribution of local densities.\n Relevant only if 'desired_samples' is left unspecified. \n \n desired_samples : int, optional (default = None)\n The number of samples to be selected from the whole data-set such that members\n of rare populations and members of more common populations are roughly\n equally represented. To that purpose, a target density is computed that to selects about\n 'desired_samples' data-points.\n \n Returns\n -------\n samples_kept : array of shape (n_selected_samples,)\n If the 'i'-th sample point of 'data' has been selected by a given instance of\n density sampling, number 'i' is featured in the array returned by \n the present function.", "scope": {"holder": "GGiecold-Density_Sampling", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:GGiecold/Density_Sampling:Density_Sampling.py:get_local_densities#15574", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "Density_Sampling.py", "symbol": "get_local_densities"}, "source_id": "csn:GGiecold/Density_Sampling:Density_Sampling.py:get_local_densities#15574"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/GGiecold/Density_Sampling/blob/8c8e6c63a97fecf958238e12947e5e6542b64102/Density_Sampling.py#L147-L209", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:GGiecold-Density_Sampling:get_local_densities-e1acf061bb", "question": "For each sample point of the data-set 'data', estimate a local density in feature\n space by counting the number of neighboring data-points within a particular\n region centered around that sample point.\n \n Parameters\n ----------\n data : array of shape (n_samples, n_features)\n The data-set, a fraction of whose sample points will be extracted\n by density sampling.\n \n kernel_mult : float, optional (default = 2.0)\n The kernel multiplier, which determine (in terms of the median of the distribution\n of distances among nearest neighbors) the extent of the regions centered\n around each sample point to consider for the computation of the local density\n associated to that particular sample point.\n \n metric : string, optional (default = 'manhattan')\n The distance metric used to determine the nearest-neighbor to each data-point.\n The DistanceMetric class defined in scikit-learn's library lists all available\n metrics.\n \n Returns\n -------\n local_densities : array of shape (n_samples,)\n The i-th entry of this vector corresponds to the local density of the i-th sample\n point in the order of the rows of 'data'.", "scope": {"holder": "GGiecold-Density_Sampling", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:Gandi/pyramid_kvs:pyramid_kvs/perlsess.py:PerlSession.connect#13744", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pyramid_kvs/perlsess.py", "symbol": "PerlSession.connect"}, "source_id": "csn:Gandi/pyramid_kvs:pyramid_kvs/perlsess.py:PerlSession.connect#13744"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Gandi/pyramid_kvs/blob/36285f2e50d8181428f383f6fc1d79a34ea9ac3c/pyramid_kvs/perlsess.py#L31-L38", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Gandi-pyramid_kvs:PerlSession.connect-df42aed15c", "question": "Call that method in the pyramid configuration phase.", "scope": {"holder": "Gandi-pyramid_kvs", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:GeoffAtHome/lightwave:lightwave/lightwave.py:LWLink._send_message#19266", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "lightwave/lightwave.py", "symbol": "LWLink._send_message"}, "source_id": "csn:GeoffAtHome/lightwave:lightwave/lightwave.py:LWLink._send_message#19266"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/GeoffAtHome/lightwave/blob/2fab4ee8c9f14dd97dffd4b8cd70b217e884e581/lightwave/lightwave.py#L29-L34", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:GeoffAtHome-lightwave:LWLink._send_message-3c92ed8d66", "question": "Add message to queue and start processing the queue.", "scope": {"holder": "GeoffAtHome-lightwave", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:GeoffAtHome/lightwave:lightwave/lightwave.py:LWLink.turn_on_light#19267", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "lightwave/lightwave.py", "symbol": "LWLink.turn_on_light"}, "source_id": "csn:GeoffAtHome/lightwave:lightwave/lightwave.py:LWLink.turn_on_light#19267"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/GeoffAtHome/lightwave/blob/2fab4ee8c9f14dd97dffd4b8cd70b217e884e581/lightwave/lightwave.py#L46-L49", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:GeoffAtHome-lightwave:LWLink.turn_on_light-eaf8e4ffc3", "question": "Create the message to turn light on.", "scope": {"holder": "GeoffAtHome-lightwave", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:GreatFruitOmsk/tailhead:tailhead/__init__.py:Tailer.follow#14990", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "tailhead/__init__.py", "symbol": "Tailer.follow"}, "source_id": "csn:GreatFruitOmsk/tailhead:tailhead/__init__.py:Tailer.follow#14990"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/GreatFruitOmsk/tailhead/blob/a3b1324a39935f8ffcfda59328a9a458672889d9/tailhead/__init__.py#L249-L284", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:GreatFruitOmsk-tailhead:Tailer.follow-ffd220f10c", "question": "Iterator generator that returns lines as data is added to the file.\n\n None will be yielded if no new line is available.\n Caller may either wait and re-try or end iteration.", "scope": {"holder": "GreatFruitOmsk-tailhead", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:GreatFruitOmsk/tailhead:tailhead/__init__.py:Tailer.seek_previous_line#14987", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "tailhead/__init__.py", "symbol": "Tailer.seek_previous_line"}, "source_id": "csn:GreatFruitOmsk/tailhead:tailhead/__init__.py:Tailer.seek_previous_line#14987"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/GreatFruitOmsk/tailhead/blob/a3b1324a39935f8ffcfda59328a9a458672889d9/tailhead/__init__.py#L143-L196", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:GreatFruitOmsk-tailhead:Tailer.seek_previous_line-ed714d7b5b", "question": "Seek previous line relative to the current file position.\n\n :return: Position of the line or -1 if previous line was not found.", "scope": {"holder": "GreatFruitOmsk-tailhead", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:HaaLeo/pylint-file-header:pylintfileheader/file_header_checker.py:FileHeaderChecker.process_module#19460", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pylintfileheader/file_header_checker.py", "symbol": "FileHeaderChecker.process_module"}, "source_id": "csn:HaaLeo/pylint-file-header:pylintfileheader/file_header_checker.py:FileHeaderChecker.process_module#19460"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/HaaLeo/pylint-file-header/blob/245421616fdb6b9aca234fd58c503f9a937749f6/pylintfileheader/file_header_checker.py#L41-L61", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:HaaLeo-pylint-file-header:FileHeaderChecker.process_module-d650fe2e6e", "question": "Process the astroid node stream.", "scope": {"holder": "HaaLeo-pylint-file-header", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:HumanBrainProject/hbp-service-client:hbp_service_client/storage_service/api.py:ApiClient._prep_params#15578", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "hbp_service_client/storage_service/api.py", "symbol": "ApiClient._prep_params"}, "source_id": "csn:HumanBrainProject/hbp-service-client:hbp_service_client/storage_service/api.py:ApiClient._prep_params#15578"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/HumanBrainProject/hbp-service-client/blob/b338fb41a7f0e7b9d654ff28fcf13a56d03bff4d/hbp_service_client/storage_service/api.py#L85-L88", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:HumanBrainProject-hbp-service-client:ApiClient._prep_params-4eed5e74df", "question": "Remove empty (None) valued keywords and self from function parameters", "scope": {"holder": "HumanBrainProject-hbp-service-client", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:HumanBrainProject/hbp-service-client:hbp_service_client/storage_service/api.py:ApiClient.list_folder_content#15591", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "hbp_service_client/storage_service/api.py", "symbol": "ApiClient.list_folder_content"}, "source_id": "csn:HumanBrainProject/hbp-service-client:hbp_service_client/storage_service/api.py:ApiClient.list_folder_content#15591"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/HumanBrainProject/hbp-service-client/blob/b338fb41a7f0e7b9d654ff28fcf13a56d03bff4d/hbp_service_client/storage_service/api.py#L659-L715", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:HumanBrainProject-hbp-service-client:ApiClient.list_folder_content-6ca9c1b69a", "question": "List files and folders (not recursively) contained in the folder.\n\n This function does not retrieve all results, pages have\n to be manually retrieved by the caller.\n\n Args:\n folder (str): The UUID of the requested folder.\n name (str): Optional filter on entity name.\n entity_type (str): Optional filter on entity type.\n Admitted values: ['file', 'folder'].\n content_type (str): Optional filter on entity content type (only\n files are returned).\n page_size (int): Number of elements per page.\n page (int): Number of the page.\n ordering (str): Indicate on which fields to sort the result. Prepend\n '-' to invert order. Multiple values can be provided.\n Ordering is supported on: ['name', 'created_on', 'modified_on'].\n Example: 'ordering=name,created_on'\n\n Returns:\n A dictionary of the results::\n\n {\n u'count': 1,\n u'next': None,\n u'previous': None,\n u'results': [{u'content_type': u'plain/text',\n u'created_by': u'303447',\n u'created_on': u'2017-03-13T10:17:01.688472Z',\n u'description': u'',\n u'entity_type': u'file',\n u'modified_by': u'303447',\n u'modified_on': u'2017-03-13T10:17:01.688632Z',\n u'name': u'file_1',\n u'parent': u'eac11058-4ae0-4ea9-ada8-d3ea23887509',\n u'uuid': u'0e17eaac-cb00-4336-b9d7-657026844281'}]\n }\n\n Raises:\n StorageArgumentException: Invalid arguments\n StorageForbiddenException: Server response code 403\n StorageNotFoundException: Server response code 404\n StorageException: other 400-600 error codes", "scope": {"holder": "HumanBrainProject-hbp-service-client", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:HydraChain/hydrachain:hydrachain/consensus/base.py:BlockProposal.validate_votes#16670", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "hydrachain/consensus/base.py", "symbol": "BlockProposal.validate_votes"}, "source_id": "csn:HydraChain/hydrachain:hydrachain/consensus/base.py:BlockProposal.validate_votes#16670"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/HydraChain/hydrachain/blob/6c0919b0575dc8aa481f3a8c703e1a7f0575ecc3/hydrachain/consensus/base.py#L497-L511", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:HydraChain-hydrachain:BlockProposal.validate_votes-ab82735b90", "question": "set of validators may change between heights", "scope": {"holder": "HydraChain-hydrachain", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:HydraChain/hydrachain:hydrachain/consensus/manager.py:RoundManager.get_timeout#16679", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "hydrachain/consensus/manager.py", "symbol": "RoundManager.get_timeout"}, "source_id": "csn:HydraChain/hydrachain:hydrachain/consensus/manager.py:RoundManager.get_timeout#16679"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/HydraChain/hydrachain/blob/6c0919b0575dc8aa481f3a8c703e1a7f0575ecc3/hydrachain/consensus/manager.py#L572-L581", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:HydraChain-hydrachain:RoundManager.get_timeout-8b467feaab", "question": "setup a timeout for waiting for a proposal", "scope": {"holder": "HydraChain-hydrachain", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:IEMLdev/ieml:ieml/dictionary/version.py:DictionaryVersion.load#10376", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "ieml/dictionary/version.py", "symbol": "DictionaryVersion.load"}, "source_id": "csn:IEMLdev/ieml:ieml/dictionary/version.py:DictionaryVersion.load#10376"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/IEMLdev/ieml/blob/4c842ba7e6165e2f1b4a4e2e98759f9f33af5f25/ieml/dictionary/version.py#L145-L164", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:IEMLdev-ieml:DictionaryVersion.load-45e75bb446", "question": "Download the dictionary version and cache the retrieved file.\n :return: None", "scope": {"holder": "IEMLdev-ieml", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:IEMLdev/ieml:scripts/dictionary_tools.py:_add_mode_t#10380", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "scripts/dictionary_tools.py", "symbol": "_add_mode_t"}, "source_id": "csn:IEMLdev/ieml:scripts/dictionary_tools.py:_add_mode_t#10380"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/IEMLdev/ieml/blob/4c842ba7e6165e2f1b4a4e2e98759f9f33af5f25/scripts/dictionary_tools.py#L106-L112", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:IEMLdev-ieml:_add_mode_t-ebbf7708da", "question": "O:O:.O:O:.- => O:O:.O:O:.t.-", "scope": {"holder": "IEMLdev-ieml", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:IdentityPython/fedoidcmsg:src/fedoidcmsg/entity.py:FederationEntity.pick_signed_metadata_statements#19665", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "src/fedoidcmsg/entity.py", "symbol": "FederationEntity.pick_signed_metadata_statements"}, "source_id": "csn:IdentityPython/fedoidcmsg:src/fedoidcmsg/entity.py:FederationEntity.pick_signed_metadata_statements#19665"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/IdentityPython/fedoidcmsg/blob/d30107be02521fa6cdfe285da3b6b0cdd153c8cc/src/fedoidcmsg/entity.py#L91-L105", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:IdentityPython-fedoidcmsg:FederationEntity.pick_signed_metadata_statements-6c7c2b59b5", "question": "Pick signed metadata statements based on ISS pattern matching\n \n :param fo: Federation operators ID\n :param context: In connect with which operation (one of the values in \n :py:data:`fedoidc.CONTEXTS`). \n :return: list of tuples (FO ID, signed metadata statement)", "scope": {"holder": "IdentityPython-fedoidcmsg", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:IdentityPython/fedoidcmsg:src/fedoidcmsg/operator.py:LessOrEqual.eval#19547", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "src/fedoidcmsg/operator.py", "symbol": "LessOrEqual.eval"}, "source_id": "csn:IdentityPython/fedoidcmsg:src/fedoidcmsg/operator.py:LessOrEqual.eval#19547"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/IdentityPython/fedoidcmsg/blob/d30107be02521fa6cdfe285da3b6b0cdd153c8cc/src/fedoidcmsg/operator.py#L88-L117", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:IdentityPython-fedoidcmsg:LessOrEqual.eval-10eb3f18aa", "question": "Apply the less or equal algorithm on the ordered list of metadata\n statements\n \n :param orig: Start values\n :return:", "scope": {"holder": "IdentityPython-fedoidcmsg", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:JIC-CSB/jicbioimage.illustrate:jicbioimage/illustrate/__init__.py:AnnotatedImage.from_grayscale#22167", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "jicbioimage/illustrate/__init__.py", "symbol": "AnnotatedImage.from_grayscale"}, "source_id": "csn:JIC-CSB/jicbioimage.illustrate:jicbioimage/illustrate/__init__.py:AnnotatedImage.from_grayscale#22167"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/JIC-CSB/jicbioimage.illustrate/blob/d88ddf81ee3eb3949677e2ef746af8169ce88092/jicbioimage/illustrate/__init__.py#L159-L171", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:JIC-CSB-jicbioimage.illustrate:AnnotatedImage.from_grayscale-b20bbf803e", "question": "Return a canvas from a grayscale image.\n\n :param im: single channel image\n :channels_on: channels to populate with input image\n :returns: :class:`jicbioimage.illustrate.Canvas`", "scope": {"holder": "JIC-CSB-jicbioimage.illustrate", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:JIC-CSB/jicbioimage.illustrate:jicbioimage/illustrate/__init__.py:Canvas.draw_cross#22164", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "jicbioimage/illustrate/__init__.py", "symbol": "Canvas.draw_cross"}, "source_id": "csn:JIC-CSB/jicbioimage.illustrate:jicbioimage/illustrate/__init__.py:Canvas.draw_cross#22164"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/JIC-CSB/jicbioimage.illustrate/blob/d88ddf81ee3eb3949677e2ef746af8169ce88092/jicbioimage/illustrate/__init__.py#L65-L86", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:JIC-CSB-jicbioimage.illustrate:Canvas.draw_cross-7a817e634e", "question": "Draw a cross on the canvas.\n\n :param position: (row, col) tuple\n :param color: RGB tuple\n :param radius: radius of the cross (int)", "scope": {"holder": "JIC-CSB-jicbioimage.illustrate", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:Jasily/jasily-python:jasily/collection/funcs.py:CallableList.insert_func#21432", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "jasily/collection/funcs.py", "symbol": "CallableList.insert_func"}, "source_id": "csn:Jasily/jasily-python:jasily/collection/funcs.py:CallableList.insert_func#21432"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Jasily/jasily-python/blob/1c821a120ebbbbc3c5761f5f1e8a73588059242a/jasily/collection/funcs.py#L48-L53", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Jasily-jasily-python:CallableList.insert_func-35c52d094b", "question": "insert func with given arguments and keywords.", "scope": {"holder": "Jasily-jasily-python", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:Jasily/jasily-python:jasily/utils/__init__.py:jrepr#21314", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "jasily/utils/__init__.py", "symbol": "jrepr"}, "source_id": "csn:Jasily/jasily-python:jasily/utils/__init__.py:jrepr#21314"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Jasily/jasily-python/blob/1c821a120ebbbbc3c5761f5f1e8a73588059242a/jasily/utils/__init__.py#L11-L18", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Jasily-jasily-python:jrepr-605526a928", "question": "customized `repr()`.", "scope": {"holder": "Jasily-jasily-python", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:Jaymon/pyt:pyt/path.py:PathFinder._find_basename#16119", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pyt/path.py", "symbol": "PathFinder._find_basename"}, "source_id": "csn:Jaymon/pyt:pyt/path.py:PathFinder._find_basename#16119"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Jaymon/pyt/blob/801581fd0ae238158134bde1c937fa199fa626b2/pyt/path.py#L286-L361", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Jaymon-pyt:PathFinder._find_basename-fea83cb441", "question": "check if name combined with test prefixes or postfixes is found anywhere\n in the list of basenames\n\n :param name: string, the name you're searching for\n :param basenames: list, a list of basenames to check\n :param is_prefix: bool, True if this is a prefix search, which means it will\n also check if name matches any of the basenames without the prefixes or\n postfixes, if it is False then the prefixes or postfixes must be present\n (ie, the module we're looking for is the actual test module, not the parent\n modules it's contained in)\n :returns: string, the basename if it is found", "scope": {"holder": "Jaymon-pyt", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:Jaymon/pyt:pyt/path.py:PathFinder.paths#16123", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pyt/path.py", "symbol": "PathFinder.paths"}, "source_id": "csn:Jaymon/pyt:pyt/path.py:PathFinder.paths#16123"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Jaymon/pyt/blob/801581fd0ae238158134bde1c937fa199fa626b2/pyt/path.py#L490-L559", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Jaymon-pyt:PathFinder.paths-d44bab332e", "question": "given a basedir, yield all test modules paths recursively found in\n basedir that are test modules\n\n return -- generator", "scope": {"holder": "Jaymon-pyt", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:Jaza/s3-saver:s3_saver.py:S3Saver._delete_local#18501", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "s3_saver.py", "symbol": "S3Saver._delete_local"}, "source_id": "csn:Jaza/s3-saver:s3_saver.py:S3Saver._delete_local#18501"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Jaza/s3-saver/blob/81dc4447d76c2fc0b0238fb96fa70e879612e355/s3_saver.py#L53-L57", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Jaza-s3-saver:S3Saver._delete_local-e76c96ca33", "question": "Deletes the specified file from the local filesystem.", "scope": {"holder": "Jaza-s3-saver", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:Jaza/s3-saver:s3_saver.py:S3Saver.delete#18503", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "s3_saver.py", "symbol": "S3Saver.delete"}, "source_id": "csn:Jaza/s3-saver:s3_saver.py:S3Saver.delete#18503"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Jaza/s3-saver/blob/81dc4447d76c2fc0b0238fb96fa70e879612e355/s3_saver.py#L77-L86", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Jaza-s3-saver:S3Saver.delete-bf177bed80", "question": "Deletes the specified file, either locally or from S3, depending on the file's storage type.", "scope": {"holder": "Jaza-s3-saver", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:JonathanRaiman/ciseau:ciseau/sentence_tokenizer.py:detect_sentence_boundaries#14592", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "ciseau/sentence_tokenizer.py", "symbol": "detect_sentence_boundaries"}, "source_id": "csn:JonathanRaiman/ciseau:ciseau/sentence_tokenizer.py:detect_sentence_boundaries#14592"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/JonathanRaiman/ciseau/blob/f72d1c82d85eeb3d3ac9fac17690041725402175/ciseau/sentence_tokenizer.py#L15-L96", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:JonathanRaiman-ciseau:detect_sentence_boundaries-1451a4cd9e", "question": "Subdivide an input list of strings (tokens)\n into multiple lists according to detected\n sentence boundaries.\n\n ```\n detect_sentence_boundaries(\n [\"Cat \", \"sat \", \"mat\", \". \", \"Cat \", \"'s \", \"named \", \"Cool\", \".\"]\n )\n #=> [\n [\"Cat \", \"sat \", \"mat\", \". \"],\n [\"Cat \", \"'s \", \"named \", \"Cool\", \".\"]\n ]\n ```\n\n Arguments:\n ----------\n\n tokens : list<str>\n\n Returns:\n --------\n list<list<str>> : original list subdivided into multiple\n lists according to (detected) sentence boundaries.", "scope": {"holder": "JonathanRaiman-ciseau", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:JonathanRaiman/ciseau:ciseau/word_tokenizer.py:split_with_locations#14597", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "ciseau/word_tokenizer.py", "symbol": "split_with_locations"}, "source_id": "csn:JonathanRaiman/ciseau:ciseau/word_tokenizer.py:split_with_locations#14597"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/JonathanRaiman/ciseau/blob/f72d1c82d85eeb3d3ac9fac17690041725402175/ciseau/word_tokenizer.py#L112-L138", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:JonathanRaiman-ciseau:split_with_locations-6550dbdf39", "question": "Use an integer list to split the string\n contained in `text`.\n\n Arguments:\n ----------\n text : str, same length as locations.\n locations : list<int>, contains values\n 'SHOULD_SPLIT', 'UNDECIDED', and\n 'SHOULD_NOT_SPLIT'. Will create\n strings between each 'SHOULD_SPLIT'\n locations.\n Returns:\n --------\n Generator<str> : the substrings of text\n corresponding to the slices given\n in locations.", "scope": {"holder": "JonathanRaiman-ciseau", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:JukeboxPipeline/jukedj:src/jukedj/models.py:Project.path#19618", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "src/jukedj/models.py", "symbol": "Project.path"}, "source_id": "csn:JukeboxPipeline/jukedj:src/jukedj/models.py:Project.path#19618"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/JukeboxPipeline/jukedj/blob/d4159961c819c26792a278981ee68106ee15f3f3/src/jukedj/models.py#L88-L98", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:JukeboxPipeline-jukedj:Project.path-1e64360368", "question": "Set path\n\n :param value: The value for path\n :type value: str\n :raises: None", "scope": {"holder": "JukeboxPipeline-jukedj", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:JukeboxPipeline/jukedj:src/jukedj/models.py:add_default_deps#19610", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "src/jukedj/models.py", "symbol": "add_default_deps"}, "source_id": "csn:JukeboxPipeline/jukedj:src/jukedj/models.py:add_default_deps#19610"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/JukeboxPipeline/jukedj/blob/d4159961c819c26792a278981ee68106ee15f3f3/src/jukedj/models.py#L366-L380", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:JukeboxPipeline-jukedj:add_default_deps-27868f6de1", "question": "Add or create the default departments for the given project\n\n :param project: the project that needs default departments\n :type project: :class:`muke.models.Project`\n :returns: None\n :rtype: None\n :raises: None", "scope": {"holder": "JukeboxPipeline-jukedj", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:Julian/Ivoire:ivoire/result.py:DotsFormatter.result_summary#15234", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "ivoire/result.py", "symbol": "DotsFormatter.result_summary"}, "source_id": "csn:Julian/Ivoire:ivoire/result.py:DotsFormatter.result_summary#15234"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Julian/Ivoire/blob/5b8218cffa409ed733cf850a6fde16fafb8fc2af/ivoire/result.py#L206-L214", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Julian-Ivoire:DotsFormatter.result_summary-f060c3d93b", "question": "Return a summary of the results.", "scope": {"holder": "Julian-Ivoire", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:Julian/Ivoire:ivoire/transform.py:ExampleTransformer.visit_With#15239", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "ivoire/transform.py", "symbol": "ExampleTransformer.visit_With"}, "source_id": "csn:Julian/Ivoire:ivoire/transform.py:ExampleTransformer.visit_With#15239"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Julian/Ivoire/blob/5b8218cffa409ed733cf850a6fde16fafb8fc2af/ivoire/transform.py#L32-L53", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Julian-Ivoire:ExampleTransformer.visit_With-d31c6a9fe3", "question": "with describe(thing) as it:\n ...\n\n |\n v\n\n class TestThing(TestCase):\n ...", "scope": {"holder": "Julian-Ivoire", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:Julian/Virtue:virtue/cli.py:main#18325", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "virtue/cli.py", "symbol": "main"}, "source_id": "csn:Julian/Virtue:virtue/cli.py:main#18325"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Julian/Virtue/blob/d08be37d759c38c94a160bc13fe8f51bb2aeeedd/virtue/cli.py#L61-L70", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Julian-Virtue:main-74acba3b52", "question": "virtue discovers and runs tests found in the given objects.\n\n Provide it with one or more tests (packages, modules or objects) to run.", "scope": {"holder": "Julian-Virtue", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:Julian/Virtue:virtue/locators.py:prefixed_by#18305", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "virtue/locators.py", "symbol": "prefixed_by"}, "source_id": "csn:Julian/Virtue:virtue/locators.py:prefixed_by#18305"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Julian/Virtue/blob/d08be37d759c38c94a160bc13fe8f51bb2aeeedd/virtue/locators.py#L11-L25", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Julian-Virtue:prefixed_by-f5ba260646", "question": "Make a callable returning True for names starting with the given prefix.\n\n The returned callable takes two arguments, the attribute or name of\n the object, and possibly its corresponding value (which is ignored),\n as suitable for use with :meth:`ObjectLocator.is_test_module` and\n :meth:`ObjectLocator.is_test_method`\\ .", "scope": {"holder": "Julian-Virtue", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:Kroisse/FormEncode-Jinja2:formencode_jinja2/formfill.py:default_formatter#19919", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "formencode_jinja2/formfill.py", "symbol": "default_formatter"}, "source_id": "csn:Kroisse/FormEncode-Jinja2:formencode_jinja2/formfill.py:default_formatter#19919"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Kroisse/FormEncode-Jinja2/blob/5e8c97ec282bd85aa39f9ff83cf31fd27ed7b594/formencode_jinja2/formfill.py#L114-L117", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Kroisse-FormEncode-Jinja2:default_formatter-1cc91aa292", "question": "Escape the error, and wrap it in a span with class ``error-message``", "scope": {"holder": "Kroisse-FormEncode-Jinja2", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:L3viathan/sql-mojo-parser:sql_mojo_parser/__init__.py:p_colspec#20164", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "sql_mojo_parser/__init__.py", "symbol": "p_colspec"}, "source_id": "csn:L3viathan/sql-mojo-parser:sql_mojo_parser/__init__.py:p_colspec#20164"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/L3viathan/sql-mojo-parser/blob/fc460c42f3fbcc21c6fc08c0aede8e2a5db637f3/sql_mojo_parser/__init__.py#L103-L125", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:L3viathan-sql-mojo-parser:p_colspec-edf7d0d08c", "question": "colspec : STAR\n | NAME\n | function\n | NAME COMMA colspec\n | function COMMA colspec", "scope": {"holder": "L3viathan-sql-mojo-parser", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:L3viathan/sql-mojo-parser:sql_mojo_parser/__init__.py:t_NAME#20161", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "sql_mojo_parser/__init__.py", "symbol": "t_NAME"}, "source_id": "csn:L3viathan/sql-mojo-parser:sql_mojo_parser/__init__.py:t_NAME#20161"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/L3viathan/sql-mojo-parser/blob/fc460c42f3fbcc21c6fc08c0aede8e2a5db637f3/sql_mojo_parser/__init__.py#L19-L26", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:L3viathan-sql-mojo-parser:t_NAME-43e8b2b86a", "question": "r'[A-Za-z_][A-Za-z0-9_]*", "scope": {"holder": "L3viathan-sql-mojo-parser", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:LLNL/scraper:scraper/github/queryManager.py:DataManager.fileLoad#10327", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "scraper/github/queryManager.py", "symbol": "DataManager.fileLoad"}, "source_id": "csn:LLNL/scraper:scraper/github/queryManager.py:DataManager.fileLoad#10327"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/LLNL/scraper/blob/881a316e4c04dfa5a9cf491b7c7f9f997a7c56ea/scraper/github/queryManager.py#L454-L478", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:LLNL-scraper:DataManager.fileLoad-a7429ae0c1", "question": "Load a JSON data file into the internal JSON data dictionary.\n\n Current internal data will be overwritten.\n If no file path is provided, the stored data file path will be used.\n\n Args:\n filePath (Optional[str]): A relative or absolute path to a\n '.json' file. Defaults to None.\n updatePath (Optional[bool]): Specifies whether or not to update\n the stored data file path. Defaults to True.", "scope": {"holder": "LLNL-scraper", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:LLNL/scraper:scripts/get_users_emails.py:GitHub_Users_Emails.write_to_file#10313", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "scripts/get_users_emails.py", "symbol": "GitHub_Users_Emails.write_to_file"}, "source_id": "csn:LLNL/scraper:scripts/get_users_emails.py:GitHub_Users_Emails.write_to_file#10313"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/LLNL/scraper/blob/881a316e4c04dfa5a9cf491b7c7f9f997a7c56ea/scripts/get_users_emails.py#L104-L114", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:LLNL-scraper:GitHub_Users_Emails.write_to_file-fc2d658a5c", "question": "Writes the user emails to file.", "scope": {"holder": "LLNL-scraper", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:LionelAuroux/pyrser:pyrser/parsing/base.py:BasicParser.begin_tag#18525", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pyrser/parsing/base.py", "symbol": "BasicParser.begin_tag"}, "source_id": "csn:LionelAuroux/pyrser:pyrser/parsing/base.py:BasicParser.begin_tag#18525"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/LionelAuroux/pyrser/blob/f153a97ef2b6bf915a1ed468c0252a9a59b754d5/pyrser/parsing/base.py#L151-L155", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:LionelAuroux-pyrser:BasicParser.begin_tag-e8bef76bd6", "question": "Save the current index under the given name.", "scope": {"holder": "LionelAuroux-pyrser", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:LionelAuroux/pyrser:pyrser/type_system/scope.py:Scope.last#18473", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pyrser/type_system/scope.py", "symbol": "Scope.last"}, "source_id": "csn:LionelAuroux/pyrser:pyrser/type_system/scope.py:Scope.last#18473"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/LionelAuroux/pyrser/blob/f153a97ef2b6bf915a1ed468c0252a9a59b754d5/pyrser/type_system/scope.py#L338-L341", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:LionelAuroux-pyrser:Scope.last-e63eb9ae74", "question": "Retrieve the last Signature ordered by mangling descendant", "scope": {"holder": "LionelAuroux-pyrser", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:LordSputnik/mutagen:mutagen/apev2.py:APEValue#17388", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "mutagen/apev2.py", "symbol": "APEValue"}, "source_id": "csn:LordSputnik/mutagen:mutagen/apev2.py:APEValue#17388"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/LordSputnik/mutagen/blob/38e62c8dc35c72b16554f5dbe7c0fde91acc3411/mutagen/apev2.py#L460-L482", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:LordSputnik-mutagen:APEValue-c8b60189de", "question": "APEv2 tag value factory.\n\n Use this if you need to specify the value's type manually. Binary\n and text data are automatically detected by APEv2.__setitem__.", "scope": {"holder": "LordSputnik-mutagen", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:LordSputnik/mutagen:mutagen/mp4.py:MP4Tags.__update_parents#17377", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "mutagen/mp4.py", "symbol": "MP4Tags.__update_parents"}, "source_id": "csn:LordSputnik/mutagen:mutagen/mp4.py:MP4Tags.__update_parents#17377"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/LordSputnik/mutagen/blob/38e62c8dc35c72b16554f5dbe7c0fde91acc3411/mutagen/mp4.py#L447-L459", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:LordSputnik-mutagen:MP4Tags.__update_parents-020231e413", "question": "Update all parent atoms with the new size.", "scope": {"holder": "LordSputnik-mutagen", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:Loudr/asana-hub:asana_hub/action.py:Action.add_arguments#15127", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "asana_hub/action.py", "symbol": "Action.add_arguments"}, "source_id": "csn:Loudr/asana-hub:asana_hub/action.py:Action.add_arguments#15127"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Loudr/asana-hub/blob/af996ce890ed23d8ede5bf68dcd318e3438829cb/asana_hub/action.py#L27-L62", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Loudr-asana-hub:Action.add_arguments-ad6e162612", "question": "Add arguments to the parser for collection in app.args.\n\n Args:\n parser:\n `argparse.ArgumentParser`. Parser.\n Arguments added here are server on\n self.args.", "scope": {"holder": "Loudr-asana-hub", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:Loudr/asana-hub:asana_hub/tool.py:ToolApp.get_saved_task_data#15140", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "asana_hub/tool.py", "symbol": "ToolApp.get_saved_task_data"}, "source_id": "csn:Loudr/asana-hub:asana_hub/tool.py:ToolApp.get_saved_task_data#15140"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Loudr/asana-hub/blob/af996ce890ed23d8ede5bf68dcd318e3438829cb/asana_hub/tool.py#L262-L282", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Loudr-asana-hub:ToolApp.get_saved_task_data-7ea18ce669", "question": "Returns task data from local data.\n\n Args:\n task:\n `int`. Asana task number.", "scope": {"holder": "Loudr-asana-hub", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:LudovicRousseau/PyKCS11:PyKCS11/__init__.py:CK_OBJECT_HANDLE.to_dict#11133", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "PyKCS11/__init__.py", "symbol": "CK_OBJECT_HANDLE.to_dict"}, "source_id": "csn:LudovicRousseau/PyKCS11:PyKCS11/__init__.py:CK_OBJECT_HANDLE.to_dict#11133"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/LudovicRousseau/PyKCS11/blob/76ccd8741af2ea193aaf1ca29dfedfa412c134fe/PyKCS11/__init__.py#L129-L155", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:LudovicRousseau-PyKCS11:CK_OBJECT_HANDLE.to_dict-c534018c2a", "question": "convert the fields of the object into a dictionnary", "scope": {"holder": "LudovicRousseau-PyKCS11", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:LudovicRousseau/PyKCS11:PyKCS11/__init__.py:Session.digestSession#11158", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "PyKCS11/__init__.py", "symbol": "Session.digestSession"}, "source_id": "csn:LudovicRousseau/PyKCS11:PyKCS11/__init__.py:Session.digestSession#11158"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/LudovicRousseau/PyKCS11/blob/76ccd8741af2ea193aaf1ca29dfedfa412c134fe/PyKCS11/__init__.py#L975-L985", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:LudovicRousseau-PyKCS11:Session.digestSession-cb30c32aba", "question": "C_DigestInit/C_DigestUpdate/C_DigestKey/C_DigestFinal\n\n :param mecha: the digesting mechanism to be used\n (use `MechanismSHA1` for `CKM_SHA_1`)\n :type mecha: :class:`Mechanism`\n :return: A :class:`DigestSession` object\n :rtype: DigestSession", "scope": {"holder": "LudovicRousseau-PyKCS11", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:LuminosoInsight/luminoso-api-client-python:luminoso_api/v4_client.py:LuminosoClient._get_default_account#9049", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "luminoso_api/v4_client.py", "symbol": "LuminosoClient._get_default_account"}, "source_id": "csn:LuminosoInsight/luminoso-api-client-python:luminoso_api/v4_client.py:LuminosoClient._get_default_account#9049"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/LuminosoInsight/luminoso-api-client-python/blob/3bedf2a454aee39214c11fbf556ead3eecc27881/luminoso_api/v4_client.py#L389-L403", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:LuminosoInsight-luminoso-api-client-python:LuminosoClient._get_default_account-5fbbe5b72a", "question": "Get the ID of an account you can use to access projects.", "scope": {"holder": "LuminosoInsight-luminoso-api-client-python", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:LuminosoInsight/luminoso-api-client-python:luminoso_api/v5_cli.py:_print_csv#9054", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "luminoso_api/v5_cli.py", "symbol": "_print_csv"}, "source_id": "csn:LuminosoInsight/luminoso-api-client-python:luminoso_api/v5_cli.py:_print_csv#9054"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/LuminosoInsight/luminoso-api-client-python/blob/3bedf2a454aee39214c11fbf556ead3eecc27881/luminoso_api/v5_cli.py#L43-L51", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:LuminosoInsight-luminoso-api-client-python:_print_csv-6efed6e092", "question": "Print a JSON list of JSON objects in CSV format.", "scope": {"holder": "LuminosoInsight-luminoso-api-client-python", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:ManageIQ/manageiq-api-client-python:src/manageiq_client/api.py:Action._get_entity_from_href#11874", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "src/manageiq_client/api.py", "symbol": "Action._get_entity_from_href"}, "source_id": "csn:ManageIQ/manageiq-api-client-python:src/manageiq_client/api.py:Action._get_entity_from_href#11874"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/ManageIQ/manageiq-api-client-python/blob/e0c8884929e45766c2835bc7dcf4e78b0794248f/src/manageiq_client/api.py#L703-L724", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:ManageIQ-manageiq-api-client-python:Action._get_entity_from_href-cffa72314a", "question": "Returns entity in correct collection.\n\n If the \"href\" value in result doesn't match the current collection,\n try to find the collection that the \"href\" refers to.", "scope": {"holder": "ManageIQ-manageiq-api-client-python", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:ManageIQ/manageiq-api-client-python:src/manageiq_client/api.py:Collection.raw_filter#11872", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "src/manageiq_client/api.py", "symbol": "Collection.raw_filter"}, "source_id": "csn:ManageIQ/manageiq-api-client-python:src/manageiq_client/api.py:Collection.raw_filter#11872"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/ManageIQ/manageiq-api-client-python/blob/e0c8884929e45766c2835bc7dcf4e78b0794248f/src/manageiq_client/api.py#L339-L349", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:ManageIQ-manageiq-api-client-python:Collection.raw_filter-429c7959c2", "question": "Sends all filters to the API.\n\n No fancy, just a wrapper. Any advanced functionality shall be implemented as another method.\n\n Args:\n filters: List of filters (strings)\n\n Returns: :py:class:`SearchResult`", "scope": {"holder": "ManageIQ-manageiq-api-client-python", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:MartinHjelmare/leicacam:leicacam/async_cam.py:AsyncCAM.close#13447", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "leicacam/async_cam.py", "symbol": "AsyncCAM.close"}, "source_id": "csn:MartinHjelmare/leicacam:leicacam/async_cam.py:AsyncCAM.close#13447"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/MartinHjelmare/leicacam/blob/1df37bccd34884737d3b5e169fae71dd2f21f1e2/leicacam/async_cam.py#L97-L101", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:MartinHjelmare-leicacam:AsyncCAM.close-572f03ab21", "question": "Close stream.", "scope": {"holder": "MartinHjelmare-leicacam", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:MartinHjelmare/leicacam:leicacam/cam.py:CAM.receive#13482", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "leicacam/cam.py", "symbol": "CAM.receive"}, "source_id": "csn:MartinHjelmare/leicacam:leicacam/cam.py:CAM.receive#13482"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/MartinHjelmare/leicacam/blob/1df37bccd34884737d3b5e169fae71dd2f21f1e2/leicacam/cam.py#L222-L229", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:MartinHjelmare-leicacam:CAM.receive-16672ded8f", "question": "Receive message from socket interface as list of OrderedDict.", "scope": {"holder": "MartinHjelmare-leicacam", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:MaxStrange/AudioSegment:audiosegment.py:AudioSegment._execute_sox_cmd#9385", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "audiosegment.py", "symbol": "AudioSegment._execute_sox_cmd"}, "source_id": "csn:MaxStrange/AudioSegment:audiosegment.py:AudioSegment._execute_sox_cmd#9385"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/MaxStrange/AudioSegment/blob/1daefb8de626ddff3ff7016697c3ad31d262ecd6/audiosegment.py#L619-L663", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:MaxStrange-AudioSegment:AudioSegment._execute_sox_cmd-63bb463677", "question": "Executes a Sox command in a platform-independent manner.\n\n `cmd` must be a format string that includes {inputfile} and {outputfile}.", "scope": {"holder": "MaxStrange-AudioSegment", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:MaxStrange/AudioSegment:algorithms/asa.py:_get_corresponding_offsets#9412", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "algorithms/asa.py", "symbol": "_get_corresponding_offsets"}, "source_id": "csn:MaxStrange/AudioSegment:algorithms/asa.py:_get_corresponding_offsets#9412"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/MaxStrange/AudioSegment/blob/1daefb8de626ddff3ff7016697c3ad31d262ecd6/algorithms/asa.py#L605-L613", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:MaxStrange-AudioSegment:_get_corresponding_offsets-83d0cf1886", "question": "Gets the offsets that occur as close as possible to the onsets in the given onset-front.", "scope": {"holder": "MaxStrange-AudioSegment", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:MeirKriheli/django-bidi-utils:bidiutils/templatetags/bidiutils_tags.py:add_direction#19952", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "bidiutils/templatetags/bidiutils_tags.py", "symbol": "add_direction"}, "source_id": "csn:MeirKriheli/django-bidi-utils:bidiutils/templatetags/bidiutils_tags.py:add_direction#19952"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/MeirKriheli/django-bidi-utils/blob/48a8c481fe728fbccf486582999e79454195036e/bidiutils/templatetags/bidiutils_tags.py#L10-L42", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:MeirKriheli-django-bidi-utils:add_direction-f18ffc8120", "question": "Adds direction to the element\n\n :arguments:\n arg\n * rtl_only: Add the direction only in case of a\n right-to-left language (default)\n * both: add the direction in both case\n * ltr_only: Add the direction only in case of a\n left-to-right language\n\n {{image_name|add_direction}} when image_name is 'start_arrow.png'\n results in 'start_arrow_rtl.png' in case of RTL language, and\n 'start_arrow.png' or 'start_arrow_ltr.png' depends on `arg` value.", "scope": {"holder": "MeirKriheli-django-bidi-utils", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:MeirKriheli/django-bidi-utils:bidiutils/context_processors.py:bidi#20065", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "bidiutils/context_processors.py", "symbol": "bidi"}, "source_id": "csn:MeirKriheli/django-bidi-utils:bidiutils/context_processors.py:bidi#20065"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/MeirKriheli/django-bidi-utils/blob/48a8c481fe728fbccf486582999e79454195036e/bidiutils/context_processors.py#L3-L33", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:MeirKriheli-django-bidi-utils:bidi-84cd369ea2", "question": "Adds to the context BiDi related variables\n\n LANGUAGE_DIRECTION -- Direction of current language ('ltr' or 'rtl')\n LANGUAGE_START -- Start of language layout ('right' for rtl, 'left'\n for 'ltr')\n LANGUAGE_END -- End of language layout ('left' for rtl, 'right'\n for 'ltr')\n LANGUAGE_MARKER -- Language marker entity ('&rlm;' for rtl, '&lrm'\n for ltr)", "scope": {"holder": "MeirKriheli-django-bidi-utils", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:MeirKriheli/python-bidi:bidi/algorithm.py:apply_mirroring#14321", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "bidi/algorithm.py", "symbol": "apply_mirroring"}, "source_id": "csn:MeirKriheli/python-bidi:bidi/algorithm.py:apply_mirroring#14321"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/MeirKriheli/python-bidi/blob/a0e265bb465c1b7ad628487991e33b5ebe364641/bidi/algorithm.py#L580-L596", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:MeirKriheli-python-bidi:apply_mirroring-67dd9d0b49", "question": "Applies L4: mirroring\n\n See: http://unicode.org/reports/tr9/#L4", "scope": {"holder": "MeirKriheli-python-bidi", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:MeirKriheli/python-bidi:bidi/algorithm.py:get_embedding_levels#14313", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "bidi/algorithm.py", "symbol": "get_embedding_levels"}, "source_id": "csn:MeirKriheli/python-bidi:bidi/algorithm.py:get_embedding_levels#14313"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/MeirKriheli/python-bidi/blob/a0e265bb465c1b7ad628487991e33b5ebe364641/bidi/algorithm.py#L153-L181", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:MeirKriheli-python-bidi:get_embedding_levels-7121b64673", "question": "Get the paragraph base embedding level and direction,\n set the storage to the array of chars", "scope": {"holder": "MeirKriheli-python-bidi", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:Microsoft/botbuilder-python:libraries/botbuilder-ai/botbuilder/ai/luis/activity_util.py:ActivityUtil.create_trace#3617", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "libraries/botbuilder-ai/botbuilder/ai/luis/activity_util.py", "symbol": "ActivityUtil.create_trace"}, "source_id": "csn:Microsoft/botbuilder-python:libraries/botbuilder-ai/botbuilder/ai/luis/activity_util.py:ActivityUtil.create_trace#3617"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Microsoft/botbuilder-python/blob/274663dd91c811bae6ac4488915ba5880771b0a7/libraries/botbuilder-ai/botbuilder/ai/luis/activity_util.py#L16-L69", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Microsoft-botbuilder-python:ActivityUtil.create_trace-1a0674ca90", "question": "Creates a trace activity based on this activity.\n\n :param turn_activity:\n :type turn_activity: Activity\n :param name: The value to assign to the trace activity's <see cref=\"Activity.name\"/> property.\n :type name: str\n :param value: The value to assign to the trace activity's <see cref=\"Activity.value\"/> property., defaults to None\n :param value: object, optional\n :param value_type: The value to assign to the trace activity's <see cref=\"Activity.value_type\"/> property, defaults to None\n :param value_type: str, optional\n :param label: The value to assign to the trace activity's <see cref=\"Activity.label\"/> property, defaults to None\n :param label: str, optional\n :return: The created trace activity.\n :rtype: Activity", "scope": {"holder": "Microsoft-botbuilder-python", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:Microsoft/botbuilder-python:libraries/botbuilder-azure/botbuilder/azure/cosmosdb_storage.py:CosmosDbStorage.__create_dict#3636", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "libraries/botbuilder-azure/botbuilder/azure/cosmosdb_storage.py", "symbol": "CosmosDbStorage.__create_dict"}, "source_id": "csn:Microsoft/botbuilder-python:libraries/botbuilder-azure/botbuilder/azure/cosmosdb_storage.py:CosmosDbStorage.__create_dict#3636"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Microsoft/botbuilder-python/blob/274663dd91c811bae6ac4488915ba5880771b0a7/libraries/botbuilder-azure/botbuilder/azure/cosmosdb_storage.py#L176-L189", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Microsoft-botbuilder-python:CosmosDbStorage.__create_dict-e4ddac00b6", "question": "Return the dict of a StoreItem.\n\n This eliminates non_magic attributes and the e_tag.\n\n :param si:\n :return dict:", "scope": {"holder": "Microsoft-botbuilder-python", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:MinchinWeb/minchin.text:minchin/text.py:centered#19652", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "minchin/text.py", "symbol": "centered"}, "source_id": "csn:MinchinWeb/minchin.text:minchin/text.py:centered#19652"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/MinchinWeb/minchin.text/blob/4d136039561892c3adab49fe81b2f246e5a1507b/minchin/text.py#L85-L95", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:MinchinWeb-minchin.text:centered-f29aa3dbf6", "question": "Takes a string, centres it, and pads it on both sides", "scope": {"holder": "MinchinWeb-minchin.text", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:MinchinWeb/minchin.text:minchin/text.py:query_yes_no#19654", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "minchin/text.py", "symbol": "query_yes_no"}, "source_id": "csn:MinchinWeb/minchin.text:minchin/text.py:query_yes_no#19654"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/MinchinWeb/minchin.text/blob/4d136039561892c3adab49fe81b2f246e5a1507b/minchin/text.py#L106-L139", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:MinchinWeb-minchin.text:query_yes_no-c399a21d13", "question": "Ask a yes/no question via raw_input() and return their answer.\n\n \"question\" is a string that is presented to the user.\n \"default\" is the presumed answer if the user just hits <Enter>.\n It must be \"yes\" (the default), \"no\" or None (meaning\n an answer is required of the user).\n\n The return value is one of Answers.YES or Answers.NO.\n\n Copied (and modified) from\n http://stackoverflow.com/questions/3041986/python-command-line-yes-no-input", "scope": {"holder": "MinchinWeb-minchin.text", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:MisterY/price-database:pricedb/config.py:Config.__create_user_config#9893", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pricedb/config.py", "symbol": "Config.__create_user_config"}, "source_id": "csn:MisterY/price-database:pricedb/config.py:Config.__create_user_config#9893"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/MisterY/price-database/blob/b4fd366b7763891c690fe3000b8840e656da023e/pricedb/config.py#L74-L89", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:MisterY-price-database:Config.__create_user_config-be8f8832f9", "question": "Copy the config template into user's directory", "scope": {"holder": "MisterY-price-database", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:MisterY/price-database:pricedb/app.py:PriceDbApplication.get_price_repository#9908", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pricedb/app.py", "symbol": "PriceDbApplication.get_price_repository"}, "source_id": "csn:MisterY/price-database:pricedb/app.py:PriceDbApplication.get_price_repository#9908"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/MisterY/price-database/blob/b4fd366b7763891c690fe3000b8840e656da023e/pricedb/app.py#L210-L216", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:MisterY-price-database:PriceDbApplication.get_price_repository-d8eefbfb16", "question": "Price repository", "scope": {"holder": "MisterY-price-database", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:MitchellChu/torndsession:demos/memory_session.py:DeleteHandler.get#17586", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "demos/memory_session.py", "symbol": "DeleteHandler.get"}, "source_id": "csn:MitchellChu/torndsession:demos/memory_session.py:DeleteHandler.get#17586"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/MitchellChu/torndsession/blob/dd08554c06f47d33396a0a4485f53d0522961155/demos/memory_session.py#L53-L65", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:MitchellChu-torndsession:DeleteHandler.get-49726e2201", "question": "Please don't do this in production environments.", "scope": {"holder": "MitchellChu-torndsession", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:MomsFriendlyRobotCompany/fake_rpi:fake_rpi/Adafruit.py:LSM303.read#8292", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "fake_rpi/Adafruit.py", "symbol": "LSM303.read"}, "source_id": "csn:MomsFriendlyRobotCompany/fake_rpi:fake_rpi/Adafruit.py:LSM303.read#8292"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/MomsFriendlyRobotCompany/fake_rpi/blob/eb2f640f19f74db9082bfbf8aed524e3ccba6d4f/fake_rpi/Adafruit.py#L24-L34", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:MomsFriendlyRobotCompany-fake_rpi:LSM303.read-77bc37e008", "question": "Since there isn't a real sensor connected, read() creates random\n\t\tdata.", "scope": {"holder": "MomsFriendlyRobotCompany-fake_rpi", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:MuhammedHasan/sklearn_utils:sklearn_utils/preprocessing/dict_input.py:DictInput.transform#16527", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "sklearn_utils/preprocessing/dict_input.py", "symbol": "DictInput.transform"}, "source_id": "csn:MuhammedHasan/sklearn_utils:sklearn_utils/preprocessing/dict_input.py:DictInput.transform#16527"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/MuhammedHasan/sklearn_utils/blob/337c3b7a27f4921d12da496f66a2b83ef582b413/sklearn_utils/preprocessing/dict_input.py#L29-L39", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:MuhammedHasan-sklearn_utils:DictInput.transform-819d61c867", "question": ":param X: features.", "scope": {"holder": "MuhammedHasan-sklearn_utils", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:MuhammedHasan/sklearn_utils:sklearn_utils/utils/skutils_io.py:SkUtilsIO.to_json#16532", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "sklearn_utils/utils/skutils_io.py", "symbol": "SkUtilsIO.to_json"}, "source_id": "csn:MuhammedHasan/sklearn_utils:sklearn_utils/utils/skutils_io.py:SkUtilsIO.to_json#16532"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/MuhammedHasan/sklearn_utils/blob/337c3b7a27f4921d12da496f66a2b83ef582b413/sklearn_utils/utils/skutils_io.py#L48-L57", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:MuhammedHasan-sklearn_utils:SkUtilsIO.to_json-3e75640edf", "question": "Reads dataset to csv.\n\n :param X: dataset as list of dict.\n :param y: labels.", "scope": {"holder": "MuhammedHasan-sklearn_utils", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:Music-Moo/music2storage:music2storage/connection.py:ConnectionHandler.use_music_service#16528", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "music2storage/connection.py", "symbol": "ConnectionHandler.use_music_service"}, "source_id": "csn:Music-Moo/music2storage:music2storage/connection.py:ConnectionHandler.use_music_service#16528"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Music-Moo/music2storage/blob/de12b9046dd227fc8c1512b5060e7f5fcd8b0ee2/music2storage/connection.py#L16-L34", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Music-Moo-music2storage:ConnectionHandler.use_music_service-d293629472", "question": "Sets the current music service to service_name.\n\n :param str service_name: Name of the music service\n :param str api_key: Optional API key if necessary", "scope": {"holder": "Music-Moo-music2storage", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:Music-Moo/music2storage:music2storage/__init__.py:Music2Storage.add_to_queue#16509", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "music2storage/__init__.py", "symbol": "Music2Storage.add_to_queue"}, "source_id": "csn:Music-Moo/music2storage:music2storage/__init__.py:Music2Storage.add_to_queue#16509"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Music-Moo/music2storage/blob/de12b9046dd227fc8c1512b5060e7f5fcd8b0ee2/music2storage/__init__.py#L36-L48", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Music-Moo-music2storage:Music2Storage.add_to_queue-7c668dba00", "question": "Adds an URL to the download queue.\n\n :param str url: URL to the music service track", "scope": {"holder": "Music-Moo-music2storage", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:MycroftAI/padaos:padaos.py:IntentContainer._create_regex#12161", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "padaos.py", "symbol": "IntentContainer._create_regex"}, "source_id": "csn:MycroftAI/padaos:padaos.py:IntentContainer._create_regex#12161"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/MycroftAI/padaos/blob/c7fb3d72fefbe552963c5a5a0f606e1f2fde2968/padaos.py#L104-L112", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:MycroftAI-padaos:IntentContainer._create_regex-98fedd09a6", "question": "Create regex and return. If error occurs returns None.", "scope": {"holder": "MycroftAI-padaos", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:NLeSC/pycoeman:pycoeman/utils_execution.py:apply_argument_parser#15247", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pycoeman/utils_execution.py", "symbol": "apply_argument_parser"}, "source_id": "csn:NLeSC/pycoeman:pycoeman/utils_execution.py:apply_argument_parser#15247"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/NLeSC/pycoeman/blob/246d517b55cb98eb46f69aae453492cf9dd9d5af/pycoeman/utils_execution.py#L51-L57", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:NLeSC-pycoeman:apply_argument_parser-4f8aedcf63", "question": "Apply the argument parser.", "scope": {"holder": "NLeSC-pycoeman", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:NarrativeScience/lsi:src/lsi/utils/hosts.py:HostEntry._get_attrib#19339", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "src/lsi/utils/hosts.py", "symbol": "HostEntry._get_attrib"}, "source_id": "csn:NarrativeScience/lsi:src/lsi/utils/hosts.py:HostEntry._get_attrib#19339"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/NarrativeScience/lsi/blob/7d901b03fdb1a34ef795e5412bfe9685d948e32d/src/lsi/utils/hosts.py#L146-L179", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:NarrativeScience-lsi:HostEntry._get_attrib-b255fda2b2", "question": "Given an attribute name, looks it up on the entry. Names that\n start with ``tags.`` are looked up in the ``tags`` dictionary.\n\n :param attr: Name of attribute to look up.\n :type attr: ``str``\n :param convert_to_str: Convert result to a string.\n :type convert_to_str: ``bool``\n\n :rtype: ``object``", "scope": {"holder": "NarrativeScience-lsi", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:NarrativeScience/lsi:src/lsi/lsi.py:_run_ssh#19387", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "src/lsi/lsi.py", "symbol": "_run_ssh"}, "source_id": "csn:NarrativeScience/lsi:src/lsi/lsi.py:_run_ssh#19387"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/NarrativeScience/lsi/blob/7d901b03fdb1a34ef795e5412bfe9685d948e32d/src/lsi/lsi.py#L195-L350", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:NarrativeScience-lsi:_run_ssh-c35c6a3a50", "question": "Lets the user choose which instance to SSH into.\n\n :param entries: The list of host entries.\n :type entries: [:py:class:`HostEntry`]\n :param username: The SSH username to use. Defaults to current user.\n :type username: ``str`` or ``NoneType``\n :param idfile: The identity file to use. Optional.\n :type idfile: ``str`` or ``NoneType``\n :param no_prompt: Whether to disable confirmation for SSH command.\n :type no_prompt: ``bool``\n :param command: SSH command to run on matching instances.\n :type command: ``str`` or ``NoneType``\n :param show: Instance attributes to show in addition to defaults.\n :type show: ``NoneType`` or ``list`` of ``str``\n :param only: If not ``None``, will *only* show these attributes.\n :type only: ``NoneType`` or ``list`` of ``str``\n :param sort_by: What to sort columns by. By default, sort by 'name'.\n :type sort_by: ``str``\n :param limit: At most how many results to show.\n :type limit: ``int`` or ``NoneType``\n :param num: If not None, choose the given entry from within filters.\n :type num: ``int`` or ``NoneType``\n :param random: If true, choose a random entry from within filters.\n :type random: ``bool``", "scope": {"holder": "NarrativeScience-lsi", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:NateFerrero/oauth2lib:oauth2lib/provider.py:AuthorizationProvider.get_authorization_code#14084", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "oauth2lib/provider.py", "symbol": "AuthorizationProvider.get_authorization_code"}, "source_id": "csn:NateFerrero/oauth2lib:oauth2lib/provider.py:AuthorizationProvider.get_authorization_code#14084"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/NateFerrero/oauth2lib/blob/d161b010f8a596826050a09e5e94d59443cc12d9/oauth2lib/provider.py#L205-L268", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:NateFerrero-oauth2lib:AuthorizationProvider.get_authorization_code-9c982f7df5", "question": "Generate authorization code HTTP response.\n\n :param response_type: Desired response type. Must be exactly \"code\".\n :type response_type: str\n :param client_id: Client ID.\n :type client_id: str\n :param redirect_uri: Client redirect URI.\n :type redirect_uri: str\n :rtype: requests.Response", "scope": {"holder": "NateFerrero-oauth2lib", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:NateFerrero/oauth2lib:oauth2lib/provider.py:Provider._make_json_response#14083", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "oauth2lib/provider.py", "symbol": "Provider._make_json_response"}, "source_id": "csn:NateFerrero/oauth2lib:oauth2lib/provider.py:Provider._make_json_response#14083"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/NateFerrero/oauth2lib/blob/d161b010f8a596826050a09e5e94d59443cc12d9/oauth2lib/provider.py#L61-L80", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:NateFerrero-oauth2lib:Provider._make_json_response-cb7434bd3a", "question": "Return a response object from the given JSON data.\n\n :param data: Data to JSON-encode.\n :type data: mixed\n :param headers: Dict of headers to include in the requests.\n :type headers: dict\n :param status_code: HTTP status code.\n :type status_code: int\n :rtype: requests.Response", "scope": {"holder": "NateFerrero-oauth2lib", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:Nekmo/amazon-dash:amazon_dash/config.py:Config.read#6531", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "amazon_dash/config.py", "symbol": "Config.read"}, "source_id": "csn:Nekmo/amazon-dash:amazon_dash/config.py:Config.read#6531"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Nekmo/amazon-dash/blob/0e2bdc24ff8ea32cecb2f5f54f5cc1c0f99c197b/amazon_dash/config.py#L227-L240", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Nekmo-amazon-dash:Config.read-2c5d8fb71a", "question": "Parse and validate the config file. The read data is accessible as a dictionary in this instance\n\n :return: None", "scope": {"holder": "Nekmo-amazon-dash", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:Nekmo/amazon-dash:amazon_dash/listener.py:Listener.run#6550", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "amazon_dash/listener.py", "symbol": "Listener.run"}, "source_id": "csn:Nekmo/amazon-dash:amazon_dash/listener.py:Listener.run#6550"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Nekmo/amazon-dash/blob/0e2bdc24ff8ea32cecb2f5f54f5cc1c0f99c197b/amazon_dash/listener.py#L152-L159", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Nekmo-amazon-dash:Listener.run-89057f767e", "question": "Start daemon mode\n\n :param bool root_allowed: Only used for ExecuteCmd\n :return: loop", "scope": {"holder": "Nekmo-amazon-dash", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:Nekroze/greencard:greencard/greencard.py:card#19716", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "greencard/greencard.py", "symbol": "card"}, "source_id": "csn:Nekroze/greencard:greencard/greencard.py:card#19716"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Nekroze/greencard/blob/30fe7eba5742c31b666027e31f33aaa641699857/greencard/greencard.py#L9-L19", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Nekroze-greencard:card-21eb5e421e", "question": "A decorator for providing a unittesting function/method with every card in\n a librarian card library database when it is called.", "scope": {"holder": "Nekroze-greencard", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:Nekroze/greencard:greencard/greencard.py:library#19717", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "greencard/greencard.py", "symbol": "library"}, "source_id": "csn:Nekroze/greencard:greencard/greencard.py:library#19717"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Nekroze/greencard/blob/30fe7eba5742c31b666027e31f33aaa641699857/greencard/greencard.py#L22-L32", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Nekroze-greencard:library-067ffd3dcc", "question": "A decorator for providing a unittest with a library and have it called only\n once.", "scope": {"holder": "Nekroze-greencard", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:Nic30/hwt:hwt/hdl/assignment.py:Assignment._cut_off_drivers_of#9677", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "hwt/hdl/assignment.py", "symbol": "Assignment._cut_off_drivers_of"}, "source_id": "csn:Nic30/hwt:hwt/hdl/assignment.py:Assignment._cut_off_drivers_of#9677"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Nic30/hwt/blob/8cbb399e326da3b22c233b98188a9d08dec057e6/hwt/hdl/assignment.py#L69-L77", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Nic30-hwt:Assignment._cut_off_drivers_of-6e151838a5", "question": "Cut off statements which are driver of specified signal", "scope": {"holder": "Nic30-hwt", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:Nic30/hwt:hwt/hdl/switchContainer.py:SwitchContainer._condHasEffect#9696", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "hwt/hdl/switchContainer.py", "symbol": "SwitchContainer._condHasEffect"}, "source_id": "csn:Nic30/hwt:hwt/hdl/switchContainer.py:SwitchContainer._condHasEffect#9696"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Nic30/hwt/blob/8cbb399e326da3b22c233b98188a9d08dec057e6/hwt/hdl/switchContainer.py#L228-L251", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Nic30-hwt:SwitchContainer._condHasEffect-ad4445d38f", "question": ":return: True if statements in branches has different effect", "scope": {"holder": "Nic30-hwt", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:Numergy/yoda:yoda/adapter/abstract.py:Abstract.execute#17898", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "yoda/adapter/abstract.py", "symbol": "Abstract.execute"}, "source_id": "csn:Numergy/yoda:yoda/adapter/abstract.py:Abstract.execute#17898"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Numergy/yoda/blob/109f0e9441130488b0155f05883ef6531cf46ee9/yoda/adapter/abstract.py#L37-L62", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Numergy-yoda:Abstract.execute-cb0f4d61ce", "question": "Execute command with os.popen and return output.", "scope": {"holder": "Numergy-yoda", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:Numergy/yoda:yoda/subcommand/status.py:Status.print_workspace#17903", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "yoda/subcommand/status.py", "symbol": "Status.print_workspace"}, "source_id": "csn:Numergy/yoda:yoda/subcommand/status.py:Status.print_workspace#17903"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Numergy/yoda/blob/109f0e9441130488b0155f05883ef6531cf46ee9/yoda/subcommand/status.py#L56-L65", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Numergy-yoda:Status.print_workspace-2b1ddfe63d", "question": "Print workspace status.", "scope": {"holder": "Numergy-yoda", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:ONSdigital/sdc-cryptography:sdc/crypto/key_store.py:KeyStore.get_key_for_purpose_and_type#13433", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "sdc/crypto/key_store.py", "symbol": "KeyStore.get_key_for_purpose_and_type"}, "source_id": "csn:ONSdigital/sdc-cryptography:sdc/crypto/key_store.py:KeyStore.get_key_for_purpose_and_type#13433"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/ONSdigital/sdc-cryptography/blob/846feb2b27b1c62d35ff2c290c05abcead68b23c/sdc/crypto/key_store.py#L62-L72", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:ONSdigital-sdc-cryptography:KeyStore.get_key_for_purpose_and_type-25f922d56c", "question": "Gets a list of keys that match the purpose and key_type, and returns the first key in that list\n Note, if there are many keys that match the criteria, the one you get back will be random from that list\n :returns: A key object that matches the criteria", "scope": {"holder": "ONSdigital-sdc-cryptography", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:ONSdigital/sdc-cryptography:sdc/crypto/decrypter.py:decrypt#13431", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "sdc/crypto/decrypter.py", "symbol": "decrypt"}, "source_id": "csn:ONSdigital/sdc-cryptography:sdc/crypto/decrypter.py:decrypt#13431"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/ONSdigital/sdc-cryptography/blob/846feb2b27b1c62d35ff2c290c05abcead68b23c/sdc/crypto/decrypter.py#L6-L25", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:ONSdigital-sdc-cryptography:decrypt-dbab51df03", "question": "This decrypts the provided jwe token, then decodes resulting jwt token and returns\n the payload.\n\n :param str token: The jwe token.\n :param key_store: The key store.\n :param str key_purpose: Context for the key.\n :param int leeway: Extra allowed time in seconds after expiration to account for clock skew.\n :return: The decrypted payload.", "scope": {"holder": "ONSdigital-sdc-cryptography", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:OldhamMade/exemelopy:exemelopy/__init__.py:XMLEncoder.to_string#22078", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "exemelopy/__init__.py", "symbol": "XMLEncoder.to_string"}, "source_id": "csn:OldhamMade/exemelopy:exemelopy/__init__.py:XMLEncoder.to_string#22078"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/OldhamMade/exemelopy/blob/5f5141b169e61a5b6912146a995917f5d862ee9c/exemelopy/__init__.py#L52-L66", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:OldhamMade-exemelopy:XMLEncoder.to_string-051193b4dc", "question": "Encodes the stored ``data`` to XML and returns a\n ``string``.\n\n Setting ``indent`` to ``False`` will forego any pretty-printing\n and return a condensed value.\n\n Setting ``declaration`` to ``False`` will skip inserting the\n XML declaration.", "scope": {"holder": "OldhamMade-exemelopy", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:OldhamMade/exemelopy:exemelopy/__init__.py:XMLEncoder.to_xml#22079", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "exemelopy/__init__.py", "symbol": "XMLEncoder.to_xml"}, "source_id": "csn:OldhamMade/exemelopy:exemelopy/__init__.py:XMLEncoder.to_xml#22079"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/OldhamMade/exemelopy/blob/5f5141b169e61a5b6912146a995917f5d862ee9c/exemelopy/__init__.py#L68-L75", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:OldhamMade-exemelopy:XMLEncoder.to_xml-2fae15444e", "question": "Encodes the stored ``data`` to XML and returns\n an ``lxml.etree`` value.", "scope": {"holder": "OldhamMade-exemelopy", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:OpenKMIP/PyKMIP:kmip/core/messages/payloads/activate.py:ActivateRequestPayload.validate#7196", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "kmip/core/messages/payloads/activate.py", "symbol": "ActivateRequestPayload.validate"}, "source_id": "csn:OpenKMIP/PyKMIP:kmip/core/messages/payloads/activate.py:ActivateRequestPayload.validate#7196"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/OpenKMIP/PyKMIP/blob/b51c5b044bd05f8c85a1d65d13a583a4d8fc1b0e/kmip/core/messages/payloads/activate.py#L95-L103", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:OpenKMIP-PyKMIP:ActivateRequestPayload.validate-8bf883f4f3", "question": "Error check the attributes of the ActivateRequestPayload object.", "scope": {"holder": "OpenKMIP-PyKMIP", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:OpenKMIP/PyKMIP:kmip/services/server/engine.py:KmipEngine._get_attribute_from_managed_object#7050", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "kmip/services/server/engine.py", "symbol": "KmipEngine._get_attribute_from_managed_object"}, "source_id": "csn:OpenKMIP/PyKMIP:kmip/services/server/engine.py:KmipEngine._get_attribute_from_managed_object#7050"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/OpenKMIP/PyKMIP/blob/b51c5b044bd05f8c85a1d65d13a583a4d8fc1b0e/kmip/services/server/engine.py#L627-L719", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:OpenKMIP-PyKMIP:KmipEngine._get_attribute_from_managed_object-8f4bcf1342", "question": "Get the attribute value from the kmip.pie managed object.", "scope": {"holder": "OpenKMIP-PyKMIP", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:OpenMath/py-openmath:openmath/convert.py:Converter._deprecated_register#17819", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "openmath/convert.py", "symbol": "Converter._deprecated_register"}, "source_id": "csn:OpenMath/py-openmath:openmath/convert.py:Converter._deprecated_register#17819"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/OpenMath/py-openmath/blob/4906aa9ccf606f533675c28823772e07c30fd220/openmath/convert.py#L242-L250", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:OpenMath-py-openmath:Converter._deprecated_register-848345e331", "question": "This is a shorthand for:\n\n ``self.register_to_python(om_cd, om_name, to_py)``\n ``self.register_to_openmath(py_class, to_om)``", "scope": {"holder": "OpenMath-py-openmath", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:OpenMath/py-openmath:openmath/convert_pickle.py:cls_build#17869", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "openmath/convert_pickle.py", "symbol": "cls_build"}, "source_id": "csn:OpenMath/py-openmath:openmath/convert_pickle.py:cls_build#17869"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/OpenMath/py-openmath/blob/4906aa9ccf606f533675c28823772e07c30fd220/openmath/convert_pickle.py#L331-L389", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:OpenMath-py-openmath:cls_build-d530b95eb0", "question": "Apply the setstate protocol to initialize `inst` from `state`.\n\n INPUT:\n\n - ``inst`` -- a raw instance of a class\n - ``state`` -- the state to restore; typically a dictionary mapping attribute names to their values\n\n EXAMPLES::\n\n >>> from openmath.convert_pickle import cls_build\n >>> class A(object): pass\n >>> inst = A.__new__(A)\n >>> state = {\"foo\": 1, \"bar\": 4}\n >>> inst2 = cls_build(inst,state)\n >>> inst is inst2\n True\n >>> inst.foo\n 1\n >>> inst.bar\n 4", "scope": {"holder": "OpenMath-py-openmath", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:Patreon/multiget-cache-py:multiget_cache/base_cache_wrapper.py:BaseCacheWrapper.delete#13436", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "multiget_cache/base_cache_wrapper.py", "symbol": "BaseCacheWrapper.delete"}, "source_id": "csn:Patreon/multiget-cache-py:multiget_cache/base_cache_wrapper.py:BaseCacheWrapper.delete#13436"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Patreon/multiget-cache-py/blob/824ec4809c97cc7e0035810bd9fefd1262de3318/multiget_cache/base_cache_wrapper.py#L55-L60", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Patreon-multiget-cache-py:BaseCacheWrapper.delete-2516784610", "question": "Remove the key from the request cache and from memcache.", "scope": {"holder": "Patreon-multiget-cache-py", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:Patreon/multiget-cache-py:multiget_cache/function_tools.py:map_arguments_to_objects#13435", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "multiget_cache/function_tools.py", "symbol": "map_arguments_to_objects"}, "source_id": "csn:Patreon/multiget-cache-py:multiget_cache/function_tools.py:map_arguments_to_objects#13435"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Patreon/multiget-cache-py/blob/824ec4809c97cc7e0035810bd9fefd1262de3318/multiget_cache/function_tools.py#L105-L124", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Patreon-multiget-cache-py:map_arguments_to_objects-dd30ce50b8", "question": ":param kwargs: kwargs used to call the multiget function\n :param objects: objects returned from the inner function\n :param object_key: field or set of fields that map to the kwargs provided\n :param object_tuple_key: A temporary shortcut until we allow dot.path traversal for object_key.\n Will call getattr(getattr(result, join_table_name), object_key)\n :param argument_key: field or set of fields that map to the objects provided\n :param result_value: Limit the fields returned to this field or set of fields (none = whole object)\n :param default_result: If the inner function returned none for a set of parameters, default to this\n :return:", "scope": {"holder": "Patreon-multiget-cache-py", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:PierreRaybaut/PyQtdoc:setup.py:get_data_files#17775", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "setup.py", "symbol": "get_data_files"}, "source_id": "csn:PierreRaybaut/PyQtdoc:setup.py:get_data_files#17775"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/PierreRaybaut/PyQtdoc/blob/71dce1cf11d958f72db2f5b9519d3540569b7720/setup.py#L8-L14", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:PierreRaybaut-PyQtdoc:get_data_files-b5079c3e68", "question": "Return data files in directory *dirname*", "scope": {"holder": "PierreRaybaut-PyQtdoc", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:Pirionfr/pyLinky:pylinky/client.py:LinkyClient._get_data#9068", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pylinky/client.py", "symbol": "LinkyClient._get_data"}, "source_id": "csn:Pirionfr/pyLinky:pylinky/client.py:LinkyClient._get_data#9068"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Pirionfr/pyLinky/blob/4372496bfcdd95ccfd2f017634cf02b38a2d6fd1/pylinky/client.py#L76-L126", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Pirionfr-pyLinky:LinkyClient._get_data-f60d4fe78f", "question": "Get data.", "scope": {"holder": "Pirionfr-pyLinky", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:Pirionfr/pyLinky:pylinky/client.py:LinkyClient._post_login_page#9067", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pylinky/client.py", "symbol": "LinkyClient._post_login_page"}, "source_id": "csn:Pirionfr/pyLinky:pylinky/client.py:LinkyClient._post_login_page#9067"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Pirionfr/pyLinky/blob/4372496bfcdd95ccfd2f017634cf02b38a2d6fd1/pylinky/client.py#L55-L74", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Pirionfr-pyLinky:LinkyClient._post_login_page-85cefbd8db", "question": "Login to enedis.", "scope": {"holder": "Pirionfr-pyLinky", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:PolicyStat/docx2html:docx2html/core.py:_strip_tag#14162", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "docx2html/core.py", "symbol": "_strip_tag"}, "source_id": "csn:PolicyStat/docx2html:docx2html/core.py:_strip_tag#14162"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/PolicyStat/docx2html/blob/2dc4afd1e3a3f2f0b357d0bff903eb58bcc94429/docx2html/core.py#L1344-L1350", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:PolicyStat-docx2html:_strip_tag-d0c4b975f6", "question": "Remove all tags that have the tag name ``tag``", "scope": {"holder": "PolicyStat-docx2html", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:PolicyStat/docx2html:docx2html/core.py:get_style_dict#14153", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "docx2html/core.py", "symbol": "get_style_dict"}, "source_id": "csn:PolicyStat/docx2html:docx2html/core.py:get_style_dict#14153"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/PolicyStat/docx2html/blob/2dc4afd1e3a3f2f0b357d0bff903eb58bcc94429/docx2html/core.py#L674-L729", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:PolicyStat-docx2html:get_style_dict-c22c46cfc7", "question": "Some things that are considered lists are actually supposed to be H tags\n (h1, h2, etc.) These can be denoted by their styleId", "scope": {"holder": "PolicyStat-docx2html", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:Polyconseil/devpi-metawheel:devpi_metawheel/main.py:devpiserver_on_upload#13735", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "devpi_metawheel/main.py", "symbol": "devpiserver_on_upload"}, "source_id": "csn:Polyconseil/devpi-metawheel:devpi_metawheel/main.py:devpiserver_on_upload#13735"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Polyconseil/devpi-metawheel/blob/8794f7b74c406979aa4a35fa1cd28e1e9c8864ae/devpi_metawheel/main.py#L17-L52", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Polyconseil-devpi-metawheel:devpiserver_on_upload-c26515fbce", "question": "called when a file is uploaded to a private stage for\n a projectname/version. link.entry.file_exists() may be false because\n a more recent revision deleted the file (and files are not revisioned).\n NOTE that this hook is currently NOT called for the implicit \"caching\"\n uploads to the pypi mirror.\n\n If the uploaded file is a wheel and is the latest version on this index,\n store its metadata in json file at the root of index/+f/ directory.\n With the standard config with nginx, nginx will directly serve this file.", "scope": {"holder": "Polyconseil-devpi-metawheel", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:PyCQA/pylint:pylint/utils/ast_walker.py:ASTWalker.add_checker#5879", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pylint/utils/ast_walker.py", "symbol": "ASTWalker.add_checker"}, "source_id": "csn:PyCQA/pylint:pylint/utils/ast_walker.py:ASTWalker.add_checker#5879"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/PyCQA/pylint/blob/2bf5c61a3ff6ae90613b81679de42c0f19aea600/pylint/utils/ast_walker.py#L27-L55", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:PyCQA-pylint:ASTWalker.add_checker-5c44da7a9a", "question": "walk to the checker's dir and collect visit and leave methods", "scope": {"holder": "PyCQA-pylint", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:PyCQA/pylint:pylint/checkers/raw_metrics.py:RawMetricsChecker.process_tokens#5775", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pylint/checkers/raw_metrics.py", "symbol": "RawMetricsChecker.process_tokens"}, "source_id": "csn:PyCQA/pylint:pylint/checkers/raw_metrics.py:RawMetricsChecker.process_tokens#5775"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/PyCQA/pylint/blob/2bf5c61a3ff6ae90613b81679de42c0f19aea600/pylint/checkers/raw_metrics.py#L77-L84", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:PyCQA-pylint:RawMetricsChecker.process_tokens-7f7c421111", "question": "update stats", "scope": {"holder": "PyCQA-pylint", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:PyFilesystem/s3fs:fs_s3fs/_s3fs.py:S3File.factory#10222", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "fs_s3fs/_s3fs.py", "symbol": "S3File.factory"}, "source_id": "csn:PyFilesystem/s3fs:fs_s3fs/_s3fs.py:S3File.factory#10222"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/PyFilesystem/s3fs/blob/1c5e3a1b6abbb9dff91ea7fc4cec7353798cd536/fs_s3fs/_s3fs.py#L65-L69", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:PyFilesystem-s3fs:S3File.factory-4fa100ab85", "question": "Create a S3File backed with a temporary file.", "scope": {"holder": "PyFilesystem-s3fs", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:PyFilesystem/s3fs:fs_s3fs/_s3fs.py:_make_repr#10220", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "fs_s3fs/_s3fs.py", "symbol": "_make_repr"}, "source_id": "csn:PyFilesystem/s3fs:fs_s3fs/_s3fs.py:_make_repr#10220"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/PyFilesystem/s3fs/blob/1c5e3a1b6abbb9dff91ea7fc4cec7353798cd536/fs_s3fs/_s3fs.py#L34-L58", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:PyFilesystem-s3fs:_make_repr-306be9867b", "question": "Generate a repr string.\n\n Positional arguments should be the positional arguments used to\n construct the class. Keyword arguments should consist of tuples of\n the attribute value and default. If the value is the default, then\n it won't be rendered in the output.\n\n Here's an example::\n\n def __repr__(self):\n return make_repr('MyClass', 'foo', name=(self.name, None))\n\n The output of this would be something line ``MyClass('foo',\n name='Will')``.", "scope": {"holder": "PyFilesystem-s3fs", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:PyProphet/pyprophet:pyprophet/main.py:backpropagate#12237", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pyprophet/main.py", "symbol": "backpropagate"}, "source_id": "csn:PyProphet/pyprophet:pyprophet/main.py:backpropagate#12237"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/PyProphet/pyprophet/blob/f546ad171750cd7685afbde6785fe71f82cadb35/pyprophet/main.py#L247-L257", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:PyProphet-pyprophet:backpropagate-f486c81fd2", "question": "Backpropagate multi-run peptide and protein scores to single files", "scope": {"holder": "PyProphet-pyprophet", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:PyProphet/pyprophet:pyprophet/main.py:peptide#12232", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pyprophet/main.py", "symbol": "peptide"}, "source_id": "csn:PyProphet/pyprophet:pyprophet/main.py:peptide#12232"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/PyProphet/pyprophet/blob/f546ad171750cd7685afbde6785fe71f82cadb35/pyprophet/main.py#L144-L154", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:PyProphet-pyprophet:peptide-e9af82a648", "question": "Infer peptides and conduct error-rate estimation in different contexts.", "scope": {"holder": "PyProphet-pyprophet", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:PythonSanSebastian/docstamp:docstamp/data_source.py:GoogleData.getCSV#19164", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "docstamp/data_source.py", "symbol": "GoogleData.getCSV"}, "source_id": "csn:PythonSanSebastian/docstamp:docstamp/data_source.py:GoogleData.getCSV#19164"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/PythonSanSebastian/docstamp/blob/b43808f2e15351b0b2f0b7eade9c7ef319c9e646/docstamp/data_source.py#L11-L39", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:PythonSanSebastian-docstamp:GoogleData.getCSV-4e8e2fc1f1", "question": "Returns\n -------\n filename: str", "scope": {"holder": "PythonSanSebastian-docstamp", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:PythonSanSebastian/docstamp:docstamp/file_utils.py:cleanup#19106", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "docstamp/file_utils.py", "symbol": "cleanup"}, "source_id": "csn:PythonSanSebastian/docstamp:docstamp/file_utils.py:cleanup#19106"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/PythonSanSebastian/docstamp/blob/b43808f2e15351b0b2f0b7eade9c7ef319c9e646/docstamp/file_utils.py#L118-L129", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:PythonSanSebastian-docstamp:cleanup-7d14da8065", "question": "Remove the files in workdir that have the given extension.\n\n Parameters\n ----------\n workdir:\n Folder path from where to clean the files.\n\n extension: str\n File extension without the dot, e.g., 'txt'", "scope": {"holder": "PythonSanSebastian-docstamp", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:Qiskit/qiskit-terra:qiskit/converters/ast_to_dag.py:AstInterpreter._create_dag_op#3743", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "qiskit/converters/ast_to_dag.py", "symbol": "AstInterpreter._create_dag_op"}, "source_id": "csn:Qiskit/qiskit-terra:qiskit/converters/ast_to_dag.py:AstInterpreter._create_dag_op#3743"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/converters/ast_to_dag.py#L306-L377", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:AstInterpreter._create_dag_op-b15961168d", "question": "Create a DAG node out of a parsed AST op node.\n\n Args:\n name (str): operation name to apply to the dag.\n params (list): op parameters\n qargs (list(QuantumRegister, int)): qubits to attach to\n\n Raises:\n QiskitError: if encountering a non-basis opaque gate", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:Qiskit/qiskit-terra:qiskit/circuit/quantumcircuit.py:QuantumCircuit._bind_parameter#3914", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "qiskit/circuit/quantumcircuit.py", "symbol": "QuantumCircuit._bind_parameter"}, "source_id": "csn:Qiskit/qiskit-terra:qiskit/circuit/quantumcircuit.py:QuantumCircuit._bind_parameter#3914"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/circuit/quantumcircuit.py#L725-L728", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:QuantumCircuit._bind_parameter-bb54a16251", "question": "Assigns a parameter value to matching instructions in-place.", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:RRZE-HPC/kerncraft:kerncraft/models/benchmark.py:Benchmark.analyze#12077", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "kerncraft/models/benchmark.py", "symbol": "Benchmark.analyze"}, "source_id": "csn:RRZE-HPC/kerncraft:kerncraft/models/benchmark.py:Benchmark.analyze#12077"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/RRZE-HPC/kerncraft/blob/c60baf8043e4da8d8d66da7575021c2f4c6c78af/kerncraft/models/benchmark.py#L343-L486", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:RRZE-HPC-kerncraft:Benchmark.analyze-57963ff82c", "question": "Run analysis.", "scope": {"holder": "RRZE-HPC-kerncraft", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:RRZE-HPC/kerncraft:kerncraft/kernel.py:KernelCode.iaca_analysis#12054", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "kerncraft/kernel.py", "symbol": "KernelCode.iaca_analysis"}, "source_id": "csn:RRZE-HPC/kerncraft:kerncraft/kernel.py:KernelCode.iaca_analysis#12054"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/RRZE-HPC/kerncraft/blob/c60baf8043e4da8d8d66da7575021c2f4c6c78af/kerncraft/kernel.py#L1514-L1535", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:RRZE-HPC-kerncraft:KernelCode.iaca_analysis-362649ef89", "question": "Run an IACA analysis and return its outcome.\n\n *asm_block* controls how the to-be-marked block is chosen. \"auto\" (default) results in\n the largest block, \"manual\" results in interactive and a number in the according block.\n\n *pointer_increment* is the number of bytes the pointer is incremented after the loop or\n - 'auto': automatic detection, RuntimeError is raised in case of failure\n - 'auto_with_manual_fallback': automatic detection, fallback to manual input\n - 'manual': prompt user", "scope": {"holder": "RRZE-HPC-kerncraft", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:RazerM/yourls-python:yourls/core.py:YOURLSAPIMixin.db_stats#13505", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "yourls/core.py", "symbol": "YOURLSAPIMixin.db_stats"}, "source_id": "csn:RazerM/yourls-python:yourls/core.py:YOURLSAPIMixin.db_stats#13505"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/RazerM/yourls-python/blob/716845562a2bbb430de3c379c9481b195e451ccf/yourls/core.py#L166-L181", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:RazerM-yourls-python:YOURLSAPIMixin.db_stats-fc65a012dd", "question": "Get database statistics.\n\n Returns:\n DBStats: Total clicks and links statistics.\n\n Raises:\n requests.exceptions.HTTPError: Generic HTTP Error", "scope": {"holder": "RazerM-yourls-python", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:RazerM/yourls-python:yourls/core.py:YOURLSAPIMixin.stats#13504", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "yourls/core.py", "symbol": "YOURLSAPIMixin.stats"}, "source_id": "csn:RazerM/yourls-python:yourls/core.py:YOURLSAPIMixin.stats#13504"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/RazerM/yourls-python/blob/716845562a2bbb430de3c379c9481b195e451ccf/yourls/core.py#L121-L164", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:RazerM-yourls-python:YOURLSAPIMixin.stats-8cca43918e", "question": "Get stats about links.\n\n Parameters:\n filter: 'top', 'bottom', 'rand', or 'last'.\n limit: Number of links to return from filter.\n start: Optional start number.\n\n Returns:\n Tuple containing list of ShortenedURLs and DBStats.\n\n Example:\n\n .. code-block:: python\n\n links, stats = yourls.stats(filter='top', limit=10)\n\n Raises:\n ValueError: Incorrect value for filter parameter.\n requests.exceptions.HTTPError: Generic HTTP Error", "scope": {"holder": "RazerM-yourls-python", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:SeabornGames/Logger:seaborn_logger/logger.py:SeabornLogger.findCaller#19813", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "seaborn_logger/logger.py", "symbol": "SeabornLogger.findCaller"}, "source_id": "csn:SeabornGames/Logger:seaborn_logger/logger.py:SeabornLogger.findCaller#19813"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/SeabornGames/Logger/blob/fb8b1700557aaea8d3216bd4c4df33c302bece7f/seaborn_logger/logger.py#L45-L72", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:SeabornGames-Logger:SeabornLogger.findCaller-f01ee29b63", "question": "Find the stack frame of the caller so that we can note the source\n file name, line number and function name.", "scope": {"holder": "SeabornGames-Logger", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:SeabornGames/Logger:seaborn_logger/logger.py:setup_file_logging#19809", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "seaborn_logger/logger.py", "symbol": "setup_file_logging"}, "source_id": "csn:SeabornGames/Logger:seaborn_logger/logger.py:setup_file_logging#19809"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/SeabornGames/Logger/blob/fb8b1700557aaea8d3216bd4c4df33c302bece7f/seaborn_logger/logger.py#L289-L323", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:SeabornGames-Logger:setup_file_logging-283045562e", "question": "This will setup logging for a single file but can be called more than once\n LOG LEVELS are \"CRITICAL\", \"ERROR\", \"INFO\", \"DEBUG\"\n :param log_filename: str of the file location\n :param log_file_level str of the log level to use on this file\n :param str_format: str of the logging format\n :param date_format: str of the date format\n :param log_restart: bool if True the log file will be deleted first\n :param log_history: bool if True will save another log file in a folder\n called history with the datetime\n :param formatter: logging.Format instance to use\n :param log_filter: logging.filter instance to add to handler\n :param silence_modules list of str of modules to silence\n :return: None", "scope": {"holder": "SeabornGames-Logger", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:SectorLabs/django-postgres-extra:psqlextra/datastructures.py:ConditionalJoin.add_condition#4851", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "psqlextra/datastructures.py", "symbol": "ConditionalJoin.add_condition"}, "source_id": "csn:SectorLabs/django-postgres-extra:psqlextra/datastructures.py:ConditionalJoin.add_condition#4851"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/SectorLabs/django-postgres-extra/blob/eef2ed5504d225858d4e4f5d77a838082ca6053e/psqlextra/datastructures.py#L17-L28", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:SectorLabs-django-postgres-extra:ConditionalJoin.add_condition-e83603d980", "question": "Adds an extra condition to this join.\n\n Arguments:\n field:\n The field that the condition will apply to.\n\n value:\n The value to compare.", "scope": {"holder": "SectorLabs-django-postgres-extra", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:SectorLabs/django-postgres-extra:psqlextra/compiler.py:PostgresInsertCompiler._get_model_field#4838", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "psqlextra/compiler.py", "symbol": "PostgresInsertCompiler._get_model_field"}, "source_id": "csn:SectorLabs/django-postgres-extra:psqlextra/compiler.py:PostgresInsertCompiler._get_model_field#4838"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/SectorLabs/django-postgres-extra/blob/eef2ed5504d225858d4e4f5d77a838082ca6053e/psqlextra/compiler.py#L240-L266", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:SectorLabs-django-postgres-extra:PostgresInsertCompiler._get_model_field-27ebe5dc0d", "question": "Gets the field on a model with the specified name.\n\n Arguments:\n name:\n The name of the field to look for.\n\n This can be both the actual field name, or\n the name of the column, both will work :)\n\n Returns:\n The field with the specified name or None if\n no such field exists.", "scope": {"holder": "SectorLabs-django-postgres-extra", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:SiLab-Bonn/pixel_clusterizer:pixel_clusterizer/clusterizer.py:HitClusterizer.add_cluster_field#18546", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pixel_clusterizer/clusterizer.py", "symbol": "HitClusterizer.add_cluster_field"}, "source_id": "csn:SiLab-Bonn/pixel_clusterizer:pixel_clusterizer/clusterizer.py:HitClusterizer.add_cluster_field#18546"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/SiLab-Bonn/pixel_clusterizer/blob/d2c8c3072fb03ebb7c6a3e8c57350fbbe38efd4d/pixel_clusterizer/clusterizer.py#L241-L252", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:SiLab-Bonn-pixel_clusterizer:HitClusterizer.add_cluster_field-bfb64b9159", "question": "Adds a field or a list of fields to the cluster result array. Has to be defined as a numpy dtype entry, e.g.: ('parameter', '<i4')", "scope": {"holder": "SiLab-Bonn-pixel_clusterizer", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:SiLab-Bonn/pixel_clusterizer:pixel_clusterizer/cluster_functions.py:_finish_cluster#18488", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pixel_clusterizer/cluster_functions.py", "symbol": "_finish_cluster"}, "source_id": "csn:SiLab-Bonn/pixel_clusterizer:pixel_clusterizer/cluster_functions.py:_finish_cluster#18488"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/SiLab-Bonn/pixel_clusterizer/blob/d2c8c3072fb03ebb7c6a3e8c57350fbbe38efd4d/pixel_clusterizer/cluster_functions.py#L33-L77", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:SiLab-Bonn-pixel_clusterizer:_finish_cluster-91414e1841", "question": "Set hit and cluster information of the cluster (e.g. number of hits in the cluster (cluster_size), total cluster charge (charge), ...).", "scope": {"holder": "SiLab-Bonn-pixel_clusterizer", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:SketchingDev/Doodle-Dashboard:doodledashboard/configuration.py:ComponentConfigParser.parse#18899", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "doodledashboard/configuration.py", "symbol": "ComponentConfigParser.parse"}, "source_id": "csn:SketchingDev/Doodle-Dashboard:doodledashboard/configuration.py:ComponentConfigParser.parse#18899"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/SketchingDev/Doodle-Dashboard/blob/4d7f4c248875f82a962c275009aac4aa76bd0320/doodledashboard/configuration.py#L43-L62", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:SketchingDev-Doodle-Dashboard:ComponentConfigParser.parse-2006e4f82a", "question": "Parses the section of configuration pertaining to a component\n :param config: dict of specific config section\n :return:", "scope": {"holder": "SketchingDev-Doodle-Dashboard", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:SketchingDev/Doodle-Dashboard:doodledashboard/cli.py:list#18898", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "doodledashboard/cli.py", "symbol": "list"}, "source_id": "csn:SketchingDev/Doodle-Dashboard:doodledashboard/cli.py:list#18898"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/SketchingDev/Doodle-Dashboard/blob/4d7f4c248875f82a962c275009aac4aa76bd0320/doodledashboard/cli.py#L163-L184", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:SketchingDev-Doodle-Dashboard:list-5952758093", "question": "List components that are available on your machine", "scope": {"holder": "SketchingDev-Doodle-Dashboard", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:Skyscanner/pages:pages/element_with_traits.py:ElementWithTraits.evaluate_traits#17656", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pages/element_with_traits.py", "symbol": "ElementWithTraits.evaluate_traits"}, "source_id": "csn:Skyscanner/pages:pages/element_with_traits.py:ElementWithTraits.evaluate_traits#17656"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Skyscanner/pages/blob/f80471ef01f84b11e4d751dff1e6398ae1e230b8/pages/element_with_traits.py#L61-L74", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Skyscanner-pages:ElementWithTraits.evaluate_traits-cbaf91bc4d", "question": "Evaluates traits and returns a list containing the description of traits which are not true.\n Notice that if LAZY_EVALUATION is set to False all traits are evaluated before returning. Use this option\n only for debugging purposes.", "scope": {"holder": "Skyscanner-pages", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:Skyscanner/pages:pages/ui_component.py:UIComponent.locate#17653", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pages/ui_component.py", "symbol": "UIComponent.locate"}, "source_id": "csn:Skyscanner/pages:pages/ui_component.py:UIComponent.locate#17653"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Skyscanner/pages/blob/f80471ef01f84b11e4d751dff1e6398ae1e230b8/pages/ui_component.py#L68-L80", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Skyscanner-pages:UIComponent.locate-662da7fb1f", "question": "Lazily locates the element on the DOM if the WebElement instance is not available already.\n Returns a WebElement object.\n It also caches the element if caching has been set through cache().", "scope": {"holder": "Skyscanner-pages", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:SmBe19/praw-OAuth2Util:OAuth2Util/OAuth2Util.py:OAuth2Util._change_value#14465", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "OAuth2Util/OAuth2Util.py", "symbol": "OAuth2Util._change_value"}, "source_id": "csn:SmBe19/praw-OAuth2Util:OAuth2Util/OAuth2Util.py:OAuth2Util._change_value#14465"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/SmBe19/praw-OAuth2Util/blob/ca0a2d4d7eefcc681aac92c9cd4b83cd9ea6c5fe/OAuth2Util/OAuth2Util.py#L196-L206", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:SmBe19-praw-OAuth2Util:OAuth2Util._change_value-19b103ccd3", "question": "Change the value of the given key in the given file to the given value", "scope": {"holder": "SmBe19-praw-OAuth2Util", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:SmBe19/praw-OAuth2Util:OAuth2Util/OAuth2Util.py:OAuth2Util._set_app_info#14463", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "OAuth2Util/OAuth2Util.py", "symbol": "OAuth2Util._set_app_info"}, "source_id": "csn:SmBe19/praw-OAuth2Util:OAuth2Util/OAuth2Util.py:OAuth2Util._set_app_info#14463"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/SmBe19/praw-OAuth2Util/blob/ca0a2d4d7eefcc681aac92c9cd4b83cd9ea6c5fe/OAuth2Util/OAuth2Util.py#L167-L175", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:SmBe19-praw-OAuth2Util:OAuth2Util._set_app_info-83b4caf263", "question": "Set the app info (id & secret) read from the config file on the Reddit object", "scope": {"holder": "SmBe19-praw-OAuth2Util", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:SmartDeveloperHub/sdh-curator-py:sdh/curator/client/__init__.py:FragmentRequestGraph.__extend_uri#20745", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "sdh/curator/client/__init__.py", "symbol": "FragmentRequestGraph.__extend_uri"}, "source_id": "csn:SmartDeveloperHub/sdh-curator-py:sdh/curator/client/__init__.py:FragmentRequestGraph.__extend_uri#20745"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/SmartDeveloperHub/sdh-curator-py/blob/f2fd14751cbf49918b2a4e34ec4518c8bc62083c/sdh/curator/client/__init__.py#L189-L200", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:SmartDeveloperHub-sdh-curator-py:FragmentRequestGraph.__extend_uri-5ac4f6391e", "question": "Extend a prefixed uri with the help of a specific dictionary of prefixes\n :param short: Prefixed uri to be extended\n :return:", "scope": {"holder": "SmartDeveloperHub-sdh-curator-py", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:SmokinCaterpillar/pypet:pypet/annotations.py:Annotations.f_ann_to_str#12567", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pypet/annotations.py", "symbol": "Annotations.f_ann_to_str"}, "source_id": "csn:SmokinCaterpillar/pypet:pypet/annotations.py:Annotations.f_ann_to_str#12567"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/SmokinCaterpillar/pypet/blob/97ad3e80d46dbdea02deeb98ea41f05a19565826/pypet/annotations.py#L175-L180", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:SmokinCaterpillar-pypet:Annotations.f_ann_to_str-628b1d1537", "question": "Returns all annotations lexicographically sorted as a concatenated string.", "scope": {"holder": "SmokinCaterpillar-pypet", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:SmokinCaterpillar/pypet:pypet/parameter.py:PickleParameter._load#12801", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pypet/parameter.py", "symbol": "PickleParameter._load"}, "source_id": "csn:SmokinCaterpillar/pypet:pypet/parameter.py:PickleParameter._load#12801"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/SmokinCaterpillar/pypet/blob/97ad3e80d46dbdea02deeb98ea41f05a19565826/pypet/parameter.py#L1792-L1832", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:SmokinCaterpillar-pypet:PickleParameter._load-7517f5c6d6", "question": "Reconstructs objects from the pickle dumps in `load_dict`.\n\n The 'explored_data' entry in `load_dict` is used to reconstruct\n the exploration range in the correct order.\n\n Sets the `v_protocol` property to the protocol used to store 'data'.", "scope": {"holder": "SmokinCaterpillar-pypet", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:StackSentinel/stacksentinel-python:StackSentinel/__init__.py:StackSentinelClient.handle_exception#19581", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "StackSentinel/__init__.py", "symbol": "StackSentinelClient.handle_exception"}, "source_id": "csn:StackSentinel/stacksentinel-python:StackSentinel/__init__.py:StackSentinelClient.handle_exception#19581"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/StackSentinel/stacksentinel-python/blob/253664ac5ccaeb312f4288580e10061dac65403c/StackSentinel/__init__.py#L113-L190", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:StackSentinel-stacksentinel-python:StackSentinelClient.handle_exception-0fa48c2d4f", "question": "Call this method from within a try/except clause to generate a call to Stack Sentinel.\n\n :param exc_info: Return value of sys.exc_info(). If you pass None, handle_exception will call sys.exc_info() itself\n :param state: Dictionary of state information associated with the error. This could be form data, cookie data, whatnot. NOTE: sys and machine are added to this dictionary if they are not already included.\n :param tags: Any string tags you want associated with the exception report.\n :param return_feedback_urls: If True, Stack Sentinel will return feedback URLs you can present to the user for extra debugging information.\n :param dry_run: If True, method will not actively send in error information to API. Instead, it will return a request object and payload. Used in unittests.", "scope": {"holder": "StackSentinel-stacksentinel-python", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:StackSentinel/stacksentinel-python:StackSentinel/__init__.py:StackSentinelClient.send_error#19582", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "StackSentinel/__init__.py", "symbol": "StackSentinelClient.send_error"}, "source_id": "csn:StackSentinel/stacksentinel-python:StackSentinel/__init__.py:StackSentinelClient.send_error#19582"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/StackSentinel/stacksentinel-python/blob/253664ac5ccaeb312f4288580e10061dac65403c/StackSentinel/__init__.py#L219-L254", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:StackSentinel-stacksentinel-python:StackSentinelClient.send_error-e7ab8769ac", "question": "Sends error payload to Stack Sentinel API, returning a parsed JSON response. (Parsed as in,\n converted into Python dict/list objects)\n\n :param error_type: Type of error generated. (Eg, \"TypeError\")\n :param error_message: Message of error generated (Eg, \"cannot concatenate 'str' and 'int' objects\")\n :param traceback: List of dictionaries. Each dictionary should contain, \"line\", \"method\", and \"module\" keys.\n :param environment: Environment the error occurred in (eg, \"devel\")_\n :param state: State of the application when the error happened. Could contain form data, cookies, etc.\n :param tags: Arbitrary tags you want associated with the error. list.\n :param return_feedback_urls: If True, return payload will offer URLs to send users to collect additional feedback for debugging.\n :return: Parsed return value from Stack Sentinel API", "scope": {"holder": "StackSentinel-stacksentinel-python", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:StaticCube/python-synology:SynologyDSM/SynologyDSM.py:SynoFormatHelper.bytes_to_readable#14437", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "SynologyDSM/SynologyDSM.py", "symbol": "SynoFormatHelper.bytes_to_readable"}, "source_id": "csn:StaticCube/python-synology:SynologyDSM/SynologyDSM.py:SynoFormatHelper.bytes_to_readable#14437"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/StaticCube/python-synology/blob/a5446a052fc91a38f7589803dc7a654180db2566/SynologyDSM/SynologyDSM.py#L12-L23", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:StaticCube-python-synology:SynoFormatHelper.bytes_to_readable-33c563c2c4", "question": "Converts bytes to a human readable format", "scope": {"holder": "StaticCube-python-synology", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:StaticCube/python-synology:SynologyDSM/SynologyDSM.py:SynoUtilization._get_network#14440", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "SynologyDSM/SynologyDSM.py", "symbol": "SynoUtilization._get_network"}, "source_id": "csn:StaticCube/python-synology:SynologyDSM/SynologyDSM.py:SynoUtilization._get_network#14440"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/StaticCube/python-synology/blob/a5446a052fc91a38f7589803dc7a654180db2566/SynologyDSM/SynologyDSM.py#L178-L183", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:StaticCube-python-synology:SynoUtilization._get_network-d8828f4274", "question": "Function to get specific network (eth0, total, etc)", "scope": {"holder": "StaticCube-python-synology", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:TDG-Platform/cloud-harness:gbdx_cloud_harness/services/account_storage_service.py:AccountStorageService.download#15550", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "gbdx_cloud_harness/services/account_storage_service.py", "symbol": "AccountStorageService.download"}, "source_id": "csn:TDG-Platform/cloud-harness:gbdx_cloud_harness/services/account_storage_service.py:AccountStorageService.download#15550"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/TDG-Platform/cloud-harness/blob/1d8f972f861816b90785a484e9bec5bd4bc2f569/gbdx_cloud_harness/services/account_storage_service.py#L95-L139", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:TDG-Platform-cloud-harness:AccountStorageService.download-4ce9945685", "question": "download all files from a users account location\n :param local_port_path: the local path where the data is to download to\n :param key_name: can start with self.prefix or taken as relative to prefix.\n\n Example:\n local_port_path = /home/user/myworkflow/input_images/ (sync all data in this folder)\n s3_folder = myworkflow/input_images/ (location on s3 that will be synced to local path)", "scope": {"holder": "TDG-Platform-cloud-harness", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:TDG-Platform/cloud-harness:gbdx_cloud_harness/controller.py:TaskController._register_anonymous_task#15543", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "gbdx_cloud_harness/controller.py", "symbol": "TaskController._register_anonymous_task"}, "source_id": "csn:TDG-Platform/cloud-harness:gbdx_cloud_harness/controller.py:TaskController._register_anonymous_task#15543"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/TDG-Platform/cloud-harness/blob/1d8f972f861816b90785a484e9bec5bd4bc2f569/gbdx_cloud_harness/controller.py#L85-L114", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:TDG-Platform-cloud-harness:TaskController._register_anonymous_task-fb2d898929", "question": "Register the anonymouse task or overwrite it.\n :return: success or fail message.", "scope": {"holder": "TDG-Platform-cloud-harness", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:Terrance/SkPy:skpy/main.py:Skype.getEvents#7816", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "skpy/main.py", "symbol": "Skype.getEvents"}, "source_id": "csn:Terrance/SkPy:skpy/main.py:Skype.getEvents#7816"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Terrance/SkPy/blob/0f9489c94e8ec4d3effab4314497428872a80ad1/skpy/main.py#L94-L107", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Terrance-SkPy:Skype.getEvents-76774c7c85", "question": "Retrieve a list of events since the last poll. Multiple calls may be needed to retrieve all events.\n\n If no events occur, the API will block for up to 30 seconds, after which an empty list is returned. As soon as\n an event is received in this time, it is returned immediately.\n\n Returns:\n :class:`.SkypeEvent` list: a list of events, possibly empty", "scope": {"holder": "Terrance-SkPy", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:Terrance/SkPy:skpy/user.py:SkypeContacts.contact#7823", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "skpy/user.py", "symbol": "SkypeContacts.contact"}, "source_id": "csn:Terrance/SkPy:skpy/user.py:SkypeContacts.contact#7823"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Terrance/SkPy/blob/0f9489c94e8ec4d3effab4314497428872a80ad1/skpy/user.py#L388-L409", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Terrance-SkPy:SkypeContacts.contact-9f9f99db8f", "question": "Retrieve all details for a specific contact, including fields such as birthday and mood.\n\n Args:\n id (str): user identifier to lookup\n\n Returns:\n SkypeContact: resulting contact object", "scope": {"holder": "Terrance-SkPy", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:Tivix/django-rest-auth:rest_auth/serializers.py:JWTSerializer.get_user#4674", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "rest_auth/serializers.py", "symbol": "JWTSerializer.get_user"}, "source_id": "csn:Tivix/django-rest-auth:rest_auth/serializers.py:JWTSerializer.get_user#4674"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Tivix/django-rest-auth/blob/624ad01afbc86fa15b4e652406f3bdcd01f36e00/rest_auth/serializers.py#L143-L153", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Tivix-django-rest-auth:JWTSerializer.get_user-38ecc4ba03", "question": "Required to allow using custom USER_DETAILS_SERIALIZER in\n JWTSerializer. Defining it here to avoid circular imports", "scope": {"holder": "Tivix-django-rest-auth", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:Tivix/django-rest-auth:rest_auth/registration/serializers.py:SocialConnectMixin.get_social_login#4675", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "rest_auth/registration/serializers.py", "symbol": "SocialConnectMixin.get_social_login"}, "source_id": "csn:Tivix/django-rest-auth:rest_auth/registration/serializers.py:SocialConnectMixin.get_social_login#4675"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Tivix/django-rest-auth/blob/624ad01afbc86fa15b4e652406f3bdcd01f36e00/rest_auth/registration/serializers.py#L151-L159", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Tivix-django-rest-auth:SocialConnectMixin.get_social_login-0a342c732f", "question": "Set the social login process state to connect rather than login\n Refer to the implementation of get_social_login in base class and to the\n allauth.socialaccount.helpers module complete_social_login function.", "scope": {"holder": "Tivix-django-rest-auth", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:Toblerity/rtree:rtree/index.py:CustomStorage.loadByteArray#8522", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "rtree/index.py", "symbol": "CustomStorage.loadByteArray"}, "source_id": "csn:Toblerity/rtree:rtree/index.py:CustomStorage.loadByteArray#8522"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Toblerity/rtree/blob/5d33357c8e88f1a8344415dc15a7d2440211b281/rtree/index.py#L1441-L1445", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Toblerity-rtree:CustomStorage.loadByteArray-b2df323bb1", "question": "Must be overridden. Must return a string with the loaded data.", "scope": {"holder": "Toblerity-rtree", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:Toblerity/rtree:rtree/index.py:Index.deinterleave#8514", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "rtree/index.py", "symbol": "Index.deinterleave"}, "source_id": "csn:Toblerity/rtree:rtree/index.py:Index.deinterleave#8514"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Toblerity/rtree/blob/5d33357c8e88f1a8344415dc15a7d2440211b281/rtree/index.py#L661-L677", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Toblerity-rtree:Index.deinterleave-d178b18c59", "question": "[xmin, ymin, xmax, ymax] => [xmin, xmax, ymin, ymax]\n\n >>> Index.deinterleave([0, 10, 1, 11])\n [0, 1, 10, 11]\n\n >>> Index.deinterleave([0, 1, 2, 10, 11, 12])\n [0, 10, 1, 11, 2, 12]", "scope": {"holder": "Toblerity-rtree", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:ToucanToco/toucan-data-sdk:toucan_data_sdk/sdk.py:ToucanDataSdk.read_entry#9159", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "toucan_data_sdk/sdk.py", "symbol": "ToucanDataSdk.read_entry"}, "source_id": "csn:ToucanToco/toucan-data-sdk:toucan_data_sdk/sdk.py:ToucanDataSdk.read_entry#9159"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/ToucanToco/toucan-data-sdk/blob/c3ca874e1b64f4bdcc2edda750a72d45d1561d8a/toucan_data_sdk/sdk.py#L127-L137", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:ToucanToco-toucan-data-sdk:ToucanDataSdk.read_entry-87965c4c4b", "question": "Args:\n file_name (str):\n\n Returns:\n pd.DataFrame:", "scope": {"holder": "ToucanToco-toucan-data-sdk", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:ToucanToco/toucan-data-sdk:toucan_data_sdk/sdk.py:extract#9157", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "toucan_data_sdk/sdk.py", "symbol": "extract"}, "source_id": "csn:ToucanToco/toucan-data-sdk:toucan_data_sdk/sdk.py:extract#9157"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/ToucanToco/toucan-data-sdk/blob/c3ca874e1b64f4bdcc2edda750a72d45d1561d8a/toucan_data_sdk/sdk.py#L194-L213", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:ToucanToco-toucan-data-sdk:extract-623730ea3b", "question": "Args:\n data (str | byte):\n\n Returns:\n dict: Dict[str, DataFrame]", "scope": {"holder": "ToucanToco-toucan-data-sdk", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:Trim21/sdu_bkjws:sdu_bkjws/__init__.py:SduBkjws._aodata#19560", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "sdu_bkjws/__init__.py", "symbol": "SduBkjws._aodata"}, "source_id": "csn:Trim21/sdu_bkjws:sdu_bkjws/__init__.py:SduBkjws._aodata#19560"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Trim21/sdu_bkjws/blob/87e74c84e6a20b2abd20905e2381f0a572398f6c/sdu_bkjws/__init__.py#L54-L86", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Trim21-sdu_bkjws:SduBkjws._aodata-42e8029479", "question": "生成用于post的数据\n\n :param echo: a int to check is response is write\n :type echo: int\n :param columns: 所有columns列名组成的list\n :type columns: list\n :param xnxq: str\n :type xnxq: string\n :param final_exam: 是否期末考试\n :rtype: bool\n :return: a valid data for post to get data", "scope": {"holder": "Trim21-sdu_bkjws", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:Trim21/sdu_bkjws:sdu_bkjws/__init__.py:SduBkjws.get_lesson#19562", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "sdu_bkjws/__init__.py", "symbol": "SduBkjws.get_lesson"}, "source_id": "csn:Trim21/sdu_bkjws:sdu_bkjws/__init__.py:SduBkjws.get_lesson#19562"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Trim21/sdu_bkjws/blob/87e74c84e6a20b2abd20905e2381f0a572398f6c/sdu_bkjws/__init__.py#L135-L163", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Trim21-sdu_bkjws:SduBkjws.get_lesson-99889b4e44", "question": "获取课表,返回一个列表,包含所有课表对象\n\n :return: list of lessons\n :rtype: list[dict]", "scope": {"holder": "Trim21-sdu_bkjws", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:Tsjerk/Insane:insane/lipids.py:Lipid.build#17296", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "insane/lipids.py", "symbol": "Lipid.build"}, "source_id": "csn:Tsjerk/Insane:insane/lipids.py:Lipid.build#17296"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Tsjerk/Insane/blob/b73f08910ddb0b66597b20ff75ecee7f65f4ecf6/insane/lipids.py#L90-L144", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Tsjerk-Insane:Lipid.build-cf6d07e309", "question": "Build/return a list of [(bead, x, y, z), ...]", "scope": {"holder": "Tsjerk-Insane", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:Tsjerk/Insane:insane/utils.py:iter_resource#17294", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "insane/utils.py", "symbol": "iter_resource"}, "source_id": "csn:Tsjerk/Insane:insane/utils.py:iter_resource#17294"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Tsjerk/Insane/blob/b73f08910ddb0b66597b20ff75ecee7f65f4ecf6/insane/utils.py#L25-L34", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Tsjerk-Insane:iter_resource-79fa442df3", "question": "Return a stream for a given resource file in the module.\n\n The resource file has to be part of the module and its filenane given\n relative to the module.", "scope": {"holder": "Tsjerk-Insane", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:UCBerkeleySETI/blimpy:blimpy/file_wrapper.py:FilReader._find_blob_start#11779", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "blimpy/file_wrapper.py", "symbol": "FilReader._find_blob_start"}, "source_id": "csn:UCBerkeleySETI/blimpy:blimpy/file_wrapper.py:FilReader._find_blob_start#11779"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/UCBerkeleySETI/blimpy/blob/b8822d3e3e911944370d84371a91fa0c29e9772e/blimpy/file_wrapper.py#L624-L639", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:UCBerkeleySETI-blimpy:FilReader._find_blob_start-66c06f9bec", "question": "Find first blob from selection.", "scope": {"holder": "UCBerkeleySETI-blimpy", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:UCBerkeleySETI/blimpy:blimpy/waterfall.py:Waterfall.__write_to_hdf5_heavy#11791", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "blimpy/waterfall.py", "symbol": "Waterfall.__write_to_hdf5_heavy"}, "source_id": "csn:UCBerkeleySETI/blimpy:blimpy/waterfall.py:Waterfall.__write_to_hdf5_heavy#11791"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/UCBerkeleySETI/blimpy/blob/b8822d3e3e911944370d84371a91fa0c29e9772e/blimpy/waterfall.py#L309-L404", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:UCBerkeleySETI-blimpy:Waterfall.__write_to_hdf5_heavy-dcb644cef3", "question": "Write data to HDF5 file.\n\n Args:\n filename_out (str): Name of output file", "scope": {"holder": "UCBerkeleySETI-blimpy", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:UDST/pandana:pandana/network.py:Network.aggregate#10805", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pandana/network.py", "symbol": "Network.aggregate"}, "source_id": "csn:UDST/pandana:pandana/network.py:Network.aggregate#10805"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/UDST/pandana/blob/961a7ef8d3b0144b190cb60bbd61845fca6fb314/pandana/network.py#L274-L336", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:UDST-pandana:Network.aggregate-e087a871e1", "question": "Aggregate information for every source node in the network - this is\n really the main purpose of this library. This allows you to touch\n the data specified by calling set and perform some aggregation on it\n within the specified distance. For instance, summing the population\n within 1000 meters.\n\n Parameters\n ----------\n distance : float\n The maximum distance to aggregate data within. 'distance' can\n represent any impedance unit that you have set as your edge\n weight. This will usually be a distance unit in meters however\n if you have customized the impedance this could be in other\n units such as utility or time etc.\n type : string\n The type of aggregation, can be one of \"ave\", \"sum\", \"std\",\n \"count\", and now \"min\", \"25pct\", \"median\", \"75pct\", and \"max\" will\n compute the associated quantiles. (Quantiles are computed by\n sorting so might be slower than the others.)\n decay : string\n The type of decay to apply, which makes things that are further\n away count less in the aggregation - must be one of \"linear\",\n \"exponential\" or \"flat\" (which means no decay). Linear is the\n fastest computation to perform. When performing an \"ave\",\n the decay is typically \"flat\"\n imp_name : string, optional\n The impedance name to use for the aggregation on this network.\n Must be one of the impedance names passed in the constructor of\n this object. If not specified, there must be only one impedance\n passed in the constructor, which will be used.\n name : string, optional\n The variable to aggregate. This variable will have been created\n and named by a call to set. If not specified, the default\n variable name will be used so that the most recent call to set\n without giving a name will be the variable used.\n\n Returns\n -------\n agg : Pandas Series\n Returns a Pandas Series for every origin node in the network,\n with the index which is the same as the node_ids passed to the\n init method and the values are the aggregations for each source\n node in the network.", "scope": {"holder": "UDST-pandana", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:UDST/pandana:pandana/loaders/osm.py:build_node_query#10814", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pandana/loaders/osm.py", "symbol": "build_node_query"}, "source_id": "csn:UDST/pandana:pandana/loaders/osm.py:build_node_query#10814"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/UDST/pandana/blob/961a7ef8d3b0144b190cb60bbd61845fca6fb314/pandana/loaders/osm.py#L120-L157", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:UDST-pandana:build_node_query-53fe220c9b", "question": "Build the string for a node-based OSM query.\n\n Parameters\n ----------\n lat_min, lng_min, lat_max, lng_max : float\n tags : str or list of str, optional\n Node tags that will be used to filter the search.\n See http://wiki.openstreetmap.org/wiki/Overpass_API/Language_Guide\n for information about OSM Overpass queries\n and http://wiki.openstreetmap.org/wiki/Map_Features\n for a list of tags.\n\n Returns\n -------\n query : str", "scope": {"holder": "UDST-pandana", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:URXtech/cmph-cffi:cmph/__init__.py:MPH.lookup#19280", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "cmph/__init__.py", "symbol": "MPH.lookup"}, "source_id": "csn:URXtech/cmph-cffi:cmph/__init__.py:MPH.lookup#19280"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/URXtech/cmph-cffi/blob/85298572e51675cd0c7ef1052ed9989b0e57f0cc/cmph/__init__.py#L252-L273", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:URXtech-cmph-cffi:MPH.lookup-8397716751", "question": "Generate hash code for a key from the Minimal Perfect Hash (MPH)\n\n Parameters\n ----------\n Key : object\n The item to generate a key for, this works best for keys that\n are strings, or can be transformed fairly directly into bytes\n\n Returns : int\n The code for the given item", "scope": {"holder": "URXtech-cmph-cffi", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:URXtech/cmph-cffi:cmph/__init__.py:generate_hash#19277", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "cmph/__init__.py", "symbol": "generate_hash"}, "source_id": "csn:URXtech/cmph-cffi:cmph/__init__.py:generate_hash#19277"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/URXtech/cmph-cffi/blob/85298572e51675cd0c7ef1052ed9989b0e57f0cc/cmph/__init__.py#L388-L567", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:URXtech-cmph-cffi:generate_hash-956208fecb", "question": "Generates a new Minimal Perfect Hash (MPH)\n\n Parameters\n ----------\n data : list, array-like, file-like\n The input that is used to generate the minimal perfect hash.\n\n Be aware, in most cases the input is expected to be distinct, and\n many of the algorithms benefit from the input being sorted.\n\n algorithm : string, optional\n {chd_ph (default), chd, bmz, bmz8, chm, brz, fch, bdz, bdz_ph}\n The algorithm to use in generating MPH's, choice of:\n\n chd / chd_ph - Compress Hash and Displace (default)\n (http://cmph.sourceforge.net/chd.html)\n - It is the fastest algorithm to build PHFs and MPHFs in linear\n time.\n - It generates the most compact PHFs and MPHFs we know of.\n - It can generate PHFs with a load factor up to 99 %.\n - It can be used to generate t-perfect hash functions. A\n t-perfect hash function allows at most t collisions in a given\n bin. It is a well-known fact that modern memories are\n organized as blocks which constitute transfer unit. Example of\n such blocks are cache lines for internal memory or sectors for\n hard disks. Thus, it can be very useful for devices that\n carry out I/O operations in blocks.\n - It is a two level scheme. It uses a first level hash function\n to split the key set in buckets of average size determined by\n a parameter b in the range [1,32]. In the second level it uses\n displacement values to resolve the collisions that have given\n rise to the buckets.\n - It can generate MPHFs that can be stored in approximately 2.07\n bits per key.\n - For a load factor equal to the maximum one that is achieved by\n the BDZ algorithm (81 %), the resulting PHFs are stored in\n approximately 1.40 bits per key.\n\n bdz - BDZ / BPZ algorithm\n (http://cmph.sourceforge.net/bdz.html)\n - It is very simple and efficient. It outperforms all others\n except CHD.\n - It constructs both PHFs and MPHFs in linear time.\n - The maximum load factor one can achieve for a PHF is 1/1.23.\n - It is based on acyclic random 3-graphs. A 3-graph is a\n generalization of a graph where each edge connects 3 vertices\n instead of only 2.\n - The resulting MPHFs are not order preserving.\n - The resulting MPHFs can be stored in only (2 + x)cn bits,\n where c should be larger than or equal to 1.23 and x is a\n constant larger than 0 (actually, x = 1/b and b is a parameter\n that should be larger than 2). For c = 1.23 and b = 8, the\n resulting functions are stored in approximately 2.6 bits per\n key.\n - For its maximum load factor (81 %), the resulting PHFs are\n stored in approximately 1.95 bits per key.\n\n bmz - Botelho, Menoti and Ziviani algorithm:\n (http://cmph.sourceforge.net/bdz.html)\n - Constructs MPHFs in linear time.\n - It is based on cyclic random graphs. This makes it faster than\n the CHM algorithm.\n - The resulting MPHFs are not order preserving.\n - The resulting MPHFs are more compact than the ones generated by\n the CHM algorithm and can be stored in 4cn bytes, where c is in\n the range [0.93,1.15].\n\n brz - BRZ algorithm:\n (http://cmph.sourceforge.net/brz.html)\n - A very fast external memory based algorithm for constructing\n minimal perfect hash functions for sets in the order of\n billions of keys.\n - It works in linear time.\n - The resulting MPHFs are not order preserving.\n - The resulting MPHFs can be stored using less than 8.0 bits per\n key.\n\n chm - Czech, Havas and Majewski algorithm:\n (http://cmph.sourceforge.net/chm.html)\n - Construct minimal MPHFs in linear time.\n - It is based on acyclic random graphs\n - The resulting MPHFs are order preserving.\n - The resulting MPHFs are stored in 4cn bytes, where c is greater\n than 2.\n\n fch - Fox, Chen and Heath algorithm:\n (http://cmph.sourceforge.net/chm.html)\n - Construct minimal perfect hash functions that require less than\n 4 bits per key to be stored.\n - The resulting MPHFs are very compact and very efficient at\n evaluation time\n - The algorithm is only efficient for small sets.\n - It is used as internal algorithm in the BRZ algorithm to\n efficiently solve larger problems and even so to generate MPHFs\n that require approximately 4.1 bits per key to be stored. For\n that, you just need to set the parameters -a to brz and -c to a\n value larger than or equal to 2.6.\n\n hash_fns : list {jenkins (default), count} optional\n Internal hash functions to use inside MPH generation functions,\n can be multiple fns as a list.\n\n chd_keys_per_bin : int [1 to 128], optional\n Set the number of keys per bin for a t-perfect hashing function. A\n t-perfect hash function allows at most t collisions in a given bin.\n This parameter applies only to the `chd` and `chd_ph` algorithms.\n Its value should be an integer in the range [1, 128].\n\n Default is 1\n\n chd_load_factor : float, optional\n The load factor used in the `chd_ph` algorithm\n\n fch_bits_per_key : int, optional\n The number of bits per key required in the FCH algorithm\n\n num_graph_vertices : int, optional\n The number of vertices in the graph for the algorithms BMZ and CHM\n\n brz_memory_size : int (default 8), optional\n Main memory availability (in MB) used in BRZ algorithm\n\n Default is 8Mb\n\n brz_temp_dir : string, optional\n Temporary directory used in BRZ algorithm\n\n brz_max_keys_per_bucket : int [64 to 175] (default 128), optional\n Used to make the maximal number of keys in a bucket lower than 256.\n In this case its value should be an integer in the range [64,175].\n Default is 128.\n\n bdz_precomputed_rank : int [3 to 10] (default 7), optional\n For BDZ it is used to determine the size of some precomputed rank\n information and its value should be an integer in the range [3,10].\n\n Default is 7.\n\n The larger is this value, the more compact are the resulting\n functions and the slower are them at evaluation time.\n\n chd_avg_keys_per_bucket : int [1 to 32] (default 4), optional\n For CHD and CHD_PH it is used to set the average number of keys per\n bucket and its value should be an integer in the range [1,32].\n\n Default is 4.\n\n The larger is this value, the slower is the construction of the\n functions.\n\n Returns\n -------\n MPH\n A wrapper object that represents a minimal perfect hash in memory\n\n Raises\n ------\n ValueError\n If arguments presented are incomplete, or incompatable\n RuntimeError\n If the MPH generation fails", "scope": {"holder": "URXtech-cmph-cffi", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:Valuehorizon/valuehorizon-forex:forex/models.py:Currency.compute_return#21405", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "forex/models.py", "symbol": "Currency.compute_return"}, "source_id": "csn:Valuehorizon/valuehorizon-forex:forex/models.py:Currency.compute_return#21405"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Valuehorizon/valuehorizon-forex/blob/e921379ae6c9d07ddad87a1fd3b5bb8fdfc74cb8/forex/models.py#L59-L75", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Valuehorizon-valuehorizon-forex:Currency.compute_return-10ea9791d5", "question": "Compute the return of the currency between two dates", "scope": {"holder": "Valuehorizon-valuehorizon-forex", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:Valuehorizon/valuehorizon-forex:forex/models.py:CurrencyPriceManager.generate_dataframe#21406", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "forex/models.py", "symbol": "CurrencyPriceManager.generate_dataframe"}, "source_id": "csn:Valuehorizon/valuehorizon-forex:forex/models.py:CurrencyPriceManager.generate_dataframe#21406"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Valuehorizon/valuehorizon-forex/blob/e921379ae6c9d07ddad87a1fd3b5bb8fdfc74cb8/forex/models.py#L81-L125", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Valuehorizon-valuehorizon-forex:CurrencyPriceManager.generate_dataframe-ed13cc5132", "question": "Generate a dataframe consisting of the currency prices (specified by symbols)\n from the start to end date", "scope": {"holder": "Valuehorizon-valuehorizon-forex", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:VingtCinq/python-resize-image:resizeimage/resizeimage.py:_height_is_big_enough#12992", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "resizeimage/resizeimage.py", "symbol": "_height_is_big_enough"}, "source_id": "csn:VingtCinq/python-resize-image:resizeimage/resizeimage.py:_height_is_big_enough#12992"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/VingtCinq/python-resize-image/blob/a4e645792ef30c5fcc558df6da6de18b1ecb95ea/resizeimage/resizeimage.py#L50-L53", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:VingtCinq-python-resize-image:_height_is_big_enough-e65dfc7fbb", "question": "Check that the image height is superior to `height`", "scope": {"holder": "VingtCinq-python-resize-image", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:VingtCinq/python-resize-image:resizeimage/resizeimage.py:resize_height#12997", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "resizeimage/resizeimage.py", "symbol": "resize_height"}, "source_id": "csn:VingtCinq/python-resize-image:resizeimage/resizeimage.py:resize_height#12997"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/VingtCinq/python-resize-image/blob/a4e645792ef30c5fcc558df6da6de18b1ecb95ea/resizeimage/resizeimage.py#L142-L162", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:VingtCinq-python-resize-image:resize_height-e139f734ce", "question": "Resize image according to size.\n image: a Pillow image instance\n size: an integer or a list or tuple of two integers [width, height]", "scope": {"holder": "VingtCinq-python-resize-image", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:VorskiImagineering/C3PO:c3po/mod/communicator.py:Communicator._clear_temp#20987", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "c3po/mod/communicator.py", "symbol": "Communicator._clear_temp"}, "source_id": "csn:VorskiImagineering/C3PO:c3po/mod/communicator.py:Communicator._clear_temp#20987"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/VorskiImagineering/C3PO/blob/e3e35835e5ac24158848afed4f905ca44ac3ae00/c3po/mod/communicator.py#L115-L125", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:VorskiImagineering-C3PO:Communicator._clear_temp-12802afa55", "question": "Clear temp directory from created csv and ods files during\n communicator operations.", "scope": {"holder": "VorskiImagineering-C3PO", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:VorskiImagineering/C3PO:c3po/converters/po_csv.py:_prepare_polib_files#20780", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "c3po/converters/po_csv.py", "symbol": "_prepare_polib_files"}, "source_id": "csn:VorskiImagineering/C3PO:c3po/converters/po_csv.py:_prepare_polib_files#20780"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/VorskiImagineering/C3PO/blob/e3e35835e5ac24158848afed4f905ca44ac3ae00/c3po/converters/po_csv.py#L61-L80", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:VorskiImagineering-C3PO:_prepare_polib_files-01e5a98124", "question": "Prepare polib file object for writing/reading from them.\n Create directories and write header if needed. For each language,\n ensure there's a translation file named \"filename\" in the correct place.\n Assumes (and creates) a directory structure:\n <locale_root>/<lang>/<po_files_path>/<filename>.", "scope": {"holder": "VorskiImagineering-C3PO", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:WGBH/wagtail-streamfieldtools:streamfield_tools/registry.py:RegisteredBlockStreamFieldRegistry.register_block#16545", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "streamfield_tools/registry.py", "symbol": "RegisteredBlockStreamFieldRegistry.register_block"}, "source_id": "csn:WGBH/wagtail-streamfieldtools:streamfield_tools/registry.py:RegisteredBlockStreamFieldRegistry.register_block#16545"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/WGBH/wagtail-streamfieldtools/blob/192f86845532742b0b7d432bef3987357833b8ed/streamfield_tools/registry.py#L51-L57", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:WGBH-wagtail-streamfieldtools:RegisteredBlockStreamFieldRegistry.register_block-73567e0473", "question": "Registers `block` to `block_type` in the registry.", "scope": {"holder": "WGBH-wagtail-streamfieldtools", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:WGBH/wagtail-streamfieldtools:streamfield_tools/blocks/struct_block.py:RenditionAwareStructBlock.get_context#16506", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "streamfield_tools/blocks/struct_block.py", "symbol": "RenditionAwareStructBlock.get_context"}, "source_id": "csn:WGBH/wagtail-streamfieldtools:streamfield_tools/blocks/struct_block.py:RenditionAwareStructBlock.get_context#16506"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/WGBH/wagtail-streamfieldtools/blob/192f86845532742b0b7d432bef3987357833b8ed/streamfield_tools/blocks/struct_block.py#L118-L123", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:WGBH-wagtail-streamfieldtools:RenditionAwareStructBlock.get_context-d9a4b359de", "question": "Ensure `image_rendition` is added to the global context.", "scope": {"holder": "WGBH-wagtail-streamfieldtools", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:WhoopInc/pytsdb:pytsdb.py:Connection.fetch_metric#16622", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pytsdb.py", "symbol": "Connection.fetch_metric"}, "source_id": "csn:WhoopInc/pytsdb:pytsdb.py:Connection.fetch_metric#16622"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/WhoopInc/pytsdb/blob/f053c2effa7a9175c5521e690dbb23700c6c0cfe/pytsdb.py#L20-L101", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:WhoopInc-pytsdb:Connection.fetch_metric-ea5e52bfb2", "question": "Fetch time series data from OpenTSDB\n\n Parameters:\n metric:\n A string representing a valid OpenTSDB metric.\n\n tags:\n A dict mapping tag names to tag values. Tag names and values are\n always strings.\n\n { 'user_id': '44' }\n\n start:\n A datetime.datetime-like object representing the start of the\n range to query over.\n\n end:\n A datetime.datetime-like object representing the end of the\n range to query over.\n\n aggregator:\n The function for merging multiple time series together. For\n example, if the \"user_id\" tag is not specified, this aggregator\n function is used to combine all heart rate time series into one\n time series. (Yes, this isn't very useful.)\n\n For queries that return only one time series, this parameter is\n not relevant.\n\n Valid values: \"sum\", \"min\", \"max\", \"avg\", \"dev\"\n\n See: http://opentsdb.net/docs/build/html/user_guide/query/aggregators.html\n\n downsampling:\n A relative time interval to \"downsample\". This isn't true\n downsampling; rather, if you specify a downsampling of \"5m\"\n (five minutes), OpenTSDB will split data into five minute\n intervals, and return one data point in the middle of each\n interval whose value is the average of all data points within\n that interval.\n\n Valid relative time values are strings of the following format:\n\n \"<amount><time_unit>\"\n\n Valid time units: \"ms\", \"s\", \"m\", \"h\", \"d\", \"w\", \"n\", \"y\"\n\n Date and time format: http://opentsdb.net/docs/build/html/user_guide/query/dates.html\n\n ms_resolution:\n Whether or not to output data point timestamps in milliseconds\n or seconds. If this flag is false and there are multiple\n data points within a second, those data points will be down\n sampled using the query's aggregation function.\n\n Returns:\n A dict mapping timestamps to data points", "scope": {"holder": "WhoopInc-pytsdb", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:WhoopInc/pytsdb:pytsdb.py:Connection.fetch_sorted_metric#16623", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pytsdb.py", "symbol": "Connection.fetch_sorted_metric"}, "source_id": "csn:WhoopInc/pytsdb:pytsdb.py:Connection.fetch_sorted_metric#16623"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/WhoopInc/pytsdb/blob/f053c2effa7a9175c5521e690dbb23700c6c0cfe/pytsdb.py#L103-L110", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:WhoopInc-pytsdb:Connection.fetch_sorted_metric-44a26876fa", "question": "Fetch and sort time series data from OpenTSDB\n\n Takes the same parameters as `fetch_metric`, but returns a list of\n (timestamp, value) tuples sorted by timestamp.", "scope": {"holder": "WhoopInc-pytsdb", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:WoLpH/mt940:mt940/processors.py:date_fixup_pre_processor#7411", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "mt940/processors.py", "symbol": "date_fixup_pre_processor"}, "source_id": "csn:WoLpH/mt940:mt940/processors.py:date_fixup_pre_processor#7411"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/WoLpH/mt940/blob/fd71c88f7ec8372f4194f831f4c29c6f9bd9d0eb/mt940/processors.py#L17-L31", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:WoLpH-mt940:date_fixup_pre_processor-9b603a2d69", "question": "Replace illegal February 29, 30 dates with the last day of February.\n\n German banks use a variant of the 30/360 interest rate calculation,\n where each month has always 30 days even February. Python's datetime\n module won't accept such dates.", "scope": {"holder": "WoLpH-mt940", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:WoLpH/mt940:mt940/processors.py:mBank_set_tnr#7414", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "mt940/processors.py", "symbol": "mBank_set_tnr"}, "source_id": "csn:WoLpH/mt940:mt940/processors.py:mBank_set_tnr#7414"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/WoLpH/mt940/blob/fd71c88f7ec8372f4194f831f4c29c6f9bd9d0eb/mt940/processors.py#L73-L87", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:WoLpH-mt940:mBank_set_tnr-a2ae2bf062", "question": "mBank Collect states TNR in transaction details as unique id for\n transactions, that may be used to identify the same transactions in\n different statement files eg. partial mt942 and full mt940\n Information about tnr uniqueness has been obtained from mBank support,\n it lacks in mt940 mBank specification.", "scope": {"holder": "WoLpH-mt940", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:Yaco-Sistemas/django-transmeta:transmeta/management/commands/sync_transmeta_db.py:Command.get_db_change_languages#14851", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "transmeta/management/commands/sync_transmeta_db.py", "symbol": "Command.get_db_change_languages"}, "source_id": "csn:Yaco-Sistemas/django-transmeta:transmeta/management/commands/sync_transmeta_db.py:Command.get_db_change_languages#14851"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Yaco-Sistemas/django-transmeta/blob/de070aae27770df046b4ba995f01f654db7ed1a2/transmeta/management/commands/sync_transmeta_db.py#L134-L145", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Yaco-Sistemas-django-transmeta:Command.get_db_change_languages-7733e38e30", "question": "get only db changes fields", "scope": {"holder": "Yaco-Sistemas-django-transmeta", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:Yaco-Sistemas/django-transmeta:transmeta/management/commands/sync_transmeta_db.py:Command.handle#14850", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "transmeta/management/commands/sync_transmeta_db.py", "symbol": "Command.handle"}, "source_id": "csn:Yaco-Sistemas/django-transmeta:transmeta/management/commands/sync_transmeta_db.py:Command.handle#14850"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Yaco-Sistemas/django-transmeta/blob/de070aae27770df046b4ba995f01f654db7ed1a2/transmeta/management/commands/sync_transmeta_db.py#L63-L117", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Yaco-Sistemas-django-transmeta:Command.handle-87bdf7fec7", "question": "command execution", "scope": {"holder": "Yaco-Sistemas-django-transmeta", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:Yelp/py_zipkin:py_zipkin/encoding/_helpers.py:Span.build_v1_span#7374", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "py_zipkin/encoding/_helpers.py", "symbol": "Span.build_v1_span"}, "source_id": "csn:Yelp/py_zipkin:py_zipkin/encoding/_helpers.py:Span.build_v1_span#7374"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Yelp/py_zipkin/blob/0944d9a3fb1f1798dbb276694aeed99f2b4283ba/py_zipkin/encoding/_helpers.py#L117-L153", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Yelp-py_zipkin:Span.build_v1_span-78a1303568", "question": "Builds and returns a V1 Span.\n\n :return: newly generated _V1Span\n :rtype: _V1Span", "scope": {"holder": "Yelp-py_zipkin", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:Yelp/py_zipkin:py_zipkin/encoding/_helpers.py:copy_endpoint_with_new_service_name#7373", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "py_zipkin/encoding/_helpers.py", "symbol": "copy_endpoint_with_new_service_name"}, "source_id": "csn:Yelp/py_zipkin:py_zipkin/encoding/_helpers.py:copy_endpoint_with_new_service_name#7373"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Yelp/py_zipkin/blob/0944d9a3fb1f1798dbb276694aeed99f2b4283ba/py_zipkin/encoding/_helpers.py#L206-L220", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Yelp-py_zipkin:copy_endpoint_with_new_service_name-9213824200", "question": "Creates a copy of a given endpoint with a new service name.\n\n :param endpoint: existing Endpoint object\n :type endpoint: Endpoint\n :param new_service_name: new service name\n :type new_service_name: str\n :returns: zipkin new Endpoint object", "scope": {"holder": "Yelp-py_zipkin", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:Yubico/python-u2flib-host:u2flib_host/device.py:U2FDevice.get_supported_versions#12970", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "u2flib_host/device.py", "symbol": "U2FDevice.get_supported_versions"}, "source_id": "csn:Yubico/python-u2flib-host:u2flib_host/device.py:U2FDevice.get_supported_versions#12970"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Yubico/python-u2flib-host/blob/eadc4dbf3bf516e74ea00d2e5690742a535834cb/u2flib_host/device.py#L69-L80", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Yubico-python-u2flib-host:U2FDevice.get_supported_versions-729e2aa275", "question": "Gets a list of supported U2F versions from the device.", "scope": {"holder": "Yubico-python-u2flib-host", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:Yubico/python-u2flib-host:u2flib_host/u2f_v2.py:authenticate#12974", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "u2flib_host/u2f_v2.py", "symbol": "authenticate"}, "source_id": "csn:Yubico/python-u2flib-host:u2flib_host/u2f_v2.py:authenticate#12974"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Yubico/python-u2flib-host/blob/eadc4dbf3bf516e74ea00d2e5690742a535834cb/u2flib_host/u2f_v2.py#L81-L126", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Yubico-python-u2flib-host:authenticate-f3e9a132e0", "question": "Signs an authentication challenge\n\n data = {\n 'version': \"U2F_V2\",\n 'challenge': websafe_encode(self.challenge),\n 'appId': self.binding.app_id,\n 'keyHandle': websafe_encode(self.binding.key_handle)\n }", "scope": {"holder": "Yubico-python-u2flib-host", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:ZELLMECHANIK-DRESDEN/fcswrite:examples/tdms2fcs.py:add_deformation#12908", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "examples/tdms2fcs.py", "symbol": "add_deformation"}, "source_id": "csn:ZELLMECHANIK-DRESDEN/fcswrite:examples/tdms2fcs.py:add_deformation#12908"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/ZELLMECHANIK-DRESDEN/fcswrite/blob/5584983aa1eb927660183252039e73285c0724b3/examples/tdms2fcs.py#L32-L44", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:ZELLMECHANIK-DRESDEN-fcswrite:add_deformation-76d0555270", "question": "From circularity, compute the deformation\n\n This method is useful for RT-DC data sets that contain\n the circularity but not the deformation.", "scope": {"holder": "ZELLMECHANIK-DRESDEN-fcswrite", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:ZELLMECHANIK-DRESDEN/fcswrite:examples/tdms2fcs.py:tdms2fcs#12909", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "examples/tdms2fcs.py", "symbol": "tdms2fcs"}, "source_id": "csn:ZELLMECHANIK-DRESDEN/fcswrite:examples/tdms2fcs.py:tdms2fcs#12909"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/ZELLMECHANIK-DRESDEN/fcswrite/blob/5584983aa1eb927660183252039e73285c0724b3/examples/tdms2fcs.py#L47-L54", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:ZELLMECHANIK-DRESDEN-fcswrite:tdms2fcs-959f8a5053", "question": "Creates an fcs file for a given tdms file", "scope": {"holder": "ZELLMECHANIK-DRESDEN-fcswrite", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:a-tal/nagaram:nagaram/anagrams.py:_letter_map#19569", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "nagaram/anagrams.py", "symbol": "_letter_map"}, "source_id": "csn:a-tal/nagaram:nagaram/anagrams.py:_letter_map#19569"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/a-tal/nagaram/blob/2edcb0ef8cb569ebd1c398be826472b4831d6110/nagaram/anagrams.py#L7-L23", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:a-tal-nagaram:_letter_map-10173fda89", "question": "Creates a map of letter use in a word.\n\n Args:\n word: a string to create a letter map from\n\n Returns:\n a dictionary of {letter: integer count of letter in word}", "scope": {"holder": "a-tal-nagaram", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:a-tal/nagaram:nagaram/cmdline.py:main#19675", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "nagaram/cmdline.py", "symbol": "main"}, "source_id": "csn:a-tal/nagaram:nagaram/cmdline.py:main#19675"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/a-tal/nagaram/blob/2edcb0ef8cb569ebd1c398be826472b4831d6110/nagaram/cmdline.py#L148-L160", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:a-tal-nagaram:main-f72fd797b0", "question": "Main command line entry point.", "scope": {"holder": "a-tal-nagaram", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:abau171/highfive:highfive/jobs.py:JobManager._distribute_jobs#19322", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "highfive/jobs.py", "symbol": "JobManager._distribute_jobs"}, "source_id": "csn:abau171/highfive:highfive/jobs.py:JobManager._distribute_jobs#19322"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/abau171/highfive/blob/07b3829331072035ab100d1d66deca3e8f3f372a/highfive/jobs.py#L359-L370", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:abau171-highfive:JobManager._distribute_jobs-6924ada722", "question": "Distributes jobs from the active job set to any waiting get_job\n callbacks.", "scope": {"holder": "abau171-highfive", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:abau171/highfive:highfive/master.py:Master.run#19311", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "highfive/master.py", "symbol": "Master.run"}, "source_id": "csn:abau171/highfive:highfive/master.py:Master.run#19311"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/abau171/highfive/blob/07b3829331072035ab100d1d66deca3e8f3f372a/highfive/master.py#L183-L191", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:abau171-highfive:Master.run-1e82ee1150", "question": "Runs a job set which consists of the jobs in an iterable job list.", "scope": {"holder": "abau171-highfive", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:accraze/pymtranslate:pymtranslate/translator.py:Translator.convertArgsToTokens#16173", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pymtranslate/translator.py", "symbol": "Translator.convertArgsToTokens"}, "source_id": "csn:accraze/pymtranslate:pymtranslate/translator.py:Translator.convertArgsToTokens#16173"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/accraze/pymtranslate/blob/b18f9d7e8ef1583c988e8beb6c3304d362a4d979/pymtranslate/translator.py#L44-L62", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:accraze-pymtranslate:Translator.convertArgsToTokens-018e3c04b4", "question": "this converts the readin lines from\n sys to useable format, returns list\n of token and dict of tokens", "scope": {"holder": "accraze-pymtranslate", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:accraze/pymtranslate:pymtranslate/translator.py:Translator.iterateEM#16175", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pymtranslate/translator.py", "symbol": "Translator.iterateEM"}, "source_id": "csn:accraze/pymtranslate:pymtranslate/translator.py:Translator.iterateEM#16175"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/accraze/pymtranslate/blob/b18f9d7e8ef1583c988e8beb6c3304d362a4d979/pymtranslate/translator.py#L103-L179", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:accraze-pymtranslate:Translator.iterateEM-584bce293e", "question": "Iterate through all transmissions of english to\n foreign words. keep count of repeated occurences\n do until convergence\n set count(e|f) to 0 for all e,f\n set total(f) to 0 for all f\n for all sentence pairs (e_s,f_s)\n set total_s(e) = 0 for all e\n for all words e in e_s\n for all words f in f_s\n total_s(e) += t(e|f)\n for all words e in e_s\n for all words f in f_s\n count(e|f) += t(e|f) / total_s(e)\n total(f) += t(e|f) / total_s(e)\n for all f\n for all e\n t(e|f) = count(e|f) / total(f)", "scope": {"holder": "accraze-pymtranslate", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:adafruit/Adafruit_Python_PureIO:Adafruit_PureIO/smbus.py:SMBus.process_call#14104", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "Adafruit_PureIO/smbus.py", "symbol": "SMBus.process_call"}, "source_id": "csn:adafruit/Adafruit_Python_PureIO:Adafruit_PureIO/smbus.py:SMBus.process_call#14104"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/adafruit/Adafruit_Python_PureIO/blob/6f4976d91c52d70b67b28bba75a429b5328a52c1/Adafruit_PureIO/smbus.py#L296-L314", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:adafruit-Adafruit_Python_PureIO:SMBus.process_call-edd65038ad", "question": "Perform a smbus process call by writing a word (2 byte) value to\n the specified register of the device, and then reading a word of response\n data (which is returned).", "scope": {"holder": "adafruit-Adafruit_Python_PureIO", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:adafruit/Adafruit_Python_PureIO:Adafruit_PureIO/smbus.py:SMBus.write_byte#14098", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "Adafruit_PureIO/smbus.py", "symbol": "SMBus.write_byte"}, "source_id": "csn:adafruit/Adafruit_Python_PureIO:Adafruit_PureIO/smbus.py:SMBus.write_byte#14098"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/adafruit/Adafruit_Python_PureIO/blob/6f4976d91c52d70b67b28bba75a429b5328a52c1/Adafruit_PureIO/smbus.py#L232-L238", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:adafruit-Adafruit_Python_PureIO:SMBus.write_byte-185ed65c9c", "question": "Write a single byte to the specified device.", "scope": {"holder": "adafruit-Adafruit_Python_PureIO", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:addok/addok:addok/helpers/__init__.py:ChunkedPool.imap_unordered#9483", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "addok/helpers/__init__.py", "symbol": "ChunkedPool.imap_unordered"}, "source_id": "csn:addok/addok:addok/helpers/__init__.py:ChunkedPool.imap_unordered#9483"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/addok/addok/blob/46a270d76ec778d2b445c2be753e5c6ba070a9b2/addok/helpers/__init__.py#L144-L164", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:addok-addok:ChunkedPool.imap_unordered-08486e4b80", "question": "Customized version of imap_unordered.\n\n Directly send chunks to func, instead of iterating in each process and\n sending one by one.\n\n Original:\n https://hg.python.org/cpython/file/tip/Lib/multiprocessing/pool.py#l271\n\n Other tried options:\n - map_async: makes a list(iterable), so it loads all the data for each\n process into RAM\n - apply_async: needs manual chunking", "scope": {"holder": "addok-addok", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:addok/addok:addok/shell.py:Cmd.do_INTERSECT#9490", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "addok/shell.py", "symbol": "Cmd.do_INTERSECT"}, "source_id": "csn:addok/addok:addok/shell.py:Cmd.do_INTERSECT#9490"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/addok/addok/blob/46a270d76ec778d2b445c2be753e5c6ba070a9b2/addok/shell.py#L218-L234", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:addok-addok:Cmd.do_INTERSECT-18e8b24e97", "question": "Do a raw intersect between tokens (default limit 100).\n INTERSECT rue des lilas [LIMIT 100]", "scope": {"holder": "addok-addok", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:agabrown/PyGaia:pygaia/astrometry/coordinates.py:CoordinateTransformation._getJacobian#11912", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pygaia/astrometry/coordinates.py", "symbol": "CoordinateTransformation._getJacobian"}, "source_id": "csn:agabrown/PyGaia:pygaia/astrometry/coordinates.py:CoordinateTransformation._getJacobian#11912"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/agabrown/PyGaia/blob/ae972b0622a15f713ffae471f925eac25ccdae47/pygaia/astrometry/coordinates.py#L298-L342", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:agabrown-PyGaia:CoordinateTransformation._getJacobian-5ee61af87e", "question": "Calculates the Jacobian for the transformation of the position errors and proper motion errors\n between coordinate systems. This Jacobian is also the rotation matrix for the transformation of\n proper motions. See section 1.5.3 of the Hipparcos Explanatory Volume 1 (equation 1.5.20). This\n matrix has the following form:\n\n | c s |\n J = | |\n | -s c |\n\n Parameters\n ----------\n\n phi - The longitude-like angle of the position of the source (radians).\n theta - The latitude-like angle of the position of the source (radians).\n\n Returns\n -------\n\n c, s - The Jacobian matrix elements c and s corresponding to (phi, theta) and the currently\n desired coordinate system transformation.", "scope": {"holder": "agabrown-PyGaia", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:agabrown/PyGaia:examples/radialVelocityHorizons.py:makePlot#11916", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "examples/radialVelocityHorizons.py", "symbol": "makePlot"}, "source_id": "csn:agabrown/PyGaia:examples/radialVelocityHorizons.py:makePlot#11916"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/agabrown/PyGaia/blob/ae972b0622a15f713ffae471f925eac25ccdae47/examples/radialVelocityHorizons.py#L35-L129", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:agabrown-PyGaia:makePlot-2c382b0b29", "question": "Make the plot with parallax horizons. The plot shows V-band magnitude vs distance for a number of\n spectral types and over the range 5.7<G<20. In addition a set of crudely drawn contours show the points\n where 0.1, 1, and 10 per cent relative parallax accracy are reached.\n\n Parameters\n ----------\n \n args - Command line arguments.", "scope": {"holder": "agabrown-PyGaia", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:agile-geoscience/striplog:striplog/component.py:Component._repr_html_#7665", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "striplog/component.py", "symbol": "Component._repr_html_"}, "source_id": "csn:agile-geoscience/striplog:striplog/component.py:Component._repr_html_#7665"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/agile-geoscience/striplog/blob/8033b673a151f96c29802b43763e863519a3124c/striplog/component.py#L130-L139", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:agile-geoscience-striplog:Component._repr_html_-abcea0fc68", "question": "Jupyter Notebook magic repr function.", "scope": {"holder": "agile-geoscience-striplog", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:agile-geoscience/striplog:striplog/striplog.py:Striplog.depth#7698", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "striplog/striplog.py", "symbol": "Striplog.depth"}, "source_id": "csn:agile-geoscience/striplog:striplog/striplog.py:Striplog.depth#7698"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/agile-geoscience/striplog/blob/8033b673a151f96c29802b43763e863519a3124c/striplog/striplog.py#L1592-L1600", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:agile-geoscience-striplog:Striplog.depth-923e387781", "question": "For backwards compatibility.", "scope": {"holder": "agile-geoscience-striplog", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:aholkner/bacon:native/Vendor/FreeType/src/tools/docmaker/content.py:ContentProcessor.add_markup#17410", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "native/Vendor/FreeType/src/tools/docmaker/content.py", "symbol": "ContentProcessor.add_markup"}, "source_id": "csn:aholkner/bacon:native/Vendor/FreeType/src/tools/docmaker/content.py:ContentProcessor.add_markup#17410"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/aholkner/bacon/blob/edf3810dcb211942d392a8637945871399b0650d/native/Vendor/FreeType/src/tools/docmaker/content.py#L373-L387", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:aholkner-bacon:ContentProcessor.add_markup-d7f583f2ba", "question": "add a new markup section", "scope": {"holder": "aholkner-bacon", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:aholkner/bacon:native/Vendor/FreeType/src/tools/docmaker/sources.py:SourceProcessor.parse_file#17363", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "native/Vendor/FreeType/src/tools/docmaker/sources.py", "symbol": "SourceProcessor.parse_file"}, "source_id": "csn:aholkner/bacon:native/Vendor/FreeType/src/tools/docmaker/sources.py:SourceProcessor.parse_file#17363"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/aholkner/bacon/blob/edf3810dcb211942d392a8637945871399b0650d/native/Vendor/FreeType/src/tools/docmaker/sources.py#L284-L320", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:aholkner-bacon:SourceProcessor.parse_file-10062e455d", "question": "parse a C source file, and add its blocks to the processor's list", "scope": {"holder": "aholkner-bacon", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:albertodonato/prometheus-aioexporter:prometheus_aioexporter/metric.py:MetricsRegistry.get_metric#13145", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "prometheus_aioexporter/metric.py", "symbol": "MetricsRegistry.get_metric"}, "source_id": "csn:albertodonato/prometheus-aioexporter:prometheus_aioexporter/metric.py:MetricsRegistry.get_metric#13145"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/albertodonato/prometheus-aioexporter/blob/e1b85544ce72bfaae9182597709a2ecede8c8242/prometheus_aioexporter/metric.py#L90-L98", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:albertodonato-prometheus-aioexporter:MetricsRegistry.get_metric-8b0647f5c6", "question": "Return a metric, optionally configured with labels.", "scope": {"holder": "albertodonato-prometheus-aioexporter", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:albertodonato/prometheus-aioexporter:prometheus_aioexporter/web.py:PrometheusExporter.run#13146", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "prometheus_aioexporter/web.py", "symbol": "PrometheusExporter.run"}, "source_id": "csn:albertodonato/prometheus-aioexporter:prometheus_aioexporter/web.py:PrometheusExporter.run#13146"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/albertodonato/prometheus-aioexporter/blob/e1b85544ce72bfaae9182597709a2ecede8c8242/prometheus_aioexporter/web.py#L62-L69", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:albertodonato-prometheus-aioexporter:PrometheusExporter.run-d9aa6a76e1", "question": "Run the :class:`aiohttp.web.Application` for the exporter.", "scope": {"holder": "albertodonato-prometheus-aioexporter", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:alexprengere/currencyconverter:currency_converter/currency_converter.py:CurrencyConverter._compute_missing_rates#9812", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "currency_converter/currency_converter.py", "symbol": "CurrencyConverter._compute_missing_rates"}, "source_id": "csn:alexprengere/currencyconverter:currency_converter/currency_converter.py:CurrencyConverter._compute_missing_rates#9812"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/alexprengere/currencyconverter/blob/e3cb0d693819c0c824214225b23a47e9380f71df/currency_converter/currency_converter.py#L208-L243", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:alexprengere-currencyconverter:CurrencyConverter._compute_missing_rates-081daef234", "question": "Fill missing rates of a currency.\n\n This is done by linear interpolation of the two closest available rates.\n\n :param str currency: The currency to fill missing rates for.", "scope": {"holder": "alexprengere-currencyconverter", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:alexprengere/currencyconverter:currency_converter/currency_converter.py:CurrencyConverter.load_file#9810", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "currency_converter/currency_converter.py", "symbol": "CurrencyConverter.load_file"}, "source_id": "csn:alexprengere/currencyconverter:currency_converter/currency_converter.py:CurrencyConverter.load_file#9810"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/alexprengere/currencyconverter/blob/e3cb0d693819c0c824214225b23a47e9380f71df/currency_converter/currency_converter.py#L147-L159", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:alexprengere-currencyconverter:CurrencyConverter.load_file-76b02cbd01", "question": "To be subclassed if alternate methods of loading data.", "scope": {"holder": "alexprengere-currencyconverter", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:alexseitsinger/find_best_string:src/find_best_string/main.py:find_best_string#22076", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "src/find_best_string/main.py", "symbol": "find_best_string"}, "source_id": "csn:alexseitsinger/find_best_string:src/find_best_string/main.py:find_best_string#22076"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/alexseitsinger/find_best_string/blob/833499113d9c560c91fe4761921a4d5717939ae7/src/find_best_string/main.py#L8-L101", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:alexseitsinger-find_best_string:find_best_string-5e1d107244", "question": "Return best matching substring of corpus.\n\n Parameters\n ----------\n query : str\n corpus : str\n step : int\n Step size of first match-value scan through corpus. Can be thought of\n as a sort of \"scan resolution\". Should not exceed length of query.\n flex : int\n Max. left/right substring position adjustment value. Should not\n exceed length of query / 2.\n\n Outputs\n -------\n output0 : str\n Best matching substring.\n output1 : float\n Match ratio of best matching substring. 1 is perfect match.", "scope": {"holder": "alexseitsinger-find_best_string", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:alghafli/fileslice:fileslice.py:FileSlice.read#20947", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "fileslice.py", "symbol": "FileSlice.read"}, "source_id": "csn:alghafli/fileslice:fileslice.py:FileSlice.read#20947"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/alghafli/fileslice/blob/ada4cb2a1bb78a3d7f7b43fc81f6a1921f8d41c2/fileslice.py#L192-L208", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:alghafli-fileslice:FileSlice.read-83de3bc978", "question": "Same as `file.read()` but for the slice. Does not read beyond\r\n `self.end`.", "scope": {"holder": "alghafli-fileslice", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:alghafli/fileslice:fileslice.py:FileSlice.write#20948", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "fileslice.py", "symbol": "FileSlice.write"}, "source_id": "csn:alghafli/fileslice:fileslice.py:FileSlice.write#20948"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/alghafli/fileslice/blob/ada4cb2a1bb78a3d7f7b43fc81f6a1921f8d41c2/fileslice.py#L210-L228", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:alghafli-fileslice:FileSlice.write-427915b4a2", "question": "Same as `file.write()` but for the slice.\r\n \r\n raises:\r\n EOFError if the new seek position is > `self.size`.", "scope": {"holder": "alghafli-fileslice", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:algofairness/BlackBoxAuditing:python2_source/BlackBoxAuditing/measurements.py:BCR#9437", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "python2_source/BlackBoxAuditing/measurements.py", "symbol": "BCR"}, "source_id": "csn:algofairness/BlackBoxAuditing:python2_source/BlackBoxAuditing/measurements.py:BCR#9437"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/algofairness/BlackBoxAuditing/blob/b06c4faed5591cd7088475b2a203127bc5820483/python2_source/BlackBoxAuditing/measurements.py#L14-L30", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:algofairness-BlackBoxAuditing:BCR-85fc417701", "question": "Given a confusion matrix, returns Balanced Classification Rate.\n BCR is (1 - Balanced Error Rate).\n BER Definition: http://research.ics.aalto.fi/events/eyechallenge2005/evaluation.shtml", "scope": {"holder": "algofairness-BlackBoxAuditing", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:algofairness/BlackBoxAuditing:BlackBoxAuditing/repairers/calculators.py:get_median#9438", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "BlackBoxAuditing/repairers/calculators.py", "symbol": "get_median"}, "source_id": "csn:algofairness/BlackBoxAuditing:BlackBoxAuditing/repairers/calculators.py:get_median#9438"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/algofairness/BlackBoxAuditing/blob/b06c4faed5591cd7088475b2a203127bc5820483/BlackBoxAuditing/repairers/calculators.py#L3-L24", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:algofairness-BlackBoxAuditing:get_median-9cfaeedf31", "question": "Given an unsorted list of numeric values, return median value (as a float).\n Note that in the case of even-length lists of values, we apply the value to\n the left of the center to be the median (such that the median can only be\n a value from the list of values).\n Eg: get_median([1,2,3,4]) == 2, not 2.5.", "scope": {"holder": "algofairness-BlackBoxAuditing", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:alimuldal/PyFNND:pyfnnd/demo.py:make_fake_movie#17655", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pyfnnd/demo.py", "symbol": "make_fake_movie"}, "source_id": "csn:alimuldal/PyFNND:pyfnnd/demo.py:make_fake_movie#17655"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/alimuldal/PyFNND/blob/3cbe0622a385f5206837bfd944d781aa7b1649ea/pyfnnd/demo.py#L8-L73", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:alimuldal-PyFNND:make_fake_movie-368566c8b6", "question": "Generate 2D fake fluorescence movie\n\n Arguments:\n ---------------------------------------------------------------------------\n nframes: number of timebins to simulate\n mask_shape: tuple (nrows, ncols), shape of a single movie frame\n mask_center: tuple (x, y), pixel coords of cell center\n bg_intensity: scalar, amplitude of (static) baseline fluorescence\n mask_sigma: scalar, standard deviation of Gaussian mask\n dt: timestep (s)\n rate: mean spike rate (Hz)\n tau: time constant of decay in calcium concentration (s)\n sigma: SD of additive noise on fluorescence\n seed: Seed for RNG\n\n Returns:\n ---------------------------------------------------------------------------\n F: fluorescence [npixels, nframes]\n c: calcium concentration [nframes,]\n n: spike train [nframes,]\n theta: tuple of true model parameters:\n (sigma, alpha, beta, lambda, gamma)", "scope": {"holder": "alimuldal-PyFNND", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:alimuldal/PyFNND:pyfnnd/utils.py:s2h#17660", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pyfnnd/utils.py", "symbol": "s2h"}, "source_id": "csn:alimuldal/PyFNND:pyfnnd/utils.py:s2h#17660"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/alimuldal/PyFNND/blob/3cbe0622a385f5206837bfd944d781aa7b1649ea/pyfnnd/utils.py#L24-L34", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:alimuldal-PyFNND:s2h-f4ca2d684a", "question": "convert seconds to a pretty \"d hh:mm:ss.s\" format", "scope": {"holder": "alimuldal-PyFNND", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:allanlei/django-argparse-command:argcmd/management/base.py:BaseCommand.create_parser#20599", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "argcmd/management/base.py", "symbol": "BaseCommand.create_parser"}, "source_id": "csn:allanlei/django-argparse-command:argcmd/management/base.py:BaseCommand.create_parser#20599"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/allanlei/django-argparse-command/blob/27ea77e1dd0cf2f0567223735762a5ebd14fdaef/argcmd/management/base.py#L46-L61", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:allanlei-django-argparse-command:BaseCommand.create_parser-e2a6343a44", "question": "Create and return the ``ArgumentParser`` which will be used to\n parse the arguments to this command.", "scope": {"holder": "allanlei-django-argparse-command", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:alpacahq/alpaca-trade-api-python:alpaca_trade_api/rest.py:REST._one_request#4543", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "alpaca_trade_api/rest.py", "symbol": "REST._one_request"}, "source_id": "csn:alpacahq/alpaca-trade-api-python:alpaca_trade_api/rest.py:REST._one_request#4543"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/alpacahq/alpaca-trade-api-python/blob/9c9dea3b4a37c909f88391b202e86ff356a8b4d7/alpaca_trade_api/rest.py#L111-L134", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:alpacahq-alpaca-trade-api-python:REST._one_request-589595b454", "question": "Perform one request, possibly raising RetryException in the case\n the response is 429. Otherwise, if error text contain \"code\" string,\n then it decodes to json object and returns APIError.\n Returns the body json in the 200 status.", "scope": {"holder": "alpacahq-alpaca-trade-api-python", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:alpacahq/alpaca-trade-api-python:alpaca_trade_api/rest.py:REST.list_orders#4544", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "alpaca_trade_api/rest.py", "symbol": "REST.list_orders"}, "source_id": "csn:alpacahq/alpaca-trade-api-python:alpaca_trade_api/rest.py:REST.list_orders#4544"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/alpacahq/alpaca-trade-api-python/blob/9c9dea3b4a37c909f88391b202e86ff356a8b4d7/alpaca_trade_api/rest.py#L154-L173", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:alpacahq-alpaca-trade-api-python:REST.list_orders-e106d6c3de", "question": "Get a list of orders\n https://docs.alpaca.markets/web-api/orders/#get-a-list-of-orders", "scope": {"holder": "alpacahq-alpaca-trade-api-python", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:ambitioninc/python-logentries-api:logentries_api/resources.py:Alerts.get#18163", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "logentries_api/resources.py", "symbol": "Alerts.get"}, "source_id": "csn:ambitioninc/python-logentries-api:logentries_api/resources.py:Alerts.get#18163"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/ambitioninc/python-logentries-api/blob/77ff1a7a2995d7ea2725b74e34c0f880f4ee23bc/logentries_api/resources.py#L560-L591", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:ambitioninc-python-logentries-api:Alerts.get-a73e1ec293", "question": "Get alerts that match the alert type and args.\n\n :param alert_type: The type of the alert. Must be one of 'pagerduty',\n 'mailto', 'webhook', 'slack', or 'hipchat'\n :type alert_type: str\n\n :param alert_args: The args for the alert. The provided args must be a\n subset of the actual alert args. If no args are provided, all\n alerts matching the ``alert_type`` are returned. For example:\n ``.get('mailto', alert_args={'direct': 'me@mydomain.com'})`` or\n ``.get('slack', {'url': 'https://hooks.slack.com/services...'})``\n\n :return: A list of matching alerts. An empty list is returned if there\n are not any matches\n :rtype: list of dict\n\n :raises: This will raise a\n :class:`ServerException<logentries_api.exceptions.ServerException>`\n if there is an error from Logentries", "scope": {"holder": "ambitioninc-python-logentries-api", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:ambitioninc/python-logentries-api:logentries_api/resources.py:Labels.update#18153", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "logentries_api/resources.py", "symbol": "Labels.update"}, "source_id": "csn:ambitioninc/python-logentries-api:logentries_api/resources.py:Labels.update#18153"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/ambitioninc/python-logentries-api/blob/77ff1a7a2995d7ea2725b74e34c0f880f4ee23bc/logentries_api/resources.py#L151-L192", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:ambitioninc-python-logentries-api:Labels.update-84d27ebdcf", "question": "Update a Label\n\n :param label: The data to update. Must include keys:\n\n * id (str)\n * appearance (dict)\n * description (str)\n * name (str)\n * title (str)\n :type label: dict\n\n Example:\n\n .. code-block:: python\n\n Labels().update(\n label={\n 'id': 'd9d4596e-49e4-4135-b3b3-847f9e7c1f43',\n 'appearance': {'color': '278abe'},\n 'name': 'My Sandbox',\n 'description': 'My Sandbox',\n 'title': 'My Sandbox',\n }\n )\n\n :return:\n :rtype: dict", "scope": {"holder": "ambitioninc-python-logentries-api", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:amcat/progressmonitor:progressmonitor/__init__.py:ProgressMonitor.begin#20822", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "progressmonitor/__init__.py", "symbol": "ProgressMonitor.begin"}, "source_id": "csn:amcat/progressmonitor:progressmonitor/__init__.py:ProgressMonitor.begin#20822"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/amcat/progressmonitor/blob/d4cabebc95bfd1447120f601c094b20bee954285/progressmonitor/__init__.py#L72-L77", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:amcat-progressmonitor:ProgressMonitor.begin-cfa7b1e9b1", "question": "Call before starting work on a monitor, specifying name and amount of work", "scope": {"holder": "amcat-progressmonitor", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:amcat/progressmonitor:progressmonitor/__init__.py:ProgressMonitor.task#20823", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "progressmonitor/__init__.py", "symbol": "ProgressMonitor.task"}, "source_id": "csn:amcat/progressmonitor:progressmonitor/__init__.py:ProgressMonitor.task#20823"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/amcat/progressmonitor/blob/d4cabebc95bfd1447120f601c094b20bee954285/progressmonitor/__init__.py#L80-L86", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:amcat-progressmonitor:ProgressMonitor.task-878e65b887", "question": "Wrap code into a begin and end call on this monitor", "scope": {"holder": "amcat-progressmonitor", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:amelchio/eternalegypt:eternalegypt/eternalegypt.py:autologin#14823", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "eternalegypt/eternalegypt.py", "symbol": "autologin"}, "source_id": "csn:amelchio/eternalegypt:eternalegypt/eternalegypt.py:autologin#14823"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/amelchio/eternalegypt/blob/895e0b235ceaf7f61458c620237c3ad397780e98/eternalegypt/eternalegypt.py#L52-L71", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:amelchio-eternalegypt:autologin-8452358fe5", "question": "Decorator that will try to login and redo an action before failing.", "scope": {"holder": "amelchio-eternalegypt", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:amelchio/eternalegypt:examples/status.py:get_information#14826", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "examples/status.py", "symbol": "get_information"}, "source_id": "csn:amelchio/eternalegypt:examples/status.py:get_information#14826"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/amelchio/eternalegypt/blob/895e0b235ceaf7f61458c620237c3ad397780e98/examples/status.py#L11-L41", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:amelchio-eternalegypt:get_information-b336a13310", "question": "Example of printing the current upstream.", "scope": {"holder": "amelchio-eternalegypt", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:amorison/loam:loam/cli.py:CLIManager._add_options_to_parser#19295", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "loam/cli.py", "symbol": "CLIManager._add_options_to_parser"}, "source_id": "csn:amorison/loam:loam/cli.py:CLIManager._add_options_to_parser#19295"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/amorison/loam/blob/a566c943a75e068a4510099331a1ddfe5bbbdd94/loam/cli.py#L141-L154", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:amorison-loam:CLIManager._add_options_to_parser-7a1b874349", "question": "Add options to a parser.", "scope": {"holder": "amorison-loam", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:amorison/loam:loam/manager.py:ConfigurationManager.read_configs_#19290", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "loam/manager.py", "symbol": "ConfigurationManager.read_configs_"}, "source_id": "csn:amorison/loam:loam/manager.py:ConfigurationManager.read_configs_#19290"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/amorison/loam/blob/a566c943a75e068a4510099331a1ddfe5bbbdd94/loam/manager.py#L366-L389", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:amorison-loam:ConfigurationManager.read_configs_-26ed94d364", "question": "Read config files and set config values accordingly.\n\n Returns:\n (dict, list, list): respectively content of files, list of\n missing/empty files and list of files for which a parsing error\n arised.", "scope": {"holder": "amorison-loam", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:amyth/django-instapush:instapush/models/base.py:GCMDevice.send_message#17148", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "instapush/models/base.py", "symbol": "GCMDevice.send_message"}, "source_id": "csn:amyth/django-instapush:instapush/models/base.py:GCMDevice.send_message#17148"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/amyth/django-instapush/blob/f8643a2e342fc73a16c95dff79c3daac8ce4b034/instapush/models/base.py#L63-L74", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:amyth-django-instapush:GCMDevice.send_message-3d6e50b667", "question": "Sends a push notification to this device via GCM", "scope": {"holder": "amyth-django-instapush", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:amyth/django-instapush:instapush/libs/apns.py:apns_fetch_inactive_ids#17150", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "instapush/libs/apns.py", "symbol": "apns_fetch_inactive_ids"}, "source_id": "csn:amyth/django-instapush:instapush/libs/apns.py:apns_fetch_inactive_ids#17150"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/amyth/django-instapush/blob/f8643a2e342fc73a16c95dff79c3daac8ce4b034/instapush/libs/apns.py#L245-L256", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:amyth-django-instapush:apns_fetch_inactive_ids-5129563f34", "question": "Queries the APNS server for id's that are no longer active since\n the last fetch", "scope": {"holder": "amyth-django-instapush", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:analytehealth/django-analytics:djanalytics/reports/utils.py:average_duration#15386", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "djanalytics/reports/utils.py", "symbol": "average_duration"}, "source_id": "csn:analytehealth/django-analytics:djanalytics/reports/utils.py:average_duration#15386"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/analytehealth/django-analytics/blob/7782d3f81249dcb1b266afb0cb1e90000108c74d/djanalytics/reports/utils.py#L12-L19", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:analytehealth-django-analytics:average_duration-39aa544068", "question": "Method to calculate and format an average duration safely", "scope": {"holder": "analytehealth-django-analytics", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:andrefsp/pyflot:flot/__init__.py:Graph._get_axis_mode#18903", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "flot/__init__.py", "symbol": "Graph._get_axis_mode"}, "source_id": "csn:andrefsp/pyflot:flot/__init__.py:Graph._get_axis_mode#18903"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/andrefsp/pyflot/blob/f2dde10709aeed39074fcce8172184b5cd8bfd66/flot/__init__.py#L266-L270", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:andrefsp-pyflot:Graph._get_axis_mode-9f2273e610", "question": "will get the axis mode for the current series", "scope": {"holder": "andrefsp-pyflot", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:andrefsp/pyflot:flot/__init__.py:Series._set_data#18902", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "flot/__init__.py", "symbol": "Series._set_data"}, "source_id": "csn:andrefsp/pyflot:flot/__init__.py:Series._set_data#18902"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/andrefsp/pyflot/blob/f2dde10709aeed39074fcce8172184b5cd8bfd66/flot/__init__.py#L168-L186", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:andrefsp-pyflot:Series._set_data-5b2c4c6aa9", "question": "This method will be called to set Series data", "scope": {"holder": "andrefsp-pyflot", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:andreikop/python-ws-discovery:wsdiscovery/daemon.py:NetworkingThread.addSourceAddr#7517", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "wsdiscovery/daemon.py", "symbol": "NetworkingThread.addSourceAddr"}, "source_id": "csn:andreikop/python-ws-discovery:wsdiscovery/daemon.py:NetworkingThread.addSourceAddr#7517"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/andreikop/python-ws-discovery/blob/a7b852cf43115c6f986e509b1870d6963e76687f/wsdiscovery/daemon.py#L126-L135", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:andreikop-python-ws-discovery:NetworkingThread.addSourceAddr-0557345ca7", "question": "None means 'system default", "scope": {"holder": "andreikop-python-ws-discovery", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:andreikop/python-ws-discovery:wsdiscovery/daemon.py:WSDiscovery.setRemoteServiceHelloCallback#7519", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "wsdiscovery/daemon.py", "symbol": "WSDiscovery.setRemoteServiceHelloCallback"}, "source_id": "csn:andreikop/python-ws-discovery:wsdiscovery/daemon.py:WSDiscovery.setRemoteServiceHelloCallback#7519"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/andreikop/python-ws-discovery/blob/a7b852cf43115c6f986e509b1870d6963e76687f/wsdiscovery/daemon.py#L291-L303", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:andreikop-python-ws-discovery:WSDiscovery.setRemoteServiceHelloCallback-f84704e6fc", "question": "Set callback, which will be called when new service appeared online\n and sent Hi message\n\n typesFilter and scopesFilter might be list of types and scopes.\n If filter is set, callback is called only for Hello messages,\n which match filter\n\n Set None to disable callback", "scope": {"holder": "andreikop-python-ws-discovery", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:anentropic/dirtyebay:dirtyebay/utils.py:_default_ns_prefix#21865", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "dirtyebay/utils.py", "symbol": "_default_ns_prefix"}, "source_id": "csn:anentropic/dirtyebay:dirtyebay/utils.py:_default_ns_prefix#21865"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/anentropic/dirtyebay/blob/c3194932360445563cfe0c7e034e41f09358c7eb/dirtyebay/utils.py#L60-L90", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:anentropic-dirtyebay:_default_ns_prefix-4d1afb181a", "question": "XML doc may have several prefix:namespace_url pairs, can also specify\n a namespace_url as default, tags in that namespace don't need a prefix\n NOTE:\n we rely on default namespace also present in prefixed form, I'm not sure if\n this is an XML certainty or a quirk of the eBay WSDLs\n\n in our case the WSDL contains:\n <wsdl:documentation>\n <Version>1.0.0</Version>\n </wsdl:documentation>\n ...but our query needs to give a prefix to the path of `Version` so we need\n to determine the default namespace of the doc, find the matching prefix and\n return it", "scope": {"holder": "anentropic-dirtyebay", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:anentropic/dirtyebay:dirtyebay/utils.py:version_from_schema#21864", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "dirtyebay/utils.py", "symbol": "version_from_schema"}, "source_id": "csn:anentropic/dirtyebay:dirtyebay/utils.py:version_from_schema#21864"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/anentropic/dirtyebay/blob/c3194932360445563cfe0c7e034e41f09358c7eb/dirtyebay/utils.py#L36-L57", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:anentropic-dirtyebay:version_from_schema-fadf23a2d9", "question": "returns: API version number <str>\n raises: <VersionNotFound>\n\n NOTE:\n relies on presence of comment tags in the XSD, which are currently present\n for both ebaySvc.xsd (TradingAPI) and ShoppingService.xsd (ShoppingAPI)", "scope": {"holder": "anentropic-dirtyebay", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:ankitmathur3193/song-cli:song/commands/SearchEngineParser/GoogleParser.py:GoogleParser.Parse#17683", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "song/commands/SearchEngineParser/GoogleParser.py", "symbol": "GoogleParser.Parse"}, "source_id": "csn:ankitmathur3193/song-cli:song/commands/SearchEngineParser/GoogleParser.py:GoogleParser.Parse#17683"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/ankitmathur3193/song-cli/blob/ca8ccfe547e9d702313ff6d14e81ae4355989a67/song/commands/SearchEngineParser/GoogleParser.py#L33-L43", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:ankitmathur3193-song-cli:GoogleParser.Parse-2b9e9ab31a", "question": "song_name is a list of strings\n\t\twebsite is a string\n\t\tIt will return the url from where music file needs to be downloaded", "scope": {"holder": "ankitmathur3193-song-cli", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:ankitmathur3193/song-cli:song/commands/SearchEngineParser/GoogleParser.py:GoogleParser.parse_google#17682", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "song/commands/SearchEngineParser/GoogleParser.py", "symbol": "GoogleParser.parse_google"}, "source_id": "csn:ankitmathur3193/song-cli:song/commands/SearchEngineParser/GoogleParser.py:GoogleParser.parse_google#17682"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/ankitmathur3193/song-cli/blob/ca8ccfe547e9d702313ff6d14e81ae4355989a67/song/commands/SearchEngineParser/GoogleParser.py#L20-L30", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:ankitmathur3193-song-cli:GoogleParser.parse_google-a0ecf6cb30", "question": "It will parse google html response\n\t\t\tand return the first url", "scope": {"holder": "ankitmathur3193-song-cli", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:ansible/ansible-lint:lib/ansiblelint/utils.py:normalize_task_v2#3564", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "lib/ansiblelint/utils.py", "symbol": "normalize_task_v2"}, "source_id": "csn:ansible/ansible-lint:lib/ansiblelint/utils.py:normalize_task_v2#3564"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/ansible/ansible-lint/blob/b4a8743794e592698c32e760bc774a85f8eebeb5/lib/ansiblelint/utils.py#L368-L416", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:ansible-ansible-lint:normalize_task_v2-9eb0c41b8f", "question": "Ensures tasks have an action key and strings are converted to python objects", "scope": {"holder": "ansible-ansible-lint", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:ansible/ansible-lint:lib/ansiblelint/utils.py:parse_yaml_linenumbers#3565", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "lib/ansiblelint/utils.py", "symbol": "parse_yaml_linenumbers"}, "source_id": "csn:ansible/ansible-lint:lib/ansiblelint/utils.py:parse_yaml_linenumbers#3565"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/ansible/ansible-lint/blob/b4a8743794e592698c32e760bc774a85f8eebeb5/lib/ansiblelint/utils.py#L546-L585", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:ansible-ansible-lint:parse_yaml_linenumbers-344302e324", "question": "Parses yaml as ansible.utils.parse_yaml but with linenumbers.\n\n The line numbers are stored in each node's LINE_NUMBER_KEY key.", "scope": {"holder": "ansible-ansible-lint", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:antevens/listen:listen/signal_handler.py:SignalHandler._unreg_event#16617", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "listen/signal_handler.py", "symbol": "SignalHandler._unreg_event"}, "source_id": "csn:antevens/listen:listen/signal_handler.py:SignalHandler._unreg_event#16617"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/antevens/listen/blob/d3ddff8e7fbfb672c5bd7f6f4febeb5e921d8c67/listen/signal_handler.py#L190-L204", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:antevens-listen:SignalHandler._unreg_event-f112f63ce1", "question": "Tries to remove a registered event without triggering it", "scope": {"holder": "antevens-listen", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:antevens/listen:listen/signal_handler.py:SignalHandler.reg_on_abort#16619", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "listen/signal_handler.py", "symbol": "SignalHandler.reg_on_abort"}, "source_id": "csn:antevens/listen:listen/signal_handler.py:SignalHandler.reg_on_abort#16619"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/antevens/listen/blob/d3ddff8e7fbfb672c5bd7f6f4febeb5e921d8c67/listen/signal_handler.py#L240-L245", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:antevens-listen:SignalHandler.reg_on_abort-a58a5bab8c", "question": "Register a function/method to be called when execution is aborted", "scope": {"holder": "antevens-listen", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:apache/airflow:airflow/contrib/hooks/aws_athena_hook.py:AWSAthenaHook.check_query_status#651", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "airflow/contrib/hooks/aws_athena_hook.py", "symbol": "AWSAthenaHook.check_query_status"}, "source_id": "csn:apache/airflow:airflow/contrib/hooks/aws_athena_hook.py:AWSAthenaHook.check_query_status#651"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/hooks/aws_athena_hook.py#L74-L89", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:AWSAthenaHook.check_query_status-d861e509da", "question": "Fetch the status of submitted athena query. Returns None or one of valid query states.\n\n :param query_execution_id: Id of submitted athena query\n :type query_execution_id: str\n :return: str", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:apache/airflow:airflow/contrib/sensors/imap_attachment_sensor.py:ImapAttachmentSensor.poke#753", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "airflow/contrib/sensors/imap_attachment_sensor.py", "symbol": "ImapAttachmentSensor.poke"}, "source_id": "csn:apache/airflow:airflow/contrib/sensors/imap_attachment_sensor.py:ImapAttachmentSensor.poke#753"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/sensors/imap_attachment_sensor.py#L60-L76", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:ImapAttachmentSensor.poke-f96f856db6", "question": "Pokes for a mail attachment on the mail server.\n\n :param context: The context that is being provided when poking.\n :type context: dict\n :return: True if attachment with the given name is present and False if not.\n :rtype: bool", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:appier/h5sparse:h5sparse/h5sparse.py:Group.create_dataset#12251", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "h5sparse/h5sparse.py", "symbol": "Group.create_dataset"}, "source_id": "csn:appier/h5sparse:h5sparse/h5sparse.py:Group.create_dataset#12251"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/appier/h5sparse/blob/b12ee65c624207d3020c283ce561cfcc7ab71731/h5sparse/h5sparse.py#L46-L94", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:appier-h5sparse:Group.create_dataset-ae16f3f8f4", "question": "Create 3 datasets in a group to represent the sparse array.\n\n Parameters\n ----------\n sparse_format:", "scope": {"holder": "appier-h5sparse", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:appknox/google-chartwrapper:GChartWrapper/GChart.py:Axes.label#19516", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "GChartWrapper/GChart.py", "symbol": "Axes.label"}, "source_id": "csn:appknox/google-chartwrapper:GChartWrapper/GChart.py:Axes.label#19516"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/appknox/google-chartwrapper/blob/3769aecbef6c83b6cd93ee72ece478ffe433ac57/GChartWrapper/GChart.py#L122-L131", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:appknox-google-chartwrapper:Axes.label-470acef192", "question": "Label each axes one at a time\n args are of the form <label 1>,...,<label n>\n APIPARAM: chxl", "scope": {"holder": "appknox-google-chartwrapper", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:appknox/google-chartwrapper:GChartWrapper/GChart.py:GChart.img#19539", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "GChartWrapper/GChart.py", "symbol": "GChart.img"}, "source_id": "csn:appknox/google-chartwrapper:GChartWrapper/GChart.py:GChart.img#19539"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/appknox/google-chartwrapper/blob/3769aecbef6c83b6cd93ee72ece478ffe433ac57/GChartWrapper/GChart.py#L584-L597", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:appknox-google-chartwrapper:GChart.img-a22f60f497", "question": "Returns an XHTML <img/> tag of the chart\n\n kwargs can be other img tag attributes, which are strictly enforced\n uses strict escaping on the url, necessary for proper XHTML", "scope": {"holder": "appknox-google-chartwrapper", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:arlyon/hyperion:hyperion/models/bike.py:Bike.get_most_recent_bike#20039", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "hyperion/models/bike.py", "symbol": "Bike.get_most_recent_bike"}, "source_id": "csn:arlyon/hyperion:hyperion/models/bike.py:Bike.get_most_recent_bike#20039"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/arlyon/hyperion/blob/d8de0388ba98b85ce472e0f49ac18fecb14d3343/hyperion/models/bike.py#L29-L37", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:arlyon-hyperion:Bike.get_most_recent_bike-361f12d444", "question": "Gets the most recently cached bike from the database.\n :return: The bike that was cached most recently.", "scope": {"holder": "arlyon-hyperion", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:arlyon/hyperion:hyperion/fetch/police.py:fetch_neighbourhood#20062", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "hyperion/fetch/police.py", "symbol": "fetch_neighbourhood"}, "source_id": "csn:arlyon/hyperion:hyperion/fetch/police.py:fetch_neighbourhood#20062"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/arlyon/hyperion/blob/d8de0388ba98b85ce472e0f49ac18fecb14d3343/hyperion/fetch/police.py#L15-L49", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:arlyon-hyperion:fetch_neighbourhood-2947bdb4c6", "question": "Gets the neighbourhood from the fetch that is associated with the given postcode.\n :return: A neighbourhood object parsed from the fetch.\n :raise ApiError: When there was an error connecting to the API.", "scope": {"holder": "arlyon-hyperion", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:arve0/microscopestitching:microscopestitching/stitching.py:_add_ones_dim#18693", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "microscopestitching/stitching.py", "symbol": "_add_ones_dim"}, "source_id": "csn:arve0/microscopestitching:microscopestitching/stitching.py:_add_ones_dim#18693"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/arve0/microscopestitching/blob/381a78a1d1dca711e1732193e09d6ff7dce23baa/microscopestitching/stitching.py#L196-L199", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:arve0-microscopestitching:_add_ones_dim-ba85d34787", "question": "Adds a dimensions with ones to array.", "scope": {"holder": "arve0-microscopestitching", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:arve0/microscopestitching:microscopestitching/stitching.py:stitch#18692", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "microscopestitching/stitching.py", "symbol": "stitch"}, "source_id": "csn:arve0/microscopestitching:microscopestitching/stitching.py:stitch#18692"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/arve0/microscopestitching/blob/381a78a1d1dca711e1732193e09d6ff7dce23baa/microscopestitching/stitching.py#L40-L84", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:arve0-microscopestitching:stitch-12c812958c", "question": "Stitch regular spaced images.\n\n Parameters\n ----------\n images : ImageCollection or list of tuple(path, row, column)\n Each image-tuple should contain path, row and column. Row 0,\n column 0 is top left image.\n\n Example:\n >>> images = [('1.png', 0, 0), ('2.png', 0, 1)]\n\n Returns\n -------\n tuple (stitched, offset)\n Stitched image and registered offset (y, x).", "scope": {"holder": "arve0-microscopestitching", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:asciimoo/searx:searx/webapp.py:autocompleter#903", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "searx/webapp.py", "symbol": "autocompleter"}, "source_id": "csn:asciimoo/searx:searx/webapp.py:autocompleter#903"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/asciimoo/searx/blob/a84caa22cf947e973c10aa968d35fb2bdda6d048/searx/webapp.py#L616-L664", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:asciimoo-searx:autocompleter-1932e8078e", "question": "Return autocompleter results", "scope": {"holder": "asciimoo-searx", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:asciimoo/searx:searx/poolrequests.py:request#900", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "searx/poolrequests.py", "symbol": "request"}, "source_id": "csn:asciimoo/searx:searx/poolrequests.py:request#900"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/asciimoo/searx/blob/a84caa22cf947e973c10aa968d35fb2bdda6d048/searx/poolrequests.py#L90-L128", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:asciimoo-searx:request-349e94ad96", "question": "same as requests/requests/api.py request(...)", "scope": {"holder": "asciimoo-searx", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:ashleysommer/sanic-cors:sanic_cors/decorator.py:cross_origin#9368", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "sanic_cors/decorator.py", "symbol": "cross_origin"}, "source_id": "csn:ashleysommer/sanic-cors:sanic_cors/decorator.py:cross_origin#9368"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/ashleysommer/sanic-cors/blob/f3d68def8cf859398b3c83e4109d815f1f038ea2/sanic_cors/decorator.py#L18-L120", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:ashleysommer-sanic-cors:cross_origin-771910c1d8", "question": "This function is the decorator which is used to wrap a Sanic route with.\n In the simplest case, simply use the default parameters to allow all\n origins in what is the most permissive configuration. If this method\n modifies state or performs authentication which may be brute-forced, you\n should add some degree of protection, such as Cross Site Forgery\n Request protection.\n\n :param origins:\n The origin, or list of origins to allow requests from.\n The origin(s) may be regular expressions, case-sensitive strings,\n or else an asterisk\n\n Default : '*'\n :type origins: list, string or regex\n\n :param methods:\n The method or list of methods which the allowed origins are allowed to\n access for non-simple requests.\n\n Default : [GET, HEAD, POST, OPTIONS, PUT, PATCH, DELETE]\n :type methods: list or string\n\n :param expose_headers:\n The header or list which are safe to expose to the API of a CORS API\n specification.\n\n Default : None\n :type expose_headers: list or string\n\n :param allow_headers:\n The header or list of header field names which can be used when this\n resource is accessed by allowed origins. The header(s) may be regular\n expressions, case-sensitive strings, or else an asterisk.\n\n Default : '*', allow all headers\n :type allow_headers: list, string or regex\n\n :param supports_credentials:\n Allows users to make authenticated requests. If true, injects the\n `Access-Control-Allow-Credentials` header in responses. This allows\n cookies and credentials to be submitted across domains.\n\n :note: This option cannot be used in conjuction with a '*' origin\n\n Default : False\n :type supports_credentials: bool\n\n :param max_age:\n The maximum time for which this CORS request maybe cached. This value\n is set as the `Access-Control-Max-Age` header.\n\n Default : None\n :type max_age: timedelta, integer, string or None\n\n :param send_wildcard: If True, and the origins parameter is `*`, a wildcard\n `Access-Control-Allow-Origin` header is sent, rather than the\n request's `Origin` header.\n\n Default : False\n :type send_wildcard: bool\n\n :param vary_header:\n If True, the header Vary: Origin will be returned as per the W3\n implementation guidelines.\n\n Setting this header when the `Access-Control-Allow-Origin` is\n dynamically generated (e.g. when there is more than one allowed\n origin, and an Origin than '*' is returned) informs CDNs and other\n caches that the CORS headers are dynamic, and cannot be cached.\n\n If False, the Vary header will never be injected or altered.\n\n Default : True\n :type vary_header: bool\n\n :param automatic_options:\n Only applies to the `cross_origin` decorator. If True, Sanic-CORS will\n override Sanic's default OPTIONS handling to return CORS headers for\n OPTIONS requests.\n\n Default : True\n :type automatic_options: bool", "scope": {"holder": "ashleysommer-sanic-cors", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:ashleysommer/sanic-cors:sanic_cors/core.py:flexible_str#9371", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "sanic_cors/core.py", "symbol": "flexible_str"}, "source_id": "csn:ashleysommer/sanic-cors:sanic_cors/core.py:flexible_str#9371"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/ashleysommer/sanic-cors/blob/f3d68def8cf859398b3c83e4109d815f1f038ea2/sanic_cors/core.py#L329-L342", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:ashleysommer-sanic-cors:flexible_str-dd331c1f58", "question": "A more flexible str function which intelligently handles stringifying\n strings, lists and other iterables. The results are lexographically sorted\n to ensure generated responses are consistent when iterables such as Set\n are used.", "scope": {"holder": "ashleysommer-sanic-cors", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:assemblerflow/flowcraft:flowcraft/templates/process_abricate.py:Abricate._parser#10576", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "flowcraft/templates/process_abricate.py", "symbol": "Abricate._parser"}, "source_id": "csn:assemblerflow/flowcraft:flowcraft/templates/process_abricate.py:Abricate._parser#10576"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/assemblerflow/flowcraft/blob/fc3f4bddded1efc76006600016dc71a06dd908c0/flowcraft/templates/process_abricate.py#L152-L207", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:assemblerflow-flowcraft:Abricate._parser-61bae86f77", "question": "Parser for a single abricate output file.\n\n This parser will scan a single Abricate output file and populate\n the :py:attr:`Abricate.storage` attribute.\n\n Parameters\n ----------\n fl : str\n Path to abricate output file\n\n Notes\n -----\n This method will populate the :py:attr:`Abricate.storage` attribute\n with all compliant lines in the abricate output file. Entries are\n inserted using an arbitrary key that is set by the\n :py:attr:`Abricate._key` attribute.", "scope": {"holder": "assemblerflow-flowcraft", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:assemblerflow/flowcraft:flowcraft/generator/inspect.py:NextflowInspector._update_pipeline_status#10538", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "flowcraft/generator/inspect.py", "symbol": "NextflowInspector._update_pipeline_status"}, "source_id": "csn:assemblerflow/flowcraft:flowcraft/generator/inspect.py:NextflowInspector._update_pipeline_status#10538"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/assemblerflow/flowcraft/blob/fc3f4bddded1efc76006600016dc71a06dd908c0/flowcraft/generator/inspect.py#L477-L537", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:assemblerflow-flowcraft:NextflowInspector._update_pipeline_status-5470e7f438", "question": "Parses the .nextflow.log file for signatures of pipeline status.\n It sets the :attr:`status_info` attribute.", "scope": {"holder": "assemblerflow-flowcraft", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:astrofrog/numtraits:numtraits.py:assert_unit_convertability#19660", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "numtraits.py", "symbol": "assert_unit_convertability"}, "source_id": "csn:astrofrog/numtraits:numtraits.py:assert_unit_convertability#19660"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/astrofrog/numtraits/blob/d0afadc946e9d81d1d5b6c851530899d6b0e1d7c/numtraits.py#L201-L248", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:astrofrog-numtraits:assert_unit_convertability-ad49a13eb5", "question": "Check that a value has physical type consistent with user-specified units\n\n Note that this does not convert the value, only check that the units have\n the right physical dimensionality.\n\n Parameters\n ----------\n name : str\n The name of the value to check (used for error messages).\n value : `numpy.ndarray` or instance of `numpy.ndarray` subclass\n The value to check.\n target_unit : unit\n The unit that the value should be convertible to.\n unit_framework : str\n The unit framework to use", "scope": {"holder": "astrofrog-numtraits", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:astrofrog/numtraits:numtraits.py:identify_unit_framework#19659", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "numtraits.py", "symbol": "identify_unit_framework"}, "source_id": "csn:astrofrog/numtraits:numtraits.py:identify_unit_framework#19659"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/astrofrog/numtraits/blob/d0afadc946e9d81d1d5b6c851530899d6b0e1d7c/numtraits.py#L167-L198", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:astrofrog-numtraits:identify_unit_framework-f0550a49df", "question": "Identify whether the user is requesting unit validation against\n astropy.units, pint, or quantities.", "scope": {"holder": "astrofrog-numtraits", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:astrorafael/twisted-mqtt:mqtt/client/base.py:BaseState.handleCONNACK#14614", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "mqtt/client/base.py", "symbol": "BaseState.handleCONNACK"}, "source_id": "csn:astrorafael/twisted-mqtt:mqtt/client/base.py:BaseState.handleCONNACK#14614"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/astrorafael/twisted-mqtt/blob/5b322f7c2b82a502b1e1b70703ae45f1f668d07d/mqtt/client/base.py#L138-L143", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:astrorafael-twisted-mqtt:BaseState.handleCONNACK-8932de9c48", "question": "Handles CONNACK packet from the server", "scope": {"holder": "astrorafael-twisted-mqtt", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:astrorafael/twisted-mqtt:mqtt/pdu.py:PUBREL.decode#14633", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "mqtt/pdu.py", "symbol": "PUBREL.decode"}, "source_id": "csn:astrorafael/twisted-mqtt:mqtt/pdu.py:PUBREL.decode#14633"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/astrorafael/twisted-mqtt/blob/5b322f7c2b82a502b1e1b70703ae45f1f668d07d/mqtt/pdu.py#L651-L661", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:astrorafael-twisted-mqtt:PUBREL.decode-77d91e7eb9", "question": "Decode a PUBREL control packet.", "scope": {"holder": "astrorafael-twisted-mqtt", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:athre0z/wasm:wasm/decode.py:decode_bytecode#8581", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "wasm/decode.py", "symbol": "decode_bytecode"}, "source_id": "csn:athre0z/wasm:wasm/decode.py:decode_bytecode#8581"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/athre0z/wasm/blob/bc9c7e3f40242a2a8fc9650c4b994f0cddf8d755/wasm/decode.py#L14-L29", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:athre0z-wasm:decode_bytecode-b435477843", "question": "Decodes raw bytecode, yielding `Instruction`s.", "scope": {"holder": "athre0z-wasm", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:athre0z/wasm:wasm/compat.py:deprecated_func#8583", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "wasm/compat.py", "symbol": "deprecated_func"}, "source_id": "csn:athre0z/wasm:wasm/compat.py:deprecated_func#8583"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/athre0z/wasm/blob/bc9c7e3f40242a2a8fc9650c4b994f0cddf8d755/wasm/compat.py#L50-L67", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:athre0z-wasm:deprecated_func-47964f0adc", "question": "Deprecates a function, printing a warning on the first usage.", "scope": {"holder": "athre0z-wasm", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:atlassistant/pychatl:pychatl/parser.py:parse#19407", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pychatl/parser.py", "symbol": "parse"}, "source_id": "csn:atlassistant/pychatl:pychatl/parser.py:parse#19407"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/atlassistant/pychatl/blob/e2b5600c3183830be266f55fd110dc5e75a86e1c/pychatl/parser.py#L37-L54", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:atlassistant-pychatl:parse-a71a1849cc", "question": "Parses the given DSL string and returns parsed results.\n\n Args:\n input_string (str): DSL string\n prefix (str): Optional prefix to add to every element name, useful to namespace things\n\n Returns:\n dict: Parsed content", "scope": {"holder": "atlassistant-pychatl", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:attm2x/m2x-python:m2x/v2/collections.py:Collection.add_device#17200", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "m2x/v2/collections.py", "symbol": "Collection.add_device"}, "source_id": "csn:attm2x/m2x-python:m2x/v2/collections.py:Collection.add_device#17200"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/attm2x/m2x-python/blob/df83f590114692b1f96577148b7ba260065905bb/m2x/v2/collections.py#L28-L37", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:attm2x-m2x-python:Collection.add_device-e828ef858a", "question": "Method for `Add device to collection <https://m2x.att.com/developer/documentation/v2/collections#Add-device-to-collection>`_ endpoint.\n\n :param device_id: ID of the Device being added to Collection\n :type device_id: str\n\n :raises: :class:`~requests.exceptions.HTTPError` if an error occurs when sending the HTTP request", "scope": {"holder": "attm2x-m2x-python", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:attm2x/m2x-python:m2x/v2/devices.py:Device.update_stream#17203", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "m2x/v2/devices.py", "symbol": "Device.update_stream"}, "source_id": "csn:attm2x/m2x-python:m2x/v2/devices.py:Device.update_stream#17203"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/attm2x/m2x-python/blob/df83f590114692b1f96577148b7ba260065905bb/m2x/v2/devices.py#L50-L61", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:attm2x-m2x-python:Device.update_stream-21a5c33208", "question": "Method for `Create/Update Data Stream <https://m2x.att.com/developer/documentation/v2/device#Create-Update-Data-Stream>`_ endpoint.\n\n :param name: Name of the stream to be updated\n :param params: Query parameters passed as keyword arguments. View M2X API Docs for listing of available parameters.\n\n :return: The Stream being updated\n :rtype: Stream\n\n :raises: :class:`~requests.exceptions.HTTPError` if an error occurs when sending the HTTP request", "scope": {"holder": "attm2x-m2x-python", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:audiencepi/SimilarWeb-Python:similarweb/utils.py:domain_from_url#14588", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "similarweb/utils.py", "symbol": "domain_from_url"}, "source_id": "csn:audiencepi/SimilarWeb-Python:similarweb/utils.py:domain_from_url#14588"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/audiencepi/SimilarWeb-Python/blob/4bf5e2315815cb622bd64714573f8df29339e615/similarweb/utils.py#L5-L15", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:audiencepi-SimilarWeb-Python:domain_from_url-a83f4e40df", "question": "Get root domain from url.\n Will prune away query strings, url paths, protocol prefix and sub-domains\n Exceptions will be raised on invalid urls", "scope": {"holder": "audiencepi-SimilarWeb-Python", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:authomatic/authomatic:authomatic/core.py:Authomatic.access#9335", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "authomatic/core.py", "symbol": "Authomatic.access"}, "source_id": "csn:authomatic/authomatic:authomatic/core.py:Authomatic.access#9335"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/authomatic/authomatic/blob/90a9ce60cc405ae8a2bf5c3713acd5d78579a04e/authomatic/core.py#L1433-L1483", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:authomatic-authomatic:Authomatic.access-57e32d456f", "question": "Accesses **protected resource** on behalf of the **user**.\n\n :param credentials:\n The **user's** :class:`.Credentials` (serialized or normal).\n\n :param str url:\n The **protected resource** URL.\n\n :param str method:\n HTTP method of the request.\n\n :param dict headers:\n HTTP headers of the request.\n\n :param str body:\n Body of ``POST``, ``PUT`` and ``PATCH`` requests.\n\n :param int max_redirects:\n Maximum number of HTTP redirects to follow.\n\n :param function content_parser:\n A function to be used to parse the :attr:`.Response.data`\n from :attr:`.Response.content`.\n\n :returns:\n :class:`.Response`", "scope": {"holder": "authomatic-authomatic", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:authomatic/authomatic:authomatic/core.py:LoginResult.popup_js#9329", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "authomatic/core.py", "symbol": "LoginResult.popup_js"}, "source_id": "csn:authomatic/authomatic:authomatic/core.py:LoginResult.popup_js#9329"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/authomatic/authomatic/blob/90a9ce60cc405ae8a2bf5c3713acd5d78579a04e/authomatic/core.py#L943-L1004", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:authomatic-authomatic:LoginResult.popup_js-89114371e3", "question": "Returns JavaScript that:\n\n #. Triggers the ``options.onLoginComplete(result, closer)``\n handler set with the :ref:`authomatic.setup() <js_setup>`\n function of :ref:`javascript.js <js>`.\n #. Calls the JavasScript callback specified by :data:`callback_name`\n on the opener of the *login handler popup* and passes it the\n *login result* JSON object as first argument and the `closer`\n function which you should call in your callback to close the popup.\n\n :param str callback_name:\n The name of the javascript callback e.g ``foo.bar.loginCallback``\n will result in ``window.opener.foo.bar.loginCallback(result);``\n in the HTML.\n\n :param int indent:\n The number of spaces to indent the JSON result object.\n If ``0`` or negative, only newlines are added.\n If ``None``, no newlines are added.\n\n :param custom:\n Any JSON serializable object that will be passed to the\n ``result.custom`` attribute.\n\n :param str stay_open:\n If ``True``, the popup will stay open.\n\n :returns:\n :class:`str` with JavaScript.", "scope": {"holder": "authomatic-authomatic", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:avelino/bottle-auth:bottle_auth/__init__.py:AuthPlugin.setup#17277", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "bottle_auth/__init__.py", "symbol": "AuthPlugin.setup"}, "source_id": "csn:avelino/bottle-auth:bottle_auth/__init__.py:AuthPlugin.setup#17277"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/avelino/bottle-auth/blob/db07e526864aeac05ee68444b47e5db29540ce18/bottle_auth/__init__.py#L18-L27", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:avelino-bottle-auth:AuthPlugin.setup-a6b0692594", "question": "Make sure that other installed plugins don't affect the same\n keyword argument and check if metadata is available.", "scope": {"holder": "avelino-bottle-auth", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:avelino/bottle-auth:bottle_auth/core/httputil.py:HTTPHeaders.get_all#17269", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "bottle_auth/core/httputil.py", "symbol": "HTTPHeaders.get_all"}, "source_id": "csn:avelino/bottle-auth:bottle_auth/core/httputil.py:HTTPHeaders.get_all#17269"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/avelino/bottle-auth/blob/db07e526864aeac05ee68444b47e5db29540ce18/bottle_auth/core/httputil.py#L93-L101", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:avelino-bottle-auth:HTTPHeaders.get_all-96729f2211", "question": "Returns an iterable of all (name, value) pairs.\n\n If a header has multiple values, multiple pairs will be\n returned with the same name.", "scope": {"holder": "avelino-bottle-auth", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:awentzonline/keras-vgg-buddy:keras_vgg_buddy/models.py:VGG16.get_f_layer#16696", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "keras_vgg_buddy/models.py", "symbol": "VGG16.get_f_layer"}, "source_id": "csn:awentzonline/keras-vgg-buddy:keras_vgg_buddy/models.py:VGG16.get_f_layer#16696"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/awentzonline/keras-vgg-buddy/blob/716cb66396b839a66ec8dc66998066b360a8f395/keras_vgg_buddy/models.py#L41-L46", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:awentzonline-keras-vgg-buddy:VGG16.get_f_layer-d0e3f9355d", "question": "Create a function for the response of a layer.", "scope": {"holder": "awentzonline-keras-vgg-buddy", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:awentzonline/keras-vgg-buddy:keras_vgg_buddy/models.py:VGG16.get_layer_output#16697", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "keras_vgg_buddy/models.py", "symbol": "VGG16.get_layer_output"}, "source_id": "csn:awentzonline/keras-vgg-buddy:keras_vgg_buddy/models.py:VGG16.get_layer_output#16697"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/awentzonline/keras-vgg-buddy/blob/716cb66396b839a66ec8dc66998066b360a8f395/keras_vgg_buddy/models.py#L48-L53", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:awentzonline-keras-vgg-buddy:VGG16.get_layer_output-d1ba345432", "question": "Get symbolic output of a layer.", "scope": {"holder": "awentzonline-keras-vgg-buddy", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:bakwc/PySyncObj:pysyncobj/batteries.py:ReplLockManager.isAcquired#6601", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pysyncobj/batteries.py", "symbol": "ReplLockManager.isAcquired"}, "source_id": "csn:bakwc/PySyncObj:pysyncobj/batteries.py:ReplLockManager.isAcquired#6601"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/bakwc/PySyncObj/blob/be3b0aaa932d5156f5df140c23c962430f51b7b8/pysyncobj/batteries.py#L511-L518", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:bakwc-PySyncObj:ReplLockManager.isAcquired-2f1c9b7f0f", "question": "Check if lock is acquired by ourselves.\n\n :param lockID: unique lock identifier.\n :type lockID: str\n :return True if lock is acquired by ourselves.", "scope": {"holder": "bakwc-PySyncObj", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:bakwc/PySyncObj:pysyncobj/transport.py:TCPTransport._connectIfNecessarySingle#6589", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pysyncobj/transport.py", "symbol": "TCPTransport._connectIfNecessarySingle"}, "source_id": "csn:bakwc/PySyncObj:pysyncobj/transport.py:TCPTransport._connectIfNecessarySingle#6589"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/bakwc/PySyncObj/blob/be3b0aaa932d5156f5df140c23c962430f51b7b8/pysyncobj/transport.py#L393-L409", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:bakwc-PySyncObj:TCPTransport._connectIfNecessarySingle-e189f85df9", "question": "Connect to a node if necessary.\n\n :param node: node to connect to\n :type node: Node", "scope": {"holder": "bakwc-PySyncObj", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:bheinzerling/descriptors:descriptors/Descriptor.py:Descriptor.err_msg#18900", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "descriptors/Descriptor.py", "symbol": "Descriptor.err_msg"}, "source_id": "csn:bheinzerling/descriptors:descriptors/Descriptor.py:Descriptor.err_msg#18900"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/bheinzerling/descriptors/blob/04fff864649fba9bd6a2d8f8b649cf30994e0e46/descriptors/Descriptor.py#L83-L99", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:bheinzerling-descriptors:Descriptor.err_msg-1f894e3cae", "question": "Return an error message for use in exceptions thrown by\n subclasses.", "scope": {"holder": "bheinzerling-descriptors", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:bheinzerling/descriptors:descriptors/handmade.py:ForceNumeric.try_convert#18909", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "descriptors/handmade.py", "symbol": "ForceNumeric.try_convert"}, "source_id": "csn:bheinzerling/descriptors:descriptors/handmade.py:ForceNumeric.try_convert#18909"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/bheinzerling/descriptors/blob/04fff864649fba9bd6a2d8f8b649cf30994e0e46/descriptors/handmade.py#L143-L153", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:bheinzerling-descriptors:ForceNumeric.try_convert-d4816e263f", "question": "Convert value to a numeric value or raise a ValueError\n if that isn't possible.", "scope": {"holder": "bheinzerling-descriptors", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:bicv/LogGabor:LogGabor/LogGabor.py:LogGabor.argmax#14236", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "LogGabor/LogGabor.py", "symbol": "LogGabor.argmax"}, "source_id": "csn:bicv/LogGabor:LogGabor/LogGabor.py:LogGabor.argmax#14236"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/bicv/LogGabor/blob/dea9560d8752cc9aa040ac3fd895cf9bb72b61f4/LogGabor/LogGabor.py#L48-L59", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:bicv-LogGabor:LogGabor.argmax-d59e4e2f7e", "question": "Returns the ArgMax from C by returning the\n (x_pos, y_pos, theta, scale) tuple\n\n >>> C = np.random.randn(10, 10, 5, 4)\n >>> x_pos, y_pos, theta, scale = mp.argmax(C)\n >>> C[x_pos][y_pos][theta][scale] = C.max()", "scope": {"holder": "bicv-LogGabor", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:bicv/LogGabor:LogGabor/LogGabor.py:LogGabor.loggabor#14240", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "LogGabor/LogGabor.py", "symbol": "LogGabor.loggabor"}, "source_id": "csn:bicv/LogGabor:LogGabor/LogGabor.py:LogGabor.loggabor#14240"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/bicv/LogGabor/blob/dea9560d8752cc9aa040ac3fd895cf9bb72b61f4/LogGabor/LogGabor.py#L178-L197", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:bicv-LogGabor:LogGabor.loggabor-ce20a284c7", "question": "Returns the envelope of a LogGabor\n\n Note that the convention for coordinates follows that of matrices:\n the origin is at the top left of the image, and coordinates are first\n the rows (vertical axis, going down) then the columns (horizontal axis,\n going right).", "scope": {"holder": "bicv-LogGabor", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:bigdatacesga/kvstore:kvstore.py:Client.get#16514", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "kvstore.py", "symbol": "Client.get"}, "source_id": "csn:bigdatacesga/kvstore:kvstore.py:Client.get#16514"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/bigdatacesga/kvstore/blob/8ad2222b39d47defc8ad30deda3da06798e2a9a4/kvstore.py#L39-L57", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:bigdatacesga-kvstore:Client.get-4eb525bda7", "question": "Get the value of a given key", "scope": {"holder": "bigdatacesga-kvstore", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:bigdatacesga/kvstore:kvstore.py:Client.index#16516", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "kvstore.py", "symbol": "Client.index"}, "source_id": "csn:bigdatacesga/kvstore:kvstore.py:Client.index#16516"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/bigdatacesga/kvstore/blob/8ad2222b39d47defc8ad30deda3da06798e2a9a4/kvstore.py#L85-L95", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:bigdatacesga-kvstore:Client.index-4cbe160edc", "question": "Get the current index of the key or the subtree.\n This is needed for later creating long polling requests", "scope": {"holder": "bigdatacesga-kvstore", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:bindlock/vklancer:vklancer/api.py:API.get_url#14634", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "vklancer/api.py", "symbol": "API.get_url"}, "source_id": "csn:bindlock/vklancer:vklancer/api.py:API.get_url#14634"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/bindlock/vklancer/blob/10151c3856bc6f46a1f446ae4d605d46aace3669/vklancer/api.py#L26-L39", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:bindlock-vklancer:API.get_url-cb9e24ad51", "question": "Return url for call method.\n\n :param method (optional): `str` method name.\n :returns: `str` URL.", "scope": {"holder": "bindlock-vklancer", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:bindlock/vklancer:vklancer/api.py:API.request#14635", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "vklancer/api.py", "symbol": "API.request"}, "source_id": "csn:bindlock/vklancer:vklancer/api.py:API.request#14635"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/bindlock/vklancer/blob/10151c3856bc6f46a1f446ae4d605d46aace3669/vklancer/api.py#L41-L53", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:bindlock-vklancer:API.request-bc8b7bde37", "question": "Send request to API.\n\n :param method: `str` method name.\n :returns: `dict` response.", "scope": {"holder": "bindlock-vklancer", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:bipsandbytes/django-api:django_api/json_helpers.py:JsonResponseEncoder.default#16019", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "django_api/json_helpers.py", "symbol": "JsonResponseEncoder.default"}, "source_id": "csn:bipsandbytes/django-api:django_api/json_helpers.py:JsonResponseEncoder.default#16019"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/bipsandbytes/django-api/blob/df99f4ccbb0c5128bd06da83f60881a85f6dbfe1/django_api/json_helpers.py#L11-L20", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:bipsandbytes-django-api:JsonResponseEncoder.default-50fb1b8381", "question": "Convert QuerySet objects to their list counter-parts", "scope": {"holder": "bipsandbytes-django-api", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:bipsandbytes/django-api:django_api/decorators.py:api_accepts#16064", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "django_api/decorators.py", "symbol": "api_accepts"}, "source_id": "csn:bipsandbytes/django-api:django_api/decorators.py:api_accepts#16064"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/bipsandbytes/django-api/blob/df99f4ccbb0c5128bd06da83f60881a85f6dbfe1/django_api/decorators.py#L35-L119", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:bipsandbytes-django-api:api_accepts-5b64921ea0", "question": "Define the accept schema of an API (GET or POST).\n\n 'fields' is a dict of Django form fields keyed by field name that specifies\n the form-urlencoded fields that the API accepts*.\n\n The view function is then called with GET/POST data that has been cleaned\n by the Django form.\n\n In debug and test modes, failure to validate the fields will result in a\n 400 Bad Request response.\n In production mode, failure to validate will just log a\n warning, unless overwritten by a 'strict' setting.\n\n For example:\n\n @api_accepts({\n 'x': forms.IntegerField(min_value=0),\n 'y': forms.IntegerField(min_value=0),\n })\n def add(request, *args, **kwargs):\n x = request.POST['x']\n y = request.POST['y']\n\n # x and y are integers already.\n return HttpResponse('%d' % (x + y))\n\n\n *: 'fields' can also include Django models as {'key': Model()}. If present,\n api_accepts will look for the field keyed by '<key>-id'\n and pick the object that has that primary key. For example, if the entry is\n {'course': Course()}, it will search for the key course_id='course-id' in\n the request object, and find the object Course.objects.get(pk=course_id)", "scope": {"holder": "bipsandbytes-django-api", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:bitlabstudio/django-dashboard-app:dashboard_app/widget_base.py:DashboardWidgetBase.get_setting#16877", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "dashboard_app/widget_base.py", "symbol": "DashboardWidgetBase.get_setting"}, "source_id": "csn:bitlabstudio/django-dashboard-app:dashboard_app/widget_base.py:DashboardWidgetBase.get_setting#16877"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/bitlabstudio/django-dashboard-app/blob/ed98f2bca91a4ced36d0dd1aa1baee78e989cf64/dashboard_app/widget_base.py#L52-L66", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:bitlabstudio-django-dashboard-app:DashboardWidgetBase.get_setting-9a6d4d7cba", "question": "Returns the setting for this widget from the database.\n\n :setting_name: The name of the setting.\n :default: Optional default value if the setting cannot be found.", "scope": {"holder": "bitlabstudio-django-dashboard-app", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:bitlabstudio/django-dashboard-app:dashboard_app/widget_pool.py:DashboardWidgetPool.get_widgets_that_need_update#16873", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "dashboard_app/widget_pool.py", "symbol": "DashboardWidgetPool.get_widgets_that_need_update"}, "source_id": "csn:bitlabstudio/django-dashboard-app:dashboard_app/widget_pool.py:DashboardWidgetPool.get_widgets_that_need_update#16873"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/bitlabstudio/django-dashboard-app/blob/ed98f2bca91a4ced36d0dd1aa1baee78e989cf64/dashboard_app/widget_pool.py#L56-L67", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:bitlabstudio-django-dashboard-app:DashboardWidgetPool.get_widgets_that_need_update-854ba4d289", "question": "Returns all widgets that need an update.\n\n This should be scheduled every minute via crontab.", "scope": {"holder": "bitlabstudio-django-dashboard-app", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:bitlabstudio/django-hero-slider:hero_slider/south_migrations/0003_set_existing_slideritems_to_be_published.py:Migration.forwards#12339", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "hero_slider/south_migrations/0003_set_existing_slideritems_to_be_published.py", "symbol": "Migration.forwards"}, "source_id": "csn:bitlabstudio/django-hero-slider:hero_slider/south_migrations/0003_set_existing_slideritems_to_be_published.py:Migration.forwards#12339"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/bitlabstudio/django-hero-slider/blob/8153b3eece76c47210a266c2edb660725c34a56e/hero_slider/south_migrations/0003_set_existing_slideritems_to_be_published.py#L10-L15", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:bitlabstudio-django-hero-slider:Migration.forwards-fa5db65565", "question": "Write your forwards methods here.", "scope": {"holder": "bitlabstudio-django-hero-slider", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:bitlabstudio/django-hero-slider:hero_slider/templatetags/hero_slider_tags.py:get_slider_items#12340", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "hero_slider/templatetags/hero_slider_tags.py", "symbol": "get_slider_items"}, "source_id": "csn:bitlabstudio/django-hero-slider:hero_slider/templatetags/hero_slider_tags.py:get_slider_items#12340"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/bitlabstudio/django-hero-slider/blob/8153b3eece76c47210a266c2edb660725c34a56e/hero_slider/templatetags/hero_slider_tags.py#L11-L17", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:bitlabstudio-django-hero-slider:get_slider_items-13de1afe53", "question": "Returns the published slider items.", "scope": {"holder": "bitlabstudio-django-hero-slider", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:bivab/smbus-cffi:smbus/smbus.py:SMBus._set_addr#16765", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "smbus/smbus.py", "symbol": "SMBus._set_addr"}, "source_id": "csn:bivab/smbus-cffi:smbus/smbus.py:SMBus._set_addr#16765"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/bivab/smbus-cffi/blob/7486931edf55fcdde84db38356331c65851a40b1/smbus/smbus.py#L85-L89", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:bivab-smbus-cffi:SMBus._set_addr-1d66e03c0a", "question": "private helper method", "scope": {"holder": "bivab-smbus-cffi", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:bivab/smbus-cffi:smbus/smbus.py:SMBus.read_byte_data#16769", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "smbus/smbus.py", "symbol": "SMBus.read_byte_data"}, "source_id": "csn:bivab/smbus-cffi:smbus/smbus.py:SMBus.read_byte_data#16769"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/bivab/smbus-cffi/blob/7486931edf55fcdde84db38356331c65851a40b1/smbus/smbus.py#L124-L133", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:bivab-smbus-cffi:SMBus.read_byte_data-066518dae0", "question": "read_byte_data(addr, cmd) -> result\n\n Perform SMBus Read Byte Data transaction.", "scope": {"holder": "bivab-smbus-cffi", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:bjodah/pycvodes:pycvodes/__init__.py:integrate_adaptive#10258", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pycvodes/__init__.py", "symbol": "integrate_adaptive"}, "source_id": "csn:bjodah/pycvodes:pycvodes/__init__.py:integrate_adaptive#10258"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/bjodah/pycvodes/blob/00637a682d363319bc5c7c73a78f033556fde8a5/pycvodes/__init__.py#L21-L147", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:bjodah-pycvodes:integrate_adaptive-8da86a4595", "question": "Integrates a system of ordinary differential equations.\n\n Solves the initial value problem (IVP) defined by the user supplied\n arguments. The solver chooses at what values of the independent variable\n results should be reported.\n\n Parameters\n ----------\n rhs : callable\n Function with signature f(t, y, fout) which modifies fout *inplace*.\n jac : callable\n Function with signature either jac(t, y, jmat_out, dfdx_out) for\n dense/banded jacobians, or jac(t, y, data, colptrs, rowvals) for\n sparse (CSC) jacobians. ``jac`` should modify ``jmat_out``, ``dfdx_out``\n (dense, banded) or (``data``, ``colptrs``, ``rowvals``) *inplace*.\n (see also ``lband``, ``uband``, ``nnz``)\n y0 : array_like\n Initial values of the dependent variables.\n x0 : float\n Initial value of the independent variable.\n xend : float\n Stopping value for the independent variable.\n dx0 : float\n Initial step-size.\n atol : float\n Absolute tolerance.\n rtol : float\n Relative tolerance.\n dx_min : float\n Minimum step (default: 0.0).\n dx_max : float\n Maximum step (default: 0.0).\n nsteps : int\n Maximum number of steps (default: 500).\n method : str\n One of: 'adams' or 'bdf' (default: 'bdf')\n nderiv : int\n Number of derivatives (default: 0).\n roots : callback\n With signature ``roots(x, yarr[:ny], out[:nroots]) -> None``.\n nroots : int\n Number of root functions in roots.\n return_on_root : bool\n Exit early (on first found root).\n check_callable : bool\n perform signature sanity checks on ``rhs`` and ``jac``\n check_indexing : bool\n Perform item setting sanity checks on ``rhs`` and ``jac``.\n \\*\\*kwargs:\n 'lband' : int\n Number of lower bands.\n Indexing: ``banded[row_i - col_i + uband, col_i]``.\n 'uband' : int\n Number of upper bands.\n Indexing: ``banded[row_i - col_i + uband, col_i]``.\n 'iter_type' : str (default: 'default')\n One of: 'default', 'functional', 'newton'\n 'linear_solver': str (default: 'default')\n One of: 'default', 'dense', 'banded', 'gmres',\n 'gmres_classic', 'bicgstab', 'tfqmr'\n 'return_on_error' : bool\n Returns on error without raising an excpetion (with ``'success'==False``).\n 'autorestart' : int\n Useful for autonomous systems where conditions change during integration.\n Will restart the integration with ``x==0``. Maximum number of steps is then\n given by ``autorestart * nsteps``.\n 'record_rhs_xvals' : bool\n When True: will return x values for rhs calls in ``info['rhs_xvals']``.\n 'record_jac_xvals' : bool\n When True will return x values for jac calls in ``info['jac_xvals']``.\n 'record_order' : bool\n When True will return used time stepper order in ``info['orders']``.\n 'record_fpe' : bool\n When True will return observed floating point errors in ``info['fpes']``. (see ``fpes``)\n 'record_steps' : bool\n When True will return stepsizes taken in ``info['steps']``.\n 'dx0cb' : callable\n Callback for calculating dx0 (make sure to pass ``dx0==0.0``) to enable.\n Signature: ``f(x, y[:]) -> float``.\n 'dx_max_cb' : callable\n Callback for calculating dx_max.\n Signature: ``f(x, y[:]) -> float``.\n 'autonomous_exprs' bool\n Whether expressions contain the independent variable. If not, autorestart\n is allowed to shift the independent variable to zero at restart).\n 'nnz' : int\n Maximum number of nonzero entries in the sparse (CSC) jacobian (default: -1).\n Must set ``nnz >= 0`` and ``linear_solver`` to 'klu' to enable use of sparse\n ``jac`` signature.\n 'jtimes' : callable\n Function with signature f(v, Jv, t, y, fy) to calculate the product of the\n Jacobian evaluated at t, y with a vector v. Should modify Jv *inplace*.\n For use with linear solvers 'gmres', 'gmres_classic', 'bicgstab', 'tfqmr'.\n 'ew_ele' : bool\n Whether to return error_weights, estimated_local_errors in info dict.\n 'constraints': array\n Per component constraints 0.0: no constraint, 1.0: >=0, -1.0: <=0, 2.0: >0.0, -2.0: <0.0.\n\n Returns\n -------\n (xout, yout, info):\n xout: 1-dimensional array of values for the independent variable\n yout: 2-dimensional array of the dependent variables (axis 1) for\n values corresponding to xout (axis 0).\n info: Dictionary with information about the integration.", "scope": {"holder": "bjodah-pycvodes", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:bjodah/pycvodes:examples/van_der_pol.py:integrate_ivp#10257", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "examples/van_der_pol.py", "symbol": "integrate_ivp"}, "source_id": "csn:bjodah/pycvodes:examples/van_der_pol.py:integrate_ivp#10257"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/bjodah/pycvodes/blob/00637a682d363319bc5c7c73a78f033556fde8a5/examples/van_der_pol.py#L25-L50", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:bjodah-pycvodes:integrate_ivp-2354dd18f6", "question": "Example program integrating an IVP problem of van der Pol oscillator", "scope": {"holder": "bjodah-pycvodes", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:bjoernricks/python-quilt:quilt/add.py:Add._backup_file#12916", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "quilt/add.py", "symbol": "Add._backup_file"}, "source_id": "csn:bjoernricks/python-quilt:quilt/add.py:Add._backup_file#12916"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/bjoernricks/python-quilt/blob/fae88237f601848cc34d073584d9dcb409f01777/quilt/add.py#L62-L70", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:bjoernricks-python-quilt:Add._backup_file-7b21ea8056", "question": "Creates a backup of file", "scope": {"holder": "bjoernricks-python-quilt", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:bjoernricks/python-quilt:quilt/db.py:PatchSeries.add_patch#12934", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "quilt/db.py", "symbol": "PatchSeries.add_patch"}, "source_id": "csn:bjoernricks/python-quilt:quilt/db.py:PatchSeries.add_patch#12934"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/bjoernricks/python-quilt/blob/fae88237f601848cc34d073584d9dcb409f01777/quilt/db.py#L132-L138", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:bjoernricks-python-quilt:PatchSeries.add_patch-3fe926e829", "question": "Add a patch to the patches list", "scope": {"holder": "bjoernricks-python-quilt", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:bkg/greenwich:greenwich/raster.py:AffineTransform.project#19223", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "greenwich/raster.py", "symbol": "AffineTransform.project"}, "source_id": "csn:bkg/greenwich:greenwich/raster.py:AffineTransform.project#19223"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/bkg/greenwich/blob/57ec644dadfe43ce0ecf2cfd32a2de71e0c8c141/greenwich/raster.py#L129-L144", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:bkg-greenwich:AffineTransform.project-3e4c56a32f", "question": "Convert image pixel/line coordinates to georeferenced x/y, return a\n generator of two-tuples.\n\n Arguments:\n coords -- input coordinates as iterable containing two-tuples/lists\n such as ((0, 0), (10, 10))", "scope": {"holder": "bkg-greenwich", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:bkg/greenwich:greenwich/raster.py:Raster.get_offset#19232", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "greenwich/raster.py", "symbol": "Raster.get_offset"}, "source_id": "csn:bkg/greenwich:greenwich/raster.py:Raster.get_offset#19232"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/bkg/greenwich/blob/57ec644dadfe43ce0ecf2cfd32a2de71e0c8c141/greenwich/raster.py#L474-L488", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:bkg-greenwich:Raster.get_offset-b78eff7ed5", "question": "Returns a 4-tuple pixel window (x_offset, y_offset, x_size, y_size).\n\n Arguments:\n envelope -- coordinate extent tuple or Envelope", "scope": {"holder": "bkg-greenwich", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:bkosciow/python_iot-1:iot_message/message.py:Message._validate_message#20550", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "iot_message/message.py", "symbol": "Message._validate_message"}, "source_id": "csn:bkosciow/python_iot-1:iot_message/message.py:Message._validate_message#20550"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/bkosciow/python_iot-1/blob/32880760e0d218a686ebdb0b6ee3ce07e5cbf018/iot_message/message.py#L81-L93", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:bkosciow-python_iot-1:Message._validate_message-b41399ca7b", "question": ":return boolean", "scope": {"holder": "bkosciow-python_iot-1", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:bkosciow/python_iot-1:iot_message/message.py:Message.prepare_message#20548", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "iot_message/message.py", "symbol": "Message.prepare_message"}, "source_id": "csn:bkosciow/python_iot-1:iot_message/message.py:Message.prepare_message#20548"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/bkosciow/python_iot-1/blob/32880760e0d218a686ebdb0b6ee3ce07e5cbf018/iot_message/message.py#L44-L65", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:bkosciow-python_iot-1:Message.prepare_message-2ec486db40", "question": "Return message as dict\n :return dict", "scope": {"holder": "bkosciow-python_iot-1", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:blockstack-packages/keychain-manager-py:keychain/public_keychain.py:PublicKeychain.descendant#15346", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "keychain/public_keychain.py", "symbol": "PublicKeychain.descendant"}, "source_id": "csn:blockstack-packages/keychain-manager-py:keychain/public_keychain.py:PublicKeychain.descendant#15346"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/blockstack-packages/keychain-manager-py/blob/c15c4ed8f3ed155f71ccac7c13ee08f081d38c06/keychain/public_keychain.py#L28-L41", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:blockstack-packages-keychain-manager-py:PublicKeychain.descendant-2b937e266a", "question": "A descendant is a child many steps down.", "scope": {"holder": "blockstack-packages-keychain-manager-py", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:blockstack-packages/keychain-manager-py:keychain/utils.py:bip32_deserialize#15348", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "keychain/utils.py", "symbol": "bip32_deserialize"}, "source_id": "csn:blockstack-packages/keychain-manager-py:keychain/utils.py:bip32_deserialize#15348"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/blockstack-packages/keychain-manager-py/blob/c15c4ed8f3ed155f71ccac7c13ee08f081d38c06/keychain/utils.py#L41-L55", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:blockstack-packages-keychain-manager-py:bip32_deserialize-4c9307ba12", "question": "Derived from code from pybitcointools (https://github.com/vbuterin/pybitcointools)\n by Vitalik Buterin", "scope": {"holder": "blockstack-packages-keychain-manager-py", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:blockstack/zone-file-py:blockstack_zones/parse_zone_file.py:add_default_name#11839", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "blockstack_zones/parse_zone_file.py", "symbol": "add_default_name"}, "source_id": "csn:blockstack/zone-file-py:blockstack_zones/parse_zone_file.py:add_default_name#11839"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/blockstack/zone-file-py/blob/c1078c8c3c28f0881bc9a3af53d4972c4a6862d0/blockstack_zones/parse_zone_file.py#L272-L292", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:blockstack-zone-file-py:add_default_name-481d8cc197", "question": "Go through each line of the text and ensure that \n a name is defined. Use '@' if there is none.", "scope": {"holder": "blockstack-zone-file-py", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:blockstack/zone-file-py:blockstack_zones/record_processors.py:process_origin#11844", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "blockstack_zones/record_processors.py", "symbol": "process_origin"}, "source_id": "csn:blockstack/zone-file-py:blockstack_zones/record_processors.py:process_origin#11844"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/blockstack/zone-file-py/blob/c1078c8c3c28f0881bc9a3af53d4972c4a6862d0/blockstack_zones/record_processors.py#L4-L12", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:blockstack-zone-file-py:process_origin-69b8975222", "question": "Replace {$origin} in template with a serialized $ORIGIN record", "scope": {"holder": "blockstack-zone-file-py", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:bloomreach/s4cmd:s4cmd.py:BotoClient.add_options#5314", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "s4cmd.py", "symbol": "BotoClient.add_options"}, "source_id": "csn:bloomreach/s4cmd:s4cmd.py:BotoClient.add_options#5314"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/bloomreach/s4cmd/blob/bb51075bf43703e7cd95aa39288cf7732ec13a6d/s4cmd.py#L441-L444", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:bloomreach-s4cmd:BotoClient.add_options-c0d22238f9", "question": "Add the whole list of API parameters into optparse.", "scope": {"holder": "bloomreach-s4cmd", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:bloomreach/s4cmd:s4cmd.py:S3Handler.relative_dir_walk#5341", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "s4cmd.py", "symbol": "S3Handler.relative_dir_walk"}, "source_id": "csn:bloomreach/s4cmd:s4cmd.py:S3Handler.relative_dir_walk#5341"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/bloomreach/s4cmd/blob/bb51075bf43703e7cd95aa39288cf7732ec13a6d/s4cmd.py#L964-L978", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:bloomreach-s4cmd:S3Handler.relative_dir_walk-14d2d550c4", "question": "Generic version of directory walk. Return file list without base path\n for comparison.", "scope": {"holder": "bloomreach-s4cmd", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:bluedisk/hangul-toolkit:hgtk/josa.py:attach#5416", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "hgtk/josa.py", "symbol": "attach"}, "source_id": "csn:bluedisk/hangul-toolkit:hgtk/josa.py:attach#5416"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/bluedisk/hangul-toolkit/blob/f36b534ee339263fb72e687b732697cc7ed290dc/hgtk/josa.py#L34-L45", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:bluedisk-hangul-toolkit:attach-6a5f7d7810", "question": "add josa at the end of this word", "scope": {"holder": "bluedisk-hangul-toolkit", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:bluedisk/hangul-toolkit:hgtk/letter.py:decompose#5414", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "hgtk/letter.py", "symbol": "decompose"}, "source_id": "csn:bluedisk/hangul-toolkit:hgtk/letter.py:decompose#5414"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/bluedisk/hangul-toolkit/blob/f36b534ee339263fb72e687b732697cc7ed290dc/hgtk/letter.py#L49-L79", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:bluedisk-hangul-toolkit:decompose-bfb1381b3c", "question": "This function returns letters by decomposing the specified Hangul letter.", "scope": {"holder": "bluedisk-hangul-toolkit", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:bmaeser/pyque:pyque/db/mysql.py:_connection#19779", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pyque/db/mysql.py", "symbol": "_connection"}, "source_id": "csn:bmaeser/pyque:pyque/db/mysql.py:_connection#19779"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/bmaeser/pyque/blob/856dceab8d89cf3771cf21e682466c29a85ae8eb/pyque/db/mysql.py#L37-L49", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:bmaeser-pyque:_connection-8c650d3653", "question": "returns a connected cursor to the database-server.", "scope": {"holder": "bmaeser-pyque", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:bmaeser/pyque:pyque/db/postgresql.py:db_list#19699", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pyque/db/postgresql.py", "symbol": "db_list"}, "source_id": "csn:bmaeser/pyque:pyque/db/postgresql.py:db_list#19699"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/bmaeser/pyque/blob/856dceab8d89cf3771cf21e682466c29a85ae8eb/pyque/db/postgresql.py#L70-L88", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:bmaeser-pyque:db_list-1ed1b78587", "question": "returns a list of all databases on this server", "scope": {"holder": "bmaeser-pyque", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:bolt-project/bolt:bolt/local/array.py:BoltArrayLocal._align#16896", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "bolt/local/array.py", "symbol": "BoltArrayLocal._align"}, "source_id": "csn:bolt-project/bolt:bolt/local/array.py:BoltArrayLocal._align#16896"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/bolt-project/bolt/blob/9cd7104aa085498da3097b72696184b9d3651c51/bolt/local/array.py#L30-L64", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:bolt-project-bolt:BoltArrayLocal._align-ee201a32d1", "question": "Align local bolt array so that axes for iteration are in the keys.\n\n This operation is applied before most functional operators.\n It ensures that the specified axes are valid, and might transpose/reshape\n the underlying array so that the functional operators can be applied\n over the correct records.\n\n Parameters\n ----------\n axes: tuple[int]\n One or more axes that will be iterated over by a functional operator\n\n Returns\n -------\n BoltArrayLocal", "scope": {"holder": "bolt-project-bolt", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:bolt-project/bolt:bolt/spark/chunk.py:ChunkedArray._chunk#16906", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "bolt/spark/chunk.py", "symbol": "ChunkedArray._chunk"}, "source_id": "csn:bolt-project/bolt:bolt/spark/chunk.py:ChunkedArray._chunk#16906"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/bolt-project/bolt/blob/9cd7104aa085498da3097b72696184b9d3651c51/bolt/spark/chunk.py#L87-L144", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:bolt-project-bolt:ChunkedArray._chunk-ef8a4d6465", "question": "Split values of distributed array into chunks.\n\n Transforms an underlying pair RDD of (key, value) into\n records of the form: (key, chunk id), (chunked value).\n Here, chunk id is a tuple identifying the chunk and\n chunked value is a subset of the data from each original value,\n that has been divided along the specified dimensions.\n\n Parameters\n ----------\n size : str or tuple or int\n If str, the average size (in KB) of the chunks in all value dimensions.\n If int or tuple, an explicit specification of the number chunks in\n each value dimension.\n\n axis : tuple, optional, default=None\n One or more axes to estimate chunks for, if provided any\n other axes will use one chunk.\n\n padding: tuple or int, default = None\n Number of elements per dimension that will overlap with the adjacent chunk.\n If a tuple, specifies padding along each chunked dimension; if a int, same\n padding will be applied to all chunked dimensions.", "scope": {"holder": "bolt-project-bolt", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:boto/s3transfer:s3transfer/bandwidth.py:BandwidthLimitedStream.read#8154", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "s3transfer/bandwidth.py", "symbol": "BandwidthLimitedStream.read"}, "source_id": "csn:boto/s3transfer:s3transfer/bandwidth.py:BandwidthLimitedStream.read#8154"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/boto/s3transfer/blob/2aead638c8385d8ae0b1756b2de17e8fad45fffa/s3transfer/bandwidth.py#L138-L156", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:boto-s3transfer:BandwidthLimitedStream.read-af396a04e7", "question": "Read a specified amount\n\n Reads will only be throttled if bandwidth limiting is enabled.", "scope": {"holder": "boto-s3transfer", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:boto/s3transfer:s3transfer/__init__.py:S3Transfer.download_file#8210", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "s3transfer/__init__.py", "symbol": "S3Transfer.download_file"}, "source_id": "csn:boto/s3transfer:s3transfer/__init__.py:S3Transfer.download_file#8210"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/boto/s3transfer/blob/2aead638c8385d8ae0b1756b2de17e8fad45fffa/s3transfer/__init__.py#L656-L680", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:boto-s3transfer:S3Transfer.download_file-433de95e20", "question": "Download an S3 object to a file.\n\n Variants have also been injected into S3 client, Bucket and Object.\n You don't have to use S3Transfer.download_file() directly.", "scope": {"holder": "boto-s3transfer", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:boundary/pulse-api-cli:boundary/alarm_delete.py:AlarmDelete.get_arguments#18368", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "boundary/alarm_delete.py", "symbol": "AlarmDelete.get_arguments"}, "source_id": "csn:boundary/pulse-api-cli:boundary/alarm_delete.py:AlarmDelete.get_arguments#18368"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/boundary/pulse-api-cli/blob/b01ca65b442eed19faac309c9d62bbc3cb2c098f/boundary/alarm_delete.py#L45-L50", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:boundary-pulse-api-cli:AlarmDelete.get_arguments-e8fb6961f8", "question": "Extracts the specific arguments of this CLI", "scope": {"holder": "boundary-pulse-api-cli", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:boundary/pulse-api-cli:boundary/measurement_plot.py:MeasurementPlot.execute#18297", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "boundary/measurement_plot.py", "symbol": "MeasurementPlot.execute"}, "source_id": "csn:boundary/pulse-api-cli:boundary/measurement_plot.py:MeasurementPlot.execute#18297"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/boundary/pulse-api-cli/blob/b01ca65b442eed19faac309c9d62bbc3cb2c098f/boundary/measurement_plot.py#L169-L180", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:boundary-pulse-api-cli:MeasurementPlot.execute-6b963000ab", "question": "Run the steps to execute the CLI", "scope": {"holder": "boundary-pulse-api-cli", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:brandon-rhodes/python-jplephem:jplephem/binary_pck.py:BinaryPCK.close#9838", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "jplephem/binary_pck.py", "symbol": "BinaryPCK.close"}, "source_id": "csn:brandon-rhodes/python-jplephem:jplephem/binary_pck.py:BinaryPCK.close#9838"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/brandon-rhodes/python-jplephem/blob/48c99ce40c627e24c95479d8845e312ea168f567/jplephem/binary_pck.py#L42-L47", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:brandon-rhodes-python-jplephem:BinaryPCK.close-ff881841a9", "question": "Close this file.", "scope": {"holder": "brandon-rhodes-python-jplephem", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:brandon-rhodes/python-jplephem:jplephem/ephem.py:Ephemeris.compute_bundle#9823", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "jplephem/ephem.py", "symbol": "Ephemeris.compute_bundle"}, "source_id": "csn:brandon-rhodes/python-jplephem:jplephem/ephem.py:Ephemeris.compute_bundle#9823"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/brandon-rhodes/python-jplephem/blob/48c99ce40c627e24c95479d8845e312ea168f567/jplephem/ephem.py#L112-L171", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:brandon-rhodes-python-jplephem:Ephemeris.compute_bundle-0519cfaecc", "question": "[DEPRECATED] Return a tuple of coefficients and parameters for `tdb`.\n\n The return value is a tuple that bundles together the\n coefficients and other Chebyshev intermediate values that are\n needed for the computation of either the position or velocity.\n The bundle can then be passed to either `position_from_bundle()`\n or `velocity_from_bundle()` to finish the computation. See the\n package-level documentation for details; most users will simply\n call `position()` or `position_and_velocity()` instead.\n\n The barycentric dynamical time `tdb` argument should be a float.\n If there are many dates you want computed, then make `tdb` an\n array, which is more efficient than calling this method multiple\n times; the return values will be arrays providing a value for\n each time in `tdb`.\n\n For extra precision, the time can be split into two floats; a\n popular choice is to use `tdb` for the integer or half-integer\n date, and `tdb2` to hold the remaining fraction.\n\n Consult the `names` attribute of this ephemeris for the values\n of `name` it supports, such as ``'mars'`` or ``'earthmoon'``.", "scope": {"holder": "brandon-rhodes-python-jplephem", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:bruth/cypher:cypher/utils.py:delimit#15270", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "cypher/utils.py", "symbol": "delimit"}, "source_id": "csn:bruth/cypher:cypher/utils.py:delimit#15270"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/bruth/cypher/blob/4f962f51539ac5a667ab5a050b6b4052d4c10c0f/cypher/utils.py#L4-L22", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:bruth-cypher:delimit-45b3e6987b", "question": "Returns a list of tokens interleaved with the delimiter.", "scope": {"holder": "bruth-cypher", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:bruth/cypher:cypher/shortcuts.py:exists#15279", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "cypher/shortcuts.py", "symbol": "exists"}, "source_id": "csn:bruth/cypher:cypher/shortcuts.py:exists#15279"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/bruth/cypher/blob/4f962f51539ac5a667ab5a050b6b4052d4c10c0f/cypher/shortcuts.py#L5-L23", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:bruth-cypher:exists-592ddad171", "question": "Query to test if a value exists.", "scope": {"holder": "bruth-cypher", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:bsmithyman/problemo:problemo/solverwrap.py:BaseSolver.Ainv#21997", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "problemo/solverwrap.py", "symbol": "BaseSolver.Ainv"}, "source_id": "csn:bsmithyman/problemo:problemo/solverwrap.py:BaseSolver.Ainv#21997"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/bsmithyman/problemo/blob/711c54894e50200accd02c5e5b427194b628b3e9/problemo/solverwrap.py#L61-L66", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:bsmithyman-problemo:BaseSolver.Ainv-4139239fcb", "question": "Returns a Solver instance", "scope": {"holder": "bsmithyman-problemo", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:bsmithyman/problemo:problemo/solverwrap.py:MKLPardisoSolver.Ainv#21998", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "problemo/solverwrap.py", "symbol": "MKLPardisoSolver.Ainv"}, "source_id": "csn:bsmithyman/problemo:problemo/solverwrap.py:MKLPardisoSolver.Ainv#21998"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/bsmithyman/problemo/blob/711c54894e50200accd02c5e5b427194b628b3e9/problemo/solverwrap.py#L143-L149", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:bsmithyman-problemo:MKLPardisoSolver.Ainv-ef917343f9", "question": "Returns a Solver instance", "scope": {"holder": "bsmithyman-problemo", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:bucknerns/concordance:concordance/drivers/runner.py:parse_args#19556", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "concordance/drivers/runner.py", "symbol": "parse_args"}, "source_id": "csn:bucknerns/concordance:concordance/drivers/runner.py:parse_args#19556"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/bucknerns/concordance/blob/a4f39b60e7f8ec64741dd7a603105734bd9cca72/concordance/drivers/runner.py#L19-L40", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:bucknerns-concordance:parse_args-dc56385434", "question": "Parses command line args using argparse library", "scope": {"holder": "bucknerns-concordance", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:bunchesofdonald/photohash:photohash/photohash.py:distance#9770", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "photohash/photohash.py", "symbol": "distance"}, "source_id": "csn:bunchesofdonald/photohash:photohash/photohash.py:distance#9770"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/bunchesofdonald/photohash/blob/1839a37a884e8c31cb94e661bd76f8125b0dfcb6/photohash/photohash.py#L37-L42", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:bunchesofdonald-photohash:distance-a4ef572df0", "question": "Compute the hamming distance between two images", "scope": {"holder": "bunchesofdonald-photohash", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:bunchesofdonald/photohash:photohash/photohash.py:hash_distance#9768", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "photohash/photohash.py", "symbol": "hash_distance"}, "source_id": "csn:bunchesofdonald/photohash:photohash/photohash.py:hash_distance#9768"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/bunchesofdonald/photohash/blob/1839a37a884e8c31cb94e661bd76f8125b0dfcb6/photohash/photohash.py#L6-L11", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:bunchesofdonald-photohash:hash_distance-8a3b6a68e5", "question": "Compute the hamming distance between two hashes", "scope": {"holder": "bunchesofdonald-photohash", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:buzzfeed/phonon:phonon/nodelist.py:Nodelist.find_expired_nodes#15260", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "phonon/nodelist.py", "symbol": "Nodelist.find_expired_nodes"}, "source_id": "csn:buzzfeed/phonon:phonon/nodelist.py:Nodelist.find_expired_nodes#15260"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/buzzfeed/phonon/blob/32fd036d64fab19c554e841f162466f6eb28b50f/phonon/nodelist.py#L40-L57", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:buzzfeed-phonon:Nodelist.find_expired_nodes-8396f1fd97", "question": "Detects connections that have held a reference for longer than its\n process_ttl without refreshing its session. This function does not\n actually removed them from the hash. (See remove_expired_nodes.)\n\n :param list node_ids: optional, a list of ids to check to see if they\n have expired. If node_ids is not passed in, all nodes in the hash\n will be checked.", "scope": {"holder": "buzzfeed-phonon", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:buzzfeed/phonon:phonon/nodelist.py:Nodelist.remove_node#15262", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "phonon/nodelist.py", "symbol": "Nodelist.remove_node"}, "source_id": "csn:buzzfeed/phonon:phonon/nodelist.py:Nodelist.remove_node#15262"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/buzzfeed/phonon/blob/32fd036d64fab19c554e841f162466f6eb28b50f/phonon/nodelist.py#L75-L84", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:buzzfeed-phonon:Nodelist.remove_node-9c4177a109", "question": "Removes a particular node from the nodelist.\n\n :param string node_id: optional, the process id of the node to remove", "scope": {"holder": "buzzfeed-phonon", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:c-soft/satel_integra:satel_integra/satel_integra.py:AsyncSatel._output_changed#8016", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "satel_integra/satel_integra.py", "symbol": "AsyncSatel._output_changed"}, "source_id": "csn:c-soft/satel_integra:satel_integra/satel_integra.py:AsyncSatel._output_changed#8016"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/c-soft/satel_integra/blob/3b6d2020d1e10dc5aa40f30ee4ecc0f3a053eb3c/satel_integra/satel_integra.py#L221-L239", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:c-soft-satel_integra:AsyncSatel._output_changed-94901d6afb", "question": "0x17 outputs state 0x17 + 16/32 bytes", "scope": {"holder": "c-soft-satel_integra", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:c-soft/satel_integra:satel_integra/satel_integra.py:AsyncSatel.set_output#8020", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "satel_integra/satel_integra.py", "symbol": "AsyncSatel.set_output"}, "source_id": "csn:c-soft/satel_integra:satel_integra/satel_integra.py:AsyncSatel.set_output#8020"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/c-soft/satel_integra/blob/3b6d2020d1e10dc5aa40f30ee4ecc0f3a053eb3c/satel_integra/satel_integra.py#L324-L340", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:c-soft-satel_integra:AsyncSatel.set_output-5409755598", "question": "Send output turn on command to the alarm.", "scope": {"holder": "c-soft-satel_integra", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:caktus/rapidsms-twilio:rtwilio/views.py:validate_twilio_signature#18046", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "rtwilio/views.py", "symbol": "validate_twilio_signature"}, "source_id": "csn:caktus/rapidsms-twilio:rtwilio/views.py:validate_twilio_signature#18046"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/caktus/rapidsms-twilio/blob/77ab913cc12d00c3afe5252dc6345903bee9a483/rtwilio/views.py#L20-L44", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:caktus-rapidsms-twilio:validate_twilio_signature-26734f6cb1", "question": "View decorator to validate requests from Twilio per http://www.twilio.com/docs/security.", "scope": {"holder": "caktus-rapidsms-twilio", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:calston/tensor:tensor/logs/parsers.py:ApacheLogParser._parse_format#15391", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "tensor/logs/parsers.py", "symbol": "ApacheLogParser._parse_format"}, "source_id": "csn:calston/tensor:tensor/logs/parsers.py:ApacheLogParser._parse_format#15391"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/calston/tensor/blob/7c0c99708b5dbff97f3895f705e11996b608549d/tensor/logs/parsers.py#L65-L122", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:calston-tensor:ApacheLogParser._parse_format-79223b5312", "question": "Converts the input format to a regular\n expression, as well as extracting fields\n\n Raises an exception if it couldn't compile\n the generated regex.", "scope": {"holder": "calston-tensor", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:calston/tensor:tensor/outputs/riemann.py:RiemannTCP.createClient#15439", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "tensor/outputs/riemann.py", "symbol": "RiemannTCP.createClient"}, "source_id": "csn:calston/tensor:tensor/outputs/riemann.py:RiemannTCP.createClient#15439"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/calston/tensor/blob/7c0c99708b5dbff97f3895f705e11996b608549d/tensor/outputs/riemann.py#L83-L123", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:calston-tensor:RiemannTCP.createClient-b402033459", "question": "Create a TCP connection to Riemann with automatic reconnection", "scope": {"holder": "calston-tensor", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:capitalone/giraffez:giraffez/types.py:Columns.deserialize#16730", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "giraffez/types.py", "symbol": "Columns.deserialize"}, "source_id": "csn:capitalone/giraffez:giraffez/types.py:Columns.deserialize#16730"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/capitalone/giraffez/blob/6b4d27eb1a1eaf188c6885c7364ef27e92b1b957/giraffez/types.py#L347-L364", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:capitalone-giraffez:Columns.deserialize-1e8e728d15", "question": "Deserializes giraffez Archive header. See\n :meth:`~giraffez.types.Columns.serialize` for more information.\n\n :param str data: data in giraffez Archive format, to be deserialized\n :return: :class:`~giraffez.types.Columns` object decoded from data", "scope": {"holder": "capitalone-giraffez", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:capitalone/giraffez:giraffez/types.py:Row.items#16731", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "giraffez/types.py", "symbol": "Row.items"}, "source_id": "csn:capitalone/giraffez:giraffez/types.py:Row.items#16731"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/capitalone/giraffez/blob/6b4d27eb1a1eaf188c6885c7364ef27e92b1b957/giraffez/types.py#L474-L481", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:capitalone-giraffez:Row.items-5101fca44f", "question": "Represents the contents of the row as a :code:`dict` with the column\n names as keys, and the row's fields as values.\n\n :rtype: dict", "scope": {"holder": "capitalone-giraffez", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:cartoonist/pystream-protobuf:stream/stream.py:Stream._read_varint#17644", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "stream/stream.py", "symbol": "Stream._read_varint"}, "source_id": "csn:cartoonist/pystream-protobuf:stream/stream.py:Stream._read_varint#17644"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/cartoonist/pystream-protobuf/blob/40e70b932436887b748905e5e0a82839e4c559f0/stream/stream.py#L148-L163", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:cartoonist-pystream-protobuf:Stream._read_varint-bef1f0029d", "question": "Read a varint from file, parse it, and return the decoded integer.", "scope": {"holder": "cartoonist-pystream-protobuf", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:cartoonist/pystream-protobuf:stream/stream.py:Stream.write#17647", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "stream/stream.py", "symbol": "Stream.write"}, "source_id": "csn:cartoonist/pystream-protobuf:stream/stream.py:Stream.write#17647"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/cartoonist/pystream-protobuf/blob/40e70b932436887b748905e5e0a82839e4c559f0/stream/stream.py#L198-L219", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:cartoonist-pystream-protobuf:Stream.write-df38ed3858", "question": "Write a group of one or more protobuf objects to the file. Multiple\n object groups can be written by calling this method several times\n before closing stream or exiting the runtime context.\n\n The input protobuf objects get buffered and will be written down when\n the number of buffered objects exceed the `self._buffer_size`.\n\n Args:\n pb2_obj (*protobuf.message.Message): list of protobuf messages.", "scope": {"holder": "cartoonist-pystream-protobuf", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:cassinyio/SwarmSpawner:cassinyspawner/swarmspawner.py:SwarmSpawner._docker#14394", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "cassinyspawner/swarmspawner.py", "symbol": "SwarmSpawner._docker"}, "source_id": "csn:cassinyio/SwarmSpawner:cassinyspawner/swarmspawner.py:SwarmSpawner._docker#14394"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/cassinyio/SwarmSpawner/blob/3c39134ef7e02e2afc5d18da7d18d2c69421ed08/cassinyspawner/swarmspawner.py#L189-L195", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:cassinyio-SwarmSpawner:SwarmSpawner._docker-6f1228919b", "question": "wrapper for calling docker methods\n\n to be passed to ThreadPoolExecutor", "scope": {"holder": "cassinyio-SwarmSpawner", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:cassinyio/SwarmSpawner:cassinyspawner/swarmspawner.py:SwarmSpawner.poll#14396", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "cassinyspawner/swarmspawner.py", "symbol": "SwarmSpawner.poll"}, "source_id": "csn:cassinyio/SwarmSpawner:cassinyspawner/swarmspawner.py:SwarmSpawner.poll#14396"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/cassinyio/SwarmSpawner/blob/3c39134ef7e02e2afc5d18da7d18d2c69421ed08/cassinyspawner/swarmspawner.py#L205-L234", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:cassinyio-SwarmSpawner:SwarmSpawner.poll-7f828502e2", "question": "Check for a task state like `docker service ps id`", "scope": {"holder": "cassinyio-SwarmSpawner", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:ccubed/Shosetsu:Shosetsu/VNDB.py:Shosetsu.get_novel#15643", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "Shosetsu/VNDB.py", "symbol": "Shosetsu.get_novel"}, "source_id": "csn:ccubed/Shosetsu:Shosetsu/VNDB.py:Shosetsu.get_novel#15643"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/ccubed/Shosetsu/blob/eba01c058100ec8806129b11a2859f3126a1b101/Shosetsu/VNDB.py#L64-L209", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:ccubed-Shosetsu:Shosetsu.get_novel-ee0ed377aa", "question": "If term is an ID will return that specific ID. If it's a string, it will return the details of the first search result for that term.\n Returned Dictionary Has the following structure:\n Please note, if it says list or dict, it means the python types.\n Indentation indicates level. So English is ['Titles']['English']\n\n 'Titles' - Contains all the titles found for the anime\n 'English' - English title of the novel\n 'Alt' - Alternative title (Usually the Japanese one, but other languages exist)\n 'Aliases' - A list of str that define the aliases as given in VNDB.\n 'Img' - Link to the Image shown on VNDB for that Visual Novel\n 'Length' - Length given by VNDB\n 'Developers' - A list containing the Developers of the VN.\n 'Publishers' - A list containing the Publishers of the VN.\n 'Tags' - Contains 3 lists of different tag categories\n 'Content' - List of tags that have to do with the story's content as defined by VNDB. Ex: Edo Era\n 'Technology' - List of tags that have to do with the VN's technology. Ex: Protagonist with a Face (Wew Lad, 21st century)\n 'Erotic' - List of tags that have to do with the VN's sexual content. Ex: Tentacles\n 'Releases' - A list of dictionaries. They have the following format.\n 'Date' - Date VNDB lists for release\n 'Ages' - Age group appropriate for as determined on VNDB\n 'Platform' - Release Platform\n 'Name' - The name for this particular Release\n 'ID' - The id for this release, also doubles as the link if you append https://vndb.org/ to it\n 'Description' - Contains novel description text if there is any.\n 'ID' - The id for this novel, also doubles as the link if you append https://vndb.org/ to it\n\n :param term: id or name to get details of.\n :param hide_nsfw: bool if 'Img' should filter links flagged as NSFW or not. (no reason to be kwargs...yet)\n :return dict: Dictionary with the parsed results of a novel", "scope": {"holder": "ccubed-Shosetsu", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:ccubed/Shosetsu:Shosetsu/Parsing.py:parse_prod_staff_results#15622", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "Shosetsu/Parsing.py", "symbol": "parse_prod_staff_results"}, "source_id": "csn:ccubed/Shosetsu:Shosetsu/Parsing.py:parse_prod_staff_results#15622"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/ccubed/Shosetsu/blob/eba01c058100ec8806129b11a2859f3126a1b101/Shosetsu/Parsing.py#L37-L48", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:ccubed-Shosetsu:parse_prod_staff_results-886c2832af", "question": "Parse a page of producer or staff results\n\n :param soup: The BS4 class object\n :return: A list of dictionaries containing a name and nationality.", "scope": {"holder": "ccubed-Shosetsu", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:celiao/tmdbsimple:tmdbsimple/account.py:Account.info#5240", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "tmdbsimple/account.py", "symbol": "Account.info"}, "source_id": "csn:celiao/tmdbsimple:tmdbsimple/account.py:Account.info#5240"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/celiao/tmdbsimple/blob/ff17893110c99771d6398a62c35d36dd9735f4b9/tmdbsimple/account.py#L43-L58", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:celiao-tmdbsimple:Account.info-6120f29acd", "question": "Get the basic information for an account.\n\n Call this method first, before calling other Account methods.\n\n Returns:\n A dict respresentation of the JSON returned from the API.", "scope": {"holder": "celiao-tmdbsimple", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:celiao/tmdbsimple:tmdbsimple/movies.py:Movies.releases#5221", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "tmdbsimple/movies.py", "symbol": "Movies.releases"}, "source_id": "csn:celiao/tmdbsimple:tmdbsimple/movies.py:Movies.releases#5221"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/celiao/tmdbsimple/blob/ff17893110c99771d6398a62c35d36dd9735f4b9/tmdbsimple/movies.py#L185-L200", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:celiao-tmdbsimple:Movies.releases-7cc70bdf21", "question": "Get the release date and certification information by country for a\n specific movie id.\n\n Args:\n append_to_response: (optional) Comma separated, any movie method.\n\n Returns:\n A dict representation of the JSON returned from the API.", "scope": {"holder": "celiao-tmdbsimple", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:cgarciae/dicto:dicto/dicto_legacy.py:dicto.merge_#19398", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "dicto/dicto_legacy.py", "symbol": "dicto.merge_"}, "source_id": "csn:cgarciae/dicto:dicto/dicto_legacy.py:dicto.merge_#19398"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/cgarciae/dicto/blob/fee67e1abcf2538455fee62414c34eb2354bdafa/dicto/dicto_legacy.py#L54-L70", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:cgarciae-dicto:dicto.merge_-5760a555c2", "question": "Recursive dict merge. Inspired by :meth:``dict.update()``, instead of\n updating only top-level keys, dict_merge recurses down into dicts nested\n to an arbitrary depth, updating keys. The ``merge_dct`` is merged into\n ``self``.\n :param self: dict onto which the merge is executed\n :param merge_dct: self merged into self\n :return: None", "scope": {"holder": "cgarciae-dicto", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:chairco/pyRscript:pyRscript/pyRscript.py:Rscript.cd#22029", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pyRscript/pyRscript.py", "symbol": "Rscript.cd"}, "source_id": "csn:chairco/pyRscript:pyRscript/pyRscript.py:Rscript.cd#22029"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/chairco/pyRscript/blob/e952f450a873de52baa4fe80ed901f0cf990c0b7/pyRscript/pyRscript.py#L52-L61", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:chairco-pyRscript:Rscript.cd-2b39443e66", "question": "go to the path", "scope": {"holder": "chairco-pyRscript", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:chairco/pyRscript:pyRscript/pyRscript.py:Rscript.execute#22032", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pyRscript/pyRscript.py", "symbol": "Rscript.execute"}, "source_id": "csn:chairco/pyRscript:pyRscript/pyRscript.py:Rscript.execute#22032"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/chairco/pyRscript/blob/e952f450a873de52baa4fe80ed901f0cf990c0b7/pyRscript/pyRscript.py#L100-L111", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:chairco-pyRscript:Rscript.execute-d92daec3da", "question": "Execute R script", "scope": {"holder": "chairco-pyRscript", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:chaoss/grimoirelab-kingarthur:arthur/arthur.py:Arthur.__parse_archive_args#12367", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "arthur/arthur.py", "symbol": "Arthur.__parse_archive_args"}, "source_id": "csn:chaoss/grimoirelab-kingarthur:arthur/arthur.py:Arthur.__parse_archive_args#12367"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/chaoss/grimoirelab-kingarthur/blob/9d6a638bee68d5e5c511f045eeebf06340fd3252/arthur/arthur.py#L139-L152", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:chaoss-grimoirelab-kingarthur:Arthur.__parse_archive_args-3a2e479a5c", "question": "Parse the archive arguments of a task", "scope": {"holder": "chaoss-grimoirelab-kingarthur", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:chaoss/grimoirelab-kingarthur:arthur/scheduler.py:Scheduler._build_job_arguments#12378", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "arthur/scheduler.py", "symbol": "Scheduler._build_job_arguments"}, "source_id": "csn:chaoss/grimoirelab-kingarthur:arthur/scheduler.py:Scheduler._build_job_arguments#12378"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/chaoss/grimoirelab-kingarthur/blob/9d6a638bee68d5e5c511f045eeebf06340fd3252/arthur/scheduler.py#L369-L399", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:chaoss-grimoirelab-kingarthur:Scheduler._build_job_arguments-a0411a0b1b", "question": "Build the set of arguments required for running a job", "scope": {"holder": "chaoss-grimoirelab-kingarthur", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:chaoss/grimoirelab-perceval:perceval/archive.py:Archive._count_table_rows#5089", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "perceval/archive.py", "symbol": "Archive._count_table_rows"}, "source_id": "csn:chaoss/grimoirelab-perceval:perceval/archive.py:Archive._count_table_rows#5089"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/chaoss/grimoirelab-perceval/blob/41c908605e88b7ebc3a536c643fa0f212eaf9e0e/perceval/archive.py#L330-L345", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:chaoss-grimoirelab-perceval:Archive._count_table_rows-b974e816c6", "question": "Fetch the number of rows in a table", "scope": {"holder": "chaoss-grimoirelab-perceval", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:chaoss/grimoirelab-perceval:perceval/backends/core/git.py:GitRepository.rev_list#5028", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "perceval/backends/core/git.py", "symbol": "GitRepository.rev_list"}, "source_id": "csn:chaoss/grimoirelab-perceval:perceval/backends/core/git.py:GitRepository.rev_list#5028"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/chaoss/grimoirelab-perceval/blob/41c908605e88b7ebc3a536c643fa0f212eaf9e0e/perceval/backends/core/git.py#L944-L982", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:chaoss-grimoirelab-perceval:GitRepository.rev_list-55179f779a", "question": "Read the list commits from the repository\n\n The list of branches is a list of strings, with the names of the\n branches to fetch. If the list of branches is empty, no commit\n is fetched. If the list of branches is None, all commits\n for all branches will be fetched.\n\n The method returns the Git rev-list of the repository using the\n following options:\n\n git rev-list --topo-order\n\n :param branches: names of branches to fetch from (default: None)\n\n :raises EmptyRepositoryError: when the repository is empty and\n the action cannot be performed\n :raises RepositoryError: when an error occurs executing the command", "scope": {"holder": "chaoss-grimoirelab-perceval", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:chaoss/grimoirelab-perceval-mozilla:perceval/backends/mozilla/crates.py:Crates.__fetch_crate_owner_team#17739", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "perceval/backends/mozilla/crates.py", "symbol": "Crates.__fetch_crate_owner_team"}, "source_id": "csn:chaoss/grimoirelab-perceval-mozilla:perceval/backends/mozilla/crates.py:Crates.__fetch_crate_owner_team#17739"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/chaoss/grimoirelab-perceval-mozilla/blob/4514f8d3d609d3cb79d83c72d51fcc4b4a7daeb4/perceval/backends/mozilla/crates.py#L204-L211", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:chaoss-grimoirelab-perceval-mozilla:Crates.__fetch_crate_owner_team-e13eac9f5f", "question": "Get crate team owner", "scope": {"holder": "chaoss-grimoirelab-perceval-mozilla", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:chaoss/grimoirelab-perceval-mozilla:perceval/backends/mozilla/kitsune.py:Kitsune.fetch_items#17751", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "perceval/backends/mozilla/kitsune.py", "symbol": "Kitsune.fetch_items"}, "source_id": "csn:chaoss/grimoirelab-perceval-mozilla:perceval/backends/mozilla/kitsune.py:Kitsune.fetch_items#17751"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/chaoss/grimoirelab-perceval-mozilla/blob/4514f8d3d609d3cb79d83c72d51fcc4b4a7daeb4/perceval/backends/mozilla/kitsune.py#L89-L162", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:chaoss-grimoirelab-perceval-mozilla:Kitsune.fetch_items-5af87f9c8e", "question": "Fetch questions from the Kitsune url\n\n :param category: the category of items to fetch\n :param kwargs: backend arguments\n\n :returns: a generator of items", "scope": {"holder": "chaoss-grimoirelab-perceval-mozilla", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:chrisjrn/registrasion:registrasion/controllers/batch.py:BatchController.memoise#15009", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "registrasion/controllers/batch.py", "symbol": "BatchController.memoise"}, "source_id": "csn:chrisjrn/registrasion:registrasion/controllers/batch.py:BatchController.memoise#15009"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/chrisjrn/registrasion/blob/461d5846c6f9f3b7099322a94f5d9911564448e4/registrasion/controllers/batch.py#L71-L104", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:chrisjrn-registrasion:BatchController.memoise-0ccacce5ed", "question": "Decorator that stores the result of the stored function in the\n user's results cache until the batch completes. Keyword arguments are\n not yet supported.\n\n Arguments:\n func (callable(*a)): The function whose results we want\n to store. The positional arguments, ``a``, are used as cache\n keys.\n\n Returns:\n callable(*a): The memosing version of ``func``.", "scope": {"holder": "chrisjrn-registrasion", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:chrisjrn/registrasion:registrasion/views.py:_handle_products#15070", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "registrasion/views.py", "symbol": "_handle_products"}, "source_id": "csn:chrisjrn/registrasion:registrasion/views.py:_handle_products#15070"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/chrisjrn/registrasion/blob/461d5846c6f9f3b7099322a94f5d9911564448e4/registrasion/views.py#L509-L569", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:chrisjrn-registrasion:_handle_products-7b30053617", "question": "Handles a products list form in the given request. Returns the\n form instance, the discounts applicable to this form, and whether the\n contents were handled.", "scope": {"holder": "chrisjrn-registrasion", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:chrisnorman7/wxgoodies:wxgoodies/keys.py:add_accelerator#18373", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "wxgoodies/keys.py", "symbol": "add_accelerator"}, "source_id": "csn:chrisnorman7/wxgoodies:wxgoodies/keys.py:add_accelerator#18373"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/chrisnorman7/wxgoodies/blob/0064e4d5784714b90357ebb0bc721395e103349b/wxgoodies/keys.py#L111-L128", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:chrisnorman7-wxgoodies:add_accelerator-d46c62b006", "question": "Adds a key to the control.\n \n control: The control that the accelerator should be added to.\n key: A string like \"CTRL+F\", or \"CMD+T\" that specifies the key to use.\n func: The function that should be called when key is pressed.\n id: The id to Bind the event to. Defaults to wx.NewId().", "scope": {"holder": "chrisnorman7-wxgoodies", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:chrisnorman7/wxgoodies:wxgoodies/keys.py:key_to_str#18370", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "wxgoodies/keys.py", "symbol": "key_to_str"}, "source_id": "csn:chrisnorman7/wxgoodies:wxgoodies/keys.py:key_to_str#18370"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/chrisnorman7/wxgoodies/blob/0064e4d5784714b90357ebb0bc721395e103349b/wxgoodies/keys.py#L44-L68", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:chrisnorman7-wxgoodies:key_to_str-b97bcb6884", "question": "Returns a human-readable version of numerical modifiers and key.\n \n To make the key suitable for global hotkey usage, supply:\n mods_table = global_mods, key_table = win32con, key_prefix = 'VK_'", "scope": {"holder": "chrisnorman7-wxgoodies", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:chrisrink10/basilisp:src/basilisp/importer.py:BasilispImporter._exec_cached_module#13288", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "src/basilisp/importer.py", "symbol": "BasilispImporter._exec_cached_module"}, "source_id": "csn:chrisrink10/basilisp:src/basilisp/importer.py:BasilispImporter._exec_cached_module#13288"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/chrisrink10/basilisp/blob/3d82670ee218ec64eb066289c82766d14d18cc92/src/basilisp/importer.py#L175-L201", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:chrisrink10-basilisp:BasilispImporter._exec_cached_module-f5aecc2b95", "question": "Load and execute a cached Basilisp module.", "scope": {"holder": "chrisrink10-basilisp", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:chrisrink10/basilisp:src/basilisp/lang/runtime.py:_new_module#13358", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "src/basilisp/lang/runtime.py", "symbol": "_new_module"}, "source_id": "csn:chrisrink10/basilisp:src/basilisp/lang/runtime.py:_new_module#13358"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/chrisrink10/basilisp/blob/3d82670ee218ec64eb066289c82766d14d18cc92/src/basilisp/lang/runtime.py#L118-L126", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:chrisrink10-basilisp:_new_module-f05777035a", "question": "Create a new empty Basilisp Python module.\n Modules are created for each Namespace when it is created.", "scope": {"holder": "chrisrink10-basilisp", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:chuck1/codemach:codemach/machine.py:Machine.build_class#19776", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "codemach/machine.py", "symbol": "Machine.build_class"}, "source_id": "csn:chuck1/codemach:codemach/machine.py:Machine.build_class#19776"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/chuck1/codemach/blob/b0e02f363da7aa58de7d6ad6499784282958adeb/codemach/machine.py#L385-L431", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:chuck1-codemach:Machine.build_class-7045a779dd", "question": "Implement ``builtins.__build_class__``.\n We must wrap all class member functions using :py:func:`function_wrapper`.\n This requires using a :py:class:`Machine` to execute the class source code\n and then recreating the class source code using an :py:class:`Assembler`.\n\n .. note: We might be able to bypass the call to ``builtins.__build_class__``\n entirely and manually construct a class object.\n\n https://github.com/python/cpython/blob/master/Python/bltinmodule.c", "scope": {"holder": "chuck1-codemach", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:chuck1/codemach:codemach/machine.py:Machine.execute#19773", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "codemach/machine.py", "symbol": "Machine.execute"}, "source_id": "csn:chuck1/codemach:codemach/machine.py:Machine.execute#19773"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/chuck1/codemach/blob/b0e02f363da7aa58de7d6ad6499784282958adeb/codemach/machine.py#L262-L291", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:chuck1-codemach:Machine.execute-a4c1980ff9", "question": "Execute a code object\n \n The inputs and behavior of this function should match those of\n eval_ and exec_.\n\n .. _eval: https://docs.python.org/3/library/functions.html?highlight=eval#eval\n .. _exec: https://docs.python.org/3/library/functions.html?highlight=exec#exec\n\n .. note:: Need to figure out how the internals of this function must change for\n ``eval`` or ``exec``.\n\n :param code: a python code object\n :param globals_: optional globals dictionary\n :param _locals: optional locals dictionary", "scope": {"holder": "chuck1-codemach", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:cloud9ers/gurumate:environment/lib/python2.7/site-packages/distribute-0.6.31-py2.7.egg/setuptools/sandbox.py:AbstractSandbox.run#20521", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "environment/lib/python2.7/site-packages/distribute-0.6.31-py2.7.egg/setuptools/sandbox.py", "symbol": "AbstractSandbox.run"}, "source_id": "csn:cloud9ers/gurumate:environment/lib/python2.7/site-packages/distribute-0.6.31-py2.7.egg/setuptools/sandbox.py:AbstractSandbox.run#20521"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/cloud9ers/gurumate/blob/075dc74d1ee62a8c6b7a8bf2b271364f01629d1e/environment/lib/python2.7/site-packages/distribute-0.6.31-py2.7.egg/setuptools/sandbox.py#L70-L84", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:cloud9ers-gurumate:AbstractSandbox.run-e508c85ca1", "question": "Run 'func' under os sandboxing", "scope": {"holder": "cloud9ers-gurumate", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:cloud9ers/gurumate:environment/lib/python2.7/site-packages/psutil/__init__.py:Process.exe#21497", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "environment/lib/python2.7/site-packages/psutil/__init__.py", "symbol": "Process.exe"}, "source_id": "csn:cloud9ers/gurumate:environment/lib/python2.7/site-packages/psutil/__init__.py:Process.exe#21497"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/cloud9ers/gurumate/blob/075dc74d1ee62a8c6b7a8bf2b271364f01629d1e/environment/lib/python2.7/site-packages/psutil/__init__.py#L232-L262", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:cloud9ers-gurumate:Process.exe-17ffad4f7f", "question": "The process executable path. May also be an empty string.", "scope": {"holder": "cloud9ers-gurumate", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:clouserw/tower:tower/__init__.py:activate#18005", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "tower/__init__.py", "symbol": "activate"}, "source_id": "csn:clouserw/tower:tower/__init__.py:activate#18005"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/clouserw/tower/blob/e2ac254f7dac887952441592f7772af7bb25cc7b/tower/__init__.py#L93-L107", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:clouserw-tower:activate-5cc23d3064", "question": "Override django's utils.translation.activate(). Django forces files\n to be named django.mo (http://code.djangoproject.com/ticket/6376). Since\n that's dumb and we want to be able to load different files depending on\n what part of the site the user is in, we'll make our own function here.", "scope": {"holder": "clouserw-tower", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:clouserw/tower:tower/__init__.py:ugettext#18002", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "tower/__init__.py", "symbol": "ugettext"}, "source_id": "csn:clouserw/tower:tower/__init__.py:ugettext#18002"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/clouserw/tower/blob/e2ac254f7dac887952441592f7772af7bb25cc7b/tower/__init__.py#L22-L31", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:clouserw-tower:ugettext-c26b34ee07", "question": "Always return a stripped string, localized if possible", "scope": {"holder": "clouserw-tower", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:cmcginty/PyWeather:weather/services/_base.py:HttpPublisher.publish#16824", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "weather/services/_base.py", "symbol": "HttpPublisher.publish"}, "source_id": "csn:cmcginty/PyWeather:weather/services/_base.py:HttpPublisher.publish#16824"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/cmcginty/PyWeather/blob/8c25d9cd1fa921e0a6e460d523656279cac045cb/weather/services/_base.py#L63-L67", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:cmcginty-PyWeather:HttpPublisher.publish-46a1b3485c", "question": "Perform HTTP session to transmit defined weather values.", "scope": {"holder": "cmcginty-PyWeather", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:cmcginty/PyWeather:weather/stations/davis.py:VantagePro._use_rev_b_archive#16828", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "weather/stations/davis.py", "symbol": "VantagePro._use_rev_b_archive"}, "source_id": "csn:cmcginty/PyWeather:weather/stations/davis.py:VantagePro._use_rev_b_archive#16828"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/cmcginty/PyWeather/blob/8c25d9cd1fa921e0a6e460d523656279cac045cb/weather/stations/davis.py#L364-L380", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:cmcginty-PyWeather:VantagePro._use_rev_b_archive-24caadd709", "question": "return True if weather station returns Rev.B archives", "scope": {"holder": "cmcginty-PyWeather", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:cnu/scrapy-random-useragent:setup.py:get_package_meta#13015", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "setup.py", "symbol": "get_package_meta"}, "source_id": "csn:cnu/scrapy-random-useragent:setup.py:get_package_meta#13015"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/cnu/scrapy-random-useragent/blob/0f49a66ec800733ea001e3140ce6a8f86e10ed9c/setup.py#L19-L24", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:cnu-scrapy-random-useragent:get_package_meta-96371da672", "question": "Return value of variable set in the package where said variable is\n named in the Python meta format `__<meta_name>__`.", "scope": {"holder": "cnu-scrapy-random-useragent", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:codeghar/brokerlso:brokerlso/qmfv2.py:RequestCmd.create_queue#20030", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "brokerlso/qmfv2.py", "symbol": "RequestCmd.create_queue"}, "source_id": "csn:codeghar/brokerlso:brokerlso/qmfv2.py:RequestCmd.create_queue#20030"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/codeghar/brokerlso/blob/e110e12502b090e12b06c7615dd0a96a14a92585/brokerlso/qmfv2.py#L18-L45", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:codeghar-brokerlso:RequestCmd.create_queue-29873c0aca", "question": "Create message content and properties to create queue with QMFv2\n\n :param name: Name of queue to create\n :type name: str\n :param strict: Whether command should fail when unrecognized properties are provided\n Not used by QMFv2\n Default: True\n :type strict: bool\n :param auto_delete: Whether queue should be auto deleted\n Default: False\n :type auto_delete: bool\n :param auto_delete_timeout: Timeout in seconds for auto deleting queue\n Default: 10\n :type auto_delete_timeout: int\n\n :returns: Tuple containing content and method properties", "scope": {"holder": "codeghar-brokerlso", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:codeghar/brokerlso:brokerlso/qmfv2.py:RequestCmd.list_exchanges#20033", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "brokerlso/qmfv2.py", "symbol": "RequestCmd.list_exchanges"}, "source_id": "csn:codeghar/brokerlso:brokerlso/qmfv2.py:RequestCmd.list_exchanges#20033"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/codeghar/brokerlso/blob/e110e12502b090e12b06c7615dd0a96a14a92585/brokerlso/qmfv2.py#L168-L177", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:codeghar-brokerlso:RequestCmd.list_exchanges-b46103d089", "question": "Create message content and properties to list all exchanges with QMFv2\n\n :returns: Tuple containing content and query properties", "scope": {"holder": "codeghar-brokerlso", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:codeinthehole/django-async-messages:async_messages/middleware.py:AsyncMiddleware.process_response#17301", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "async_messages/middleware.py", "symbol": "AsyncMiddleware.process_response"}, "source_id": "csn:codeinthehole/django-async-messages:async_messages/middleware.py:AsyncMiddleware.process_response#17301"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/codeinthehole/django-async-messages/blob/292cb2fc517521dabc67b90e7ca5b1617f59e214/async_messages/middleware.py#L8-L18", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:codeinthehole-django-async-messages:AsyncMiddleware.process_response-5c39e6f014", "question": "Check for messages for this user and, if it exists,\n call the messages API with it", "scope": {"holder": "codeinthehole-django-async-messages", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:codeinthehole/django-async-messages:async_messages/__init__.py:message_user#17298", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "async_messages/__init__.py", "symbol": "message_user"}, "source_id": "csn:codeinthehole/django-async-messages:async_messages/__init__.py:message_user#17298"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/codeinthehole/django-async-messages/blob/292cb2fc517521dabc67b90e7ca5b1617f59e214/async_messages/__init__.py#L5-L18", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:codeinthehole-django-async-messages:message_user-b4a0a47d57", "question": "Send a message to a particular user.\n\n :param user: User instance\n :param message: Message to show\n :param level: Message level", "scope": {"holder": "codeinthehole-django-async-messages", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:codelv/enaml-web:examples/simple_site/handlers.py:BaseHandler.prepare#9071", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "examples/simple_site/handlers.py", "symbol": "BaseHandler.prepare"}, "source_id": "csn:codelv/enaml-web:examples/simple_site/handlers.py:BaseHandler.prepare#9071"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/codelv/enaml-web/blob/88f1131a7b3ba9e83467b4f44bc3bab6f0de7559/examples/simple_site/handlers.py#L18-L33", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:codelv-enaml-web:BaseHandler.prepare-d3069fb5c2", "question": "Load the view on first load", "scope": {"holder": "codelv-enaml-web", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:codelv/enaml-web:web/components/html.py:Tag.prepare#9090", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "web/components/html.py", "symbol": "Tag.prepare"}, "source_id": "csn:codelv/enaml-web:web/components/html.py:Tag.prepare#9090"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/codelv/enaml-web/blob/88f1131a7b3ba9e83467b4f44bc3bab6f0de7559/web/components/html.py#L154-L161", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:codelv-enaml-web:Tag.prepare-b446f35d85", "question": "Prepare for rendering", "scope": {"holder": "codelv-enaml-web", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:coleifer/irc:botnet/worker.py:BaseWorkerBot.command_patterns#14380", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "botnet/worker.py", "symbol": "BaseWorkerBot.command_patterns"}, "source_id": "csn:coleifer/irc:botnet/worker.py:BaseWorkerBot.command_patterns#14380"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/coleifer/irc/blob/f9d2bd6369aafe6cb0916c9406270ca8ecea2080/botnet/worker.py#L110-L121", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:coleifer-irc:BaseWorkerBot.command_patterns-cd19403014", "question": "\\\n Actual messages listened for by the worker bot - note that worker-execute\n actually dispatches again by adding the command to the task queue,\n from which it is pulled then matched against self.task_patterns", "scope": {"holder": "coleifer-irc", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:coleifer/irc:irc.py:IRCConnection.dispatch_patterns#14370", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "irc.py", "symbol": "IRCConnection.dispatch_patterns"}, "source_id": "csn:coleifer/irc:irc.py:IRCConnection.dispatch_patterns#14370"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/coleifer/irc/blob/f9d2bd6369aafe6cb0916c9406270ca8ecea2080/irc.py#L146-L168", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:coleifer-irc:IRCConnection.dispatch_patterns-68141ba974", "question": "\\\n Low-level dispatching of socket data based on regex matching, in general\n handles\n\n * In event a nickname is taken, registers under a different one\n * Responds to periodic PING messages from server\n * Dispatches to registered callbacks when\n - any user leaves or enters a room currently connected to\n - a channel message is observed\n - a private message is received", "scope": {"holder": "coleifer-irc", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:collab-project/django-admin-footer:admin_footer/templatetags/footer.py:admin_footer#15470", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "admin_footer/templatetags/footer.py", "symbol": "admin_footer"}, "source_id": "csn:collab-project/django-admin-footer:admin_footer/templatetags/footer.py:admin_footer#15470"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/collab-project/django-admin-footer/blob/55d5b7a4b168fa56f39664091af06820236057c6/admin_footer/templatetags/footer.py#L34-L49", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:collab-project-django-admin-footer:admin_footer-e62fd00492", "question": "Template tag that renders the footer information based on the\n authenticated user's permissions.", "scope": {"holder": "collab-project-django-admin-footer", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:collab-project/django-admin-footer:admin_footer/__init__.py:get_version#15476", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "admin_footer/__init__.py", "symbol": "get_version"}, "source_id": "csn:collab-project/django-admin-footer:admin_footer/__init__.py:get_version#15476"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/collab-project/django-admin-footer/blob/55d5b7a4b168fa56f39664091af06820236057c6/admin_footer/__init__.py#L23-L34", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:collab-project-django-admin-footer:get_version-aac9a925d9", "question": "Return full version nr, inc. rc, beta etc tags.\n\n For example: `2.0.0a1`\n :rtype: str", "scope": {"holder": "collab-project-django-admin-footer", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:connectordb/connectordb-python:connectordb/_connectordb.py:ConnectorDB.import_users#15649", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "connectordb/_connectordb.py", "symbol": "ConnectorDB.import_users"}, "source_id": "csn:connectordb/connectordb-python:connectordb/_connectordb.py:ConnectorDB.import_users#15649"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/connectordb/connectordb-python/blob/2092b0cb30898139a247176bcf433d5a4abde7cb/connectordb/_connectordb.py#L134-L163", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:connectordb-connectordb-python:ConnectorDB.import_users-9e8f9816d2", "question": "Imports version 1 of ConnectorDB export. These exports can be generated\n by running user.export(dir), possibly on multiple users.", "scope": {"holder": "connectordb-connectordb-python", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:connectordb/connectordb-python:connectordb/logger.py:Logger.data#15659", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "connectordb/logger.py", "symbol": "Logger.data"}, "source_id": "csn:connectordb/connectordb-python:connectordb/logger.py:Logger.data#15659"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/connectordb/connectordb-python/blob/2092b0cb30898139a247176bcf433d5a4abde7cb/connectordb/logger.py#L361-L379", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:connectordb-connectordb-python:Logger.data-8f3dd4f31d", "question": "The data property allows the user to save settings/data in the database, so that\n there does not need to be extra code messing around with settings.\n\n Use this property to save things that can be converted to JSON inside the logger database,\n so that you don't have to mess with configuration files or saving setting otherwise::\n\n from connectordb.logger import Logger\n\n l = Logger(\"log.db\")\n\n l.data = {\"hi\": 56}\n\n # prints the data dictionary\n print l.data", "scope": {"holder": "connectordb-connectordb-python", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:coops/r53:src/r53/r53.py:fetch_config#15767", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "src/r53/r53.py", "symbol": "fetch_config"}, "source_id": "csn:coops/r53:src/r53/r53.py:fetch_config#15767"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/coops/r53/blob/3c4e7242ad65b0e1ad4ba6b4ac893c7d501ceb0a/src/r53/r53.py#L39-L71", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:coops-r53:fetch_config-037a192d78", "question": "Fetch all pieces of a Route 53 config from Amazon.\n\n Args: zone: string, hosted zone id.\n conn: boto.route53.Route53Connection\n Returns: list of ElementTrees, one for each piece of config.", "scope": {"holder": "coops-r53", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:coops/r53:src/r53/r53.py:lookup_zone#15766", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "src/r53/r53.py", "symbol": "lookup_zone"}, "source_id": "csn:coops/r53:src/r53/r53.py:lookup_zone#15766"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/coops/r53/blob/3c4e7242ad65b0e1ad4ba6b4ac893c7d501ceb0a/src/r53/r53.py#L26-L37", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:coops-r53:lookup_zone-e8fdafd431", "question": "Look up a zone ID for a zone string.\n\n Args: conn: boto.route53.Route53Connection\n zone: string eg. foursquare.com\n Returns: zone ID eg. ZE2DYFZDWGSL4.\n Raises: ZoneNotFoundError if zone not found.", "scope": {"holder": "coops-r53", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:crankycoder/hydra:src/hydra.py:WritingBloomFilter#17689", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "src/hydra.py", "symbol": "WritingBloomFilter"}, "source_id": "csn:crankycoder/hydra:src/hydra.py:WritingBloomFilter#17689"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/crankycoder/hydra/blob/3be536bd0c6716d4efcfde3e132582e6066bae43/src/hydra.py#L38-L56", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:crankycoder-hydra:WritingBloomFilter-174ebbcef6", "question": "Create a read/write bloom filter with an upperbound of\n (num_elements, max_fp_prob) as a specification and using filename\n as the backing datastore.", "scope": {"holder": "crankycoder-hydra", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:cthoyt/ols-client:src/ols_client/client.py:OlsClient.get_ontology#15745", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "src/ols_client/client.py", "symbol": "OlsClient.get_ontology"}, "source_id": "csn:cthoyt/ols-client:src/ols_client/client.py:OlsClient.get_ontology#15745"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/cthoyt/ols-client/blob/8c6bb54888675652d25324184967392d00d128fc/src/ols_client/client.py#L56-L65", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:cthoyt-ols-client:OlsClient.get_ontology-d2098fa121", "question": "Gets the metadata for a given ontology\n\n :param str ontology: The name of the ontology\n :return: The dictionary representing the JSON from the OLS\n :rtype: dict", "scope": {"holder": "cthoyt-ols-client", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:cthoyt/ols-client:src/ols_client/client.py:OlsClient.search#15747", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "src/ols_client/client.py", "symbol": "OlsClient.search"}, "source_id": "csn:cthoyt/ols-client:src/ols_client/client.py:OlsClient.search#15747"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/cthoyt/ols-client/blob/8c6bb54888675652d25324184967392d00d128fc/src/ols_client/client.py#L79-L91", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:cthoyt-ols-client:OlsClient.search-1092458a2f", "question": "Searches the OLS with the given term\n\n :param str name:\n :param list[str] query_fields: Fields to query\n :return: dict", "scope": {"holder": "cthoyt-ols-client", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:cyberdelia/metrology:metrology/instruments/derive.py:Derive.mark#10416", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "metrology/instruments/derive.py", "symbol": "Derive.mark"}, "source_id": "csn:cyberdelia/metrology:metrology/instruments/derive.py:Derive.mark#10416"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/cyberdelia/metrology/blob/7599bea7de1fd59374c06e2f8041a217e3cf9c01/metrology/instruments/derive.py#L20-L28", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:cyberdelia-metrology:Derive.mark-f0f55bbada", "question": "Record an event with the derive.\n\n :param value: counter value to record", "scope": {"holder": "cyberdelia-metrology", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:cyberdelia/metrology:metrology/reporter/statsd.py:StatsDReporter._buffered_send_metric#10421", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "metrology/reporter/statsd.py", "symbol": "StatsDReporter._buffered_send_metric"}, "source_id": "csn:cyberdelia/metrology:metrology/reporter/statsd.py:StatsDReporter._buffered_send_metric#10421"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/cyberdelia/metrology/blob/7599bea7de1fd59374c06e2f8041a217e3cf9c01/metrology/reporter/statsd.py#L190-L200", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:cyberdelia-metrology:StatsDReporter._buffered_send_metric-2428c58b41", "question": "Add a metric to the buffer.", "scope": {"holder": "cyberdelia-metrology", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:d0ugal/home:home/__init__.py:create_app#15757", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "home/__init__.py", "symbol": "create_app"}, "source_id": "csn:d0ugal/home:home/__init__.py:create_app#15757"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/d0ugal/home/blob/e984716ae6c74dc8e40346584668ac5cfeaaf520/home/__init__.py#L26-L74", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:d0ugal-home:create_app-00d679ec24", "question": "This needs some tidying up. To avoid circular imports we import\n everything here but it makes this method a bit more gross.", "scope": {"holder": "d0ugal-home", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:d0ugal/home:home/__main__.py:create_user#15618", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "home/__main__.py", "symbol": "create_user"}, "source_id": "csn:d0ugal/home:home/__main__.py:create_user#15618"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/d0ugal/home/blob/e984716ae6c74dc8e40346584668ac5cfeaaf520/home/__main__.py#L55-L60", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:d0ugal-home:create_user-1b01ed7b46", "question": "Create a new user.", "scope": {"holder": "d0ugal-home", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:dagster-io/dagster:python_modules/dagster/dagster/core/types/field_utils.py:Dict#4604", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "python_modules/dagster/dagster/core/types/field_utils.py", "symbol": "Dict"}, "source_id": "csn:dagster-io/dagster:python_modules/dagster/dagster/core/types/field_utils.py:Dict#4604"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/dagster-io/dagster/blob/4119f8c773089de64831b1dfb9e168e353d401dc/python_modules/dagster/dagster/core/types/field_utils.py#L261-L281", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:dagster-io-dagster:Dict-ac664d78be", "question": "Schema for configuration data with string keys and typed values via :py:class:`Field` .\n\n Args:\n fields (Dict[str, Field])", "scope": {"holder": "dagster-io-dagster", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:dagster-io/dagster:python_modules/dagster-airflow/dagster_airflow/compile.py:coalesce_execution_steps#4618", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "python_modules/dagster-airflow/dagster_airflow/compile.py", "symbol": "coalesce_execution_steps"}, "source_id": "csn:dagster-io/dagster:python_modules/dagster-airflow/dagster_airflow/compile.py:coalesce_execution_steps#4618"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/dagster-io/dagster/blob/4119f8c773089de64831b1dfb9e168e353d401dc/python_modules/dagster-airflow/dagster_airflow/compile.py#L16-L28", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:dagster-io-dagster:coalesce_execution_steps-e218d12e2c", "question": "Groups execution steps by solid, in topological order of the solids.", "scope": {"holder": "dagster-io-dagster", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:datacamp/pythonwhat:pythonwhat/State.py:Dispatcher._getx#9940", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pythonwhat/State.py", "symbol": "Dispatcher._getx"}, "source_id": "csn:datacamp/pythonwhat:pythonwhat/State.py:Dispatcher._getx#9940"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/datacamp/pythonwhat/blob/ffbf7f8436a51f77c22f3bed75ba3bc37a5c666f/pythonwhat/State.py#L282-L301", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:datacamp-pythonwhat:Dispatcher._getx-8fccdf0d50", "question": "getter for Parser outputs", "scope": {"holder": "datacamp-pythonwhat", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:datacamp/pythonwhat:pythonwhat/tasks.py:getResultFromProcess#9929", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pythonwhat/tasks.py", "symbol": "getResultFromProcess"}, "source_id": "csn:datacamp/pythonwhat:pythonwhat/tasks.py:getResultFromProcess#9929"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/datacamp/pythonwhat/blob/ffbf7f8436a51f77c22f3bed75ba3bc37a5c666f/pythonwhat/tasks.py#L297-L303", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:datacamp-pythonwhat:getResultFromProcess-43bb67f2ba", "question": "Get a value from process, return tuple of value, res if succesful", "scope": {"holder": "datacamp-pythonwhat", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:dave-shawley/ietfparse:ietfparse/_helpers.py:ParameterParser.add_value#16574", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "ietfparse/_helpers.py", "symbol": "ParameterParser.add_value"}, "source_id": "csn:dave-shawley/ietfparse:ietfparse/_helpers.py:ParameterParser.add_value#16574"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/dave-shawley/ietfparse/blob/d28f360941316e45c1596589fa59bc7d25aa20e0/ietfparse/_helpers.py#L49-L80", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:dave-shawley-ietfparse:ParameterParser.add_value-714032d18f", "question": "Add a new value to the list.\n\n :param str name: name of the value that is being parsed\n :param str value: value that is being parsed\n :raises ietfparse.errors.MalformedLinkValue:\n if *strict mode* is enabled and a validation error\n is detected\n\n This method implements most of the validation mentioned in\n sections 5.3 and 5.4 of :rfc:`5988`. The ``_rfc_values``\n dictionary contains the appropriate values for the attributes\n that get special handling. If *strict mode* is enabled, then\n only values that are acceptable will be added to ``_values``.", "scope": {"holder": "dave-shawley-ietfparse", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:dave-shawley/ietfparse:ietfparse/headers.py:parse_content_type#16563", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "ietfparse/headers.py", "symbol": "parse_content_type"}, "source_id": "csn:dave-shawley/ietfparse:ietfparse/headers.py:parse_content_type#16563"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/dave-shawley/ietfparse/blob/d28f360941316e45c1596589fa59bc7d25aa20e0/ietfparse/headers.py#L202-L223", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:dave-shawley-ietfparse:parse_content_type-e648f506ed", "question": "Parse a content type like header.\n\n :param str content_type: the string to parse as a content type\n :param bool normalize_parameter_values:\n setting this to ``False`` will enable strict RFC2045 compliance\n in which content parameter values are case preserving.\n :return: a :class:`~ietfparse.datastructures.ContentType` instance", "scope": {"holder": "dave-shawley-ietfparse", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:davidmiller/urlhelp:urlhelp/__init__.py:find_links#19596", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "urlhelp/__init__.py", "symbol": "find_links"}, "source_id": "csn:davidmiller/urlhelp:urlhelp/__init__.py:find_links#19596"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/davidmiller/urlhelp/blob/9cc417a5dc5bd4a7e17ed78a1f1394a6ece9faa5/urlhelp/__init__.py#L34-L52", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:davidmiller-urlhelp:find_links-906d332b34", "question": "Find the href destinations of all links at URL\n\n Arguments:\n - `url`:\n\n Return: list[str]\n Exceptions: None", "scope": {"holder": "davidmiller-urlhelp", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:dbcli/cli_helpers:tasks.py:BaseCommand.apply_option#11113", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "tasks.py", "symbol": "BaseCommand.apply_option"}, "source_id": "csn:dbcli/cli_helpers:tasks.py:BaseCommand.apply_option#11113"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/dbcli/cli_helpers/blob/3ebd891ac0c02bad061182dbcb54a47fb21980ae/tasks.py#L48-L51", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:dbcli-cli_helpers:BaseCommand.apply_option-f3b4582349", "question": "Apply a command-line option.", "scope": {"holder": "dbcli-cli_helpers", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:dbcli/cli_helpers:cli_helpers/tabular_output/terminaltables_adapter.py:adapter#11131", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "cli_helpers/tabular_output/terminaltables_adapter.py", "symbol": "adapter"}, "source_id": "csn:dbcli/cli_helpers:cli_helpers/tabular_output/terminaltables_adapter.py:adapter#11131"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/dbcli/cli_helpers/blob/3ebd891ac0c02bad061182dbcb54a47fb21980ae/cli_helpers/tabular_output/terminaltables_adapter.py#L83-L96", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:dbcli-cli_helpers:adapter-51e138ea84", "question": "Wrap terminaltables inside a function for TabularOutputFormatter.", "scope": {"holder": "dbcli-cli_helpers", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:deepmipt/DeepPavlov:deeppavlov/models/elmo/elmo_model.py:BidirectionalLanguageModelGraph._build_word_char_embeddings#1828", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "deeppavlov/models/elmo/elmo_model.py", "symbol": "BidirectionalLanguageModelGraph._build_word_char_embeddings"}, "source_id": "csn:deepmipt/DeepPavlov:deeppavlov/models/elmo/elmo_model.py:BidirectionalLanguageModelGraph._build_word_char_embeddings#1828"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/deepmipt/DeepPavlov/blob/f3e4a69a3764d25d2f5bad4f1f1aebc872b00f9c/deeppavlov/models/elmo/elmo_model.py#L292-L462", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:deepmipt-DeepPavlov:BidirectionalLanguageModelGraph._build_word_char_embeddings-01c5ead8d1", "question": "options contains key 'char_cnn': {\n\n 'n_characters': 262,\n\n # includes the start / end characters\n 'max_characters_per_token': 50,\n\n 'filters': [\n [1, 32],\n [2, 32],\n [3, 64],\n [4, 128],\n [5, 256],\n [6, 512],\n [7, 512]\n ],\n 'activation': 'tanh',\n\n # for the character embedding\n 'embedding': {'dim': 16}\n\n # for highway layers\n # if omitted, then no highway layers\n 'n_highway': 2,\n }", "scope": {"holder": "deepmipt-DeepPavlov", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:deepmipt/DeepPavlov:deeppavlov/metrics/google_bleu.py:compute_bleu#1757", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "deeppavlov/metrics/google_bleu.py", "symbol": "compute_bleu"}, "source_id": "csn:deepmipt/DeepPavlov:deeppavlov/metrics/google_bleu.py:compute_bleu#1757"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/deepmipt/DeepPavlov/blob/f3e4a69a3764d25d2f5bad4f1f1aebc872b00f9c/deeppavlov/metrics/google_bleu.py#L48-L112", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:deepmipt-DeepPavlov:compute_bleu-3d3834c080", "question": "Computes BLEU score of translated segments against one or more references.\n\n Args:\n reference_corpus: list of lists of references for each translation. Each\n reference should be tokenized into a list of tokens.\n translation_corpus: list of translations to score. Each translation\n should be tokenized into a list of tokens.\n max_order: Maximum n-gram order to use when computing BLEU score.\n smooth: Whether or not to apply Lin et al. 2004 smoothing.\n\n Returns:\n 3-Tuple with the BLEU score, n-gram precisions, geometric mean of n-gram\n precisions and brevity penalty.", "scope": {"holder": "deepmipt-DeepPavlov", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:dessibelle/sorl-thumbnail-serializer-field:sorl_thumbnail_serializer/fields.py:HyperlinkedSorlImageField.to_representation#13925", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "sorl_thumbnail_serializer/fields.py", "symbol": "HyperlinkedSorlImageField.to_representation"}, "source_id": "csn:dessibelle/sorl-thumbnail-serializer-field:sorl_thumbnail_serializer/fields.py:HyperlinkedSorlImageField.to_representation#13925"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/dessibelle/sorl-thumbnail-serializer-field/blob/ac36f9de2f1df4c902e7bb371ac5be24d8b50f1f/sorl_thumbnail_serializer/fields.py#L71-L92", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:dessibelle-sorl-thumbnail-serializer-field:HyperlinkedSorlImageField.to_representation-d74f8b7a8f", "question": "Perform the actual serialization.\n\n Args:\n value: the image to transform\n Returns:\n a url pointing at a scaled and cached image", "scope": {"holder": "dessibelle-sorl-thumbnail-serializer-field", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:dialoguemd/multi-method:dialogue/multi_method/__init__.py:method#16542", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "dialogue/multi_method/__init__.py", "symbol": "method"}, "source_id": "csn:dialoguemd/multi-method:dialogue/multi_method/__init__.py:method#16542"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/dialoguemd/multi-method/blob/8b405d4c5ad74a2a36a4ecf88283262defa2e737/dialogue/multi_method/__init__.py#L30-L45", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:dialoguemd-multi-method:method-c2cf942254", "question": "A decorator for a function implementing dispatch_fn for dispatch_key.\n\n If no dispatch_key is specified, the function is used as the\n default dispacth function.", "scope": {"holder": "dialoguemd-multi-method", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:dialoguemd/multi-method:dialogue/multi_method/__init__.py:multi#16541", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "dialogue/multi_method/__init__.py", "symbol": "multi"}, "source_id": "csn:dialoguemd/multi-method:dialogue/multi_method/__init__.py:multi#16541"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/dialoguemd/multi-method/blob/8b405d4c5ad74a2a36a4ecf88283262defa2e737/dialogue/multi_method/__init__.py#L5-L27", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:dialoguemd-multi-method:multi-b3cddf8974", "question": "A decorator for a function to dispatch on.\n\n The value returned by the dispatch function is used to look up the\n implementation function based on its dispatch key.\n\n The dispatch function is available using the `dispatch_fn` function.", "scope": {"holder": "dialoguemd-multi-method", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:disqus/python-phabricator:phabricator/__init__.py:map_param_type#8636", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "phabricator/__init__.py", "symbol": "map_param_type"}, "source_id": "csn:disqus/python-phabricator:phabricator/__init__.py:map_param_type#8636"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/disqus/python-phabricator/blob/ad08e335081531fae053a78a1c708cd11e3e6c49/phabricator/__init__.py#L111-L134", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:disqus-python-phabricator:map_param_type-921f35c17d", "question": "Perform param type mapping\n This requires a bit of logic since this isn't standardized.\n If a type doesn't map, assume str", "scope": {"holder": "disqus-python-phabricator", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:django-inplaceedit/django-inplaceedit:inplaceeditform/fields.py:BaseAdaptorField.empty_value#13137", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "inplaceeditform/fields.py", "symbol": "BaseAdaptorField.empty_value"}, "source_id": "csn:django-inplaceedit/django-inplaceedit:inplaceeditform/fields.py:BaseAdaptorField.empty_value#13137"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/django-inplaceedit/django-inplaceedit/blob/7ba18e7906f56c56395ca07e2486755062efce00/inplaceeditform/fields.py#L143-L151", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:django-inplaceedit-django-inplaceedit:BaseAdaptorField.empty_value-c7569a2779", "question": "Get the text to display when the field is empty.", "scope": {"holder": "django-inplaceedit-django-inplaceedit", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:django-inplaceedit/django-inplaceedit:inplaceeditform/commons.py:get_dict_from_obj#13135", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "inplaceeditform/commons.py", "symbol": "get_dict_from_obj"}, "source_id": "csn:django-inplaceedit/django-inplaceedit:inplaceeditform/commons.py:get_dict_from_obj#13135"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/django-inplaceedit/django-inplaceedit/blob/7ba18e7906f56c56395ca07e2486755062efce00/inplaceeditform/commons.py#L35-L57", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:django-inplaceedit-django-inplaceedit:get_dict_from_obj-21da55bd57", "question": "Edit to get the dict even when the object is a GenericRelatedObjectManager.\n Added the try except.", "scope": {"holder": "django-inplaceedit-django-inplaceedit", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:djangobot/djangobot:djangobot/cli.py:CLI.run#14048", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "djangobot/cli.py", "symbol": "CLI.run"}, "source_id": "csn:djangobot/djangobot:djangobot/cli.py:CLI.run#14048"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/djangobot/djangobot/blob/0ec951891812ea4114c27a08c790f63d0f0fd254/djangobot/cli.py#L38-L57", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:djangobot-djangobot:CLI.run-ed73e1fad3", "question": "Pass in raw arguments, instantiate Slack API and begin client.", "scope": {"holder": "djangobot-djangobot", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:djangobot/djangobot:djangobot/slack.py:SlackAPI.channels#14039", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "djangobot/slack.py", "symbol": "SlackAPI.channels"}, "source_id": "csn:djangobot/djangobot:djangobot/slack.py:SlackAPI.channels#14039"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/djangobot/djangobot/blob/0ec951891812ea4114c27a08c790f63d0f0fd254/djangobot/slack.py#L68-L74", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:djangobot-djangobot:SlackAPI.channels-b4d45d88c8", "question": "List of channels of this slack team", "scope": {"holder": "djangobot-djangobot", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:dogoncouch/lightcli:lightcli.py:choice_input#17522", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "lightcli.py", "symbol": "choice_input"}, "source_id": "csn:dogoncouch/lightcli:lightcli.py:choice_input#17522"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/dogoncouch/lightcli/blob/e63093dfc4f983ec9c9571ff186bf114c1f782c3/lightcli.py#L44-L79", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:dogoncouch-lightcli:choice_input-70ddb37fe9", "question": "Get input from a list of choices (q to quit)", "scope": {"holder": "dogoncouch-lightcli", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:dogoncouch/lightcli:lightcli.py:outfile_input#17525", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "lightcli.py", "symbol": "outfile_input"}, "source_id": "csn:dogoncouch/lightcli:lightcli.py:outfile_input#17525"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/dogoncouch/lightcli/blob/e63093dfc4f983ec9c9571ff186bf114c1f782c3/lightcli.py#L158-L209", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:dogoncouch-lightcli:outfile_input-67b9ef0e14", "question": "Get an output file name as input", "scope": {"holder": "dogoncouch-lightcli", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:domainaware/parsedmarc:parsedmarc/splunk.py:HECClient.save_aggregate_reports_to_splunk#6629", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "parsedmarc/splunk.py", "symbol": "HECClient.save_aggregate_reports_to_splunk"}, "source_id": "csn:domainaware/parsedmarc:parsedmarc/splunk.py:HECClient.save_aggregate_reports_to_splunk#6629"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/domainaware/parsedmarc/blob/ecc9fd434c23d896ccd1f35795ccc047f946ed05/parsedmarc/splunk.py#L58-L123", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:domainaware-parsedmarc:HECClient.save_aggregate_reports_to_splunk-9ea4c6fae0", "question": "Saves aggregate DMARC reports to Splunk\n\n Args:\n aggregate_reports: A list of aggregate report dictionaries\n to save in Splunk", "scope": {"holder": "domainaware-parsedmarc", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:domainaware/parsedmarc:parsedmarc/__init__.py:get_report_zip#6626", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "parsedmarc/__init__.py", "symbol": "get_report_zip"}, "source_id": "csn:domainaware/parsedmarc:parsedmarc/__init__.py:get_report_zip#6626"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/domainaware/parsedmarc/blob/ecc9fd434c23d896ccd1f35795ccc047f946ed05/parsedmarc/__init__.py#L1369-L1411", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:domainaware-parsedmarc:get_report_zip-f0ad2846a7", "question": "Creates a zip file of parsed report output\n\n Args:\n results (OrderedDict): The parsed results\n\n Returns:\n bytes: zip file bytes", "scope": {"holder": "domainaware-parsedmarc", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:dopefishh/pympi:pympi/Elan.py:Eaf.add_cv_description#14261", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pympi/Elan.py", "symbol": "Eaf.add_cv_description"}, "source_id": "csn:dopefishh/pympi:pympi/Elan.py:Eaf.add_cv_description#14261"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/dopefishh/pympi/blob/79c747cde45b5ba203ed93154d8c123ac9c3ef56/pympi/Elan.py#L171-L183", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:dopefishh-pympi:Eaf.add_cv_description-34fc65ece7", "question": "Add a description to a controlled vocabulary.\n\n :param str cv_id: Name of the controlled vocabulary to add the\n description.\n :param str lang_ref: Language reference.\n :param str description: Description, this can be none.\n :throws KeyError: If there is no controlled vocabulary with that id.\n :throws ValueError: If the language provided doesn't exist.", "scope": {"holder": "dopefishh-pympi", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:dopefishh/pympi:pympi/Elan.py:Eaf.get_tier_ids_for_linguistic_type#14293", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pympi/Elan.py", "symbol": "Eaf.get_tier_ids_for_linguistic_type"}, "source_id": "csn:dopefishh/pympi:pympi/Elan.py:Eaf.get_tier_ids_for_linguistic_type#14293"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/dopefishh/pympi/blob/79c747cde45b5ba203ed93154d8c123ac9c3ef56/pympi/Elan.py#L978-L989", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:dopefishh-pympi:Eaf.get_tier_ids_for_linguistic_type-b94610a2d0", "question": "Give a list of all tiers matching a linguistic type.\n\n :param str ling_type: Name of the linguistic type.\n :param str parent: Only match tiers from this parent, when ``None``\n this option will be ignored.\n :returns: List of tiernames.\n :raises KeyError: If a tier or linguistic type is non existent.", "scope": {"holder": "dopefishh-pympi", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:dossier/dossier.store:dossier/store/elastic.py:ElasticStore._create_index#19904", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "dossier/store/elastic.py", "symbol": "ElasticStore._create_index"}, "source_id": "csn:dossier/dossier.store:dossier/store/elastic.py:ElasticStore._create_index#19904"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/dossier/dossier.store/blob/b22ffe2470bba9fcc98a30cb55b437bfa1521e7f/dossier/store/elastic.py#L676-L689", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:dossier-dossier.store:ElasticStore._create_index-691bdb82e8", "question": "Create the index", "scope": {"holder": "dossier-dossier.store", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:dossier/dossier.store:dossier/store/elastic.py:ElasticStore.keyword_scan_ids#19900", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "dossier/store/elastic.py", "symbol": "ElasticStore.keyword_scan_ids"}, "source_id": "csn:dossier/dossier.store:dossier/store/elastic.py:ElasticStore.keyword_scan_ids#19900"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/dossier/dossier.store/blob/b22ffe2470bba9fcc98a30cb55b437bfa1521e7f/dossier/store/elastic.py#L420-L438", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:dossier-dossier.store:ElasticStore.keyword_scan_ids-a49f4308ea", "question": "Keyword scan for ids.\n\n This performs a keyword scan using the query given. A keyword\n scan searches for FCs with terms in each of the query's indexed\n fields.\n\n At least one of ``query_id`` or ``query_fc`` must be provided.\n If ``query_fc`` is ``None``, then the query is retrieved\n automatically corresponding to ``query_id``.\n\n :param str query_id: Optional query id.\n :param query_fc: Optional query feature collection.\n :type query_fc: :class:`dossier.fc.FeatureCollection`\n :rtype: Iterable of ``content_id``", "scope": {"holder": "dossier-dossier.store", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:draios/python-sdc-client:sdcclient/_monitor.py:SdMonitorClient.create_alert#7461", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "sdcclient/_monitor.py", "symbol": "SdMonitorClient.create_alert"}, "source_id": "csn:draios/python-sdc-client:sdcclient/_monitor.py:SdMonitorClient.create_alert#7461"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/draios/python-sdc-client/blob/47f83415842048778939b90944f64386a3bcb205/sdcclient/_monitor.py#L94-L170", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:draios-python-sdc-client:SdMonitorClient.create_alert-6f3e81b24a", "question": "**Description**\n Create a threshold-based alert.\n\n **Arguments**\n - **name**: the alert name. This will appear in the Sysdig Monitor UI and in notification emails.\n - **description**: the alert description. This will appear in the Sysdig Monitor UI and in notification emails.\n - **severity**: syslog-encoded alert severity. This is a number from 0 to 7 where 0 means 'emergency' and 7 is 'debug'.\n - **for_atleast_s**: the number of consecutive seconds the condition must be satisfied for the alert to fire.\n - **condition**: the alert condition, as described here https://app.sysdigcloud.com/apidocs/#!/Alerts/post_api_alerts\n - **segmentby**: a list of Sysdig Monitor segmentation criteria that can be used to apply the alert to multiple entities. For example, segmenting a CPU alert by ['host.mac', 'proc.name'] allows to apply it to any process in any machine.\n - **segment_condition**: When *segmentby* is specified (and therefore the alert will cover multiple entities) this field is used to determine when it will fire. In particular, you have two options for *segment_condition*: **ANY** (the alert will fire when at least one of the monitored entities satisfies the condition) and **ALL** (the alert will fire when all of the monitored entities satisfy the condition).\n - **user_filter**: a boolean expression combining Sysdig Monitor segmentation criteria that makes it possible to reduce the scope of the alert. For example: *kubernetes.namespace.name='production' and container.image='nginx'*.\n - **notify**: the type of notification you want this alert to generate. Options are *EMAIL*, *SNS*, *PAGER_DUTY*, *SYSDIG_DUMP*.\n - **enabled**: if True, the alert will be enabled when created.\n - **annotations**: an optional dictionary of custom properties that you can associate to this alert for automation or management reasons\n - **alert_obj**: an optional fully-formed Alert object of the format returned in an \"alerts\" list by :func:`~SdcClient.get_alerts` This is an alternative to creating the Alert using the individual parameters listed above.\n\n **Success Return Value**\n A dictionary describing the just created alert, with the format described at `this link <https://app.sysdigcloud.com/apidocs/#!/Alerts/post_api_alerts>`__\n\n **Example**\n `examples/create_alert.py <https://github.com/draios/python-sdc-client/blob/master/examples/create_alert.py>`_", "scope": {"holder": "draios-python-sdc-client", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:draios/python-sdc-client:sdcclient/_secure.py:SdSecureClient.add_compliance_task#7450", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "sdcclient/_secure.py", "symbol": "SdSecureClient.add_compliance_task"}, "source_id": "csn:draios/python-sdc-client:sdcclient/_secure.py:SdSecureClient.add_compliance_task#7450"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/draios/python-sdc-client/blob/47f83415842048778939b90944f64386a3bcb205/sdcclient/_secure.py#L754-L777", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:draios-python-sdc-client:SdSecureClient.add_compliance_task-3f1ecb4bf9", "question": "**Description**\n Add a new compliance task.\n\n **Arguments**\n - name: The name of the task e.g. 'Check Docker Compliance'.\n - module_name: The name of the module that implements this task. Separate from task name in case you want to use the same module to run separate tasks with different scopes or schedules. [ 'docker-bench-security', 'kube-bench' ]\n - schedule: The frequency at which this task should run. Expressed as an `ISO 8601 Duration <https://en.wikipedia.org/wiki/ISO_8601#Durations>`_\n - scope: The agent will only run the task on hosts matching this scope or on hosts where containers match this scope.\n - enabled: Whether this task should actually run as defined by its schedule.\n\n **Success Return Value**\n A JSON representation of the compliance task.", "scope": {"holder": "draios-python-sdc-client", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:dreidev/Suggestions:suggestions/views.py:get_suggestions_with_size#21714", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "suggestions/views.py", "symbol": "get_suggestions_with_size"}, "source_id": "csn:dreidev/Suggestions:suggestions/views.py:get_suggestions_with_size#21714"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/dreidev/Suggestions/blob/f04c181dc815d32c35b44c6e1c91521e88a9dd6c/suggestions/views.py#L100-L111", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:dreidev-Suggestions:get_suggestions_with_size-6932efbbcb", "question": "Gets a list with a certain size of suggestions for an object", "scope": {"holder": "dreidev-Suggestions", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:dreidev/Suggestions:suggestions/views.py:update_suggestions_dictionary#21713", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "suggestions/views.py", "symbol": "update_suggestions_dictionary"}, "source_id": "csn:dreidev/Suggestions:suggestions/views.py:update_suggestions_dictionary#21713"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/dreidev/Suggestions/blob/f04c181dc815d32c35b44c6e1c91521e88a9dd6c/suggestions/views.py#L5-L42", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:dreidev-Suggestions:update_suggestions_dictionary-375585ff9b", "question": "Updates the suggestions' dictionary for an object upon visiting its page", "scope": {"holder": "dreidev-Suggestions", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:drestebon/papageorge:lib/papageorge/model.py:find_attacker_slider#18170", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "lib/papageorge/model.py", "symbol": "find_attacker_slider"}, "source_id": "csn:drestebon/papageorge:lib/papageorge/model.py:find_attacker_slider#18170"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/drestebon/papageorge/blob/a30ea59bf6b4f5d151bd3f476a0a8357d89495d4/lib/papageorge/model.py#L256-L289", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:drestebon-papageorge:find_attacker_slider-b471bcaef7", "question": "Find a slider attacker\n\n Parameters\n ----------\n dest_list : list\n To store the results.\n occ_bb : int, bitboard\n Occupancy bitboard.\n piece_bb : int, bitboard\n Bitboard with the position of the attacker piece.\n target_bb : int, bitboard\n Occupancy bitboard without any of the sliders in question.\n pos : int\n Target position.\n pos_map : function\n Mapping between a board position and its position in a single\n rotated/translated rank produced with domain_trans.\n domain_trans : function\n Transformation from a rank/file/diagonal/anti-diagonal containing pos\n to a single rank\n pos_inv_map : function\n Inverse of pos_map", "scope": {"holder": "drestebon-papageorge", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:drewsonne/pyum:pyum/repometadata/base.py:Data.load#15533", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pyum/repometadata/base.py", "symbol": "Data.load"}, "source_id": "csn:drewsonne/pyum:pyum/repometadata/base.py:Data.load#15533"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/drewsonne/pyum/blob/5d2955f86575c9430ab7104211b3d67bd4c0febe/pyum/repometadata/base.py#L64-L71", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:drewsonne-pyum:Data.load-ab5f6fee61", "question": "Load the repo database from the remote source, and then parse it.\n :return:", "scope": {"holder": "drewsonne-pyum", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:drewsonne/pyum:pyum/rpm.py:Package.dependencies#15529", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pyum/rpm.py", "symbol": "Package.dependencies"}, "source_id": "csn:drewsonne/pyum:pyum/rpm.py:Package.dependencies#15529"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/drewsonne/pyum/blob/5d2955f86575c9430ab7104211b3d67bd4c0febe/pyum/rpm.py#L126-L133", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:drewsonne-pyum:Package.dependencies-14a575e636", "question": "Read the contents of the rpm itself\n :return:", "scope": {"holder": "drewsonne-pyum", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:drhagen/parsita:parsita/state.py:Reader.expected_error#15274", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "parsita/state.py", "symbol": "Reader.expected_error"}, "source_id": "csn:drhagen/parsita:parsita/state.py:Reader.expected_error#15274"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/drhagen/parsita/blob/d97414a05541f48231381f607d1d2e6b50781d39/parsita/state.py#L31-L48", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:drhagen-parsita:Reader.expected_error-ff38fc4043", "question": "Generate a basic error to include the current state.\n\n A parser can supply only a representation of what it is expecting to\n this method and the reader will provide the context, including the index\n to the error.\n\n Args:\n expected: A representation of what the parser is currently expecting\n\n Returns:\n A full error message", "scope": {"holder": "drhagen-parsita", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:drhagen/parsita:parsita/util.py:constant#15281", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "parsita/util.py", "symbol": "constant"}, "source_id": "csn:drhagen/parsita:parsita/util.py:constant#15281"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/drhagen/parsita/blob/d97414a05541f48231381f607d1d2e6b50781d39/parsita/util.py#L6-L19", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:drhagen-parsita:constant-908a7bbd3f", "question": "Produce a function that always returns a supplied value.\n\n Args:\n x: Any object.\n\n Returns:\n A function that accepts any number of positional and keyword arguments, discards them, and returns ``x``.", "scope": {"holder": "drhagen-parsita", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:dropseed/combine:combine/jinja_extensions/code.py:CodeHighlightExtension._code_support#16316", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "combine/jinja_extensions/code.py", "symbol": "CodeHighlightExtension._code_support"}, "source_id": "csn:dropseed/combine:combine/jinja_extensions/code.py:CodeHighlightExtension._code_support#16316"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/dropseed/combine/blob/b0d622d09fcb121bc12e65f6044cb3a940b6b052/combine/jinja_extensions/code.py#L23-L47", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:dropseed-combine:CodeHighlightExtension._code_support-cc031ad732", "question": "Helper callback.", "scope": {"holder": "dropseed-combine", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:dropseed/combine:combine/jinja_extensions/markdown.py:MarkdownExtension._support#16313", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "combine/jinja_extensions/markdown.py", "symbol": "MarkdownExtension._support"}, "source_id": "csn:dropseed/combine:combine/jinja_extensions/markdown.py:MarkdownExtension._support#16313"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/dropseed/combine/blob/b0d622d09fcb121bc12e65f6044cb3a940b6b052/combine/jinja_extensions/markdown.py#L21-L32", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:dropseed-combine:MarkdownExtension._support-c11db7c0b6", "question": "Helper callback.", "scope": {"holder": "dropseed-combine", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:dry-python/dependencies:src/dependencies/contrib/_rest_framework.py:api_view#10441", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "src/dependencies/contrib/_rest_framework.py", "symbol": "api_view"}, "source_id": "csn:dry-python/dependencies:src/dependencies/contrib/_rest_framework.py:api_view#10441"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/dry-python/dependencies/blob/297912cbc6482ba26b3104729645f3a2aba5facc/src/dependencies/contrib/_rest_framework.py#L12-L18", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:dry-python-dependencies:api_view-6d8fbbf14a", "question": "Create DRF class-based API view from injector class.", "scope": {"holder": "dry-python-dependencies", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:dry-python/dependencies:src/dependencies/contrib/_flask.py:method_view#10440", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "src/dependencies/contrib/_flask.py", "symbol": "method_view"}, "source_id": "csn:dry-python/dependencies:src/dependencies/contrib/_flask.py:method_view#10440"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/dry-python/dependencies/blob/297912cbc6482ba26b3104729645f3a2aba5facc/src/dependencies/contrib/_flask.py#L7-L12", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:dry-python-dependencies:method_view-f04057ceb9", "question": "Create Flask method based dispatching view from injector class.", "scope": {"holder": "dry-python-dependencies", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:dsoprea/pytzPure:pytzpure/tz_descriptor.py:TzDescriptor.create_from_pytz#18264", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pytzpure/tz_descriptor.py", "symbol": "TzDescriptor.create_from_pytz"}, "source_id": "csn:dsoprea/pytzPure:pytzpure/tz_descriptor.py:TzDescriptor.create_from_pytz#18264"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/dsoprea/pytzPure/blob/ec8f7803ca1025d363ba954905ae7717a0524a0e/pytzpure/tz_descriptor.py#L36-L76", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:dsoprea-pytzPure:TzDescriptor.create_from_pytz-cd0151e7ab", "question": "Create an instance using the result of the timezone() call in \n \"pytz\".", "scope": {"holder": "dsoprea-pytzPure", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:dsoprea/pytzPure:pytzpure/__init__.py:_FixedOffset.normalize#18308", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pytzpure/__init__.py", "symbol": "_FixedOffset.normalize"}, "source_id": "csn:dsoprea/pytzPure:pytzpure/__init__.py:_FixedOffset.normalize#18308"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/dsoprea/pytzPure/blob/ec8f7803ca1025d363ba954905ae7717a0524a0e/pytzpure/__init__.py#L406-L410", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:dsoprea-pytzPure:_FixedOffset.normalize-b1639d5252", "question": "Correct the timezone information on the given datetime", "scope": {"holder": "dsoprea-pytzPure", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:dwavesystems/minorminer:examples/fourcolor.py:chimera_block_quotient#10230", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "examples/fourcolor.py", "symbol": "chimera_block_quotient"}, "source_id": "csn:dwavesystems/minorminer:examples/fourcolor.py:chimera_block_quotient#10230"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/dwavesystems/minorminer/blob/05cac6db180adf8223a613dff808248e3048b07d/examples/fourcolor.py#L83-L126", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:dwavesystems-minorminer:chimera_block_quotient-b00c660f94", "question": "Extract the blocks from a graph, and returns a\n block-quotient graph according to the acceptability\n functions block_good and eblock_good\n\n Inputs:\n G: a networkx graph\n blocks: a tuple of tuples", "scope": {"holder": "dwavesystems-minorminer", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:dwavesystems/minorminer:examples/fourcolor.py:embed_with_quotient#10231", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "examples/fourcolor.py", "symbol": "embed_with_quotient"}, "source_id": "csn:dwavesystems/minorminer:examples/fourcolor.py:embed_with_quotient#10231"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/dwavesystems/minorminer/blob/05cac6db180adf8223a613dff808248e3048b07d/examples/fourcolor.py#L129-L202", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:dwavesystems-minorminer:embed_with_quotient-a971fa0c06", "question": "Produce an embedding in target_graph suitable to\n check if source_graph is 4-colorable. More generally,\n if target_graph is a (M,N,L) Chimera subgraph, the\n test is for L-colorability. This depends heavily upon\n the Chimera structure\n\n Inputs:\n source_graph, target_graph: networkx graphs\n M,N,L: integers defining the base chimera topology\n\n Outputs:\n emb: a dictionary mapping (v,i)", "scope": {"holder": "dwavesystems-minorminer", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:dwhswenson/autorelease:autorelease/git_repo_checks.py:GitReleaseChecks.reasonable_desired_version#16555", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "autorelease/git_repo_checks.py", "symbol": "GitReleaseChecks.reasonable_desired_version"}, "source_id": "csn:dwhswenson/autorelease:autorelease/git_repo_checks.py:GitReleaseChecks.reasonable_desired_version#16555"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/dwhswenson/autorelease/blob/339c32c3934e4751857f35aaa2bfffaaaf3b39c4/autorelease/git_repo_checks.py#L50-L96", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:dwhswenson-autorelease:GitReleaseChecks.reasonable_desired_version-763bb9c791", "question": "Determine whether the desired version is a reasonable next version.\n\n Parameters\n ----------\n desired_version: str\n the proposed next version name", "scope": {"holder": "dwhswenson-autorelease", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:dwhswenson/autorelease:setup.py:get_git_version#16483", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "setup.py", "symbol": "get_git_version"}, "source_id": "csn:dwhswenson/autorelease:setup.py:get_git_version#16483"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/dwhswenson/autorelease/blob/339c32c3934e4751857f35aaa2bfffaaaf3b39c4/setup.py#L70-L104", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:dwhswenson-autorelease:get_git_version-eda9712bf8", "question": "Return the git hash as a string.\n\n Apparently someone got this from numpy's setup.py. It has since been\n modified a few times.", "scope": {"holder": "dwhswenson-autorelease", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:eagleflo/adjutant:adjutant.py:SC2Replay.get_duration#16637", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "adjutant.py", "symbol": "SC2Replay.get_duration"}, "source_id": "csn:eagleflo/adjutant:adjutant.py:SC2Replay.get_duration#16637"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/eagleflo/adjutant/blob/85d800d9979fa122e0888af48c2e6a697f9da458/adjutant.py#L241-L249", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:eagleflo-adjutant:SC2Replay.get_duration-5e7f053958", "question": "Transform duration into a human-readable form.", "scope": {"holder": "eagleflo-adjutant", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:eagleflo/adjutant:adjutant.py:read_table#16635", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "adjutant.py", "symbol": "read_table"}, "source_id": "csn:eagleflo/adjutant:adjutant.py:read_table#16635"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/eagleflo/adjutant/blob/85d800d9979fa122e0888af48c2e6a697f9da458/adjutant.py#L122-L146", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:eagleflo-adjutant:read_table-8305b945ff", "question": "Read a table structure.\n\n These are used by Blizzard to collect pieces of data together. Each\n value is prefixed by two bytes, first denoting (doubled) index and the\n second denoting some sort of key -- so far it has always been '09'. The\n actual value follows as a Variable-Length Quantity, also known as uintvar.\n The actual value is also doubled.\n\n In some tables the keys might jump from 0A 09 to 04 09 for example.\n I have no idea why this happens, as the next logical key is 0C. Perhaps\n it's a table in a table? Some sort of headers might exist for these\n tables, I'd imagine at least denoting length. Further research required.", "scope": {"holder": "eagleflo-adjutant", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:eclarke/melt:melting.py:temp#18893", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "melting.py", "symbol": "temp"}, "source_id": "csn:eclarke/melt:melting.py:temp#18893"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/eclarke/melt/blob/31520349be0296c7a6aab0010016f093f866b999/melting.py#L72-L166", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:eclarke-melt:temp-d6dfbb7a69", "question": "Returns the DNA/DNA melting temp using nearest-neighbor thermodynamics.\n\n This function returns better results than EMBOSS DAN because it uses updated\n thermodynamics values and takes into account initialization parameters from\n the work of SantaLucia (1998).\n\n Corrects for mono- and divalent cation concentrations.\n\n Arguments:\n - DNA_c: DNA concentration [nM]\n - Na_c: Na+ concentration [mM]\n - Mg_c: Mg2+ concentration [mM]\n - dNTPs_c: dNTP concentration [mM]\n - correction: correct for cation concentration?", "scope": {"holder": "eclarke-melt", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:ecometrica/grandfatherson:grandfatherson/filters.py:Days.mask#16782", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "grandfatherson/filters.py", "symbol": "Days.mask"}, "source_id": "csn:ecometrica/grandfatherson:grandfatherson/filters.py:Days.mask#16782"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/ecometrica/grandfatherson/blob/b166e4e44887960c3066ebd28eecadfae19561e1/grandfatherson/filters.py#L124-L129", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:ecometrica-grandfatherson:Days.mask-f124e127bb", "question": "Return a datetime with the same value as ``dt``, to a\n resolution of days.", "scope": {"holder": "ecometrica-grandfatherson", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:ecometrica/grandfatherson:grandfatherson/filters.py:Years.start#16786", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "grandfatherson/filters.py", "symbol": "Years.start"}, "source_id": "csn:ecometrica/grandfatherson:grandfatherson/filters.py:Years.start#16786"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/ecometrica/grandfatherson/blob/b166e4e44887960c3066ebd28eecadfae19561e1/grandfatherson/filters.py#L193-L197", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:ecometrica-grandfatherson:Years.start-7caf3e7f5d", "question": "Return the starting datetime: ``number`` of years before ``now``.", "scope": {"holder": "ecometrica-grandfatherson", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:edavis/django-override-settings:override_settings/__init__.py:override_settings.get_global_settings#14461", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "override_settings/__init__.py", "symbol": "override_settings.get_global_settings"}, "source_id": "csn:edavis/django-override-settings:override_settings/__init__.py:override_settings.get_global_settings#14461"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/edavis/django-override-settings/blob/016a2ba44cf7132d3aeefbfeddaf201217b1d4b6/override_settings/__init__.py#L14-L19", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:edavis-django-override-settings:override_settings.get_global_settings-879a46e4d3", "question": "Return a dictionary of all global_settings values.", "scope": {"holder": "edavis-django-override-settings", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:edavis/django-override-settings:override_settings/__init__.py:with_apps#14459", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "override_settings/__init__.py", "symbol": "with_apps"}, "source_id": "csn:edavis/django-override-settings:override_settings/__init__.py:with_apps#14459"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/edavis/django-override-settings/blob/016a2ba44cf7132d3aeefbfeddaf201217b1d4b6/override_settings/__init__.py#L66-L73", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:edavis-django-override-settings:with_apps-efafd2966c", "question": "Class decorator that makes sure the passed apps are present in\n INSTALLED_APPS.", "scope": {"holder": "edavis-django-override-settings", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:edoburu/django-debugtools:debugtools/formatter.py:DebugPrettyPrinter._format#14499", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "debugtools/formatter.py", "symbol": "DebugPrettyPrinter._format"}, "source_id": "csn:edoburu/django-debugtools:debugtools/formatter.py:DebugPrettyPrinter._format#14499"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/edoburu/django-debugtools/blob/5c609c00fa9954330cd135fc62a1e18b8e7fea8a/debugtools/formatter.py#L384-L391", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:edoburu-django-debugtools:DebugPrettyPrinter._format-8151c39751", "question": "Recursive part of the formatting", "scope": {"holder": "edoburu-django-debugtools", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:edoburu/django-debugtools:debugtools/formatter.py:_format_object#14495", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "debugtools/formatter.py", "symbol": "_format_object"}, "source_id": "csn:edoburu/django-debugtools:debugtools/formatter.py:_format_object#14495"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/edoburu/django-debugtools/blob/5c609c00fa9954330cd135fc62a1e18b8e7fea8a/debugtools/formatter.py#L155-L246", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:edoburu-django-debugtools:_format_object-21ab068d59", "question": "# Instead of just printing <SomeType at 0xfoobar>, expand the fields.", "scope": {"holder": "edoburu-django-debugtools", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:edoburu/django-tag-parser:tag_parser/basetags.py:BaseAssignmentOrInclusionNode.get_context_data#15316", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "tag_parser/basetags.py", "symbol": "BaseAssignmentOrInclusionNode.get_context_data"}, "source_id": "csn:edoburu/django-tag-parser:tag_parser/basetags.py:BaseAssignmentOrInclusionNode.get_context_data#15316"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/edoburu/django-tag-parser/blob/c24256cfdd0248434f2e3df3444ed9f945d4181f/tag_parser/basetags.py#L388-L401", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:edoburu-django-tag-parser:BaseAssignmentOrInclusionNode.get_context_data-5d2a0acff9", "question": "Return the context data for the inclusion tag.\n\n Returns ``{'value': self.get_value(parent_context, *tag_args, **tag_kwargs)}`` by default.", "scope": {"holder": "edoburu-django-tag-parser", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:edoburu/django-tag-parser:tag_parser/basetags.py:BaseNode.parse#15307", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "tag_parser/basetags.py", "symbol": "BaseNode.parse"}, "source_id": "csn:edoburu/django-tag-parser:tag_parser/basetags.py:BaseNode.parse#15307"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/edoburu/django-tag-parser/blob/c24256cfdd0248434f2e3df3444ed9f945d4181f/tag_parser/basetags.py#L128-L146", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:edoburu-django-tag-parser:BaseNode.parse-a11f58e5f5", "question": "Parse the tag, instantiate the class.\n\n :type parser: django.template.base.Parser\n :type token: django.template.base.Token", "scope": {"holder": "edoburu-django-tag-parser", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:edx/ecommerce-worker:ecommerce_worker/cache.py:Cache.set#12097", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "ecommerce_worker/cache.py", "symbol": "Cache.set"}, "source_id": "csn:edx/ecommerce-worker:ecommerce_worker/cache.py:Cache.set#12097"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/edx/ecommerce-worker/blob/55246961d805b1f64d661a5c0bae0a216589401f/ecommerce_worker/cache.py#L53-L66", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:edx-ecommerce-worker:Cache.set-bfeab6031e", "question": "Save an object in the cache\n\n Arguments:\n key (str): Cache key\n value (object): object to cache\n duration (int): time in seconds to keep object in cache", "scope": {"holder": "edx-ecommerce-worker", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:edx/ecommerce-worker:ecommerce_worker/fulfillment/v1/tasks.py:fulfill_order#12094", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "ecommerce_worker/fulfillment/v1/tasks.py", "symbol": "fulfill_order"}, "source_id": "csn:edx/ecommerce-worker:ecommerce_worker/fulfillment/v1/tasks.py:fulfill_order#12094"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/edx/ecommerce-worker/blob/55246961d805b1f64d661a5c0bae0a216589401f/ecommerce_worker/fulfillment/v1/tasks.py#L31-L62", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:edx-ecommerce-worker:fulfill_order-9150081daf", "question": "Fulfills an order.\n\n Arguments:\n order_number (str): Order number indicating which order to fulfill.\n\n Returns:\n None", "scope": {"holder": "edx-ecommerce-worker", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:edx/web-fragments:web_fragments/examples/views.py:ExampleFragmentView.render_to_fragment#12204", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "web_fragments/examples/views.py", "symbol": "ExampleFragmentView.render_to_fragment"}, "source_id": "csn:edx/web-fragments:web_fragments/examples/views.py:ExampleFragmentView.render_to_fragment#12204"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/edx/web-fragments/blob/42d760d700d70465e4e573b7b41442d8802ccd3c/web_fragments/examples/views.py#L22-L29", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:edx-web-fragments:ExampleFragmentView.render_to_fragment-db4ebdc9a4", "question": "Returns a simple fragment", "scope": {"holder": "edx-web-fragments", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:edx/web-fragments:web_fragments/fragment.py:Fragment.resources#12205", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "web_fragments/fragment.py", "symbol": "Fragment.resources"}, "source_id": "csn:edx/web-fragments:web_fragments/fragment.py:Fragment.resources#12205"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/edx/web-fragments/blob/42d760d700d70465e4e573b7b41442d8802ccd3c/web_fragments/fragment.py#L44-L52", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:edx-web-fragments:Fragment.resources-ceef2e27d0", "question": "Returns list of unique `FragmentResource`s by order of first appearance.", "scope": {"holder": "edx-web-fragments", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:eecs-autograder/autograder-sandbox:autograder_sandbox/autograder_sandbox.py:AutograderSandbox.add_and_rename_file#13019", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "autograder_sandbox/autograder_sandbox.py", "symbol": "AutograderSandbox.add_and_rename_file"}, "source_id": "csn:eecs-autograder/autograder-sandbox:autograder_sandbox/autograder_sandbox.py:AutograderSandbox.add_and_rename_file#13019"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/eecs-autograder/autograder-sandbox/blob/230e806e3740e2aaf5f5568dd6a265558f165c63/autograder_sandbox/autograder_sandbox.py#L347-L356", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:eecs-autograder-autograder-sandbox:AutograderSandbox.add_and_rename_file-b57ca38376", "question": "Copies the specified file into the working directory of this\n sandbox and renames it to new_filename.", "scope": {"holder": "eecs-autograder-autograder-sandbox", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:eecs-autograder/autograder-sandbox:autograder_sandbox/autograder_sandbox.py:AutograderSandbox.allow_network_access#13016", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "autograder_sandbox/autograder_sandbox.py", "symbol": "AutograderSandbox.allow_network_access"}, "source_id": "csn:eecs-autograder/autograder-sandbox:autograder_sandbox/autograder_sandbox.py:AutograderSandbox.allow_network_access#13016"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/eecs-autograder/autograder-sandbox/blob/230e806e3740e2aaf5f5568dd6a265558f165c63/autograder_sandbox/autograder_sandbox.py#L180-L188", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:eecs-autograder-autograder-sandbox:AutograderSandbox.allow_network_access-ac346ad9d4", "question": "Raises ValueError if this sandbox instance is currently running.", "scope": {"holder": "eecs-autograder-autograder-sandbox", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:egh/ledger-autosync:ledgerautosync/converter.py:OfxConverter.convert#6553", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "ledgerautosync/converter.py", "symbol": "OfxConverter.convert"}, "source_id": "csn:egh/ledger-autosync:ledgerautosync/converter.py:OfxConverter.convert#6553"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/egh/ledger-autosync/blob/7a303f3a693261d10f677c01fb08f35c105a1e1b/ledgerautosync/converter.py#L403-L507", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:egh-ledger-autosync:OfxConverter.convert-170f6dbce0", "question": "Convert an OFX Transaction to a posting", "scope": {"holder": "egh-ledger-autosync", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:egh/ledger-autosync:ledgerautosync/cli.py:find_ledger_file#6554", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "ledgerautosync/cli.py", "symbol": "find_ledger_file"}, "source_id": "csn:egh/ledger-autosync:ledgerautosync/cli.py:find_ledger_file#6554"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/egh/ledger-autosync/blob/7a303f3a693261d10f677c01fb08f35c105a1e1b/ledgerautosync/cli.py#L40-L55", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:egh-ledger-autosync:find_ledger_file-00a52c9943", "question": "Returns main ledger file path or raise exception if it cannot be \\\nfound.", "scope": {"holder": "egh-ledger-autosync", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:eisber/sarplus:python/pysarplus/SARPlus.py:SARPlus.fit#15720", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "python/pysarplus/SARPlus.py", "symbol": "SARPlus.fit"}, "source_id": "csn:eisber/sarplus:python/pysarplus/SARPlus.py:SARPlus.fit#15720"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/eisber/sarplus/blob/945a1182e00a8bf70414fc3600086316701777f9/python/pysarplus/SARPlus.py#L48-L207", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:eisber-sarplus:SARPlus.fit-823e35607f", "question": "Main fit method for SAR. Expects the dataframes to have row_id, col_id columns which are indexes,\n i.e. contain the sequential integer index of the original alphanumeric user and item IDs.\n Dataframe also contains rating and timestamp as floats; timestamp is in seconds since Epoch by default.\n\n Arguments:\n df (pySpark.DataFrame): input dataframe which contains the index of users and items.", "scope": {"holder": "eisber-sarplus", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:eisber/sarplus:python/pysarplus/SARPlus.py:SARPlus.get_user_affinity#15721", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "python/pysarplus/SARPlus.py", "symbol": "SARPlus.get_user_affinity"}, "source_id": "csn:eisber/sarplus:python/pysarplus/SARPlus.py:SARPlus.get_user_affinity#15721"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/eisber/sarplus/blob/945a1182e00a8bf70414fc3600086316701777f9/python/pysarplus/SARPlus.py#L209-L236", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:eisber-sarplus:SARPlus.get_user_affinity-e6825bbf1a", "question": "Prepare test set for C++ SAR prediction code.\n Find all items the test users have seen in the past.\n\n Arguments:\n test (pySpark.DataFrame): input dataframe which contains test users.", "scope": {"holder": "eisber-sarplus", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:ekmmetering/ekmmeters:ekmmeters.py:Meter.assignHolidayDate#15191", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "ekmmeters.py", "symbol": "Meter.assignHolidayDate"}, "source_id": "csn:ekmmetering/ekmmeters:ekmmeters.py:Meter.assignHolidayDate#15191"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/ekmmetering/ekmmeters/blob/b3748bdf30263bfa46ea40157bdf8df2522e1904/ekmmeters.py#L2546-L2574", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:ekmmetering-ekmmeters:Meter.assignHolidayDate-cbca0adf5b", "question": "Set a singe holiday day and month in object buffer.\n\n There is no class style enum for holidays.\n\n Args:\n holiday (int): 0-19 or range(Extents.Holidays).\n month (int): Month 1-12.\n day (int): Day 1-31\n\n Returns:\n bool: True on completion.", "scope": {"holder": "ekmmetering-ekmmeters", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:ekmmetering/ekmmeters:ekmmeters.py:Meter.unregisterObserver#15178", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "ekmmeters.py", "symbol": "Meter.unregisterObserver"}, "source_id": "csn:ekmmetering/ekmmeters:ekmmeters.py:Meter.unregisterObserver#15178"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/ekmmetering/ekmmeters/blob/b3748bdf30263bfa46ea40157bdf8df2522e1904/ekmmeters.py#L1931-L1939", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:ekmmetering-ekmmeters:Meter.unregisterObserver-fb9f1f24c9", "question": "Remove an observer from the meter update() chain.\n\n Args:\n observer (MeterObserver): Subclassed MeterObserver.", "scope": {"holder": "ekmmetering-ekmmeters", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:ekzhu/datasketch:datasketch/experimental/aio/lsh.py:AsyncMinHashLSH.close#4667", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "datasketch/experimental/aio/lsh.py", "symbol": "AsyncMinHashLSH.close"}, "source_id": "csn:ekzhu/datasketch:datasketch/experimental/aio/lsh.py:AsyncMinHashLSH.close#4667"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/ekzhu/datasketch/blob/b3e4129987890a2beb04f2c0b6dc618ae35f2e14/datasketch/experimental/aio/lsh.py#L167-L178", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:ekzhu-datasketch:AsyncMinHashLSH.close-1eec399291", "question": "Cleanup client resources and disconnect from AsyncMinHashLSH storage.", "scope": {"holder": "ekzhu-datasketch", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:ekzhu/datasketch:datasketch/lshforest.py:MinHashLSHForest._binary_search#4666", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "datasketch/lshforest.py", "symbol": "MinHashLSHForest._binary_search"}, "source_id": "csn:ekzhu/datasketch:datasketch/lshforest.py:MinHashLSHForest._binary_search#4666"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/ekzhu/datasketch/blob/b3e4129987890a2beb04f2c0b6dc618ae35f2e14/datasketch/lshforest.py#L113-L124", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:ekzhu-datasketch:MinHashLSHForest._binary_search-046d932844", "question": "https://golang.org/src/sort/search.go?s=2247:2287#L49", "scope": {"holder": "ekzhu-datasketch", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:ellisonleao/vl:vl/cli.py:main#9799", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "vl/cli.py", "symbol": "main"}, "source_id": "csn:ellisonleao/vl:vl/cli.py:main#9799"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/ellisonleao/vl/blob/2650b1fc9172a1fa46aaef4e66bd944bcc0a6ece/vl/cli.py#L90-L213", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:ellisonleao-vl:main-6f9f267bc8", "question": "Examples:\n simple call\n $ vl README.md\n\n Adding debug outputs\n\n $ vl README.md --debug\n\n Adding a custom timeout for each url. time on seconds.\n\n $ vl README.md -t 3\n\n Adding a custom size param, to add throttle n requests per time\n\n $ vl README -s 1000\n\n Skipping some error codes. This will allow 500 and 404 responses to\n be ignored\n\n $ vl README.md -a 500,404\n\n Adding Whitelists\n\n $ vl README.md -w server1.com,server2.com", "scope": {"holder": "ellisonleao-vl", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:elliterate/capybara.py:capybara/node/actions.py:ActionsMixin._check_with_label#14010", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "capybara/node/actions.py", "symbol": "ActionsMixin._check_with_label"}, "source_id": "csn:elliterate/capybara.py:capybara/node/actions.py:ActionsMixin._check_with_label#14010"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/elliterate/capybara.py/blob/0c6ae449cc37e4445ec3cd6af95674533beedc6c/capybara/node/actions.py#L197-L234", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:elliterate-capybara.py:ActionsMixin._check_with_label-3895e62ae3", "question": "Args:\n selector (str): The selector for the type of element that should be checked/unchecked.\n checked (bool): Whether the element should be checked.\n locator (str, optional): Which element to check.\n allow_label_click (bool, optional): Attempt to click the label to toggle state if\n element is non-visible. Defaults to :data:`capybara.automatic_label_click`.\n visible (bool | str, optional): The desired element visibility. Defaults to\n :data:`capybara.ignore_hidden_elements`.\n wait (int | float, optional): The number of seconds to wait to check the element.\n Defaults to :data:`capybara.default_max_wait_time`.\n **kwargs: Arbitrary keyword arguments for :class:`SelectorQuery`.", "scope": {"holder": "elliterate-capybara.py", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:elliterate/capybara.py:capybara/queries/selector_query.py:SelectorQuery.description#13944", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "capybara/queries/selector_query.py", "symbol": "SelectorQuery.description"}, "source_id": "csn:elliterate/capybara.py:capybara/queries/selector_query.py:SelectorQuery.description#13944"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/elliterate/capybara.py/blob/0c6ae449cc37e4445ec3cd6af95674533beedc6c/capybara/queries/selector_query.py#L101-L113", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:elliterate-capybara.py:SelectorQuery.description-51b9bce84c", "question": "str: A long description of this query.", "scope": {"holder": "elliterate-capybara.py", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:ellmetha/neojsonrpc:neojsonrpc/client.py:Client._call#13729", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "neojsonrpc/client.py", "symbol": "Client._call"}, "source_id": "csn:ellmetha/neojsonrpc:neojsonrpc/client.py:Client._call#13729"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/ellmetha/neojsonrpc/blob/e369b633a727482d5f9e310f0c3337ae5f7265db/neojsonrpc/client.py#L334-L378", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:ellmetha-neojsonrpc:Client._call-288df97a48", "question": "Calls the JSON-RPC endpoint.", "scope": {"holder": "ellmetha-neojsonrpc", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:ellmetha/neojsonrpc:neojsonrpc/client.py:Client.invoke#13724", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "neojsonrpc/client.py", "symbol": "Client.invoke"}, "source_id": "csn:ellmetha/neojsonrpc:neojsonrpc/client.py:Client.invoke#13724"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/ellmetha/neojsonrpc/blob/e369b633a727482d5f9e310f0c3337ae5f7265db/neojsonrpc/client.py#L258-L275", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:ellmetha-neojsonrpc:Client.invoke-f94072acef", "question": "Invokes a contract with given parameters and returns the result.\n\n It should be noted that the name of the function invoked in the contract should be part of\n paramaters.\n\n :param script_hash: contract script hash\n :param params: list of paramaters to be passed in to the smart contract\n :type script_hash: str\n :type params: list\n :return: result of the invocation\n :rtype: dictionary", "scope": {"holder": "ellmetha-neojsonrpc", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:elyase/masstable:masstable/masstable.py:Table.at#19181", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "masstable/masstable.py", "symbol": "Table.at"}, "source_id": "csn:elyase/masstable:masstable/masstable.py:Table.at#19181"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/elyase/masstable/blob/3eb72b22cd3337bc5c6bb95bb7bb73fdbe6ae9e2/masstable/masstable.py#L245-L266", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:elyase-masstable:Table.at-f5a95528d4", "question": "Return a selection of the Table at positions given by ``nuclei``\n\n Parameters\n ----------\n nuclei: list of tuples\n A list where each element is tuple of the form (Z,N)\n\n Example\n -------\n Return binding energies at magic nuclei:\n\n >>> magic_nuclei = [(20,28), (50,50), (50,82), (82,126)]\n >>> Table('AME2012').binding_energy.at(magic_nuclei)\n Z N\n 20 28 416.014215\n 50 50 825.325172\n 82 1102.876416\n 82 126 1636.486450", "scope": {"holder": "elyase-masstable", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:elyase/masstable:masstable/masstable.py:Table.not_in#19183", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "masstable/masstable.py", "symbol": "Table.not_in"}, "source_id": "csn:elyase/masstable:masstable/masstable.py:Table.not_in#19183"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/elyase/masstable/blob/3eb72b22cd3337bc5c6bb95bb7bb73fdbe6ae9e2/masstable/masstable.py#L309-L325", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:elyase-masstable:Table.not_in-e01c26385e", "question": "Select nuclei not in table\n\n Parameters\n ----------\n table: Table, Table object from where nuclei should be removed\n\n Example:\n ----------\n Find the new nuclei in AME2003 with Z,N >= 8:\n\n >>> Table('AME2003').not_in(Table('AME1995'))[8:,8:].count\n 389", "scope": {"holder": "elyase-masstable", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:eng-tools/geofound:geofound/capacity.py:capacity_hansen_1970#13028", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "geofound/capacity.py", "symbol": "capacity_hansen_1970"}, "source_id": "csn:eng-tools/geofound:geofound/capacity.py:capacity_hansen_1970#13028"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/eng-tools/geofound/blob/6b1b097d5db998907bdcb5b4798fb4629674c770/geofound/capacity.py#L202-L313", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:eng-tools-geofound:capacity_hansen_1970-706ffa9bcb", "question": "Calculates the foundation capacity according Hansen (1970)\n Ref: http://bestengineeringprojects.com/civil-projects/\n hansens-bearing-capacity-theory/\n\n :param sl: Soil object\n :param fd: Foundation object\n :param h_l: Horizontal load parallel to length\n :param h_b: Horizontal load parallel to width\n :param vertical_load: Vertical load\n :param slope: ground slope\n :param base_tilt: The slope of the underside of the foundation\n :param verbose: verbosity\n :return: ultimate bearing stress", "scope": {"holder": "eng-tools-geofound", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:eng-tools/geofound:geofound/capacity.py:capacity_terzaghi_1943#13027", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "geofound/capacity.py", "symbol": "capacity_terzaghi_1943"}, "source_id": "csn:eng-tools/geofound:geofound/capacity.py:capacity_terzaghi_1943#13027"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/eng-tools/geofound/blob/6b1b097d5db998907bdcb5b4798fb4629674c770/geofound/capacity.py#L143-L199", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:eng-tools-geofound:capacity_terzaghi_1943-feae9f2312", "question": "Calculates the foundation capacity according Terzaghi (1943)\n Ref: http://geo.cv.nctu.edu.tw/foundation/\n download/BearingCapacityOfFoundations.pdf\n\n :param sl: Soil object\n :param fd: Foundation object\n :param round_footing: if True, then foundation is round\n :param verbose: verbosity\n :return: ultimate bearing stress\n Note: the shape factor of 1.3 is used for aspect ratio > 6", "scope": {"holder": "eng-tools-geofound", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:erichiggins/gaek:gaek/ndb_json.py:NdbDecoder.decode#13455", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "gaek/ndb_json.py", "symbol": "NdbDecoder.decode"}, "source_id": "csn:erichiggins/gaek:gaek/ndb_json.py:NdbDecoder.decode#13455"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/erichiggins/gaek/blob/eb6bbc2d2688302834f97fd97891592e8b9659f2/gaek/ndb_json.py#L162-L169", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:erichiggins-gaek:NdbDecoder.decode-3fc3651231", "question": "Override of the default decode method that also uses decode_date.", "scope": {"holder": "erichiggins-gaek", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:erichiggins/gaek:gaek/ndb_json.py:encode_model#13451", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "gaek/ndb_json.py", "symbol": "encode_model"}, "source_id": "csn:erichiggins/gaek:gaek/ndb_json.py:encode_model#13451"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/erichiggins/gaek/blob/eb6bbc2d2688302834f97fd97891592e8b9659f2/gaek/ndb_json.py#L53-L63", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:erichiggins-gaek:encode_model-69bae260d4", "question": "Encode objects like ndb.Model which have a `.to_dict()` method.", "scope": {"holder": "erichiggins-gaek", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:ethereum/py_ecc:py_ecc/bls/utils.py:compress_G1#7635", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "py_ecc/bls/utils.py", "symbol": "compress_G1"}, "source_id": "csn:ethereum/py_ecc:py_ecc/bls/utils.py:compress_G1#7635"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/ethereum/py_ecc/blob/2088796c59574b256dc8e18f8c9351bc3688ca71/py_ecc/bls/utils.py#L99-L115", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:ethereum-py_ecc:compress_G1-3a243647b1", "question": "A compressed point is a 384-bit integer with the bit order (c_flag, b_flag, a_flag, x),\n where the c_flag bit is always set to 1,\n the b_flag bit indicates infinity when set to 1,\n the a_flag bit helps determine the y-coordinate when decompressing,\n and the 381-bit integer x is the x-coordinate of the point.", "scope": {"holder": "ethereum-py_ecc", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:ethereum/py_ecc:py_ecc/bls/utils.py:decompress_G2#7638", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "py_ecc/bls/utils.py", "symbol": "decompress_G2"}, "source_id": "csn:ethereum/py_ecc:py_ecc/bls/utils.py:decompress_G2#7638"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/ethereum/py_ecc/blob/2088796c59574b256dc8e18f8c9351bc3688ca71/py_ecc/bls/utils.py#L189-L219", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:ethereum-py_ecc:decompress_G2-f4e827add9", "question": "Recovers x and y coordinates from the compressed point (z1, z2).", "scope": {"holder": "ethereum-py_ecc", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:etsinko/pymonoprice:pymonoprice/__init__.py:get_async_monoprice#15462", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pymonoprice/__init__.py", "symbol": "get_async_monoprice"}, "source_id": "csn:etsinko/pymonoprice:pymonoprice/__init__.py:get_async_monoprice#15462"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/etsinko/pymonoprice/blob/7e54cd349942bfe42a4c9aad0ad814ffff2b5109/pymonoprice/__init__.py#L270-L385", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:etsinko-pymonoprice:get_async_monoprice-8932a7ff69", "question": "Return asynchronous version of Monoprice interface\n :param port_url: serial port, i.e. '/dev/ttyUSB0'\n :return: asynchronous implementation of Monoprice interface", "scope": {"holder": "etsinko-pymonoprice", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:etsinko/pymonoprice:pymonoprice/__init__.py:get_monoprice#15461", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pymonoprice/__init__.py", "symbol": "get_monoprice"}, "source_id": "csn:etsinko/pymonoprice:pymonoprice/__init__.py:get_monoprice#15461"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/etsinko/pymonoprice/blob/7e54cd349942bfe42a4c9aad0ad814ffff2b5109/pymonoprice/__init__.py#L169-L266", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:etsinko-pymonoprice:get_monoprice-ec276610e3", "question": "Return synchronous version of Monoprice interface\n :param port_url: serial port, i.e. '/dev/ttyUSB0'\n :return: synchronous implementation of Monoprice interface", "scope": {"holder": "etsinko-pymonoprice", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:eyeseast/python-frontmatter:frontmatter/default_handlers.py:JSONHandler.export#7876", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "frontmatter/default_handlers.py", "symbol": "JSONHandler.export"}, "source_id": "csn:eyeseast/python-frontmatter:frontmatter/default_handlers.py:JSONHandler.export#7876"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/eyeseast/python-frontmatter/blob/c318e583c48599eb597e0ad59c5d972258c3febc/frontmatter/default_handlers.py#L238-L242", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:eyeseast-python-frontmatter:JSONHandler.export-14013f3663", "question": "Turn metadata into JSON", "scope": {"holder": "eyeseast-python-frontmatter", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:eyeseast/python-frontmatter:frontmatter/__init__.py:dump#7871", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "frontmatter/__init__.py", "symbol": "dump"}, "source_id": "csn:eyeseast/python-frontmatter:frontmatter/__init__.py:dump#7871"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/eyeseast/python-frontmatter/blob/c318e583c48599eb597e0ad59c5d972258c3febc/frontmatter/__init__.py#L133-L159", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:eyeseast-python-frontmatter:dump-eedd06ec38", "question": "Serialize :py:class:`post <frontmatter.Post>` to a string and write to a file-like object.\n Text will be encoded on the way out (utf-8 by default).\n\n ::\n\n >>> from io import BytesIO\n >>> f = BytesIO()\n >>> frontmatter.dump(post, f)\n >>> print(f.getvalue())\n ---\n excerpt: tl;dr\n layout: post\n title: Hello, world!\n ---\n Well, hello there, world.", "scope": {"holder": "eyeseast-python-frontmatter", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:farzadghanei/statsd-metrics:statsdmetrics/client/__init__.py:AbstractClient.gauge#17795", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "statsdmetrics/client/__init__.py", "symbol": "AbstractClient.gauge"}, "source_id": "csn:farzadghanei/statsd-metrics:statsdmetrics/client/__init__.py:AbstractClient.gauge#17795"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/farzadghanei/statsd-metrics/blob/153ff37b79777f208e49bb9d3fb737ba52b99f98/statsdmetrics/client/__init__.py#L186-L199", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:farzadghanei-statsd-metrics:AbstractClient.gauge-cd31ddee8e", "question": "Send a Gauge metric with the specified value", "scope": {"holder": "farzadghanei-statsd-metrics", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:farzadghanei/statsd-metrics:statsdmetrics/client/__init__.py:BatchClient.unit_client#17800", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "statsdmetrics/client/__init__.py", "symbol": "BatchClient.unit_client"}, "source_id": "csn:farzadghanei/statsd-metrics:statsdmetrics/client/__init__.py:BatchClient.unit_client#17800"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/farzadghanei/statsd-metrics/blob/153ff37b79777f208e49bb9d3fb737ba52b99f98/statsdmetrics/client/__init__.py#L352-L358", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:farzadghanei-statsd-metrics:BatchClient.unit_client-6257d3ec3c", "question": "Return a client with same settings of the batch client", "scope": {"holder": "farzadghanei-statsd-metrics", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:fastmonkeys/stellar:stellar/command.py:gc#8613", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "stellar/command.py", "symbol": "gc"}, "source_id": "csn:fastmonkeys/stellar:stellar/command.py:gc#8613"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/fastmonkeys/stellar/blob/79f0353563c35fa6ae46a2f00886ab1dd31c4492/stellar/command.py#L46-L53", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:fastmonkeys-stellar:gc-9a328d508d", "question": "Deletes old stellar tables that are not used anymore", "scope": {"holder": "fastmonkeys-stellar", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:fastmonkeys/stellar:stellar/command.py:rename#8618", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "stellar/command.py", "symbol": "rename"}, "source_id": "csn:fastmonkeys/stellar:stellar/command.py:rename#8618"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/fastmonkeys/stellar/blob/79f0353563c35fa6ae46a2f00886ab1dd31c4492/stellar/command.py#L151-L166", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:fastmonkeys-stellar:rename-0678c578dd", "question": "Renames a snapshot", "scope": {"holder": "fastmonkeys-stellar", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:fatihsucu/pyzomato:pyzomato/pyzomato.py:Pyzomato.getCityDetails#16880", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pyzomato/pyzomato.py", "symbol": "Pyzomato.getCityDetails"}, "source_id": "csn:fatihsucu/pyzomato:pyzomato/pyzomato.py:Pyzomato.getCityDetails#16880"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/fatihsucu/pyzomato/blob/91c805bac8a49c808d497b7b0b6222a48f2d1324/pyzomato/pyzomato.py#L16-L35", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:fatihsucu-pyzomato:Pyzomato.getCityDetails-dda65a2c66", "question": ":param q: query by city name\n :param lat: latitude\n :param lon: longitude\n :param city_ids: comma separated city_id values\n :param count: number of max results to display\n\n Find the Zomato ID and other details for a city . You can obtain the Zomato City ID in one of the following ways:\n -City Name in the Search Query - Returns list of cities matching the query\n -Using coordinates - Identifies the city details based on the coordinates of any location inside a city\n If you already know the Zomato City ID, this API can be used to get other details of the city.", "scope": {"holder": "fatihsucu-pyzomato", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:fatihsucu/pyzomato:pyzomato/pyzomato.py:Pyzomato.getLocationDetails#16884", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pyzomato/pyzomato.py", "symbol": "Pyzomato.getLocationDetails"}, "source_id": "csn:fatihsucu/pyzomato:pyzomato/pyzomato.py:Pyzomato.getLocationDetails#16884"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/fatihsucu/pyzomato/blob/91c805bac8a49c808d497b7b0b6222a48f2d1324/pyzomato/pyzomato.py#L109-L118", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:fatihsucu-pyzomato:Pyzomato.getLocationDetails-7fcaf92c15", "question": ":param entity_id: location id obtained from locations api\n :param entity_type: location type obtained from locations api\n :return:\n Get Foodie Index, Nightlife Index, Top Cuisines and Best rated restaurants in a given location", "scope": {"holder": "fatihsucu-pyzomato", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:feifangit/dj-api-auth:djapiauth/models.py:APIKeys.permission_check#19459", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "djapiauth/models.py", "symbol": "APIKeys.permission_check"}, "source_id": "csn:feifangit/dj-api-auth:djapiauth/models.py:APIKeys.permission_check#19459"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/feifangit/dj-api-auth/blob/9d833134fc8a6e74bf8d9fe6c98598dd5061ea9b/djapiauth/models.py#L85-L96", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:feifangit-dj-api-auth:APIKeys.permission_check-d200c331a1", "question": "return (user, seckey) if url end point is in allowed entry point list", "scope": {"holder": "feifangit-dj-api-auth", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:feifangit/dj-api-auth:djapiauth/forms.py:get_api_key_form#19495", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "djapiauth/forms.py", "symbol": "get_api_key_form"}, "source_id": "csn:feifangit/dj-api-auth:djapiauth/forms.py:get_api_key_form#19495"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/feifangit/dj-api-auth/blob/9d833134fc8a6e74bf8d9fe6c98598dd5061ea9b/djapiauth/forms.py#L7-L17", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:feifangit-dj-api-auth:get_api_key_form-4646d0a321", "question": "userfileter: when binding api key with user, filter some users if necessary", "scope": {"holder": "feifangit-dj-api-auth", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:ferrix/dj-mongohq-url:dj_mongohq_url.py:parse#21911", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "dj_mongohq_url.py", "symbol": "parse"}, "source_id": "csn:ferrix/dj-mongohq-url:dj_mongohq_url.py:parse#21911"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/ferrix/dj-mongohq-url/blob/0901ca46cf7071881726310e666a5fe9aa0303ef/dj_mongohq_url.py#L36-L62", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:ferrix-dj-mongohq-url:parse-f0e6e0129e", "question": "Parses a database URL.", "scope": {"holder": "ferrix-dj-mongohq-url", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:filepreviews/filepreviews-python:filepreviews/__main__.py:retrieve#15452", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "filepreviews/__main__.py", "symbol": "retrieve"}, "source_id": "csn:filepreviews/filepreviews-python:filepreviews/__main__.py:retrieve#15452"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/filepreviews/filepreviews-python/blob/11be871a07438e3ab5d87ab1f2c163bbac4d4570/filepreviews/__main__.py#L64-L71", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:filepreviews-filepreviews-python:retrieve-7c0f05be26", "question": "Retreive preview results for ID.", "scope": {"holder": "filepreviews-filepreviews-python", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:flit/elapsedtimer:elapsedtimer.py:format_duration#16394", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "elapsedtimer.py", "symbol": "format_duration"}, "source_id": "csn:flit/elapsedtimer:elapsedtimer.py:format_duration#16394"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/flit/elapsedtimer/blob/30cd61bb4e3f4dff4e13c7a3e49c410795224a4b/elapsedtimer.py#L78-L82", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:flit-elapsedtimer:format_duration-8d27addea8", "question": "Formats a number of seconds using the best units.", "scope": {"holder": "flit-elapsedtimer", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:flit/elapsedtimer:elapsedtimer.py:get_time_units_and_multiplier#16393", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "elapsedtimer.py", "symbol": "get_time_units_and_multiplier"}, "source_id": "csn:flit/elapsedtimer:elapsedtimer.py:get_time_units_and_multiplier#16393"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/flit/elapsedtimer/blob/30cd61bb4e3f4dff4e13c7a3e49c410795224a4b/elapsedtimer.py#L68-L76", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:flit-elapsedtimer:get_time_units_and_multiplier-c1a07f1bdd", "question": "Given a duration in seconds, determines the best units and multiplier to\n use to display the time. Return value is a 2-tuple of units and multiplier.", "scope": {"holder": "flit-elapsedtimer", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:fm4d/PyMarkovTextGenerator:markov.py:MarkovChain.startwords#16373", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "markov.py", "symbol": "MarkovChain.startwords"}, "source_id": "csn:fm4d/PyMarkovTextGenerator:markov.py:MarkovChain.startwords#16373"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/fm4d/PyMarkovTextGenerator/blob/4a7e8e2cfe14c9745aba6b9df7d7b402a9029a37/markov.py#L107-L120", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:fm4d-PyMarkovTextGenerator:MarkovChain.startwords-3b818b74fb", "question": "!DEMO!\n Cached list of keys that can be used to generate sentence.", "scope": {"holder": "fm4d-PyMarkovTextGenerator", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:fm4d/PyMarkovTextGenerator:markov.py:MarkovGenerator.generate_sentence#16377", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "markov.py", "symbol": "MarkovGenerator.generate_sentence"}, "source_id": "csn:fm4d/PyMarkovTextGenerator:markov.py:MarkovGenerator.generate_sentence#16377"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/fm4d/PyMarkovTextGenerator/blob/4a7e8e2cfe14c9745aba6b9df7d7b402a9029a37/markov.py#L194-L223", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:fm4d-PyMarkovTextGenerator:MarkovGenerator.generate_sentence-51d63f4c73", "question": "!DEMO!\n Demo function that shows how to generate a simple sentence starting with\n uppercase letter without lenght limit.\n\n Args:\n chain: MarkovChain that will be used to generate sentence", "scope": {"holder": "fm4d-PyMarkovTextGenerator", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:frascoweb/easywebassets:easywebassets/package.py:Package._yield_bundle_contents#19589", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "easywebassets/package.py", "symbol": "Package._yield_bundle_contents"}, "source_id": "csn:frascoweb/easywebassets:easywebassets/package.py:Package._yield_bundle_contents#19589"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/frascoweb/easywebassets/blob/02f84376067c827c84fc1773895bb2784e033949/easywebassets/package.py#L80-L94", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:frascoweb-easywebassets:Package._yield_bundle_contents-541408d6de", "question": "Yield bundle contents from the given dict.\n\n Each item yielded will be either a string representing a file path\n or a bundle.", "scope": {"holder": "frascoweb-easywebassets", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:frascoweb/easywebassets:easywebassets/package.py:Package.html_tags#19593", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "easywebassets/package.py", "symbol": "Package.html_tags"}, "source_id": "csn:frascoweb/easywebassets:easywebassets/package.py:Package.html_tags#19593"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/frascoweb/easywebassets/blob/02f84376067c827c84fc1773895bb2784e033949/easywebassets/package.py#L210-L216", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:frascoweb-easywebassets:Package.html_tags-b45362a895", "question": "Return all html tags for all asset_type", "scope": {"holder": "frascoweb-easywebassets", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:frispete/keyrings.cryptfile:keyrings/cryptfile/cryptfile.py:ArgonAESEncryption._create_cipher#14602", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "keyrings/cryptfile/cryptfile.py", "symbol": "ArgonAESEncryption._create_cipher"}, "source_id": "csn:frispete/keyrings.cryptfile:keyrings/cryptfile/cryptfile.py:ArgonAESEncryption._create_cipher#14602"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/frispete/keyrings.cryptfile/blob/cfa80d4848a5c3c0aeee41a954b2b120c80e69b2/keyrings/cryptfile/cryptfile.py#L38-L58", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:frispete-keyrings.cryptfile:ArgonAESEncryption._create_cipher-686dbbe682", "question": "Create the cipher object to encrypt or decrypt a payload.", "scope": {"holder": "frispete-keyrings.cryptfile", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:frispete/keyrings.cryptfile:keyrings/cryptfile/cryptfile.py:CryptFileKeyring.priority#14604", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "keyrings/cryptfile/cryptfile.py", "symbol": "CryptFileKeyring.priority"}, "source_id": "csn:frispete/keyrings.cryptfile:keyrings/cryptfile/cryptfile.py:CryptFileKeyring.priority#14604"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/frispete/keyrings.cryptfile/blob/cfa80d4848a5c3c0aeee41a954b2b120c80e69b2/keyrings/cryptfile/cryptfile.py#L90-L106", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:frispete-keyrings.cryptfile:CryptFileKeyring.priority-d7e04f7a5f", "question": "Applicable for all platforms, where the schemes, that are integrated\n with your environment, does not fit.", "scope": {"holder": "frispete-keyrings.cryptfile", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:fukuball/fuku-ml:FukuML/DecisionStump.py:BinaryClassifier.score_function#10479", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "FukuML/DecisionStump.py", "symbol": "BinaryClassifier.score_function"}, "source_id": "csn:fukuball/fuku-ml:FukuML/DecisionStump.py:BinaryClassifier.score_function#10479"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/fukuball/fuku-ml/blob/0da15ad7af76adf344b5a6b3f3dbabbbab3446b0/FukuML/DecisionStump.py#L112-L121", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:fukuball-fuku-ml:BinaryClassifier.score_function-789768cbe7", "question": "Score function to calculate score", "scope": {"holder": "fukuball-fuku-ml", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:fukuball/fuku-ml:FukuML/MLBase.py:Learner.prediction#10485", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "FukuML/MLBase.py", "symbol": "Learner.prediction"}, "source_id": "csn:fukuball/fuku-ml:FukuML/MLBase.py:Learner.prediction#10485"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/fukuball/fuku-ml/blob/0da15ad7af76adf344b5a6b3f3dbabbbab3446b0/FukuML/MLBase.py#L102-L142", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:fukuball-fuku-ml:Learner.prediction-adcdc09c09", "question": "Make prediction\n input test data\n output the prediction", "scope": {"holder": "fukuball-fuku-ml", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:funilrys/PyFunceble:PyFunceble/adblock.py:AdBlock._extract_base#6842", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "PyFunceble/adblock.py", "symbol": "AdBlock._extract_base"}, "source_id": "csn:funilrys/PyFunceble:PyFunceble/adblock.py:AdBlock._extract_base#6842"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/funilrys/PyFunceble/blob/cdf69cbde120199171f7158e1c33635753e6e2f5/PyFunceble/adblock.py#L178-L214", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:funilrys-PyFunceble:AdBlock._extract_base-ac5717f4a9", "question": "Extract the base of the given element.\n\n .. example:\n given \"hello/world?world=beautiful\" return \"hello\"\n\n :param element: The element we are working with.\n :type element: str|list", "scope": {"holder": "funilrys-PyFunceble", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:funilrys/PyFunceble:PyFunceble/database.py:Inactive.add#6969", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "PyFunceble/database.py", "symbol": "Inactive.add"}, "source_id": "csn:funilrys/PyFunceble:PyFunceble/database.py:Inactive.add#6969"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/funilrys/PyFunceble/blob/cdf69cbde120199171f7158e1c33635753e6e2f5/PyFunceble/database.py#L468-L550", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:funilrys-PyFunceble:Inactive.add-6774844ca7", "question": "Save the current :code.`PyFunceble.CONFIGURATION['to_test']`\n into the current timestamp.", "scope": {"holder": "funilrys-PyFunceble", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:garyelephant/pygrok:pygrok/pygrok.py:Grok.match#9865", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pygrok/pygrok.py", "symbol": "Grok.match"}, "source_id": "csn:garyelephant/pygrok:pygrok/pygrok.py:Grok.match#9865"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/garyelephant/pygrok/blob/de9e3f92f5a52f0fc101aaa0f694f52aee6afba8/pygrok/pygrok.py#L33-L57", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:garyelephant-pygrok:Grok.match-d4b520d0e3", "question": "If text is matched with pattern, return variable names specified(%{pattern:variable name})\n in pattern and their corresponding values.If not matched, return None.\n custom patterns can be passed in by custom_patterns(pattern name, pattern regular expression pair)\n or custom_patterns_dir.", "scope": {"holder": "garyelephant-pygrok", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:gawel/panoramisk:panoramisk/fast_agi.py:Application.add_route#8592", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "panoramisk/fast_agi.py", "symbol": "Application.add_route"}, "source_id": "csn:gawel/panoramisk:panoramisk/fast_agi.py:Application.add_route#8592"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/gawel/panoramisk/blob/2ccb5d18be28a8e8f444dc0cd3a3bfb59aa19a8e/panoramisk/fast_agi.py#L80-L106", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:gawel-panoramisk:Application.add_route-d8c3f0b592", "question": "Add a route for FastAGI requests:\n\n :param path: URI to answer. Ex: 'calls/start'\n :type path: String\n :param endpoint: command to launch. Ex: start\n :type endpoint: callable\n\n :Example:\n\n ::\n\n @asyncio.coroutine\n def start(request):\n print('Receive a FastAGI request')\n print(['AGI variables:', request.headers])\n\n fa_app = Application()\n fa_app.add_route('calls/start', start)", "scope": {"holder": "gawel-panoramisk", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:gawel/panoramisk:panoramisk/manager.py:Manager.send_action#8584", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "panoramisk/manager.py", "symbol": "Manager.send_action"}, "source_id": "csn:gawel/panoramisk:panoramisk/manager.py:Manager.send_action#8584"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/gawel/panoramisk/blob/2ccb5d18be28a8e8f444dc0cd3a3bfb59aa19a8e/panoramisk/manager.py#L110-L138", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:gawel-panoramisk:Manager.send_action-b6e350506f", "question": "Send an :class:`~panoramisk.actions.Action` to the server:\n\n :param action: an Action or dict with action name and parameters to\n send\n :type action: Action or dict or Command\n :param as_list: If True, the action Future will retrieve all responses\n :type as_list: boolean\n :return: a Future that will receive the response\n :rtype: asyncio.Future\n\n :Example:\n\n To retrieve answer in a coroutine::\n\n manager = Manager()\n resp = yield from manager.send_action({'Action': 'Status'})\n\n With a callback::\n\n manager = Manager()\n future = manager.send_action({'Action': 'Status'})\n future.add_done_callback(handle_status_response)\n\n See https://wiki.asterisk.org/wiki/display/AST/AMI+Actions for\n more information on actions", "scope": {"holder": "gawel-panoramisk", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:gears/gears:gears/asset_attributes.py:AssetAttributes.compiler_extensions#17700", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "gears/asset_attributes.py", "symbol": "AssetAttributes.compiler_extensions"}, "source_id": "csn:gears/gears:gears/asset_attributes.py:AssetAttributes.compiler_extensions#17700"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/gears/gears/blob/5729c2525a8c04c185e998bd9a86233708972921/gears/asset_attributes.py#L148-L161", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:gears-gears:AssetAttributes.compiler_extensions-af69021259", "question": "The list of compiler extensions.\n Example::\n\n >>> attrs = AssetAttributes(environment, 'js/lib/external.min.js.coffee')\n >>> attrs.compiler_extensions\n ['.coffee']", "scope": {"holder": "gears-gears", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:gears/gears:gears/asset_attributes.py:AssetAttributes.unknown_extensions#17699", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "gears/asset_attributes.py", "symbol": "AssetAttributes.unknown_extensions"}, "source_id": "csn:gears/gears:gears/asset_attributes.py:AssetAttributes.unknown_extensions#17699"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/gears/gears/blob/5729c2525a8c04c185e998bd9a86233708972921/gears/asset_attributes.py#L131-L145", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:gears-gears:AssetAttributes.unknown_extensions-6e7d11e0a4", "question": "The list of unknown extensions, which are actually parts of asset\n filename. Example::\n\n >>> attrs = AssetAttributes(environment, 'js/lib-2.0.min.js')\n >>> attrs.suffix\n ['.0', '.min']", "scope": {"holder": "gears-gears", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:genialis/genesis-pyapi:genesis/data.py:GenData.download#15114", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "genesis/data.py", "symbol": "GenData.download"}, "source_id": "csn:genialis/genesis-pyapi:genesis/data.py:GenData.download#15114"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/genialis/genesis-pyapi/blob/dfe9bcc8b332a8b9873db4ab9994b0cc10eb209a/genesis/data.py#L72-L90", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:genialis-genesis-pyapi:GenData.download-cf650822af", "question": "Download a file.\n\n :param field: file field to download\n :type field: string\n :rtype: a file handle", "scope": {"holder": "genialis-genesis-pyapi", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:genialis/genesis-pyapi:genesis/genesis.py:Genesis.data#15118", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "genesis/genesis.py", "symbol": "Genesis.data"}, "source_id": "csn:genialis/genesis-pyapi:genesis/genesis.py:Genesis.data#15118"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/genialis/genesis-pyapi/blob/dfe9bcc8b332a8b9873db4ab9994b0cc10eb209a/genesis/genesis.py#L108-L157", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:genialis-genesis-pyapi:Genesis.data-b50e47cbca", "question": "Query for Data object annotation.", "scope": {"holder": "genialis-genesis-pyapi", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:geopython/OWSLib:owslib/swe/observation/om.py:MeasurementObservation._parse_result#5196", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "owslib/swe/observation/om.py", "symbol": "MeasurementObservation._parse_result"}, "source_id": "csn:geopython/OWSLib:owslib/swe/observation/om.py:MeasurementObservation._parse_result#5196"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/geopython/OWSLib/blob/96d47842401a129f1e86fa9f66dccef5a5a6872c/owslib/swe/observation/om.py#L82-L92", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:geopython-OWSLib:MeasurementObservation._parse_result-9c60e553ba", "question": "Parse the result property, extracting the value\n and unit of measure", "scope": {"holder": "geopython-OWSLib", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:geopython/OWSLib:owslib/feature/wfs300.py:WebFeatureService_3_0_0.collection_items#5203", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "owslib/feature/wfs300.py", "symbol": "WebFeatureService_3_0_0.collection_items"}, "source_id": "csn:geopython/OWSLib:owslib/feature/wfs300.py:WebFeatureService_3_0_0.collection_items#5203"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/geopython/OWSLib/blob/96d47842401a129f1e86fa9f66dccef5a5a6872c/owslib/feature/wfs300.py#L101-L127", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:geopython-OWSLib:WebFeatureService_3_0_0.collection_items-5850be2a1b", "question": "implements Requirement 17 (/req/core/fc-op)\n\n @type collection_name: string\n @param collection_name: name of collection\n @type bbox: list\n @param bbox: list of minx,miny,maxx,maxy\n @type time: string\n @param time: time extent or time instant\n @type limit: int\n @param limit: limit number of features\n @type startindex: int\n @param startindex: start position of results\n\n @returns: feature results", "scope": {"holder": "geopython-OWSLib", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:getgauge/gauge-python:getgauge/parser_parso.py:ParsoPythonFile._iter_step_func_decorators#8215", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "getgauge/parser_parso.py", "symbol": "ParsoPythonFile._iter_step_func_decorators"}, "source_id": "csn:getgauge/gauge-python:getgauge/parser_parso.py:ParsoPythonFile._iter_step_func_decorators#8215"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/getgauge/gauge-python/blob/90f3547dcfd2d16d51f116cdd4e53527eeab1a57/getgauge/parser_parso.py#L50-L57", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:getgauge-gauge-python:ParsoPythonFile._iter_step_func_decorators-4881e11d94", "question": "Find functions with step decorator in parsed file", "scope": {"holder": "getgauge-gauge-python", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:getgauge/gauge-python:getgauge/parser_redbaron.py:RedbaronPythonFile._find_step_node#8224", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "getgauge/parser_redbaron.py", "symbol": "RedbaronPythonFile._find_step_node"}, "source_id": "csn:getgauge/gauge-python:getgauge/parser_redbaron.py:RedbaronPythonFile._find_step_node#8224"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/getgauge/gauge-python/blob/90f3547dcfd2d16d51f116cdd4e53527eeab1a57/getgauge/parser_redbaron.py#L89-L99", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:getgauge-gauge-python:RedbaronPythonFile._find_step_node-2c035a3535", "question": "Find the ast node which contains the text.", "scope": {"holder": "getgauge-gauge-python", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:getsentry/sentry-hipchat-ac:sentry_hipchat_ac/models.py:Context.for_request#14456", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "sentry_hipchat_ac/models.py", "symbol": "Context.for_request"}, "source_id": "csn:getsentry/sentry-hipchat-ac:sentry_hipchat_ac/models.py:Context.for_request#14456"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/getsentry/sentry-hipchat-ac/blob/9063666f1e06cf352fed0530a8a437e45badc917/sentry_hipchat_ac/models.py#L245-L271", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:getsentry-sentry-hipchat-ac:Context.for_request-fe916b5914", "question": "Creates the context for a specific request.", "scope": {"holder": "getsentry-sentry-hipchat-ac", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:getsentry/sentry-hipchat-ac:sentry_hipchat_ac/models.py:Context.tenant_token#14457", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "sentry_hipchat_ac/models.py", "symbol": "Context.tenant_token"}, "source_id": "csn:getsentry/sentry-hipchat-ac:sentry_hipchat_ac/models.py:Context.tenant_token#14457"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/getsentry/sentry-hipchat-ac/blob/9063666f1e06cf352fed0530a8a437e45badc917/sentry_hipchat_ac/models.py#L283-L288", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:getsentry-sentry-hipchat-ac:Context.tenant_token-0662fa0710", "question": "The cached token of the current tenant.", "scope": {"holder": "getsentry-sentry-hipchat-ac", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:ghcollin/multitables:multitables.py:Barrier.wait#17630", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "multitables.py", "symbol": "Barrier.wait"}, "source_id": "csn:ghcollin/multitables:multitables.py:Barrier.wait#17630"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/ghcollin/multitables/blob/9654a45800289a20e66d2b0e0666149f0d370f93/multitables.py#L57-L63", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:ghcollin-multitables:Barrier.wait-3b60d7e845", "question": "Wait until all processes have reached the barrier.", "scope": {"holder": "ghcollin-multitables", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:ghcollin/multitables:multitables.py:SharedCircBuf.get_direct#17636", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "multitables.py", "symbol": "SharedCircBuf.get_direct"}, "source_id": "csn:ghcollin/multitables:multitables.py:SharedCircBuf.get_direct#17636"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/ghcollin/multitables/blob/9654a45800289a20e66d2b0e0666149f0d370f93/multitables.py#L329-L343", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:ghcollin-multitables:SharedCircBuf.get_direct-ef4c6b06f1", "question": "Allows direct access to the buffer element.\n Blocks until there is data that can be read.\n\n :return: A guard object that returns the buffer element.", "scope": {"holder": "ghcollin-multitables", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:gholt/swiftly:swiftly/cli/cli.py:CLI._resolve_option#12295", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "swiftly/cli/cli.py", "symbol": "CLI._resolve_option"}, "source_id": "csn:gholt/swiftly:swiftly/cli/cli.py:CLI._resolve_option#12295"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/gholt/swiftly/blob/5bcc1c65323b1caf1f85adbefd9fc4988c072149/swiftly/cli/cli.py#L433-L458", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:gholt-swiftly:CLI._resolve_option-ad1094cb13", "question": "Resolves an option value into options.\n\n Sets options.<option_name> to a resolved value. Any value\n already in options overrides a value in os.environ which\n overrides self.context.conf.\n\n :param options: The options instance as returned by optparse.\n :param option_name: The name of the option, such as\n ``auth_url``.\n :param section_name: The name of the section, such as\n ``swiftly``.", "scope": {"holder": "gholt-swiftly", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:gholt/swiftly:swiftly/cli/optionparser.py:OptionParser.error#12270", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "swiftly/cli/optionparser.py", "symbol": "OptionParser.error"}, "source_id": "csn:gholt/swiftly:swiftly/cli/optionparser.py:OptionParser.error#12270"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/gholt/swiftly/blob/5bcc1c65323b1caf1f85adbefd9fc4988c072149/swiftly/cli/optionparser.py#L97-L106", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:gholt-swiftly:OptionParser.error-4470790026", "question": "Outputs the error msg to the file if specified, or to the\n io_manager's stderr if available, or to sys.stderr.", "scope": {"holder": "gholt-swiftly", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:giffels/CloudStackAIO:CloudStackAIO/CloudStack.py:CloudStack._handle_response#21346", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "CloudStackAIO/CloudStack.py", "symbol": "CloudStack._handle_response"}, "source_id": "csn:giffels/CloudStackAIO:CloudStackAIO/CloudStack.py:CloudStack._handle_response#21346"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/giffels/CloudStackAIO/blob/f9df856622eb8966a6816f8008cc16d75b0067e5/CloudStackAIO/CloudStack.py#L157-L201", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:giffels-CloudStackAIO:CloudStack._handle_response-f7fa8e7bbd", "question": "Handles the response returned from the CloudStack API. Some CloudStack API are implemented asynchronous, which\n means that the API call returns just a job id. The actually expected API response is postponed and a specific\n asyncJobResults API has to be polled using the job id to get the final result once the API call has been\n processed.\n\n :param response: The response returned by the aiohttp call.\n :type response: aiohttp.client_reqrep.ClientResponse\n :param await_final_result: Specifier that indicates whether the function should poll the asyncJobResult API\n until the asynchronous API call has been processed\n :type await_final_result: bool\n :return: Dictionary containing the JSON response of the API call\n :rtype: dict", "scope": {"holder": "giffels-CloudStackAIO", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:giffels/CloudStackAIO:CloudStackAIO/CloudStack.py:CloudStack._sign#21347", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "CloudStackAIO/CloudStack.py", "symbol": "CloudStack._sign"}, "source_id": "csn:giffels/CloudStackAIO:CloudStackAIO/CloudStack.py:CloudStack._sign#21347"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/giffels/CloudStackAIO/blob/f9df856622eb8966a6816f8008cc16d75b0067e5/CloudStackAIO/CloudStack.py#L203-L220", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:giffels-CloudStackAIO:CloudStack._sign-461219f6b0", "question": "According to the CloudStack documentation, each request needs to be signed in order to authenticate the user\n account executing the API command. The signature is generated using a combination of the api secret and a SHA-1\n hash of the url parameters including the command string. In order to generate a unique identifier, the url\n parameters have to be transformed to lower case and ordered alphabetically.\n\n :param url_parameters: The url parameters of the API call including the command string\n :type url_parameters: dict\n :return: The url parameters including a new key, which contains the signature\n :rtype: dict", "scope": {"holder": "giffels-CloudStackAIO", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:globality-corp/flake8-logging-format:logging_format/visitor.py:LoggingVisitor.check_exc_info#9855", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "logging_format/visitor.py", "symbol": "LoggingVisitor.check_exc_info"}, "source_id": "csn:globality-corp/flake8-logging-format:logging_format/visitor.py:LoggingVisitor.check_exc_info#9855"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/globality-corp/flake8-logging-format/blob/3c6ce53d0ff1ec369799cff0ed6d048343252e40/logging_format/visitor.py#L275-L289", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:globality-corp-flake8-logging-format:LoggingVisitor.check_exc_info-825629e39d", "question": "Reports a violation if exc_info keyword is used with logging.error or logging.exception.", "scope": {"holder": "globality-corp-flake8-logging-format", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:globality-corp/flake8-logging-format:logging_format/visitor.py:LoggingVisitor.is_bare_exception#9853", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "logging_format/visitor.py", "symbol": "LoggingVisitor.is_bare_exception"}, "source_id": "csn:globality-corp/flake8-logging-format:logging_format/visitor.py:LoggingVisitor.is_bare_exception#9853"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/globality-corp/flake8-logging-format/blob/3c6ce53d0ff1ec369799cff0ed6d048343252e40/logging_format/visitor.py#L251-L256", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:globality-corp-flake8-logging-format:LoggingVisitor.is_bare_exception-540e5891a6", "question": "Checks if the node is a bare exception name from an except block.", "scope": {"holder": "globality-corp-flake8-logging-format", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:glottobank/python-newick:src/newick.py:Node.ascii_art#17233", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "src/newick.py", "symbol": "Node.ascii_art"}, "source_id": "csn:glottobank/python-newick:src/newick.py:Node.ascii_art#17233"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/glottobank/python-newick/blob/e8d4d1e4610f271d0f0e5cb86c0e0360b43bd702/src/newick.py#L137-L179", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:glottobank-python-newick:Node.ascii_art-abea93254b", "question": "Return a unicode string representing a tree in ASCII art fashion.\n\n :param strict: Use ASCII characters strictly (for the tree symbols).\n :param show_internal: Show labels of internal nodes.\n :return: unicode string\n\n >>> node = loads('((A,B)C,((D,E)F,G,H)I)J;')[0]\n >>> print(node.ascii_art(show_internal=False, strict=True))\n /-A\n /---|\n | \\-B\n ----| /-D\n | /---|\n | | \\-E\n \\---|\n |-G\n \\-H", "scope": {"holder": "glottobank-python-newick", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:glottobank/python-newick:src/newick.py:Node.resolve_polytomies#17240", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "src/newick.py", "symbol": "Node.resolve_polytomies"}, "source_id": "csn:glottobank/python-newick:src/newick.py:Node.resolve_polytomies#17240"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/glottobank/python-newick/blob/e8d4d1e4610f271d0f0e5cb86c0e0360b43bd702/src/newick.py#L321-L333", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:glottobank-python-newick:Node.resolve_polytomies-2b4fc6a74b", "question": "Insert additional nodes with length=0 into the subtree in such a way\n that all non-leaf nodes have only 2 descendants, i.e. the tree becomes\n a fully resolved binary tree.", "scope": {"holder": "glottobank-python-newick", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:gmr/tornado-elasticsearch:tornado_elasticsearch.py:AsyncElasticsearch.clear_scroll#14434", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "tornado_elasticsearch.py", "symbol": "AsyncElasticsearch.clear_scroll"}, "source_id": "csn:gmr/tornado-elasticsearch:tornado_elasticsearch.py:AsyncElasticsearch.clear_scroll#14434"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/gmr/tornado-elasticsearch/blob/fafe0de680277ce6faceb7449ded0b33822438d0/tornado_elasticsearch.py#L690-L713", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:gmr-tornado-elasticsearch:AsyncElasticsearch.clear_scroll-7ed8aba65d", "question": "Clear the scroll request created by specifying the scroll parameter to\n search.\n `<http://www.elasticsearch.org/guide/reference/api/search/scroll/>`_\n\n :arg scroll_id: The scroll ID or a list of scroll IDs", "scope": {"holder": "gmr-tornado-elasticsearch", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:gmr/tornado-elasticsearch:tornado_elasticsearch.py:AsyncElasticsearch.index#14429", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "tornado_elasticsearch.py", "symbol": "AsyncElasticsearch.index"}, "source_id": "csn:gmr/tornado-elasticsearch:tornado_elasticsearch.py:AsyncElasticsearch.index#14429"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/gmr/tornado-elasticsearch/blob/fafe0de680277ce6faceb7449ded0b33822438d0/tornado_elasticsearch.py#L319-L345", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:gmr-tornado-elasticsearch:AsyncElasticsearch.index-a73b974d59", "question": "Adds or updates a typed JSON document in a specific index, making it\n searchable. `<http://elasticsearch.org/guide/reference/api/index_/>`_\n\n :arg index: The name of the index\n :arg doc_type: The type of the document\n :arg body: The document\n :arg id: Document ID\n :arg consistency: Explicit write consistency setting for the operation\n :arg op_type: Explicit operation type (default: index)\n :arg parent: ID of the parent document\n :arg percolate: Percolator queries to execute while indexing the doc\n :arg refresh: Refresh the index after performing the operation\n :arg replication: Specific replication type (default: sync)\n :arg routing: Specific routing value\n :arg timeout: Explicit operation timeout\n :arg timestamp: Explicit timestamp for the document\n :arg ttl: Expiration time for the document\n :arg version: Explicit version number for concurrency control\n :arg version_type: Specific version type", "scope": {"holder": "gmr-tornado-elasticsearch", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:gnosis/gnosis-py:gnosis/eth/ethereum_client.py:Erc20Manager.get_transfer_history#14891", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "gnosis/eth/ethereum_client.py", "symbol": "Erc20Manager.get_transfer_history"}, "source_id": "csn:gnosis/gnosis-py:gnosis/eth/ethereum_client.py:Erc20Manager.get_transfer_history#14891"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/gnosis/gnosis-py/blob/2a9a5d75a375fc9813ac04df133e6910c82f9d49/gnosis/eth/ethereum_client.py#L130-L172", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:gnosis-gnosis-py:Erc20Manager.get_transfer_history-5660e32f85", "question": "Get events for erc20 transfers. At least one of `from_address`, `to_address` or `token_address` must be\n defined\n An example of event:\n {\n \"args\": {\n \"from\": \"0x1Ce67Ea59377A163D47DFFc9BaAB99423BE6EcF1\",\n \"to\": \"0xaE9E15896fd32E59C7d89ce7a95a9352D6ebD70E\",\n \"value\": 15000000000000000\n },\n \"event\": \"Transfer\",\n \"logIndex\": 42,\n \"transactionIndex\": 60,\n \"transactionHash\": \"0x71d6d83fef3347bad848e83dfa0ab28296e2953de946ee152ea81c6dfb42d2b3\",\n \"address\": \"0xfecA834E7da9D437645b474450688DA9327112a5\",\n \"blockHash\": \"0x054de9a496fc7d10303068cbc7ee3e25181a3b26640497859a5e49f0342e7db2\",\n \"blockNumber\": 7265022\n }\n :param from_block: Block to start querying from\n :param to_block: Block to stop querying from\n :param from_address: Address sending the erc20 transfer\n :param to_address: Address receiving the erc20 transfer\n :param token_address: Address of the token\n :return: List of events\n :throws: ReadTimeout", "scope": {"holder": "gnosis-gnosis-py", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:gnosis/gnosis-py:gnosis/safe/safe_service.py:SafeService.check_proxy_code#14913", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "gnosis/safe/safe_service.py", "symbol": "SafeService.check_proxy_code"}, "source_id": "csn:gnosis/gnosis-py:gnosis/safe/safe_service.py:SafeService.check_proxy_code#14913"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/gnosis/gnosis-py/blob/2a9a5d75a375fc9813ac04df133e6910c82f9d49/gnosis/safe/safe_service.py#L198-L211", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:gnosis-gnosis-py:SafeService.check_proxy_code-8005d84caa", "question": "Check if proxy is valid\n :param address: address of the proxy\n :return: True if proxy is valid, False otherwise", "scope": {"holder": "gnosis-gnosis-py", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:google/brotli:research/brotlidump.py:BitStream.peek#3019", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "research/brotlidump.py", "symbol": "BitStream.peek"}, "source_id": "csn:google/brotli:research/brotlidump.py:BitStream.peek#3019"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/google/brotli/blob/4b2b2d4f83ffeaac7708e44409fe34896a01a278/research/brotlidump.py#L79-L95", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:google-brotli:BitStream.peek-55c0b637d8", "question": "Peek an n bit integer from the stream without updating the pointer.\n It is not an error to read beyond the end of the stream.\n >>> olleke.data[:2]==b'\\x1b\\x2e' and 0x2e1b==11803\n True\n >>> olleke.peek(15)\n 11803\n >>> hex(olleke.peek(32))\n '0x2e1b'", "scope": {"holder": "google-brotli", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:google/brotli:research/brotlidump.py:Layout.readPrefixCode#3047", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "research/brotlidump.py", "symbol": "Layout.readPrefixCode"}, "source_id": "csn:google/brotli:research/brotlidump.py:Layout.readPrefixCode#3047"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/google/brotli/blob/4b2b2d4f83ffeaac7708e44409fe34896a01a278/research/brotlidump.py#L1424-L1456", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:google-brotli:Layout.readPrefixCode-8ecfe6e23b", "question": "give alphabet the prefix code that is read from the stream\n Called for the following alphabets, in this order:\n The alphabet in question must have a \"logical\" order,\n otherwise the assignment of symbols doesn't work.", "scope": {"holder": "google-brotli", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:google/gin-config:gin/config_parser.py:ConfigParser._maybe_parse_basic_type#4688", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "gin/config_parser.py", "symbol": "ConfigParser._maybe_parse_basic_type"}, "source_id": "csn:google/gin-config:gin/config_parser.py:ConfigParser._maybe_parse_basic_type#4688"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/google/gin-config/blob/17a170e0a6711005d1c78e67cf493dc44674d44f/gin/config_parser.py#L388-L415", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:google-gin-config:ConfigParser._maybe_parse_basic_type-c4148a4710", "question": "Try to parse a basic type (str, bool, number).", "scope": {"holder": "google-gin-config", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:google/gin-config:gin/config.py:_make_configurable#4708", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "gin/config.py", "symbol": "_make_configurable"}, "source_id": "csn:google/gin-config:gin/config.py:_make_configurable#4708"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/google/gin-config/blob/17a170e0a6711005d1c78e67cf493dc44674d44f/gin/config.py#L838-L1046", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:google-gin-config:_make_configurable-f277ff204a", "question": "Wraps `fn_or_cls` to make it configurable.\n\n Infers the configurable name from `fn_or_cls.__name__` if necessary, and\n updates global state to keep track of configurable name <-> function\n mappings, as well as whitelisted and blacklisted parameters.\n\n Args:\n fn_or_cls: The function or class to decorate.\n name: A name for the configurable. If `None`, the name will be inferred from\n from `fn_or_cls`. The `name` may also include module components to be used\n for disambiguation (these will be appended to any components explicitly\n specified by `module`).\n module: The module to associate with the configurable, to help handle naming\n collisions. If `None`, `fn_or_cls.__module__` will be used (if no module\n is specified as part of `name`).\n whitelist: A whitelisted set of parameter names to supply values for.\n blacklist: A blacklisted set of parameter names not to supply values for.\n subclass: If `fn_or_cls` is a class and `subclass` is `True`, decorate by\n subclassing `fn_or_cls` and overriding its `__init__` method. If `False`,\n replace the existing `__init__` with a decorated version.\n\n Returns:\n A wrapped version of `fn_or_cls` that will take parameter values from the\n global configuration.\n\n Raises:\n RuntimeError: If the config is locked.\n ValueError: If a configurable with `name` (or the name of `fn_or_cls`)\n already exists, or if both a whitelist and blacklist are specified.", "scope": {"holder": "google-gin-config", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:google/pybadges:pybadges/pil_text_measurer.py:PilMeasurer.text_width#6557", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pybadges/pil_text_measurer.py", "symbol": "PilMeasurer.text_width"}, "source_id": "csn:google/pybadges:pybadges/pil_text_measurer.py:PilMeasurer.text_width#6557"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/google/pybadges/blob/d42c8080adb21b81123ac9540c53127ed2fa1edc/pybadges/pil_text_measurer.py#L37-L40", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:google-pybadges:PilMeasurer.text_width-f63d037fd0", "question": "Returns the width, in pixels, of a string in DejaVu Sans 110pt.", "scope": {"holder": "google-pybadges", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:google/pybadges:pybadges/precalculate_text.py:calculate_character_to_length_mapping#6565", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pybadges/precalculate_text.py", "symbol": "calculate_character_to_length_mapping"}, "source_id": "csn:google/pybadges:pybadges/precalculate_text.py:calculate_character_to_length_mapping#6565"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/google/pybadges/blob/d42c8080adb21b81123ac9540c53127ed2fa1edc/pybadges/precalculate_text.py#L87-L105", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:google-pybadges:calculate_character_to_length_mapping-0c260b20bf", "question": "Return a mapping between each given character and its length.\n\n Args:\n measurer: The TextMeasurer used to measure the width of the text in\n pixels.\n characters: The characters to measure e.g. \"ml\".\n\n Returns:\n A mapping from the given characters to their length in pixels, as\n determined by 'measurer' e.g. {'m': 5.2, 'l', 1.2}.", "scope": {"holder": "google-pybadges", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:gooofy/py-nltools:nltools/misc.py:render_template#11132", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "nltools/misc.py", "symbol": "render_template"}, "source_id": "csn:gooofy/py-nltools:nltools/misc.py:render_template#11132"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/gooofy/py-nltools/blob/26b990e816fe840dfc69a4dfee01354201b921be/nltools/misc.py#L273-L311", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:gooofy-py-nltools:render_template-51481ad95c", "question": "Copy template and substitute template strings\n\n File `template_file` is copied to `dst_file`. Then, each template variable\n is replaced by a value. Template variables are of the form\n\n {{val}}\n\n Example:\n\n Contents of template_file:\n\n VAR1={{val1}}\n VAR2={{val2}}\n VAR3={{val3}}\n\n render_template(template_file, output_file, val1=\"hello\", val2=\"world\")\n\n Contents of output_file:\n\n VAR1=hello\n VAR2=world\n VAR3={{val3}}\n\n :param template_file: Path to the template file.\n :param dst_file: Path to the destination file.\n :param kwargs: Keys correspond to template variables.\n :return:", "scope": {"holder": "gooofy-py-nltools", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:grampajoe/happy:happy/__init__.py:Happy.create#19505", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "happy/__init__.py", "symbol": "Happy.create"}, "source_id": "csn:grampajoe/happy:happy/__init__.py:Happy.create#19505"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/grampajoe/happy/blob/707e056eb033ea010d181f5fab8d44e129ea9906/happy/__init__.py#L18-L32", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:grampajoe-happy:Happy.create-ab306fb32e", "question": "Creates a Heroku app-setup build.\n\n :param tarball_url: URL of a tarball containing an ``app.json``.\n :param env: (optional) Dict containing environment variable overrides.\n :param app_name: (optional) Name of the Heroku app to create.\n :returns: A tuple with ``(build_id, app_name)``.", "scope": {"holder": "grampajoe-happy", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:grampajoe/happy:happy/heroku.py:Heroku.create_build#19484", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "happy/heroku.py", "symbol": "Heroku.create_build"}, "source_id": "csn:grampajoe/happy:happy/heroku.py:Heroku.create_build#19484"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/grampajoe/happy/blob/707e056eb033ea010d181f5fab8d44e129ea9906/happy/heroku.py#L69-L89", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:grampajoe-happy:Heroku.create_build-70e1468fbe", "question": "Creates an app-setups build. Returns response data as a dict.\n\n :param tarball_url: URL of a tarball containing an ``app.json``.\n :param env: Dict containing environment variable overrides.\n :param app_name: Name of the Heroku app to create.\n :returns: Response data as a ``dict``.", "scope": {"holder": "grampajoe-happy", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:graphql-python/graphene-sqlalchemy:graphene_sqlalchemy/utils.py:sort_enum_for_model#4402", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "graphene_sqlalchemy/utils.py", "symbol": "sort_enum_for_model"}, "source_id": "csn:graphql-python/graphene-sqlalchemy:graphene_sqlalchemy/utils.py:sort_enum_for_model#4402"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/graphql-python/graphene-sqlalchemy/blob/e362e3fc4993d7e95873044bb4d00185b1d3dd8b/graphene_sqlalchemy/utils.py#L82-L100", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:graphql-python-graphene-sqlalchemy:sort_enum_for_model-7a5353252a", "question": "Create Graphene Enum for sorting a SQLAlchemy class query\n\n Parameters\n - cls : Sqlalchemy model class\n Model used to create the sort enumerator\n - name : str, optional, default None\n Name to use for the enumerator. If not provided it will be set to `cls.__name__ + 'SortEnum'`\n - symbol_name : function, optional, default `_symbol_name`\n Function which takes the column name and a boolean indicating if the sort direction is ascending,\n and returns the symbol name for the current column and sort direction.\n The default function will create, for a column named 'foo', the symbols 'foo_asc' and 'foo_desc'\n\n Returns\n - Enum\n The Graphene enumerator", "scope": {"holder": "graphql-python-graphene-sqlalchemy", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:greenbender/pynntp:nntp/nntp.py:BaseNNTPClient.__buf_gen#18178", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "nntp/nntp.py", "symbol": "BaseNNTPClient.__buf_gen"}, "source_id": "csn:greenbender/pynntp:nntp/nntp.py:BaseNNTPClient.__buf_gen#18178"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/greenbender/pynntp/blob/991a76331cdf5d8f9dbf5b18f6e29adc80749a2f/nntp/nntp.py#L164-L189", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:greenbender-pynntp:BaseNNTPClient.__buf_gen-749bc00871", "question": "Generator that reads a block of data from the server.\n\n It first attempts to read from the internal buffer. If there is not\n enough data in the internal buffer it then requests more data from the\n server and adds it to the buffer.\n\n Args:\n length: An optional amount of data to retrieve. A length of 0 (the\n default) will retrieve a least one buffer of data.\n\n Yields:\n A block of data when enough data becomes available.\n\n Note:\n If a length of 0 is supplied then the size of the yielded buffer can\n vary. If there is data in the internal buffer it will yield all of\n that data otherwise it will yield the the data returned by a recv\n on the socket.", "scope": {"holder": "greenbender-pynntp", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:greenbender/pynntp:nntp/nntp.py:NNTPClient.newnews#18193", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "nntp/nntp.py", "symbol": "NNTPClient.newnews"}, "source_id": "csn:greenbender/pynntp:nntp/nntp.py:NNTPClient.newnews#18193"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/greenbender/pynntp/blob/991a76331cdf5d8f9dbf5b18f6e29adc80749a2f/nntp/nntp.py#L692-L708", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:greenbender-pynntp:NNTPClient.newnews-e633948d59", "question": "NEWNEWS command.\n\n Retrieves a list of message-ids for articles created since the specified\n timestamp for newsgroups with names that match the given pattern. See\n newnews_gen() for more details.\n\n See <http://tools.ietf.org/html/rfc3977#section-7.4>\n\n Args:\n pattern: Glob matching newsgroups of intrest.\n timestamp: Datetime object giving 'created since' datetime.\n\n Returns:\n A list of message-ids as given by newnews_gen()", "scope": {"holder": "greenbender-pynntp", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:griffithlab/civicpy:civicpy/civic.py:CivicRecord.update#15133", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "civicpy/civic.py", "symbol": "CivicRecord.update"}, "source_id": "csn:griffithlab/civicpy:civicpy/civic.py:CivicRecord.update#15133"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/griffithlab/civicpy/blob/feac435483bac46ea650f46d1b4f15eb3395a2b8/civicpy/civic.py#L176-L192", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:griffithlab-civicpy:CivicRecord.update-fa48d41775", "question": "Updates record and returns True if record is complete after update, else False.", "scope": {"holder": "griffithlab-civicpy", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:griffithlab/civicpy:civicpy/recipes.py:get_variant_phenotypes_with_suggested_changes#15129", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "civicpy/recipes.py", "symbol": "get_variant_phenotypes_with_suggested_changes"}, "source_id": "csn:griffithlab/civicpy:civicpy/recipes.py:get_variant_phenotypes_with_suggested_changes#15129"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/griffithlab/civicpy/blob/feac435483bac46ea650f46d1b4f15eb3395a2b8/civicpy/recipes.py#L5-L25", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:griffithlab-civicpy:get_variant_phenotypes_with_suggested_changes-cd71b25f56", "question": "for each variant, yields evidence and associated phenotypes, both current and suggested", "scope": {"holder": "griffithlab-civicpy", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:gtaylor/python-route53:route53/transport.py:BaseTransport.get_request_headers#17383", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "route53/transport.py", "symbol": "BaseTransport.get_request_headers"}, "source_id": "csn:gtaylor/python-route53:route53/transport.py:BaseTransport.get_request_headers#17383"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/gtaylor/python-route53/blob/b9fc7e258a79551c9ed61e4a71668b7f06f9e774/route53/transport.py#L67-L88", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:gtaylor-python-route53:BaseTransport.get_request_headers-cfc77b091f", "question": "Determine the headers to send along with the request. These are\n pretty much the same for every request, with Route53.", "scope": {"holder": "gtaylor-python-route53", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:gtaylor/python-route53:route53/connection.py:Route53Connection._do_autopaginating_api_call#17393", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "route53/connection.py", "symbol": "Route53Connection._do_autopaginating_api_call"}, "source_id": "csn:gtaylor/python-route53:route53/connection.py:Route53Connection._do_autopaginating_api_call#17393"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/gtaylor/python-route53/blob/b9fc7e258a79551c9ed61e4a71668b7f06f9e774/route53/connection.py#L53-L111", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:gtaylor-python-route53:Route53Connection._do_autopaginating_api_call-c9b9dda6df", "question": "Given an API method, the arguments passed to it, and a function to\n hand parsing off to, loop through the record sets in the API call\n until all records have been yielded.\n\n\n :param str method: The API method on the endpoint.\n :param dict params: The kwargs from the top-level API method.\n :param callable parser_func: A callable that is used for parsing the\n output from the API call.\n :param str next_marker_param_name: The XPath to the marker tag that\n will determine whether we continue paginating.\n :param str next_marker_param_name: The parameter name to manipulate\n in the request data to bring up the next page on the next\n request loop.\n :keyword str next_type_xpath: For the\n py:meth:`list_resource_record_sets_by_zone_id` method, there's\n an additional paginator token. Specifying this XPath looks for it.\n :keyword dict parser_kwargs: Optional dict of additional kwargs to pass\n on to the parser function.\n :rtype: generator\n :returns: Returns a generator that may be returned by the top-level\n API method.", "scope": {"holder": "gtaylor-python-route53", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:gtzampanakis/aml:aml/__init__.py:create_lang_instance#20689", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "aml/__init__.py", "symbol": "create_lang_instance"}, "source_id": "csn:gtzampanakis/aml:aml/__init__.py:create_lang_instance#20689"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/gtzampanakis/aml/blob/56e089a101cc9a51ae7c8f631663c2f568ebd0d1/aml/__init__.py#L16-L445", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:gtzampanakis-aml:create_lang_instance-1489acc1f1", "question": ">>> lang_instance = create_lang_instance()\n\t>>> lang_instance.aml_evaluate(lang_instance.aml_compile('1 = 1'))\n\tTrue\n\t>>> li = create_lang_instance()\n\t>>> c = li.aml_compile\n\t>>> e = li.aml_evaluate\n\t>>> p = li.aml_translate_python\n\t>>> s = li.aml_translate_sql\n\t>>> u = li.aml_suggest\n\t>>> e(c('1 = 0'))\n\tFalse\n\t>>> e(c('\"1\" = \"1\"'))\n\tTrue\n\t>>> e(c('(1=1)'))\n\tTrue\n\t>>> e(c('1 > 1'))\n\tFalse\n\t>>> e(c('not 1 > 1'))\n\tTrue\n\t>>> e(c('1 != 1'))\n\tFalse\n\t>>> e(c('-2 = -2'))\n\tTrue\n\t>>> eval(p(c('-2 = -2')))\n\tTrue\n\t>>> eval(p(c('-2 >= -1')))\n\tFalse\n\t>>> eval(p(c('-2 <= -1')))\n\tTrue\n\t>>> eval(p(c('2 >= 1')))\n\tTrue\n\t>>> eval(p(c('2 <= 1')))\n\tFalse\n\t>>> eval(p(c('null = null')))\n\tTrue\n\t>>> eval(p(c('1 = null')))\n\tFalse\n\t>>> e(c('\"foo\" = \"foo\"'))\n\tTrue\n\t>>> e(c('\"foo\"' '=' \"'foo'\"))\n\tTrue\n\t>>> e(c('\"foo\" = \\\\'foo\\\\''))\n\tTrue\n\t>>> e(c('\"fo\\\\'o\" = \"fo\\\\'o\"'))\n\tTrue\n\t>>> e(c(\"'foo'\" + '=' + '\"foo\"'))\n\tTrue\n\t>>> li = create_lang_instance({'foo' : 1});\n\t>>> c = li.aml_compile\n\t>>> e = li.aml_evaluate\n\t>>> e(c('foo = 1'))\n\tTrue\n\t>>> li = create_lang_instance({'foo' : 1.00})\n\t>>> c = li.aml_compile\n\t>>> e = li.aml_evaluate\n\t>>> e(c('foo = 1'))\n\tTrue\n\t>>> li = create_lang_instance({'foo' : 2.24})\n\t>>> c = li.aml_compile\n\t>>> e = li.aml_evaluate\n\t>>> e(c('foo = 2.24'))\n\tTrue\n\t>>> e(c('foo = 2.2399 or foo = 2.24'))\n\tTrue\n\t>>> e(c('foo = 2.2399 or foo = 2.2401'))\n\tFalse\n\t>>> e(c('foo in (2.2399, 2.24, null,)'))\n\tTrue\n\t>>> e(c('foo in (2.2399, 2.2401, null,)'))\n\tFalse\n\t>>> e(c('null in (2.2399, 2.2401, null)'))\n\tTrue\n\t>>> e(c('\"null\" in (2.2399, 2.2401, null)'))\n\tFalse\n\t>>> e(c('\"null\"' 'in' \"(2.2399, 'null', null)\"))\n\tTrue\n\t>>> li = create_lang_instance({'foo' : 'foo'})\n\t>>> c = li.aml_compile\n\t>>> e = li.aml_evaluate\n\t>>> e(c('foo = \"foo\"'))\n\tTrue\n\t>>> li = create_lang_instance()\n\t>>> c = li.aml_compile\n\t>>> p = li.aml_translate_python\n\t>>> s = li.aml_translate_sql\n\t>>> s(c('null = null'))\n\tu'null is null'\n\t>>> p(c('null = null'))\n\tu'None == None'\n\t>>> s(c('null != null'))\n\tu'null is not null'\n\t>>> p(c('null != null'))\n\tu'None != None'\n\t>>> s(c('5 != 3'))\n\tu'5 <> 3'\n\t>>> p(c('5 != 3'))\n\tu'5 != 3'\n\t>>> p(c('5 in (3, 4, 5)'))\n\tu'5 in (3, 4, 5,)'\n\t>>> p(s('5 in (3, 4, 5)'))\n\tu'5 in (3, 4, 5)'\n\t>>> li = create_lang_instance({'foo' : 'bar', 'fo2' : 'ba2'})\n\t>>> c = li.aml_compile\n\t>>> p = li.aml_translate_python\n\t>>> e = li.aml_evaluate\n\t>>> u = li.aml_suggest\n\t>>> u('1 = fo')\n\t[u'fo2', u'foo']\n\t>>> u('1 = FO')\n\t[u'fo2', u'foo']\n\t>>> p(c('null = null'))\n\tu'None == None'\n\t>>> e(c('foo = \"bar\"'))\n\tTrue\n\t>>> e(c('fo2 = \"ba2\"'))\n\tTrue", "scope": {"holder": "gtzampanakis-aml", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:gunyarakun/python-shogi:shogi/__init__.py:Board.is_checkmate#9784", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "shogi/__init__.py", "symbol": "Board.is_checkmate"}, "source_id": "csn:gunyarakun/python-shogi:shogi/__init__.py:Board.is_checkmate#9784"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/gunyarakun/python-shogi/blob/137fe5f5e72251e8a97a1dba4a9b44b7c3c79914/shogi/__init__.py#L933-L942", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:gunyarakun-python-shogi:Board.is_checkmate-33827e821e", "question": "Checks if the current position is a checkmate.", "scope": {"holder": "gunyarakun-python-shogi", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:gunyarakun/python-shogi:shogi/__init__.py:Board.reset#9777", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "shogi/__init__.py", "symbol": "Board.reset"}, "source_id": "csn:gunyarakun/python-shogi:shogi/__init__.py:Board.reset#9777"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/gunyarakun/python-shogi/blob/137fe5f5e72251e8a97a1dba4a9b44b7c3c79914/shogi/__init__.py#L526-L564", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:gunyarakun-python-shogi:Board.reset-892d07ed22", "question": "Restores the starting position.", "scope": {"holder": "gunyarakun-python-shogi", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:gvalkov/tornado-http-auth:tornado_http_auth.py:auth_required#17243", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "tornado_http_auth.py", "symbol": "auth_required"}, "source_id": "csn:gvalkov/tornado-http-auth:tornado_http_auth.py:auth_required#17243"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/gvalkov/tornado-http-auth/blob/9eb225c1740fad1e53320b55d8d4fc6ab4ba58b6/tornado_http_auth.py#L227-L234", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:gvalkov-tornado-http-auth:auth_required-fa7991fb9b", "question": "Decorator that protect methods with HTTP authentication.", "scope": {"holder": "gvalkov-tornado-http-auth", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:h2non/pook:pook/matchers/base.py:BaseMatcher.compare#10820", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pook/matchers/base.py", "symbol": "BaseMatcher.compare"}, "source_id": "csn:h2non/pook:pook/matchers/base.py:BaseMatcher.compare#10820"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/h2non/pook/blob/e64094e41e4d89d98d2d29af7608ef27dc50cf19/pook/matchers/base.py#L47-L59", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:h2non-pook:BaseMatcher.compare-002b64f2bc", "question": "Compares two values with regular expression matching support.\n\n Arguments:\n value (mixed): value to compare.\n expectation (mixed): value to match.\n regex_expr (bool, optional): enables string based regex matching.\n\n Returns:\n bool", "scope": {"holder": "h2non-pook", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:h2non/pook:pook/mock.py:Mock.persist#10846", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pook/mock.py", "symbol": "Mock.persist"}, "source_id": "csn:h2non/pook:pook/mock.py:Mock.persist#10846"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/h2non/pook/blob/e64094e41e4d89d98d2d29af7608ef27dc50cf19/pook/mock.py#L496-L503", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:h2non-pook:Mock.persist-ddcfe1b533", "question": "Enables persistent mode for the current mock.\n\n Returns:\n self: current Mock instance.", "scope": {"holder": "h2non-pook", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:h2oai/h2o-3:h2o-docs/src/product/sphinxext/apigen.py:ApiDocWriter._get_object_name#2321", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "h2o-docs/src/product/sphinxext/apigen.py", "symbol": "ApiDocWriter._get_object_name"}, "source_id": "csn:h2oai/h2o-3:h2o-docs/src/product/sphinxext/apigen.py:ApiDocWriter._get_object_name#2321"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/h2oai/h2o-3/blob/dd62aaa1e7f680a8b16ee14bc66b0fb5195c2ad8/h2o-docs/src/product/sphinxext/apigen.py#L97-L110", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:h2oai-h2o-3:ApiDocWriter._get_object_name-221282694a", "question": "Get second token in line\n >>> docwriter = ApiDocWriter('sphinx')\n >>> docwriter._get_object_name(\" def func(): \")\n 'func'\n >>> docwriter._get_object_name(\" class Klass(object): \")\n 'Klass'\n >>> docwriter._get_object_name(\" class Klass: \")\n 'Klass'", "scope": {"holder": "h2oai-h2o-3", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:h2oai/h2o-3:h2o-py/h2o/model/model_base.py:ModelBase._check_targets#2296", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "h2o-py/h2o/model/model_base.py", "symbol": "ModelBase._check_targets"}, "source_id": "csn:h2oai/h2o-3:h2o-py/h2o/model/model_base.py:ModelBase._check_targets#2296"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/h2oai/h2o-3/blob/dd62aaa1e7f680a8b16ee14bc66b0fb5195c2ad8/h2o-py/h2o/model/model_base.py#L1299-L1308", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:h2oai-h2o-3:ModelBase._check_targets-8a0ba3389d", "question": "Check that y_actual and y_predicted have the same length.\n\n :param H2OFrame y_actual:\n :param H2OFrame y_predicted:\n\n :returns: None", "scope": {"holder": "h2oai-h2o-3", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:hamelsmu/ktext:ktext/data_gen.py:Neg_Sampling_Data_Gen.on_epoch_end#8621", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "ktext/data_gen.py", "symbol": "Neg_Sampling_Data_Gen.on_epoch_end"}, "source_id": "csn:hamelsmu/ktext:ktext/data_gen.py:Neg_Sampling_Data_Gen.on_epoch_end#8621"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/hamelsmu/ktext/blob/221f09f5b1762705075fd1bd914881c0724d5e02/ktext/data_gen.py#L72-L76", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:hamelsmu-ktext:Neg_Sampling_Data_Gen.on_epoch_end-fbd1aec382", "question": "Updates indexes after each epoch for shuffling", "scope": {"holder": "hamelsmu-ktext", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:hamelsmu/ktext:ktext/preprocess.py:processor.generate_doc_length_stats#8627", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "ktext/preprocess.py", "symbol": "processor.generate_doc_length_stats"}, "source_id": "csn:hamelsmu/ktext:ktext/preprocess.py:processor.generate_doc_length_stats#8627"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/hamelsmu/ktext/blob/221f09f5b1762705075fd1bd914881c0724d5e02/ktext/preprocess.py#L237-L252", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:hamelsmu-ktext:processor.generate_doc_length_stats-ca715286ac", "question": "Analyze document length statistics for padding strategy", "scope": {"holder": "hamelsmu-ktext", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:hdima/erlport:priv/python3/erlport/erlproto.py:Port.close#7435", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "priv/python3/erlport/erlproto.py", "symbol": "Port.close"}, "source_id": "csn:hdima/erlport:priv/python3/erlport/erlproto.py:Port.close#7435"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/hdima/erlport/blob/246b7722d62b87b48be66d9a871509a537728962/priv/python3/erlport/erlproto.py#L115-L118", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:hdima-erlport:Port.close-df391228ef", "question": "Close port.", "scope": {"holder": "hdima-erlport", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:hdima/erlport:priv/python3/erlport/erlterms.py:decode#7436", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "priv/python3/erlport/erlterms.py", "symbol": "decode"}, "source_id": "csn:hdima/erlport:priv/python3/erlport/erlterms.py:decode#7436"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/hdima/erlport/blob/246b7722d62b87b48be66d9a871509a537728962/priv/python3/erlport/erlterms.py#L168-L188", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:hdima-erlport:decode-27951b08a9", "question": "Decode Erlang external term.", "scope": {"holder": "hdima-erlport", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:hipikat/adjspecies:adjspecies/__init__.py:_random_adjspecies_pair#18970", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "adjspecies/__init__.py", "symbol": "_random_adjspecies_pair"}, "source_id": "csn:hipikat/adjspecies:adjspecies/__init__.py:_random_adjspecies_pair#18970"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/hipikat/adjspecies/blob/bffceceb08a868ea215f16dd341159d39ca75971/adjspecies/__init__.py#L52-L58", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:hipikat-adjspecies:_random_adjspecies_pair-a27e90dbb1", "question": "Return an ordered 2-tuple containing a species and a describer.", "scope": {"holder": "hipikat-adjspecies", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:hipikat/adjspecies:adjspecies/__init__.py:get_file_lines#18968", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "adjspecies/__init__.py", "symbol": "get_file_lines"}, "source_id": "csn:hipikat/adjspecies:adjspecies/__init__.py:get_file_lines#18968"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/hipikat/adjspecies/blob/bffceceb08a868ea215f16dd341159d39ca75971/adjspecies/__init__.py#L25-L29", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:hipikat-adjspecies:get_file_lines-6db3f68028", "question": "Return a list of non-empty lines from `file_path`.", "scope": {"holder": "hipikat-adjspecies", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:hiposfer/o2g:o2g/gtfs/gtfs_writer.py:GTFSWriter.write_unzipped#12966", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "o2g/gtfs/gtfs_writer.py", "symbol": "GTFSWriter.write_unzipped"}, "source_id": "csn:hiposfer/o2g:o2g/gtfs/gtfs_writer.py:GTFSWriter.write_unzipped#12966"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/hiposfer/o2g/blob/1165ba75a5eb64b3091e9b71ebd589507ae1ebf3/o2g/gtfs/gtfs_writer.py#L119-L127", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:hiposfer-o2g:GTFSWriter.write_unzipped-42ca953ce9", "question": "Write GTFS text files in the given path.", "scope": {"holder": "hiposfer-o2g", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:hiposfer/o2g:o2g/gtfs/gtfs_dummy.py:_create_dummy_trip_stoptimes#12964", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "o2g/gtfs/gtfs_dummy.py", "symbol": "_create_dummy_trip_stoptimes"}, "source_id": "csn:hiposfer/o2g:o2g/gtfs/gtfs_dummy.py:_create_dummy_trip_stoptimes#12964"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/hiposfer/o2g/blob/1165ba75a5eb64b3091e9b71ebd589507ae1ebf3/o2g/gtfs/gtfs_dummy.py#L117-L162", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:hiposfer-o2g:_create_dummy_trip_stoptimes-f4c072bec7", "question": "Create station stop times for each trip.", "scope": {"holder": "hiposfer-o2g", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:hirmeos/entity-fishing-client-python:nerd/client.py:ApiClient.call_api#13156", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "nerd/client.py", "symbol": "ApiClient.call_api"}, "source_id": "csn:hirmeos/entity-fishing-client-python:nerd/client.py:ApiClient.call_api#13156"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/hirmeos/entity-fishing-client-python/blob/cd5c6e10c6c4e653669e11d735d5773766986bda/nerd/client.py#L93-L141", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:hirmeos-entity-fishing-client-python:ApiClient.call_api-7e00d922a9", "question": "Call API.\n\n This returns object containing data, with error details if applicable.\n\n Args:\n method (str): The HTTP method to use.\n url (str): Resource location relative to the base URL.\n headers (dict or None): Extra request headers to set.\n params (dict or None): Query-string parameters.\n data (dict or None): Request body contents for POST or PUT requests.\n files (dict or None: Files to be passed to the request.\n timeout (int): Maximum time before timing out.\n\n Returns:\n ResultParser or ErrorParser.", "scope": {"holder": "hirmeos-entity-fishing-client-python", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:hirmeos/entity-fishing-client-python:nerd/nerd_client.py:NerdClient._process_query#13161", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "nerd/nerd_client.py", "symbol": "NerdClient._process_query"}, "source_id": "csn:hirmeos/entity-fishing-client-python:nerd/nerd_client.py:NerdClient._process_query#13161"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/hirmeos/entity-fishing-client-python/blob/cd5c6e10c6c4e653669e11d735d5773766986bda/nerd/nerd_client.py#L39-L133", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:hirmeos-entity-fishing-client-python:NerdClient._process_query-fce7088d6e", "question": "Process query recursively, if the text is too long,\n it is split and processed bit a bit.\n\n Args:\n query (sdict): Text to be processed.\n prepared (bool): True when the query is ready to be submitted via\n POST request.\n Returns:\n str: Body ready to be submitted to the API.", "scope": {"holder": "hirmeos-entity-fishing-client-python", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:hivetech/dna:python/dna/apy/worker.py:RestfulWorker.delete#19354", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "python/dna/apy/worker.py", "symbol": "RestfulWorker.delete"}, "source_id": "csn:hivetech/dna:python/dna/apy/worker.py:RestfulWorker.delete#19354"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/hivetech/dna/blob/50ad00031be29765b2576fa407d35a36e0608de9/python/dna/apy/worker.py#L117-L135", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:hivetech-dna:RestfulWorker.delete-19b514f15a", "question": "Stop and remove a worker", "scope": {"holder": "hivetech-dna", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:hivetech/dna:python/dna/debug.py:emphasis#19257", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "python/dna/debug.py", "symbol": "emphasis"}, "source_id": "csn:hivetech/dna:python/dna/debug.py:emphasis#19257"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/hivetech/dna/blob/50ad00031be29765b2576fa407d35a36e0608de9/python/dna/debug.py#L28-L38", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:hivetech-dna:emphasis-82fb9e4b30", "question": "Clearer data printing", "scope": {"holder": "hivetech-dna", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:horazont/aiosasl:aiosasl/__init__.py:SASLState.from_reply#15463", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "aiosasl/__init__.py", "symbol": "SASLState.from_reply"}, "source_id": "csn:horazont/aiosasl:aiosasl/__init__.py:SASLState.from_reply#15463"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/horazont/aiosasl/blob/af58bf30f688757e58af6e87892d35a8ce798482/aiosasl/__init__.py#L316-L340", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:horazont-aiosasl:SASLState.from_reply-51566cb431", "question": "Comptaibility layer for old :class:`SASLInterface`\n implementations.\n\n Accepts the follwing set of :class:`SASLState` or strings and\n maps the strings to :class:`SASLState` elements as follows:\n\n ``\"challenge\"``\n :member:`SASLState.CHALLENGE`\n\n ``\"failue\"``\n :member:`SASLState.FAILURE`\n\n ``\"success\"``\n :member:`SASLState.SUCCESS`", "scope": {"holder": "horazont-aiosasl", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:horazont/aiosasl:aiosasl/__init__.py:SASLStateMachine.response#15465", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "aiosasl/__init__.py", "symbol": "SASLStateMachine.response"}, "source_id": "csn:horazont/aiosasl:aiosasl/__init__.py:SASLStateMachine.response#15465"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/horazont/aiosasl/blob/af58bf30f688757e58af6e87892d35a8ce798482/aiosasl/__init__.py#L464-L509", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:horazont-aiosasl:SASLStateMachine.response-ff360e5ec4", "question": "Send a response to the previously received challenge, with the given\n `payload`. The payload is encoded using base64 and transmitted to the\n server.\n\n Return the next state of the state machine as tuple (see\n :class:`SASLStateMachine` for details).", "scope": {"holder": "horazont-aiosasl", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:howie6879/ruia:ruia/middleware.py:Middleware.request#3548", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "ruia/middleware.py", "symbol": "Middleware.request"}, "source_id": "csn:howie6879/ruia:ruia/middleware.py:Middleware.request#3548"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/howie6879/ruia/blob/2dc5262fc9c3e902a8faa7d5fa2f046f9d9ee1fa/ruia/middleware.py#L19-L31", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:howie6879-ruia:Middleware.request-65b7853bc7", "question": "Define a Decorate to be called before a request.\n eg: @middleware.request", "scope": {"holder": "howie6879-ruia", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:howie6879/ruia:ruia/spider.py:Spider.async_start#3554", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "ruia/spider.py", "symbol": "Spider.async_start"}, "source_id": "csn:howie6879/ruia:ruia/spider.py:Spider.async_start#3554"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/howie6879/ruia/blob/2dc5262fc9c3e902a8faa7d5fa2f046f9d9ee1fa/ruia/spider.py#L265-L283", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:howie6879-ruia:Spider.async_start-65c1ef5632", "question": "Start an async spider\n :param middleware: customize middleware or a list of middleware\n :param loop:\n :param after_start: hook\n :param before_stop: hook\n :return:", "scope": {"holder": "howie6879-ruia", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:hustlzp/Flask-Boost:flask_boost/cli.py:_mkdir_p#7250", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "flask_boost/cli.py", "symbol": "_mkdir_p"}, "source_id": "csn:hustlzp/Flask-Boost:flask_boost/cli.py:_mkdir_p#7250"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/hustlzp/Flask-Boost/blob/d0308408ebb248dd752b77123b845f8ec637fab2/flask_boost/cli.py#L303-L313", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:hustlzp-Flask-Boost:_mkdir_p-6228ecaf71", "question": "mkdir -p path", "scope": {"holder": "hustlzp-Flask-Boost", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:hustlzp/Flask-Boost:flask_boost/project/application/utils/account.py:get_current_user#7260", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "flask_boost/project/application/utils/account.py", "symbol": "get_current_user"}, "source_id": "csn:hustlzp/Flask-Boost:flask_boost/project/application/utils/account.py:get_current_user#7260"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/hustlzp/Flask-Boost/blob/d0308408ebb248dd752b77123b845f8ec637fab2/flask_boost/project/application/utils/account.py#L17-L25", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:hustlzp-Flask-Boost:get_current_user-e1dd0ad4be", "question": "Get current user.", "scope": {"holder": "hustlzp-Flask-Boost", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:hydrosquall/tiingo-python:tiingo/restclient.py:RestClient._request#6755", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "tiingo/restclient.py", "symbol": "RestClient._request"}, "source_id": "csn:hydrosquall/tiingo-python:tiingo/restclient.py:RestClient._request#6755"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/hydrosquall/tiingo-python/blob/9bb98ca9d24f2e4db651cf0590e4b47184546482/tiingo/restclient.py#L39-L58", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:hydrosquall-tiingo-python:RestClient._request-539a34cad3", "question": "Make HTTP request and return response object\n\n Args:\n method (str): GET, POST, PUT, DELETE\n url (str): path appended to the base_url to create request\n **kwargs: passed directly to a requests.request object", "scope": {"holder": "hydrosquall-tiingo-python", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:hydrosquall/tiingo-python:tiingo/api.py:TiingoClient.get_ticker_metadata#6748", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "tiingo/api.py", "symbol": "TiingoClient.get_ticker_metadata"}, "source_id": "csn:hydrosquall/tiingo-python:tiingo/api.py:TiingoClient.get_ticker_metadata#6748"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/hydrosquall/tiingo-python/blob/9bb98ca9d24f2e4db651cf0590e4b47184546482/tiingo/api.py#L127-L140", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:hydrosquall-tiingo-python:TiingoClient.get_ticker_metadata-11320d7742", "question": "Return metadata for 1 ticker\n Use TiingoClient.list_tickers() to get available options\n\n Args:\n ticker (str) : Unique identifier for stock", "scope": {"holder": "hydrosquall-tiingo-python", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:ianare/django-memcache-admin:memcache_admin/views.py:_context_data#18011", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "memcache_admin/views.py", "symbol": "_context_data"}, "source_id": "csn:ianare/django-memcache-admin:memcache_admin/views.py:_context_data#18011"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/ianare/django-memcache-admin/blob/330db10139ccf04c6137255e23115482b0c89aec/memcache_admin/views.py#L67-L74", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:ianare-django-memcache-admin:_context_data-063eda1923", "question": "Add admin global context, for compatibility with Django 1.7", "scope": {"holder": "ianare-django-memcache-admin", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:ianare/django-memcache-admin:memcache_admin/views.py:dashboard#18013", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "memcache_admin/views.py", "symbol": "dashboard"}, "source_id": "csn:ianare/django-memcache-admin:memcache_admin/views.py:dashboard#18013"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/ianare/django-memcache-admin/blob/330db10139ccf04c6137255e23115482b0c89aec/memcache_admin/views.py#L88-L113", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:ianare-django-memcache-admin:dashboard-3d8ebff333", "question": "Show the dashboard.", "scope": {"holder": "ianare-django-memcache-admin", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:iandees/pyosm:pyosm/parsing.py:iter_changeset_stream#15015", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pyosm/parsing.py", "symbol": "iter_changeset_stream"}, "source_id": "csn:iandees/pyosm:pyosm/parsing.py:iter_changeset_stream#15015"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/iandees/pyosm/blob/532dffceae91e2bce89c530ceff627bc8210f8aa/pyosm/parsing.py#L53-L133", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:iandees-pyosm:iter_changeset_stream-2e67754040", "question": "Start processing an OSM changeset stream and yield one (action, primitive) tuple\n at a time to the caller.", "scope": {"holder": "iandees-pyosm", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:iandees/pyosm:pyosm/parsing.py:parse_osm_file#15017", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pyosm/parsing.py", "symbol": "parse_osm_file"}, "source_id": "csn:iandees/pyosm:pyosm/parsing.py:parse_osm_file#15017"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/iandees/pyosm/blob/532dffceae91e2bce89c530ceff627bc8210f8aa/pyosm/parsing.py#L375-L392", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:iandees-pyosm:parse_osm_file-b166fb1b61", "question": "Parse a file-like containing OSM XML into memory and return an object with\n the nodes, ways, and relations it contains.", "scope": {"holder": "iandees-pyosm", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:ibm-watson-iot/iot-python:src/wiotp/sdk/client.py:AbstractClient._onConnect#8485", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "src/wiotp/sdk/client.py", "symbol": "AbstractClient._onConnect"}, "source_id": "csn:ibm-watson-iot/iot-python:src/wiotp/sdk/client.py:AbstractClient._onConnect#8485"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/ibm-watson-iot/iot-python/blob/195f05adce3fba4ec997017e41e02ebd85c0c4cc/src/wiotp/sdk/client.py#L278-L321", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:ibm-watson-iot-iot-python:AbstractClient._onConnect-d2bf6ef471", "question": "Called when the broker responds to our connection request.\n\n The value of rc determines success or not:\n 0: Connection successful\n 1: Connection refused - incorrect protocol version\n 2: Connection refused - invalid client identifier\n 3: Connection refused - server unavailable\n 4: Connection refused - bad username or password\n 5: Connection refused - not authorised\n 6-255: Currently unused.", "scope": {"holder": "ibm-watson-iot-iot-python", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:ibm-watson-iot/iot-python:tmp/src/things/things.py:addLogicalInterfaceToDeviceType#8467", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "tmp/src/things/things.py", "symbol": "addLogicalInterfaceToDeviceType"}, "source_id": "csn:ibm-watson-iot/iot-python:tmp/src/things/things.py:addLogicalInterfaceToDeviceType#8467"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/ibm-watson-iot/iot-python/blob/195f05adce3fba4ec997017e41e02ebd85c0c4cc/tmp/src/things/things.py#L1081-L1101", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:ibm-watson-iot-iot-python:addLogicalInterfaceToDeviceType-da95e5f798", "question": "Adds a logical interface to a device type.\n Parameters:\n - typeId (string) - the device type\n - logicalInterfaceId (string) - the id returned by the platform on creation of the logical interface\n - description (string) - optional (not used)\n Throws APIException on failure.", "scope": {"holder": "ibm-watson-iot-iot-python", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:idlesign/django-etc:etc/toolbox.py:get_model_class_from_string#15521", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "etc/toolbox.py", "symbol": "get_model_class_from_string"}, "source_id": "csn:idlesign/django-etc:etc/toolbox.py:get_model_class_from_string#15521"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/idlesign/django-etc/blob/dbfc7e9dfc4fdfe69547f71ba4921989f9e97dbe/etc/toolbox.py#L90-L114", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:idlesign-django-etc:get_model_class_from_string-73dec81a4f", "question": "Returns a certain model as defined in a string formatted `<app_name>.<model_name>`.\n\n Example:\n\n model = get_model_class_from_string('myapp.MyModel')", "scope": {"holder": "idlesign-django-etc", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:idlesign/django-etc:etc/toolbox.py:import_app_module#15523", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "etc/toolbox.py", "symbol": "import_app_module"}, "source_id": "csn:idlesign/django-etc:etc/toolbox.py:import_app_module#15523"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/idlesign/django-etc/blob/dbfc7e9dfc4fdfe69547f71ba4921989f9e97dbe/etc/toolbox.py#L190-L214", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:idlesign-django-etc:import_app_module-fcd8b11be1", "question": "Returns a module from a given app by its name.\n\n :param str app_name:\n :param str module_name:\n :rtype: module or None", "scope": {"holder": "idlesign-django-etc", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:idlesign/django-sitetree:sitetree/sitetreeapp.py:Cache.empty#7304", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "sitetree/sitetreeapp.py", "symbol": "Cache.empty"}, "source_id": "csn:idlesign/django-sitetree:sitetree/sitetreeapp.py:Cache.empty#7304"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/idlesign/django-sitetree/blob/61de4608e6e415247c75fe8691027d7c4ed0d1e7/sitetree/sitetreeapp.py#L334-L339", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:idlesign-django-sitetree:Cache.empty-72be2342ba", "question": "Empties cached sitetree data.", "scope": {"holder": "idlesign-django-sitetree", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:idlesign/django-sitetree:sitetree/admin.py:TreeAdmin.dump_view#7348", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "sitetree/admin.py", "symbol": "TreeAdmin.dump_view"}, "source_id": "csn:idlesign/django-sitetree:sitetree/admin.py:TreeAdmin.dump_view#7348"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/idlesign/django-sitetree/blob/61de4608e6e415247c75fe8691027d7c4ed0d1e7/sitetree/admin.py#L357-L364", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:idlesign-django-sitetree:TreeAdmin.dump_view-c961cf8ab5", "question": "Dumps sitetrees with items using django-smuggler.\n\n :param request:\n :return:", "scope": {"holder": "idlesign-django-sitetree", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:idlesign/django-yaturbo:yaturbo/toolbox.py:YandexTurboFeed.configure_analytics_yandex#16994", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "yaturbo/toolbox.py", "symbol": "YandexTurboFeed.configure_analytics_yandex"}, "source_id": "csn:idlesign/django-yaturbo:yaturbo/toolbox.py:YandexTurboFeed.configure_analytics_yandex#16994"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/idlesign/django-yaturbo/blob/a5ac9053bb800ea8082dc0615b93398917c3290a/yaturbo/toolbox.py#L170-L188", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:idlesign-django-yaturbo:YandexTurboFeed.configure_analytics_yandex-c87595c9e2", "question": "Configure Yandex Metrika analytics counter.\n\n :param str|unicode ident: Metrika counter ID.\n\n :param dict params: Additional params.", "scope": {"holder": "idlesign-django-yaturbo", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:idlesign/django-yaturbo:yaturbo/toolbox.py:sanitize_turbo#16993", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "yaturbo/toolbox.py", "symbol": "sanitize_turbo"}, "source_id": "csn:idlesign/django-yaturbo:yaturbo/toolbox.py:sanitize_turbo#16993"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/idlesign/django-yaturbo/blob/a5ac9053bb800ea8082dc0615b93398917c3290a/yaturbo/toolbox.py#L18-L28", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:idlesign-django-yaturbo:sanitize_turbo-d3b924c5d8", "question": "Sanitizes HTML, removing not allowed tags and attributes.\n\n :param str|unicode html:\n\n :param list allowed_tags: List of allowed tags.\n :param dict allowed_attrs: Dictionary with attributes allowed for tags.\n\n :rtype: unicode", "scope": {"holder": "idlesign-django-yaturbo", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:impulsare/config:impulsare_config/reader.py:Reader.parse#20335", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "impulsare_config/reader.py", "symbol": "Reader.parse"}, "source_id": "csn:impulsare/config:impulsare_config/reader.py:Reader.parse#20335"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/impulsare/config/blob/cc9a043d389c132ac42c987fe4740f84c74f53a2/impulsare_config/reader.py#L10-L36", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:impulsare-config:Reader.parse-ba74bf325c", "question": "Read a config_file, check the validity with a JSON Schema as specs\n and get default values from default_file if asked.\n\n All parameters are optionnal.\n\n If there is no config_file defined, read the venv base\n dir and try to get config/app.yml.\n\n If no specs, don't validate anything.\n\n If no default_file, don't merge with default values.", "scope": {"holder": "impulsare-config", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:incuna/django-pgcrypto-fields:pgcrypto/mixins.py:DecryptedCol.as_sql#10866", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pgcrypto/mixins.py", "symbol": "DecryptedCol.as_sql"}, "source_id": "csn:incuna/django-pgcrypto-fields:pgcrypto/mixins.py:DecryptedCol.as_sql#10866"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/incuna/django-pgcrypto-fields/blob/406fddf0cbe9091ba71b97206d0f4719c0450ac1/pgcrypto/mixins.py#L30-L34", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:incuna-django-pgcrypto-fields:DecryptedCol.as_sql-95ca73d3c3", "question": "Build SQL with decryption and casting.", "scope": {"holder": "incuna-django-pgcrypto-fields", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:incuna/django-pgcrypto-fields:pgcrypto/mixins.py:HashMixin.pre_save#10867", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pgcrypto/mixins.py", "symbol": "HashMixin.pre_save"}, "source_id": "csn:incuna/django-pgcrypto-fields:pgcrypto/mixins.py:HashMixin.pre_save#10867"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/incuna/django-pgcrypto-fields/blob/406fddf0cbe9091ba71b97206d0f4719c0450ac1/pgcrypto/mixins.py#L50-L56", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:incuna-django-pgcrypto-fields:HashMixin.pre_save-cac09a3233", "question": "Save the original_value.", "scope": {"holder": "incuna-django-pgcrypto-fields", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:incuna/django-user-management:user_management/models/mixins.py:EmailVerifyUserMethodsMixin.send_password_reset#14385", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "user_management/models/mixins.py", "symbol": "EmailVerifyUserMethodsMixin.send_password_reset"}, "source_id": "csn:incuna/django-user-management:user_management/models/mixins.py:EmailVerifyUserMethodsMixin.send_password_reset#14385"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/incuna/django-user-management/blob/6784e33191d4eff624d2cf2df9ca01db4f23c9c6/user_management/models/mixins.py#L163-L166", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:incuna-django-user-management:EmailVerifyUserMethodsMixin.send_password_reset-0204efa32d", "question": "Send a password reset to the user's email address.", "scope": {"holder": "incuna-django-user-management", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:incuna/django-user-management:user_management/api/views.py:ResendConfirmationEmail.post#14406", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "user_management/api/views.py", "symbol": "ResendConfirmationEmail.post"}, "source_id": "csn:incuna/django-user-management:user_management/api/views.py:ResendConfirmationEmail.post#14406"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/incuna/django-user-management/blob/6784e33191d4eff624d2cf2df9ca01db4f23c9c6/user_management/api/views.py#L289-L301", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:incuna-django-user-management:ResendConfirmationEmail.post-792b25e080", "question": "Validate `email` and send a request to confirm it.", "scope": {"holder": "incuna-django-user-management", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:incuna/django-wkhtmltopdf:wkhtmltopdf/views.py:PDFTemplateResponse.rendered_content#9859", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "wkhtmltopdf/views.py", "symbol": "PDFTemplateResponse.rendered_content"}, "source_id": "csn:incuna/django-wkhtmltopdf:wkhtmltopdf/views.py:PDFTemplateResponse.rendered_content#9859"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/incuna/django-wkhtmltopdf/blob/4e73f604c48f7f449c916c4257a72af59517322c/wkhtmltopdf/views.py#L64-L82", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:incuna-django-wkhtmltopdf:PDFTemplateResponse.rendered_content-2bed8514e7", "question": "Returns the freshly rendered content for the template and context\n described by the PDFResponse.\n\n This *does not* set the final content of the response. To set the\n response content, you must either call render(), or set the\n content explicitly using the value of this property.", "scope": {"holder": "incuna-django-wkhtmltopdf", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:incuna/django-wkhtmltopdf:wkhtmltopdf/utils.py:http_quote#9863", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "wkhtmltopdf/utils.py", "symbol": "http_quote"}, "source_id": "csn:incuna/django-wkhtmltopdf:wkhtmltopdf/utils.py:http_quote#9863"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/incuna/django-wkhtmltopdf/blob/4e73f604c48f7f449c916c4257a72af59517322c/wkhtmltopdf/utils.py#L254-L270", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:incuna-django-wkhtmltopdf:http_quote-a0b93a5d7b", "question": "Given a unicode string, will do its dandiest to give you back a\n valid ascii charset string you can use in, say, http headers and the\n like.", "scope": {"holder": "incuna-django-wkhtmltopdf", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:ingolemo/python-lenses:examples/naughts_and_crosses.py:Board._potential_wins#13709", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "examples/naughts_and_crosses.py", "symbol": "Board._potential_wins"}, "source_id": "csn:ingolemo/python-lenses:examples/naughts_and_crosses.py:Board._potential_wins#13709"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/ingolemo/python-lenses/blob/a3a6ed0a31f6674451e542e7380a8aa16e6f8edf/examples/naughts_and_crosses.py#L71-L77", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:ingolemo-python-lenses:Board._potential_wins-cd21261a18", "question": "Generates all the combinations of board positions that need\n to be checked for a win.", "scope": {"holder": "ingolemo-python-lenses", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:ingolemo/python-lenses:lenses/optics/base.py:LensLike.to_list_of#13694", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "lenses/optics/base.py", "symbol": "LensLike.to_list_of"}, "source_id": "csn:ingolemo/python-lenses:lenses/optics/base.py:LensLike.to_list_of#13694"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/ingolemo/python-lenses/blob/a3a6ed0a31f6674451e542e7380a8aa16e6f8edf/lenses/optics/base.py#L174-L186", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:ingolemo-python-lenses:LensLike.to_list_of-62dffda9f0", "question": "Returns a list of all the foci within `state`.\n\n Requires kind Fold. This method will raise TypeError if the\n optic has no way to get any foci.", "scope": {"holder": "ingolemo-python-lenses", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:instagrambot/instabot:instabot/api/api.py:API.json_data#2385", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "instabot/api/api.py", "symbol": "API.json_data"}, "source_id": "csn:instagrambot/instabot:instabot/api/api.py:API.json_data#2385"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/instagrambot/instabot/blob/d734f892ac4cc35d22746a4f2680425ffaff0927/instabot/api/api.py#L283-L288", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:instagrambot-instabot:API.json_data-652f6316d9", "question": "Adds the default_data to data and dumps it to a json.", "scope": {"holder": "instagrambot-instabot", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:instagrambot/instabot:instabot/bot/bot_like.py:like_hashtag#2392", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "instabot/bot/bot_like.py", "symbol": "like_hashtag"}, "source_id": "csn:instagrambot/instabot:instabot/bot/bot_like.py:like_hashtag#2392"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/instagrambot/instabot/blob/d734f892ac4cc35d22746a4f2680425ffaff0927/instabot/bot/bot_like.py#L117-L121", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:instagrambot-instabot:like_hashtag-99bc02d48f", "question": "Likes last medias from hashtag", "scope": {"holder": "instagrambot-instabot", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:intel-analytics/BigDL:pyspark/bigdl/optim/optimizer.py:BaseOptimizer.set_checkpoint#1626", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pyspark/bigdl/optim/optimizer.py", "symbol": "BaseOptimizer.set_checkpoint"}, "source_id": "csn:intel-analytics/BigDL:pyspark/bigdl/optim/optimizer.py:BaseOptimizer.set_checkpoint#1626"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/intel-analytics/BigDL/blob/e9c19788285986ab789a2e2998f9a85d7524779f/pyspark/bigdl/optim/optimizer.py#L719-L732", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:intel-analytics-BigDL:BaseOptimizer.set_checkpoint-575874d084", "question": "Configure checkpoint settings.\n\n\n :param checkpoint_trigger: the interval to write snapshots\n :param checkpoint_path: the path to write snapshots into\n :param isOverWrite: whether to overwrite existing snapshots in path.default is True", "scope": {"holder": "intel-analytics-BigDL", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:intel-analytics/BigDL:pyspark/bigdl/nn/layer.py:Layer.unfreeze#1701", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pyspark/bigdl/nn/layer.py", "symbol": "Layer.unfreeze"}, "source_id": "csn:intel-analytics/BigDL:pyspark/bigdl/nn/layer.py:Layer.unfreeze#1701"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/intel-analytics/BigDL/blob/e9c19788285986ab789a2e2998f9a85d7524779f/pyspark/bigdl/nn/layer.py#L586-L593", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:intel-analytics-BigDL:Layer.unfreeze-a080a7d694", "question": "unfreeze module, if names is not None, unfreeze layers that match given names\n :param names: an array of layer names\n :return:", "scope": {"holder": "intel-analytics-BigDL", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:inveniosoftware/counter-robots:counter_robots/__init__.py:memoize#19249", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "counter_robots/__init__.py", "symbol": "memoize"}, "source_id": "csn:inveniosoftware/counter-robots:counter_robots/__init__.py:memoize#19249"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/inveniosoftware/counter-robots/blob/484943fdc7e08f41d3ad7a9e2229afe0cec05547/counter_robots/__init__.py#L27-L36", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:inveniosoftware-counter-robots:memoize-edbb92bd77", "question": "Cache result of function call.", "scope": {"holder": "inveniosoftware-counter-robots", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:inveniosoftware/counter-robots:scripts/update-lists.py:update_file#19216", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "scripts/update-lists.py", "symbol": "update_file"}, "source_id": "csn:inveniosoftware/counter-robots:scripts/update-lists.py:update_file#19216"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/inveniosoftware/counter-robots/blob/484943fdc7e08f41d3ad7a9e2229afe0cec05547/scripts/update-lists.py#L43-L52", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:inveniosoftware-counter-robots:update_file-43f98ab7f6", "question": "Update the content of a single file.", "scope": {"holder": "inveniosoftware-counter-robots", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:inveniosoftware/invenio-migrator:invenio_migrator/records.py:RecordDump.is_deleted#18706", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "invenio_migrator/records.py", "symbol": "RecordDump.is_deleted"}, "source_id": "csn:inveniosoftware/invenio-migrator:invenio_migrator/records.py:RecordDump.is_deleted#18706"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/inveniosoftware/invenio-migrator/blob/6902c6968a39b747d15e32363f43b7dffe2622c2/invenio_migrator/records.py#L337-L343", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:inveniosoftware-invenio-migrator:RecordDump.is_deleted-7a39c09fcd", "question": "Check if record is deleted.", "scope": {"holder": "inveniosoftware-invenio-migrator", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:inveniosoftware/invenio-migrator:invenio_migrator/legacy/remotetokens.py:dump#18657", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "invenio_migrator/legacy/remotetokens.py", "symbol": "dump"}, "source_id": "csn:inveniosoftware/invenio-migrator:invenio_migrator/legacy/remotetokens.py:dump#18657"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/inveniosoftware/invenio-migrator/blob/6902c6968a39b747d15e32363f43b7dffe2622c2/invenio_migrator/legacy/remotetokens.py#L37-L48", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:inveniosoftware-invenio-migrator:dump-f24dcd91ca", "question": "Dump the remote tokens as a list of dictionaries.\n\n :param ra: Remote toekn to be dumped.\n :type ra: `invenio_oauthclient.models.RemoteToken [Invenio2.x]`\n :returns: Remote tokens serialized to dictionary.\n :rtype: dict", "scope": {"holder": "inveniosoftware-invenio-migrator", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:inveniosoftware/invenio-records-ui:invenio_records_ui/ext.py:InvenioRecordsUI.init_app#17782", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "invenio_records_ui/ext.py", "symbol": "InvenioRecordsUI.init_app"}, "source_id": "csn:inveniosoftware/invenio-records-ui:invenio_records_ui/ext.py:InvenioRecordsUI.init_app#17782"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/inveniosoftware/invenio-records-ui/blob/ae92367978f2e1e96634685bd296f0fd92b4da54/invenio_records_ui/ext.py#L64-L70", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:inveniosoftware-invenio-records-ui:InvenioRecordsUI.init_app-42921035d3", "question": "Flask application initialization.\n\n :param app: The Flask application.", "scope": {"holder": "inveniosoftware-invenio-records-ui", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:inveniosoftware/invenio-records-ui:invenio_records_ui/views.py:export#17787", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "invenio_records_ui/views.py", "symbol": "export"}, "source_id": "csn:inveniosoftware/invenio-records-ui:invenio_records_ui/views.py:export#17787"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/inveniosoftware/invenio-records-ui/blob/ae92367978f2e1e96634685bd296f0fd92b4da54/invenio_records_ui/views.py#L231-L260", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:inveniosoftware-invenio-records-ui:export-abd46377c3", "question": "r\"\"\"Record serialization view.\n\n Serializes record with given format and renders record export template.\n\n :param pid: PID object.\n :param record: Record object.\n :param template: Template to render.\n :param \\*\\*kwargs: Additional view arguments based on URL rule.\n :return: The rendered template.", "scope": {"holder": "inveniosoftware-invenio-records-ui", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:ioam/parambokeh:parambokeh/widgets.py:TextWidget#14421", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "parambokeh/widgets.py", "symbol": "TextWidget"}, "source_id": "csn:ioam/parambokeh:parambokeh/widgets.py:TextWidget#14421"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/ioam/parambokeh/blob/fb9744f216273c7b24e65d037b1d621c08d7fde6/parambokeh/widgets.py#L16-L20", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:ioam-parambokeh:TextWidget-3ffadd7b60", "question": "Forces a parameter value to be text", "scope": {"holder": "ioam-parambokeh", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:ioam/parambokeh:parambokeh/util.py:get_method_owner#14423", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "parambokeh/util.py", "symbol": "get_method_owner"}, "source_id": "csn:ioam/parambokeh:parambokeh/util.py:get_method_owner#14423"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/ioam/parambokeh/blob/fb9744f216273c7b24e65d037b1d621c08d7fde6/parambokeh/util.py#L34-L43", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:ioam-parambokeh:get_method_owner-3a4f9f5a81", "question": "Returns the instance owning the supplied instancemethod or\n the class owning the supplied classmethod.", "scope": {"holder": "ioam-parambokeh", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:ionelmc/python-tblib:src/tblib/__init__.py:Traceback.to_dict#11831", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "src/tblib/__init__.py", "symbol": "Traceback.to_dict"}, "source_id": "csn:ionelmc/python-tblib:src/tblib/__init__.py:Traceback.to_dict#11831"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/ionelmc/python-tblib/blob/00be69aa97e1eb1c09282b1cdb72539c947d4515/src/tblib/__init__.py#L141-L160", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:ionelmc-python-tblib:Traceback.to_dict-dafac6ebb0", "question": "Convert a Traceback into a dictionary representation", "scope": {"holder": "ionelmc-python-tblib", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:iotaledger/iota.lib.py:iota/types.py:Address._generate_checksum#7538", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "iota/types.py", "symbol": "Address._generate_checksum"}, "source_id": "csn:iotaledger/iota.lib.py:iota/types.py:Address._generate_checksum#7538"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/iotaledger/iota.lib.py/blob/97cdd1e241498446b46157b79b2a1ea2ec6d387a/iota/types.py#L858-L871", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:iotaledger-iota.lib.py:Address._generate_checksum-a79e6dd149", "question": "Generates the correct checksum for this address.", "scope": {"holder": "iotaledger-iota.lib.py", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:iotaledger/iota.lib.py:iota/crypto/kerl/pykerl.py:Kerl.squeeze#7621", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "iota/crypto/kerl/pykerl.py", "symbol": "Kerl.squeeze"}, "source_id": "csn:iotaledger/iota.lib.py:iota/crypto/kerl/pykerl.py:Kerl.squeeze#7621"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/iotaledger/iota.lib.py/blob/97cdd1e241498446b46157b79b2a1ea2ec6d387a/iota/crypto/kerl/pykerl.py#L82-L144", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:iotaledger-iota.lib.py:Kerl.squeeze-188efbd006", "question": "Squeeze trits from the sponge into a buffer.\n\n :param trits:\n Buffer that will hold the squeezed trits.\n\n IMPORTANT: If ``trits`` is too small, it will be extended!\n\n :param offset:\n Starting offset in ``trits``.\n\n :param length:\n Number of trits to squeeze from the sponge.\n\n If not specified, defaults to :py:data:`TRIT_HASH_LENGTH`\n (i.e., by default, we will try to squeeze exactly 1 hash).", "scope": {"holder": "iotaledger-iota.lib.py", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:iotile/typedargs:typedargs/metadata.py:AnnotatedMetadata.add_param#13645", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "typedargs/metadata.py", "symbol": "AnnotatedMetadata.add_param"}, "source_id": "csn:iotile/typedargs:typedargs/metadata.py:AnnotatedMetadata.add_param#13645"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/iotile/typedargs/blob/0a5091a664b9b4d836e091e9ba583e944f438fd8/typedargs/metadata.py#L109-L129", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:iotile-typedargs:AnnotatedMetadata.add_param-58297703aa", "question": "Add type information for a parameter by name.\n\n Args:\n name (str): The name of the parameter we wish to annotate\n type_name (str): The name of the parameter's type\n validators (list): A list of either strings or n tuples that each\n specify a validator defined for type_name. If a string is passed,\n the validator is invoked with no extra arguments. If a tuple is\n passed, the validator will be invoked with the extra arguments.\n desc (str): Optional parameter description.", "scope": {"holder": "iotile-typedargs", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:iotile/typedargs:typedargs/doc_parser.py:ParsedDocstring._classify_section#13627", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "typedargs/doc_parser.py", "symbol": "ParsedDocstring._classify_section"}, "source_id": "csn:iotile/typedargs:typedargs/doc_parser.py:ParsedDocstring._classify_section#13627"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/iotile/typedargs/blob/0a5091a664b9b4d836e091e9ba583e944f438fd8/typedargs/doc_parser.py#L131-L145", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:iotile-typedargs:ParsedDocstring._classify_section-a1d36b0d44", "question": "Attempt to find the canonical name of this section.", "scope": {"holder": "iotile-typedargs", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:isambard-uob/budeff:src/budeff/force_field.py:BuffForceField._make_ff_params_dict#19411", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "src/budeff/force_field.py", "symbol": "BuffForceField._make_ff_params_dict"}, "source_id": "csn:isambard-uob/budeff:src/budeff/force_field.py:BuffForceField._make_ff_params_dict#19411"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/isambard-uob/budeff/blob/8be099b7e50d4855ad3cc4aa875938da2c9449e6/src/budeff/force_field.py#L143-L165", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:isambard-uob-budeff:BuffForceField._make_ff_params_dict-c09ccb2f9d", "question": "Makes a dictionary containing PyAtomData for the force field.\n\n Returns\n -------\n ff_params_struct_dict: dict\n Dictionary containing PyAtomData structs for the force field\n parameters for each atom in the force field.", "scope": {"holder": "isambard-uob-budeff", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:isambard-uob/budeff:src/budeff/force_field.py:assign_force_field#19409", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "src/budeff/force_field.py", "symbol": "assign_force_field"}, "source_id": "csn:isambard-uob/budeff:src/budeff/force_field.py:assign_force_field#19409"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/isambard-uob/budeff/blob/8be099b7e50d4855ad3cc4aa875938da2c9449e6/src/budeff/force_field.py#L10-L49", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:isambard-uob-budeff:assign_force_field-a0277f0c29", "question": "Assigns force field parameters to Atoms in the AMPAL object.\n\n Parameters\n ----------\n ampal_obj : AMPAL Object\n Any AMPAL object with a `get_atoms` method.\n ff: BuffForceField\n The force field to be used for scoring.", "scope": {"holder": "isambard-uob-budeff", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:its-rigs/Trolly:trolly/authorise.py:Authorise.get_authorisation_url#14535", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "trolly/authorise.py", "symbol": "Authorise.get_authorisation_url"}, "source_id": "csn:its-rigs/Trolly:trolly/authorise.py:Authorise.get_authorisation_url#14535"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/its-rigs/Trolly/blob/483dc94c352df40dc05ead31820b059b2545cf82/trolly/authorise.py#L14-L33", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:its-rigs-Trolly:Authorise.get_authorisation_url-356a3a3766", "question": "Returns a URL that needs to be opened in a browser to retrieve an\n access token.", "scope": {"holder": "its-rigs-Trolly", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:its-rigs/Trolly:trolly/client.py:Client.create_card#14578", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "trolly/client.py", "symbol": "Client.create_card"}, "source_id": "csn:its-rigs/Trolly:trolly/client.py:Client.create_card#14578"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/its-rigs/Trolly/blob/483dc94c352df40dc05ead31820b059b2545cf82/trolly/client.py#L154-L166", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:its-rigs-Trolly:Client.create_card-5bb644fe48", "question": "Create a Card object from JSON object\n\n Returns:\n Card: The card from the given `card_json`.", "scope": {"holder": "its-rigs-Trolly", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:jab/bidict:bidict/_base.py:BidictBase._dedup_item#8640", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "bidict/_base.py", "symbol": "BidictBase._dedup_item"}, "source_id": "csn:jab/bidict:bidict/_base.py:BidictBase._dedup_item#8640"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/jab/bidict/blob/1a1ba9758651aed9c4f58384eff006d2e2ad6835/bidict/_base.py#L241-L293", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:jab-bidict:BidictBase._dedup_item-2e3ca24fa5", "question": "Check *key* and *val* for any duplication in self.\n\n Handle any duplication as per the duplication policies given in *on_dup*.\n\n (key, val) already present is construed as a no-op, not a duplication.\n\n If duplication is found and the corresponding duplication policy is\n :attr:`~bidict.RAISE`, raise the appropriate error.\n\n If duplication is found and the corresponding duplication policy is\n :attr:`~bidict.IGNORE`, return *None*.\n\n If duplication is found and the corresponding duplication policy is\n :attr:`~bidict.OVERWRITE`,\n or if no duplication is found,\n return the _DedupResult *(isdupkey, isdupval, oldkey, oldval)*.", "scope": {"holder": "jab-bidict", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:jab/bidict:bidict/_mut.py:MutableBidict.update#8657", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "bidict/_mut.py", "symbol": "MutableBidict.update"}, "source_id": "csn:jab/bidict:bidict/_mut.py:MutableBidict.update#8657"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/jab/bidict/blob/1a1ba9758651aed9c4f58384eff006d2e2ad6835/bidict/_mut.py#L153-L156", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:jab-bidict:MutableBidict.update-9aaba17aa4", "question": "Like :meth:`putall` with default duplication policies.", "scope": {"holder": "jab-bidict", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:jaraco/jaraco.classes:jaraco/classes/ancestry.py:iter_subclasses#17278", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "jaraco/classes/ancestry.py", "symbol": "iter_subclasses"}, "source_id": "csn:jaraco/jaraco.classes:jaraco/classes/ancestry.py:iter_subclasses#17278"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/jaraco/jaraco.classes/blob/6347957478d589101a0774464d8d282520c2c990/jaraco/classes/ancestry.py#L30-L75", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:jaraco-jaraco.classes:iter_subclasses-3361d3f2d1", "question": "Generator over all subclasses of a given class, in depth-first order.\n\n\t>>> bool in list(iter_subclasses(int))\n\tTrue\n\t>>> class A(object): pass\n\t>>> class B(A): pass\n\t>>> class C(A): pass\n\t>>> class D(B,C): pass\n\t>>> class E(D): pass\n\t>>>\n\t>>> for cls in iter_subclasses(A):\n\t...\t\tprint(cls.__name__)\n\tB\n\tD\n\tE\n\tC\n\t>>> # get ALL (new-style) classes currently defined\n\t>>> res = [cls.__name__ for cls in iter_subclasses(object)]\n\t>>> 'type' in res\n\tTrue\n\t>>> 'tuple' in res\n\tTrue\n\t>>> len(res) > 100\n\tTrue", "scope": {"holder": "jaraco-jaraco.classes", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:jaraco/jaraco.itertools:jaraco/itertools.py:Reusable.reset#15342", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "jaraco/itertools.py", "symbol": "Reusable.reset"}, "source_id": "csn:jaraco/jaraco.itertools:jaraco/itertools.py:Reusable.reset#15342"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/jaraco/jaraco.itertools/blob/0dc47c8924fa3d9ab676c3a6e195f03f728b72c6/jaraco/itertools.py#L554-L560", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:jaraco-jaraco.itertools:Reusable.reset-3814d5658a", "question": "Resets the iterator to the start.\n\n\t\tAny remaining values in the current iteration are discarded.", "scope": {"holder": "jaraco-jaraco.itertools", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:jaraco/jaraco.itertools:jaraco/itertools.py:flatten#15324", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "jaraco/itertools.py", "symbol": "flatten"}, "source_id": "csn:jaraco/jaraco.itertools:jaraco/itertools.py:flatten#15324"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/jaraco/jaraco.itertools/blob/0dc47c8924fa3d9ab676c3a6e195f03f728b72c6/jaraco/itertools.py#L494-L502", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:jaraco-jaraco.itertools:flatten-d362822afb", "question": "*Deprecated*: Use more_itertools.collapse instead.", "scope": {"holder": "jaraco-jaraco.itertools", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:jaraco/jaraco.util:jaraco/util/subprocess.py:Popen_nonblocking#16213", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "jaraco/util/subprocess.py", "symbol": "Popen_nonblocking"}, "source_id": "csn:jaraco/jaraco.util:jaraco/util/subprocess.py:Popen_nonblocking#16213"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/jaraco/jaraco.util/blob/f21071c64f165a5cf844db15e39356e1a47f4b02/jaraco/util/subprocess.py#L17-L52", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:jaraco-jaraco.util:Popen_nonblocking-871aaed7ce", "question": "Open a subprocess without blocking. Return a process handle with any\n\toutput streams replaced by queues of lines from that stream.\n\n\tUsage::\n\n\t\tproc = Popen_nonblocking(..., stdout=subprocess.PIPE)\n\t\ttry:\n\t\t\tout_line = proc.stdout.get_nowait()\n\t\texcept queue.Empty:\n\t\t\t\"no output available\"\n\t\telse:\n\t\t\thandle_output(out_line)", "scope": {"holder": "jaraco-jaraco.util", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:jaraco/jaraco.util:jaraco/util/numbers.py:coerce#15864", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "jaraco/util/numbers.py", "symbol": "coerce"}, "source_id": "csn:jaraco/jaraco.util:jaraco/util/numbers.py:coerce#15864"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/jaraco/jaraco.util/blob/f21071c64f165a5cf844db15e39356e1a47f4b02/jaraco/util/numbers.py#L10-L37", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:jaraco-jaraco.util:coerce-f4c282d5c8", "question": "coerce takes a value and attempts to convert it to a float,\n\tor int.\n\n\tIf none of the conversions are successful, the original value is\n\treturned.\n\n\t>>> coerce('3')\n\t3\n\n\t>>> coerce('3.0')\n\t3.0\n\n\t>>> coerce('foo')\n\t'foo'\n\n\t>>> coerce({})\n\t{}\n\n\t>>> coerce('{}')\n\t'{}'", "scope": {"holder": "jaraco-jaraco.util", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:jaraco/svg.charts:svg/charts/graph.py:Graph.add_data#14348", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "svg/charts/graph.py", "symbol": "Graph.add_data"}, "source_id": "csn:jaraco/svg.charts:svg/charts/graph.py:Graph.add_data#14348"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/jaraco/svg.charts/blob/23053497b3f1af4e760f355050107ae3bc05909d/svg/charts/graph.py#L100-L109", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:jaraco-svg.charts:Graph.add_data-f09f365fa1", "question": "Add data to the graph object. May be called several times to add\n\t\tadditional data sets.\n\n\t\tconf should be a dictionary including 'data' and 'title' keys", "scope": {"holder": "jaraco-svg.charts", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:jaraco/svg.charts:svg/charts/graph.py:Graph.get_stylesheet_resources#14365", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "svg/charts/graph.py", "symbol": "Graph.get_stylesheet_resources"}, "source_id": "csn:jaraco/svg.charts:svg/charts/graph.py:Graph.get_stylesheet_resources#14365"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/jaraco/svg.charts/blob/23053497b3f1af4e760f355050107ae3bc05909d/svg/charts/graph.py#L697-L705", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:jaraco-svg.charts:Graph.get_stylesheet_resources-97ba1e33bc", "question": "Get the stylesheets for this instance", "scope": {"holder": "jaraco-svg.charts", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:jaraco/wolframalpha:wolframalpha/__init__.py:Client.query#13152", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "wolframalpha/__init__.py", "symbol": "Client.query"}, "source_id": "csn:jaraco/wolframalpha:wolframalpha/__init__.py:Client.query#13152"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/jaraco/wolframalpha/blob/50bf2e047b698e308a9a88770a23e7e210aa5bcb/wolframalpha/__init__.py#L24-L56", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:jaraco-wolframalpha:Client.query-56e653612f", "question": "Query Wolfram|Alpha using the v2.0 API\n\n Allows for arbitrary parameters to be passed in\n the query. For example, to pass assumptions:\n\n client.query(input='pi', assumption='*C.pi-_*NamedConstant-')\n\n To pass multiple assumptions, pass multiple items\n as params:\n\n params = (\n ('assumption', '*C.pi-_*NamedConstant-'),\n ('assumption', 'DateOrder_**Day.Month.Year--'),\n )\n client.query(input='pi', params=params)\n\n For more details on Assumptions, see\n https://products.wolframalpha.com/api/documentation.html#6", "scope": {"holder": "jaraco-wolframalpha", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:jaraco/wolframalpha:wolframalpha/__init__.py:Result.results#13154", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "wolframalpha/__init__.py", "symbol": "Result.results"}, "source_id": "csn:jaraco/wolframalpha:wolframalpha/__init__.py:Result.results#13154"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/jaraco/wolframalpha/blob/50bf2e047b698e308a9a88770a23e7e210aa5bcb/wolframalpha/__init__.py#L206-L215", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:jaraco-wolframalpha:Result.results-b71aabd1e1", "question": "The pods that hold the response to a simple, discrete query.", "scope": {"holder": "jaraco-wolframalpha", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:jazzband/django-ddp:dddp/api.py:APIMixin.api_path_map#17103", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "dddp/api.py", "symbol": "APIMixin.api_path_map"}, "source_id": "csn:jazzband/django-ddp:dddp/api.py:APIMixin.api_path_map#17103"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/jazzband/django-ddp/blob/1e1954b06fe140346acea43582515991685e4e01/dddp/api.py#L149-L157", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:jazzband-django-ddp:APIMixin.api_path_map-25c9cc8d86", "question": "Cached dict of api_path: func.", "scope": {"holder": "jazzband-django-ddp", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:jazzband/django-ddp:dddp/websocket.py:DDPWebSocketApplication.send#17114", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "dddp/websocket.py", "symbol": "DDPWebSocketApplication.send"}, "source_id": "csn:jazzband/django-ddp:dddp/websocket.py:DDPWebSocketApplication.send#17114"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/jazzband/django-ddp/blob/1e1954b06fe140346acea43582515991685e4e01/dddp/websocket.py#L320-L371", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:jazzband-django-ddp:DDPWebSocketApplication.send-54d6620b8d", "question": "Send `data` (raw string or EJSON payload) to WebSocket client.", "scope": {"holder": "jazzband-django-ddp", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:jdrumgoole/pymongo_formatter:pymongo_formatter/formatter.py:CursorFormatter.output#19606", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pymongo_formatter/formatter.py", "symbol": "CursorFormatter.output"}, "source_id": "csn:jdrumgoole/pymongo_formatter:pymongo_formatter/formatter.py:CursorFormatter.output#19606"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/jdrumgoole/pymongo_formatter/blob/313fef8f2ff5e7d4f1515ea59a99ec25f7999e7b/pymongo_formatter/formatter.py#L229-L235", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:jdrumgoole-pymongo_formatter:CursorFormatter.output-32fdc935d2", "question": "Output all fields using the fieldNames list. for fields in the list datemap indicates the field must\n be date", "scope": {"holder": "jdrumgoole-pymongo_formatter", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:jdrumgoole/pymongo_formatter:pymongo_formatter/formatter.py:Doc_Formatter.date_map#19604", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pymongo_formatter/formatter.py", "symbol": "Doc_Formatter.date_map"}, "source_id": "csn:jdrumgoole/pymongo_formatter:pymongo_formatter/formatter.py:Doc_Formatter.date_map#19604"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/jdrumgoole/pymongo_formatter/blob/313fef8f2ff5e7d4f1515ea59a99ec25f7999e7b/pymongo_formatter/formatter.py#L102-L111", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:jdrumgoole-pymongo_formatter:Doc_Formatter.date_map-978344a8fd", "question": "For all the datetime fields in \"datemap\" find that key in doc and map the datetime object to\n a strftime string. This pprint and others will print out readable datetimes.", "scope": {"holder": "jdrumgoole-pymongo_formatter", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:jerith/txfake:txfake/fake_connection.py:FakeConnection.accept_connection#21224", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "txfake/fake_connection.py", "symbol": "FakeConnection.accept_connection"}, "source_id": "csn:jerith/txfake:txfake/fake_connection.py:FakeConnection.accept_connection#21224"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/jerith/txfake/blob/5c1cda2b9a56458c254d0d9476b6c426d57f5757/txfake/fake_connection.py#L123-L131", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:jerith-txfake:FakeConnection.accept_connection-6671fc9bf5", "question": "Accept a pending connection.", "scope": {"holder": "jerith-txfake", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:jerith/txfake:txfake/fake_connection.py:patch_if_missing#21221", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "txfake/fake_connection.py", "symbol": "patch_if_missing"}, "source_id": "csn:jerith/txfake:txfake/fake_connection.py:patch_if_missing#21221"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/jerith/txfake/blob/5c1cda2b9a56458c254d0d9476b6c426d57f5757/txfake/fake_connection.py#L203-L207", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:jerith-txfake:patch_if_missing-b4ebd40497", "question": "Patch a method onto an object if it isn't already there.", "scope": {"holder": "jerith-txfake", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:jfialkoff/pyphaxio:phaxio/api.py:PhaxioApi._get#18888", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "phaxio/api.py", "symbol": "PhaxioApi._get"}, "source_id": "csn:jfialkoff/pyphaxio:phaxio/api.py:PhaxioApi._get#18888"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/jfialkoff/pyphaxio/blob/d8fb6b9fc7a4057bb826d94ab974237f8417846d/phaxio/api.py#L69-L102", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:jfialkoff-pyphaxio:PhaxioApi._get-2cb2b57f59", "question": "Builds the url for the specified method and arguments and returns\n the response as a dictionary.", "scope": {"holder": "jfialkoff-pyphaxio", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:jfialkoff/pyphaxio:phaxio/api.py:PhaxioApi.parse_response#18887", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "phaxio/api.py", "symbol": "PhaxioApi.parse_response"}, "source_id": "csn:jfialkoff/pyphaxio:phaxio/api.py:PhaxioApi.parse_response#18887"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/jfialkoff/pyphaxio/blob/d8fb6b9fc7a4057bb826d94ab974237f8417846d/phaxio/api.py#L38-L67", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:jfialkoff-pyphaxio:PhaxioApi.parse_response-dd0637ce86", "question": "Parses the API response and raises appropriate\n errors if raise_errors was set to True\n\n :param response: response from requests http call\n :returns: dictionary of response\n :rtype: dict", "scope": {"holder": "jfialkoff-pyphaxio", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:jgorset/django-kronos:kronos/__init__.py:load#13669", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "kronos/__init__.py", "symbol": "load"}, "source_id": "csn:jgorset/django-kronos:kronos/__init__.py:load#13669"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/jgorset/django-kronos/blob/82ca16f5d499de3d34e0677e64ffab62d45424ce/kronos/__init__.py#L25-L45", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:jgorset-django-kronos:load-b09da91b94", "question": "Load ``cron`` modules for applications listed in ``INSTALLED_APPS``.", "scope": {"holder": "jgorset-django-kronos", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:jgorset/django-kronos:kronos/__init__.py:printtasks#13671", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "kronos/__init__.py", "symbol": "printtasks"}, "source_id": "csn:jgorset/django-kronos:kronos/__init__.py:printtasks#13671"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/jgorset/django-kronos/blob/82ca16f5d499de3d34e0677e64ffab62d45424ce/kronos/__init__.py#L129-L139", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:jgorset-django-kronos:printtasks-ed568a0c5d", "question": "Print the tasks that would be installed in the\n crontab, for debugging purposes.", "scope": {"holder": "jgorset-django-kronos", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:jic-dtool/dtool-azure:dtool_azure/storagebroker.py:AzureStorageBroker.add_item_metadata#16476", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "dtool_azure/storagebroker.py", "symbol": "AzureStorageBroker.add_item_metadata"}, "source_id": "csn:jic-dtool/dtool-azure:dtool_azure/storagebroker.py:AzureStorageBroker.add_item_metadata#16476"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/jic-dtool/dtool-azure/blob/5f5f1faa040e047e619380faf437a74cdfa09737/dtool_azure/storagebroker.py#L300-L326", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:jic-dtool-dtool-azure:AzureStorageBroker.add_item_metadata-fa4c105bb9", "question": "Store the given key:value pair for the item associated with handle.\n\n :param handle: handle for accessing an item before the dataset is\n frozen\n :param key: metadata key\n :param value: metadata value", "scope": {"holder": "jic-dtool-dtool-azure", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:jic-dtool/dtool-azure:dtool_azure/storagebroker.py:AzureStorageBroker.iter_item_handles#16479", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "dtool_azure/storagebroker.py", "symbol": "AzureStorageBroker.iter_item_handles"}, "source_id": "csn:jic-dtool/dtool-azure:dtool_azure/storagebroker.py:AzureStorageBroker.iter_item_handles#16479"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/jic-dtool/dtool-azure/blob/5f5f1faa040e047e619380faf437a74cdfa09737/dtool_azure/storagebroker.py#L387-L399", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:jic-dtool-dtool-azure:AzureStorageBroker.iter_item_handles-236b53c94d", "question": "Return iterator over item handles.", "scope": {"holder": "jic-dtool-dtool-azure", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:jic-dtool/dtool-s3:dtool_s3/storagebroker.py:S3StorageBroker.add_item_metadata#18592", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "dtool_s3/storagebroker.py", "symbol": "S3StorageBroker.add_item_metadata"}, "source_id": "csn:jic-dtool/dtool-s3:dtool_s3/storagebroker.py:S3StorageBroker.add_item_metadata#18592"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/jic-dtool/dtool-s3/blob/b92aca9b557797bb99390463982521a557a2e704/dtool_s3/storagebroker.py#L370-L385", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:jic-dtool-dtool-s3:S3StorageBroker.add_item_metadata-075527437c", "question": "Store the given key:value pair for the item associated with handle.\n\n :param handle: handle for accessing an item before the dataset is\n frozen\n :param key: metadata key\n :param value: metadata value", "scope": {"holder": "jic-dtool-dtool-s3", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:jic-dtool/dtool-s3:dtool_s3/storagebroker.py:S3StorageBroker.get_item_metadata#18594", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "dtool_s3/storagebroker.py", "symbol": "S3StorageBroker.get_item_metadata"}, "source_id": "csn:jic-dtool/dtool-s3:dtool_s3/storagebroker.py:S3StorageBroker.get_item_metadata#18594"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/jic-dtool/dtool-s3/blob/b92aca9b557797bb99390463982521a557a2e704/dtool_s3/storagebroker.py#L424-L449", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:jic-dtool-dtool-s3:S3StorageBroker.get_item_metadata-e2f2a6ae58", "question": "Return dictionary containing all metadata associated with handle.\n\n In other words all the metadata added using the ``add_item_metadata``\n method.\n\n :param handle: handle for accessing an item before the dataset is\n frozen\n :returns: dictionary containing item metadata", "scope": {"holder": "jic-dtool-dtool-s3", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:jjangsangy/py-translate:translate/__main__.py:main#10789", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "translate/__main__.py", "symbol": "main"}, "source_id": "csn:jjangsangy/py-translate:translate/__main__.py:main#10789"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/jjangsangy/py-translate/blob/fe6279b2ee353f42ce73333ffae104e646311956/translate/__main__.py#L107-L115", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:jjangsangy-py-translate:main-91c0f7178e", "question": "Main Entry point for translator and argument parser", "scope": {"holder": "jjangsangy-py-translate", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:jjangsangy/py-translate:translate/coroutines.py:spool#10794", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "translate/coroutines.py", "symbol": "spool"}, "source_id": "csn:jjangsangy/py-translate:translate/coroutines.py:spool#10794"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/jjangsangy/py-translate/blob/fe6279b2ee353f42ce73333ffae104e646311956/translate/coroutines.py#L152-L180", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:jjangsangy-py-translate:spool-ade55e2099", "question": "Consumes text streams and spools them together for more io\n efficient processes.\n\n :param iterable: Sends text stream for further processing\n :type iterable: Coroutine\n\n :param maxlen: Maximum query string size\n :type maxlen: Integer", "scope": {"holder": "jjangsangy-py-translate", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:joeblackwaslike/pricing:pricing/exchange.py:BackendBase.quotation#15925", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pricing/exchange.py", "symbol": "BackendBase.quotation"}, "source_id": "csn:joeblackwaslike/pricing:pricing/exchange.py:BackendBase.quotation#15925"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/joeblackwaslike/pricing/blob/be988b0851b4313af81f1db475bc33248700e39c/pricing/exchange.py#L41-L47", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:joeblackwaslike-pricing:BackendBase.quotation-eafb8cc849", "question": "Return quotation between two currencies (origin, target)", "scope": {"holder": "joeblackwaslike-pricing", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:joeblackwaslike/pricing:pricing/babel_numbers.py:format_currency#15982", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pricing/babel_numbers.py", "symbol": "format_currency"}, "source_id": "csn:joeblackwaslike/pricing:pricing/babel_numbers.py:format_currency#15982"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/joeblackwaslike/pricing/blob/be988b0851b4313af81f1db475bc33248700e39c/pricing/babel_numbers.py#L22-L112", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:joeblackwaslike-pricing:format_currency-671e9149ee", "question": "Return formatted currency value.\n\n >>> format_currency(1099.98, 'USD', locale='en_US')\n u'$1,099.98'\n >>> format_currency(1099.98, 'USD', locale='es_CO')\n u'US$\\\\xa01.099,98'\n >>> format_currency(1099.98, 'EUR', locale='de_DE')\n u'1.099,98\\\\xa0\\\\u20ac'\n\n The format can also be specified explicitly. The currency is\n placed with the '¤' sign. As the sign gets repeated the format\n expands (¤ being the symbol, ¤¤ is the currency abbreviation and\n ¤¤¤ is the full name of the currency):\n\n >>> format_currency(1099.98, 'EUR', u'\\xa4\\xa4 #,##0.00', locale='en_US')\n u'EUR 1,099.98'\n >>> format_currency(1099.98, 'EUR', u'#,##0.00 \\xa4\\xa4\\xa4',\n ... locale='en_US')\n u'1,099.98 euros'\n\n Currencies usually have a specific number of decimal digits. This function\n favours that information over the given format:\n\n >>> format_currency(1099.98, 'JPY', locale='en_US')\n u'\\\\xa51,100'\n >>> format_currency(1099.98, 'COP', u'#,##0.00', locale='es_ES')\n u'1.100'\n\n However, the number of decimal digits can be overriden from the currency\n information, by setting the last parameter to ``False``:\n\n >>> format_currency(1099.98, 'JPY', locale='en_US', currency_digits=False)\n u'\\\\xa51,099.98'\n >>> format_currency(1099.98, 'COP', u'#,##0.00', locale='es_ES',\n ... currency_digits=False)\n u'1.099,98'\n\n If a format is not specified the type of currency format to use\n from the locale can be specified:\n\n >>> format_currency(1099.98, 'EUR', locale='en_US', format_type='standard')\n u'\\\\u20ac1,099.98'\n\n When the given currency format type is not available, an exception is\n raised:\n\n >>> format_currency('1099.98', 'EUR', locale='root', format_type='unknown')\n Traceback (most recent call last):\n ...\n UnknownCurrencyFormatError: \"'unknown' is not a known currency format type\"\n\n By default the locale is allowed to truncate and round a high-precision\n number by forcing its format pattern onto the decimal part. You can bypass\n this behavior with the `decimal_quantization` parameter:\n\n >>> format_currency(1099.9876, 'USD', locale='en_US')\n u'$1,099.99'\n >>> format_currency(1099.9876, 'USD', locale='en_US',\n ... decimal_quantization=False)\n u'$1,099.9876'\n\n :param number: the number to format\n :param currency: the currency code\n :param format: the format string to use\n :param locale: the `Locale` object or locale identifier\n :param currency_digits: use the currency's natural number of decimal digits\n :param format_type: the currency format type to use\n :param decimal_quantization: Truncate and round high-precision numbers to\n the format pattern. Defaults to `True`.", "scope": {"holder": "joeblackwaslike-pricing", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:jonashaag/django-addanother:django_addanother/widgets.py:WidgetWrapperMixin.build_attrs#14458", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "django_addanother/widgets.py", "symbol": "WidgetWrapperMixin.build_attrs"}, "source_id": "csn:jonashaag/django-addanother:django_addanother/widgets.py:WidgetWrapperMixin.build_attrs#14458"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/jonashaag/django-addanother/blob/83dc0c8cc7665cc481dd58da0b9a746972264046/django_addanother/widgets.py#L28-L31", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:jonashaag-django-addanother:WidgetWrapperMixin.build_attrs-9ea1dbd4e6", "question": "Helper function for building an attribute dictionary.", "scope": {"holder": "jonashaag-django-addanother", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:jonfaustman/django-frontend:djfrontend/templatetags/djfrontend.py:djfrontend_fontawesome#17044", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "djfrontend/templatetags/djfrontend.py", "symbol": "djfrontend_fontawesome"}, "source_id": "csn:jonfaustman/django-frontend:djfrontend/templatetags/djfrontend.py:djfrontend_fontawesome#17044"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/jonfaustman/django-frontend/blob/897934d593fade0eb1998f8fadd18c91a89e5b9a/djfrontend/templatetags/djfrontend.py#L60-L70", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:jonfaustman-django-frontend:djfrontend_fontawesome-7526bc77d6", "question": "Returns Font Awesome CSS file.\n TEMPLATE_DEBUG returns full file, otherwise returns minified file.", "scope": {"holder": "jonfaustman-django-frontend", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:jonfaustman/django-frontend:djfrontend/templatetags/djfrontend.py:djfrontend_jquery_formset#17051", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "djfrontend/templatetags/djfrontend.py", "symbol": "djfrontend_jquery_formset"}, "source_id": "csn:jonfaustman/django-frontend:djfrontend/templatetags/djfrontend.py:djfrontend_jquery_formset#17051"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/jonfaustman/django-frontend/blob/897934d593fade0eb1998f8fadd18c91a89e5b9a/djfrontend/templatetags/djfrontend.py#L186-L200", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:jonfaustman-django-frontend:djfrontend_jquery_formset-1007428aa7", "question": "Returns the jQuery Dynamic Formset plugin file according to version number.\n TEMPLATE_DEBUG returns full file, otherwise returns minified file.", "scope": {"holder": "jonfaustman-django-frontend", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:joopert/nad_receiver:nad_receiver/__init__.py:NADReceiver.exec_command#17661", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "nad_receiver/__init__.py", "symbol": "NADReceiver.exec_command"}, "source_id": "csn:joopert/nad_receiver:nad_receiver/__init__.py:NADReceiver.exec_command#17661"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/joopert/nad_receiver/blob/416de0173a330c75cc73f9c90b0c5df32e5e0ba3/nad_receiver/__init__.py#L28-L66", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:joopert-nad_receiver:NADReceiver.exec_command-aa5cf60a60", "question": "Write a command to the receiver and read the value it returns.\n\n The receiver will always return a value, also when setting a value.", "scope": {"holder": "joopert-nad_receiver", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:joopert/nad_receiver:nad_receiver/__init__.py:NADReceiverTCP.power_off#17666", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "nad_receiver/__init__.py", "symbol": "NADReceiverTCP.power_off"}, "source_id": "csn:joopert/nad_receiver:nad_receiver/__init__.py:NADReceiverTCP.power_off#17666"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/joopert/nad_receiver/blob/416de0173a330c75cc73f9c90b0c5df32e5e0ba3/nad_receiver/__init__.py#L239-L243", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:joopert-nad_receiver:NADReceiverTCP.power_off-d60a76cdf7", "question": "Power the device off.", "scope": {"holder": "joopert-nad_receiver", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:josiahcarlson/rom:rom/util.py:EntityLock#8769", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "rom/util.py", "symbol": "EntityLock"}, "source_id": "csn:josiahcarlson/rom:rom/util.py:EntityLock#8769"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/josiahcarlson/rom/blob/8b5607a856341df85df33422accc30ba9294dbdb/rom/util.py#L1000-L1017", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:josiahcarlson-rom:EntityLock-3cebe26158", "question": "Useful when you want exclusive access to an entity across all writers.::\n\n # example\n import rom\n\n class Document(rom.Model):\n owner = rom.ManyToOne('User', on_delete='restrict')\n ...\n\n def change_owner(document, new_owner):\n with rom.util.EntityLock(document, 5, 90):\n document.owner = new_owner\n document.save()", "scope": {"holder": "josiahcarlson-rom", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:josiahcarlson/rom:rom/query.py:Query.select#8744", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "rom/query.py", "symbol": "Query.select"}, "source_id": "csn:josiahcarlson/rom:rom/query.py:Query.select#8744"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/josiahcarlson/rom/blob/8b5607a856341df85df33422accc30ba9294dbdb/rom/query.py#L107-L180", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:josiahcarlson-rom:Query.select-f915ecf70d", "question": "Select the provided column names from the model, do not return an entity,\n do not involve the rom session, just get the raw and/or processed column\n data from Redis.\n\n Keyword-only arguments:\n\n * *include_pk=False* - whether to include the primary key in the\n returned data (we need to get this in some cases, so we fetch\n it anyway; if you want it, we can return it to you - just be\n careful with the namedtuple option - see the warning below)\n * *decode=True* - whether to take a pass through normal data\n decoding in the model (will not return an entity/model)\n * *ff=_dict_data_factory* - the type of data to return from the\n select after all filters/limits/order_by are applied\n\n .. warning:: If ``include_pk = True`` and if you don't provide\n the primary key column, it will be appended to your list of columns.\n\n .. note:: if you want to provide a new factory function for the returned\n data, it must be of the form (below is the actual dict factory\n function)\n\n ::\n\n def _dict_data_factory(columns):\n _dict = dict\n _zip = zip\n def make(data):\n # do whatever you need to turn your tuple of columns plus\n # your list of data into whatever you want:\n return _dict(_zip(columns, data))\n return make\n\n Available factory functions:\n\n * *``rom.query._dict_data_factory``* - default\n * *``rom.query._list_data_factory``* - lowest overhead, as the\n ``data`` passed in above is a list that you can do anything to\n * *``rom.query._tuple_data_factory``* - when you want tuples instead\n * *``rom.query._namedtuple_data_factory``* - get namedtuples, see\n see warning below\n\n .. warning:: If you use the ``_namedtuple_data_factory``, and your\n columns include underscore prefixes, they will be stripped. If this\n results in a name collision, you *will* get an exception. If you want\n differerent behavior, write your own 20 line factory function that\n does exactly what you want, and pass it; they are really easy!", "scope": {"holder": "josiahcarlson-rom", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:jrfonseca/xdot.py:xdot/ui/elements.py:BezierShape._cubic_bernstein#7296", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "xdot/ui/elements.py", "symbol": "BezierShape._cubic_bernstein"}, "source_id": "csn:jrfonseca/xdot.py:xdot/ui/elements.py:BezierShape._cubic_bernstein#7296"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/jrfonseca/xdot.py/blob/6248c81c21a0fe825089311b17f2c302eea614a2/xdot/ui/elements.py#L386-L392", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:jrfonseca-xdot.py:BezierShape._cubic_bernstein-2b7b6fe7ad", "question": "Evaluate polynomial of given bernstein coefficients\n using de Casteljau's algorithm.", "scope": {"holder": "jrfonseca-xdot.py", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:jrfonseca/xdot.py:xdot/ui/pen.py:Pen.copy#7292", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "xdot/ui/pen.py", "symbol": "Pen.copy"}, "source_id": "csn:jrfonseca/xdot.py:xdot/ui/pen.py:Pen.copy#7292"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/jrfonseca/xdot.py/blob/6248c81c21a0fe825089311b17f2c302eea614a2/xdot/ui/pen.py#L46-L50", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:jrfonseca-xdot.py:Pen.copy-0dba6dbc28", "question": "Create a copy of this pen.", "scope": {"holder": "jrfonseca-xdot.py", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:jrxFive/python-nomad:nomad/api/acl.py:Acl.create_policy#7728", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "nomad/api/acl.py", "symbol": "Acl.create_policy"}, "source_id": "csn:jrxFive/python-nomad:nomad/api/acl.py:Acl.create_policy#7728"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/jrxFive/python-nomad/blob/37df37e4de21e6f8ac41c6154e7f1f44f1800020/nomad/api/acl.py#L137-L150", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:jrxFive-python-nomad:Acl.create_policy-e235816673", "question": "Create policy.\n\n https://www.nomadproject.io/api/acl-policies.html\n\n arguments:\n - policy\n returns: request.Response\n\n raises:\n - nomad.api.exceptions.BaseNomadException\n - nomad.api.exceptions.URLNotFoundNomadException", "scope": {"holder": "jrxFive-python-nomad", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:jrxFive/python-nomad:nomad/api/jobs.py:Jobs.parse#7726", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "nomad/api/jobs.py", "symbol": "Jobs.parse"}, "source_id": "csn:jrxFive/python-nomad:nomad/api/jobs.py:Jobs.parse#7726"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/jrxFive/python-nomad/blob/37df37e4de21e6f8ac41c6154e7f1f44f1800020/nomad/api/jobs.py#L93-L104", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:jrxFive-python-nomad:Jobs.parse-7fdd6fc26a", "question": "Parse a HCL Job file. Returns a dict with the JSON formatted job.\n This API endpoint is only supported from Nomad version 0.8.3.\n\n https://www.nomadproject.io/api/jobs.html#parse-job\n\n returns: dict\n raises:\n - nomad.api.exceptions.BaseNomadException\n - nomad.api.exceptions.URLNotFoundNomadException", "scope": {"holder": "jrxFive-python-nomad", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:jshiv/turntable:turntable/press.py:RecordSetter.set_attributes#20175", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "turntable/press.py", "symbol": "RecordSetter.set_attributes"}, "source_id": "csn:jshiv/turntable:turntable/press.py:RecordSetter.set_attributes#20175"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/jshiv/turntable/blob/c095a93df14d672ba54db164a7ab7373444d1829/turntable/press.py#L149-L163", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:jshiv-turntable:RecordSetter.set_attributes-625908cb50", "question": "Initalizes the given argument structure as properties of the class\n to be used by name in specific method execution.\n\n Parameters\n ----------\n kwargs : dictionary\n Dictionary of extra attributes,\n where keys are attributes names and values attributes values.", "scope": {"holder": "jshiv-turntable", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:jshiv/turntable:turntable/press.py:load_record#20171", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "turntable/press.py", "symbol": "load_record"}, "source_id": "csn:jshiv/turntable:turntable/press.py:load_record#20171"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/jshiv/turntable/blob/c095a93df14d672ba54db164a7ab7373444d1829/turntable/press.py#L240-L264", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:jshiv-turntable:load_record-5a21706855", "question": "Generates an instance of Record() from a tuple of the form (index, pandas.Series) \n with associated parameters kwargs\n\n Paremeters\n ----------\n index_series_tuple : tuple\n tuple consisting of (index, pandas.Series)\n kwargs : dict\n aditional arguments\n\n Returns\n -------\n Record : object", "scope": {"holder": "jshiv-turntable", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:jtambasco/opticalmaterialspy:opticalmaterialspy/_material_base.py:_Material._cauchy_equation#14951", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "opticalmaterialspy/_material_base.py", "symbol": "_Material._cauchy_equation"}, "source_id": "csn:jtambasco/opticalmaterialspy:opticalmaterialspy/_material_base.py:_Material._cauchy_equation#14951"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/jtambasco/opticalmaterialspy/blob/bfdfacad7fe280a0e63a3eb89de09a5c153595cc/opticalmaterialspy/_material_base.py#L238-L255", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:jtambasco-opticalmaterialspy:_Material._cauchy_equation-c529e8f45a", "question": "Helpful function to evaluate Cauchy equations.\n\n Args:\n wavelength (float, list, None): The wavelength(s) the\n Cauchy equation will be evaluated at.\n coefficients (list): A list of the coefficients of\n the Cauchy equation.\n\n Returns:\n float, list: The refractive index at the target wavelength(s).", "scope": {"holder": "jtambasco-opticalmaterialspy", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:jtambasco/opticalmaterialspy:opticalmaterialspy/_material_base.py:_Material.gvd#14950", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "opticalmaterialspy/_material_base.py", "symbol": "_Material.gvd"}, "source_id": "csn:jtambasco/opticalmaterialspy:opticalmaterialspy/_material_base.py:_Material.gvd#14950"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/jtambasco/opticalmaterialspy/blob/bfdfacad7fe280a0e63a3eb89de09a5c153595cc/opticalmaterialspy/_material_base.py#L167-L179", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:jtambasco-opticalmaterialspy:_Material.gvd-4c8c84bc40", "question": "The group velocity dispersion (GVD) with respect to wavelength.\n\n Args:\n wavelength (float, list, None): The wavelength(s) the GVD will\n be evaluated at.\n\n Returns:\n float, list: The GVD at the target wavelength(s).", "scope": {"holder": "jtambasco-opticalmaterialspy", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:jterrace/pyssim:ssim/ssimlib.py:SSIM.cw_ssim_value#6573", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "ssim/ssimlib.py", "symbol": "SSIM.cw_ssim_value"}, "source_id": "csn:jterrace/pyssim:ssim/ssimlib.py:SSIM.cw_ssim_value#6573"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/jterrace/pyssim/blob/ff9bd90c3eb7525013ad46babf66b7cc78391e89/ssim/ssimlib.py#L147-L191", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:jterrace-pyssim:SSIM.cw_ssim_value-37660126c1", "question": "Compute the complex wavelet SSIM (CW-SSIM) value from the reference\n image to the target image.\n\n Args:\n target (str or PIL.Image): Input image to compare the reference image\n to. This may be a PIL Image object or, to save time, an SSIMImage\n object (e.g. the img member of another SSIM object).\n width: width for the wavelet convolution (default: 30)\n\n Returns:\n Computed CW-SSIM float value.", "scope": {"holder": "jterrace-pyssim", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:jterrace/pyssim:ssim/utils.py:get_gaussian_kernel#6569", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "ssim/utils.py", "symbol": "get_gaussian_kernel"}, "source_id": "csn:jterrace/pyssim:ssim/utils.py:get_gaussian_kernel#6569"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/jterrace/pyssim/blob/ff9bd90c3eb7525013ad46babf66b7cc78391e89/ssim/utils.py#L19-L29", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:jterrace-pyssim:get_gaussian_kernel-40933d6e0f", "question": "Generate a gaussian kernel.", "scope": {"holder": "jterrace-pyssim", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:juga0/dhcpcanon:dhcpcanon/dhcpcapfsm.py:DHCPCAPFSM.BOUND#12879", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "dhcpcanon/dhcpcapfsm.py", "symbol": "DHCPCAPFSM.BOUND"}, "source_id": "csn:juga0/dhcpcanon:dhcpcanon/dhcpcapfsm.py:DHCPCAPFSM.BOUND#12879"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/juga0/dhcpcanon/blob/9f51a29e57fe93dc93fb22bb0ed12fcfe9557e59/dhcpcanon/dhcpcapfsm.py#L356-L370", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:juga0-dhcpcanon:DHCPCAPFSM.BOUND-6d9b6c6348", "question": "BOUND state.", "scope": {"holder": "juga0-dhcpcanon", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:juga0/dhcpcanon:dhcpcanon/dhcpcapfsm.py:DHCPCAPFSM.reset#12869", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "dhcpcanon/dhcpcapfsm.py", "symbol": "DHCPCAPFSM.reset"}, "source_id": "csn:juga0/dhcpcanon:dhcpcanon/dhcpcapfsm.py:DHCPCAPFSM.reset#12869"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/juga0/dhcpcanon/blob/9f51a29e57fe93dc93fb22bb0ed12fcfe9557e59/dhcpcanon/dhcpcapfsm.py#L48-L70", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:juga0-dhcpcanon:DHCPCAPFSM.reset-748fe6d546", "question": "Reset object attributes when state is INIT.", "scope": {"holder": "juga0-dhcpcanon", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:jupyter-widgets/jupyterlab-sidecar:setupbase.py:_get_data_files#8315", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "setupbase.py", "symbol": "_get_data_files"}, "source_id": "csn:jupyter-widgets/jupyterlab-sidecar:setupbase.py:_get_data_files#8315"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/jupyter-widgets/jupyterlab-sidecar/blob/8889d09f1a0933e2cbee06d4874f720b075b29e8/setupbase.py#L502-L540", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:jupyter-widgets-jupyterlab-sidecar:_get_data_files-1c532f18bd", "question": "Expand data file specs into valid data files metadata.\n\n Parameters\n ----------\n data_specs: list of tuples\n See [createcmdclass] for description.\n existing: list of tuples\n The existing distribution data_files metadata.\n\n Returns\n -------\n A valid list of data_files items.", "scope": {"holder": "jupyter-widgets-jupyterlab-sidecar", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:jupyter-widgets/jupyterlab-sidecar:setupbase.py:command_for_func#8309", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "setupbase.py", "symbol": "command_for_func"}, "source_id": "csn:jupyter-widgets/jupyterlab-sidecar:setupbase.py:command_for_func#8309"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/jupyter-widgets/jupyterlab-sidecar/blob/8889d09f1a0933e2cbee06d4874f720b075b29e8/setupbase.py#L196-L205", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:jupyter-widgets-jupyterlab-sidecar:command_for_func-a9b7163c04", "question": "Create a command that calls the given function.", "scope": {"holder": "jupyter-widgets-jupyterlab-sidecar", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:justanr/flask-allows:src/flask_allows/additional.py:AdditionalManager.additional#16858", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "src/flask_allows/additional.py", "symbol": "AdditionalManager.additional"}, "source_id": "csn:justanr/flask-allows:src/flask_allows/additional.py:AdditionalManager.additional#16858"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/justanr/flask-allows/blob/39fa5c8692836a33646ea43b4081e7c2181ec7c4/src/flask_allows/additional.py#L178-L185", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:justanr-flask-allows:AdditionalManager.additional-c0c32a2a4e", "question": "Allows temporarily pushing an additional context, yields the new context\n into the following block.", "scope": {"holder": "justanr-flask-allows", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:justanr/flask-allows:src/flask_allows/requirements.py:ConditionalRequirement.Or#16849", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "src/flask_allows/requirements.py", "symbol": "ConditionalRequirement.Or"}, "source_id": "csn:justanr/flask-allows:src/flask_allows/requirements.py:ConditionalRequirement.Or#16849"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/justanr/flask-allows/blob/39fa5c8692836a33646ea43b4081e7c2181ec7c4/src/flask_allows/requirements.py#L106-L114", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:justanr-flask-allows:ConditionalRequirement.Or-7b3b63753a", "question": "Short cut helper to construct a combinator that uses\n :meth:`operator.or_` to reduce requirement results and stops evaluating\n on the first True.\n\n This is also exported at the module level as ``Or``", "scope": {"holder": "justanr-flask-allows", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:justbilt/untp:src/untp/pvr.py:_pvr_head#8336", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "src/untp/pvr.py", "symbol": "_pvr_head"}, "source_id": "csn:justbilt/untp:src/untp/pvr.py:_pvr_head#8336"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/justbilt/untp/blob/98ec6199e62e7a97ad74b5cf5a1ea7be9b4c9d01/src/untp/pvr.py#L60-L76", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:justbilt-untp:_pvr_head-919a5767f7", "question": "struct CCZHeader {\n unsigned char sig[4]; // signature. Should be 'CCZ!' 4 bytes\n unsigned short compression_type; // should 0\n unsigned short version; // should be 2 (although version type==1 is also supported)\n unsigned int reserved; // Reserved for users.\n unsigned int len; // size of the uncompressed file\n };", "scope": {"holder": "justbilt-untp", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:justbilt/untp:src/untp/dataparse.py:parse_fntdata#8335", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "src/untp/dataparse.py", "symbol": "parse_fntdata"}, "source_id": "csn:justbilt/untp:src/untp/dataparse.py:parse_fntdata#8335"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/justbilt/untp/blob/98ec6199e62e7a97ad74b5cf5a1ea7be9b4c9d01/src/untp/dataparse.py#L32-L85", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:justbilt-untp:parse_fntdata-b99f9da014", "question": "info face=\"Haettenschweiler\" size=60 bold=0 italic=0 charset=\"\" unicode=0 stretchH=100 smooth=1 aa=1 padding=0,0,0,0 spacing=2,2\n\tcommon lineHeight=64 base=53 scaleW=256 scaleH=128 pages=1 packed=0\n\tpage id=0 file=\"attack_num.png\"\n\tchars count=12\n\tchar id=52 x=2 y=2 width=33 height=51 xoffset=0 yoffset=5 xadvance=32 page=0 chnl=0 letter=\"4\"\n\tchar id=48 x=37 y=2 width=29 height=50 xoffset=1 yoffset=6 xadvance=29 page=0 chnl=0 letter=\"0\"\n\tchar id=53 x=68 y=2 width=29 height=50 xoffset=1 yoffset=6 xadvance=28 page=0 chnl=0 letter=\"5\"\n\tchar id=57 x=99 y=2 width=28 height=50 xoffset=1 yoffset=6 xadvance=28 page=0 chnl=0 letter=\"9\"\n\tchar id=54 x=129 y=2 width=28 height=50 xoffset=1 yoffset=6 xadvance=28 page=0 chnl=0 letter=\"6\"\n\tchar id=56 x=159 y=2 width=28 height=50 xoffset=1 yoffset=6 xadvance=28 page=0 chnl=0 letter=\"8\"\n\tchar id=51 x=189 y=2 width=28 height=50 xoffset=1 yoffset=6 xadvance=28 page=0 chnl=0 letter=\"3\"\n\tchar id=50 x=219 y=2 width=28 height=49 xoffset=1 yoffset=7 xadvance=28 page=0 chnl=0 letter=\"2\"\n\tchar id=55 x=2 y=55 width=30 height=48 xoffset=1 yoffset=8 xadvance=28 page=0 chnl=0 letter=\"7\"\n\tchar id=49 x=34 y=55 width=20 height=48 xoffset=1 yoffset=8 xadvance=20 page=0 chnl=0 letter=\"1\"\n\tchar id=45 x=56 y=55 width=18 height=12 xoffset=1 yoffset=36 xadvance=19 page=0 chnl=0 letter=\"-\"\n\tchar id=32 x=76 y=55 width=0 height=0 xoffset=11 yoffset=73 xadvance=16 page=0 chnl=0 letter=\"space\"", "scope": {"holder": "justbilt-untp", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:kadrlica/pymodeler:pymodeler/parameter.py:Derived.value#18256", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pymodeler/parameter.py", "symbol": "Derived.value"}, "source_id": "csn:kadrlica/pymodeler:pymodeler/parameter.py:Derived.value#18256"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/kadrlica/pymodeler/blob/f426c01416fd4b8fc3afeeb6d3b5d1cb0cb8f8e3/pymodeler/parameter.py#L290-L317", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:kadrlica-pymodeler:Derived.value-65fb4f4f7a", "question": "Return the current value.\n\n This first checks if the value is cached (i.e., if\n `self.__value__` is not None)\n\n If it is not cached then it invokes the `loader` function to\n compute the value, and caches the computed value", "scope": {"holder": "kadrlica-pymodeler", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:kadrlica/pymodeler:pymodeler/parameter.py:Parameter.set#18261", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pymodeler/parameter.py", "symbol": "Parameter.set"}, "source_id": "csn:kadrlica/pymodeler:pymodeler/parameter.py:Parameter.set#18261"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/kadrlica/pymodeler/blob/f426c01416fd4b8fc3afeeb6d3b5d1cb0cb8f8e3/pymodeler/parameter.py#L627-L641", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:kadrlica-pymodeler:Parameter.set-c38e1976ce", "question": "Set the value,bounds,free,errors based on corresponding kwargs\n\n The invokes hooks for type-checking and bounds-checking that\n may be implemented by sub-classes.", "scope": {"holder": "kadrlica-pymodeler", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:kamalshadi/Localization:localization/geometry.py:Sphere.gcd#16996", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "localization/geometry.py", "symbol": "Sphere.gcd"}, "source_id": "csn:kamalshadi/Localization:localization/geometry.py:Sphere.gcd#16996"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/kamalshadi/Localization/blob/f99470712c65a48896f6e4095181a1a3c9545d43/localization/geometry.py#L634-L649", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:kamalshadi-Localization:Sphere.gcd-c9c159f678", "question": "Calculate the great circle distance between two points\n on the earth (specified in decimal degrees)", "scope": {"holder": "kamalshadi-Localization", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:karimbahgat/PyCRS:pycrs/elements/cs.py:GeogCS.to_esri_wkt#7926", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pycrs/elements/cs.py", "symbol": "GeogCS.to_esri_wkt"}, "source_id": "csn:karimbahgat/PyCRS:pycrs/elements/cs.py:GeogCS.to_esri_wkt#7926"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/karimbahgat/PyCRS/blob/d6a8bb9c28787a25b4a1d59a7e4603db3221eaef/pycrs/elements/cs.py#L96-L100", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:karimbahgat-PyCRS:GeogCS.to_esri_wkt-c3775de073", "question": "Returns the CS as a ESRI WKT formatted string.", "scope": {"holder": "karimbahgat-PyCRS", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:karimbahgat/PyCRS:pycrs/utils.py:build_crs_table#7922", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pycrs/utils.py", "symbol": "build_crs_table"}, "source_id": "csn:karimbahgat/PyCRS:pycrs/utils.py:build_crs_table#7922"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/karimbahgat/PyCRS/blob/d6a8bb9c28787a25b4a1d59a7e4603db3221eaef/pycrs/utils.py#L11-L69", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:karimbahgat-PyCRS:build_crs_table-b86ed02ac5", "question": "Build crs table of all equivalent format variations by scraping spatialreference.org.\n Saves table as tab-delimited text file.\n NOTE: Might take a while.\n\n Arguments:\n\n - *savepath*: The absolute or relative filepath to which to save the crs table, including the \".txt\" extension.", "scope": {"holder": "karimbahgat-PyCRS", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:katerina7479/pypdflite:pypdflite/font_loader.py:FontLoader.get_ttf#18097", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pypdflite/font_loader.py", "symbol": "FontLoader.get_ttf"}, "source_id": "csn:katerina7479/pypdflite:pypdflite/font_loader.py:FontLoader.get_ttf#18097"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/katerina7479/pypdflite/blob/ac2501f30d6619eae9dea5644717575ca9263d0a/pypdflite/font_loader.py#L30-L68", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:katerina7479-pypdflite:FontLoader.get_ttf-fcd25ff5d4", "question": "Given a search path, find file with requested extension", "scope": {"holder": "katerina7479-pypdflite", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:katerina7479/pypdflite:pypdflite/pdfobjects/pdfimage.py:PDFImage._output#18116", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pypdflite/pdfobjects/pdfimage.py", "symbol": "PDFImage._output"}, "source_id": "csn:katerina7479/pypdflite:pypdflite/pdfobjects/pdfimage.py:PDFImage._output#18116"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/katerina7479/pypdflite/blob/ac2501f30d6619eae9dea5644717575ca9263d0a/pypdflite/pdfobjects/pdfimage.py#L228-L267", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:katerina7479-pypdflite:PDFImage._output-85e2329261", "question": "Prompts the creating of image objects.", "scope": {"holder": "katerina7479-pypdflite", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:keflavich/plfit:plfit/plfit.py:alpha_gen#16972", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "plfit/plfit.py", "symbol": "alpha_gen"}, "source_id": "csn:keflavich/plfit:plfit/plfit.py:alpha_gen#16972"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/keflavich/plfit/blob/7dafa6302b427ba8c89651148e3e9d29add436c3/plfit/plfit.py#L53-L79", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:keflavich-plfit:alpha_gen-5692009436", "question": "Create a mappable function alpha to apply to each xmin in a list of xmins.\n This is essentially the slow version of fplfit/cplfit, though I bet it could\n be speeded up with a clever use of parellel_map. Not intended to be used by users.\n\n Docstring for the generated alpha function::\n\n Given a sorted data set and a minimum, returns power law MLE fit\n data is passed as a keyword parameter so that it can be vectorized\n\n If there is only one element, return alpha=0", "scope": {"holder": "keflavich-plfit", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:keflavich/plfit:plfit/plfit.py:plfit.alphavsks#16986", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "plfit/plfit.py", "symbol": "plfit.alphavsks"}, "source_id": "csn:keflavich/plfit:plfit/plfit.py:plfit.alphavsks#16986"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/keflavich/plfit/blob/7dafa6302b427ba8c89651148e3e9d29add436c3/plfit/plfit.py#L474-L493", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:keflavich-plfit:plfit.alphavsks-b279df48df", "question": "Plot alpha versus the ks value for derived alpha. This plot can be used\n as a diagnostic of whether you have derived the 'best' fit: if there are\n multiple local minima, your data set may be well suited to a broken\n powerlaw or a different function.", "scope": {"holder": "keflavich-plfit", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:kejbaly2/comdev:comdev/google_api.py:Contacts.update_membership#19819", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "comdev/google_api.py", "symbol": "Contacts.update_membership"}, "source_id": "csn:kejbaly2/comdev:comdev/google_api.py:Contacts.update_membership#19819"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/kejbaly2/comdev/blob/5a9067d3c1ae46eeccb9d36e8c231ea5224b42b4/comdev/google_api.py#L184-L205", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:kejbaly2-comdev:Contacts.update_membership-d00d6d7547", "question": "input: gdata ContactEntry and GroupEntry objects", "scope": {"holder": "kejbaly2-comdev", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:kejbaly2/comdev:comdev/facebook_api.py:get_token#20042", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "comdev/facebook_api.py", "symbol": "get_token"}, "source_id": "csn:kejbaly2/comdev:comdev/facebook_api.py:get_token#20042"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/kejbaly2/comdev/blob/5a9067d3c1ae46eeccb9d36e8c231ea5224b42b4/comdev/facebook_api.py#L19-L38", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:kejbaly2-comdev:get_token-fcbf598a0e", "question": "See: http://nodotcom.org/python-facebook-tutorial.html", "scope": {"holder": "kejbaly2-comdev", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:kenneth-reitz/dynamo:dynamo.py:table#17731", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "dynamo.py", "symbol": "table"}, "source_id": "csn:kenneth-reitz/dynamo:dynamo.py:table#17731"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/kenneth-reitz/dynamo/blob/e24276a7e68d868857fd1d0deabccd001920e0c2/dynamo.py#L113-L119", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:kenneth-reitz-dynamo:table-eaa302c2e4", "question": "Returns a given table for the given user.", "scope": {"holder": "kenneth-reitz-dynamo", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:kennethreitz/flask-common:flask_common.py:Common.init_app#8530", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "flask_common.py", "symbol": "Common.init_app"}, "source_id": "csn:kennethreitz/flask-common:flask_common.py:Common.init_app#8530"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/kennethreitz/flask-common/blob/7345514942f863396056e0fd252f29082623cec6/flask_common.py#L101-L134", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:kennethreitz-flask-common:Common.init_app-f815a0550c", "question": "Initializes the Flask application with Common.", "scope": {"holder": "kennethreitz-flask-common", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:kennethreitz/flask-common:flask_common.py:Common.serve#8531", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "flask_common.py", "symbol": "Common.serve"}, "source_id": "csn:kennethreitz/flask-common:flask_common.py:Common.serve#8531"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/kennethreitz/flask-common/blob/7345514942f863396056e0fd252f29082623cec6/flask_common.py#L136-L149", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:kennethreitz-flask-common:Common.serve-15b4dc766c", "question": "Serves the Flask application.", "scope": {"holder": "kennethreitz-flask-common", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:kgiusti/pyngus:pyngus/connection.py:Connection._connection_failed#18088", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pyngus/connection.py", "symbol": "Connection._connection_failed"}, "source_id": "csn:kgiusti/pyngus:pyngus/connection.py:Connection._connection_failed#18088"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/kgiusti/pyngus/blob/5392392046989f1bb84ba938c30e4d48311075f1/pyngus/connection.py#L731-L735", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:kgiusti-pyngus:Connection._connection_failed-4c316c9dc1", "question": "Clean up after connection failure detected.", "scope": {"holder": "kgiusti-pyngus", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:kgiusti/pyngus:examples/rpc-server.py:SocketConnection.process_input#18050", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "examples/rpc-server.py", "symbol": "SocketConnection.process_input"}, "source_id": "csn:kgiusti/pyngus:examples/rpc-server.py:SocketConnection.process_input#18050"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/kgiusti/pyngus/blob/5392392046989f1bb84ba938c30e4d48311075f1/examples/rpc-server.py#L92-L100", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:kgiusti-pyngus:SocketConnection.process_input-da0604a439", "question": "Called when socket is read-ready", "scope": {"holder": "kgiusti-pyngus", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:kmmbvnr/django-any:django_any/functions.py:ExtensionMethod._create_value#17824", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "django_any/functions.py", "symbol": "ExtensionMethod._create_value"}, "source_id": "csn:kmmbvnr/django-any:django_any/functions.py:ExtensionMethod._create_value#17824"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/kmmbvnr/django-any/blob/6f64ebd05476e2149e2e71deeefbb10f8edfc412/django_any/functions.py#L71-L91", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:kmmbvnr-django-any:ExtensionMethod._create_value-7d1f5d36f0", "question": "Lowest value generator.\n\n Separated from __call__, because it seems that python\n cache __call__ reference on module import", "scope": {"holder": "kmmbvnr-django-any", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:kmmbvnr/django-any:django_any/models.py:any_slug_field#17863", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "django_any/models.py", "symbol": "any_slug_field"}, "source_id": "csn:kmmbvnr/django-any:django_any/models.py:any_slug_field#17863"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/kmmbvnr/django-any/blob/6f64ebd05476e2149e2e71deeefbb10f8edfc412/django_any/models.py#L311-L322", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:kmmbvnr-django-any:any_slug_field-09e43bdd80", "question": "Return random value for SlugField\r\n >>> result = any_field(models.SlugField())\r\n >>> type(result)\r\n <type 'str'>\r\n >>> from django.core.validators import slug_re\r\n >>> re.match(slug_re, result) is not None\r\n True", "scope": {"holder": "kmmbvnr-django-any", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:kolypto/py-smsframework:smsframework/providers/forward/provider.py:ForwardClientProvider.send#14885", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "smsframework/providers/forward/provider.py", "symbol": "ForwardClientProvider.send"}, "source_id": "csn:kolypto/py-smsframework:smsframework/providers/forward/provider.py:ForwardClientProvider.send#14885"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/kolypto/py-smsframework/blob/4f3d812711f5e2e037dc80c4014c815fe2d68a0b/smsframework/providers/forward/provider.py#L162-L176", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:kolypto-py-smsframework:ForwardClientProvider.send-ea77d2c153", "question": "Send a message by forwarding it to the server\n :param message: Message\n :type message: smsframework.data.OutgoingMessage\n :rtype: smsframework.data.OutgoingMessage\n :raise Exception: any exception reported by the other side\n :raise urllib2.URLError: Connection error", "scope": {"holder": "kolypto-py-smsframework", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:kolypto/py-smsframework:smsframework/IProvider.py:IProvider._receive_status#14878", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "smsframework/IProvider.py", "symbol": "IProvider._receive_status"}, "source_id": "csn:kolypto/py-smsframework:smsframework/IProvider.py:IProvider._receive_status#14878"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/kolypto/py-smsframework/blob/4f3d812711f5e2e037dc80c4014c815fe2d68a0b/smsframework/IProvider.py#L76-L98", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:kolypto-py-smsframework:IProvider._receive_status-affb650bb5", "question": "Incoming status callback\n\n Calls Gateway.onStatus event hook\n\n Providers are required to:\n * Cast phone numbers to digits-only\n * Use proper MessageStatus subclasses\n * Populate `status.msgid` and `status.meta` fields\n * If this method fails with an exception, the provider is required to respond with an error to the service\n\n :type status: MessageStatus\n :param status: The received status\n :rtype: MessageStatus", "scope": {"holder": "kolypto-py-smsframework", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:ktdreyer/rhcalendar:rhcalendar/__init__.py:networkdays#19385", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "rhcalendar/__init__.py", "symbol": "networkdays"}, "source_id": "csn:ktdreyer/rhcalendar:rhcalendar/__init__.py:networkdays#19385"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/ktdreyer/rhcalendar/blob/fee4bd4b0a4fe42bea8b876e2e871e42c362c40b/rhcalendar/__init__.py#L7-L10", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:ktdreyer-rhcalendar:networkdays-2364a8880b", "question": "Return the net work days according to RH's calendar.", "scope": {"holder": "ktdreyer-rhcalendar", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:kurtbrose/sampro:sampro/sampro.py:_BaseSampler.hotspots#19444", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "sampro/sampro.py", "symbol": "_BaseSampler.hotspots"}, "source_id": "csn:kurtbrose/sampro:sampro/sampro.py:_BaseSampler.hotspots#19444"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/kurtbrose/sampro/blob/368aa0cd1a3683d12483925c4e97d225f40c8d36/sampro/sampro.py#L108-L120", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:kurtbrose-sampro:_BaseSampler.hotspots-f9ee6862d5", "question": "Get lines sampled accross all threads, in order\n from most to least sampled.", "scope": {"holder": "kurtbrose-sampro", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:kurtbrose/sampro:sampro/sampro.py:_BaseSampler.rooted_samples_by_file#19442", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "sampro/sampro.py", "symbol": "_BaseSampler.rooted_samples_by_file"}, "source_id": "csn:kurtbrose/sampro:sampro/sampro.py:_BaseSampler.rooted_samples_by_file#19442"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/kurtbrose/sampro/blob/368aa0cd1a3683d12483925c4e97d225f40c8d36/sampro/sampro.py#L73-L87", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:kurtbrose-sampro:_BaseSampler.rooted_samples_by_file-18cd4a70f6", "question": "Get sample counts by file, and root thread function.\n (Useful for answering quesitons like \"what modules are hot?\")", "scope": {"holder": "kurtbrose-sampro", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:kxepal/viivakoodi:barcode/base.py:Barcode.render#13740", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "barcode/base.py", "symbol": "Barcode.render"}, "source_id": "csn:kxepal/viivakoodi:barcode/base.py:Barcode.render#13740"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/kxepal/viivakoodi/blob/79f5e866465f481982f9870c31f49a815e921c28/barcode/base.py#L87-L103", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:kxepal-viivakoodi:Barcode.render-f4a29f5c87", "question": "Renders the barcode using `self.writer`.\n\n :parameters:\n writer_options : Dict\n Options for `self.writer`, see writer docs for details.\n\n :returns: Output of the writers render method.", "scope": {"holder": "kxepal-viivakoodi", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:kxepal/viivakoodi:barcode/base.py:Barcode.save#13739", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "barcode/base.py", "symbol": "Barcode.save"}, "source_id": "csn:kxepal/viivakoodi:barcode/base.py:Barcode.save#13739"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/kxepal/viivakoodi/blob/79f5e866465f481982f9870c31f49a815e921c28/barcode/base.py#L54-L69", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:kxepal-viivakoodi:Barcode.save-3e07534529", "question": "Renders the barcode and saves it in `filename`.\n\n :parameters:\n filename : String\n Filename to save the barcode in (without filename\n extension).\n options : Dict\n The same as in `self.render`.\n\n :returns: The full filename with extension.\n :rtype: String", "scope": {"holder": "kxepal-viivakoodi", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:labstreaminglayer/liblsl-Python:pylsl/pylsl.py:ContinuousResolver.results#9476", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pylsl/pylsl.py", "symbol": "ContinuousResolver.results"}, "source_id": "csn:labstreaminglayer/liblsl-Python:pylsl/pylsl.py:ContinuousResolver.results#9476"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/labstreaminglayer/liblsl-Python/blob/1ff6fe2794f8dba286b7491d1f7a4c915b8a0605/pylsl/pylsl.py#L1092-L1102", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:labstreaminglayer-liblsl-Python:ContinuousResolver.results-aac3d61532", "question": "Obtain the set of currently present streams on the network.\n\n Returns a list of matching StreamInfo objects (with empty desc\n field), any of which can subsequently be used to open an inlet.", "scope": {"holder": "labstreaminglayer-liblsl-Python", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:labstreaminglayer/liblsl-Python:pylsl/pylsl.py:XMLElement.next_sibling#9463", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pylsl/pylsl.py", "symbol": "XMLElement.next_sibling"}, "source_id": "csn:labstreaminglayer/liblsl-Python:pylsl/pylsl.py:XMLElement.next_sibling#9463"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/labstreaminglayer/liblsl-Python/blob/1ff6fe2794f8dba286b7491d1f7a4c915b8a0605/pylsl/pylsl.py#L924-L933", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:labstreaminglayer-liblsl-Python:XMLElement.next_sibling-4ecd0a5c40", "question": "Get the next sibling in the children list of the parent node.\n\n If a name is provided, the next sibling with the given name is returned.", "scope": {"holder": "labstreaminglayer-liblsl-Python", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:lambdalisue/django-codemirror-widget:codemirror/widgets.py:CodeMirrorTextarea.render#17057", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "codemirror/widgets.py", "symbol": "CodeMirrorTextarea.render"}, "source_id": "csn:lambdalisue/django-codemirror-widget:codemirror/widgets.py:CodeMirrorTextarea.render#17057"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/lambdalisue/django-codemirror-widget/blob/e795ade2c0c18b462e729feafa616a3047998b4b/codemirror/widgets.py#L162-L171", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:lambdalisue-django-codemirror-widget:CodeMirrorTextarea.render-f8b99e1992", "question": "u\"\"\"Render CodeMirrorTextarea", "scope": {"holder": "lambdalisue-django-codemirror-widget", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:laplacesdemon/django-youtube:django_youtube/api.py:Api._access_control#17178", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "django_youtube/api.py", "symbol": "Api._access_control"}, "source_id": "csn:laplacesdemon/django-youtube:django_youtube/api.py:Api._access_control#17178"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/laplacesdemon/django-youtube/blob/8051ef372473eccb053f773c68e2e5e1b2cfb538/django_youtube/api.py#L63-L88", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:laplacesdemon-django-youtube:Api._access_control-87bd824f3b", "question": "Prepares the extension element for access control\n Extension element is the optional parameter for the YouTubeVideoEntry\n We use extension element to modify access control settings\n\n Returns:\n tuple of extension elements", "scope": {"holder": "laplacesdemon-django-youtube", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:laplacesdemon/django-youtube:django_youtube/models.py:Video.delete#17195", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "django_youtube/models.py", "symbol": "Video.delete"}, "source_id": "csn:laplacesdemon/django-youtube:django_youtube/models.py:Video.delete#17195"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/laplacesdemon/django-youtube/blob/8051ef372473eccb053f773c68e2e5e1b2cfb538/django_youtube/models.py#L95-L111", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:laplacesdemon-django-youtube:Video.delete-c7dcc660f9", "question": "Deletes the video from youtube\n\n Raises:\n OperationError", "scope": {"holder": "laplacesdemon-django-youtube", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:larsyencken/proj:proj/__init__.py:_mkdir#15560", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "proj/__init__.py", "symbol": "_mkdir"}, "source_id": "csn:larsyencken/proj:proj/__init__.py:_mkdir#15560"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/larsyencken/proj/blob/44fd72aeb9bbf72046d81c4e9e4306a23335dc0a/proj/__init__.py#L106-L118", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:larsyencken-proj:_mkdir-905cd5e227", "question": "The equivalent of 'mkdir -p' in shell.", "scope": {"holder": "larsyencken-proj", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:larsyencken/proj:proj/__init__.py:list#15561", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "proj/__init__.py", "symbol": "list"}, "source_id": "csn:larsyencken/proj:proj/__init__.py:list#15561"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/larsyencken/proj/blob/44fd72aeb9bbf72046d81c4e9e4306a23335dc0a/proj/__init__.py#L123-L140", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:larsyencken-proj:list-ca16f53f1d", "question": "List the contents of the archive directory.", "scope": {"holder": "larsyencken-proj", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:lcharleux/argiope:argiope/materials.py:Hollomon.get_plastic_table#18891", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "argiope/materials.py", "symbol": "Hollomon.get_plastic_table"}, "source_id": "csn:lcharleux/argiope:argiope/materials.py:Hollomon.get_plastic_table#18891"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/lcharleux/argiope/blob/8170e431362dc760589f7d141090fd133dece259/argiope/materials.py#L148-L164", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:lcharleux-argiope:Hollomon.get_plastic_table-7afc8f9844", "question": "Calculates the plastic data", "scope": {"holder": "lcharleux-argiope", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:lcharleux/argiope:argiope/mesh.py:Mesh.to_triangulation#18876", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "argiope/mesh.py", "symbol": "Mesh.to_triangulation"}, "source_id": "csn:lcharleux/argiope:argiope/mesh.py:Mesh.to_triangulation#18876"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/lcharleux/argiope/blob/8170e431362dc760589f7d141090fd133dece259/argiope/mesh.py#L560-L569", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:lcharleux-argiope:Mesh.to_triangulation-16bda897fb", "question": "Returns the mesh as a matplotlib.tri.Triangulation instance. (2D only)", "scope": {"holder": "lcharleux-argiope", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:ldesousa/hex-utils:hex_utils/hasc.py:HASC.getCellVertexes#18123", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "hex_utils/hasc.py", "symbol": "HASC.getCellVertexes"}, "source_id": "csn:ldesousa/hex-utils:hex_utils/hasc.py:HASC.getCellVertexes#18123"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/ldesousa/hex-utils/blob/34b47bd9da7c0106defbe1aa5645b52c999c0e1e/hex_utils/hasc.py#L211-L232", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:ldesousa-hex-utils:HASC.getCellVertexes-9f63860faa", "question": "Edge coordinates of an hexagon centered in (x,y) having a side of d:\n \n [x-d/2, y+sqrt(3)*d/2] [x+d/2, y+sqrt(3)*d/2] \n \n [x-d, y] [x+d, y]\n \n [x-d/2, y-sqrt(3)*d/2] [x+d/2, y-sqrt(3)*d/2]", "scope": {"holder": "ldesousa-hex-utils", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:leVirve/dcard-spider:dcard/prequests.py:imap#9506", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "dcard/prequests.py", "symbol": "imap"}, "source_id": "csn:leVirve/dcard-spider:dcard/prequests.py:imap#9506"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/leVirve/dcard-spider/blob/ac64cbcfe7ef6be7e554cef422b1a8a6bb968d46/dcard/prequests.py#L130-L152", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:leVirve-dcard-spider:imap-2d5acb4d3d", "question": "Concurrently converts a generator object of Requests to\n a generator of Responses.\n\n :param requests: a generator of Request objects.\n :param stream: If False, the content will not be downloaded immediately.\n :param size: Specifies the number of requests to make at a time. default is 2\n :param exception_handler: Callback function, called when exception occured. Params: Request, Exception", "scope": {"holder": "leVirve-dcard-spider", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:leVirve/dcard-spider:dcard/prequests.py:send#9504", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "dcard/prequests.py", "symbol": "send"}, "source_id": "csn:leVirve/dcard-spider:dcard/prequests.py:send#9504"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/leVirve/dcard-spider/blob/ac64cbcfe7ef6be7e554cef422b1a8a6bb968d46/dcard/prequests.py#L80-L83", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:leVirve-dcard-spider:send-79685e1507", "question": "Just sends the request using its send method and returns its response.", "scope": {"holder": "leVirve-dcard-spider", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:lensacom/sparkit-learn:splearn/rdd.py:ArrayLikeRDDMixin.shape#6524", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "splearn/rdd.py", "symbol": "ArrayLikeRDDMixin.shape"}, "source_id": "csn:lensacom/sparkit-learn:splearn/rdd.py:ArrayLikeRDDMixin.shape#6524"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/lensacom/sparkit-learn/blob/0498502107c1f7dcf33cda0cdb6f5ba4b42524b7/splearn/rdd.py#L303-L308", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:lensacom-sparkit-learn:ArrayLikeRDDMixin.shape-6b5ff28b44", "question": "Returns the shape of the data.", "scope": {"holder": "lensacom-sparkit-learn", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:lensacom/sparkit-learn:splearn/cluster/k_means_.py:SparkKMeans.predict#6508", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "splearn/cluster/k_means_.py", "symbol": "SparkKMeans.predict"}, "source_id": "csn:lensacom/sparkit-learn:splearn/cluster/k_means_.py:SparkKMeans.predict#6508"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/lensacom/sparkit-learn/blob/0498502107c1f7dcf33cda0cdb6f5ba4b42524b7/splearn/cluster/k_means_.py#L100-L125", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:lensacom-sparkit-learn:SparkKMeans.predict-e1ddf0180c", "question": "Predict the closest cluster each sample in X belongs to.\n\n In the vector quantization literature, `cluster_centers_` is called\n the code book and each value returned by `predict` is the index of\n the closest code in the code book.\n\n Parameters\n ----------\n X : ArrayRDD containing array-like, sparse matrix\n New data to predict.\n\n Returns\n -------\n labels : ArrayRDD with predictions\n Index of the cluster each sample belongs to.", "scope": {"holder": "lensacom-sparkit-learn", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:leovp/steamfiles:steamfiles/acf.py:_dumps#17286", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "steamfiles/acf.py", "symbol": "_dumps"}, "source_id": "csn:leovp/steamfiles:steamfiles/acf.py:_dumps#17286"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/leovp/steamfiles/blob/e2264d09d128aecb838c4d310d7ea11e28c6597e/steamfiles/acf.py#L76-L100", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:leovp-steamfiles:_dumps-8f564bf024", "question": "Does the actual serializing of data into an ACF format.\n :param obj: A dictionary to serialize.\n :param level: Nesting level.\n :return: A List of strings.", "scope": {"holder": "leovp-steamfiles", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:leovp/steamfiles:steamfiles/appinfo.py:dumps#17281", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "steamfiles/appinfo.py", "symbol": "dumps"}, "source_id": "csn:leovp/steamfiles:steamfiles/appinfo.py:dumps#17281"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/leovp/steamfiles/blob/e2264d09d128aecb838c4d310d7ea11e28c6597e/steamfiles/appinfo.py#L54-L63", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:leovp-steamfiles:dumps-a97c94ff63", "question": "Serializes a dictionary into Appinfo data.\n :param obj: A dictionary to serialize.\n :return:", "scope": {"holder": "leovp-steamfiles", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:lepture/flask-oauthlib:flask_oauthlib/contrib/client/application.py:BaseApplication._make_client_with_token#5919", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "flask_oauthlib/contrib/client/application.py", "symbol": "BaseApplication._make_client_with_token"}, "source_id": "csn:lepture/flask-oauthlib:flask_oauthlib/contrib/client/application.py:BaseApplication._make_client_with_token#5919"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/lepture/flask-oauthlib/blob/9e6f152a5bb360e7496210da21561c3e6d41b0e1/flask_oauthlib/contrib/client/application.py#L88-L100", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:lepture-flask-oauthlib:BaseApplication._make_client_with_token-0da63a222a", "question": "Uses cached client or create new one with specific token.", "scope": {"holder": "lepture-flask-oauthlib", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:lepture/flask-oauthlib:flask_oauthlib/provider/oauth2.py:OAuth2RequestValidator._get_client_creds_from_request#5954", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "flask_oauthlib/provider/oauth2.py", "symbol": "OAuth2RequestValidator._get_client_creds_from_request"}, "source_id": "csn:lepture/flask-oauthlib:flask_oauthlib/provider/oauth2.py:OAuth2RequestValidator._get_client_creds_from_request#5954"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/lepture/flask-oauthlib/blob/9e6f152a5bb360e7496210da21561c3e6d41b0e1/flask_oauthlib/provider/oauth2.py#L636-L661", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:lepture-flask-oauthlib:OAuth2RequestValidator._get_client_creds_from_request-1396d64153", "question": "Return client credentials based on the current request.\n\n According to the rfc6749, client MAY use the HTTP Basic authentication\n scheme as defined in [RFC2617] to authenticate with the authorization\n server. The client identifier is encoded using the\n \"application/x-www-form-urlencoded\" encoding algorithm per Appendix B,\n and the encoded value is used as the username; the client password is\n encoded using the same algorithm and used as the password. The\n authorization server MUST support the HTTP Basic authentication scheme\n for authenticating clients that were issued a client password.\n See `Section 2.3.1`_.\n\n .. _`Section 2.3.1`: https://tools.ietf.org/html/rfc6749#section-2.3.1", "scope": {"holder": "lepture-flask-oauthlib", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:librosa/librosa:librosa/core/time_frequency.py:A_weighting#3310", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "librosa/core/time_frequency.py", "symbol": "A_weighting"}, "source_id": "csn:librosa/librosa:librosa/core/time_frequency.py:A_weighting#3310"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/librosa/librosa/blob/180e8e6eb8f958fa6b20b8cba389f7945d508247/librosa/core/time_frequency.py#L957-L1011", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:librosa-librosa:A_weighting-4f947e5b95", "question": "Compute the A-weighting of a set of frequencies.\n\n Parameters\n ----------\n frequencies : scalar or np.ndarray [shape=(n,)]\n One or more frequencies (in Hz)\n\n min_db : float [scalar] or None\n Clip weights below this threshold.\n If `None`, no clipping is performed.\n\n Returns\n -------\n A_weighting : scalar or np.ndarray [shape=(n,)]\n `A_weighting[i]` is the A-weighting of `frequencies[i]`\n\n See Also\n --------\n perceptual_weighting\n\n\n Examples\n --------\n\n Get the A-weighting for CQT frequencies\n\n >>> import matplotlib.pyplot as plt\n >>> freqs = librosa.cqt_frequencies(108, librosa.note_to_hz('C1'))\n >>> aw = librosa.A_weighting(freqs)\n >>> plt.plot(freqs, aw)\n >>> plt.xlabel('Frequency (Hz)')\n >>> plt.ylabel('Weighting (log10)')\n >>> plt.title('A-Weighting of CQT frequencies')", "scope": {"holder": "librosa-librosa", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:librosa/librosa:librosa/core/spectrum.py:istft#3369", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "librosa/core/spectrum.py", "symbol": "istft"}, "source_id": "csn:librosa/librosa:librosa/core/spectrum.py:istft#3369"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/librosa/librosa/blob/180e8e6eb8f958fa6b20b8cba389f7945d508247/librosa/core/spectrum.py#L193-L343", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:librosa-librosa:istft-08d063afb9", "question": "Inverse short-time Fourier transform (ISTFT).\n\n Converts a complex-valued spectrogram `stft_matrix` to time-series `y`\n by minimizing the mean squared error between `stft_matrix` and STFT of\n `y` as described in [1]_ up to Section 2 (reconstruction from MSTFT).\n\n In general, window function, hop length and other parameters should be same\n as in stft, which mostly leads to perfect reconstruction of a signal from\n unmodified `stft_matrix`.\n\n .. [1] D. W. Griffin and J. S. Lim,\n \"Signal estimation from modified short-time Fourier transform,\"\n IEEE Trans. ASSP, vol.32, no.2, pp.236–243, Apr. 1984.\n\n Parameters\n ----------\n stft_matrix : np.ndarray [shape=(1 + n_fft/2, t)]\n STFT matrix from `stft`\n\n hop_length : int > 0 [scalar]\n Number of frames between STFT columns.\n If unspecified, defaults to `win_length / 4`.\n\n win_length : int <= n_fft = 2 * (stft_matrix.shape[0] - 1)\n When reconstructing the time series, each frame is windowed\n and each sample is normalized by the sum of squared window\n according to the `window` function (see below).\n\n If unspecified, defaults to `n_fft`.\n\n window : string, tuple, number, function, np.ndarray [shape=(n_fft,)]\n - a window specification (string, tuple, or number);\n see `scipy.signal.get_window`\n - a window function, such as `scipy.signal.hanning`\n - a user-specified window vector of length `n_fft`\n\n .. see also:: `filters.get_window`\n\n center : boolean\n - If `True`, `D` is assumed to have centered frames.\n - If `False`, `D` is assumed to have left-aligned frames.\n\n dtype : numeric type\n Real numeric type for `y`. Default is 32-bit float.\n\n length : int > 0, optional\n If provided, the output `y` is zero-padded or clipped to exactly\n `length` samples.\n\n Returns\n -------\n y : np.ndarray [shape=(n,)]\n time domain signal reconstructed from `stft_matrix`\n\n See Also\n --------\n stft : Short-time Fourier Transform\n\n Notes\n -----\n This function caches at level 30.\n\n Examples\n --------\n >>> y, sr = librosa.load(librosa.util.example_audio_file())\n >>> D = librosa.stft(y)\n >>> y_hat = librosa.istft(D)\n >>> y_hat\n array([ -4.812e-06, -4.267e-06, ..., 6.271e-06, 2.827e-07], dtype=float32)\n\n Exactly preserving length of the input signal requires explicit padding.\n Otherwise, a partial frame at the end of `y` will not be represented.\n\n >>> n = len(y)\n >>> n_fft = 2048\n >>> y_pad = librosa.util.fix_length(y, n + n_fft // 2)\n >>> D = librosa.stft(y_pad, n_fft=n_fft)\n >>> y_out = librosa.istft(D, length=n)\n >>> np.max(np.abs(y - y_out))\n 1.4901161e-07", "scope": {"holder": "librosa-librosa", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:lincolnloop/goodconf:goodconf/__init__.py:GoodConf.generate_markdown#9806", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "goodconf/__init__.py", "symbol": "GoodConf.generate_markdown"}, "source_id": "csn:lincolnloop/goodconf:goodconf/__init__.py:GoodConf.generate_markdown#9806"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/lincolnloop/goodconf/blob/19515da5783f86b9516dbf81531107c2d9eae567/goodconf/__init__.py#L129-L145", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:lincolnloop-goodconf:GoodConf.generate_markdown-c1a367d014", "question": "Documents values in markdown", "scope": {"holder": "lincolnloop-goodconf", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:lincolnloop/goodconf:goodconf/__init__.py:_load_config#9803", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "goodconf/__init__.py", "symbol": "_load_config"}, "source_id": "csn:lincolnloop/goodconf:goodconf/__init__.py:_load_config#9803"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/lincolnloop/goodconf/blob/19515da5783f86b9516dbf81531107c2d9eae567/goodconf/__init__.py#L18-L32", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:lincolnloop-goodconf:_load_config-b12b7d4274", "question": "Given a file path, parse it based on its extension (YAML or JSON)\n and return the values as a Python dictionary. JSON is the default if an\n extension can't be determined.", "scope": {"holder": "lincolnloop-goodconf", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:linjackson78/jstyleson:jstyleson.py:dispose#17244", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "jstyleson.py", "symbol": "dispose"}, "source_id": "csn:linjackson78/jstyleson:jstyleson.py:dispose#17244"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/linjackson78/jstyleson/blob/a5aff96642684118a9a5efcb69e366f8b840346b/jstyleson.py#L4-L99", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:linjackson78-jstyleson:dispose-759a78241d", "question": "Clear all comments in json_str.\n\n Clear JS-style comments like // and /**/ in json_str.\n Accept a str or unicode as input.\n\n Args:\n json_str: A json string of str or unicode to clean up comment\n\n Returns:\n str: The str without comments (or unicode if you pass in unicode)", "scope": {"holder": "linjackson78-jstyleson", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:linuxwhatelse/mapper:mapper.py:Mapper.add#20148", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "mapper.py", "symbol": "Mapper.add"}, "source_id": "csn:linuxwhatelse/mapper:mapper.py:Mapper.add#20148"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/linuxwhatelse/mapper/blob/3481715b2a36d2da8bf5e9c6da80ceaed0d7ca59/mapper.py#L108-L131", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:linuxwhatelse-mapper:Mapper.add-852f3e3515", "question": "Function for registering a path pattern.\n\n Args:\n pattern (str): Regex pattern to match a certain path.\n function (function): Function to associate with this path.\n method (str, optional): Usually used to define one of GET, POST,\n PUT, DELETE. You may use whatever fits your situation though.\n Defaults to None.\n type_cast (dict, optional): Mapping between the param name and\n one of `int`, `float` or `bool`. The value reflected by the\n provided param name will than be casted to the given type.\n Defaults to None.", "scope": {"holder": "linuxwhatelse-mapper", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:linuxwhatelse/mapper:mapper.py:Mapper.s_add#20149", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "mapper.py", "symbol": "Mapper.s_add"}, "source_id": "csn:linuxwhatelse/mapper:mapper.py:Mapper.s_add#20149"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/linuxwhatelse/mapper/blob/3481715b2a36d2da8bf5e9c6da80ceaed0d7ca59/mapper.py#L133-L156", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:linuxwhatelse-mapper:Mapper.s_add-2815c47962", "question": "Function for registering a simple path.\n\n Args:\n path (str): Path to be matched.\n function (function): Function to associate with this path.\n method (str, optional): Usually used to define one of GET, POST,\n PUT, DELETE. You may use whatever fits your situation though.\n Defaults to None.\n type_cast (dict, optional): Mapping between the param name and\n one of `int`, `float` or `bool`. The value reflected by the\n provided param name will than be casted to the given type.\n Defaults to None.", "scope": {"holder": "linuxwhatelse-mapper", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:litl/leeroy:leeroy/github.py:get_pull_requests#12331", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "leeroy/github.py", "symbol": "get_pull_requests"}, "source_id": "csn:litl/leeroy:leeroy/github.py:get_pull_requests#12331"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/litl/leeroy/blob/ab6565a3b63e9103d8c011d9c62a9c0ad589b051/leeroy/github.py#L251-L262", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:litl-leeroy:get_pull_requests-fff5cd9e34", "question": "Last 30 pull requests from a repository.\n\n :param app: Flask app\n :param repo_config: dict with ``github_repo`` key\n\n :returns: id for a pull request", "scope": {"holder": "litl-leeroy", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:littlemo/mohand:source/mohand/main.py:cli#16549", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "source/mohand/main.py", "symbol": "cli"}, "source_id": "csn:littlemo/mohand:source/mohand/main.py:cli#16549"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/littlemo/mohand/blob/9bd4591e457d594f2ce3a0c089ef28d3b4e027e8/source/mohand/main.py#L86-L95", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:littlemo-mohand:cli-b5f7712899", "question": "通用自动化处理工具\n\n 详情参考 `GitHub <https://github.com/littlemo/mohand>`_", "scope": {"holder": "littlemo-mohand", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:littlemo/mohand:source/mohand/version.py:get_cli_version#16521", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "source/mohand/version.py", "symbol": "get_cli_version"}, "source_id": "csn:littlemo/mohand:source/mohand/version.py:get_cli_version#16521"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/littlemo/mohand/blob/9bd4591e457d594f2ce3a0c089ef28d3b4e027e8/source/mohand/version.py#L45-L60", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:littlemo-mohand:get_cli_version-6b62771c8d", "question": "获取终端命令版本号，若存在VERSION文件则使用其中的版本号，\n 否则使用 :meth:`.get_setup_version`\n\n :return: 终端命令版本号\n :rtype: str", "scope": {"holder": "littlemo-mohand", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:liubola/sangreal-db:sangreal_db/core/database.py:DataBase.insert#13756", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "sangreal_db/core/database.py", "symbol": "DataBase.insert"}, "source_id": "csn:liubola/sangreal-db:sangreal_db/core/database.py:DataBase.insert#13756"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/liubola/sangreal-db/blob/f9b6339421d8d308e0ebc2a42c432ca99026c264/sangreal_db/core/database.py#L114-L141", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:liubola-sangreal-db:DataBase.insert-8ad3dc2d16", "question": "[insert bulk data]\n\n Arguments:\n table {[DeclarativeMeta cls]} -- [reflection of table]\n insert_obj {[pd.DataFrame or list of dicts]} -- [insert_obj]\n\n Keyword Arguments:\n ignore {bool} -- [wether ignore exception or not] (default: {True})\n\n Raises:\n ValueError -- [f\"The {reprlib.repr(insert_obj)} must be list of dicts type!\"]\n\n Returns:\n [type] -- [description]", "scope": {"holder": "liubola-sangreal-db", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:liubola/sangreal-db:sangreal_db/core/database.py:DataBase.update#13755", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "sangreal_db/core/database.py", "symbol": "DataBase.update"}, "source_id": "csn:liubola/sangreal-db:sangreal_db/core/database.py:DataBase.update#13755"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/liubola/sangreal-db/blob/f9b6339421d8d308e0ebc2a42c432ca99026c264/sangreal_db/core/database.py#L102-L112", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:liubola-sangreal-db:DataBase.update-d993968c84", "question": "[update table]\n\n Arguments:\n t_obj {[objs of DeclarativeMeta]} -- [update the table]", "scope": {"holder": "liubola-sangreal-db", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:lkreidberg/batman:batman/transitmodel.py:TransitModel.get_t_conjunction#9952", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "batman/transitmodel.py", "symbol": "TransitModel.get_t_conjunction"}, "source_id": "csn:lkreidberg/batman:batman/transitmodel.py:TransitModel.get_t_conjunction#9952"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/lkreidberg/batman/blob/77f3275c12a01ef5b7a89b1aeb6272a7c28452a1/batman/transitmodel.py#L299-L305", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:lkreidberg-batman:TransitModel.get_t_conjunction-37ea15b752", "question": "Return the time of primary transit center (calculated using `params.t_secondary`).", "scope": {"holder": "lkreidberg-batman", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:lkreidberg/batman:batman/transitmodel.py:TransitModel.get_true_anomaly#9953", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "batman/transitmodel.py", "symbol": "TransitModel.get_true_anomaly"}, "source_id": "csn:lkreidberg/batman:batman/transitmodel.py:TransitModel.get_true_anomaly#9953"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/lkreidberg/batman/blob/77f3275c12a01ef5b7a89b1aeb6272a7c28452a1/batman/transitmodel.py#L307-L314", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:lkreidberg-batman:TransitModel.get_true_anomaly-5f2ba363db", "question": "Return the true anomaly at each time", "scope": {"holder": "lkreidberg-batman", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:llimllib/pub:pub/pub.py:get_tasks#19607", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pub/pub.py", "symbol": "get_tasks"}, "source_id": "csn:llimllib/pub:pub/pub.py:get_tasks#19607"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/llimllib/pub/blob/bd8472f04800612c50cac0682a4aee0a441b1d56/pub/pub.py#L66-L83", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:llimllib-pub:get_tasks-2942d4016c", "question": "Given a list of tasks to perform and a dependency graph, return the tasks\n that must be performed, in the correct order", "scope": {"holder": "llimllib-pub", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:llimllib/pub:pub/shortcuts/shortcuts.py:make_shortcut#19742", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pub/shortcuts/shortcuts.py", "symbol": "make_shortcut"}, "source_id": "csn:llimllib/pub:pub/shortcuts/shortcuts.py:make_shortcut#19742"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/llimllib/pub/blob/bd8472f04800612c50cac0682a4aee0a441b1d56/pub/shortcuts/shortcuts.py#L21-L28", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:llimllib-pub:make_shortcut-30c1f398c0", "question": "return a function which runs the given cmd\n \n make_shortcut('ls') returns a function which executes\n envoy.run('ls ' + arguments)", "scope": {"holder": "llimllib-pub", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:lmjohns3/theanets:theanets/feedforward.py:Autoencoder._find_output#14177", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "theanets/feedforward.py", "symbol": "Autoencoder._find_output"}, "source_id": "csn:lmjohns3/theanets:theanets/feedforward.py:Autoencoder._find_output#14177"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/lmjohns3/theanets/blob/79db9f878ef2071f2f576a1cf5d43a752a55894a/theanets/feedforward.py#L180-L208", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:lmjohns3-theanets:Autoencoder._find_output-82fc59f530", "question": "Find a layer output name for the given layer specifier.\n\n Parameters\n ----------\n layer : None, int, str, or :class:`theanets.layers.Layer`\n A layer specification. If this is None, the \"middle\" layer in the\n network will be used (i.e., the layer at the middle index in the\n list of network layers). If this is an integer, the corresponding\n layer in the network's layer list will be used. If this is a string,\n the layer with the corresponding name will be returned.\n\n Returns\n -------\n name : str\n The fully-scoped output name for the desired layer.", "scope": {"holder": "lmjohns3-theanets", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:lmjohns3/theanets:theanets/graph.py:Network.find#14212", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "theanets/graph.py", "symbol": "Network.find"}, "source_id": "csn:lmjohns3/theanets:theanets/graph.py:Network.find#14212"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/lmjohns3/theanets/blob/79db9f878ef2071f2f576a1cf5d43a752a55894a/theanets/graph.py#L467-L499", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:lmjohns3-theanets:Network.find-abf30d0cd2", "question": "Get a parameter from a layer in the network.\n\n Parameters\n ----------\n which : int or str\n The layer that owns the parameter to return.\n\n If this is an integer, then 0 refers to the input layer, 1 refers\n to the first hidden layer, 2 to the second, and so on.\n\n If this is a string, the layer with the corresponding name, if any,\n will be used.\n\n param : int or str\n Name of the parameter to retrieve from the specified layer, or its\n index in the parameter list of the layer.\n\n Raises\n ------\n KeyError\n If there is no such layer, or if there is no such parameter in the\n specified layer.\n\n Returns\n -------\n param : Theano shared variable\n A shared parameter variable from the indicated layer.", "scope": {"holder": "lmjohns3-theanets", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:loanzen/probe-py:probe/api_client.py:ApiClient.prepare_post_parameters#19379", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "probe/api_client.py", "symbol": "ApiClient.prepare_post_parameters"}, "source_id": "csn:loanzen/probe-py:probe/api_client.py:ApiClient.prepare_post_parameters#19379"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/loanzen/probe-py/blob/b5dbb0dba26c9b451e9bf1dec9e1aaa7f42d75a5/probe/api_client.py#L381-L406", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:loanzen-probe-py:ApiClient.prepare_post_parameters-50043ae1ac", "question": "Builds form parameters.\n\n :param post_params: Normal form parameters.\n :param files: File parameters.\n :return: Form parameters with files.", "scope": {"holder": "loanzen-probe-py", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:loanzen/probe-py:probe/models/company_detail_company.py:CompanyDetailCompany.classification#19265", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "probe/models/company_detail_company.py", "symbol": "CompanyDetailCompany.classification"}, "source_id": "csn:loanzen/probe-py:probe/models/company_detail_company.py:CompanyDetailCompany.classification#19265"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/loanzen/probe-py/blob/b5dbb0dba26c9b451e9bf1dec9e1aaa7f42d75a5/probe/models/company_detail_company.py#L182-L196", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:loanzen-probe-py:CompanyDetailCompany.classification-9c4705e58f", "question": "Sets the classification of this CompanyDetailCompany.\n Classification of Company\n\n :param classification: The classification of this CompanyDetailCompany.\n :type: str", "scope": {"holder": "loanzen-probe-py", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:lord63/five.py:five/five.py:Five.loud#19427", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "five/five.py", "symbol": "Five.loud"}, "source_id": "csn:lord63/five.py:five/five.py:Five.loud#19427"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/lord63/five.py/blob/d7970d5059af9e2f6648f3867649694799415d00/five/five.py#L63-L69", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:lord63-five.py:Five.loud-c5cdfe140f", "question": "Speak loudly! FIVE! Use upper case!", "scope": {"holder": "lord63-five.py", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:lord63/five.py:five/five.py:Five.rotate#19428", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "five/five.py", "symbol": "Five.rotate"}, "source_id": "csn:lord63/five.py:five/five.py:Five.rotate#19428"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/lord63/five.py/blob/d7970d5059af9e2f6648f3867649694799415d00/five/five.py#L339-L348", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:lord63-five.py:Five.rotate-b7be1acea3", "question": "Replaced by a letter 5 right shift.\n e.g. a->f, b->g, . -> .", "scope": {"holder": "lord63-five.py", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:lsst-sqre/ltd-conveyor:ltdconveyor/s3/upload.py:ObjectManager._create_prefix#19423", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "ltdconveyor/s3/upload.py", "symbol": "ObjectManager._create_prefix"}, "source_id": "csn:lsst-sqre/ltd-conveyor:ltdconveyor/s3/upload.py:ObjectManager._create_prefix#19423"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/lsst-sqre/ltd-conveyor/blob/c492937c4c1e050ccc4a0b9dcc38f9980d57e305/ltdconveyor/s3/upload.py#L409-L419", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:lsst-sqre-ltd-conveyor:ObjectManager._create_prefix-595515b5e5", "question": "Make an absolute directory path in the bucker for dirname,\n which is is assumed relative to the self._bucket_root prefix directory.", "scope": {"holder": "lsst-sqre-ltd-conveyor", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:lsst-sqre/ltd-conveyor:ltdconveyor/cli/utils.py:ensure_login#19426", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "ltdconveyor/cli/utils.py", "symbol": "ensure_login"}, "source_id": "csn:lsst-sqre/ltd-conveyor:ltdconveyor/cli/utils.py:ensure_login#19426"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/lsst-sqre/ltd-conveyor/blob/c492937c4c1e050ccc4a0b9dcc38f9980d57e305/ltdconveyor/cli/utils.py#L12-L52", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:lsst-sqre-ltd-conveyor:ensure_login-a552d913ba", "question": "Ensure a token is in the Click context object or authenticate and obtain\n the token from LTD Keeper.\n\n Parameters\n ----------\n ctx : `click.Context`\n The Click context. ``ctx.obj`` must be a `dict` that contains keys:\n ``keeper_hostname``, ``username``, ``password``, ``token``. This\n context object is prepared by the main Click group,\n `ltdconveyor.cli.main.main`.", "scope": {"holder": "lsst-sqre-ltd-conveyor", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:lucaslamounier/USGSDownload:usgsdownload/usgs.py:USGSDownload.connect_earthexplorer#18303", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "usgsdownload/usgs.py", "symbol": "USGSDownload.connect_earthexplorer"}, "source_id": "csn:lucaslamounier/USGSDownload:usgsdownload/usgs.py:USGSDownload.connect_earthexplorer#18303"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/lucaslamounier/USGSDownload/blob/0969483ea9f9648aa17b099f36d2e1010488b2a4/usgsdownload/usgs.py#L193-L215", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:lucaslamounier-USGSDownload:USGSDownload.connect_earthexplorer-9877894bf2", "question": "Connection to Earth explorer without proxy", "scope": {"holder": "lucaslamounier-USGSDownload", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:lucaslamounier/USGSDownload:usgsdownload/usgs.py:USGSDownload.get_remote_file_size#18300", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "usgsdownload/usgs.py", "symbol": "USGSDownload.get_remote_file_size"}, "source_id": "csn:lucaslamounier/USGSDownload:usgsdownload/usgs.py:USGSDownload.get_remote_file_size#18300"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/lucaslamounier/USGSDownload/blob/0969483ea9f9648aa17b099f36d2e1010488b2a4/usgsdownload/usgs.py#L114-L123", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:lucaslamounier-USGSDownload:USGSDownload.get_remote_file_size-15eae9a56d", "question": "Gets the filesize of a remote file", "scope": {"holder": "lucaslamounier-USGSDownload", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:lvh/txampext:txampext/constraints.py:ConstrainedArgument.fromString#19757", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "txampext/constraints.py", "symbol": "ConstrainedArgument.fromString"}, "source_id": "csn:lvh/txampext:txampext/constraints.py:ConstrainedArgument.fromString#19757"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/lvh/txampext/blob/a7d6cb9f1e9200dba597378cd40eb6a2096d4fd9/txampext/constraints.py#L29-L36", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:lvh-txampext:ConstrainedArgument.fromString-6bd9b22ece", "question": "Converts the string to a value using the composed AMP argument, then\n checks all the constraints against that value.", "scope": {"holder": "lvh-txampext", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:lvh/txampext:txampext/multiplexing.py:MultiplexingCommandLocator.receiveData#19637", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "txampext/multiplexing.py", "symbol": "MultiplexingCommandLocator.receiveData"}, "source_id": "csn:lvh/txampext:txampext/multiplexing.py:MultiplexingCommandLocator.receiveData#19637"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/lvh/txampext/blob/a7d6cb9f1e9200dba597378cd40eb6a2096d4fd9/txampext/multiplexing.py#L168-L178", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:lvh-txampext:MultiplexingCommandLocator.receiveData-9891f67680", "question": "Receives some data for the given protocol.", "scope": {"holder": "lvh-txampext", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:makearl/tornado-profile:tornado_profile.py:CProfileHandler.delete#18687", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "tornado_profile.py", "symbol": "CProfileHandler.delete"}, "source_id": "csn:makearl/tornado-profile:tornado_profile.py:CProfileHandler.delete#18687"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/makearl/tornado-profile/blob/1b721480d7edc6229f991469e88b9f7a8bb914f3/tornado_profile.py#L212-L217", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:makearl-tornado-profile:CProfileHandler.delete-bbd03b3522", "question": "Stop the profiler.", "scope": {"holder": "makearl-tornado-profile", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:makearl/tornado-profile:tornado_profile.py:CProfileStatsHandler.get#18684", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "tornado_profile.py", "symbol": "CProfileStatsHandler.get"}, "source_id": "csn:makearl/tornado-profile:tornado_profile.py:CProfileStatsHandler.get#18684"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/makearl/tornado-profile/blob/1b721480d7edc6229f991469e88b9f7a8bb914f3/tornado_profile.py#L177-L186", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:makearl-tornado-profile:CProfileStatsHandler.get-ab0bcfc9e3", "question": "Return current profiler statistics.", "scope": {"holder": "makearl-tornado-profile", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:makeev/django-boolean-switch:boolean_switch/admin.py:AdminBooleanMixin.get_list_display#15606", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "boolean_switch/admin.py", "symbol": "AdminBooleanMixin.get_list_display"}, "source_id": "csn:makeev/django-boolean-switch:boolean_switch/admin.py:AdminBooleanMixin.get_list_display#15606"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/makeev/django-boolean-switch/blob/ed740dbb56d0bb1ad20d4b1e124055283b0e932f/boolean_switch/admin.py#L44-L58", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:makeev-django-boolean-switch:AdminBooleanMixin.get_list_display-904f5a7ae2", "question": "Return a sequence containing the fields to be displayed on the\n changelist.", "scope": {"holder": "makeev-django-boolean-switch", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:makeev/django-boolean-switch:boolean_switch/views.py:switch#15719", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "boolean_switch/views.py", "symbol": "switch"}, "source_id": "csn:makeev/django-boolean-switch:boolean_switch/views.py:switch#15719"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/makeev/django-boolean-switch/blob/ed740dbb56d0bb1ad20d4b1e124055283b0e932f/boolean_switch/views.py#L9-L37", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:makeev-django-boolean-switch:switch-6b7c228dfc", "question": "Set/clear boolean field value for model object", "scope": {"holder": "makeev-django-boolean-switch", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:manrajgrover/py-spinners:examples/examples.py:animate#9816", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "examples/examples.py", "symbol": "animate"}, "source_id": "csn:manrajgrover/py-spinners:examples/examples.py:animate#9816"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/manrajgrover/py-spinners/blob/2400b5f355049a691202671cb2ccf2b269eef4a3/examples/examples.py#L75-L96", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:manrajgrover-py-spinners:animate-7d7ce314e7", "question": "Animate given frame for set number of iterations.\n\n Parameters\n ----------\n frames : list\n Frames for animating\n interval : float\n Interval between two frames\n name : str\n Name of animation\n iterations : int, optional\n Number of loops for animations", "scope": {"holder": "manrajgrover-py-spinners", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:maralla/bmd:bmd/bmd.py:download_music#19772", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "bmd/bmd.py", "symbol": "download_music"}, "source_id": "csn:maralla/bmd:bmd/bmd.py:download_music#19772"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/maralla/bmd/blob/bbf87dc01de9a363ae5031e22a5ccc50d506f78a/bmd/bmd.py#L88-L127", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:maralla-bmd:download_music-5877b52d73", "question": "process for downing music with multiple threads", "scope": {"holder": "maralla-bmd", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:maralla/bmd:bmd/bmd.py:music_info#19771", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "bmd/bmd.py", "symbol": "music_info"}, "source_id": "csn:maralla/bmd:bmd/bmd.py:music_info#19771"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/maralla/bmd/blob/bbf87dc01de9a363ae5031e22a5ccc50d506f78a/bmd/bmd.py#L61-L85", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:maralla-bmd:music_info-78c353110e", "question": "Get music info from baidu music api", "scope": {"holder": "maralla-bmd", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:marcoagner/Flask-QRcode:flask_qrcode/__init__.py:QRcode._insert_img#11176", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "flask_qrcode/__init__.py", "symbol": "QRcode._insert_img"}, "source_id": "csn:marcoagner/Flask-QRcode:flask_qrcode/__init__.py:QRcode._insert_img#11176"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/marcoagner/Flask-QRcode/blob/fbedf5a671d86cae7e446b10d612e319fc21162b/flask_qrcode/__init__.py#L162-L190", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:marcoagner-Flask-QRcode:QRcode._insert_img-c5888e7447", "question": "Inserts a small icon to QR Code image", "scope": {"holder": "marcoagner-Flask-QRcode", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:marcoagner/Flask-QRcode:flask_qrcode/__init__.py:QRcode.qrcode#11175", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "flask_qrcode/__init__.py", "symbol": "QRcode.qrcode"}, "source_id": "csn:marcoagner/Flask-QRcode:flask_qrcode/__init__.py:QRcode.qrcode#11175"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/marcoagner/Flask-QRcode/blob/fbedf5a671d86cae7e446b10d612e319fc21162b/flask_qrcode/__init__.py#L96-L159", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:marcoagner-Flask-QRcode:QRcode.qrcode-4f0dbf8718", "question": "Makes qr image using qrcode as qrc. See documentation\n for qrcode (https://pypi.python.org/pypi/qrcode) package for more info.\n\n :param data: String data.\n :param mode: Output mode, [base64|raw].\n :param version: The size of the QR Code (1-40).\n :param error_correction: The error correction used for the QR Code.\n :param box_size: The number of pixels for each \"box\" of the QR code.\n :param border: The number of box for border.\n :param fit: If `True`, find the best fit for the data.\n :param fill_color: Frontend color.\n :param back_color: Background color.\n\n :param icon_img: Small icon image name or url.\n :param factor: Resize for icon image (default: 4, one-fourth of QRCode)\n :param icon_box: Icon image position [left, top] (default: image center)", "scope": {"holder": "marcoagner-Flask-QRcode", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:marians/py-daterangestr:daterangestr.py:to_dates#19601", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "daterangestr.py", "symbol": "to_dates"}, "source_id": "csn:marians/py-daterangestr:daterangestr.py:to_dates#19601"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/marians/py-daterangestr/blob/fa5dd78c8fea5f91a85bf732af8a0bc307641134/daterangestr.py#L33-L65", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:marians-py-daterangestr:to_dates-cdc9c9ba0e", "question": "This function takes a date string in various formats\n and converts it to a normalized and validated date range. A list\n with two elements is returned, lower and upper date boundary.\n\n Valid inputs are, for example:\n 2012 => Jan 1 20012 - Dec 31 2012 (whole year)\n 201201 => Jan 1 2012 - Jan 31 2012 (whole month)\n 2012101 => Jan 1 2012 - Jan 1 2012 (whole day)\n 2011-2011 => same as \"2011\", which means whole year 2012\n 2011-2012 => Jan 1 2011 - Dec 31 2012 (two years)\n 201104-2012 => Apr 1 2011 - Dec 31 2012\n 201104-201203 => Apr 1 2011 - March 31 2012\n 20110408-2011 => Apr 8 2011 - Dec 31 2011\n 20110408-201105 => Apr 8 2011 - May 31 2011\n 20110408-20110507 => Apr 8 2011 - May 07 2011\n 2011- => Jan 1 2012 - Dec 31 9999 (unlimited)\n 201104- => Apr 1 2011 - Dec 31 9999 (unlimited)\n 20110408- => Apr 8 2011 - Dec 31 9999 (unlimited)\n -2011 Jan 1 0000 - Dez 31 2011\n -201104 Jan 1 0000 - Apr 30, 2011\n -20110408 Jan 1 0000 - Apr 8, 2011", "scope": {"holder": "marians-py-daterangestr", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:marrabld/planarradpy:gui/gui_batch.py:BatchFile.write_batch_to_file#16608", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "gui/gui_batch.py", "symbol": "BatchFile.write_batch_to_file"}, "source_id": "csn:marrabld/planarradpy:gui/gui_batch.py:BatchFile.write_batch_to_file#16608"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/marrabld/planarradpy/blob/5095d1cb98d4f67a7c3108c9282f2d59253e89a8/gui/gui_batch.py#L31-L152", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:marrabld-planarradpy:BatchFile.write_batch_to_file-e51b3f844e", "question": "This function creates a new file if he doesn't exist already, moves it to 'inputs/batch_file' folder\n and writes data and comments associated to them.\n Inputs: saa_values : <list> Sun Azimuth Angle (deg)\n sza_values : <list> Sun Zenith Angle (deg)\n batch_name : Name of the batch file.\n p_values : <list> Phytoplankton linear scaling factor\n x_value : <list> Scattering scaling factor\n y_value : <list> Scattering slope factor\n g_value : <list> CDOM absorption scaling factor\n s_value : <list> CDOM absorption slope factor\n s_value : <list> depth (m)\n waveL_values : Wavelength values used to test.\n verbose_value : Number concerning if the software explains a lot or not what it does.\n phytoplankton_path : The path to the file containing phytoplankton data.\n bottom_path : The path to the file containing bottom data.\n nb_cpu : The number of CPU we want to allowed to the software.\n executive_path : The path to the file where there is executive files using by PlanarRad.\n report_parameter :", "scope": {"holder": "marrabld-planarradpy", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:marrabld/planarradpy:gui/gui_mainLayout.py:FormEvents.graphic_slider#16647", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "gui/gui_mainLayout.py", "symbol": "FormEvents.graphic_slider"}, "source_id": "csn:marrabld/planarradpy:gui/gui_mainLayout.py:FormEvents.graphic_slider#16647"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/marrabld/planarradpy/blob/5095d1cb98d4f67a7c3108c9282f2d59253e89a8/gui/gui_mainLayout.py#L613-L628", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:marrabld-planarradpy:FormEvents.graphic_slider-6cd7b059dc", "question": "This function scales the slider for curves displayed.\n Input : The number of cases (curves).\n Return ; The slider value.", "scope": {"holder": "marrabld-planarradpy", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:marrow/package:marrow/package/loader.py:load#13458", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "marrow/package/loader.py", "symbol": "load"}, "source_id": "csn:marrow/package:marrow/package/loader.py:load#13458"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/marrow/package/blob/133d4bf67cc857d1b2423695938a00ff2dfa8af2/marrow/package/loader.py#L57-L104", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:marrow-package:load-38fc59b147", "question": "This helper function loads an object identified by a dotted-notation string.\n\t\n\tFor example::\n\t\n\t\t# Load class Foo from example.objects\n\t\tload('example.objects:Foo')\n\t\t\n\t\t# Load the result of the class method ``new`` of the Foo object\n\t\tload('example.objects:Foo.new', executable=True)\n\t\n\tIf a plugin namespace is provided simple name references are allowed. For example::\n\t\n\t\t# Load the plugin named 'routing' from the 'web.dispatch' namespace\n\t\tload('routing', 'web.dispatch')\n\t\n\tThe ``executable``, ``protect``, and first tuple element of ``separators`` are passed to the traverse function.\n\tProviding a namespace does not prevent full object lookup (dot-colon notation) from working.", "scope": {"holder": "marrow-package", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:marrow/package:marrow/package/tarjan.py:robust_topological_sort#13463", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "marrow/package/tarjan.py", "symbol": "robust_topological_sort"}, "source_id": "csn:marrow/package:marrow/package/tarjan.py:robust_topological_sort#13463"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/marrow/package/blob/133d4bf67cc857d1b2423695938a00ff2dfa8af2/marrow/package/tarjan.py#L82-L105", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:marrow-package:robust_topological_sort-24b8580733", "question": "Identify strongly connected components then perform a topological sort of those components.", "scope": {"holder": "marrow-package", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:marrow/web.db:web/ext/db.py:DatabaseExtension._handle_event#16443", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "web/ext/db.py", "symbol": "DatabaseExtension._handle_event"}, "source_id": "csn:marrow/web.db:web/ext/db.py:DatabaseExtension._handle_event#16443"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/marrow/web.db/blob/c755fbff7028a5edc223d6a631b8421858274fc4/web/ext/db.py#L52-L57", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:marrow-web.db:DatabaseExtension._handle_event-a277f45abf", "question": "Broadcast an event to the database connections registered.", "scope": {"holder": "marrow-web.db", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:marrow/web.db:web/db/me.py:MongoEngineConnection.prepare#16428", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "web/db/me.py", "symbol": "MongoEngineConnection.prepare"}, "source_id": "csn:marrow/web.db:web/db/me.py:MongoEngineConnection.prepare#16428"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/marrow/web.db/blob/c755fbff7028a5edc223d6a631b8421858274fc4/web/db/me.py#L85-L88", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:marrow-web.db:MongoEngineConnection.prepare-f864c01d8e", "question": "Attach this connection's default database to the context using our alias.", "scope": {"holder": "marrow-web.db", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:marshmallow-code/marshmallow-sqlalchemy:src/marshmallow_sqlalchemy/convert.py:ModelConverter._add_column_kwargs#8606", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "src/marshmallow_sqlalchemy/convert.py", "symbol": "ModelConverter._add_column_kwargs"}, "source_id": "csn:marshmallow-code/marshmallow-sqlalchemy:src/marshmallow_sqlalchemy/convert.py:ModelConverter._add_column_kwargs#8606"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/marshmallow-code/marshmallow-sqlalchemy/blob/afe3a9ebd886791b662607499c180d2baaeaf617/src/marshmallow_sqlalchemy/convert.py#L220-L243", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:marshmallow-code-marshmallow-sqlalchemy:ModelConverter._add_column_kwargs-205cb5b19b", "question": "Add keyword arguments to kwargs (in-place) based on the passed in\n `Column <sqlalchemy.schema.Column>`.", "scope": {"holder": "marshmallow-code-marshmallow-sqlalchemy", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:marshmallow-code/marshmallow-sqlalchemy:src/marshmallow_sqlalchemy/schema.py:ModelSchema.make_instance#8610", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "src/marshmallow_sqlalchemy/schema.py", "symbol": "ModelSchema.make_instance"}, "source_id": "csn:marshmallow-code/marshmallow-sqlalchemy:src/marshmallow_sqlalchemy/schema.py:ModelSchema.make_instance#8610"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/marshmallow-code/marshmallow-sqlalchemy/blob/afe3a9ebd886791b662607499c180d2baaeaf617/src/marshmallow_sqlalchemy/schema.py#L185-L201", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:marshmallow-code-marshmallow-sqlalchemy:ModelSchema.make_instance-fce236522d", "question": "Deserialize data to an instance of the model. Update an existing row\n if specified in `self.instance` or loaded by primary key(s) in the data;\n else create a new row.\n\n :param data: Data to deserialize.", "scope": {"holder": "marshmallow-code-marshmallow-sqlalchemy", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:matrix-org/python-canonicaljson:canonicaljson.py:_unascii#14521", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "canonicaljson.py", "symbol": "_unascii"}, "source_id": "csn:matrix-org/python-canonicaljson:canonicaljson.py:_unascii#14521"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/matrix-org/python-canonicaljson/blob/c508635e867ff11026b610c00ca906002d8fb9af/canonicaljson.py#L74-L147", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:matrix-org-python-canonicaljson:_unascii-c8f2c8ce0e", "question": "Unpack `\\\\uNNNN` escapes in 's' and encode the result as UTF-8\n\n This method takes the output of the JSONEncoder and expands any \\\\uNNNN\n escapes it finds (except for \\\\u0000 to \\\\u001F, which are converted to\n \\\\xNN escapes).\n\n For performance, it assumes that the input is valid JSON, and performs few\n sanity checks.", "scope": {"holder": "matrix-org-python-canonicaljson", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:matthewdeanmartin/find_known_secrets:find_known_secrets/searcher.py:Searcher.search_known_secrets#19884", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "find_known_secrets/searcher.py", "symbol": "Searcher.search_known_secrets"}, "source_id": "csn:matthewdeanmartin/find_known_secrets:find_known_secrets/searcher.py:Searcher.search_known_secrets#19884"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/matthewdeanmartin/find_known_secrets/blob/f25735c1ab4512bad85ade33af7021f6fac1d13b/find_known_secrets/searcher.py#L82-L126", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:matthewdeanmartin-find_known_secrets:Searcher.search_known_secrets-e3c3e25863", "question": "Search a path for known secrets, outputing text and file when found\n :return:", "scope": {"holder": "matthewdeanmartin-find_known_secrets", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:matthewdeanmartin/find_known_secrets:build.py:dead_code#20105", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "build.py", "symbol": "dead_code"}, "source_id": "csn:matthewdeanmartin/find_known_secrets:build.py:dead_code#20105"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/matthewdeanmartin/find_known_secrets/blob/f25735c1ab4512bad85ade33af7021f6fac1d13b/build.py#L332-L351", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:matthewdeanmartin-find_known_secrets:dead_code-4a919e5d3f", "question": "This also finds code you are working on today!", "scope": {"holder": "matthewdeanmartin-find_known_secrets", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:maxcountryman/flask-uploads:flask_uploads.py:UploadSet.config#6418", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "flask_uploads.py", "symbol": "UploadSet.config"}, "source_id": "csn:maxcountryman/flask-uploads:flask_uploads.py:UploadSet.config#6418"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/maxcountryman/flask-uploads/blob/dc24fa0c53d605876e5b4502cadffdf1a4345b1d/flask_uploads.py#L315-L329", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:maxcountryman-flask-uploads:UploadSet.config-277d1c4c83", "question": "This gets the current configuration. By default, it looks up the\n current application and gets the configuration from there. But if you\n don't want to go to the full effort of setting an application, or it's\n otherwise outside of a request context, set the `_config` attribute to\n an `UploadConfiguration` instance, then set it back to `None` when\n you're done.", "scope": {"holder": "maxcountryman-flask-uploads", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:maxcountryman/flask-uploads:flask_uploads.py:UploadSet.url#6419", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "flask_uploads.py", "symbol": "UploadSet.url"}, "source_id": "csn:maxcountryman/flask-uploads:flask_uploads.py:UploadSet.url#6419"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/maxcountryman/flask-uploads/blob/dc24fa0c53d605876e5b4502cadffdf1a4345b1d/flask_uploads.py#L331-L343", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:maxcountryman-flask-uploads:UploadSet.url-a2501918dc", "question": "This function gets the URL a file uploaded to this set would be\n accessed at. It doesn't check whether said file exists.\n\n :param filename: The filename to return the URL for.", "scope": {"holder": "maxcountryman-flask-uploads", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:may-day/wsgicors:wsgicors.py:CORS.selectPolicy#17279", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "wsgicors.py", "symbol": "CORS.selectPolicy"}, "source_id": "csn:may-day/wsgicors:wsgicors.py:CORS.selectPolicy#17279"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/may-day/wsgicors/blob/619867a811b10c788c40c4af5204142ffabe0f1f/wsgicors.py#L104-L127", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:may-day-wsgicors:CORS.selectPolicy-cacb4b0058", "question": "Based on the matching strategy and the origin and optionally the requested method a tuple of policyname and origin to pass back is returned.", "scope": {"holder": "may-day-wsgicors", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:mblayman/httpony:httpony/server.py:build_parser#19054", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "httpony/server.py", "symbol": "build_parser"}, "source_id": "csn:mblayman/httpony:httpony/server.py:build_parser#19054"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/mblayman/httpony/blob/5af404d647a8dac8a043b64ea09882589b3b5247/httpony/server.py#L40-L55", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:mblayman-httpony:build_parser-203d1e5db0", "question": "Build the parser that will have all available commands and options.", "scope": {"holder": "mblayman-httpony", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:mblayman/httpony:httpony/application.py:make_app#18990", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "httpony/application.py", "symbol": "make_app"}, "source_id": "csn:mblayman/httpony:httpony/application.py:make_app#18990"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/mblayman/httpony/blob/5af404d647a8dac8a043b64ea09882589b3b5247/httpony/application.py#L15-L55", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:mblayman-httpony:make_app-71e221bcc4", "question": "Make a WSGI app that has all the HTTPie pieces baked in.", "scope": {"holder": "mblayman-httpony", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:mcs07/MolVS:molvs/fragment.py:FragmentRemover.remove#10255", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "molvs/fragment.py", "symbol": "FragmentRemover.remove"}, "source_id": "csn:mcs07/MolVS:molvs/fragment.py:FragmentRemover.remove#10255"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/mcs07/MolVS/blob/d815fe52d160abcecbcbf117e6437bf727dbd8ad/molvs/fragment.py#L157-L179", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:mcs07-MolVS:FragmentRemover.remove-a373a5f14a", "question": "Return the molecule with specified fragments removed.\n\n :param mol: The molecule to remove fragments from.\n :type mol: rdkit.Chem.rdchem.Mol\n :return: The molecule with fragments removed.\n :rtype: rdkit.Chem.rdchem.Mol", "scope": {"holder": "mcs07-MolVS", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:mcs07/MolVS:molvs/standardize.py:Standardizer.stereo_parent#10246", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "molvs/standardize.py", "symbol": "Standardizer.stereo_parent"}, "source_id": "csn:mcs07/MolVS:molvs/standardize.py:Standardizer.stereo_parent#10246"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/mcs07/MolVS/blob/d815fe52d160abcecbcbf117e6437bf727dbd8ad/molvs/standardize.py#L133-L149", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:mcs07-MolVS:Standardizer.stereo_parent-77330d5d2b", "question": "Return the stereo parent of a given molecule.\n\n The stereo parent has all stereochemistry information removed from tetrahedral centers and double bonds.\n\n :param mol: The input molecule.\n :type mol: rdkit.Chem.rdchem.Mol\n :param bool skip_standardize: Set to True if mol has already been standardized.\n :returns: The stereo parent molecule.\n :rtype: rdkit.Chem.rdchem.Mol", "scope": {"holder": "mcs07-MolVS", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:mdgoldberg/sportsref:sportsref/nba/boxscores.py:BoxScore._get_player_stats#17557", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "sportsref/nba/boxscores.py", "symbol": "BoxScore._get_player_stats"}, "source_id": "csn:mdgoldberg/sportsref:sportsref/nba/boxscores.py:BoxScore._get_player_stats#17557"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/mdgoldberg/sportsref/blob/09f11ac856a23c96d666d1d510bb35d6f050b5c3/sportsref/nba/boxscores.py#L138-L165", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:mdgoldberg-sportsref:BoxScore._get_player_stats-eee83f7bdb", "question": "Returns a DataFrame of player stats from the game (either basic or\n advanced, depending on the argument.\n\n :param table_id_fmt: Format string for str.format with a placeholder\n for the team ID (e.g. 'box_{}_basic')\n :returns: DataFrame of player stats", "scope": {"holder": "mdgoldberg-sportsref", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:mdgoldberg/sportsref:sportsref/nba/seasons.py:Season.schedule#17550", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "sportsref/nba/seasons.py", "symbol": "Season.schedule"}, "source_id": "csn:mdgoldberg/sportsref:sportsref/nba/seasons.py:Season.schedule#17550"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/mdgoldberg/sportsref/blob/09f11ac856a23c96d666d1d510bb35d6f050b5c3/sportsref/nba/seasons.py#L99-L142", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:mdgoldberg-sportsref:Season.schedule-11d5cb1905", "question": "Returns a list of BoxScore IDs for every game in the season.\n Only needs to handle 'R' or 'P' options because decorator handles 'B'.\n\n :param kind: 'R' for regular season, 'P' for playoffs, 'B' for both.\n Defaults to 'R'.\n :returns: DataFrame of schedule information.\n :rtype: pd.DataFrame", "scope": {"holder": "mdgoldberg-sportsref", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:memsql/memsql-python:memsql/common/database.py:Connection.execute#8345", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "memsql/common/database.py", "symbol": "Connection.execute"}, "source_id": "csn:memsql/memsql-python:memsql/common/database.py:Connection.execute#8345"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/memsql/memsql-python/blob/aac223a1b937d5b348b42af3c601a6c685ca633a/memsql/common/database.py#L138-L140", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:memsql-memsql-python:Connection.execute-3f268a0e60", "question": "Executes the given query, returning the lastrowid from the query.", "scope": {"holder": "memsql-memsql-python", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:memsql/memsql-python:memsql/common/sql_utility.py:SQLUtility.destroy#8360", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "memsql/common/sql_utility.py", "symbol": "SQLUtility.destroy"}, "source_id": "csn:memsql/memsql-python:memsql/common/sql_utility.py:SQLUtility.destroy#8360"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/memsql/memsql-python/blob/aac223a1b937d5b348b42af3c601a6c685ca633a/memsql/common/sql_utility.py#L34-L39", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:memsql-memsql-python:SQLUtility.destroy-9249cd39fe", "question": "Destroy the SQLStepQueue tables in the database", "scope": {"holder": "memsql-memsql-python", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:mental32/spotify.py:spotify/models/album.py:Album.get_all_tracks#6790", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "spotify/models/album.py", "symbol": "Album.get_all_tracks"}, "source_id": "csn:mental32/spotify.py:spotify/models/album.py:Album.get_all_tracks#6790"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/mental32/spotify.py/blob/bb296cac7c3dd289908906b7069bd80f43950515/spotify/models/album.py#L91-L120", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:mental32-spotify.py:Album.get_all_tracks-41271ac9ce", "question": "loads all of the albums tracks, depending on how many the album has this may be a long operation.\n\n Parameters\n ----------\n market : Optional[str]\n An ISO 3166-1 alpha-2 country code. Provide this parameter if you want to apply Track Relinking.\n \n Returns\n -------\n tracks : List[Track]\n The tracks of the artist.", "scope": {"holder": "mental32-spotify.py", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:mental32/spotify.py:spotify/models/library.py:Library.contains_albums#6799", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "spotify/models/library.py", "symbol": "Library.contains_albums"}, "source_id": "csn:mental32/spotify.py:spotify/models/library.py:Library.contains_albums#6799"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/mental32/spotify.py/blob/bb296cac7c3dd289908906b7069bd80f43950515/spotify/models/library.py#L29-L38", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:mental32-spotify.py:Library.contains_albums-eb195d250b", "question": "Check if one or more albums is already saved in the current Spotify user’s ‘Your Music’ library.\n\n Parameters\n ----------\n albums : Union[Album, str]\n A sequence of artist objects or spotify IDs", "scope": {"holder": "mental32-spotify.py", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:merrychap/shellen:shellen/asms/asm.py:Assembler.avail_archs#8720", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "shellen/asms/asm.py", "symbol": "Assembler.avail_archs"}, "source_id": "csn:merrychap/shellen:shellen/asms/asm.py:Assembler.avail_archs#8720"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/merrychap/shellen/blob/3514b7ed3a1b7b1660c3f846a52f58ef02f0954c/shellen/asms/asm.py#L24-L42", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:merrychap-shellen:Assembler.avail_archs-69dcf55ad5", "question": "Initialize the dictionary of architectures for assembling via keystone", "scope": {"holder": "merrychap-shellen", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:merrychap/shellen:shellen/asms/disasm.py:Disassembler.avail_archs#8721", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "shellen/asms/disasm.py", "symbol": "Disassembler.avail_archs"}, "source_id": "csn:merrychap/shellen:shellen/asms/disasm.py:Disassembler.avail_archs#8721"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/merrychap/shellen/blob/3514b7ed3a1b7b1660c3f846a52f58ef02f0954c/shellen/asms/disasm.py#L25-L40", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:merrychap-shellen:Disassembler.avail_archs-fed3c34cdd", "question": "Initialize the dictionary of architectures for disassembling via capstone", "scope": {"holder": "merrychap-shellen", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:mesos-magellan/pyrallelsa:pyrallelsa/examples/tsp/__init__.py:TSPProblem.divide#20322", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pyrallelsa/examples/tsp/__init__.py", "symbol": "TSPProblem.divide"}, "source_id": "csn:mesos-magellan/pyrallelsa:pyrallelsa/examples/tsp/__init__.py:TSPProblem.divide#20322"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/mesos-magellan/pyrallelsa/blob/bbdeefd0c7ea4fd9a2e29624bf1b21e3da039cb1/pyrallelsa/examples/tsp/__init__.py#L109-L136", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:mesos-magellan-pyrallelsa:TSPProblem.divide-f5a4e77645", "question": "divide\n\n :type problem_data: dict", "scope": {"holder": "mesos-magellan-pyrallelsa", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:mesos-magellan/pyrallelsa:pyrallelsa/examples/tsp/__init__.py:TSPProblem.energy#20321", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pyrallelsa/examples/tsp/__init__.py", "symbol": "TSPProblem.energy"}, "source_id": "csn:mesos-magellan/pyrallelsa:pyrallelsa/examples/tsp/__init__.py:TSPProblem.energy#20321"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/mesos-magellan/pyrallelsa/blob/bbdeefd0c7ea4fd9a2e29624bf1b21e3da039cb1/pyrallelsa/examples/tsp/__init__.py#L95-L106", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:mesos-magellan-pyrallelsa:TSPProblem.energy-4ec2e94460", "question": "Calculates the length of the route.", "scope": {"holder": "mesos-magellan-pyrallelsa", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:mezuro/kalibro_client_py:kalibro_client/base.py:entity_name_decorator#19546", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "kalibro_client/base.py", "symbol": "entity_name_decorator"}, "source_id": "csn:mezuro/kalibro_client_py:kalibro_client/base.py:entity_name_decorator#19546"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/mezuro/kalibro_client_py/blob/841881acadf2ff8c06444f0bc34d541c0772edc0/kalibro_client/base.py#L139-L158", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:mezuro-kalibro_client_py:entity_name_decorator-de71d331c3", "question": "Assign an entity name based on the class immediately inhering from Base.\n\n This is needed because we don't want\n entity names to come from any class that simply inherits our classes,\n just the ones in our module.\n\n For example, if you create a class Project2 that exists outside of\n kalibro_client and inherits from Project, it's entity name should still\n be Project.", "scope": {"holder": "mezuro-kalibro_client_py", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:mfcovington/django-project-home-templatetags:project_home_tags/templatetags/project_home.py:home_url#19430", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "project_home_tags/templatetags/project_home.py", "symbol": "home_url"}, "source_id": "csn:mfcovington/django-project-home-templatetags:project_home_tags/templatetags/project_home.py:home_url#19430"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/mfcovington/django-project-home-templatetags/blob/abc660906086088792c5e5e7be6ecd151c2ccddb/project_home_tags/templatetags/project_home.py#L20-L36", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:mfcovington-django-project-home-templatetags:home_url-cddb12f545", "question": "Get project's home URL based on settings.PROJECT_HOME_NAMESPACE.\n\n Returns None if PROJECT_HOME_NAMESPACE is not defined in settings.", "scope": {"holder": "mfcovington-django-project-home-templatetags", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:mfcovington/django-project-home-templatetags:project_home_tags/templatetags/project_home.py:project_home_breadcrumb_bs4#19433", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "project_home_tags/templatetags/project_home.py", "symbol": "project_home_breadcrumb_bs4"}, "source_id": "csn:mfcovington/django-project-home-templatetags:project_home_tags/templatetags/project_home.py:project_home_breadcrumb_bs4#19433"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/mfcovington/django-project-home-templatetags/blob/abc660906086088792c5e5e7be6ecd151c2ccddb/project_home_tags/templatetags/project_home.py#L127-L166", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:mfcovington-django-project-home-templatetags:project_home_breadcrumb_bs4-94ddb779cb", "question": "A template tag to return the project's home URL and label\n formatted as a Bootstrap 4 breadcrumb.\n\n PROJECT_HOME_NAMESPACE must be defined in settings, for example:\n PROJECT_HOME_NAMESPACE = 'project_name:index_view'\n\n Usage Example:\n {% load project_home_tags %}\n\n <ol class=\"breadcrumb\">\n {% project_home_breadcrumb_bs4 %} {# <--- #}\n <li class=\"breadcrumb-item\" aria-label=\"breadcrumb\"><a href=\"{% url 'app:namespace' %}\">List of Objects</a></li>\n <li class=\" breadcrumb-item active\" aria-label=\"breadcrumb\" aria-current=\"page\">Object Detail</li>\n </ol>\n\n This gets converted into:\n <ol class=\"breadcrumb\">\n <li class=\"breadcrumb-item\" aria-label=\"breadcrumb\"><a href=\"{% url 'project_name:index_view' %}\">Home</a></li> {# <--- #}\n <li class=\"breadcrumb-item\" aria-label=\"breadcrumb\"><a href=\"{% url 'app:namespace' %}\">List of Objects</a></li>\n <li class=\" breadcrumb-item active\" aria-label=\"breadcrumb\" aria-current=\"page\">Object Detail</li>\n </ol>\n\n By default, the link's text is 'Home'. A project-wide label can be\n defined with PROJECT_HOME_LABEL in settings. Both the default and\n the project-wide label can be overridden by passing a string to\n the template tag.\n\n For example:\n {% project_home_breadcrumb_bs4 'Custom Label' %}", "scope": {"holder": "mfcovington-django-project-home-templatetags", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:mikewaters/command-session:commandsession/commandsession.py:CommandSession.check_call#20504", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "commandsession/commandsession.py", "symbol": "CommandSession.check_call"}, "source_id": "csn:mikewaters/command-session:commandsession/commandsession.py:CommandSession.check_call#20504"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/mikewaters/command-session/blob/cea0d81a56551530f52f1cf3780c0ac408e069ef/commandsession/commandsession.py#L156-L162", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:mikewaters-command-session:CommandSession.check_call-dfb1e8a15e", "question": "Fake the interface of subprocess.call().", "scope": {"holder": "mikewaters-command-session", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:mikewaters/command-session:commandsession/commandsession.py:CommandSession.last_error#20502", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "commandsession/commandsession.py", "symbol": "CommandSession.last_error"}, "source_id": "csn:mikewaters/command-session:commandsession/commandsession.py:CommandSession.last_error#20502"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/mikewaters/command-session/blob/cea0d81a56551530f52f1cf3780c0ac408e069ef/commandsession/commandsession.py#L87-L99", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:mikewaters-command-session:CommandSession.last_error-17943a04b3", "question": "Get the output of the last command exevuted.", "scope": {"holder": "mikewaters-command-session", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:mjtamlyn/django-cbvpatterns:cbvpatterns.py:patterns#20573", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "cbvpatterns.py", "symbol": "patterns"}, "source_id": "csn:mjtamlyn/django-cbvpatterns:cbvpatterns.py:patterns#20573"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/mjtamlyn/django-cbvpatterns/blob/cff213bc1e6a92c68bf519db19452f99ec07c159/cbvpatterns.py#L30-L39", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:mjtamlyn-django-cbvpatterns:patterns-dd08357f2a", "question": "As patterns() in django.", "scope": {"holder": "mjtamlyn-django-cbvpatterns", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:mjtamlyn/django-cbvpatterns:cbvpatterns.py:url#20574", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "cbvpatterns.py", "symbol": "url"}, "source_id": "csn:mjtamlyn/django-cbvpatterns:cbvpatterns.py:url#20574"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/mjtamlyn/django-cbvpatterns/blob/cff213bc1e6a92c68bf519db19452f99ec07c159/cbvpatterns.py#L42-L55", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:mjtamlyn-django-cbvpatterns:url-0cbaa49243", "question": "As url() in Django.", "scope": {"holder": "mjtamlyn-django-cbvpatterns", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:mk-fg/python-onedrive:onedrive/api_v5.py:OneDriveAPI.copy#13784", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "onedrive/api_v5.py", "symbol": "OneDriveAPI.copy"}, "source_id": "csn:mk-fg/python-onedrive:onedrive/api_v5.py:OneDriveAPI.copy#13784"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/mk-fg/python-onedrive/blob/74d3f6605b0e8a9031a2aab8092f551293ffb533/onedrive/api_v5.py#L697-L704", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:mk-fg-python-onedrive:OneDriveAPI.copy-ed100d2866", "question": "Copy specified file (object) to a folder.\n\t\t\tNote that folders cannot be copied, this is an API limitation.", "scope": {"holder": "mk-fg-python-onedrive", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:mk-fg/python-onedrive:onedrive/api_v5.py:OneDriveAPIWrapper.link#13778", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "onedrive/api_v5.py", "symbol": "OneDriveAPIWrapper.link"}, "source_id": "csn:mk-fg/python-onedrive:onedrive/api_v5.py:OneDriveAPIWrapper.link#13778"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/mk-fg/python-onedrive/blob/74d3f6605b0e8a9031a2aab8092f551293ffb533/onedrive/api_v5.py#L610-L616", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:mk-fg-python-onedrive:OneDriveAPIWrapper.link-11a086dbb9", "question": "Return a preauthenticated (usable by anyone) link to a\n\t\t\t\tspecified object. Object will be considered \"shared\" by OneDrive,\n\t\t\t\teven if link is never actually used.\n\t\t\tlink_type can be either \"embed\" (returns html), \"shared_read_link\" or \"shared_edit_link\".", "scope": {"holder": "mk-fg-python-onedrive", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:mohabusama/pyguacamole:guacamole/client.py:GuacamoleClient.client#11015", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "guacamole/client.py", "symbol": "GuacamoleClient.client"}, "source_id": "csn:mohabusama/pyguacamole:guacamole/client.py:GuacamoleClient.client#11015"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/mohabusama/pyguacamole/blob/344dccc6cb3a9a045afeaf337677e5d0001aa83a/guacamole/client.py#L65-L75", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:mohabusama-pyguacamole:GuacamoleClient.client-86c3929fe3", "question": "Socket connection.", "scope": {"holder": "mohabusama-pyguacamole", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:mohabusama/pyguacamole:guacamole/client.py:GuacamoleClient.send#11018", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "guacamole/client.py", "symbol": "GuacamoleClient.send"}, "source_id": "csn:mohabusama/pyguacamole:guacamole/client.py:GuacamoleClient.send#11018"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/mohabusama/pyguacamole/blob/344dccc6cb3a9a045afeaf337677e5d0001aa83a/guacamole/client.py#L117-L122", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:mohabusama-pyguacamole:GuacamoleClient.send-c201f6cba9", "question": "Send encoded instructions to Guacamole guacd server.", "scope": {"holder": "mohabusama-pyguacamole", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:mohan3d/PyOpenload:openload/openload.py:OpenLoad._check_status#16811", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "openload/openload.py", "symbol": "OpenLoad._check_status"}, "source_id": "csn:mohan3d/PyOpenload:openload/openload.py:OpenLoad._check_status#16811"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/mohan3d/PyOpenload/blob/7f9353915ca5546926ef07be9395c6de60e761b1/openload/openload.py#L31-L55", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:mohan3d-PyOpenload:OpenLoad._check_status-00a49ed445", "question": "Check the status of the incoming response, raise exception if status is not 200.\n\n Args:\n response_json (dict): results of the response of the GET request.\n\n Returns:\n None", "scope": {"holder": "mohan3d-PyOpenload", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:mohan3d/PyOpenload:openload/openload.py:OpenLoad.remote_upload_status#16817", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "openload/openload.py", "symbol": "OpenLoad.remote_upload_status"}, "source_id": "csn:mohan3d/PyOpenload:openload/openload.py:OpenLoad.remote_upload_status#16817"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/mohan3d/PyOpenload/blob/7f9353915ca5546926ef07be9395c6de60e761b1/openload/openload.py#L290-L331", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:mohan3d-PyOpenload:OpenLoad.remote_upload_status-0aa4c708f0", "question": "Checks a remote file upload to status.\n\n Args:\n limit (:obj:`int`, optional): Maximum number of results (Default: 5, Maximum: 100).\n remote_upload_id (:obj:`str`, optional): Remote Upload ID.\n\n Returns:\n dict: dictionary containing all remote uploads, each dictionary element is a dictionary. ::\n\n {\n \"24\": {\n \"id\": \"24\",\n \"remoteurl\": \"http://proof.ovh.net/files/100Mio.dat\",\n \"status\": \"new\",\n \"folderid\": \"4248\",\n \"added\": \"2015-02-21 09:20:26\",\n \"last_update\": \"2015-02-21 09:20:26\",\n \"extid\": False,\n \"url\": False\n },\n \"22\": {\n \"id\": \"22\",\n \"remoteurl\": \"http://proof.ovh.net/files/1Gio.dat\",\n \"status\": \"downloading\",\n \"bytes_loaded\": \"823997062\",\n \"bytes_total\": \"1073741824\",\n \"folderid\": \"4248\",\n \"added\": \"2015-02-21 09:20:26\",\n \"last_update\": \"2015-02-21 09:21:56\",\n \"extid\": False,\n \"url\": False\n },\n ...\n }", "scope": {"holder": "mohan3d-PyOpenload", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:mopidy/mopidy-spotify:mopidy_spotify/web.py:OAuthClient._parse_retry_after#4728", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "mopidy_spotify/web.py", "symbol": "OAuthClient._parse_retry_after"}, "source_id": "csn:mopidy/mopidy-spotify:mopidy_spotify/web.py:OAuthClient._parse_retry_after#4728"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/mopidy/mopidy-spotify/blob/77a293088e63a7b4b77bf9409ce57cb14048d18c/mopidy_spotify/web.py#L196-L210", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:mopidy-mopidy-spotify:OAuthClient._parse_retry_after-a01b8f93f2", "question": "Parse Retry-After header from response if it is set.", "scope": {"holder": "mopidy-mopidy-spotify", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:mopidy/mopidy-spotify:mopidy_spotify/translator.py:sp_search_query#4727", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "mopidy_spotify/translator.py", "symbol": "sp_search_query"}, "source_id": "csn:mopidy/mopidy-spotify:mopidy_spotify/translator.py:sp_search_query#4727"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/mopidy/mopidy-spotify/blob/77a293088e63a7b4b77bf9409ce57cb14048d18c/mopidy_spotify/translator.py#L205-L225", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:mopidy-mopidy-spotify:sp_search_query-fa8af26951", "question": "Translate a Mopidy search query to a Spotify search query", "scope": {"holder": "mopidy-mopidy-spotify", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:mordred-descriptor/mordred:mordred/_base/calculator.py:Calculator.echo#5286", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "mordred/_base/calculator.py", "symbol": "Calculator.echo"}, "source_id": "csn:mordred-descriptor/mordred:mordred/_base/calculator.py:Calculator.echo#5286"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/mordred-descriptor/mordred/blob/2848b088fd7b6735590242b5e22573babc724f10/mordred/_base/calculator.py#L314-L331", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:mordred-descriptor-mordred:Calculator.echo-ad35b73d54", "question": "Output message.\n\n Parameters:\n s(str): message to output\n file(file-like): output to\n end(str): end mark of message\n\n Return:\n None", "scope": {"holder": "mordred-descriptor-mordred", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:mordred-descriptor/mordred:mordred/_base/result.py:Result.fill_missing#5297", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "mordred/_base/result.py", "symbol": "Result.fill_missing"}, "source_id": "csn:mordred-descriptor/mordred:mordred/_base/result.py:Result.fill_missing#5297"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/mordred-descriptor/mordred/blob/2848b088fd7b6735590242b5e22573babc724f10/mordred/_base/result.py#L33-L47", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:mordred-descriptor-mordred:Result.fill_missing-79de02ea8a", "question": "r\"\"\"Replace missing value to \"value\".\n\n Parameters:\n value: value that missing value is replaced\n\n Returns:\n Result", "scope": {"holder": "mordred-descriptor-mordred", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:moreati/ppeg:pe.py:mult#19001", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pe.py", "symbol": "mult"}, "source_id": "csn:moreati/ppeg:pe.py:mult#19001"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/moreati/ppeg/blob/946b1f75873eb52fa974606d85f576bfa0df9666/pe.py#L25-L34", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:moreati-ppeg:mult-96a9950f2e", "question": "Returns a Pattern that matches exactly n repetitions of Pattern p.", "scope": {"holder": "moreati-ppeg", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:mozilla-iot/webthing-python:webthing/action.py:Action.as_action_description#4748", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "webthing/action.py", "symbol": "Action.as_action_description"}, "source_id": "csn:mozilla-iot/webthing-python:webthing/action.py:Action.as_action_description#4748"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/mozilla-iot/webthing-python/blob/65d467c89ed79d0bbc42b8b3c8f9e5a320edd237/webthing/action.py#L28-L48", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:mozilla-iot-webthing-python:Action.as_action_description-19a4789bf6", "question": "Get the action description.\n\n Returns a dictionary describing the action.", "scope": {"holder": "mozilla-iot-webthing-python", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:mozilla-iot/webthing-python:webthing/thing.py:Thing.event_notify#4777", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "webthing/thing.py", "symbol": "Thing.event_notify"}, "source_id": "csn:mozilla-iot/webthing-python:webthing/thing.py:Thing.event_notify#4777"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/mozilla-iot/webthing-python/blob/65d467c89ed79d0bbc42b8b3c8f9e5a320edd237/webthing/thing.py#L459-L477", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:mozilla-iot-webthing-python:Thing.event_notify-2bdedc2313", "question": "Notify all subscribers of an event.\n\n event -- the event that occurred", "scope": {"holder": "mozilla-iot-webthing-python", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:mozilla-services/sign-xpi-lib:sign_xpi_lib/sign_xpi_lib.py:ignore_certain_metainf_files#16632", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "sign_xpi_lib/sign_xpi_lib.py", "symbol": "ignore_certain_metainf_files"}, "source_id": "csn:mozilla-services/sign-xpi-lib:sign_xpi_lib/sign_xpi_lib.py:ignore_certain_metainf_files#16632"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/mozilla-services/sign-xpi-lib/blob/bc6860b555fd26de9204f8d17289903e4fb9f106/sign_xpi_lib/sign_xpi_lib.py#L25-L43", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:mozilla-services-sign-xpi-lib:ignore_certain_metainf_files-32300d9064", "question": "We do not support multiple signatures in XPI signing because the client\n side code makes some pretty reasonable assumptions about a single signature\n on any given JAR. This function returns True if the file name given is one\n that we dispose of to prevent multiple signatures.", "scope": {"holder": "mozilla-services-sign-xpi-lib", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:mpenning/polymer:polymer/Polymer.py:TaskMgrStats.log_message#15458", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "polymer/Polymer.py", "symbol": "TaskMgrStats.log_message"}, "source_id": "csn:mpenning/polymer:polymer/Polymer.py:TaskMgrStats.log_message#15458"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/mpenning/polymer/blob/1cdf4ed2573c894bde9d398fa173816b6b47e9f3/polymer/Polymer.py#L275-L306", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:mpenning-polymer:TaskMgrStats.log_message-f2400a97c7", "question": "Build a log message and reset the stats", "scope": {"holder": "mpenning-polymer", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:mpenning/polymer:polymer/Polymer.py:Worker.invalid_dict_pickle_keys#15455", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "polymer/Polymer.py", "symbol": "Worker.invalid_dict_pickle_keys"}, "source_id": "csn:mpenning/polymer:polymer/Polymer.py:Worker.invalid_dict_pickle_keys#15455"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/mpenning/polymer/blob/1cdf4ed2573c894bde9d398fa173816b6b47e9f3/polymer/Polymer.py#L163-L180", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:mpenning-polymer:Worker.invalid_dict_pickle_keys-cf5435d426", "question": "Return a list of keys that can't be pickled. Return [] if \n there are no pickling problems with the values associated with the\n keys. Return the list of keys, if there are problems.", "scope": {"holder": "mpenning-polymer", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:mrsarm/mongotail:mongotail/conn.py:connect#9098", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "mongotail/conn.py", "symbol": "connect"}, "source_id": "csn:mrsarm/mongotail:mongotail/conn.py:connect#9098"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/mrsarm/mongotail/blob/82ba74e32eff92faa320833a8d19c58555f9cd49/mongotail/conn.py#L31-L78", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:mrsarm-mongotail:connect-35dc7e06f5", "question": "Connect with `address`, and return a tuple with a :class:`~pymongo.MongoClient`,\n and a :class:`~pymongo.database.Database` object.\n :param address: a string representation with the db address\n :param args: connection arguments:\n - username: username for authentication (optional)\n - password: password for authentication. If username is given and password isn't,\n it's asked from tty.\n - auth_database: authenticate the username and password against that database (optional).\n If not specified, the database specified in address will be used.\n - ssl, ssl_certfile, ssl_keyfile, ssl_cert_reqs, ssl_ca_certs: SSL authentication options\n :return: a tuple with ``(client, db)``", "scope": {"holder": "mrsarm-mongotail", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:mrsarm/mongotail:mongotail/err.py:error_parsing#9100", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "mongotail/err.py", "symbol": "error_parsing"}, "source_id": "csn:mrsarm/mongotail:mongotail/err.py:error_parsing#9100"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/mrsarm/mongotail/blob/82ba74e32eff92faa320833a8d19c58555f9cd49/mongotail/err.py#L42-L48", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:mrsarm-mongotail:error_parsing-62a669a7ea", "question": "Print any parsing error and exit with status -1", "scope": {"holder": "mrsarm-mongotail", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:mrtazz/notifo.py:notifo/notifo.py:Notifo._query#20790", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "notifo/notifo.py", "symbol": "Notifo._query"}, "source_id": "csn:mrtazz/notifo.py:notifo/notifo.py:Notifo._query#20790"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/mrtazz/notifo.py/blob/26079db3b40c26661155af20a9f16a0eca06dbde/notifo/notifo.py#L74-L102", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:mrtazz-notifo.py:Notifo._query-bf5fa72120", "question": "query method to do HTTP POST/GET\n\n Parameters:\n url -> the url to POST/GET\n data -> header_data as a dict (only for POST)\n\n Returns:\n Parsed JSON data as dict\n or\n None on error", "scope": {"holder": "mrtazz-notifo.py", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:mrtazz/notifo.py:notifo/notifo.py:Notifo.send_notification#20788", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "notifo/notifo.py", "symbol": "Notifo.send_notification"}, "source_id": "csn:mrtazz/notifo.py:notifo/notifo.py:Notifo.send_notification#20788"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/mrtazz/notifo.py/blob/26079db3b40c26661155af20a9f16a0eca06dbde/notifo/notifo.py#L33-L56", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:mrtazz-notifo.py:Notifo.send_notification-3a12ee0a48", "question": "method to send a message to a user\n\n Parameters:\n to -> recipient\n msg -> message to send\n label -> application description\n title -> name of the notification event\n uri -> callback uri", "scope": {"holder": "mrtazz-notifo.py", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:mseclab/PyJFuzz:gramfuzz/gramfuzz/fields.py:And.build#7785", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "gramfuzz/gramfuzz/fields.py", "symbol": "And.build"}, "source_id": "csn:mseclab/PyJFuzz:gramfuzz/gramfuzz/fields.py:And.build#7785"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/mseclab/PyJFuzz/blob/f777067076f62c9ab74ffea6e90fd54402b7a1b4/gramfuzz/gramfuzz/fields.py#L432-L460", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:mseclab-PyJFuzz:And.build-31192ed026", "question": "Build the ``And`` instance\n\n :param list pre: The prerequisites list\n :param bool shortest: Whether or not the shortest reference-chain (most minimal) version of the field should be generated.", "scope": {"holder": "mseclab-PyJFuzz", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:mseclab/PyJFuzz:pyjfuzz/core/pjf_factory.py:PJFFactory.fuzz_elements#7804", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pyjfuzz/core/pjf_factory.py", "symbol": "PJFFactory.fuzz_elements"}, "source_id": "csn:mseclab/PyJFuzz:pyjfuzz/core/pjf_factory.py:PJFFactory.fuzz_elements#7804"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/mseclab/PyJFuzz/blob/f777067076f62c9ab74ffea6e90fd54402b7a1b4/pyjfuzz/core/pjf_factory.py#L129-L171", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:mseclab-PyJFuzz:PJFFactory.fuzz_elements-69ec0c4b80", "question": "Fuzz all elements inside the object", "scope": {"holder": "mseclab-PyJFuzz", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:mshroyer/pointfree:pointfree.py:partial.__new_argv#16631", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pointfree.py", "symbol": "partial.__new_argv"}, "source_id": "csn:mshroyer/pointfree:pointfree.py:partial.__new_argv#16631"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/mshroyer/pointfree/blob/a25ecb3f0cd583e0730ecdde83018e5089711854/pointfree.py#L433-L464", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:mshroyer-pointfree:partial.__new_argv-03bf9c4cda", "question": "Calculate new argv and extra_argv values resulting from adding\n the specified positional and keyword arguments.", "scope": {"holder": "mshroyer-pointfree", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:mshroyer/pointfree:pointfree.py:pfcollect#16625", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pointfree.py", "symbol": "pfcollect"}, "source_id": "csn:mshroyer/pointfree:pointfree.py:pfcollect#16625"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/mshroyer/pointfree/blob/a25ecb3f0cd583e0730ecdde83018e5089711854/pointfree.py#L649-L675", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:mshroyer-pointfree:pfcollect-0e72fe5d1e", "question": "Collects and returns a list of values from the given iterable. If\n the n parameter is not specified, collects all values from the\n iterable.\n\n :param iterable: An iterable yielding values for the list\n :param n: An optional maximum number of items to collect\n :rtype: List of values from the iterable\n\n Example::\n\n >>> @pointfree\n ... def fibonaccis():\n ... a, b = 0, 1\n ... while True:\n ... a, b = b, a+b\n ... yield a\n\n >>> (pfcollect(n=10) * fibonaccis)()\n [1, 1, 2, 3, 5, 8, 13, 21, 34, 55]", "scope": {"holder": "mshroyer-pointfree", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:mwarkentin/django-watchman:watchman/decorators.py:check#6603", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "watchman/decorators.py", "symbol": "check"}, "source_id": "csn:mwarkentin/django-watchman:watchman/decorators.py:check#6603"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/mwarkentin/django-watchman/blob/6ef98ba54dc52f27e7b42d42028b59dc67550268/watchman/decorators.py#L14-L54", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:mwarkentin-django-watchman:check-c729f72797", "question": "Decorator which wraps checks and returns an error response on failure.", "scope": {"holder": "mwarkentin-django-watchman", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:mwarkentin/django-watchman:watchman/decorators.py:token_required#6604", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "watchman/decorators.py", "symbol": "token_required"}, "source_id": "csn:mwarkentin/django-watchman:watchman/decorators.py:token_required#6604"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/mwarkentin/django-watchman/blob/6ef98ba54dc52f27e7b42d42028b59dc67550268/watchman/decorators.py#L57-L111", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:mwarkentin-django-watchman:token_required-fad1851003", "question": "Decorator which ensures that one of the WATCHMAN_TOKENS is provided if set.\n\n WATCHMAN_TOKEN_NAME can also be set if the token GET parameter must be\n customized.", "scope": {"holder": "mwarkentin-django-watchman", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:mwhooker/jsonselect:jsonselect/jsonselect.py:Parser._match_nodes#15359", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "jsonselect/jsonselect.py", "symbol": "Parser._match_nodes"}, "source_id": "csn:mwhooker/jsonselect:jsonselect/jsonselect.py:Parser._match_nodes#15359"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/mwhooker/jsonselect/blob/c64aa9ea930de0344797ff87b04c753c8fc096a6/jsonselect/jsonselect.py#L432-L442", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:mwhooker-jsonselect:Parser._match_nodes-02a490ed3c", "question": "Apply each validator in validators to each node in obj.\n\n Return each node in obj which matches all validators.", "scope": {"holder": "mwhooker-jsonselect", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:mwhooker/jsonselect:jsonselect/jsonselect.py:Parser.parse#15353", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "jsonselect/jsonselect.py", "symbol": "Parser.parse"}, "source_id": "csn:mwhooker/jsonselect:jsonselect/jsonselect.py:Parser.parse#15353"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/mwhooker/jsonselect/blob/c64aa9ea930de0344797ff87b04c753c8fc096a6/jsonselect/jsonselect.py#L153-L170", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:mwhooker-jsonselect:Parser.parse-b3bb94c7c5", "question": "Accept a list of tokens. Returns matched nodes of self.obj.", "scope": {"holder": "mwhooker-jsonselect", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:myint/autoflake:autoflake.py:_detect_encoding#7019", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "autoflake.py", "symbol": "_detect_encoding"}, "source_id": "csn:myint/autoflake:autoflake.py:_detect_encoding#7019"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/myint/autoflake/blob/68fea68646922b920d55975f9f2adaeafd84df4f/autoflake.py#L696-L703", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:myint-autoflake:_detect_encoding-2a80d7f588", "question": "Return file encoding.", "scope": {"holder": "myint-autoflake", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:myint/autoflake:autoflake.py:fix_code#7016", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "autoflake.py", "symbol": "fix_code"}, "source_id": "csn:myint/autoflake:autoflake.py:fix_code#7016"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/myint/autoflake/blob/68fea68646922b920d55975f9f2adaeafd84df4f/autoflake.py#L595-L624", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:myint-autoflake:fix_code-0e31f9661e", "question": "Return code with all filtering run on it.", "scope": {"holder": "myint-autoflake", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:napalm-automation/napalm-yang:interactive_demo/ansible/callback/selective.py:CallbackModule.v2_playbook_on_stats#14054", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "interactive_demo/ansible/callback/selective.py", "symbol": "CallbackModule.v2_playbook_on_stats"}, "source_id": "csn:napalm-automation/napalm-yang:interactive_demo/ansible/callback/selective.py:CallbackModule.v2_playbook_on_stats#14054"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/napalm-automation/napalm-yang/blob/998e8a933171d010b8544bcc5dc448e2b68051e2/interactive_demo/ansible/callback/selective.py#L242-L262", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:napalm-automation-napalm-yang:CallbackModule.v2_playbook_on_stats-1774d7251e", "question": "Display info about playbook statistics.", "scope": {"holder": "napalm-automation-napalm-yang", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:napalm-automation/napalm-yang:napalm_yang/parsers/xml_deprecated.py:XMLParser._parse_list_nested_recursive#14068", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "napalm_yang/parsers/xml_deprecated.py", "symbol": "XMLParser._parse_list_nested_recursive"}, "source_id": "csn:napalm-automation/napalm-yang:napalm_yang/parsers/xml_deprecated.py:XMLParser._parse_list_nested_recursive#14068"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/napalm-automation/napalm-yang/blob/998e8a933171d010b8544bcc5dc448e2b68051e2/napalm_yang/parsers/xml_deprecated.py#L41-L91", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:napalm-automation-napalm-yang:XMLParser._parse_list_nested_recursive-8d1e0b2025", "question": "This helps parsing shit like:\n\n <protocols>\n <bgp>\n <group>\n <name>my_peers</name>\n <neighbor>\n <name>192.168.100.2</name>\n <description>adsasd</description>\n <peer-as>65100</peer-as>\n </neighbor>\n <neighbor>\n <name>192.168.100.3</name>\n <peer-as>65100</peer-as>\n </neighbor>\n </group>\n <group>\n <name>my_other_peers</name>\n <neighbor>\n <name>172.20.0.1</name>\n <peer-as>65200</peer-as>\n </neighbor>\n </group>\n </bgp>\n </protocols>", "scope": {"holder": "napalm-automation-napalm-yang", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:nathforge/validatesns:src/validatesns/__init__.py:validate#12905", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "src/validatesns/__init__.py", "symbol": "validate"}, "source_id": "csn:nathforge/validatesns:src/validatesns/__init__.py:validate#12905"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/nathforge/validatesns/blob/39f7f7d1fae215746bb9763856045b501fae05f4/src/validatesns/__init__.py#L28-L69", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:nathforge-validatesns:validate-b9365fcf3c", "question": "Validate a decoded SNS message.\n\n Parameters:\n message:\n Decoded SNS message.\n\n get_certificate:\n Function that receives a URL, and returns the certificate from that\n URL as a string. The default doesn't implement caching.\n\n certificate_url_regex:\n Regex that validates the signing certificate URL. Default value\n checks it's hosted on an AWS-controlled domain, in the format\n \"https://sns.<data-center>.amazonaws.com/\"\n\n max_age:\n Maximum age of an SNS message before it fails validation, expressed\n as a `datetime.timedelta`. Defaults to one hour, the max. lifetime\n of an SNS message.", "scope": {"holder": "nathforge-validatesns", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:nats-io/asyncio-nats:nats/aio/client.py:Client._connect_command#6657", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "nats/aio/client.py", "symbol": "Client._connect_command"}, "source_id": "csn:nats-io/asyncio-nats:nats/aio/client.py:Client._connect_command#6657"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/nats-io/asyncio-nats/blob/39e840be0b12ce326edac0bba69aeb1be930dcb8/nats/aio/client.py#L1111-L1146", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:nats-io-asyncio-nats:Client._connect_command-b09dff5732", "question": "Generates a JSON string with the params to be used\n when sending CONNECT to the server.\n\n ->> CONNECT {\"lang\": \"python3\"}", "scope": {"holder": "nats-io-asyncio-nats", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:nats-io/asyncio-nats:nats/aio/client.py:Client._select_next_server#6654", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "nats/aio/client.py", "symbol": "Client._select_next_server"}, "source_id": "csn:nats-io/asyncio-nats:nats/aio/client.py:Client._select_next_server#6654"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/nats-io/asyncio-nats/blob/39e840be0b12ce326edac0bba69aeb1be930dcb8/nats/aio/client.py#L932-L982", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:nats-io-asyncio-nats:Client._select_next_server-5cbc364cb1", "question": "Looks up in the server pool for an available server\n and attempts to connect.", "scope": {"holder": "nats-io-asyncio-nats", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:ncolony/ncolony:ncolony/httpcheck.py:State.check#15296", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "ncolony/httpcheck.py", "symbol": "State.check"}, "source_id": "csn:ncolony/ncolony:ncolony/httpcheck.py:State.check#15296"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/ncolony/ncolony/blob/6ac71bda1de6706fb34244ae4972e36db5f062d3/ncolony/httpcheck.py#L108-L115", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:ncolony-ncolony:State.check-4ef16362dd", "question": "Check the state of HTTP", "scope": {"holder": "ncolony-ncolony", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:ncolony/ncolony:ncolony/service.py:makeService#15258", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "ncolony/service.py", "symbol": "makeService"}, "source_id": "csn:ncolony/ncolony:ncolony/service.py:makeService#15258"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/ncolony/ncolony/blob/6ac71bda1de6706fb34244ae4972e36db5f062d3/ncolony/service.py#L117-L132", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:ncolony-ncolony:makeService-3da05f1fb9", "question": "Return a service based on parsed command-line options\n\n :param opt: dict-like object. Relevant keys are config, messages,\n pid, frequency, threshold, killtime, minrestartdelay\n and maxrestartdelay\n :returns: service, {twisted.application.interfaces.IService}", "scope": {"holder": "ncolony-ncolony", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:ndokter/dsmr_parser:dsmr_parser/clients/protocol.py:DSMRProtocol.connection_lost#8300", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "dsmr_parser/clients/protocol.py", "symbol": "DSMRProtocol.connection_lost"}, "source_id": "csn:ndokter/dsmr_parser:dsmr_parser/clients/protocol.py:DSMRProtocol.connection_lost#8300"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/ndokter/dsmr_parser/blob/c04b0a5add58ce70153eede1a87ca171876b61c7/dsmr_parser/clients/protocol.py#L90-L96", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:ndokter-dsmr_parser:DSMRProtocol.connection_lost-08b2e79ff5", "question": "Stop when connection is lost.", "scope": {"holder": "ndokter-dsmr_parser", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:ndokter/dsmr_parser:dsmr_parser/parsers.py:TelegramParser.parse#8302", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "dsmr_parser/parsers.py", "symbol": "TelegramParser.parse"}, "source_id": "csn:ndokter/dsmr_parser:dsmr_parser/parsers.py:TelegramParser.parse#8302"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/ndokter/dsmr_parser/blob/c04b0a5add58ce70153eede1a87ca171876b61c7/dsmr_parser/parsers.py#L24-L59", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:ndokter-dsmr_parser:TelegramParser.parse-2139ce4f52", "question": "Parse telegram from string to dict.\n\n The telegram str type makes python 2.x integration easier.\n\n :param str telegram_data: full telegram from start ('/') to checksum\n ('!ABCD') including line endings in between the telegram's lines\n :rtype: dict\n :returns: Shortened example:\n {\n ..\n r'\\d-\\d:96\\.1\\.1.+?\\r\\n': <CosemObject>, # EQUIPMENT_IDENTIFIER\n r'\\d-\\d:1\\.8\\.1.+?\\r\\n': <CosemObject>, # ELECTRICITY_USED_TARIFF_1\n r'\\d-\\d:24\\.3\\.0.+?\\r\\n.+?\\r\\n': <MBusObject>, # GAS_METER_READING\n ..\n }\n :raises ParseError:\n :raises InvalidChecksumError:", "scope": {"holder": "ndokter-dsmr_parser", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:ndrlslz/ternya:ternya/config.py:Config.get_config_value#19626", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "ternya/config.py", "symbol": "Config.get_config_value"}, "source_id": "csn:ndrlslz/ternya:ternya/config.py:Config.get_config_value#19626"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/ndrlslz/ternya/blob/c05aec10029e645d63ff04313dbcf2644743481f/ternya/config.py#L69-L82", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:ndrlslz-ternya:Config.get_config_value-408618adbb", "question": "Read customer's config value by section and key.\n\n :param section: config file's section. i.e [default]\n :param key: config file's key under section. i.e packages_scan\n :param return_type: return value type, str | int | bool.", "scope": {"holder": "ndrlslz-ternya", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:ndrlslz/ternya:ternya/annotation.py:glance#19630", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "ternya/annotation.py", "symbol": "glance"}, "source_id": "csn:ndrlslz/ternya:ternya/annotation.py:glance#19630"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/ndrlslz/ternya/blob/c05aec10029e645d63ff04313dbcf2644743481f/ternya/annotation.py#L140-L166", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:ndrlslz-ternya:glance-6ad74de072", "question": "Glance annotation for adding function to process glance notification.\n\n if event_type include wildcard, will put {pattern: function} into process_wildcard dict\n else will put {event_type: function} into process dict\n\n :param arg: event_type of notification", "scope": {"holder": "ndrlslz-ternya", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:neherlab/treetime:treetime/clock_tree.py:ClockTree._ml_t_joint#10994", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "treetime/clock_tree.py", "symbol": "ClockTree._ml_t_joint"}, "source_id": "csn:neherlab/treetime:treetime/clock_tree.py:ClockTree._ml_t_joint#10994"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/neherlab/treetime/blob/f6cdb58d19243a18ffdaa2b2ec71872fa00e65c0/treetime/clock_tree.py#L346-L460", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:neherlab-treetime:ClockTree._ml_t_joint-9e1cb0aed7", "question": "Compute the joint maximum likelihood assignment of the internal nodes positions by\n propagating from the tree leaves towards the root. Given the assignment of parent nodes,\n reconstruct the maximum-likelihood positions of the child nodes by propagating\n from the root to the leaves. The result of this operation is the time_before_present\n value, which is the position of the node, expressed in the units of the\n branch length, and scaled from the present-day. The value is assigned to the\n corresponding attribute of each node of the tree.\n\n Returns\n -------\n\n None\n Every internal node is assigned the probability distribution in form\n of an interpolation object and sends this distribution further towards the\n root.", "scope": {"holder": "neherlab-treetime", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:neherlab/treetime:treetime/treeanc.py:TreeAnc.dict_sequence#10920", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "treetime/treeanc.py", "symbol": "TreeAnc.dict_sequence"}, "source_id": "csn:neherlab/treetime:treetime/treeanc.py:TreeAnc.dict_sequence#10920"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/neherlab/treetime/blob/f6cdb58d19243a18ffdaa2b2ec71872fa00e65c0/treetime/treeanc.py#L1086-L1117", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:neherlab-treetime:TreeAnc.dict_sequence-93ff10aa0a", "question": "For VCF-based TreeAnc objects, we do not want to store the entire\n sequence on every node, as they could be large. Instead, this returns the dict\n of variants & their positions for this sequence. This is used in place of\n :py:meth:`treetime.TreeAnc.expanded_sequence` for VCF-based objects throughout TreeAnc. However, users can still\n call :py:meth:`expanded_sequence` if they require the full sequence.\n\n Parameters\n ----------\n node : PhyloTree.Clade\n Tree node\n\n Returns\n -------\n seq : dict\n dict where keys are the basepair position (numbering from 0) and value is the variant call", "scope": {"holder": "neherlab-treetime", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:neithere/argh:argh/helpers.py:ArghParser.parse_args#8731", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "argh/helpers.py", "symbol": "ArghParser.parse_args"}, "source_id": "csn:neithere/argh:argh/helpers.py:ArghParser.parse_args#8731"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/neithere/argh/blob/dcd3253f2994400a6a58a700c118c53765bc50a4/argh/helpers.py#L57-L64", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:neithere-argh:ArghParser.parse_args-50807256da", "question": "Wrapper for :meth:`argparse.ArgumentParser.parse_args`. If `namespace`\n is not defined, :class:`argh.dispatching.ArghNamespace` is used.\n This is required for functions to be properly used as commands.", "scope": {"holder": "neithere-argh", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:neithere/argh:argh/io.py:dump#8729", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "argh/io.py", "symbol": "dump"}, "source_id": "csn:neithere/argh:argh/io.py:dump#8729"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/neithere/argh/blob/dcd3253f2994400a6a58a700c118c53765bc50a4/argh/io.py#L99-L105", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:neithere-argh:dump-8e37a33b8c", "question": "Writes given line to given output file.\n See :func:`encode_output` for details.", "scope": {"holder": "neithere-argh", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:nens/qgispluginreleaser:qgispluginreleaser/entry_point.py:create_zipfile#20724", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "qgispluginreleaser/entry_point.py", "symbol": "create_zipfile"}, "source_id": "csn:nens/qgispluginreleaser:qgispluginreleaser/entry_point.py:create_zipfile#20724"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/nens/qgispluginreleaser/blob/4826dd33e9152cc4f9c4be3b89e5b10b1a881d7e/qgispluginreleaser/entry_point.py#L17-L45", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:nens-qgispluginreleaser:create_zipfile-cd0d09d856", "question": "This is the actual zest.releaser entry point\n\n Relevant items in the context dict:\n\n name\n Name of the project being released\n\n tagdir\n Directory where the tag checkout is placed (*if* a tag\n checkout has been made)\n\n version\n Version we're releasing\n\n workingdir\n Original working directory", "scope": {"holder": "nens-qgispluginreleaser", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:nens/qgispluginreleaser:qgispluginreleaser/entry_point.py:fix_version#20725", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "qgispluginreleaser/entry_point.py", "symbol": "fix_version"}, "source_id": "csn:nens/qgispluginreleaser:qgispluginreleaser/entry_point.py:fix_version#20725"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/nens/qgispluginreleaser/blob/4826dd33e9152cc4f9c4be3b89e5b10b1a881d7e/qgispluginreleaser/entry_point.py#L48-L63", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:nens-qgispluginreleaser:fix_version-46011d59f9", "question": "Fix the version in metadata.txt\n\n Relevant context dict item for both prerelease and postrelease:\n ``new_version``.", "scope": {"holder": "nens-qgispluginreleaser", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:nesdis/djongo:djongo/models/fields.py:ArrayModelField.formfield#4625", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "djongo/models/fields.py", "symbol": "ArrayModelField.formfield"}, "source_id": "csn:nesdis/djongo:djongo/models/fields.py:ArrayModelField.formfield#4625"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/nesdis/djongo/blob/7f9d79455cf030cb5eee0b822502c50a0d9d3abb/djongo/models/fields.py#L243-L256", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:nesdis-djongo:ArrayModelField.formfield-55287e259d", "question": "Returns the formfield for the array.", "scope": {"holder": "nesdis-djongo", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:nesdis/djongo:djongo/base.py:DatabaseWrapper.create_cursor#4621", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "djongo/base.py", "symbol": "DatabaseWrapper.create_cursor"}, "source_id": "csn:nesdis/djongo:djongo/base.py:DatabaseWrapper.create_cursor#4621"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/nesdis/djongo/blob/7f9d79455cf030cb5eee0b822502c50a0d9d3abb/djongo/base.py#L199-L203", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:nesdis-djongo:DatabaseWrapper.create_cursor-7eedabec8d", "question": "Returns an active connection cursor to the database.", "scope": {"holder": "nesdis-djongo", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:netom/satispy:satispy/io/dimacs_cnf.py:DimacsCnf.tostring#9817", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "satispy/io/dimacs_cnf.py", "symbol": "DimacsCnf.tostring"}, "source_id": "csn:netom/satispy:satispy/io/dimacs_cnf.py:DimacsCnf.tostring#9817"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/netom/satispy/blob/0201a7bffd9070441b9e82187348d61c53922b6b/satispy/io/dimacs_cnf.py#L18-L51", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:netom-satispy:DimacsCnf.tostring-c1a7d8eacc", "question": "Convert Cnf object ot Dimacs cnf string\n \n cnf: Cnf object\n \n In the converted Cnf there will be only numbers for\n variable names. The conversion guarantees that the\n variables will be numbered alphabetically.", "scope": {"holder": "netom-satispy", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:netom/satispy:satispy/cnf.py:reduceCnf#9818", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "satispy/cnf.py", "symbol": "reduceCnf"}, "source_id": "csn:netom/satispy:satispy/cnf.py:reduceCnf#9818"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/netom/satispy/blob/0201a7bffd9070441b9e82187348d61c53922b6b/satispy/cnf.py#L128-L156", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:netom-satispy:reduceCnf-5915c2a62a", "question": "I just found a remarkably large bug in my SAT solver and found an\n interesting solution.\n Remove all b | -b\n (-b | b) & (b | -a) & (-b | a) & (a | -a)\n becomes\n (b | -a) & (-b | a)\n\n Remove all (-e) & (-e)\n (-e | a) & (-e | a) & (-e | a) & (-e | a)\n becomes\n (-e | a)\n (-b | b | c) becomes nothing, not (c)", "scope": {"holder": "netom-satispy", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:neurodata/ndio:ndio/remote/ndingest.py:NDIngest.add_dataset#17975", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "ndio/remote/ndingest.py", "symbol": "NDIngest.add_dataset"}, "source_id": "csn:neurodata/ndio:ndio/remote/ndingest.py:NDIngest.add_dataset#17975"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/neurodata/ndio/blob/792dd5816bc770b05a3db2f4327da42ff6253531/ndio/remote/ndingest.py#L136-L180", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:neurodata-ndio:NDIngest.add_dataset-8862a7ed19", "question": "Add a new dataset to the ingest.\n\n Arguments:\n dataset_name (str): Dataset Name is the overarching name of the\n research effort. Standard naming convention is to do\n LabNamePublicationYear or LeadResearcherCurrentYear.\n imagesize (int, int, int): Image size is the pixel count\n dimensions of the data. For example is the data is stored\n as a series of 100 slices each 2100x2000 pixel TIFF images,\n the X,Y,Z dimensions are (2100, 2000, 100).\n voxelres (float, float, float): Voxel Resolution is the number\n of voxels per unit pixel. We store X,Y,Z voxel resolution\n separately.\n offset (int, int, int): If your data is not well aligned and\n there is \"excess\" image data you do not wish to examine, but\n are present in your images, offset is how you specify where\n your actual image starts. Offset is provided a pixel\n coordinate offset from origin which specifies the \"actual\"\n origin of the image. The offset is for X,Y,Z dimensions.\n timerange (int, int): Time Range is a parameter to support\n storage of Time Series data, so the value of the tuple is a\n 0 to X range of how many images over time were taken. It\n takes 2 inputs timeStepStart and timeStepStop.\n scalinglevels (int): Scaling levels is the number of levels the\n data is scalable to (how many zoom levels are present in the\n data). The highest resolution of the data is at scaling level\n 0, and for each level up the data is down sampled by 2x2\n (per slice). To learn more about the sampling service used,\n visit the the propagation service page.\n scaling (int): Scaling is the scaling method of the data being\n stored. 0 corresponds to a Z-slice orientation (as in a\n collection of tiff images in which each tiff is a slice on\n the z plane) where data will be scaled only on the xy plane,\n not the z plane. 1 corresponds to an isotropic orientation\n (in which each tiff is a slice on the y plane) where data\n is scaled along all axis.\n\n Returns:\n None", "scope": {"holder": "neurodata-ndio", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:neurodata/ndio:ndio/remote/metadata.py:metadata.get_proj_info#17988", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "ndio/remote/metadata.py", "symbol": "metadata.get_proj_info"}, "source_id": "csn:neurodata/ndio:ndio/remote/metadata.py:metadata.get_proj_info#17988"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/neurodata/ndio/blob/792dd5816bc770b05a3db2f4327da42ff6253531/ndio/remote/metadata.py#L104-L115", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:neurodata-ndio:metadata.get_proj_info-d60cc0d93c", "question": "Return the project info for a given token.\n\n Arguments:\n token (str): Token to return information for\n\n Returns:\n JSON: representation of proj_info", "scope": {"holder": "neurodata-ndio", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:neurosynth/neurosynth:neurosynth/analysis/classify.py:Classifier.cross_val_fit#6680", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "neurosynth/analysis/classify.py", "symbol": "Classifier.cross_val_fit"}, "source_id": "csn:neurosynth/neurosynth:neurosynth/analysis/classify.py:Classifier.cross_val_fit#6680"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/neurosynth/neurosynth/blob/948ce7edce15d7df693446e76834e0c23bfe8f11/neurosynth/analysis/classify.py#L333-L386", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:neurosynth-neurosynth:Classifier.cross_val_fit-b2294889c4", "question": "Fits X to outcomes y, using clf and cv_method", "scope": {"holder": "neurosynth-neurosynth", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:neurosynth/neurosynth:neurosynth/base/dataset.py:ImageTable.get_image_data#6707", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "neurosynth/base/dataset.py", "symbol": "ImageTable.get_image_data"}, "source_id": "csn:neurosynth/neurosynth:neurosynth/base/dataset.py:ImageTable.get_image_data#6707"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/neurosynth/neurosynth/blob/948ce7edce15d7df693446e76834e0c23bfe8f11/neurosynth/base/dataset.py#L507-L537", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:neurosynth-neurosynth:ImageTable.get_image_data-0262daa1db", "question": "Slices and returns a subset of image data.\n\n Args:\n ids (list, array): A list or 1D numpy array of study ids to\n return. If None, returns data for all studies.\n voxels (list, array): A list or 1D numpy array of voxel indices\n (i.e., rows) to return. If None, returns data for all voxels.\n dense (bool): Optional boolean. When True (default), convert the\n result to a dense array before returning. When False, keep as\n sparse matrix.\n\n Returns:\n A 2D numpy array with voxels in rows and studies in columns.", "scope": {"holder": "neurosynth-neurosynth", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:nicferrier/pyproxyfs:src/pyproxyfs/__init__.py:_mergedict#16540", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "src/pyproxyfs/__init__.py", "symbol": "_mergedict"}, "source_id": "csn:nicferrier/pyproxyfs:src/pyproxyfs/__init__.py:_mergedict#16540"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/nicferrier/pyproxyfs/blob/7db09bb07bdeece56b7b1c4bf78c9f0b0a03c14b/src/pyproxyfs/__init__.py#L51-L63", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:nicferrier-pyproxyfs:_mergedict-2ebf7aaded", "question": "Recusively merge the 2 dicts.\n\n Destructive on argument 'a'.", "scope": {"holder": "nicferrier-pyproxyfs", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:nicfit/nicfit.py:nicfit/app.py:Application._atexit#19781", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "nicfit/app.py", "symbol": "Application._atexit"}, "source_id": "csn:nicfit/nicfit.py:nicfit/app.py:Application._atexit#19781"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/nicfit/nicfit.py/blob/8313f8edbc5e7361ddad496d6d818324b5236c7a/nicfit/app.py#L59-L63", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:nicfit-nicfit.py:Application._atexit-b49051705e", "question": "Invoked in the 'finally' block of Application.run.", "scope": {"holder": "nicfit-nicfit.py", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:nicfit/nicfit.py:nicfit/shell/completion.py:_updateCompleterDict#19758", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "nicfit/shell/completion.py", "symbol": "_updateCompleterDict"}, "source_id": "csn:nicfit/nicfit.py:nicfit/shell/completion.py:_updateCompleterDict#19758"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/nicfit/nicfit.py/blob/8313f8edbc5e7361ddad496d6d818324b5236c7a/nicfit/shell/completion.py#L13-L30", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:nicfit-nicfit.py:_updateCompleterDict-edb6ff289d", "question": "Merges ``cdict`` into ``completers``. In the event that a key\n in cdict already exists in the completers dict a ValueError is raised\n iff ``regex`` false'y. If a regex str is provided it and the duplicate\n key are updated to be unique, and the updated regex is returned.", "scope": {"holder": "nicfit-nicfit.py", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:nickw444/flask-ldap3-login:flask_ldap3_login/__init__.py:LDAP3LoginManager._contextualise_connection#9960", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "flask_ldap3_login/__init__.py", "symbol": "LDAP3LoginManager._contextualise_connection"}, "source_id": "csn:nickw444/flask-ldap3-login:flask_ldap3_login/__init__.py:LDAP3LoginManager._contextualise_connection#9960"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/nickw444/flask-ldap3-login/blob/3cf0faff52d0e04d4813119a2ba36d706e6fb31f/flask_ldap3_login/__init__.py#L174-L189", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:nickw444-flask-ldap3-login:LDAP3LoginManager._contextualise_connection-1ecc9ed262", "question": "Add a connection to the appcontext so it can be freed/unbound at\n a later time if an exception occured and it was not freed.\n\n Args:\n connection (ldap3.Connection): Connection to add to the appcontext", "scope": {"holder": "nickw444-flask-ldap3-login", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:nickw444/flask-ldap3-login:flask_ldap3_login/__init__.py:LDAP3LoginManager.connection#9971", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "flask_ldap3_login/__init__.py", "symbol": "LDAP3LoginManager.connection"}, "source_id": "csn:nickw444/flask-ldap3-login:flask_ldap3_login/__init__.py:LDAP3LoginManager.connection#9971"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/nickw444/flask-ldap3-login/blob/3cf0faff52d0e04d4813119a2ba36d706e6fb31f/flask_ldap3_login/__init__.py#L705-L736", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:nickw444-flask-ldap3-login:LDAP3LoginManager.connection-6e2f3b9391", "question": "Convenience property for externally accessing an authenticated\n connection to the server. This connection is automatically\n handled by the appcontext, so you do not have to perform an unbind.\n\n Returns:\n ldap3.Connection: A bound ldap3.Connection\n Raises:\n ldap3.core.exceptions.LDAPException: Since this method is performing\n a bind on behalf of the caller. You should handle this case\n occuring, such as invalid service credentials.", "scope": {"holder": "nickw444-flask-ldap3-login", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:nicolas-van/mailflash:mailflash.py:Connection.send#14935", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "mailflash.py", "symbol": "Connection.send"}, "source_id": "csn:nicolas-van/mailflash:mailflash.py:Connection.send#14935"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/nicolas-van/mailflash/blob/794598d9df0e343bb1f64b03d09a68a540229774/mailflash.py#L175-L205", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:nicolas-van-mailflash:Connection.send-90c045f7f8", "question": "Verifies and sends message.\n\n :param message: Message instance.\n :param envelope_from: Email address to be used in MAIL FROM command.", "scope": {"holder": "nicolas-van-mailflash", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:nicolas-van/mailflash:mailflash.py:Message.as_string#14937", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "mailflash.py", "symbol": "Message.as_string"}, "source_id": "csn:nicolas-van/mailflash:mailflash.py:Message.as_string#14937"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/nicolas-van/mailflash/blob/794598d9df0e343bb1f64b03d09a68a540229774/mailflash.py#L306-L374", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:nicolas-van-mailflash:Message.as_string-c5ac2be637", "question": "Creates the email", "scope": {"holder": "nicolas-van-mailflash", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:nigma/django-twilio-sms:src/utils.py:build_callback_url#18047", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "src/utils.py", "symbol": "build_callback_url"}, "source_id": "csn:nigma/django-twilio-sms:src/utils.py:build_callback_url#18047"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/nigma/django-twilio-sms/blob/386999c3da545e001cb8977c78b67408e33aba11/src/utils.py#L19-L42", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:nigma-django-twilio-sms:build_callback_url-7266e1cf81", "question": "Build Twilio callback url for confirming message delivery status\n\n :type message: OutgoingSMS", "scope": {"holder": "nigma-django-twilio-sms", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:nigma/django-twilio-sms:src/utils.py:send_sms#18048", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "src/utils.py", "symbol": "send_sms"}, "source_id": "csn:nigma/django-twilio-sms:src/utils.py:send_sms#18048"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/nigma/django-twilio-sms/blob/386999c3da545e001cb8977c78b67408e33aba11/src/utils.py#L45-L88", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:nigma-django-twilio-sms:send_sms-e48ab7e68e", "question": "Create :class:`OutgoingSMS` object and send SMS using Twilio.", "scope": {"holder": "nigma-django-twilio-sms", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:ninjaaron/libaaron:libaaron/libaaron.py:PBytes.from_str#13520", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "libaaron/libaaron.py", "symbol": "PBytes.from_str"}, "source_id": "csn:ninjaaron/libaaron:libaaron/libaaron.py:PBytes.from_str#13520"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/ninjaaron/libaaron/blob/a2ee417b784ca72c89c05bddb2e3e815a6b95154/libaaron/libaaron.py#L212-L228", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:ninjaaron-libaaron:PBytes.from_str-44da6f4875", "question": "attempt to parse a size in bytes from a human-readable string.", "scope": {"holder": "ninjaaron-libaaron", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:ninjaaron/libaaron:libaaron/libaaron.py:deepupdate#13513", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "libaaron/libaaron.py", "symbol": "deepupdate"}, "source_id": "csn:ninjaaron/libaaron:libaaron/libaaron.py:deepupdate#13513"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/ninjaaron/libaaron/blob/a2ee417b784ca72c89c05bddb2e3e815a6b95154/libaaron/libaaron.py#L124-L155", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:ninjaaron-libaaron:deepupdate-91d56a560b", "question": "update one dictionary from another recursively. Only individual\n values will be overwritten--not entire branches of nested\n dictionaries.", "scope": {"holder": "ninjaaron-libaaron", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:nixmc/chatter:chatter/base.py:ChatterCall._refresh_access_token#15453", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "chatter/base.py", "symbol": "ChatterCall._refresh_access_token"}, "source_id": "csn:nixmc/chatter:chatter/base.py:ChatterCall._refresh_access_token#15453"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/nixmc/chatter/blob/332304ed9bee45182f73871dc90c95998b0f32c9/chatter/base.py#L81-L126", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:nixmc-chatter:ChatterCall._refresh_access_token-0f03d8c878", "question": "If the client application has a refresh token, it can use it to send a request for a new access token. \n \n To ask for a new access token, the client application should send a POST request to https://login.instance_name/services/oauth2/token with the following query parameters:\n \n grant_type: Value must be refresh_token for this flow.\n refresh_token: The refresh token the client application already received. \n client_id: Consumer key from the remote access application definition.\n client_secret: Consumer secret from the remote access application definition.\n format: Expected return format. This parameter is optional. The default is json. Values are:\n \n * urlencoded\n * json\n * xml\n \n e.g.\n \n $ curl -i --form grant_type=refresh_token \\\n --form refresh_token=<refresh_token> \\\n --form client_id=<client_id> \\\n --form client_secret=<client_secret> \\\n --form format=json \\\n https://na1.salesforce.com/services/oauth2/token", "scope": {"holder": "nixmc-chatter", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:nkgilley/python-ecobee-api:pyecobee/__init__.py:Ecobee.delete_vacation#12854", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pyecobee/__init__.py", "symbol": "Ecobee.delete_vacation"}, "source_id": "csn:nkgilley/python-ecobee-api:pyecobee/__init__.py:Ecobee.delete_vacation#12854"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/nkgilley/python-ecobee-api/blob/cc8d90d20abcb9ef5b66ec9cb035bae2f06ba174/pyecobee/__init__.py#L271-L281", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:nkgilley-python-ecobee-api:Ecobee.delete_vacation-b50bf0f09f", "question": "Delete the vacation with name vacation", "scope": {"holder": "nkgilley-python-ecobee-api", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:nkgilley/python-ecobee-api:pyecobee/__init__.py:Ecobee.set_dst_mode#12860", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pyecobee/__init__.py", "symbol": "Ecobee.set_dst_mode"}, "source_id": "csn:nkgilley/python-ecobee-api:pyecobee/__init__.py:Ecobee.set_dst_mode#12860"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/nkgilley/python-ecobee-api/blob/cc8d90d20abcb9ef5b66ec9cb035bae2f06ba174/pyecobee/__init__.py#L353-L367", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:nkgilley-python-ecobee-api:Ecobee.set_dst_mode-94ed3793e4", "question": "Enable/disable daylight savings\n Values: True, False", "scope": {"holder": "nkgilley-python-ecobee-api", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:not-na/peng3d:peng3d/util/__init__.py:ActionDispatcher.addAction#18830", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "peng3d/util/__init__.py", "symbol": "ActionDispatcher.addAction"}, "source_id": "csn:not-na/peng3d:peng3d/util/__init__.py:ActionDispatcher.addAction#18830"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/not-na/peng3d/blob/1151be665b26cc8a479f6307086ba919e4d32d85/peng3d/util/__init__.py#L94-L104", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:not-na-peng3d:ActionDispatcher.addAction-2e33fcda42", "question": "Adds a callback to the specified action.\n \n All other positional and keyword arguments will be stored and passed to the function upon activation.", "scope": {"holder": "not-na-peng3d", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:not-na/peng3d:peng3d/model.py:Model.create#18736", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "peng3d/model.py", "symbol": "Model.create"}, "source_id": "csn:not-na/peng3d:peng3d/model.py:Model.create#18736"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/not-na/peng3d/blob/1151be665b26cc8a479f6307086ba919e4d32d85/peng3d/model.py#L900-L954", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:not-na-peng3d:Model.create-80907076d6", "question": "Initializes per-actor data on the given object for this model.\n \n If ``cache`` is set to True, the entity will not be redrawn after initialization.\n \n Note that this method may set several attributes on the given object, most of them starting with underscores.\n \n During initialization of vertex regions, several vertex lists will be created.\n If the given object has an attribute called ``batch3d`` it will be used, else it will be created.\n \n If the batch already existed, the :py:meth:`draw()` method will do nothing, else it will draw the batch.\n \n Memory leaks may occur if this is called more than once on the same object without calling :py:meth:`cleanup()` first.", "scope": {"holder": "not-na-peng3d", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:nprapps/copydoc:copydoc.py:CopyDoc._parse_href#19119", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "copydoc.py", "symbol": "CopyDoc._parse_href"}, "source_id": "csn:nprapps/copydoc:copydoc.py:CopyDoc._parse_href#19119"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/nprapps/copydoc/blob/e1ab09b287beb0439748c319cf165cbc06c66624/copydoc.py#L189-L195", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:nprapps-copydoc:CopyDoc._parse_href-f5348b9533", "question": "Extract \"real\" URL from Google redirected url by getting `q`\n querystring parameter.", "scope": {"holder": "nprapps-copydoc", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:nprapps/copydoc:copydoc.py:CopyDoc.create_underline#19115", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "copydoc.py", "symbol": "CopyDoc.create_underline"}, "source_id": "csn:nprapps/copydoc:copydoc.py:CopyDoc.create_underline#19115"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/nprapps/copydoc/blob/e1ab09b287beb0439748c319cf165cbc06c66624/copydoc.py#L127-L133", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:nprapps-copydoc:CopyDoc.create_underline-21810cea26", "question": "See if span tag has underline style and wrap with u tag.", "scope": {"holder": "nprapps-copydoc", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:nsqio/pynsq:nsq/backoff_timer.py:BackoffTimer.failure#10460", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "nsq/backoff_timer.py", "symbol": "BackoffTimer.failure"}, "source_id": "csn:nsqio/pynsq:nsq/backoff_timer.py:BackoffTimer.failure#10460"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/nsqio/pynsq/blob/48bf62d65ea63cddaa401efb23187b95511dbc84/nsq/backoff_timer.py#L42-L48", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:nsqio-pynsq:BackoffTimer.failure-09af7b369d", "question": "Update the timer to reflect a failed call", "scope": {"holder": "nsqio-pynsq", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:nsqio/pynsq:nsq/reader.py:Reader.connect_to_nsqd#10464", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "nsq/reader.py", "symbol": "Reader.connect_to_nsqd"}, "source_id": "csn:nsqio/pynsq:nsq/reader.py:Reader.connect_to_nsqd#10464"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/nsqio/pynsq/blob/48bf62d65ea63cddaa401efb23187b95511dbc84/nsq/reader.py#L446-L484", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:nsqio-pynsq:Reader.connect_to_nsqd-47b2b52f3f", "question": "Adds a connection to ``nsqd`` at the specified address.\n\n :param host: the address to connect to\n :param port: the port to connect to", "scope": {"holder": "nsqio-pynsq", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:nvdv/vprof:vprof/base_profiler.py:BaseProfiler._replace_sysargs#6442", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "vprof/base_profiler.py", "symbol": "BaseProfiler._replace_sysargs"}, "source_id": "csn:nvdv/vprof:vprof/base_profiler.py:BaseProfiler._replace_sysargs#6442"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/nvdv/vprof/blob/4c3ff78f8920ab10cb9c00b14143452aa09ff6bb/vprof/base_profiler.py#L140-L144", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:nvdv-vprof:BaseProfiler._replace_sysargs-9e03e003b5", "question": "Replaces sys.argv with proper args to pass to script.", "scope": {"holder": "nvdv-vprof", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:nvdv/vprof:vprof/memory_profiler.py:_CodeEventsTracker._trace_memory_usage#6428", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "vprof/memory_profiler.py", "symbol": "_CodeEventsTracker._trace_memory_usage"}, "source_id": "csn:nvdv/vprof:vprof/memory_profiler.py:_CodeEventsTracker._trace_memory_usage#6428"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/nvdv/vprof/blob/4c3ff78f8920ab10cb9c00b14143452aa09ff6bb/vprof/memory_profiler.py#L101-L107", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:nvdv-vprof:_CodeEventsTracker._trace_memory_usage-620ba2eb23", "question": "Checks memory usage when 'line' event occur.", "scope": {"holder": "nvdv-vprof", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:oceanprotocol/oceandb-elasticsearch-driver:oceandb_elasticsearch_driver/plugin.py:Plugin.delete#12335", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "oceandb_elasticsearch_driver/plugin.py", "symbol": "Plugin.delete"}, "source_id": "csn:oceanprotocol/oceandb-elasticsearch-driver:oceandb_elasticsearch_driver/plugin.py:Plugin.delete#12335"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/oceanprotocol/oceandb-elasticsearch-driver/blob/11901e8396252b9dbb70fd48debcfa82f1dd1ff2/oceandb_elasticsearch_driver/plugin.py#L83-L99", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:oceanprotocol-oceandb-elasticsearch-driver:Plugin.delete-3712824ea2", "question": "Delete an object from elasticsearch.\n :param resource_id: id of the object to be deleted.\n :return:", "scope": {"holder": "oceanprotocol-oceandb-elasticsearch-driver", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:oceanprotocol/oceandb-elasticsearch-driver:oceandb_elasticsearch_driver/plugin.py:Plugin.text_query#12338", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "oceandb_elasticsearch_driver/plugin.py", "symbol": "Plugin.text_query"}, "source_id": "csn:oceanprotocol/oceandb-elasticsearch-driver:oceandb_elasticsearch_driver/plugin.py:Plugin.text_query#12338"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/oceanprotocol/oceandb-elasticsearch-driver/blob/11901e8396252b9dbb70fd48debcfa82f1dd1ff2/oceandb_elasticsearch_driver/plugin.py#L172-L199", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:oceanprotocol-oceandb-elasticsearch-driver:Plugin.text_query-4ba61a839f", "question": "Query elasticsearch for objects.\n :param search_model: object of FullTextModel\n :return: list of objects that match the query.", "scope": {"holder": "oceanprotocol-oceandb-elasticsearch-driver", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:ojarva/python-sshpubkeys:sshpubkeys/keys.py:SSHKey._parse_long#17001", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "sshpubkeys/keys.py", "symbol": "SSHKey._parse_long"}, "source_id": "csn:ojarva/python-sshpubkeys:sshpubkeys/keys.py:SSHKey._parse_long#17001"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/ojarva/python-sshpubkeys/blob/86dc1ab27ce82dcc091ce127416cc3ee219e9bec/sshpubkeys/keys.py#L191-L202", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:ojarva-python-sshpubkeys:SSHKey._parse_long-32d7b10412", "question": "Calculate two's complement.", "scope": {"holder": "ojarva-python-sshpubkeys", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:ojarva/python-sshpubkeys:sshpubkeys/keys.py:SSHKey.decode_key#17002", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "sshpubkeys/keys.py", "symbol": "SSHKey.decode_key"}, "source_id": "csn:ojarva/python-sshpubkeys:sshpubkeys/keys.py:SSHKey.decode_key#17002"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/ojarva/python-sshpubkeys/blob/86dc1ab27ce82dcc091ce127416cc3ee219e9bec/sshpubkeys/keys.py#L239-L245", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:ojarva-python-sshpubkeys:SSHKey.decode_key-e406aba543", "question": "Decode base64 coded part of the key.", "scope": {"holder": "ojarva-python-sshpubkeys", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:ojengwa/accounting:accounting/accounting.py:Accounting._change_precision#17877", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "accounting/accounting.py", "symbol": "Accounting._change_precision"}, "source_id": "csn:ojengwa/accounting:accounting/accounting.py:Accounting._change_precision#17877"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/ojengwa/accounting/blob/6343cf373a5c57941e407a92c101ac4bc45382e3/accounting/accounting.py#L98-L113", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:ojengwa-accounting:Accounting._change_precision-e409162655", "question": "Check and normalise the value of precision (must be positive integer).\n\n Args:\n val (INT): must be positive integer\n base (INT): Description\n\n Returns:\n VAL (INT): Description", "scope": {"holder": "ojengwa-accounting", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:ojengwa/accounting:accounting/accounting.py:Accounting.parse#17878", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "accounting/accounting.py", "symbol": "Accounting.parse"}, "source_id": "csn:ojengwa/accounting:accounting/accounting.py:Accounting.parse#17878"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/ojengwa/accounting/blob/6343cf373a5c57941e407a92c101ac4bc45382e3/accounting/accounting.py#L115-L162", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:ojengwa-accounting:Accounting.parse-c74c840595", "question": "Summary.\n\n Takes a string/array of strings, removes all formatting/cruft and\n returns the raw float value\n\n Decimal must be included in the regular expression to match floats\n (defaults to Accounting.settings.number.decimal),\n so if the number uses a non-standard decimal\n separator, provide it as the second argument.\n *\n Also matches bracketed negatives (eg. \"$ (1.99)\" => -1.99)\n\n Doesn't throw any errors (`None`s become 0) but this may change\n\n Args:\n value (TYPE): Description\n decimal (TYPE): Description\n\n Returns:\n name (TYPE): Description", "scope": {"holder": "ojengwa-accounting", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:omaciel/pytest-fauxfactory:setup.py:read#15660", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "setup.py", "symbol": "read"}, "source_id": "csn:omaciel/pytest-fauxfactory:setup.py:read#15660"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/omaciel/pytest-fauxfactory/blob/4365f521e7d8a6db00bdc9a02743467aa5bd1d72/setup.py#L9-L13", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:omaciel-pytest-fauxfactory:read-d3081bd790", "question": "Build a file path from *paths* and return the contents.", "scope": {"holder": "omaciel-pytest-fauxfactory", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:open-mmlab/mmcv:mmcv/utils/config.py:Config.auto_argparser#3498", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "mmcv/utils/config.py", "symbol": "Config.auto_argparser"}, "source_id": "csn:open-mmlab/mmcv:mmcv/utils/config.py:Config.auto_argparser#3498"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/open-mmlab/mmcv/blob/0d77f61450aab4dde8b8585a577cc496acb95d7f/mmcv/utils/config.py#L100-L110", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:open-mmlab-mmcv:Config.auto_argparser-b88c597d93", "question": "Generate argparser from config file automatically (experimental)", "scope": {"holder": "open-mmlab-mmcv", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:open-mmlab/mmcv:mmcv/visualization/optflow.py:flowshow#3541", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "mmcv/visualization/optflow.py", "symbol": "flowshow"}, "source_id": "csn:open-mmlab/mmcv:mmcv/visualization/optflow.py:flowshow#3541"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/open-mmlab/mmcv/blob/0d77f61450aab4dde8b8585a577cc496acb95d7f/mmcv/visualization/optflow.py#L10-L20", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:open-mmlab-mmcv:flowshow-392839fc6a", "question": "Show optical flow.\n\n Args:\n flow (ndarray or str): The optical flow to be displayed.\n win_name (str): The window name.\n wait_time (int): Value of waitKey param.", "scope": {"holder": "open-mmlab-mmcv", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:opencast/pyCA:pyca/db.py:BaseEvent.remaining_duration#12163", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pyca/db.py", "symbol": "BaseEvent.remaining_duration"}, "source_id": "csn:opencast/pyCA:pyca/db.py:BaseEvent.remaining_duration#12163"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/opencast/pyCA/blob/c89b168d4780d157e1b3f7676628c1b131956a88/pyca/db.py#L115-L118", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:opencast-pyCA:BaseEvent.remaining_duration-c416ddeaaa", "question": "Returns the remaining duration for a recording.", "scope": {"holder": "opencast-pyCA", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:opencast/pyCA:pyca/ingest.py:ingest#12196", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pyca/ingest.py", "symbol": "ingest"}, "source_id": "csn:opencast/pyCA:pyca/ingest.py:ingest#12196"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/opencast/pyCA/blob/c89b168d4780d157e1b3f7676628c1b131956a88/pyca/ingest.py#L42-L105", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:opencast-pyCA:ingest-14a30f5762", "question": "Ingest a finished recording to the Opencast server.", "scope": {"holder": "opencast-pyCA", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:openergy/oplus:oplus/eio.py:EioTable.get_value#12134", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "oplus/eio.py", "symbol": "EioTable.get_value"}, "source_id": "csn:openergy/oplus:oplus/eio.py:EioTable.get_value#12134"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/openergy/oplus/blob/f095868d1990c1d126e906ada6acbab26348b3d3/oplus/eio.py#L109-L129", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:openergy-oplus:EioTable.get_value-e8a6d41084", "question": "Returns first occurrence of value of filter column matching filter criterion.", "scope": {"holder": "openergy-oplus", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:openergy/oplus:oplus/epm/relations_manager.py:RelationsManager.register_link#12157", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "oplus/epm/relations_manager.py", "symbol": "RelationsManager.register_link"}, "source_id": "csn:openergy/oplus:oplus/epm/relations_manager.py:RelationsManager.register_link#12157"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/openergy/oplus/blob/f095868d1990c1d126e906ada6acbab26348b3d3/oplus/epm/relations_manager.py#L65-L99", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:openergy-oplus:RelationsManager.register_link-7b4025be51", "question": "source record and index must have been set", "scope": {"holder": "openergy-oplus", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:openmicroscopy/yaclifw:yaclifw/main.py:entry_point#19329", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "yaclifw/main.py", "symbol": "entry_point"}, "source_id": "csn:openmicroscopy/yaclifw:yaclifw/main.py:entry_point#19329"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/openmicroscopy/yaclifw/blob/a01179fefb2c2c4260c75e6d1dc6e19de9979d64/yaclifw/main.py#L37-L59", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:openmicroscopy-yaclifw:entry_point-82f7013bc0", "question": "External entry point which calls main() and\n if Stop is raised, calls sys.exit()", "scope": {"holder": "openmicroscopy-yaclifw", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:openmicroscopy/yaclifw:yaclifw/framework.py:main#19355", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "yaclifw/framework.py", "symbol": "main"}, "source_id": "csn:openmicroscopy/yaclifw:yaclifw/framework.py:main#19355"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/openmicroscopy/yaclifw/blob/a01179fefb2c2c4260c75e6d1dc6e19de9979d64/yaclifw/framework.py#L148-L193", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:openmicroscopy-yaclifw:main-f6c17b06d7", "question": "Reusable entry point. Arguments are parsed\n via the argparse-subcommands configured via\n each Command class found in globals(). Stop\n exceptions are propagated to callers.\n\n The name of the framework will be used in logging\n and similar.", "scope": {"holder": "openmicroscopy-yaclifw", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:openvenues/pypostal:postal/expand.py:expand_address#6740", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "postal/expand.py", "symbol": "expand_address"}, "source_id": "csn:openvenues/pypostal:postal/expand.py:expand_address#6740"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/openvenues/pypostal/blob/1c0fd96b5e2463b7015cd3625ac276db520c69fe/postal/expand.py#L9-L54", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:openvenues-pypostal:expand_address-19e8686971", "question": "Expand the given address into one or more normalized strings.\n\n Required\n --------\n @param address: the address as either Unicode or a UTF-8 encoded string\n\n Options\n -------\n @param languages: a tuple or list of ISO language code strings (e.g. \"en\", \"fr\", \"de\", etc.)\n to use in expansion. If None is passed, use language classifier\n to detect language automatically.\n @param address_components: an integer (bit-set) of address component expansions\n to use e.g. ADDRESS_NAME | ADDRESS_STREET would use\n only expansions which apply to venue names or streets.\n @param latin_ascii: use the Latin to ASCII transliterator, which normalizes e.g. æ => ae\n @param transliterate: use any available transliterators for non-Latin scripts, e.g.\n for the Greek phrase διαφορετικούς becomes diaphoretikoús̱\n @param strip_accents: strip accented characters e.g. é => e, ç => c. This loses some\n information in various languags, but in general we want\n @param decompose: perform Unicode normalization (NFD form)\n @param lowercase: UTF-8 lowercase the string\n @param trim_string: trim spaces on either side of the string\n @param replace_word_hyphens: add version of the string replacing hyphens with space\n @param delete_word_hyphens: add version of the string with hyphens deleted\n @param replace_numeric_hyphens: add version of the string with numeric hyphens replaced \n e.g. 12345-6789 => 12345 6789\n @param delete_numeric_hyphens: add version of the string with numeric hyphens removed\n e.g. 12345-6789 => 123456789\n @param split_alpha_from_numeric: split tokens like CR17 into CR 17, helps with expansion\n of certain types of highway abbreviations\n @param delete_final_periods: remove final periods on abbreviations e.g. St. => St\n @param delete_acronym_periods: remove periods in acronyms e.g. U.S.A. => USA\n @param drop_english_possessives: normalize possessives e.g. Mark's => Marks\n @param delete_apostrophes: delete other types of hyphens e.g. O'Malley => OMalley\n @param expand_numex: converts numeric expressions e.g. Twenty sixth => 26th,\n using either the supplied languages or the result of\n automated language classification.\n @param roman_numerals: normalize Roman numerals e.g. IX => 9. Since these can be\n ambiguous (especially I and V), turning this on simply\n adds another version of the string if any potential\n Roman numerals are found.", "scope": {"holder": "openvenues-pypostal", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:openvenues/pypostal:postal/parser.py:parse_address#6742", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "postal/parser.py", "symbol": "parse_address"}, "source_id": "csn:openvenues/pypostal:postal/parser.py:parse_address#6742"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/openvenues/pypostal/blob/1c0fd96b5e2463b7015cd3625ac276db520c69fe/postal/parser.py#L6-L15", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:openvenues-pypostal:parse_address-2e1821a46f", "question": "Parse address into components.\n\n @param address: the address as either Unicode or a UTF-8 encoded string\n @param language (optional): language code\n @param country (optional): country code", "scope": {"holder": "openvenues-pypostal", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:orangain/scrapy-s3pipeline:s3pipeline/pipelines.py:S3Pipeline._make_fileobj#13713", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "s3pipeline/pipelines.py", "symbol": "S3Pipeline._make_fileobj"}, "source_id": "csn:orangain/scrapy-s3pipeline:s3pipeline/pipelines.py:S3Pipeline._make_fileobj#13713"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/orangain/scrapy-s3pipeline/blob/6301a3a057da6407b04a09c717498026f88706a4/s3pipeline/pipelines.py#L104-L125", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:orangain-scrapy-s3pipeline:S3Pipeline._make_fileobj-dea7cd3ab4", "question": "Build file object from items.", "scope": {"holder": "orangain-scrapy-s3pipeline", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:orangain/scrapy-s3pipeline:s3pipeline/pipelines.py:S3Pipeline.open_spider#13711", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "s3pipeline/pipelines.py", "symbol": "S3Pipeline.open_spider"}, "source_id": "csn:orangain/scrapy-s3pipeline:s3pipeline/pipelines.py:S3Pipeline.open_spider#13711"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/orangain/scrapy-s3pipeline/blob/6301a3a057da6407b04a09c717498026f88706a4/s3pipeline/pipelines.py#L56-L61", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:orangain-scrapy-s3pipeline:S3Pipeline.open_spider-e5450aea4a", "question": "Callback function when spider is open.", "scope": {"holder": "orangain-scrapy-s3pipeline", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:oriontvv/pyaspeller:pyaspeller/speller.py:YandexSpeller.api_options#17492", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pyaspeller/speller.py", "symbol": "YandexSpeller.api_options"}, "source_id": "csn:oriontvv/pyaspeller:pyaspeller/speller.py:YandexSpeller.api_options#17492"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/oriontvv/pyaspeller/blob/9a76d1f1fb00c7eabfa006f8e0f145f764c7a8d6/pyaspeller/speller.py#L328-L352", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:oriontvv-pyaspeller:YandexSpeller.api_options-7e4df486f7", "question": "current spelling settings\n :return: api options as number", "scope": {"holder": "oriontvv-pyaspeller", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:oriontvv/pyaspeller:pyaspeller/speller.py:YandexSpeller.dictionary#17491", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pyaspeller/speller.py", "symbol": "YandexSpeller.dictionary"}, "source_id": "csn:oriontvv/pyaspeller:pyaspeller/speller.py:YandexSpeller.dictionary#17491"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/oriontvv/pyaspeller/blob/9a76d1f1fb00c7eabfa006f8e0f145f764c7a8d6/pyaspeller/speller.py#L165-L170", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:oriontvv-pyaspeller:YandexSpeller.dictionary-cf4c649f89", "question": "Set dictionary", "scope": {"holder": "oriontvv-pyaspeller", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:oscarbranson/latools:latools/D_obj.py:D.ablation_times#14692", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "latools/D_obj.py", "symbol": "D.ablation_times"}, "source_id": "csn:oscarbranson/latools:latools/D_obj.py:D.ablation_times#14692"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/oscarbranson/latools/blob/cd25a650cfee318152f234d992708511f7047fbe/latools/D_obj.py#L593-L606", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:oscarbranson-latools:D.ablation_times-dcb88097dc", "question": "Function for calculating the ablation time for each\n ablation.\n\n Returns\n -------\n dict of times for each ablation.", "scope": {"holder": "oscarbranson-latools", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:oscarbranson/latools:latools/helpers/plot.py:autorange_plot#14713", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "latools/helpers/plot.py", "symbol": "autorange_plot"}, "source_id": "csn:oscarbranson/latools:latools/helpers/plot.py:autorange_plot#14713"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/oscarbranson/latools/blob/cd25a650cfee318152f234d992708511f7047fbe/latools/helpers/plot.py#L459-L690", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:oscarbranson-latools:autorange_plot-b9142a3e71", "question": "Function for visualising the autorange mechanism.\n\n Parameters\n ----------\n t : array-like\n Independent variable (usually time).\n sig : array-like\n Dependent signal, with distinctive 'on' and 'off' regions.\n gwin : int\n The window used for calculating first derivative.\n Defaults to 7.\n swin : int\n The window ised for signal smoothing. If None, gwin // 2.\n win : int\n The width (c +/- win) of the transition data subsets.\n Defaults to 20.\n on_mult and off_mult : tuple, len=2\n Control the width of the excluded transition regions, which is defined\n relative to the peak full-width-half-maximum (FWHM) of the transition\n gradient. The region n * FHWM below the transition, and m * FWHM above\n the tranision will be excluded, where (n, m) are specified in `on_mult`\n and `off_mult`.\n `on_mult` and `off_mult` apply to the off-on and on-off transitions,\n respectively.\n Defaults to (1.5, 1) and (1, 1.5).\n nbin : ind\n Used to calculate the number of bins in the data histogram.\n bins = len(sig) // nbin\n\n Returns\n -------\n fig, axes", "scope": {"holder": "oscarbranson-latools", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:ossobv/exactonline:exactonline/elements/invoice.py:ExactInvoice.get_ledger_code_to_guid_map#10429", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "exactonline/elements/invoice.py", "symbol": "ExactInvoice.get_ledger_code_to_guid_map"}, "source_id": "csn:ossobv/exactonline:exactonline/elements/invoice.py:ExactInvoice.get_ledger_code_to_guid_map#10429"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/ossobv/exactonline/blob/f6bee418a9cb1fcf3ef17347ea7ab0dd3b573fde/exactonline/elements/invoice.py#L69-L89", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:ossobv-exactonline:ExactInvoice.get_ledger_code_to_guid_map-761bc50041", "question": "Convert set of human codes and to a dict of code to exactonline\n guid mappings.\n\n Example::\n\n ret = inv.get_ledger_code_to_guid_map(['1234', '5555'])\n ret == {'1234': '<guid1_from_exactonline_ledgeraccounts>',\n '5555': '<guid2_from_exactonline_ledgeraccounts>'}", "scope": {"holder": "ossobv-exactonline", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:ossobv/exactonline:exactonline/api/invoices.py:Invoices.map_foreign2exact_invoice_numbers#10434", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "exactonline/api/invoices.py", "symbol": "Invoices.map_foreign2exact_invoice_numbers"}, "source_id": "csn:ossobv/exactonline:exactonline/api/invoices.py:Invoices.map_foreign2exact_invoice_numbers#10434"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/ossobv/exactonline/blob/f6bee418a9cb1fcf3ef17347ea7ab0dd3b573fde/exactonline/api/invoices.py#L94-L128", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:ossobv-exactonline:Invoices.map_foreign2exact_invoice_numbers-9e42eda046", "question": "Optionally supply a list of foreign (your) invoice numbers.\n\n Returns a dictionary of your invoice numbers (YourRef) to Exact\n Online invoice numbers.", "scope": {"holder": "ossobv-exactonline", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:pelotoncycle/cycle_detector:cycle_detector.py:brent#18140", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "cycle_detector.py", "symbol": "brent"}, "source_id": "csn:pelotoncycle/cycle_detector:cycle_detector.py:brent#18140"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/pelotoncycle/cycle_detector/blob/a7c1a2e321e232de10f5862f6042471a3c60beb9/cycle_detector.py#L256-L311", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:pelotoncycle-cycle_detector:brent-765301160b", "question": "Brent's Cycle Detector.\n\n See help(cycle_detector) for more context.\n\n Args:\n\n *args: Two iterators issueing the exact same sequence:\n -or-\n f, start: Function and starting state for finite state machine\n\n Yields: \n\n Values yielded by sequence_a if it terminates, undefined if a\n cycle is found.\n\n Raises:\n\n CycleFound if exception is found; if called with f and `start`,\n the parametres `first` and `period` will be defined indicating\n the offset of start of the cycle and the cycle's period.", "scope": {"holder": "pelotoncycle-cycle_detector", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:pelotoncycle/cycle_detector:cycle_detector.py:gosper#18139", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "cycle_detector.py", "symbol": "gosper"}, "source_id": "csn:pelotoncycle/cycle_detector:cycle_detector.py:gosper#18139"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/pelotoncycle/cycle_detector/blob/a7c1a2e321e232de10f5862f6042471a3c60beb9/cycle_detector.py#L218-L252", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:pelotoncycle-cycle_detector:gosper-52e206689a", "question": "Gosper's cycle detector\n\n See help(cycle_detector) for more context.\n\n Args:\n\n sequence: A sequence to detect cyles in.\n\n f, start: Function and starting state for finite state machine\n\n Yields: \n\n Values yielded by sequence_a if it terminates, undefined if a\n cycle is found.\n\n Raises:\n\n CycleFound if exception is found. Unlike Floyd and Brent's,\n Gosper's can only detect period of a cycle. It cannot\n compute the first position", "scope": {"holder": "pelotoncycle-cycle_detector", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:penguinmenac3/opendatalake:opendatalake/detection/utils.py:augment_detections#13134", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "opendatalake/detection/utils.py", "symbol": "augment_detections"}, "source_id": "csn:penguinmenac3/opendatalake:opendatalake/detection/utils.py:augment_detections#13134"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/penguinmenac3/opendatalake/blob/77c888377095e1812a16982c8efbd2f6b1697a33/opendatalake/detection/utils.py#L804-L926", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:penguinmenac3-opendatalake:augment_detections-2ca8070344", "question": "Augment the detection dataset.\n\n In your hyper_parameters.problem.augmentation add configurations to enable features.\n Supports \"enable_horizontal_flip\", \"enable_micro_translation\", \"random_crop\" : {\"shape\": { \"width\", \"height\" }}\n and \"enable_texture_augmentation\". Make sure to also set the \"steps\" otherwise this method will not be used properly.\n\n Random crop ensures at least one detection is in the crop region.\n\n Sample configuration\n \"problem\": {\n \"augmentation\": {\n \"steps\": 40,\n \"enable_texture_augmentation\": true,\n \"enable_micro_translation\": true,\n \"enable_horizontal_flip\": true,\n \"random_crop\": {\n \"shape\": {\n \"width\": 256,\n \"height\": 256\n }\n }\n }\n }\n\n :param hyper_params: The hyper parameters object\n :param feature: A dict containing all features, must be in the style created by detection datasets.\n :param label: A label dict in the detection dataset style.\n :return: Modified feature and label dict (copied & modified).", "scope": {"holder": "penguinmenac3-opendatalake", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:penguinmenac3/opendatalake:opendatalake/detection/utils.py:hflip_detections#13133", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "opendatalake/detection/utils.py", "symbol": "hflip_detections"}, "source_id": "csn:penguinmenac3/opendatalake:opendatalake/detection/utils.py:hflip_detections#13133"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/penguinmenac3/opendatalake/blob/77c888377095e1812a16982c8efbd2f6b1697a33/opendatalake/detection/utils.py#L787-L801", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:penguinmenac3-opendatalake:hflip_detections-44d4366dc8", "question": "Horizontally flip detections according to an image flip.\n\n :param label: The label dict containing all detection lists.\n :param w: The width of the image as a number.\n :return:", "scope": {"holder": "penguinmenac3-opendatalake", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:pgjones/hypercorn:hypercorn/config.py:Config.from_mapping#7359", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "hypercorn/config.py", "symbol": "Config.from_mapping"}, "source_id": "csn:pgjones/hypercorn:hypercorn/config.py:Config.from_mapping#7359"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/pgjones/hypercorn/blob/ef93d741fe246846a127f9318b54505ac65f1ae7/hypercorn/config.py#L206-L236", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:pgjones-hypercorn:Config.from_mapping-661b0c8d07", "question": "Create a configuration from a mapping.\n\n This allows either a mapping to be directly passed or as\n keyword arguments, for example,\n\n .. code-block:: python\n\n config = {'keep_alive_timeout': 10}\n Config.from_mapping(config)\n Config.form_mapping(keep_alive_timeout=10)\n\n Arguments:\n mapping: Optionally a mapping object.\n kwargs: Optionally a collection of keyword arguments to\n form a mapping.", "scope": {"holder": "pgjones-hypercorn", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:pgjones/hypercorn:hypercorn/asgi/h11.py:H11Mixin.asgi_send#7355", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "hypercorn/asgi/h11.py", "symbol": "H11Mixin.asgi_send"}, "source_id": "csn:pgjones/hypercorn:hypercorn/asgi/h11.py:H11Mixin.asgi_send#7355"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/pgjones/hypercorn/blob/ef93d741fe246846a127f9318b54505ac65f1ae7/hypercorn/asgi/h11.py#L123-L151", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:pgjones-hypercorn:H11Mixin.asgi_send-a957096e7a", "question": "Called by the ASGI instance to send a message.", "scope": {"holder": "pgjones-hypercorn", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:phfaist/pylatexenc:pylatexenc/latex2text.py:LatexNodes2Text._nodelistcontents_to_text#14518", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pylatexenc/latex2text.py", "symbol": "LatexNodes2Text._nodelistcontents_to_text"}, "source_id": "csn:phfaist/pylatexenc:pylatexenc/latex2text.py:LatexNodes2Text._nodelistcontents_to_text#14518"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/phfaist/pylatexenc/blob/0c1788d1349e749501e67a6fba54d79e6e0d54f6/pylatexenc/latex2text.py#L791-L811", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:phfaist-pylatexenc:LatexNodes2Text._nodelistcontents_to_text-9b6de2affe", "question": "Turn the node list to text representations of each node. Basically apply\n `node_to_text()` to each node. (But not quite actually, since we take\n some care as to where we add whitespace.)", "scope": {"holder": "phfaist-pylatexenc", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:phfaist/pylatexenc:pylatexenc/latexwalker.py:LatexWalker.get_token#14506", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pylatexenc/latexwalker.py", "symbol": "LatexWalker.get_token"}, "source_id": "csn:phfaist/pylatexenc:pylatexenc/latexwalker.py:LatexWalker.get_token#14506"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/phfaist/pylatexenc/blob/0c1788d1349e749501e67a6fba54d79e6e0d54f6/pylatexenc/latexwalker.py#L702-L821", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:phfaist-pylatexenc:LatexWalker.get_token-d2ea1717ec", "question": "Parses the latex content given to the constructor (and stored in `self.s`),\n starting at position `pos`, to parse a single \"token\", as defined by\n :py:class:`LatexToken`.\n\n Parse the token in the stream pointed to at position `pos`.\n\n Returns a :py:class:`LatexToken`. Raises :py:exc:`LatexWalkerEndOfStream` if end\n of stream reached.\n\n If `brackets_are_chars=False`, then square bracket characters count as\n 'brace_open' and 'brace_close' token types (see :py:class:`LatexToken`); otherwise\n (the default) they are considered just like other normal characters.\n\n If `environments=False`, then '\\\\begin' and '\\\\end' tokens count as regular\n 'macro' tokens (see :py:class:`LatexToken`); otherwise (the default) they are\n considered as the token types 'begin_environment' and 'end_environment'.\n\n If `keep_inline_math` is not `None`, then that value overrides that of\n `self.keep_inline_math` for the duration of this method call.", "scope": {"holder": "phfaist-pylatexenc", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:philipsoutham/py-mysql2pgsql:mysql2pgsql/lib/postgres_db_writer.py:PostgresDbWriter.truncate#8322", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "mysql2pgsql/lib/postgres_db_writer.py", "symbol": "PostgresDbWriter.truncate"}, "source_id": "csn:philipsoutham/py-mysql2pgsql:mysql2pgsql/lib/postgres_db_writer.py:PostgresDbWriter.truncate#8322"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/philipsoutham/py-mysql2pgsql/blob/66dc2a3a3119263b3fe77300fb636346509787ef/mysql2pgsql/lib/postgres_db_writer.py#L130-L141", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:philipsoutham-py-mysql2pgsql:PostgresDbWriter.truncate-6f1a6133e3", "question": "Send DDL to truncate the specified `table`\n\n :Parameters:\n - `table`: an instance of a :py:class:`mysql2pgsql.lib.mysql_reader.MysqlReader.Table` object that represents the table to read/write.\n\n Returns None", "scope": {"holder": "philipsoutham-py-mysql2pgsql", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:philipsoutham/py-mysql2pgsql:mysql2pgsql/lib/postgres_file_writer.py:PostgresFileWriter.truncate#8329", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "mysql2pgsql/lib/postgres_file_writer.py", "symbol": "PostgresFileWriter.truncate"}, "source_id": "csn:philipsoutham/py-mysql2pgsql:mysql2pgsql/lib/postgres_file_writer.py:PostgresFileWriter.truncate#8329"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/philipsoutham/py-mysql2pgsql/blob/66dc2a3a3119263b3fe77300fb636346509787ef/mysql2pgsql/lib/postgres_file_writer.py#L36-L54", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:philipsoutham-py-mysql2pgsql:PostgresFileWriter.truncate-9e1f2872d4", "question": "Write DDL to truncate the specified `table`\n\n :Parameters:\n - `table`: an instance of a :py:class:`mysql2pgsql.lib.mysql_reader.MysqlReader.Table` object that represents the table to read/write.\n\n Returns None", "scope": {"holder": "philipsoutham-py-mysql2pgsql", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:phoikoi/sisy:src/sisy/management/commands/sisy_heartbeat.py:Command.handle#21725", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "src/sisy/management/commands/sisy_heartbeat.py", "symbol": "Command.handle"}, "source_id": "csn:phoikoi/sisy:src/sisy/management/commands/sisy_heartbeat.py:Command.handle#21725"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/phoikoi/sisy/blob/840c5463ab65488d34e99531f230e61f755d2d69/src/sisy/management/commands/sisy_heartbeat.py#L15-L22", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:phoikoi-sisy:Command.handle-e52ae9ed8c", "question": "Handle CLI command", "scope": {"holder": "phoikoi-sisy", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:phoikoi/sisy:src/sisy/models.py:func_from_string#20671", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "src/sisy/models.py", "symbol": "func_from_string"}, "source_id": "csn:phoikoi/sisy:src/sisy/models.py:func_from_string#20671"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/phoikoi/sisy/blob/840c5463ab65488d34e99531f230e61f755d2d69/src/sisy/models.py#L95-L165", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:phoikoi-sisy:func_from_string-daf606d6a8", "question": "Return a live function from a full dotted path. Must be either a plain function\n directly in a module, a class function, or a static function. (No modules, classes,\n or instance methods, since those can't be called as tasks.)", "scope": {"holder": "phoikoi-sisy", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:piface/pifacecommon:pifacecommon/interrupts.py:EventQueue.add_event#16800", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pifacecommon/interrupts.py", "symbol": "EventQueue.add_event"}, "source_id": "csn:piface/pifacecommon:pifacecommon/interrupts.py:EventQueue.add_event#16800"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/piface/pifacecommon/blob/006bca14c18d43ba2d9eafaa84ef83b512c51cf6/pifacecommon/interrupts.py#L102-L128", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:piface-pifacecommon:EventQueue.add_event-1ae6602451", "question": "Adds events to the queue. Will ignore events that occur before the\n settle time for that pin/direction. Such events are assumed to be\n bouncing.", "scope": {"holder": "piface-pifacecommon", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:piface/pifacecommon:pifacecommon/interrupts.py:PortEventListener.register#16801", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pifacecommon/interrupts.py", "symbol": "PortEventListener.register"}, "source_id": "csn:piface/pifacecommon:pifacecommon/interrupts.py:PortEventListener.register#16801"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/piface/pifacecommon/blob/006bca14c18d43ba2d9eafaa84ef83b512c51cf6/pifacecommon/interrupts.py#L174-L189", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:piface-pifacecommon:PortEventListener.register-80a6ae2e75", "question": "Registers a pin number and direction to a callback function.\n\n :param pin_num: The pin pin number.\n :type pin_num: int\n :param direction: The event direction\n (use: IODIR_ON/IODIR_OFF/IODIR_BOTH)\n :type direction: int\n :param callback: The function to run when event is detected.\n :type callback: function\n :param settle_time: Time within which subsequent events are ignored.\n :type settle_time: int", "scope": {"holder": "piface-pifacecommon", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:pltrdy/rouge:rouge/rouge.py:FilesRouge.get_scores#6217", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "rouge/rouge.py", "symbol": "FilesRouge.get_scores"}, "source_id": "csn:pltrdy/rouge:rouge/rouge.py:FilesRouge.get_scores#6217"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/pltrdy/rouge/blob/7bf8a83af5ca5c1677b93620b4e1f85ffd63b377/rouge/rouge.py#L34-L50", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:pltrdy-rouge:FilesRouge.get_scores-49bc33ec89", "question": "Calculate ROUGE scores between each pair of\n lines (hyp_file[i], ref_file[i]).\n Args:\n * hyp_path: hypothesis file path\n * ref_path: references file path\n * avg (False): whether to get an average scores or a list", "scope": {"holder": "pltrdy-rouge", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:pltrdy/rouge:rouge/rouge_score.py:multi_rouge_n#6213", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "rouge/rouge_score.py", "symbol": "multi_rouge_n"}, "source_id": "csn:pltrdy/rouge:rouge/rouge_score.py:multi_rouge_n#6213"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/pltrdy/rouge/blob/7bf8a83af5ca5c1677b93620b4e1f85ffd63b377/rouge/rouge_score.py#L140-L174", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:pltrdy-rouge:multi_rouge_n-d1c15508b3", "question": "Efficient way to compute highly repetitive scoring\n i.e. sequences are involved multiple time\n\n Args:\n sequences(list[str]): list of sequences (either hyp or ref)\n scores_ids(list[tuple(int)]): list of pairs (hyp_id, ref_id)\n ie. scores[i] = rouge_n(scores_ids[i][0],\n scores_ids[i][1])\n\n Returns:\n scores: list of length `len(scores_ids)` containing rouge `n`\n scores as a dict with 'f', 'r', 'p'\n Raises:\n KeyError: if there's a value of i in scores_ids that is not in\n [0, len(sequences)[", "scope": {"holder": "pltrdy-rouge", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:pmacosta/peng:peng/wave_functions.py:_bound_waveform#13534", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "peng/wave_functions.py", "symbol": "_bound_waveform"}, "source_id": "csn:pmacosta/peng:peng/wave_functions.py:_bound_waveform#13534"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/pmacosta/peng/blob/976935377adaa3de26fc5677aceb2cdfbd6f93a7/peng/wave_functions.py#L48-L64", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:pmacosta-peng:_bound_waveform-eef20be812", "question": "Add independent variable vector bounds if they are not in vector.", "scope": {"holder": "pmacosta-peng", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:pmacosta/peng:peng/wave_functions.py:ifftm#13555", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "peng/wave_functions.py", "symbol": "ifftm"}, "source_id": "csn:pmacosta/peng:peng/wave_functions.py:ifftm#13555"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/pmacosta/peng/blob/976935377adaa3de26fc5677aceb2cdfbd6f93a7/peng/wave_functions.py#L1166-L1208", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:pmacosta-peng:ifftm-94124c21df", "question": "r\"\"\"\n Return the magnitude of the inverse Fast Fourier Transform of a waveform.\n\n :param wave: Waveform\n :type wave: :py:class:`peng.eng.Waveform`\n\n :param npoints: Number of points to use in the transform. If **npoints**\n is less than the size of the independent variable vector\n the waveform is truncated; if **npoints** is greater than\n the size of the independent variable vector, the waveform\n is zero-padded\n :type npoints: positive integer\n\n :param indep_min: Independent vector start point of computation\n :type indep_min: integer or float\n\n :param indep_max: Independent vector stop point of computation\n :type indep_max: integer or float\n\n :rtype: :py:class:`peng.eng.Waveform`\n\n .. [[[cog cog.out(exobj_eng.get_sphinx_autodoc(raised=True)) ]]]\n .. Auto-generated exceptions documentation for\n .. peng.wave_functions.ifftm\n\n :raises:\n * RuntimeError (Argument \\`indep_max\\` is not valid)\n\n * RuntimeError (Argument \\`indep_min\\` is not valid)\n\n * RuntimeError (Argument \\`npoints\\` is not valid)\n\n * RuntimeError (Argument \\`wave\\` is not valid)\n\n * RuntimeError (Incongruent \\`indep_min\\` and \\`indep_max\\`\n arguments)\n\n * RuntimeError (Non-uniform frequency spacing)\n\n .. [[[end]]]", "scope": {"holder": "pmacosta-peng", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:pmbarrett314/curses-menu:cursesmenu/items/command_item.py:CommandItem.action#9123", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "cursesmenu/items/command_item.py", "symbol": "CommandItem.action"}, "source_id": "csn:pmbarrett314/curses-menu:cursesmenu/items/command_item.py:CommandItem.action#9123"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/pmbarrett314/curses-menu/blob/c76fc00ab9d518eab275e55434fc2941f49c6b30/cursesmenu/items/command_item.py#L27-L36", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:pmbarrett314-curses-menu:CommandItem.action-6a7444568d", "question": "This class overrides this method", "scope": {"holder": "pmbarrett314-curses-menu", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:pmbarrett314/curses-menu:cursesmenu/curses_menu.py:CursesMenu.select#9120", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "cursesmenu/curses_menu.py", "symbol": "CursesMenu.select"}, "source_id": "csn:pmbarrett314/curses-menu:cursesmenu/curses_menu.py:CursesMenu.select#9120"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/pmbarrett314/curses-menu/blob/c76fc00ab9d518eab275e55434fc2941f49c6b30/cursesmenu/curses_menu.py#L323-L335", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:pmbarrett314-curses-menu:CursesMenu.select-5d5bcd2cc6", "question": "Select the current item and run it", "scope": {"holder": "pmbarrett314-curses-menu", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:power-system-simulation-toolbox/psst:psst/scenarios/reduction.py:fast_forward_selection#17158", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "psst/scenarios/reduction.py", "symbol": "fast_forward_selection"}, "source_id": "csn:power-system-simulation-toolbox/psst:psst/scenarios/reduction.py:fast_forward_selection#17158"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/power-system-simulation-toolbox/psst/blob/8c116fb7afd183881ecc605e017dffc87cdc49e6/psst/scenarios/reduction.py#L111-L237", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:power-system-simulation-toolbox-psst:fast_forward_selection-599c527c8d", "question": "Fast forward selection algorithm\n\n Parameters\n ----------\n scenarios : numpy.array\n Contain the input scenarios.\n The columns representing the individual scenarios\n The rows are the vector of values in each scenario\n number_of_reduced_scenarios : int\n final number of scenarios that\n the reduced scenarios contain.\n If number of scenarios is equal to or greater than the input scenarios,\n then the original input scenario set is returned as the reduced set\n probability : numpy.array (default=None)\n probability is a numpy.array with length equal to number of scenarios.\n if probability is not defined, all scenarios get equal probabilities\n\n Returns\n -------\n reduced_scenarios : numpy.array\n reduced set of scenarios\n reduced_probability : numpy.array\n probability of reduced set of scenarios\n reduced_scenario_set : list\n scenario numbers of reduced set of scenarios\n\n Example\n -------\n Scenario reduction can be performed as shown below::\n\n >>> import numpy as np\n >>> import random\n >>> scenarios = np.array([[random.randint(500,1000) for i in range(0,24)],\n >>> [random.randint(500,1000) for i in range(0,24)],\n >>> [random.randint(500,1000) for i in range(0,24)],\n >>> [random.randint(500,1000) for i in range(0,24)],\n >>> [random.randint(500,1000) for i in range(0,24)],\n >>> [random.randint(500,1000) for i in range(0,24)],\n >>> [random.randint(500,1000) for i in range(0,24)],\n >>> [random.randint(500,1000) for i in range(0,24)],\n >>> [random.randint(500,1000) for i in range(0,24)],\n >>> [random.randint(500,1000) for i in range(0,24)]])\n >>> import psst.scenario\n >>> reduced_scenarios, reduced_probability, reduced_scenario_numbers = psst.scenario.fast_forward_selection(scenarios, probability, 2)", "scope": {"holder": "power-system-simulation-toolbox-psst", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:power-system-simulation-toolbox/psst:psst/plot/network.py:plot_line_power#17157", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "psst/plot/network.py", "symbol": "plot_line_power"}, "source_id": "csn:power-system-simulation-toolbox/psst:psst/plot/network.py:plot_line_power#17157"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/power-system-simulation-toolbox/psst/blob/8c116fb7afd183881ecc605e017dffc87cdc49e6/psst/plot/network.py#L29-L56", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:power-system-simulation-toolbox-psst:plot_line_power-5b2e46a805", "question": "obj: case or network", "scope": {"holder": "power-system-simulation-toolbox-psst", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:praekelt/django-analytics:analytics/views.py:AnalyticsView.get_active_stats#17511", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "analytics/views.py", "symbol": "AnalyticsView.get_active_stats"}, "source_id": "csn:praekelt/django-analytics:analytics/views.py:AnalyticsView.get_active_stats#17511"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/praekelt/django-analytics/blob/29c22d03374ccc0ec451650e2c2886d324f6e5c6/analytics/views.py#L22-L31", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:praekelt-django-analytics:AnalyticsView.get_active_stats-178c697aaa", "question": "Returns all of the active statistics for the gadgets currently registered.", "scope": {"holder": "praekelt-django-analytics", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:praekelt/django-analytics:analytics/geckoboard_views.py:geckoboard_funnel#17510", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "analytics/geckoboard_views.py", "symbol": "geckoboard_funnel"}, "source_id": "csn:praekelt/django-analytics:analytics/geckoboard_views.py:geckoboard_funnel#17510"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/praekelt/django-analytics/blob/29c22d03374ccc0ec451650e2c2886d324f6e5c6/analytics/geckoboard_views.py#L199-L215", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:praekelt-django-analytics:geckoboard_funnel-8eb92706d0", "question": "Returns a funnel chart for the metrics specified in the GET variables.", "scope": {"holder": "praekelt-django-analytics", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:praekeltfoundation/seed-control-interface:ci/utils.py:get_page_of_iterator#19575", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "ci/utils.py", "symbol": "get_page_of_iterator"}, "source_id": "csn:praekeltfoundation/seed-control-interface:ci/utils.py:get_page_of_iterator#19575"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/praekeltfoundation/seed-control-interface/blob/32ddad88b5bc2f8f4d80b848361899da2e081636/ci/utils.py#L162-L185", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:praekeltfoundation-seed-control-interface:get_page_of_iterator-96e8970298", "question": "Get a page from an interator, handling invalid input from the page number\n by defaulting to the first page.", "scope": {"holder": "praekeltfoundation-seed-control-interface", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:praekeltfoundation/seed-control-interface:ci/views.py:permission_required#19704", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "ci/views.py", "symbol": "permission_required"}, "source_id": "csn:praekeltfoundation/seed-control-interface:ci/views.py:permission_required#19704"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/praekeltfoundation/seed-control-interface/blob/32ddad88b5bc2f8f4d80b848361899da2e081636/ci/views.py#L136-L150", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:praekeltfoundation-seed-control-interface:permission_required-a4331b383e", "question": "Decorator for views that checks that the user is logged in, redirecting\n to the log-in page if necessary.", "scope": {"holder": "praekeltfoundation-seed-control-interface", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:precond/django-customary:customary/api/__init__.py:api_request#19609", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "customary/api/__init__.py", "symbol": "api_request"}, "source_id": "csn:precond/django-customary:customary/api/__init__.py:api_request#19609"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/precond/django-customary/blob/2cf2295d84d3d1bb6c034d4df25e15d814c1eb75/customary/api/__init__.py#L20-L60", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:precond-django-customary:api_request-ff05ac2de4", "question": "View decorator that handles JSON based API requests and responses consistently.\n :param methods: A list of allowed methods\n :param require_token: Whether API token is checked automatically or not", "scope": {"holder": "precond-django-customary", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:proofit404/service-factory:service_factory/providers/basehttp.py:HTTPServiceProvider.bind#16176", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "service_factory/providers/basehttp.py", "symbol": "HTTPServiceProvider.bind"}, "source_id": "csn:proofit404/service-factory:service_factory/providers/basehttp.py:HTTPServiceProvider.bind#16176"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/proofit404/service-factory/blob/a09d4e097e5599244564a2a7f0611e58efb4156a/service_factory/providers/basehttp.py#L68-L72", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:proofit404-service-factory:HTTPServiceProvider.bind-65750f3a07", "question": "Bind and activate HTTP server.", "scope": {"holder": "proofit404-service-factory", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:proofit404/service-factory:service_factory/errors.py:server_error#16293", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "service_factory/errors.py", "symbol": "server_error"}, "source_id": "csn:proofit404/service-factory:service_factory/errors.py:server_error#16293"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/proofit404/service-factory/blob/a09d4e097e5599244564a2a7f0611e58efb4156a/service_factory/errors.py#L72-L91", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:proofit404-service-factory:server_error-27fff68756", "question": "JSON-RPC server error.\n\n :param request_id: JSON-RPC request id\n :type request_id: int or str or None\n :param error: server error\n :type error: Exception", "scope": {"holder": "proofit404-service-factory", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:psd-tools/packbits:src/packbits.py:decode#17874", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "src/packbits.py", "symbol": "decode"}, "source_id": "csn:psd-tools/packbits:src/packbits.py:decode#17874"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/psd-tools/packbits/blob/38909758005abfb891770996f321a630f3c9ece2/src/packbits.py#L4-L26", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:psd-tools-packbits:decode-8a43521d93", "question": "Decodes a PackBit encoded data.", "scope": {"holder": "psd-tools-packbits", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:psd-tools/packbits:src/packbits.py:encode#17875", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "src/packbits.py", "symbol": "encode"}, "source_id": "csn:psd-tools/packbits:src/packbits.py:encode#17875"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/psd-tools/packbits/blob/38909758005abfb891770996f321a630f3c9ece2/src/packbits.py#L29-L101", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:psd-tools-packbits:encode-70fddcda46", "question": "Encodes data using PackBits encoding.", "scope": {"holder": "psd-tools-packbits", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:pyblish/pyblish-maya:pyblish_maya/vendor/Qt.py:_add#14325", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pyblish_maya/vendor/Qt.py", "symbol": "_add"}, "source_id": "csn:pyblish/pyblish-maya:pyblish_maya/vendor/Qt.py:_add#14325"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/pyblish/pyblish-maya/blob/75db8b5d8de9d53ae95e74195a788b5f6db2cb5f/pyblish_maya/vendor/Qt.py#L147-L150", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:pyblish-pyblish-maya:_add-f5b88d60aa", "question": "Append to self, accessible via Qt.QtCompat", "scope": {"holder": "pyblish-pyblish-maya", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:pyblish/pyblish-maya:pyblish_maya/vendor/Qt.py:convert#14324", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pyblish_maya/vendor/Qt.py", "symbol": "convert"}, "source_id": "csn:pyblish/pyblish-maya:pyblish_maya/vendor/Qt.py:convert#14324"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/pyblish/pyblish-maya/blob/75db8b5d8de9d53ae95e74195a788b5f6db2cb5f/pyblish_maya/vendor/Qt.py#L87-L110", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:pyblish-pyblish-maya:convert-d847a1cedf", "question": "Convert compiled .ui file from PySide2 to Qt.py\n\n Arguments:\n lines (list): Each line of of .ui file\n\n Usage:\n >> with open(\"myui.py\") as f:\n .. lines = convert(f.readlines())", "scope": {"holder": "pyblish-pyblish-maya", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:pyca/pyopenssl:src/OpenSSL/crypto.py:CRL.add_revoked#6150", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "src/OpenSSL/crypto.py", "symbol": "CRL.add_revoked"}, "source_id": "csn:pyca/pyopenssl:src/OpenSSL/crypto.py:CRL.add_revoked#6150"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/pyca/pyopenssl/blob/1fbe064c50fd030948141d7d630673761525b0d0/src/OpenSSL/crypto.py#L2143-L2158", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:pyca-pyopenssl:CRL.add_revoked-abec37faad", "question": "Add a revoked (by value not reference) to the CRL structure\n\n This revocation will be added by value, not by reference. That\n means it's okay to mutate it after adding: it won't affect\n this CRL.\n\n :param Revoked revoked: The new revocation.\n :return: ``None``", "scope": {"holder": "pyca-pyopenssl", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:pyca/pyopenssl:src/OpenSSL/crypto.py:NetscapeSPKI.verify#6161", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "src/OpenSSL/crypto.py", "symbol": "NetscapeSPKI.verify"}, "source_id": "csn:pyca/pyopenssl:src/OpenSSL/crypto.py:NetscapeSPKI.verify#6161"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/pyca/pyopenssl/blob/1fbe064c50fd030948141d7d630673761525b0d0/src/OpenSSL/crypto.py#L2552-L2567", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:pyca-pyopenssl:NetscapeSPKI.verify-071c26faac", "question": "Verifies a signature on a certificate request.\n\n :param PKey key: The public key that signature is supposedly from.\n\n :return: ``True`` if the signature is correct.\n :rtype: bool\n\n :raises OpenSSL.crypto.Error: If the signature is invalid, or there was\n a problem verifying the signature.", "scope": {"holder": "pyca-pyopenssl", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:pydanny/cookiecutter-django:hooks/post_gen_project.py:generate_random_string#2380", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "hooks/post_gen_project.py", "symbol": "generate_random_string"}, "source_id": "csn:pydanny/cookiecutter-django:hooks/post_gen_project.py:generate_random_string#2380"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/pydanny/cookiecutter-django/blob/bb9b482e96d1966e20745eeea87a8aa10ed1c861/hooks/post_gen_project.py#L107-L129", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:pydanny-cookiecutter-django:generate_random_string-f37a87018a", "question": "Example:\n opting out for 50 symbol-long, [a-z][A-Z][0-9] string\n would yield log_2((26+26+50)^50) ~= 334 bit strength.", "scope": {"holder": "pydanny-cookiecutter-django", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:pydanny/cookiecutter-django:{{cookiecutter.project_slug}}/{{cookiecutter.project_slug}}/contrib/sites/migrations/0003_set_site_domain_and_name.py:update_site_forward#2379", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "{{cookiecutter.project_slug}}/{{cookiecutter.project_slug}}/contrib/sites/migrations/0003_set_site_domain_and_name.py", "symbol": "update_site_forward"}, "source_id": "csn:pydanny/cookiecutter-django:{{cookiecutter.project_slug}}/{{cookiecutter.project_slug}}/contrib/sites/migrations/0003_set_site_domain_and_name.py:update_site_forward#2379"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/pydanny/cookiecutter-django/blob/bb9b482e96d1966e20745eeea87a8aa10ed1c861/{{cookiecutter.project_slug}}/{{cookiecutter.project_slug}}/contrib/sites/migrations/0003_set_site_domain_and_name.py#L10-L19", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:pydanny-cookiecutter-django:update_site_forward-0abb045a83", "question": "Set site domain and name.", "scope": {"holder": "pydanny-cookiecutter-django", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:pydron/anycall:anycall/bytequeue.py:ByteQueue.dequeue#19649", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "anycall/bytequeue.py", "symbol": "ByteQueue.dequeue"}, "source_id": "csn:pydron/anycall:anycall/bytequeue.py:ByteQueue.dequeue#19649"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/pydron/anycall/blob/43add96660258a14b24aa8e8413dffb1741b72d7/anycall/bytequeue.py#L32-L63", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:pydron-anycall:ByteQueue.dequeue-3cf9ceb800", "question": "Remove and return the first `n` characters from the queue.\n Throws an error if there are less than `n` characters in the queue.\n \n Equivalent to::\n \n s = queue[:n]\n queue = queue[n:]\n \n if `queue` where a regular string.", "scope": {"holder": "pydron-anycall", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:pydron/anycall:anycall/packetprotocol.py:PacketProtocol.register_type#19676", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "anycall/packetprotocol.py", "symbol": "PacketProtocol.register_type"}, "source_id": "csn:pydron/anycall:anycall/packetprotocol.py:PacketProtocol.register_type#19676"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/pydron/anycall/blob/43add96660258a14b24aa8e8413dffb1741b72d7/anycall/packetprotocol.py#L53-L65", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:pydron-anycall:PacketProtocol.register_type-5e9838e610", "question": "Registers a type name so that it may be used to send and receive packages.\n \n :param typename: Name of the packet type. A method with the same name and a\n \"on_\" prefix should be added to handle incomming packets.\n \n :raises ValueError: If there is a hash code collision.", "scope": {"holder": "pydron-anycall", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:pyrocat101/moo:moo/__init__.py:main#18049", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "moo/__init__.py", "symbol": "main"}, "source_id": "csn:pyrocat101/moo:moo/__init__.py:main#18049"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/pyrocat101/moo/blob/39e86d4ecb329309260bc30876c77aa3a7a2cfb1/moo/__init__.py#L209-L229", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:pyrocat101-moo:main-7fa23c9aed", "question": "\\b\n Examples:\n $ moo README.md # live preview README.md\n $ moo -e *.md # export all markdown files\n $ moo --no-css -e README.md # export README.md without CSS\n $ cat README.md | moo -e - | less # export STDIN to STDOUT", "scope": {"holder": "pyrocat101-moo", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:python/performance:performance/benchmarks/bm_chaos.py:Spline.GetDomain#4870", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "performance/benchmarks/bm_chaos.py", "symbol": "Spline.GetDomain"}, "source_id": "csn:python/performance:performance/benchmarks/bm_chaos.py:Spline.GetDomain#4870"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/python/performance/blob/2a9524c0a5714e85106671bc61d750e800fe17db/performance/benchmarks/bm_chaos.py#L95-L98", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:python-performance:Spline.GetDomain-f471f3ac4f", "question": "Returns the domain of the B-Spline", "scope": {"holder": "python-performance", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:python/performance:performance/benchmarks/bm_regex_effbot.py:init_benchmarks#4868", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "performance/benchmarks/bm_regex_effbot.py", "symbol": "init_benchmarks"}, "source_id": "csn:python/performance:performance/benchmarks/bm_regex_effbot.py:init_benchmarks#4868"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/python/performance/blob/2a9524c0a5714e85106671bc61d750e800fe17db/performance/benchmarks/bm_regex_effbot.py#L97-L126", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:python-performance:init_benchmarks-12f7516103", "question": "Initialize the strings we'll run the regexes against.\n\n The strings used in the benchmark are prefixed and suffixed by\n strings that are repeated n times.\n\n The sequence n_values contains the values for n.\n If n_values is None the values of n from the original benchmark\n are used.\n\n The generated list of strings is cached in the string_tables\n variable, which is indexed by n.\n\n Returns:\n A list of string prefix/suffix lengths.", "scope": {"holder": "python-performance", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:python-useful-helpers/advanced-descriptors:advanced_descriptors/advanced_property.py:AdvancedProperty.cgetter#14029", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "advanced_descriptors/advanced_property.py", "symbol": "AdvancedProperty.cgetter"}, "source_id": "csn:python-useful-helpers/advanced-descriptors:advanced_descriptors/advanced_property.py:AdvancedProperty.cgetter#14029"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/python-useful-helpers/advanced-descriptors/blob/17ee4a35b3bfcb4adf4ed2f41e75c4c6b71cb003/advanced_descriptors/advanced_property.py#L164-L173", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:python-useful-helpers-advanced-descriptors:AdvancedProperty.cgetter-1d407e05d5", "question": "Descriptor to change the class wide getter on a property.\n\n :param fcget: new class-wide getter.\n :type fcget: typing.Optional[typing.Callable[[typing.Any, ], typing.Any]]\n :return: AdvancedProperty\n :rtype: AdvancedProperty", "scope": {"holder": "python-useful-helpers-advanced-descriptors", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:python-useful-helpers/advanced-descriptors:advanced_descriptors/log_on_access.py:LogOnAccess._get_logger_for_instance#14034", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "advanced_descriptors/log_on_access.py", "symbol": "LogOnAccess._get_logger_for_instance"}, "source_id": "csn:python-useful-helpers/advanced-descriptors:advanced_descriptors/log_on_access.py:LogOnAccess._get_logger_for_instance#14034"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/python-useful-helpers/advanced-descriptors/blob/17ee4a35b3bfcb4adf4ed2f41e75c4c6b71cb003/advanced_descriptors/log_on_access.py#L202-L216", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:python-useful-helpers-advanced-descriptors:LogOnAccess._get_logger_for_instance-e0ce4af609", "question": "Get logger for log calls.\n\n :param instance: Owner class instance. Filled only if instance created, else None.\n :type instance: typing.Optional[owner]\n :return: logger instance\n :rtype: logging.Logger", "scope": {"holder": "python-useful-helpers-advanced-descriptors", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:pytorch/vision:torchvision/transforms/transforms.py:ColorJitter.get_params#893", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "torchvision/transforms/transforms.py", "symbol": "ColorJitter.get_params"}, "source_id": "csn:pytorch/vision:torchvision/transforms/transforms.py:ColorJitter.get_params#893"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/pytorch/vision/blob/3afcf3cd49661c466c75ea536b0b2a7ff57f9a05/torchvision/transforms/transforms.py#L875-L905", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:pytorch-vision:ColorJitter.get_params-b44d02c9be", "question": "Get a randomized transform to be applied on image.\n\n Arguments are same as that of __init__.\n\n Returns:\n Transform which randomly adjusts brightness, contrast and\n saturation in a random order.", "scope": {"holder": "pytorch-vision", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:pytorch/vision:torchvision/models/googlenet.py:googlenet#897", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "torchvision/models/googlenet.py", "symbol": "googlenet"}, "source_id": "csn:pytorch/vision:torchvision/models/googlenet.py:googlenet#897"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/pytorch/vision/blob/3afcf3cd49661c466c75ea536b0b2a7ff57f9a05/torchvision/models/googlenet.py#L18-L47", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:pytorch-vision:googlenet-924efbfb2c", "question": "r\"\"\"GoogLeNet (Inception v1) model architecture from\n `\"Going Deeper with Convolutions\" <http://arxiv.org/abs/1409.4842>`_.\n\n Args:\n pretrained (bool): If True, returns a model pre-trained on ImageNet\n aux_logits (bool): If True, adds two auxiliary branches that can improve training.\n Default: *False* when pretrained is True otherwise *True*\n transform_input (bool): If True, preprocesses the input according to the method with which it\n was trained on ImageNet. Default: *False*", "scope": {"holder": "pytorch-vision", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:quantopian/pgcontents:pgcontents/hybridmanager.py:HybridContentsManager._managers_changed#8087", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pgcontents/hybridmanager.py", "symbol": "HybridContentsManager._managers_changed"}, "source_id": "csn:quantopian/pgcontents:pgcontents/hybridmanager.py:HybridContentsManager._managers_changed#8087"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/quantopian/pgcontents/blob/ed36268b7917332d16868208e1e565742a8753e1/pgcontents/hybridmanager.py#L195-L204", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:quantopian-pgcontents:HybridContentsManager._managers_changed-d4a3fb0717", "question": "Strip slashes from directories before updating.", "scope": {"holder": "quantopian-pgcontents", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:quantopian/pgcontents:pgcontents/crypto.py:derive_fallback_fernet_keys#8067", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pgcontents/crypto.py", "symbol": "derive_fallback_fernet_keys"}, "source_id": "csn:quantopian/pgcontents:pgcontents/crypto.py:derive_fallback_fernet_keys#8067"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/quantopian/pgcontents/blob/ed36268b7917332d16868208e1e565742a8753e1/pgcontents/crypto.py#L177-L201", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:quantopian-pgcontents:derive_fallback_fernet_keys-7f28a13bd9", "question": "Derive a list of per-user Fernet keys from a list of master keys and a\n username.\n\n If a None is encountered in ``passwords``, it is forwarded.\n\n Parameters\n ----------\n passwords : list[unicode]\n List of ascii-encodable keys to derive.\n user_id : unicode or None\n ascii-encodable user_id to use as salt", "scope": {"holder": "quantopian-pgcontents", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:quantum5/pyfortune:pyfortune/loader.py:Chooser.fromlist#18323", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pyfortune/loader.py", "symbol": "Chooser.fromlist"}, "source_id": "csn:quantum5/pyfortune:pyfortune/loader.py:Chooser.fromlist#18323"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/quantum5/pyfortune/blob/36b489b1000cb2f175b8f3b5919fed9a7214f736/pyfortune/loader.py#L88-L104", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:quantum5-pyfortune:Chooser.fromlist-abecf52132", "question": "Initialize based on a list of fortune files", "scope": {"holder": "quantum5-pyfortune", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:quantum5/pyfortune:pyfortune/loader.py:Chooser.set_chance#18324", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pyfortune/loader.py", "symbol": "Chooser.set_chance"}, "source_id": "csn:quantum5/pyfortune:pyfortune/loader.py:Chooser.set_chance#18324"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/quantum5/pyfortune/blob/36b489b1000cb2f175b8f3b5919fed9a7214f736/pyfortune/loader.py#L107-L145", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:quantum5-pyfortune:Chooser.set_chance-f79e00dddf", "question": "Initialize based on a list of fortune files with set chances", "scope": {"holder": "quantum5-pyfortune", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:rackerlabs/timid:timid/modifiers.py:ConditionalModifier.pre_call#21897", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "timid/modifiers.py", "symbol": "ConditionalModifier.pre_call"}, "source_id": "csn:rackerlabs/timid:timid/modifiers.py:ConditionalModifier.pre_call#21897"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/rackerlabs/timid/blob/b1c6aa159ab380a033740f4aa392cf0d125e0ac6/timid/modifiers.py#L61-L93", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:rackerlabs-timid:ConditionalModifier.pre_call-07df8a0862", "question": "A modifier hook function. This is called in priority order prior\n to invoking the ``Action`` for the step. This allows a\n modifier to alter the context, or to take over subsequent\n action invocation.\n\n :param ctxt: The context object.\n :param pre_mod: A list of the modifiers preceding this\n modifier in the list of modifiers that is\n applicable to the action. This list is in\n priority order.\n :param post_mod: A list of the modifiers following this\n modifier in the list of modifiers that is\n applicable to the action. This list is in\n priority order.\n :param action: The action that will be performed.\n\n :returns: A ``None`` return value indicates that the modifier\n is taking no action. A non-``None`` return value\n should consist of a ``StepResult`` object; this will\n suspend further ``pre_call()`` processing and\n proceed to the ``post_call()`` processing. This\n implementation returns a ``StepResult`` with state\n ``SKIPPED`` if the condition does not evaluate to\n ``True``.", "scope": {"holder": "rackerlabs-timid", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:rackerlabs/timid:timid/extensions.py:ExtensionSet.read_steps#21196", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "timid/extensions.py", "symbol": "ExtensionSet.read_steps"}, "source_id": "csn:rackerlabs/timid:timid/extensions.py:ExtensionSet.read_steps#21196"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/rackerlabs/timid/blob/b1c6aa159ab380a033740f4aa392cf0d125e0ac6/timid/extensions.py#L375-L393", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:rackerlabs-timid:ExtensionSet.read_steps-1779072992", "question": "Called after reading steps, prior to adding them to the list of\n test steps. Extensions are able to alter the list (in place).\n\n :param ctxt: An instance of ``timid.context.Context``.\n :param steps: A list of ``timid.steps.Step`` instances.\n\n :returns: The ``steps`` parameter, for convenience.", "scope": {"holder": "rackerlabs-timid", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:rainwoodman/bigfile:bigfile/__init__.py:FileMPI.create_from_array#14640", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "bigfile/__init__.py", "symbol": "FileMPI.create_from_array"}, "source_id": "csn:rainwoodman/bigfile:bigfile/__init__.py:FileMPI.create_from_array#14640"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/rainwoodman/bigfile/blob/1a2d05977fc8edebd8ddf9e81fdb97648596266d/bigfile/__init__.py#L221-L261", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:rainwoodman-bigfile:FileMPI.create_from_array-57aebcc175", "question": "create a block from array like objects\n The operation is well defined only if array is at most 2d.\n\n Parameters\n ----------\n array : array_like,\n array shall have a scalar dtype. \n blockname : string\n name of the block\n Nfile : int or None\n number of physical files. if None, 32M items per file\n is used.\n memorylimit : int\n number of bytes to use for the buffering. relevant only if\n indexing on array returns a copy (e.g. IO or dask array)", "scope": {"holder": "rainwoodman-bigfile", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:rainwoodman/bigfile:bigfile/__init__.py:FileMPI.refresh#14639", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "bigfile/__init__.py", "symbol": "FileMPI.refresh"}, "source_id": "csn:rainwoodman/bigfile:bigfile/__init__.py:FileMPI.refresh#14639"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/rainwoodman/bigfile/blob/1a2d05977fc8edebd8ddf9e81fdb97648596266d/bigfile/__init__.py#L199-L205", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:rainwoodman-bigfile:FileMPI.refresh-2fb6110326", "question": "Refresh the list of blocks to the disk, collectively", "scope": {"holder": "rainwoodman-bigfile", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:ralphbean/bugwarrior:bugwarrior/services/activecollab2.py:ActiveCollab2Client.get_issue_generator#6183", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "bugwarrior/services/activecollab2.py", "symbol": "ActiveCollab2Client.get_issue_generator"}, "source_id": "csn:ralphbean/bugwarrior:bugwarrior/services/activecollab2.py:ActiveCollab2Client.get_issue_generator#6183"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/ralphbean/bugwarrior/blob/b2a5108f7b40cb0c437509b64eaa28f941f7ac8b/bugwarrior/services/activecollab2.py#L46-L68", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:ralphbean-bugwarrior:ActiveCollab2Client.get_issue_generator-6bb8634d39", "question": "Approach:\n\n 1. Get user ID from bugwarriorrc file\n 2. Get list of tickets from /user-tasks for a given project\n 3. For each ticket/task returned from #2, get ticket/task info and\n check if logged-in user is primary (look at `is_owner` and\n `user_id`)", "scope": {"holder": "ralphbean-bugwarrior", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:ralphbean/bugwarrior:bugwarrior/services/trello.py:TrelloService.get_comments#6180", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "bugwarrior/services/trello.py", "symbol": "TrelloService.get_comments"}, "source_id": "csn:ralphbean/bugwarrior:bugwarrior/services/trello.py:TrelloService.get_comments#6180"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/ralphbean/bugwarrior/blob/b2a5108f7b40cb0c437509b64eaa28f941f7ac8b/bugwarrior/services/trello.py#L180-L188", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:ralphbean-bugwarrior:TrelloService.get_comments-60d1e0b22c", "question": "Returns an iterator for the comments on a certain card.", "scope": {"holder": "ralphbean-bugwarrior", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:raviparekh/webapp-error-handler:app_error_handler/application_error_handler.py:register_app_for_error_handling#19687", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "app_error_handler/application_error_handler.py", "symbol": "register_app_for_error_handling"}, "source_id": "csn:raviparekh/webapp-error-handler:app_error_handler/application_error_handler.py:register_app_for_error_handling#19687"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/raviparekh/webapp-error-handler/blob/11e20bea464331e254034b02661c53fb19102d4a/app_error_handler/application_error_handler.py#L9-L39", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:raviparekh-webapp-error-handler:register_app_for_error_handling-1696b0a315", "question": "Wraps a WSGI app and handles uncaught exceptions and defined exception and outputs a the exception in a\n structured format.\n Parameters:\n - wsgi_app is the app.wsgi_app of flask,\n - app_name should in correct format e.g. APP_NAME_1,\n - app_logger is the logger object", "scope": {"holder": "raviparekh-webapp-error-handler", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:rbarrois/aionotify:aionotify/aioutils.py:UnixFileDescriptorTransport._call_connection_lost#10449", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "aionotify/aioutils.py", "symbol": "UnixFileDescriptorTransport._call_connection_lost"}, "source_id": "csn:rbarrois/aionotify:aionotify/aioutils.py:UnixFileDescriptorTransport._call_connection_lost#10449"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/rbarrois/aionotify/blob/6cfa35b26a2660f77f29a92d3efb7d1dde685b43/aionotify/aioutils.py#L94-L102", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:rbarrois-aionotify:UnixFileDescriptorTransport._call_connection_lost-99e7237700", "question": "Finalize closing.", "scope": {"holder": "rbarrois-aionotify", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:rbarrois/aionotify:aionotify/base.py:Watcher.get_event#10454", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "aionotify/base.py", "symbol": "Watcher.get_event"}, "source_id": "csn:rbarrois/aionotify:aionotify/base.py:Watcher.get_event#10454"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/rbarrois/aionotify/blob/6cfa35b26a2660f77f29a92d3efb7d1dde685b43/aionotify/base.py#L109-L133", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:rbarrois-aionotify:Watcher.get_event-e6716d549f", "question": "Fetch an event.\n\n This coroutine will swallow events for removed watches.", "scope": {"holder": "rbarrois-aionotify", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:reflect/reflect-python:reflect/token.py:ProjectTokenBuilder.build#19408", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "reflect/token.py", "symbol": "ProjectTokenBuilder.build"}, "source_id": "csn:reflect/reflect-python:reflect/token.py:ProjectTokenBuilder.build#19408"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/reflect/reflect-python/blob/219a4400c1b9ace89009d1ab3dfa21790862d237/reflect/token.py#L73-L127", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:reflect-reflect-python:ProjectTokenBuilder.build-480804a831", "question": "Builds a final copy of the token using the given secret key.\n\n :param secret_key(string): The secret key that corresponds to this builder's access key.", "scope": {"holder": "reflect-reflect-python", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:regardscitoyens/cpc-api:cpc_api/api.py:CPCApi.synthese#18609", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "cpc_api/api.py", "symbol": "CPCApi.synthese"}, "source_id": "csn:regardscitoyens/cpc-api:cpc_api/api.py:CPCApi.synthese#18609"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/regardscitoyens/cpc-api/blob/4621dcbda3f3bb8fae1cc094fa58e054df24269d/cpc_api/api.py#L42-L55", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:regardscitoyens-cpc-api:CPCApi.synthese-db9c34a0cf", "question": "month format: YYYYMM", "scope": {"holder": "regardscitoyens-cpc-api", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:regebro/pyroma:pyroma/projectdata.py:get_data#8602", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pyroma/projectdata.py", "symbol": "get_data"}, "source_id": "csn:regebro/pyroma:pyroma/projectdata.py:get_data#8602"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/regebro/pyroma/blob/ddde9d90b95477209d88a015e43dcc083138f14a/pyroma/projectdata.py#L141-L172", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:regebro-pyroma:get_data-24dc9e9180", "question": "Returns data from a package directory.\n 'path' should be an absolute path.", "scope": {"holder": "regebro-pyroma", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:regebro/pyroma:pyroma/projectdata.py:run_setup#8601", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pyroma/projectdata.py", "symbol": "run_setup"}, "source_id": "csn:regebro/pyroma:pyroma/projectdata.py:run_setup#8601"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/regebro/pyroma/blob/ddde9d90b95477209d88a015e43dcc083138f14a/pyroma/projectdata.py#L74-L138", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:regebro-pyroma:run_setup-f83e397309", "question": "Run a setup script in a somewhat controlled environment, and\n return the Distribution instance that drives things. This is useful\n if you need to find out the distribution meta-data (passed as\n keyword args from 'script' to 'setup()', or the contents of the\n config files or command-line.\n\n 'script_name' is a file that will be run with 'execfile()';\n 'sys.argv[0]' will be replaced with 'script' for the duration of the\n call. 'script_args' is a list of strings; if supplied,\n 'sys.argv[1:]' will be replaced by 'script_args' for the duration of\n the call.\n\n 'stop_after' tells 'setup()' when to stop processing; possible\n values:\n init\n stop after the Distribution instance has been created and\n populated with the keyword arguments to 'setup()'\n config\n stop after config files have been parsed (and their data\n stored in the Distribution instance)\n commandline\n stop after the command-line ('sys.argv[1:]' or 'script_args')\n have been parsed (and the data stored in the Distribution)\n run [default]\n stop after all commands have been run (the same as if 'setup()'\n had been called in the usual way\n\n Returns the Distribution instance, which provides all information\n used to drive the Distutils.", "scope": {"holder": "regebro-pyroma", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:reingart/gui2py:gui/doc/ext/autosummary/__init__.py:Autosummary.get_table#13888", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "gui/doc/ext/autosummary/__init__.py", "symbol": "Autosummary.get_table"}, "source_id": "csn:reingart/gui2py:gui/doc/ext/autosummary/__init__.py:Autosummary.get_table#13888"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/reingart/gui2py/blob/aca0a05f6fcde55c94ad7cc058671a06608b01a4/gui/doc/ext/autosummary/__init__.py#L298-L340", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:reingart-gui2py:Autosummary.get_table-bfe987ea25", "question": "Generate a proper list of table nodes for autosummary:: directive.\n\n *items* is a list produced by :meth:`get_items`.", "scope": {"holder": "reingart-gui2py", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:reingart/gui2py:gui/tools/toolbox.py:ToolBox.set_default_tlw#13790", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "gui/tools/toolbox.py", "symbol": "ToolBox.set_default_tlw"}, "source_id": "csn:reingart/gui2py:gui/tools/toolbox.py:ToolBox.set_default_tlw#13790"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/reingart/gui2py/blob/aca0a05f6fcde55c94ad7cc058671a06608b01a4/gui/tools/toolbox.py#L133-L136", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:reingart-gui2py:ToolBox.set_default_tlw-b1087590c5", "question": "track default top level window for toolbox menu default action", "scope": {"holder": "reingart-gui2py", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:respondcreate/django-versatileimagefield:versatileimagefield/widgets.py:ClearableFileInputWithImagePreview.build_attrs#8570", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "versatileimagefield/widgets.py", "symbol": "ClearableFileInputWithImagePreview.build_attrs"}, "source_id": "csn:respondcreate/django-versatileimagefield:versatileimagefield/widgets.py:ClearableFileInputWithImagePreview.build_attrs#8570"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/respondcreate/django-versatileimagefield/blob/d41e279c39cccffafbe876c67596184704ae8877/versatileimagefield/widgets.py#L108-L113", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:respondcreate-django-versatileimagefield:ClearableFileInputWithImagePreview.build_attrs-e8743b3dfe", "question": "Build an attribute dictionary.", "scope": {"holder": "respondcreate-django-versatileimagefield", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:respondcreate/django-versatileimagefield:versatileimagefield/registry.py:VersatileImageFieldRegistry.unregister_sizer#8549", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "versatileimagefield/registry.py", "symbol": "VersatileImageFieldRegistry.unregister_sizer"}, "source_id": "csn:respondcreate/django-versatileimagefield:versatileimagefield/registry.py:VersatileImageFieldRegistry.unregister_sizer#8549"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/respondcreate/django-versatileimagefield/blob/d41e279c39cccffafbe876c67596184704ae8877/versatileimagefield/registry.py#L145-L157", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:respondcreate-django-versatileimagefield:VersatileImageFieldRegistry.unregister_sizer-92aca7af4d", "question": "Unregister the SizedImage subclass currently assigned to `attr_name`.\n\n If a SizedImage subclass isn't already registered to `attr_name`\n NotRegistered will raise.", "scope": {"holder": "respondcreate-django-versatileimagefield", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:ribalba/markdown.highlight:MarkdownHighlight/highlight.py:HighlightExtension.extendMarkdown#18074", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "MarkdownHighlight/highlight.py", "symbol": "HighlightExtension.extendMarkdown"}, "source_id": "csn:ribalba/markdown.highlight:MarkdownHighlight/highlight.py:HighlightExtension.extendMarkdown#18074"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/ribalba/markdown.highlight/blob/f220f3366dc5c42a3c303565cf7f297fce89098a/MarkdownHighlight/highlight.py#L15-L18", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:ribalba-markdown.highlight:HighlightExtension.extendMarkdown-e9d7d0b5ef", "question": "Modifies inline patterns.", "scope": {"holder": "ribalba-markdown.highlight", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:ricobl/django-importer:django_importer/importers/csv_importer.py:CSVImporter.get_value#13014", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "django_importer/importers/csv_importer.py", "symbol": "CSVImporter.get_value"}, "source_id": "csn:ricobl/django-importer:django_importer/importers/csv_importer.py:CSVImporter.get_value#13014"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/ricobl/django-importer/blob/6967adfa7a286be7aaf59d3f33c6637270bd9df6/django_importer/importers/csv_importer.py#L45-L53", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:ricobl-django-importer:CSVImporter.get_value-1622a1dd44", "question": "This method receives an item from the source and a source name,\n and returns the text content for the `source_name` node.", "scope": {"holder": "ricobl-django-importer", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:ricobl/django-importer:django_importer/importers/base.py:Importer.save_item#13010", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "django_importer/importers/base.py", "symbol": "Importer.save_item"}, "source_id": "csn:ricobl/django-importer:django_importer/importers/base.py:Importer.save_item#13010"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/ricobl/django-importer/blob/6967adfa7a286be7aaf59d3f33c6637270bd9df6/django_importer/importers/base.py#L127-L133", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:ricobl-django-importer:Importer.save_item-966fb70f20", "question": "Saves a model instance to the database.", "scope": {"holder": "ricobl-django-importer", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:riffm/mint:mint.py:base_tokenizer#15764", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "mint.py", "symbol": "base_tokenizer"}, "source_id": "csn:riffm/mint:mint.py:base_tokenizer#15764"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/riffm/mint/blob/db00855bbe9156d5ab281e00835af85a7958dd16/mint.py#L138-L196", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:riffm-mint:base_tokenizer-a6a1f06da2", "question": "Tokenizer. Generates tokens stream from text", "scope": {"holder": "riffm-mint", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:riffm/mint:mint.py:get_mint_tree#15765", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "mint.py", "symbol": "get_mint_tree"}, "source_id": "csn:riffm/mint:mint.py:get_mint_tree#15765"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/riffm/mint/blob/db00855bbe9156d5ab281e00835af85a7958dd16/mint.py#L1233-L1240", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:riffm-mint:get_mint_tree-33310a2b5d", "question": "This function is wrapper to normal parsers (tag_parser, block_parser, etc.).\n Returns mint tree.", "scope": {"holder": "riffm-mint", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:rochacon/punch:punch/app.py:App.serve#19750", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "punch/app.py", "symbol": "App.serve"}, "source_id": "csn:rochacon/punch:punch/app.py:App.serve#19750"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/rochacon/punch/blob/7f6fb81221049ab74ef561fb40a4174bdb3e77ef/punch/app.py#L70-L83", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:rochacon-punch:App.serve-72a88fb688", "question": "Serve app using wsgiref or provided server.\n\n Args:\n - server (callable): An callable", "scope": {"holder": "rochacon-punch", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:rochapps/django-secure-input:secure_input/widgets.py:WYSIWYGWidget.render#19381", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "secure_input/widgets.py", "symbol": "WYSIWYGWidget.render"}, "source_id": "csn:rochapps/django-secure-input:secure_input/widgets.py:WYSIWYGWidget.render#19381"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/rochapps/django-secure-input/blob/6da714475613870f2891b2ccf3317f55b3e81107/secure_input/widgets.py#L11-L15", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:rochapps-django-secure-input:WYSIWYGWidget.render-8cbdac114d", "question": "Include a hidden input to stored the serialized upload value.", "scope": {"holder": "rochapps-django-secure-input", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:rocky/pycolumnize:columnize.py:computed_displaywidth#19275", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "columnize.py", "symbol": "computed_displaywidth"}, "source_id": "csn:rocky/pycolumnize:columnize.py:computed_displaywidth#19275"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/rocky/pycolumnize/blob/4373faa989884d3a25f276f9bbb4911cc71eca17/columnize.py#L14-L23", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:rocky-pycolumnize:computed_displaywidth-1022c395e5", "question": "Figure out a reasonable default with. Use os.environ['COLUMNS'] if possible,\n and failing that use 80.", "scope": {"holder": "rocky-pycolumnize", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:rocky/python3-trepan:trepan/bwprocessor/main.py:BWProcessor._populate_cmd_lists#8959", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "trepan/bwprocessor/main.py", "symbol": "BWProcessor._populate_cmd_lists"}, "source_id": "csn:rocky/python3-trepan:trepan/bwprocessor/main.py:BWProcessor._populate_cmd_lists#8959"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/rocky/python3-trepan/blob/14e91bc0acce090d67be145b1ac040cab92ac5f3/trepan/bwprocessor/main.py#L447-L454", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:rocky-python3-trepan:BWProcessor._populate_cmd_lists-388b02227e", "question": "Populate self.commands", "scope": {"holder": "rocky-python3-trepan", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:rocky/python3-trepan:trepan/inout/tcpclient.py:TCPClient.read_msg#8915", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "trepan/inout/tcpclient.py", "symbol": "TCPClient.read_msg"}, "source_id": "csn:rocky/python3-trepan:trepan/inout/tcpclient.py:TCPClient.read_msg#8915"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/rocky/python3-trepan/blob/14e91bc0acce090d67be145b1ac040cab92ac5f3/trepan/inout/tcpclient.py#L84-L100", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:rocky-python3-trepan:TCPClient.read_msg-dc826b1257", "question": "Read one message unit. It's possible however that\n more than one message will be set in a receive, so we will\n have to buffer that for the next read.\n EOFError will be raised on EOF.", "scope": {"holder": "rocky-python3-trepan", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:rodluger/pysyzygy:pysyzygy/plot.py:I#18215", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pysyzygy/plot.py", "symbol": "I"}, "source_id": "csn:rodluger/pysyzygy:pysyzygy/plot.py:I#18215"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/rodluger/pysyzygy/blob/d2b64251047cc0f0d0adeb6feab4054e7fce4b7a/pysyzygy/plot.py#L30-L55", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:rodluger-pysyzygy:I-cf9d968e79", "question": "The standard quadratic limb darkening law.\n \n :param ndarray r: The radius vector\n :param limbdark: A :py:class:`pysyzygy.transit.LIMBDARK` instance containing \n the limb darkening law information\n \n :returns: The stellar intensity as a function of `r`", "scope": {"holder": "rodluger-pysyzygy", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:rodluger/pysyzygy:pysyzygy/transit.py:Transit.Bin#18174", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pysyzygy/transit.py", "symbol": "Transit.Bin"}, "source_id": "csn:rodluger/pysyzygy:pysyzygy/transit.py:Transit.Bin#18174"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/rodluger/pysyzygy/blob/d2b64251047cc0f0d0adeb6feab4054e7fce4b7a/pysyzygy/transit.py#L537-L544", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:rodluger-pysyzygy:Transit.Bin-6bc5e53190", "question": "Bins the light curve model to the provided time array", "scope": {"holder": "rodluger-pysyzygy", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:rollbar/pyrollbar:rollbar/contrib/django/middleware.py:RollbarNotifierMiddleware._ensure_log_handler#5394", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "rollbar/contrib/django/middleware.py", "symbol": "RollbarNotifierMiddleware._ensure_log_handler"}, "source_id": "csn:rollbar/pyrollbar:rollbar/contrib/django/middleware.py:RollbarNotifierMiddleware._ensure_log_handler#5394"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/rollbar/pyrollbar/blob/33ef2e723a33d09dd6302f978f4a3908be95b9d2/rollbar/contrib/django/middleware.py#L236-L246", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:rollbar-pyrollbar:RollbarNotifierMiddleware._ensure_log_handler-8377b18310", "question": "If there's no log configuration, set up a default handler.", "scope": {"holder": "rollbar-pyrollbar", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:rollbar/pyrollbar:rollbar/__init__.py:_report_message#5404", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "rollbar/__init__.py", "symbol": "_report_message"}, "source_id": "csn:rollbar/pyrollbar:rollbar/__init__.py:_report_message#5404"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/rollbar/pyrollbar/blob/33ef2e723a33d09dd6302f978f4a3908be95b9d2/rollbar/__init__.py#L727-L768", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:rollbar-pyrollbar:_report_message-96d788010f", "question": "Called by report_message() wrapper", "scope": {"holder": "rollbar-pyrollbar", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:rsennrich/Bleualign:bleualign/gale_church.py:align_blocks#5278", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "bleualign/gale_church.py", "symbol": "align_blocks"}, "source_id": "csn:rsennrich/Bleualign:bleualign/gale_church.py:align_blocks#5278"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/rsennrich/Bleualign/blob/1de181dcc3257d885a2b981f751c0220c0e8958f/bleualign/gale_church.py#L97-L146", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:rsennrich-Bleualign:align_blocks-f647233eb6", "question": "Creates the sentence alignment of two blocks of texts (usually paragraphs).\n\n @param source_sentences: The list of source sentence lengths.\n @param target_sentences: The list of target sentence lengths.\n @param params: the sentence alignment parameters.\n\n @return: The sentence alignments, a list of index pairs.", "scope": {"holder": "rsennrich-Bleualign", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:rsennrich/Bleualign:bleualign/score.py:cook_refs#5274", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "bleualign/score.py", "symbol": "cook_refs"}, "source_id": "csn:rsennrich/Bleualign:bleualign/score.py:cook_refs#5274"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/rsennrich/Bleualign/blob/1de181dcc3257d885a2b981f751c0220c0e8958f/bleualign/score.py#L74-L85", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:rsennrich-Bleualign:cook_refs-af8f133112", "question": "Takes a list of reference sentences for a single segment\n and returns an object that encapsulates everything that BLEU\n needs to know about them.", "scope": {"holder": "rsennrich-Bleualign", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:rupertford/melody:src/melody/main.py:Melody.search#19086", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "src/melody/main.py", "symbol": "Melody.search"}, "source_id": "csn:rupertford/melody:src/melody/main.py:Melody.search#19086"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/rupertford/melody/blob/d50459880a87fdd1802c6893f6e12b52d51b3b91/src/melody/main.py#L79-L84", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:rupertford-melody:Melody.search-b5e0a2ffb9", "question": "Start the optimisation/search using the supplied optimisation\n method with the supplied inputs for the supplied function", "scope": {"holder": "rupertford-melody", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:rupertford/melody:src/melody/inputs.py:create_input#19152", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "src/melody/inputs.py", "symbol": "create_input"}, "source_id": "csn:rupertford/melody:src/melody/inputs.py:create_input#19152"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/rupertford/melody/blob/d50459880a87fdd1802c6893f6e12b52d51b3b91/src/melody/inputs.py#L155-L180", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:rupertford-melody:create_input-b20087f746", "question": "create an input file using jinja2 by filling a template\n with the values from the option variable passed in.", "scope": {"holder": "rupertford-melody", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:rwl/godot:godot/common.py:Alias#16371", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "godot/common.py", "symbol": "Alias"}, "source_id": "csn:rwl/godot:godot/common.py:Alias#16371"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/rwl/godot/blob/013687c9e8983d2aa2ceebb8a76c5c4f1e37c90f/godot/common.py#L40-L52", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:rwl-godot:Alias-d903116147", "question": "Syntactically concise alias trait but creates a pair of lambda\n functions for every alias you declare.\n\n class MyClass(HasTraits):\n line_width = Float(3.0)\n thickness = Alias(\"line_width\")", "scope": {"holder": "rwl-godot", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:rwl/godot:godot/ui/graph_view_model.py:GraphViewModel.configure_graph#16353", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "godot/ui/graph_view_model.py", "symbol": "GraphViewModel.configure_graph"}, "source_id": "csn:rwl/godot:godot/ui/graph_view_model.py:GraphViewModel.configure_graph#16353"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/rwl/godot/blob/013687c9e8983d2aa2ceebb8a76c5c4f1e37c90f/godot/ui/graph_view_model.py#L303-L308", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:rwl-godot:GraphViewModel.configure_graph-519a2c90ac", "question": "Handles display of the graph dot traits.", "scope": {"holder": "rwl-godot", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:sagemath/sage-package:sage_package/sphinx.py:setup#18165", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "sage_package/sphinx.py", "symbol": "setup"}, "source_id": "csn:sagemath/sage-package:sage_package/sphinx.py:setup#18165"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/sagemath/sage-package/blob/6e511753fb0667b202f497fc00b763647456a066/sage_package/sphinx.py#L37-L70", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:sagemath-sage-package:setup-7e94c57b4c", "question": "Initialize this Sphinx extension", "scope": {"holder": "sagemath-sage-package", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:salsita/flask-raml:setup.py:init#17037", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "setup.py", "symbol": "init"}, "source_id": "csn:salsita/flask-raml:setup.py:init#17037"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/salsita/flask-raml/blob/9876f19d49401fa32f7d852239aa295a78149ab2/setup.py#L86-L141", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:salsita-flask-raml:init-b55136426d", "question": "Imports and returns a setup function.\n\n If use_markdown_readme is set,\n then README.md is added to setuptools READMES list.\n\n If use_stdeb is set on a Debian based system,\n then module stdeb is imported.\n Stdeb supports building deb packages on Debian based systems.\n The package should only be installed on the same system version\n it was built on, though. See http://github.com/astraw/stdeb.\n\n If use_distribute is set, then distribute_setup.py is imported.", "scope": {"holder": "salsita-flask-raml", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:salsita/flask-raml:setup.py:main#17036", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "setup.py", "symbol": "main"}, "source_id": "csn:salsita/flask-raml:setup.py:main#17036"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/salsita/flask-raml/blob/9876f19d49401fa32f7d852239aa295a78149ab2/setup.py#L82-L84", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:salsita-flask-raml:main-7f430368ce", "question": "Imports and runs setup function with given properties.", "scope": {"holder": "salsita-flask-raml", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:savoirfairelinux/num2words:num2words/base.py:Num2Word_Base.to_currency#4681", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "num2words/base.py", "symbol": "Num2Word_Base.to_currency"}, "source_id": "csn:savoirfairelinux/num2words:num2words/base.py:Num2Word_Base.to_currency#4681"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/savoirfairelinux/num2words/blob/f4b2bac098ae8e4850cf2f185f6ff52a5979641f/num2words/base.py#L266-L303", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:savoirfairelinux-num2words:Num2Word_Base.to_currency-c9c47b3f07", "question": "Args:\n val: Numeric value\n currency (str): Currency code\n cents (bool): Verbose cents\n separator (str): Cent separator\n adjective (bool): Prefix currency name with adjective\n Returns:\n str: Formatted string", "scope": {"holder": "savoirfairelinux-num2words", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:savoirfairelinux/num2words:num2words/lang_ID.py:Num2Word_ID.split_by_3#4678", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "num2words/lang_ID.py", "symbol": "Num2Word_ID.split_by_3"}, "source_id": "csn:savoirfairelinux/num2words:num2words/lang_ID.py:Num2Word_ID.split_by_3#4678"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/savoirfairelinux/num2words/blob/f4b2bac098ae8e4850cf2f185f6ff52a5979641f/num2words/lang_ID.py#L53-L76", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:savoirfairelinux-num2words:Num2Word_ID.split_by_3-d35cf51617", "question": "starting here, it groups the number by three from the tail\n '1234567' -> (('1',),('234',),('567',))\n :param number:str\n :rtype:tuple", "scope": {"holder": "savoirfairelinux-num2words", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:saxix/sample-data-utils:sample_data_utils/utils.py:_get_memoized_value#19487", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "sample_data_utils/utils.py", "symbol": "_get_memoized_value"}, "source_id": "csn:saxix/sample-data-utils:sample_data_utils/utils.py:_get_memoized_value#19487"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/saxix/sample-data-utils/blob/769f1b46e60def2675a14bd5872047af6d1ea398/sample_data_utils/utils.py#L42-L50", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:saxix-sample-data-utils:_get_memoized_value-898d7c4494", "question": "Used internally by memoize decorator to get/store function results", "scope": {"holder": "saxix-sample-data-utils", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:saxix/sample-data-utils:sample_data_utils/net.py:ipaddress#19479", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "sample_data_utils/net.py", "symbol": "ipaddress"}, "source_id": "csn:saxix/sample-data-utils:sample_data_utils/net.py:ipaddress#19479"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/saxix/sample-data-utils/blob/769f1b46e60def2675a14bd5872047af6d1ea398/sample_data_utils/net.py#L13-L26", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:saxix-sample-data-utils:ipaddress-7f3544778a", "question": "returns a string representing a random ip address\n\n :param not_valid: if passed must be a list of integers representing valid class A netoworks that must be ignored", "scope": {"holder": "saxix-sample-data-utils", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:sbneto/s3conf:s3conf/client.py:diff#13751", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "s3conf/client.py", "symbol": "diff"}, "source_id": "csn:sbneto/s3conf:s3conf/client.py:diff#13751"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/sbneto/s3conf/blob/92fd2973beccc85bb21d3157ff227929e62ed695/s3conf/client.py#L259-L272", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:sbneto-s3conf:diff-51a4ebc566", "question": "For each section defined in the local config file, look up for a folder inside the local config folder\n named after the section. Uploads the environemnt file named as in the S3CONF variable for this section\n to the remote S3CONF path.", "scope": {"holder": "sbneto-s3conf", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:sbneto/s3conf:s3conf/client.py:init#13754", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "s3conf/client.py", "symbol": "init"}, "source_id": "csn:sbneto/s3conf:s3conf/client.py:init#13754"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/sbneto/s3conf/blob/92fd2973beccc85bb21d3157ff227929e62ed695/s3conf/client.py#L333-L350", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:sbneto-s3conf:init-82f78ffc67", "question": "Creates the .s3conf config folder and .s3conf/config config file\n with the provided section name and configuration file. It is a very\n basic config file. Manually edit it in order to add credentials. E.g.:\n\n s3conf init development s3://my-project/development.env", "scope": {"holder": "sbneto-s3conf", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:scheibler/khard:khard/actions.py:Actions.get_action#8680", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "khard/actions.py", "symbol": "Actions.get_action"}, "source_id": "csn:scheibler/khard:khard/actions.py:Actions.get_action#8680"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/scheibler/khard/blob/0f69430c2680f1ff5f073a977a3c5b753b96cc17/khard/actions.py#L30-L43", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:scheibler-khard:Actions.get_action-f2b3064d13", "question": "Find the name of the action for the supplied alias. If no action is\n asociated with the given alias, None is returned.\n\n :param alias: the alias to look up\n :type alias: str\n :rturns: the name of the corresponding action or None\n :rtype: str or NoneType", "scope": {"holder": "scheibler-khard", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:scheibler/khard:khard/carddav_object.py:CarddavObject.get_post_addresses#8694", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "khard/carddav_object.py", "symbol": "CarddavObject.get_post_addresses"}, "source_id": "csn:scheibler/khard:khard/carddav_object.py:CarddavObject.get_post_addresses#8694"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/scheibler/khard/blob/0f69430c2680f1ff5f073a977a3c5b753b96cc17/khard/carddav_object.py#L468-L495", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:scheibler-khard:CarddavObject.get_post_addresses-bc4c342d6e", "question": ": returns: dict of type and post address list\n :rtype: dict(str, list(dict(str,list|str)))", "scope": {"holder": "scheibler-khard", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:schul-cloud/resources-api-v1:generators/python_client/schul_cloud_resources_api_v1/schema/__init__.py:Schema.get_invalid_examples#13766", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "generators/python_client/schul_cloud_resources_api_v1/schema/__init__.py", "symbol": "Schema.get_invalid_examples"}, "source_id": "csn:schul-cloud/resources-api-v1:generators/python_client/schul_cloud_resources_api_v1/schema/__init__.py:Schema.get_invalid_examples#13766"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/schul-cloud/resources-api-v1/blob/58b2d7ba13669fa013ef81c0ffcffbf6b3fdb52d/generators/python_client/schul_cloud_resources_api_v1/schema/__init__.py#L80-L83", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:schul-cloud-resources-api-v1:Schema.get_invalid_examples-4f3b8f3969", "question": "Return a list of examples which violate the schema.", "scope": {"holder": "schul-cloud-resources-api-v1", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:schul-cloud/resources-api-v1:generators/python_client/schul_cloud_resources_api_v1/schema/__init__.py:Schema.validate#13764", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "generators/python_client/schul_cloud_resources_api_v1/schema/__init__.py", "symbol": "Schema.validate"}, "source_id": "csn:schul-cloud/resources-api-v1:generators/python_client/schul_cloud_resources_api_v1/schema/__init__.py:Schema.validate#13764"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/schul-cloud/resources-api-v1/blob/58b2d7ba13669fa013ef81c0ffcffbf6b3fdb52d/generators/python_client/schul_cloud_resources_api_v1/schema/__init__.py#L57-L65", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:schul-cloud-resources-api-v1:Schema.validate-c75861e997", "question": "Validate an object against the schema.\n\n This function just passes if the schema matches the object.\n If the object does not match the schema, a ValidationException is raised.\n This error allows debugging.", "scope": {"holder": "schul-cloud-resources-api-v1", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:scrapinghub/dateparser:dateparser/date.py:DateDataParser.get_date_data#4416", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "dateparser/date.py", "symbol": "DateDataParser.get_date_data"}, "source_id": "csn:scrapinghub/dateparser:dateparser/date.py:DateDataParser.get_date_data#4416"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/scrapinghub/dateparser/blob/11a761c99d3ee522a3c63756b70c106a579e8b5c/dateparser/date.py#L354-L418", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:scrapinghub-dateparser:DateDataParser.get_date_data-afd4298bfe", "question": "Parse string representing date and/or time in recognizable localized formats.\n Supports parsing multiple languages and timezones.\n\n :param date_string:\n A string representing date and/or time in a recognizably valid format.\n :type date_string: str|unicode\n :param date_formats:\n A list of format strings using directives as given\n `here <https://docs.python.org/2/library/datetime.html#strftime-and-strptime-behavior>`_.\n The parser applies formats one by one, taking into account the detected languages.\n :type date_formats: list\n\n :return: a dict mapping keys to :mod:`datetime.datetime` object and *period*. For example:\n {'date_obj': datetime.datetime(2015, 6, 1, 0, 0), 'period': u'day'}\n\n :raises: ValueError - Unknown Language\n\n .. note:: *Period* values can be a 'day' (default), 'week', 'month', 'year'.\n\n *Period* represents the granularity of date parsed from the given string.\n\n In the example below, since no day information is present, the day is assumed to be current\n day ``16`` from *current date* (which is June 16, 2015, at the moment of writing this).\n Hence, the level of precision is ``month``:\n\n >>> DateDataParser().get_date_data(u'March 2015')\n {'date_obj': datetime.datetime(2015, 3, 16, 0, 0), 'period': u'month'}\n\n Similarly, for date strings with no day and month information present, level of precision\n is ``year`` and day ``16`` and month ``6`` are from *current_date*.\n\n >>> DateDataParser().get_date_data(u'2014')\n {'date_obj': datetime.datetime(2014, 6, 16, 0, 0), 'period': u'year'}\n\n Dates with time zone indications or UTC offsets are returned in UTC time unless\n specified using `Settings`_.\n\n >>> DateDataParser().get_date_data(u'23 March 2000, 1:21 PM CET')\n {'date_obj': datetime.datetime(2000, 3, 23, 14, 21), 'period': 'day'}", "scope": {"holder": "scrapinghub-dateparser", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:scrapinghub/dateparser:dateparser/languages/loader.py:LocaleDataLoader.get_locale_map#4406", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "dateparser/languages/loader.py", "symbol": "LocaleDataLoader.get_locale_map"}, "source_id": "csn:scrapinghub/dateparser:dateparser/languages/loader.py:LocaleDataLoader.get_locale_map#4406"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/scrapinghub/dateparser/blob/11a761c99d3ee522a3c63756b70c106a579e8b5c/dateparser/languages/loader.py#L48-L83", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:scrapinghub-dateparser:LocaleDataLoader.get_locale_map-119e96fb66", "question": "Get an ordered mapping with locale codes as keys\n and corresponding locale instances as values.\n\n :param languages:\n A list of language codes, e.g. ['en', 'es', 'zh-Hant'].\n If locales are not given, languages and region are\n used to construct locales to load.\n :type languages: list\n\n :param locales:\n A list of codes of locales which are to be loaded,\n e.g. ['fr-PF', 'qu-EC', 'af-NA']\n :type locales: list\n\n :param region:\n A region code, e.g. 'IN', '001', 'NE'.\n If locales are not given, languages and region are\n used to construct locales to load.\n :type region: str|unicode\n\n :param use_given_order:\n If True, the returned mapping is ordered in the order locales are given.\n :type allow_redetect_language: bool\n\n :param allow_conflicting_locales:\n if True, locales with same language and different region can be loaded.\n :type allow_conflicting_locales: bool\n\n :return: ordered locale code to locale instance mapping", "scope": {"holder": "scrapinghub-dateparser", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:seiferma/deterministic_encryption_utils:deterministic_encryption_utils/encryption/Padding.py:unpad#19662", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "deterministic_encryption_utils/encryption/Padding.py", "symbol": "unpad"}, "source_id": "csn:seiferma/deterministic_encryption_utils:deterministic_encryption_utils/encryption/Padding.py:unpad#19662"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/seiferma/deterministic_encryption_utils/blob/a747da3cd6daf39b0c26d4d497725e8863af1dd1/deterministic_encryption_utils/encryption/Padding.py#L64-L102", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:seiferma-deterministic_encryption_utils:unpad-ef0b436fa7", "question": "Remove standard padding.\n\n :Parameters:\n padded_data : byte string\n A piece of data with padding that needs to be stripped.\n block_size : integer\n The block boundary to use for padding. The input length\n must be a multiple of ``block_size``.\n style : string\n Padding algorithm. It can be *'pkcs7'* (default), *'iso7816'* or *'x923'*.\n :Return:\n Data without padding.\n :Raises ValueError:\n if the padding is incorrect.", "scope": {"holder": "seiferma-deterministic_encryption_utils", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:seporaitis/mysqlparse:mysqlparse/__init__.py:parse#14828", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "mysqlparse/__init__.py", "symbol": "parse"}, "source_id": "csn:seporaitis/mysqlparse:mysqlparse/__init__.py:parse#14828"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/seporaitis/mysqlparse/blob/c327c5a1d8d6d143b67f789be7dc80357a1a5556/mysqlparse/__init__.py#L11-L29", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:seporaitis-mysqlparse:parse-1751fb3301", "question": "Parse a file-like object or string.\n\n Args:\n file_or_string (file, str): File-like object or string.\n\n Returns:\n ParseResults: instance of pyparsing parse results.", "scope": {"holder": "seporaitis-mysqlparse", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:sergedomk/fiql_parser:fiql_parser/expression.py:BaseExpression.get_parent#13465", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "fiql_parser/expression.py", "symbol": "BaseExpression.get_parent"}, "source_id": "csn:sergedomk/fiql_parser:fiql_parser/expression.py:BaseExpression.get_parent#13465"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/sergedomk/fiql_parser/blob/499dd7cd0741603530ce5f3803d92813e74ac9c3/fiql_parser/expression.py#L58-L70", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:sergedomk-fiql_parser:BaseExpression.get_parent-f4bb727bb9", "question": "Get the parent ``Expression`` for this object.\n\n Returns:\n Expression: The ``Expression`` which contains this object.\n\n Raises:\n FiqlObjectException: Parent is ``None``.", "scope": {"holder": "sergedomk-fiql_parser", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:sergedomk/fiql_parser:fiql_parser/expression.py:Expression.add_operator#13466", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "fiql_parser/expression.py", "symbol": "Expression.add_operator"}, "source_id": "csn:sergedomk/fiql_parser:fiql_parser/expression.py:Expression.add_operator#13466"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/sergedomk/fiql_parser/blob/499dd7cd0741603530ce5f3803d92813e74ac9c3/fiql_parser/expression.py#L118-L166", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:sergedomk-fiql_parser:Expression.add_operator-983e7d8b86", "question": "Add an ``Operator`` to the ``Expression``.\n\n The ``Operator`` may result in a new ``Expression`` if an ``Operator``\n already exists and is of a different precedence.\n\n There are three possibilities when adding an ``Operator`` to an\n ``Expression`` depending on whether or not an ``Operator`` already\n exists:\n\n - No ``Operator`` on the working ``Expression``; Simply set the\n ``Operator`` and return ``self``.\n - ``Operator`` already exists and is higher in precedence; The\n ``Operator`` and last ``Constraint`` belong in a sub-expression of\n the working ``Expression``.\n - ``Operator`` already exists and is lower in precedence; The\n ``Operator`` belongs to the parent of the working ``Expression``\n whether one currently exists or not. To remain in the context of\n the top ``Expression``, this method will return the parent here\n rather than ``self``.\n\n Args:\n operator (Operator): What we are adding.\n\n Returns:\n Expression: ``self`` or related ``Expression``.\n\n Raises:\n FiqlObjectExpression: Operator is not a valid ``Operator``.", "scope": {"holder": "sergedomk-fiql_parser", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:sergei-maertens/django-systemjs:systemjs/management/commands/systemjs_bundle.py:Command.log#13508", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "systemjs/management/commands/systemjs_bundle.py", "symbol": "Command.log"}, "source_id": "csn:sergei-maertens/django-systemjs:systemjs/management/commands/systemjs_bundle.py:Command.log#13508"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/sergei-maertens/django-systemjs/blob/efd4a3862a39d9771609a25a5556f36023cf6e5c/systemjs/management/commands/systemjs_bundle.py#L26-L31", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:sergei-maertens-django-systemjs:Command.log-61294fd5c5", "question": "Small log helper", "scope": {"holder": "sergei-maertens-django-systemjs", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:sergei-maertens/django-systemjs:systemjs/templatetags/system_tags.py:SystemImportNode.render#13576", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "systemjs/templatetags/system_tags.py", "symbol": "SystemImportNode.render"}, "source_id": "csn:sergei-maertens/django-systemjs:systemjs/templatetags/system_tags.py:SystemImportNode.render#13576"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/sergei-maertens/django-systemjs/blob/efd4a3862a39d9771609a25a5556f36023cf6e5c/systemjs/templatetags/system_tags.py#L27-L56", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:sergei-maertens-django-systemjs:SystemImportNode.render-b848723da0", "question": "Build the filepath by appending the extension.", "scope": {"holder": "sergei-maertens-django-systemjs", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:shanbay/sea:sea/app.py:BaseApp._register_extension#6987", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "sea/app.py", "symbol": "BaseApp._register_extension"}, "source_id": "csn:shanbay/sea:sea/app.py:BaseApp._register_extension#6987"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/shanbay/sea/blob/a4484a571e3d68cc333411264077a59ea20cc5f1/sea/app.py#L96-L106", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:shanbay-sea:BaseApp._register_extension-111b7b7fb1", "question": "register extension\n\n :param name: extension name\n :param ext: extension object", "scope": {"holder": "shanbay-sea", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:shanbay/sea:sea/app.py:BaseApp._register_servicer#6986", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "sea/app.py", "symbol": "BaseApp._register_servicer"}, "source_id": "csn:shanbay/sea:sea/app.py:BaseApp._register_servicer#6986"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/shanbay/sea/blob/a4484a571e3d68cc333411264077a59ea20cc5f1/sea/app.py#L78-L88", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:shanbay-sea:BaseApp._register_servicer-34dde980f2", "question": "register serviser\n\n :param servicer: servicer", "scope": {"holder": "shanbay-sea", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:shaunduncan/giphypop:giphypop.py:Giphy._fetch#17168", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "giphypop.py", "symbol": "Giphy._fetch"}, "source_id": "csn:shaunduncan/giphypop:giphypop.py:Giphy._fetch#17168"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/shaunduncan/giphypop/blob/21e7f51c4f000ae24be3805b7eeec52bcce3d390/giphypop.py#L256-L268", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:shaunduncan-giphypop:Giphy._fetch-bb845d1f82", "question": "Wrapper for making an api request from giphy", "scope": {"holder": "shaunduncan-giphypop", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:shaunduncan/giphypop:giphypop.py:GiphyImage._make_images#17166", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "giphypop.py", "symbol": "GiphyImage._make_images"}, "source_id": "csn:shaunduncan/giphypop:giphypop.py:GiphyImage._make_images#17166"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/shaunduncan/giphypop/blob/21e7f51c4f000ae24be3805b7eeec52bcce3d390/giphypop.py#L164-L204", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:shaunduncan-giphypop:GiphyImage._make_images-5781877abf", "question": "Takes an image dict from the giphy api and converts it to attributes.\n Any fields expected to be int (width, height, size, frames) will be attempted\n to be converted. Also, the keys of `data` serve as the attribute names, but\n with special action taken. Keys are split by the last underscore; anything prior\n becomes the attribute name, anything after becomes a sub-attribute. For example:\n fixed_width_downsampled will end up at `self.fixed_width.downsampled`", "scope": {"holder": "shaunduncan-giphypop", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:shopkick/flawless:flawless/server/service.py:FlawlessServiceBaseClass._blame_line#12979", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "flawless/server/service.py", "symbol": "FlawlessServiceBaseClass._blame_line"}, "source_id": "csn:shopkick/flawless:flawless/server/service.py:FlawlessServiceBaseClass._blame_line#12979"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/shopkick/flawless/blob/c54b63ca1991c153e6f75080536f6df445aacc64/flawless/server/service.py#L189-L206", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:shopkick-flawless:FlawlessServiceBaseClass._blame_line-e762419298", "question": "Figures out which line in traceback is to blame for the error.\n Returns a 3-tuple of (ErrorKey, StackTraceEntry, [email recipients])", "scope": {"holder": "shopkick-flawless", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:shopkick/flawless:setup.py:markdown_to_reST#12983", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "setup.py", "symbol": "markdown_to_reST"}, "source_id": "csn:shopkick/flawless:setup.py:markdown_to_reST#12983"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/shopkick/flawless/blob/c54b63ca1991c153e6f75080536f6df445aacc64/setup.py#L19-L35", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:shopkick-flawless:markdown_to_reST-e1f227e8ec", "question": "This is not a general purpose converter. Only converts this readme", "scope": {"holder": "shopkick-flawless", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:siddhantgoel/tornado-sqlalchemy:tornado_sqlalchemy/__init__.py:_AsyncExecution.as_future#9012", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "tornado_sqlalchemy/__init__.py", "symbol": "_AsyncExecution.as_future"}, "source_id": "csn:siddhantgoel/tornado-sqlalchemy:tornado_sqlalchemy/__init__.py:_AsyncExecution.as_future#9012"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/siddhantgoel/tornado-sqlalchemy/blob/3e622b5a2be57b505599b98156540b52a8a5cf4e/tornado_sqlalchemy/__init__.py#L47-L80", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:siddhantgoel-tornado-sqlalchemy:_AsyncExecution.as_future-dcdcca62e9", "question": "Wrap a `sqlalchemy.orm.query.Query` object into a\n `concurrent.futures.Future` so that it can be yielded.\n\n Parameters\n ----------\n query : sqlalchemy.orm.query.Query\n SQLAlchemy query object to execute\n\n Returns\n -------\n tornado.concurrent.Future\n A `Future` object wrapping the given query so that tornado can\n await/yield on it", "scope": {"holder": "siddhantgoel-tornado-sqlalchemy", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:sigmaris/python-gssapi:gssapi/ctx.py:AcceptContext.step#17027", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "gssapi/ctx.py", "symbol": "AcceptContext.step"}, "source_id": "csn:sigmaris/python-gssapi:gssapi/ctx.py:AcceptContext.step#17027"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/sigmaris/python-gssapi/blob/a8ca577b3ccf9d9fa48f16f4954a1eddd5896236/gssapi/ctx.py#L865-L951", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:sigmaris-python-gssapi:AcceptContext.step-db226f4824", "question": "Performs a step to establish the context as an acceptor.\n\n This method should be called in a loop and fed input tokens from the initiator, and its\n output tokens should be sent to the initiator, until this context's :attr:`established`\n attribute is True.\n\n :param input_token: The input token from the initiator (required).\n :type input_token: bytes\n :returns: either a byte string with the next token to send to the initiator,\n or None if there is no further token to send to the initiator.\n :raises: :exc:`~gssapi.error.GSSException` if there is an error establishing the context.", "scope": {"holder": "sigmaris-python-gssapi", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:sigmaris/python-gssapi:gssapi/ctx.py:Context.verify_mic#17017", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "gssapi/ctx.py", "symbol": "Context.verify_mic"}, "source_id": "csn:sigmaris/python-gssapi:gssapi/ctx.py:Context.verify_mic#17017"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/sigmaris/python-gssapi/blob/a8ca577b3ccf9d9fa48f16f4954a1eddd5896236/gssapi/ctx.py#L199-L271", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:sigmaris-python-gssapi:Context.verify_mic-a10d550fb1", "question": "Takes a message integrity code (MIC) that has been generated by the peer application for a\n given message, and verifies it against a message, using this security context's\n cryptographic keys.\n\n The `supplementary` parameter determines how this method deals with replayed, unsequential,\n too-old or missing tokens, as follows:\n\n If the `supplementary` parameter is False (the default), and if a replayed or otherwise\n out-of-sequence token is detected, this method raises a :exc:`~gssapi.error.GSSCException`.\n If no replay or out-of-sequence token is detected, this method does not raise an exception\n and returns the ``qop_state`` only.\n\n If `supplementary` is True, instead of raising an exception when a replayed or\n out-of-sequence token is detected, this method returns a tuple\n ``(qop_state, supplementary_info)`` where ``supplementary_info`` is a tuple containing zero\n or more of the constants :const:`~gssapi.S_DUPLICATE_TOKEN`, :const:`~gssapi.S_OLD_TOKEN`,\n :const:`~gssapi.S_UNSEQ_TOKEN` and :const:`~gssapi.S_GAP_TOKEN`. The supplementary info\n tells the caller whether a replayed or out-of-sequence message was detected. The caller\n must check this and decide how to handle the message if any of the flags are set. For a\n reference to the meaning of the flags, check\n `RFC 2744 Section 3.9.1 <http://tools.ietf.org/html/rfc2744#section-3.9.1>` for the\n corresponding GSS_S_OLD_TOKEN, etc, constants.\n\n :param message: The message the MIC was calculated for\n :type message: bytes\n :param mic: The MIC calculated by the peer\n :type mic: bytes\n :param supplementary: Whether to also return supplementary info.\n :type supplementary: bool\n :returns: ``qop_state`` if `supplementary` is False, or ``(qop_state,\n supplementary_info)`` if `supplementary` is True.\n :raises: :exc:`~gssapi.error.GSSException` if :attr:`integrity_negotiated` is false, or\n :exc:`~gssapi.error.GSSCException` if the verification fails indicating the message was\n modified, replayed or out-of-sequence.", "scope": {"holder": "sigmaris-python-gssapi", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:simion/pip-upgrader:pip_upgrader/packages_status_detector.py:PackagesStatusDetector._parse_pypi_json_package_info#9445", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pip_upgrader/packages_status_detector.py", "symbol": "PackagesStatusDetector._parse_pypi_json_package_info"}, "source_id": "csn:simion/pip-upgrader:pip_upgrader/packages_status_detector.py:PackagesStatusDetector._parse_pypi_json_package_info#9445"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/simion/pip-upgrader/blob/716adca65d9ed56d4d416f94ede8a8e4fa8d640a/pip_upgrader/packages_status_detector.py#L188-L227", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:simion-pip-upgrader:PackagesStatusDetector._parse_pypi_json_package_info-369960d55d", "question": ":type package_name: str\n :type current_version: version.Version\n :type response: requests.models.Response", "scope": {"holder": "simion-pip-upgrader", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:simion/pip-upgrader:pip_upgrader/packages_status_detector.py:PackagesStatusDetector._update_index_url_from_configs#9443", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pip_upgrader/packages_status_detector.py", "symbol": "PackagesStatusDetector._update_index_url_from_configs"}, "source_id": "csn:simion/pip-upgrader:pip_upgrader/packages_status_detector.py:PackagesStatusDetector._update_index_url_from_configs#9443"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/simion/pip-upgrader/blob/716adca65d9ed56d4d416f94ede8a8e4fa8d640a/pip_upgrader/packages_status_detector.py#L55-L90", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:simion-pip-upgrader:PackagesStatusDetector._update_index_url_from_configs-38aa7b461f", "question": "Checks for alternative index-url in pip.conf", "scope": {"holder": "simion-pip-upgrader", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:singularityhub/sregistry-cli:sregistry/main/base/__init__.py:ApiConnection._client_tagged#9985", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "sregistry/main/base/__init__.py", "symbol": "ApiConnection._client_tagged"}, "source_id": "csn:singularityhub/sregistry-cli:sregistry/main/base/__init__.py:ApiConnection._client_tagged#9985"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/singularityhub/sregistry-cli/blob/abc96140a1d15b5e96d83432e1e0e1f4f8f36331/sregistry/main/base/__init__.py#L65-L82", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:singularityhub-sregistry-cli:ApiConnection._client_tagged-b9c96da9b2", "question": "ensure that the client name is included in a list of tags. This is\n important for matching builders to the correct client. We exit\n on fail.\n \n Parameters\n ==========\n tags: a list of tags to look for client name in", "scope": {"holder": "singularityhub-sregistry-cli", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:singularityhub/sregistry-cli:sregistry/main/base/inspect.py:get_metadata#10217", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "sregistry/main/base/inspect.py", "symbol": "get_metadata"}, "source_id": "csn:singularityhub/sregistry-cli:sregistry/main/base/inspect.py:get_metadata#10217"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/singularityhub/sregistry-cli/blob/abc96140a1d15b5e96d83432e1e0e1f4f8f36331/sregistry/main/base/inspect.py#L27-L74", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:singularityhub-sregistry-cli:get_metadata-944c476e95", "question": "extract metadata using Singularity inspect, if the executable is found.\n If not, return a reasonable default (the parsed image name)\n\n Parameters\n ==========\n image_file: the full path to a Singularity image\n names: optional, an extracted or otherwise created dictionary of\n variables for the image, likely from utils.parse_image_name", "scope": {"holder": "singularityhub-sregistry-cli", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:six8/polydatum:src/polydatum/context.py:DataAccessContext._setup#14946", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "src/polydatum/context.py", "symbol": "DataAccessContext._setup"}, "source_id": "csn:six8/polydatum:src/polydatum/context.py:DataAccessContext._setup#14946"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/six8/polydatum/blob/c98a498f8e7972218903ec027f6de78089726c1d/src/polydatum/context.py#L113-L136", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:six8-polydatum:DataAccessContext._setup-5893edc074", "question": "Setup the context. Should only be called by\n __enter__'ing the context.", "scope": {"holder": "six8-polydatum", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:six8/polydatum:src/polydatum/context.py:Meta.require#14945", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "src/polydatum/context.py", "symbol": "Meta.require"}, "source_id": "csn:six8/polydatum:src/polydatum/context.py:Meta.require#14945"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/six8/polydatum/blob/c98a498f8e7972218903ec027f6de78089726c1d/src/polydatum/context.py#L56-L63", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:six8-polydatum:Meta.require-c192cd3cf3", "question": "Raises an exception if value for ``key`` is empty.", "scope": {"holder": "six8-polydatum", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:skioo/django-datatrans-gateway:datatrans/gateway/payment_with_alias.py:pay_with_alias#15473", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "datatrans/gateway/payment_with_alias.py", "symbol": "pay_with_alias"}, "source_id": "csn:skioo/django-datatrans-gateway:datatrans/gateway/payment_with_alias.py:pay_with_alias#15473"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/skioo/django-datatrans-gateway/blob/1c4de5b589403e4ec3aadc4ff2fc1eb17b34bcc7/datatrans/gateway/payment_with_alias.py#L15-L47", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:skioo-django-datatrans-gateway:pay_with_alias-e8e01a201f", "question": "Charges money using datatrans, given a previously registered credit card alias.\n\n :param amount: The amount and currency we want to charge\n :param alias_registration_id: The alias registration to use\n :param client_ref: A unique reference for this charge\n :return: a Payment (either successful or not)", "scope": {"holder": "skioo-django-datatrans-gateway", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:skioo/django-datatrans-gateway:datatrans/gateway/refunding.py:refund#15477", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "datatrans/gateway/refunding.py", "symbol": "refund"}, "source_id": "csn:skioo/django-datatrans-gateway:datatrans/gateway/refunding.py:refund#15477"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/skioo/django-datatrans-gateway/blob/1c4de5b589403e4ec3aadc4ff2fc1eb17b34bcc7/datatrans/gateway/refunding.py#L15-L57", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:skioo-django-datatrans-gateway:refund-2500f246ed", "question": "Refunds (partially or completely) a previously authorized and settled payment.\n :param amount: The amount and currency we want to refund. Must be positive, in the same currency\n as the original payment, and not exceed the amount of the original payment.\n :param payment_id: The id of the payment to refund.\n :return: a Refund (either successful or not).", "scope": {"holder": "skioo-django-datatrans-gateway", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:skorokithakis/django-loginas:loginas/views.py:_load_module#9015", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "loginas/views.py", "symbol": "_load_module"}, "source_id": "csn:skorokithakis/django-loginas:loginas/views.py:_load_module#9015"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/skorokithakis/django-loginas/blob/6257857b40ed5b59e4c59a3af4b54d4856cacaf0/loginas/views.py#L27-L44", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:skorokithakis-django-loginas:_load_module-702dae22da", "question": "Code to load create user module. Copied off django-browserid.", "scope": {"holder": "skorokithakis-django-loginas", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:skorokithakis/django-loginas:loginas/utils.py:login_as#9013", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "loginas/utils.py", "symbol": "login_as"}, "source_id": "csn:skorokithakis/django-loginas:loginas/utils.py:login_as#9013"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/skorokithakis/django-loginas/blob/6257857b40ed5b59e4c59a3af4b54d4856cacaf0/loginas/utils.py#L41-L91", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:skorokithakis-django-loginas:login_as-15d2c8f3c1", "question": "Utility function for forcing a login as specific user -- be careful about\n calling this carelessly :)", "scope": {"holder": "skorokithakis-django-loginas", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:slacy/minimongo:minimongo/collection.py:Collection.find_one#9871", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "minimongo/collection.py", "symbol": "Collection.find_one"}, "source_id": "csn:slacy/minimongo:minimongo/collection.py:Collection.find_one#9871"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/slacy/minimongo/blob/29f38994831163b17bc625c82258068f1f90efa5/minimongo/collection.py#L50-L57", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:slacy-minimongo:Collection.find_one-96f1ac923f", "question": "Same as :meth:`pymongo.collection.Collection.find_one`, except\n it returns the right document class.", "scope": {"holder": "slacy-minimongo", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:slacy/minimongo:minimongo/options.py:_Options._configure#9867", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "minimongo/options.py", "symbol": "_Options._configure"}, "source_id": "csn:slacy/minimongo:minimongo/options.py:_Options._configure#9867"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/slacy/minimongo/blob/29f38994831163b17bc625c82258068f1f90efa5/minimongo/options.py#L82-L85", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:slacy-minimongo:_Options._configure-656c1b68e5", "question": "Updates class-level defaults for :class:`_Options` container.", "scope": {"holder": "slacy-minimongo", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:sloria/aiohttp_utils:aiohttp_utils/routing.py:ResourceRouter.add_resource_object#17146", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "aiohttp_utils/routing.py", "symbol": "ResourceRouter.add_resource_object"}, "source_id": "csn:sloria/aiohttp_utils:aiohttp_utils/routing.py:ResourceRouter.add_resource_object#17146"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/sloria/aiohttp_utils/blob/e5b41452f8077e7d749715606b1560f4b50e3d71/aiohttp_utils/routing.py#L60-L77", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:sloria-aiohttp_utils:ResourceRouter.add_resource_object-fd28b3dd5f", "question": "Add routes by an resource instance's methods.\n\n :param path: route path. Should be started with slash (``'/'``).\n :param resource: A \"resource\" instance. May be an instance of a plain object.\n :param methods: Methods (strings) to register.\n :param names: Dictionary of ``name`` overrides.", "scope": {"holder": "sloria-aiohttp_utils", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:sloria/aiohttp_utils:aiohttp_utils/runner.py:run#17147", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "aiohttp_utils/runner.py", "symbol": "run"}, "source_id": "csn:sloria/aiohttp_utils:aiohttp_utils/runner.py:run#17147"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/sloria/aiohttp_utils/blob/e5b41452f8077e7d749715606b1560f4b50e3d71/aiohttp_utils/runner.py#L99-L117", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:sloria-aiohttp_utils:run-31d2fd012e", "question": "Run an `aiohttp.web.Application` using gunicorn.\n\n :param app: The app to run.\n :param str app_uri: Import path to `app`. Takes the form\n ``$(MODULE_NAME):$(VARIABLE_NAME)``.\n The module name can be a full dotted path.\n The variable name refers to the `aiohttp.web.Application` instance.\n This argument is required if ``reload=True``.\n :param str host: Hostname to listen on.\n :param int port: Port of the server.\n :param bool reload: Whether to reload the server on a code change.\n If not set, will take the same value as ``app.debug``.\n **EXPERIMENTAL**.\n :param \\*\\*kwargs: Extra configuration options to set on the\n ``GunicornApp's`` config object.", "scope": {"holder": "sloria-aiohttp_utils", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:snare/scruffy:scruffy/config.py:ConfigApplicator.apply_to_str#18045", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "scruffy/config.py", "symbol": "ConfigApplicator.apply_to_str"}, "source_id": "csn:snare/scruffy:scruffy/config.py:ConfigApplicator.apply_to_str#18045"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/snare/scruffy/blob/0fedc08cfdb6db927ff93c09f25f24ce5a04c541/scruffy/config.py#L349-L379", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:snare-scruffy:ConfigApplicator.apply_to_str-a7b7043eaf", "question": "Apply the config to a string.", "scope": {"holder": "snare-scruffy", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:snare/scruffy:scruffy/file.py:Directory.remove#18027", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "scruffy/file.py", "symbol": "Directory.remove"}, "source_id": "csn:snare/scruffy:scruffy/file.py:Directory.remove#18027"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/snare/scruffy/blob/0fedc08cfdb6db927ff93c09f25f24ce5a04c541/scruffy/file.py#L323-L334", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:snare-scruffy:Directory.remove-61cb4fa834", "question": "Remove the directory.", "scope": {"holder": "snare-scruffy", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:snjoetw/py-synology:synology/api.py:Api.camera_event_md_param_save#14133", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "synology/api.py", "symbol": "Api.camera_event_md_param_save"}, "source_id": "csn:snjoetw/py-synology:synology/api.py:Api.camera_event_md_param_save#14133"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/snjoetw/py-synology/blob/4f7eb0a3a9f86c24ad65993802e6fb11fbaa1f7f/synology/api.py#L230-L242", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:snjoetw-py-synology:Api.camera_event_md_param_save-5489f8745f", "question": "Update motion settings matching camera_id with keyword args.", "scope": {"holder": "snjoetw-py-synology", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:snjoetw/py-synology:synology/api.py:Api.home_mode_set_state#14126", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "synology/api.py", "symbol": "Api.home_mode_set_state"}, "source_id": "csn:snjoetw/py-synology:synology/api.py:Api.home_mode_set_state#14126"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/snjoetw/py-synology/blob/4f7eb0a3a9f86c24ad65993802e6fb11fbaa1f7f/synology/api.py#L99-L120", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:snjoetw-py-synology:Api.home_mode_set_state-32e2ede69b", "question": "Set the state of Home Mode", "scope": {"holder": "snjoetw-py-synology", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:snowplow/snowplow-python-analytics-sdk:snowplow_analytics_sdk/run_manifests.py:add_to_manifest#14479", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "snowplow_analytics_sdk/run_manifests.py", "symbol": "add_to_manifest"}, "source_id": "csn:snowplow/snowplow-python-analytics-sdk:snowplow_analytics_sdk/run_manifests.py:add_to_manifest#14479"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/snowplow/snowplow-python-analytics-sdk/blob/0ddca91e3f6d8bed88627fa557790aa4868bdace/snowplow_analytics_sdk/run_manifests.py#L212-L227", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:snowplow-snowplow-python-analytics-sdk:add_to_manifest-41a765c2f8", "question": "Add run_id into DynamoDB manifest table\n\n Arguments:\n dynamodb_client - boto3 DynamoDB client (not service)\n table_name - string representing existing table name\n run_id - string representing run_id to store", "scope": {"holder": "snowplow-snowplow-python-analytics-sdk", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:snowplow/snowplow-python-analytics-sdk:snowplow_analytics_sdk/run_manifests.py:is_glacier#14476", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "snowplow_analytics_sdk/run_manifests.py", "symbol": "is_glacier"}, "source_id": "csn:snowplow/snowplow-python-analytics-sdk:snowplow_analytics_sdk/run_manifests.py:is_glacier#14476"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/snowplow/snowplow-python-analytics-sdk/blob/0ddca91e3f6d8bed88627fa557790aa4868bdace/snowplow_analytics_sdk/run_manifests.py#L140-L158", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:snowplow-snowplow-python-analytics-sdk:is_glacier-b82ab1e768", "question": "Check if prefix is archived in Glacier, by checking storage class of\n first object inside that prefix\n\n Arguments:\n s3_client - boto3 S3 client (not service)\n bucket - valid extracted bucket (without protocol and prefix)\n example: sowplow-events-data\n prefix - valid S3 prefix (usually, run_id)\n example: snowplow-archive/enriched/archive/", "scope": {"holder": "snowplow-snowplow-python-analytics-sdk", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:soimort/you-get:src/you_get/extractors/bigthink.py:Bigthink.get_streams_by_id#51", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "src/you_get/extractors/bigthink.py", "symbol": "Bigthink.get_streams_by_id"}, "source_id": "csn:soimort/you-get:src/you_get/extractors/bigthink.py:Bigthink.get_streams_by_id#51"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/soimort/you-get/blob/b746ac01c9f39de94cac2d56f665285b0523b974/src/you_get/extractors/bigthink.py#L22-L49", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:soimort-you-get:Bigthink.get_streams_by_id-1bd9050d2d", "question": "int, int->list\n \n Get the height of the videos.\n \n Since brightcove is using 3 kinds of links: rtmp, http and https,\n we will be using the HTTPS one to make it secure.\n \n If somehow akamaihd.net is blocked by the Great Fucking Wall,\n change the \"startswith https\" to http.", "scope": {"holder": "soimort-you-get", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:soimort/you-get:src/you_get/extractors/fc2video.py:makeMimi#2", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "src/you_get/extractors/fc2video.py", "symbol": "makeMimi"}, "source_id": "csn:soimort/you-get:src/you_get/extractors/fc2video.py:makeMimi#2"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/soimort/you-get/blob/b746ac01c9f39de94cac2d56f665285b0523b974/src/you_get/extractors/fc2video.py#L11-L17", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:soimort-you-get:makeMimi-1bb6ff4908", "question": "From http://cdn37.atwikiimg.com/sitescript/pub/dksitescript/FC2.site.js\n Also com.hps.util.fc2.FC2EncrptUtil.makeMimiLocal\n L110", "scope": {"holder": "soimort-you-get", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:solvebio/solvebio-python:solvebio/resource/apiresource.py:APIResource.class_url#11026", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "solvebio/resource/apiresource.py", "symbol": "APIResource.class_url"}, "source_id": "csn:solvebio/solvebio-python:solvebio/resource/apiresource.py:APIResource.class_url#11026"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/solvebio/solvebio-python/blob/b29614643043afd19c1d8074e8f25c6700d51a73/solvebio/resource/apiresource.py#L49-L52", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:solvebio-solvebio-python:APIResource.class_url-a478d14c38", "question": "Returns a versioned URI string for this class", "scope": {"holder": "solvebio-solvebio-python", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:solvebio/solvebio-python:solvebio/resource/task.py:Task.child_object#11058", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "solvebio/resource/task.py", "symbol": "Task.child_object"}, "source_id": "csn:solvebio/solvebio-python:solvebio/resource/task.py:Task.child_object#11058"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/solvebio/solvebio-python/blob/b29614643043afd19c1d8074e8f25c6700d51a73/solvebio/resource/task.py#L22-L26", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:solvebio-solvebio-python:Task.child_object-80b5e65395", "question": "Get Task child object class", "scope": {"holder": "solvebio-solvebio-python", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:sontek/pyramid_webassets:pyramid_webassets/__init__.py:maybebool#14641", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pyramid_webassets/__init__.py", "symbol": "maybebool"}, "source_id": "csn:sontek/pyramid_webassets:pyramid_webassets/__init__.py:maybebool#14641"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/sontek/pyramid_webassets/blob/d81a8f0c55aa49181ced4650fc88d434bbf94e62/pyramid_webassets/__init__.py#L24-L34", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:sontek-pyramid_webassets:maybebool-18aaa5b271", "question": "If `value` is a string type, attempts to convert it to a boolean\n if it looks like it might be one, otherwise returns the value\n unchanged. The difference between this and\n :func:`pyramid.settings.asbool` is how non-bools are handled: this\n returns the original value, whereas `asbool` returns False.", "scope": {"holder": "sontek-pyramid_webassets", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:sophilabs/django-qurl-templatetag:qurl_templatetag/qurl.py:Qurl.inc#12900", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "qurl_templatetag/qurl.py", "symbol": "Qurl.inc"}, "source_id": "csn:sophilabs/django-qurl-templatetag:qurl_templatetag/qurl.py:Qurl.inc#12900"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/sophilabs/django-qurl-templatetag/blob/8a785b112437d05cb54846b79012967fee1cb534/qurl_templatetag/qurl.py#L53-L60", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:sophilabs-django-qurl-templatetag:Qurl.inc-5031503ede", "question": "Increment value", "scope": {"holder": "sophilabs-django-qurl-templatetag", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:sophilabs/django-qurl-templatetag:qurl_templatetag/qurl.py:Qurl.remove#12899", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "qurl_templatetag/qurl.py", "symbol": "Qurl.remove"}, "source_id": "csn:sophilabs/django-qurl-templatetag:qurl_templatetag/qurl.py:Qurl.remove#12899"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/sophilabs/django-qurl-templatetag/blob/8a785b112437d05cb54846b79012967fee1cb534/qurl_templatetag/qurl.py#L47-L51", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:sophilabs-django-qurl-templatetag:Qurl.remove-fcc1371ea2", "question": "Remove a value from multiple value parameter.", "scope": {"holder": "sophilabs-django-qurl-templatetag", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:sourcesimian/pyTelegramBotAPI:TelegramBotAPI/types/field.py:Field.setup_types#14338", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "TelegramBotAPI/types/field.py", "symbol": "Field.setup_types"}, "source_id": "csn:sourcesimian/pyTelegramBotAPI:TelegramBotAPI/types/field.py:Field.setup_types#14338"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/sourcesimian/pyTelegramBotAPI/blob/bf233ac7923cc97c2036a604922c8be57817db40/TelegramBotAPI/types/field.py#L24-L36", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:sourcesimian-pyTelegramBotAPI:Field.setup_types-c5075932cf", "question": "The Message object has a circular reference on itself, thus we have to allow\n Type referencing by name. Here we lookup any Types referenced by name and\n replace with the real class.", "scope": {"holder": "sourcesimian-pyTelegramBotAPI", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:sp4ke/howto:howto/howto.py:cli_run#19726", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "howto/howto.py", "symbol": "cli_run"}, "source_id": "csn:sp4ke/howto:howto/howto.py:cli_run#19726"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/sp4ke/howto/blob/2588144a587be5138d45ca9db0ce6ab125fa7d0c/howto/howto.py#L78-L84", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:sp4ke-howto:cli_run-65890b15b7", "question": "docstring for argparse", "scope": {"holder": "sp4ke-howto", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:spotify/pyschema:pyschema/core.py:Field.mixin#11861", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pyschema/core.py", "symbol": "Field.mixin"}, "source_id": "csn:spotify/pyschema:pyschema/core.py:Field.mixin#11861"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/spotify/pyschema/blob/7e6c3934150bcb040c628d74ace6caf5fcf867df/pyschema/core.py#L272-L306", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:spotify-pyschema:Field.mixin-a9c2bf962b", "question": "Decorator for mixing in additional functionality into field type\n\n Example:\n\n >>> @Integer.mixin\n ... class IntegerPostgresExtensions:\n ... postgres_type = 'INT'\n ...\n ... def postgres_dump(self, obj):\n ... self.dump(obj) + \"::integer\"\n\n Is roughly equivalent to:\n\n >>> Integer.postgres_type = 'INT'\n ...\n ... def postgres_dump(self, obj):\n ... self.dump(obj) + \"::integer\"\n ...\n ... Integer.postgres_dump = postgres_dump", "scope": {"holder": "spotify-pyschema", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:spotify/pyschema:pyschema/core.py:load_json_dct#11856", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pyschema/core.py", "symbol": "load_json_dct"}, "source_id": "csn:spotify/pyschema:pyschema/core.py:load_json_dct#11856"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/spotify/pyschema/blob/7e6c3934150bcb040c628d74ace6caf5fcf867df/pyschema/core.py#L541-L586", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:spotify-pyschema:load_json_dct-d90c37309a", "question": "Create a Record instance from a json-compatible dictionary\n\n The dictionary values should have types that are json compatible,\n as if just loaded from a json serialized record string.\n\n :param dct:\n Python dictionary with key/value pairs for the record\n\n :param record_store:\n Record store to use for schema lookups (when $schema field is present)\n\n :param schema:\n PySchema Record class for the record to load.\n This will override any $schema fields specified in `dct`", "scope": {"holder": "spotify-pyschema", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:srevenant/onetimejwt:onetimejwt/__init__.py:Manager.already_used#21578", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "onetimejwt/__init__.py", "symbol": "Manager.already_used"}, "source_id": "csn:srevenant/onetimejwt:onetimejwt/__init__.py:Manager.already_used#21578"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/srevenant/onetimejwt/blob/f3ed561253eb4a8e1522c64f59bf64d275e9d315/onetimejwt/__init__.py#L133-L138", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:srevenant-onetimejwt:Manager.already_used-135b99fac0", "question": "has this jwt been used?", "scope": {"holder": "srevenant-onetimejwt", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:srevenant/onetimejwt:onetimejwt/__init__.py:generate#21575", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "onetimejwt/__init__.py", "symbol": "generate"}, "source_id": "csn:srevenant/onetimejwt:onetimejwt/__init__.py:generate#21575"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/srevenant/onetimejwt/blob/f3ed561253eb4a8e1522c64f59bf64d275e9d315/onetimejwt/__init__.py#L80-L87", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:srevenant-onetimejwt:generate-5ac5caf1f2", "question": "Generate a one-time jwt with an age in seconds", "scope": {"holder": "srevenant-onetimejwt", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:ssherar/hook:hook/model.py:CommandSet.from_yaml#16501", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "hook/model.py", "symbol": "CommandSet.from_yaml"}, "source_id": "csn:ssherar/hook:hook/model.py:CommandSet.from_yaml#16501"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/ssherar/hook/blob/54160df554d8b2ed65d762168e5808487e873ed9/hook/model.py#L76-L91", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:ssherar-hook:CommandSet.from_yaml-e4bab092d6", "question": "Creates a new instance of a rule by merging two dictionaries.\n\n This allows for independant configuration files to be merged\n into the defaults.", "scope": {"holder": "ssherar-hook", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:ssherar/hook:hook/model.py:Rule.execute_actions#16500", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "hook/model.py", "symbol": "Rule.execute_actions"}, "source_id": "csn:ssherar/hook:hook/model.py:Rule.execute_actions#16500"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/ssherar/hook/blob/54160df554d8b2ed65d762168e5808487e873ed9/hook/model.py#L57-L63", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:ssherar-hook:Rule.execute_actions-408c64f4b0", "question": "Iterates over the actions and executes them in order.", "scope": {"holder": "ssherar-hook", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:stevelittlefish/littlefish:littlefish/attackprotect.py:AttackProtect.log_attempt#16507", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "littlefish/attackprotect.py", "symbol": "AttackProtect.log_attempt"}, "source_id": "csn:stevelittlefish/littlefish:littlefish/attackprotect.py:AttackProtect.log_attempt#16507"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/stevelittlefish/littlefish/blob/6deee7f81fab30716c743efe2e94e786c6e17016/littlefish/attackprotect.py#L38-L52", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:stevelittlefish-littlefish:AttackProtect.log_attempt-f3a93d3409", "question": "Log an attempt against key, incrementing the number of attempts for that key and potentially adding a lock to\n the lock table", "scope": {"holder": "stevelittlefish-littlefish", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:stevelittlefish/littlefish:littlefish/redisutil.py:init#16557", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "littlefish/redisutil.py", "symbol": "init"}, "source_id": "csn:stevelittlefish/littlefish:littlefish/redisutil.py:init#16557"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/stevelittlefish/littlefish/blob/6deee7f81fab30716c743efe2e94e786c6e17016/littlefish/redisutil.py#L62-L86", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:stevelittlefish-littlefish:init-43ef1201a9", "question": "Initialise this library. The following config variables need to be in your Flask config:\n\n REDIS_HOST: The host of the Redis server\n REDIS_PORT: The port of the Redis server\n REDIS_PASSWORD: The password used to connect to Redis or None\n REDIS_GLOBAL_KEY_PREFIX: A short string unique to your application i.e. 'MYAPP'. This will be turned into\n a prefix like '~~MYAPP~~:' and will be used to allow multiple applications to share\n a single redis server\n REDIS_LOCK_TIMEOUT: An integer with the number of seconds to wait before automatically releasing a lock.\n A good number is 60 * 5 for 5 minutes. This stops locks from being held indefinitely\n if something goes wrong, but bear in mind this can also cause concurrency issues if\n you ave a locking process that takes longer than this timeout!", "scope": {"holder": "stevelittlefish-littlefish", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:stovorov/IteratorDecorator:IteratorDecorator/src.py:iter_attribute#19474", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "IteratorDecorator/src.py", "symbol": "iter_attribute"}, "source_id": "csn:stovorov/IteratorDecorator:IteratorDecorator/src.py:iter_attribute#19474"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/stovorov/IteratorDecorator/blob/9bc054a50758c19f41da8220f230beba1c2debbb/IteratorDecorator/src.py#L8-L90", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:stovorov-IteratorDecorator:iter_attribute-12479901b8", "question": "Decorator implementing Iterator interface with nicer manner.\n\n Example\n -------\n\n @iter_attribute('my_attr'):\n class DecoratedClass:\n ...\n\n Warning:\n ========\n\n When using PyCharm or MYPY you'll probably see issues with decorated class not being recognized as Iterator.\n That's an issue which I could not overcome yet, it's probably due to the fact that interpretation of object\n is being done statically rather than dynamically. MYPY checks for definition of methods in class code which\n changes at runtime. Since __iter__ and __next__ are added dynamically MYPY cannot find those\n defined in objects before object of a class is created. Possible workarounds for this issue are:\n\n 1. Define ``dummy`` __iter__ class like:\n\n @iter_attribute('attr')\n class Test:\n def __init__(self) -> None:\n self.attr = [1, 2, 3]\n\n def __iter__(self):\n pass\n\n 2. After creating object use cast or assert function denoting that particular instance inherits\n from collections.Iterator:\n\n assert isinstance(my_object, collections.Iterator)\n\n\n :param iterable_name: string representing attribute name which has to be iterated\n :return: DecoratedClass with implemented '__iter__' and '__next__' methods.", "scope": {"holder": "stovorov-IteratorDecorator", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:streamlink/streamlink:src/streamlink/plugins/abweb.py:ABweb._login#3006", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "src/streamlink/plugins/abweb.py", "symbol": "ABweb._login"}, "source_id": "csn:streamlink/streamlink:src/streamlink/plugins/abweb.py:ABweb._login#3006"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/streamlink/streamlink/blob/c8ed1daff14ac03195870238b9b900c1109dd5c1/src/streamlink/plugins/abweb.py#L93-L135", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:streamlink-streamlink:ABweb._login-b07925e11a", "question": "login and update cached cookies", "scope": {"holder": "streamlink-streamlink", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:streamlink/streamlink:src/streamlink/plugins/streann.py:Streann.device_id#2926", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "src/streamlink/plugins/streann.py", "symbol": "Streann.device_id"}, "source_id": "csn:streamlink/streamlink:src/streamlink/plugins/streann.py:Streann.device_id#2926"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/streamlink/streamlink/blob/c8ed1daff14ac03195870238b9b900c1109dd5c1/src/streamlink/plugins/streann.py#L35-L43", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:streamlink-streamlink:Streann.device_id-3d9bcbe738", "question": "Randomly generated deviceId.\n :return:", "scope": {"holder": "streamlink-streamlink", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:sublee/zeronimo:zeronimo/core.py:Collector.dispatch_reply#19851", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "zeronimo/core.py", "symbol": "Collector.dispatch_reply"}, "source_id": "csn:sublee/zeronimo:zeronimo/core.py:Collector.dispatch_reply#19851"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/sublee/zeronimo/blob/b216638232932718d2cbc5eabd870c8f5b5e83fb/zeronimo/core.py#L675-L694", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:sublee-zeronimo:Collector.dispatch_reply-b4e1f3674a", "question": "Dispatches the reply to the proper queue.", "scope": {"holder": "sublee-zeronimo", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:sublee/zeronimo:zeronimo/core.py:default_malformed_message_handler#19844", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "zeronimo/core.py", "symbol": "default_malformed_message_handler"}, "source_id": "csn:sublee/zeronimo:zeronimo/core.py:default_malformed_message_handler#19844"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/sublee/zeronimo/blob/b216638232932718d2cbc5eabd870c8f5b5e83fb/zeronimo/core.py#L133-L142", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:sublee-zeronimo:default_malformed_message_handler-934b9b4d54", "question": "The default malformed message handler for :class:`Worker`. It warns\n as a :exc:`MalformedMessage`.", "scope": {"holder": "sublee-zeronimo", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:sundarnagarajan/cffi_utils:cffi_utils/ffi.py:FFIExt.get_bytes#20130", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "cffi_utils/ffi.py", "symbol": "FFIExt.get_bytes"}, "source_id": "csn:sundarnagarajan/cffi_utils:cffi_utils/ffi.py:FFIExt.get_bytes#20130"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/sundarnagarajan/cffi_utils/blob/1d5ab2d2fcb962372228033106bc23f1d73d31fa/cffi_utils/ffi.py#L73-L89", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:sundarnagarajan-cffi_utils:FFIExt.get_bytes-6d83e87da7", "question": "all args-->_cffi_backend.CDataOwn\n Must be a pointer or an array\n Returns-->bytes (if a SINGLE argument was provided)\n LIST of bytes (if a args was a tuple or list)", "scope": {"holder": "sundarnagarajan-cffi_utils", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:sundarnagarajan/cffi_utils:cffi_utils/sowrapper.py:get_lib_ffi_shared#19913", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "cffi_utils/sowrapper.py", "symbol": "get_lib_ffi_shared"}, "source_id": "csn:sundarnagarajan/cffi_utils:cffi_utils/sowrapper.py:get_lib_ffi_shared#19913"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/sundarnagarajan/cffi_utils/blob/1d5ab2d2fcb962372228033106bc23f1d73d31fa/cffi_utils/sowrapper.py#L64-L72", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:sundarnagarajan-cffi_utils:get_lib_ffi_shared-3e9ba343a9", "question": "libpath-->str: shared library filename with optional path\n c_hdr-->str: C-style header definitions for functions to wrap\n Returns-->(ffi, lib)", "scope": {"holder": "sundarnagarajan-cffi_utils", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:sunshowers/ntfs:ntfsutils/junction.py:create#14969", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "ntfsutils/junction.py", "symbol": "create"}, "source_id": "csn:sunshowers/ntfs:ntfsutils/junction.py:create#14969"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/sunshowers/ntfs/blob/33388a514f0a5a032f68dfeb9a40ce7c772e7cf5/ntfsutils/junction.py#L110-L153", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:sunshowers-ntfs:create-11b9065454", "question": "Create a junction at link_name pointing to source.", "scope": {"holder": "sunshowers-ntfs", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:sunshowers/ntfs:ntfsutils/junction.py:new_junction_reparse_buffer#14968", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "ntfsutils/junction.py", "symbol": "new_junction_reparse_buffer"}, "source_id": "csn:sunshowers/ntfs:ntfsutils/junction.py:new_junction_reparse_buffer#14968"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/sunshowers/ntfs/blob/33388a514f0a5a032f68dfeb9a40ce7c772e7cf5/ntfsutils/junction.py#L24-L86", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:sunshowers-ntfs:new_junction_reparse_buffer-0e99f6843a", "question": "Given a path, return a pair containing a new REPARSE_DATA_BUFFER and the\n length of the buffer (not necessarily the same as sizeof due to packing\n issues).\n If no path is provided, the maximum length is assumed.", "scope": {"holder": "sunshowers-ntfs", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:susam/ice:ice.py:Ice._get_error_page_callback#18949", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "ice.py", "symbol": "Ice._get_error_page_callback"}, "source_id": "csn:susam/ice:ice.py:Ice._get_error_page_callback#18949"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/susam/ice/blob/532e685c504ea96f9e42833594585159ac1d2068/ice.py#L359-L368", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:susam-ice:Ice._get_error_page_callback-dbebcbf787", "question": "Return an error page for the current response status.", "scope": {"holder": "susam-ice", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:susam/ice:ice.py:Response.response#18957", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "ice.py", "symbol": "Response.response"}, "source_id": "csn:susam/ice:ice.py:Response.response#18957"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/susam/ice/blob/532e685c504ea96f9e42833594585159ac1d2068/ice.py#L766-L782", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:susam-ice:Response.response-b604463e88", "question": "Return the HTTP response body.\n\n Returns:\n bytes: HTTP response body as a sequence of bytes", "scope": {"holder": "susam-ice", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:sveetch/crispy-forms-foundation:sandbox/demo/views.py:FormContainersMixin.get_form_kwargs#16810", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "sandbox/demo/views.py", "symbol": "FormContainersMixin.get_form_kwargs"}, "source_id": "csn:sveetch/crispy-forms-foundation:sandbox/demo/views.py:FormContainersMixin.get_form_kwargs#16810"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/sveetch/crispy-forms-foundation/blob/835a4152ef9b2a096b9a27748341ef751823b9f0/sandbox/demo/views.py#L40-L48", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:sveetch-crispy-forms-foundation:FormContainersMixin.get_form_kwargs-df22923f40", "question": "Pass template pack argument", "scope": {"holder": "sveetch-crispy-forms-foundation", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:sveetch/crispy-forms-foundation:crispy_forms_foundation/layout/containers.py:TabHolder.render#16806", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "crispy_forms_foundation/layout/containers.py", "symbol": "TabHolder.render"}, "source_id": "csn:sveetch/crispy-forms-foundation:crispy_forms_foundation/layout/containers.py:TabHolder.render#16806"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/sveetch/crispy-forms-foundation/blob/835a4152ef9b2a096b9a27748341ef751823b9f0/crispy_forms_foundation/layout/containers.py#L112-L144", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:sveetch-crispy-forms-foundation:TabHolder.render-08f0992ade", "question": "Re-implement almost the same code from crispy_forms but passing\n ``form`` instance to item ``render_link`` method.", "scope": {"holder": "sveetch-crispy-forms-foundation", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:swarmer/fridge:fridge.py:Fridge.load#19709", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "fridge.py", "symbol": "Fridge.load"}, "source_id": "csn:swarmer/fridge:fridge.py:Fridge.load#19709"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/swarmer/fridge/blob/fcf6481307ce268c40c22f5e0062d01334f6cd95/fridge.py#L90-L105", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:swarmer-fridge:Fridge.load-3744e2c45d", "question": "Force reloading the data from the file.\n All data in the in-memory dictionary is discarded.\n This method is called automatically by the constructor, normally you\n don't need to call it.", "scope": {"holder": "swarmer-fridge", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:swarmer/fridge:fridge.py:Fridge.readonly#19708", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "fridge.py", "symbol": "Fridge.readonly"}, "source_id": "csn:swarmer/fridge:fridge.py:Fridge.readonly#19708"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/swarmer/fridge/blob/fcf6481307ce268c40c22f5e0062d01334f6cd95/fridge.py#L30-L37", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:swarmer-fridge:Fridge.readonly-0a3b91225f", "question": "Return an already closed read-only instance of Fridge.\n Arguments are the same as for the constructor.", "scope": {"holder": "swarmer-fridge", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:synw/gencharts:gencharts/__init__.py:ChartsGenerator._dict_to_df#19466", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "gencharts/__init__.py", "symbol": "ChartsGenerator._dict_to_df"}, "source_id": "csn:synw/gencharts:gencharts/__init__.py:ChartsGenerator._dict_to_df#19466"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/synw/gencharts/blob/fa35604a9445b399bb4f91bc91af488e8e8208fd/gencharts/__init__.py#L114-L124", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:synw-gencharts:ChartsGenerator._dict_to_df-9a394289e0", "question": "Converts a dictionnary to a pandas dataframe", "scope": {"holder": "synw-gencharts", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:synw/gencharts:gencharts/__init__.py:ChartsGenerator._patch_json#19464", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "gencharts/__init__.py", "symbol": "ChartsGenerator._patch_json"}, "source_id": "csn:synw/gencharts:gencharts/__init__.py:ChartsGenerator._patch_json#19464"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/synw/gencharts/blob/fa35604a9445b399bb4f91bc91af488e8e8208fd/gencharts/__init__.py#L89-L100", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:synw-gencharts:ChartsGenerator._patch_json-aa1e9d7a23", "question": "Patch the Altair generated json to the newest Vega Lite spec", "scope": {"holder": "synw-gencharts", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:takluyver/entrypoints:entrypoints.py:EntryPoint.from_string#7242", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "entrypoints.py", "symbol": "EntryPoint.from_string"}, "source_id": "csn:takluyver/entrypoints:entrypoints.py:EntryPoint.from_string#7242"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/takluyver/entrypoints/blob/d7db29fd6136f86498d8c374f531d4c198d66bf6/entrypoints.py#L90-L106", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:takluyver-entrypoints:EntryPoint.from_string-46028c1fb1", "question": "Parse an entry point from the syntax in entry_points.txt\n\n :param str epstr: The entry point string (not including 'name =')\n :param str name: The name of this entry point\n :param Distribution distro: The distribution in which the entry point was found\n :rtype: EntryPoint\n :raises BadEntryPoint: if *epstr* can't be parsed as an entry point.", "scope": {"holder": "takluyver-entrypoints", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:takluyver/entrypoints:entrypoints.py:EntryPoint.load#7241", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "entrypoints.py", "symbol": "EntryPoint.load"}, "source_id": "csn:takluyver/entrypoints:entrypoints.py:EntryPoint.load#7241"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/takluyver/entrypoints/blob/d7db29fd6136f86498d8c374f531d4c198d66bf6/entrypoints.py#L79-L87", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:takluyver-entrypoints:EntryPoint.load-3adc9edcf9", "question": "Load the object to which this entry point refers.", "scope": {"holder": "takluyver-entrypoints", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:tallero/trovotutto:trovotutto/__init__.py:Index.search#20059", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "trovotutto/__init__.py", "symbol": "Index.search"}, "source_id": "csn:tallero/trovotutto:trovotutto/__init__.py:Index.search#20059"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tallero/trovotutto/blob/7afcfacf2bb3b642654153630c1ab7447ab10fae/trovotutto/__init__.py#L201-L229", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tallero-trovotutto:Index.search-64352177e9", "question": "Searches files satisfying query\n\n It first decompose the query in ngrams, then score each document containing\n at least one ngram with the number. The ten document having the most ngrams\n in common with the query are selected.\n \n Args:\n query (str): what to search;\n results_number (int): number of results to return (default: 10)", "scope": {"holder": "tallero-trovotutto", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:tallero/trovotutto:trovotutto/__init__.py:main#20058", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "trovotutto/__init__.py", "symbol": "main"}, "source_id": "csn:tallero/trovotutto:trovotutto/__init__.py:main#20058"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tallero/trovotutto/blob/7afcfacf2bb3b642654153630c1ab7447ab10fae/trovotutto/__init__.py#L247-L273", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tallero-trovotutto:main-523e3266cf", "question": "Function for command line execution", "scope": {"holder": "tallero-trovotutto", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:tarmstrong/git2json:git2json/parser.py:parse_commit#9797", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "git2json/parser.py", "symbol": "parse_commit"}, "source_id": "csn:tarmstrong/git2json:git2json/parser.py:parse_commit#9797"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tarmstrong/git2json/blob/ee2688f91841b5e8d1e478a228b03b9df8e7d2db/git2json/parser.py#L53-L86", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tarmstrong-git2json:parse_commit-9cc642b11f", "question": "Accept a parsed single commit. Some of the named groups\n require further processing, so parse those groups.\n Return a dictionary representing the completely parsed\n commit.", "scope": {"holder": "tarmstrong-git2json", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:tarmstrong/git2json:git2json/parser.py:parse_commits#9796", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "git2json/parser.py", "symbol": "parse_commits"}, "source_id": "csn:tarmstrong/git2json:git2json/parser.py:parse_commits#9796"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tarmstrong/git2json/blob/ee2688f91841b5e8d1e478a228b03b9df8e7d2db/git2json/parser.py#L40-L50", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tarmstrong-git2json:parse_commits-d0fb89bbdb", "question": "Accept a string and parse it into many commits.\n Parse and yield each commit-dictionary.\n This function is a generator.", "scope": {"holder": "tarmstrong-git2json", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:techdragon/python-check-pypi-name:src/check_pypi_name/__init__.py:check_pypi_name#19951", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "src/check_pypi_name/__init__.py", "symbol": "check_pypi_name"}, "source_id": "csn:techdragon/python-check-pypi-name:src/check_pypi_name/__init__.py:check_pypi_name#19951"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/techdragon/python-check-pypi-name/blob/2abfa98878755ed9073b4f5448f4380f88e3e8f3/src/check_pypi_name/__init__.py#L7-L86", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:techdragon-python-check-pypi-name:check_pypi_name-bd4d09d3b3", "question": "Check if a package name exists on pypi.\n\n TODO: Document the Registry URL construction.\n It may not be obvious how pypi_package_name and pypi_registry_host are used\n I'm appending the simple HTTP API parts of the registry standard specification.\n\n It will return True if the package name, or any equivalent variation as defined by PEP 503 normalisation\n rules (https://www.python.org/dev/peps/pep-0503/#normalized-names) is registered in the PyPI registry.\n\n >>> check_pypi_name('pip')\n True\n >>> check_pypi_name('Pip')\n True\n\n It will return False if the package name, or any equivalent variation as defined by PEP 503 normalisation\n rules (https://www.python.org/dev/peps/pep-0503/#normalized-names) is not registered in the PyPI registry.\n\n >>> check_pypi_name('testy_mc-test_case-has.a.cousin_who_should_never_write_a_package')\n False\n\n :param pypi_package_name:\n :param pypi_registry_host:\n :return:", "scope": {"holder": "techdragon-python-check-pypi-name", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:tek/amino:amino/eff.py:Eff._flat_map#14802", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "amino/eff.py", "symbol": "Eff._flat_map"}, "source_id": "csn:tek/amino:amino/eff.py:Eff._flat_map#14802"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tek/amino/blob/51b314933e047a45587a24ecff02c836706d27ff/amino/eff.py#L45-L68", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tek-amino:Eff._flat_map-02f01a43fd", "question": "**f** must return the same stack type as **self.value** has.\n Iterates over the effects, sequences the inner instance\n successively to the top and joins with the outer instance.\n Example:\n List(Right(Just(1))) => List(Right(Just(List(Right(Just(5))))))\n => List(List(Right(Just(Right(Just(5))))))\n => List(Right(Just(Right(Just(5)))))\n => List(Right(Right(Just(Just(5)))))\n => List(Right(Just(Just(5))))\n => List(Right(Just(5)))\n Note: IO works only as outermost effect, as it cannot sequence", "scope": {"holder": "tek-amino", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:tek/amino:amino/string/hues.py:annihilate#14730", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "amino/string/hues.py", "symbol": "annihilate"}, "source_id": "csn:tek/amino:amino/string/hues.py:annihilate#14730"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tek/amino/blob/51b314933e047a45587a24ecff02c836706d27ff/amino/string/hues.py#L73-L80", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tek-amino:annihilate-19f0713b4f", "question": "Squash and reduce the input stack.\n Removes the elements of input that match predicate and only keeps the last\n match at the end of the stack.", "scope": {"holder": "tek-amino", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:tek/ribosome:ribosome/process.py:ProcessExecutor.run#17998", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "ribosome/process.py", "symbol": "ProcessExecutor.run"}, "source_id": "csn:tek/ribosome:ribosome/process.py:ProcessExecutor.run#17998"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tek/ribosome/blob/b2ce9e118faa46d93506cbbb5f27ecfbd4e8a1cc/ribosome/process.py#L170-L186", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tek-ribosome:ProcessExecutor.run-3ba29cd777", "question": "return values of execute are set as result of the task\n returned by ensure_future(), obtainable via task.result()", "scope": {"holder": "tek-ribosome", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:tek/ribosome:ribosome/nvim/io/compute.py:eval_step.nvim_io_recover#18000", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "ribosome/nvim/io/compute.py", "symbol": "eval_step.nvim_io_recover"}, "source_id": "csn:tek/ribosome:ribosome/nvim/io/compute.py:eval_step.nvim_io_recover#18000"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tek/ribosome/blob/b2ce9e118faa46d93506cbbb5f27ecfbd4e8a1cc/ribosome/nvim/io/compute.py#L242-L245", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tek-ribosome:eval_step.nvim_io_recover-9d759d4e53", "question": "calls `map` to shift the recover execution to flat_map_nvim_io", "scope": {"holder": "tek-ribosome", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:tell-k/goolabs:goolabs/commands.py:chrono#18979", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "goolabs/commands.py", "symbol": "chrono"}, "source_id": "csn:tell-k/goolabs:goolabs/commands.py:chrono#18979"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tell-k/goolabs/blob/3b87d0409e55c71290158ad6d5e2d8bb9a338c46/goolabs/commands.py#L305-L325", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tell-k-goolabs:chrono-2e3c9ef81b", "question": "Extract expression expressing date and time and normalize its value", "scope": {"holder": "tell-k-goolabs", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:tell-k/goolabs:goolabs/commands.py:morph#18973", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "goolabs/commands.py", "symbol": "morph"}, "source_id": "csn:tell-k/goolabs:goolabs/commands.py:morph#18973"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tell-k/goolabs/blob/3b87d0409e55c71290158ad6d5e2d8bb9a338c46/goolabs/commands.py#L107-L135", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tell-k-goolabs:morph-845a08f5f0", "question": "Morphological analysis for Japanese.", "scope": {"holder": "tell-k-goolabs", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:tensorflow/probability:tensorflow_probability/python/bijectors/affine.py:Affine._create_scale_operator#968", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "tensorflow_probability/python/bijectors/affine.py", "symbol": "Affine._create_scale_operator"}, "source_id": "csn:tensorflow/probability:tensorflow_probability/python/bijectors/affine.py:Affine._create_scale_operator#968"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/bijectors/affine.py#L238-L309", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:Affine._create_scale_operator-f33b5df489", "question": "Construct `scale` from various components.\n\n Args:\n identity_multiplier: floating point rank 0 `Tensor` representing a scaling\n done to the identity matrix.\n diag: Floating-point `Tensor` representing the diagonal matrix.`diag` has\n shape `[N1, N2, ... k]`, which represents a k x k diagonal matrix.\n tril: Floating-point `Tensor` representing the lower triangular matrix.\n `tril` has shape `[N1, N2, ... k, k]`, which represents a k x k lower\n triangular matrix.\n perturb_diag: Floating-point `Tensor` representing the diagonal matrix of\n the low rank update.\n perturb_factor: Floating-point `Tensor` representing factor matrix.\n shift: Floating-point `Tensor` representing `shift in `scale @ X + shift`.\n validate_args: Python `bool` indicating whether arguments should be\n checked for correctness.\n dtype: `DType` for arg `Tensor` conversions.\n\n Returns:\n scale. In the case of scaling by a constant, scale is a\n floating point `Tensor`. Otherwise, scale is a `LinearOperator`.\n\n Raises:\n ValueError: if all of `tril`, `diag` and `identity_multiplier` are `None`.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:tensorflow/probability:tensorflow_probability/python/stats/sample_stats.py:_squeeze#991", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "tensorflow_probability/python/stats/sample_stats.py", "symbol": "_squeeze"}, "source_id": "csn:tensorflow/probability:tensorflow_probability/python/stats/sample_stats.py:_squeeze#991"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/stats/sample_stats.py#L686-L694", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:_squeeze-cb870ade03", "question": "A version of squeeze that works with dynamic axis.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:theduke/django-baseline:django_baseline/views.py:SaveHookMixin.delete#21228", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "django_baseline/views.py", "symbol": "SaveHookMixin.delete"}, "source_id": "csn:theduke/django-baseline:django_baseline/views.py:SaveHookMixin.delete#21228"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/theduke/django-baseline/blob/7be8b956e53c70b35f34e1783a8fe8f716955afb/django_baseline/views.py#L160-L171", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:theduke-django-baseline:SaveHookMixin.delete-9ddd5b582e", "question": "Calls pre and post delete hooks for DelteViews.", "scope": {"holder": "theduke-django-baseline", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:theduke/django-baseline:django_baseline/templatetags/helpers.py:jsfile#20338", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "django_baseline/templatetags/helpers.py", "symbol": "jsfile"}, "source_id": "csn:theduke/django-baseline:django_baseline/templatetags/helpers.py:jsfile#20338"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/theduke/django-baseline/blob/7be8b956e53c70b35f34e1783a8fe8f716955afb/django_baseline/templatetags/helpers.py#L58-L68", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:theduke-django-baseline:jsfile-7cde02e969", "question": "Output a script tag to a js file.", "scope": {"holder": "theduke-django-baseline", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:thombashi/sqliteschema:sqliteschema/_extractor.py:SQLiteSchemaExtractor.fetch_table_names#15349", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "sqliteschema/_extractor.py", "symbol": "SQLiteSchemaExtractor.fetch_table_names"}, "source_id": "csn:thombashi/sqliteschema:sqliteschema/_extractor.py:SQLiteSchemaExtractor.fetch_table_names#15349"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/thombashi/sqliteschema/blob/39fa769e31a0df1123066245073fb3a4593ae72d/sqliteschema/_extractor.py#L74-L89", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:thombashi-sqliteschema:SQLiteSchemaExtractor.fetch_table_names-1c817be526", "question": ":return: List of table names in the database.\n :rtype: list", "scope": {"holder": "thombashi-sqliteschema", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:thusoy/pwm:pwm/core.py:Domain.derive_key#19202", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pwm/core.py", "symbol": "Domain.derive_key"}, "source_id": "csn:thusoy/pwm:pwm/core.py:Domain.derive_key#19202"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/thusoy/pwm/blob/fff7d755c34f3a7235a8bf217ffa2ff5aed4926f/pwm/core.py#L67-L81", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:thusoy-pwm:Domain.derive_key-8419418031", "question": "Computes the key from the salt and the master password.", "scope": {"holder": "thusoy-pwm", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:thusoy/pwm:pwm/core.py:PWM.create_domain#19207", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pwm/core.py", "symbol": "PWM.create_domain"}, "source_id": "csn:thusoy/pwm:pwm/core.py:PWM.create_domain#19207"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/thusoy/pwm/blob/fff7d755c34f3a7235a8bf217ffa2ff5aed4926f/pwm/core.py#L236-L249", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:thusoy-pwm:PWM.create_domain-f35a8bd759", "question": "Create a new domain entry in the database.\n\n :param username: The username to associate with this domain.\n :param alphabet: A character set restriction to impose on keys generated for this domain.\n :param length: The length of the generated key, in case of restrictions on the site.", "scope": {"holder": "thusoy-pwm", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:tigrawap/pybabel-hbs:pybabel_hbs/extractor.py:extract_hbs#19211", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pybabel_hbs/extractor.py", "symbol": "extract_hbs"}, "source_id": "csn:tigrawap/pybabel-hbs:pybabel_hbs/extractor.py:extract_hbs#19211"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tigrawap/pybabel-hbs/blob/5289bc0f8a5e97044f5b074c9532dcd2115625b9/pybabel_hbs/extractor.py#L34-L54", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tigrawap-pybabel-hbs:extract_hbs-42087e81ff", "question": "Extract messages from Handlebars templates.\n\n It returns an iterator yielding tuples in the following form ``(lineno,\n funcname, message, comments)``.\n\n TODO: Things to improve:\n --- Return comments", "scope": {"holder": "tigrawap-pybabel-hbs", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:timheap/django-enumchoicefield:enumchoicefield/fields.py:EnumChoiceField.from_db_value#10363", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "enumchoicefield/fields.py", "symbol": "EnumChoiceField.from_db_value"}, "source_id": "csn:timheap/django-enumchoicefield:enumchoicefield/fields.py:EnumChoiceField.from_db_value#10363"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/timheap/django-enumchoicefield/blob/59e230f8eed086c87ac6a9243448d2cd9adfc250/enumchoicefield/fields.py#L43-L49", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:timheap-django-enumchoicefield:EnumChoiceField.from_db_value-a624513d7d", "question": "Convert a string from the database into an Enum value", "scope": {"holder": "timheap-django-enumchoicefield", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:timheap/django-enumchoicefield:enumchoicefield/fields.py:EnumChoiceField.to_python#10364", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "enumchoicefield/fields.py", "symbol": "EnumChoiceField.to_python"}, "source_id": "csn:timheap/django-enumchoicefield:enumchoicefield/fields.py:EnumChoiceField.to_python#10364"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/timheap/django-enumchoicefield/blob/59e230f8eed086c87ac6a9243448d2cd9adfc250/enumchoicefield/fields.py#L51-L59", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:timheap-django-enumchoicefield:EnumChoiceField.to_python-1b56ef850c", "question": "Convert a string from a form into an Enum value.", "scope": {"holder": "timheap-django-enumchoicefield", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:tjkessler/PyGenetics:pygenetics/ga_core.py:Population.__determine_best_member#15782", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pygenetics/ga_core.py", "symbol": "Population.__determine_best_member"}, "source_id": "csn:tjkessler/PyGenetics:pygenetics/ga_core.py:Population.__determine_best_member#15782"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tjkessler/PyGenetics/blob/b78ee6393605d6e85d2279fb05f3983f5833df40/pygenetics/ga_core.py#L379-L402", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tjkessler-PyGenetics:Population.__determine_best_member-26325b0b9c", "question": "Private method: determines if any current population members have a\n fitness score better than the current best", "scope": {"holder": "tjkessler-PyGenetics", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:tjkessler/PyGenetics:pygenetics/ga_core.py:Population.fitness#15773", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pygenetics/ga_core.py", "symbol": "Population.fitness"}, "source_id": "csn:tjkessler/PyGenetics:pygenetics/ga_core.py:Population.fitness#15773"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tjkessler/PyGenetics/blob/b78ee6393605d6e85d2279fb05f3983f5833df40/pygenetics/ga_core.py#L126-L136", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tjkessler-PyGenetics:Population.fitness-834d854fba", "question": "Population fitness == average member fitness score", "scope": {"holder": "tjkessler-PyGenetics", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:tmontaigu/pylas:pylas/headers/rawheader.py:HeaderFactory.convert_header#7998", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pylas/headers/rawheader.py", "symbol": "HeaderFactory.convert_header"}, "source_id": "csn:tmontaigu/pylas:pylas/headers/rawheader.py:HeaderFactory.convert_header#7998"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tmontaigu/pylas/blob/8335a1a7d7677f0e4bc391bb6fa3c75b42ed5b06/pylas/headers/rawheader.py#L375-L404", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tmontaigu-pylas:HeaderFactory.convert_header-cdabe540d9", "question": "Converts a header to a another version\n\n Parameters\n ----------\n old_header: the old header instance\n new_version: float or str\n\n Returns\n -------\n The converted header\n\n\n >>> old_header = HeaderFactory.new(1.2)\n >>> HeaderFactory.convert_header(old_header, 1.4)\n <LasHeader(1.4)>\n\n >>> old_header = HeaderFactory.new('1.4')\n >>> HeaderFactory.convert_header(old_header, '1.2')\n <LasHeader(1.2)>", "scope": {"holder": "tmontaigu-pylas", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:tmontaigu/pylas:pylas/headers/rawheader.py:RawHeader1_1.maxs#7992", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pylas/headers/rawheader.py", "symbol": "RawHeader1_1.maxs"}, "source_id": "csn:tmontaigu/pylas:pylas/headers/rawheader.py:RawHeader1_1.maxs#7992"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tmontaigu/pylas/blob/8335a1a7d7677f0e4bc391bb6fa3c75b42ed5b06/pylas/headers/rawheader.py#L212-L215", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tmontaigu-pylas:RawHeader1_1.maxs-50f4aaa59c", "question": "Returns de maximum values of x, y, z as a numpy array", "scope": {"holder": "tmontaigu-pylas", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:tnkteja/myhelp:virtualEnvironment/lib/python2.7/site-packages/coverage/results.py:Analysis.arcs_executed#20507", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "virtualEnvironment/lib/python2.7/site-packages/coverage/results.py", "symbol": "Analysis.arcs_executed"}, "source_id": "csn:tnkteja/myhelp:virtualEnvironment/lib/python2.7/site-packages/coverage/results.py:Analysis.arcs_executed#20507"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tnkteja/myhelp/blob/fb3a4809d448ad14d5b2e6ddf2e7e89ad52b71cb/virtualEnvironment/lib/python2.7/site-packages/coverage/results.py#L111-L116", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tnkteja-myhelp:Analysis.arcs_executed-635b20f8b4", "question": "Returns a sorted list of the arcs actually executed in the code.", "scope": {"holder": "tnkteja-myhelp", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:tnkteja/myhelp:virtualEnvironment/lib/python2.7/site-packages/coverage/results.py:Numbers._get_pc_covered_str#20516", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "virtualEnvironment/lib/python2.7/site-packages/coverage/results.py", "symbol": "Numbers._get_pc_covered_str"}, "source_id": "csn:tnkteja/myhelp:virtualEnvironment/lib/python2.7/site-packages/coverage/results.py:Numbers._get_pc_covered_str#20516"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tnkteja/myhelp/blob/fb3a4809d448ad14d5b2e6ddf2e7e89ad52b71cb/virtualEnvironment/lib/python2.7/site-packages/coverage/results.py#L241-L256", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tnkteja-myhelp:Numbers._get_pc_covered_str-a95cfabdbb", "question": "Returns the percent covered, as a string, without a percent sign.\n\n Note that \"0\" is only returned when the value is truly zero, and \"100\"\n is only returned when the value is truly 100. Rounding can never\n result in either \"0\" or \"100\".", "scope": {"holder": "tnkteja-myhelp", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:tomMoral/loky:loky/backend/_posix_reduction.py:DupFd#8801", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "loky/backend/_posix_reduction.py", "symbol": "DupFd"}, "source_id": "csn:tomMoral/loky:loky/backend/_posix_reduction.py:DupFd#8801"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tomMoral/loky/blob/dc2d941d8285a96f3a5b666a4bd04875b0b25984/loky/backend/_posix_reduction.py#L34-L46", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tomMoral-loky:DupFd-eb9fac1fb0", "question": "Return a wrapper for an fd.", "scope": {"holder": "tomMoral-loky", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:tomMoral/loky:loky/backend/utils.py:_recursive_terminate_without_psutil#8808", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "loky/backend/utils.py", "symbol": "_recursive_terminate_without_psutil"}, "source_id": "csn:tomMoral/loky:loky/backend/utils.py:_recursive_terminate_without_psutil#8808"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tomMoral/loky/blob/dc2d941d8285a96f3a5b666a4bd04875b0b25984/loky/backend/utils.py#L49-L60", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tomMoral-loky:_recursive_terminate_without_psutil-850064964a", "question": "Terminate a process and its descendants.", "scope": {"holder": "tomMoral-loky", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:tomasbasham/dominos:dominos/api.py:Client.__call_api#9115", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "dominos/api.py", "symbol": "Client.__call_api"}, "source_id": "csn:tomasbasham/dominos:dominos/api.py:Client.__call_api#9115"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tomasbasham/dominos/blob/59729a8bdca0ae30a84115a0e93e9b1f259faf0e/dominos/api.py#L264-L280", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tomasbasham-dominos:Client.__call_api-56c1793385", "question": "Make a HTTP request to the Dominos UK API with the given parameters for\n the current session.\n\n :param verb func: HTTP method on the session.\n :param string path: The API endpoint path.\n :params list kargs: A list of arguments.\n :return: A response from the Dominos UK API.\n :rtype: response.Response", "scope": {"holder": "tomasbasham-dominos", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:tomasbasham/dominos:dominos/api.py:Client.new_session#9102", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "dominos/api.py", "symbol": "Client.new_session"}, "source_id": "csn:tomasbasham/dominos:dominos/api.py:Client.new_session#9102"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tomasbasham/dominos/blob/59729a8bdca0ae30a84115a0e93e9b1f259faf0e/dominos/api.py#L31-L41", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tomasbasham-dominos:Client.new_session-3c9e894fe7", "question": "Clear out the current session on the remote and setup a new one.\n\n :return: A response from having expired the current session.\n :rtype: requests.Response", "scope": {"holder": "tomasbasham-dominos", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:tomatohater/django-unfriendly:unfriendly/utils.py:_crc#17673", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "unfriendly/utils.py", "symbol": "_crc"}, "source_id": "csn:tomatohater/django-unfriendly:unfriendly/utils.py:_crc#17673"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tomatohater/django-unfriendly/blob/38eca5fb45841db331fc66571fff37bef50dfa67/unfriendly/utils.py#L29-L33", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tomatohater-django-unfriendly:_crc-d2e987276c", "question": "Generates crc32. Modulo keep the value within int range.", "scope": {"holder": "tomatohater-django-unfriendly", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:tomatohater/django-unfriendly:unfriendly/utils.py:decrypt#17675", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "unfriendly/utils.py", "symbol": "decrypt"}, "source_id": "csn:tomatohater/django-unfriendly:unfriendly/utils.py:decrypt#17675"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tomatohater/django-unfriendly/blob/38eca5fb45841db331fc66571fff37bef50dfa67/unfriendly/utils.py#L65-L93", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tomatohater-django-unfriendly:decrypt-9049c45432", "question": "Decrypts ciphertext with secret\n ciphertext - encrypted content to decrypt\n secret - secret to decrypt ciphertext\n inital_vector - initial vector\n lazy - pad secret if less than legal blocksize (default: True)\n checksum - verify crc32 byte encoded checksum (default: True)\n returns plaintext", "scope": {"holder": "tomatohater-django-unfriendly", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:tomekwojcik/ForgeryPy:forgery_py/forgery/basic.py:text#15227", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "forgery_py/forgery/basic.py", "symbol": "text"}, "source_id": "csn:tomekwojcik/ForgeryPy:forgery_py/forgery/basic.py:text#15227"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tomekwojcik/ForgeryPy/blob/0d1864e86b4362d8d6c215c618e8451d39a7a567/forgery_py/forgery/basic.py#L42-L76", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tomekwojcik-ForgeryPy:text-260140d6d9", "question": "Random text.\n\n If `length` is present the text will be exactly this chars long. Else the\n text will be something between `at_least` and `at_most` chars long.", "scope": {"holder": "tomekwojcik-ForgeryPy", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:tonyseek/flask-navigation:flask_navigation/item.py:Item.args#17486", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "flask_navigation/item.py", "symbol": "Item.args"}, "source_id": "csn:tonyseek/flask-navigation:flask_navigation/item.py:Item.args#17486"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tonyseek/flask-navigation/blob/38fa83addcbe62f31516763fbe3c0bbdc793dc96/flask_navigation/item.py#L68-L77", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tonyseek-flask-navigation:Item.args-fd5253826c", "question": "The arguments which will be passed to ``url_for``.\n\n :type: :class:`dict`", "scope": {"holder": "tonyseek-flask-navigation", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:tonyseek/flask-navigation:flask_navigation/api.py:Navigation.init_app#17483", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "flask_navigation/api.py", "symbol": "Navigation.init_app"}, "source_id": "csn:tonyseek/flask-navigation:flask_navigation/api.py:Navigation.init_app#17483"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tonyseek/flask-navigation/blob/38fa83addcbe62f31516763fbe3c0bbdc793dc96/flask_navigation/api.py#L37-L48", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tonyseek-flask-navigation:Navigation.init_app-ed51e18141", "question": "Initializes an app to work with this extension.\n\n The app-context signals will be subscribed and the template context\n will be initialized.\n\n :param app: the :class:`flask.Flask` app instance.", "scope": {"holder": "tonyseek-flask-navigation", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:trapeze/fancy_tag:fancy_tag/__init__.py:fancy_tag_compiler#19806", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "fancy_tag/__init__.py", "symbol": "fancy_tag_compiler"}, "source_id": "csn:trapeze/fancy_tag:fancy_tag/__init__.py:fancy_tag_compiler#19806"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/trapeze/fancy_tag/blob/0418a995500dc5ac65cf093cb6c1634e3e628229/fancy_tag/__init__.py#L12-L68", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:trapeze-fancy_tag:fancy_tag_compiler-76eff0eaa7", "question": "Returns a template.Node subclass.", "scope": {"holder": "trapeze-fancy_tag", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:trec-kba/streamcorpus-pipeline:streamcorpus_pipeline/_taggers.py:ANY_MULTI_TOKEN_mentions#18993", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "streamcorpus_pipeline/_taggers.py", "symbol": "ANY_MULTI_TOKEN_mentions"}, "source_id": "csn:trec-kba/streamcorpus-pipeline:streamcorpus_pipeline/_taggers.py:ANY_MULTI_TOKEN_mentions#18993"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/trec-kba/streamcorpus-pipeline/blob/8bb82ea1beb83c6b40ed03fa1659df2897c2292a/streamcorpus_pipeline/_taggers.py#L104-L120", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:trec-kba-streamcorpus-pipeline:ANY_MULTI_TOKEN_mentions-b8b3260d4a", "question": "For each name string (potentially consisting of multiple tokens) in the\n target_mentions list, searches through all chain_mentions looking for any\n cleansed Token.token that contains all the tokens in the name. Returns\n True only if all of the target_mention strings appeared as substrings of at\n least one cleansed Token.token. Otherwise, returns False.\n\n :type target_mentions: list of basestring\n :type chain_mentions: list of basestring\n\n :returns bool:", "scope": {"holder": "trec-kba-streamcorpus-pipeline", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:trec-kba/streamcorpus-pipeline:streamcorpus_pipeline/_get_name_info.py:get_name_info#18988", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "streamcorpus_pipeline/_get_name_info.py", "symbol": "get_name_info"}, "source_id": "csn:trec-kba/streamcorpus-pipeline:streamcorpus_pipeline/_get_name_info.py:get_name_info#18988"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/trec-kba/streamcorpus-pipeline/blob/8bb82ea1beb83c6b40ed03fa1659df2897c2292a/streamcorpus_pipeline/_get_name_info.py#L19-L123", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:trec-kba-streamcorpus-pipeline:get_name_info-f2980f4b08", "question": "takes a chunk blob and obtains the date_hour, md5, num\n\n makes fields:\n i_str\n input_fname\n input_md5 - parsed from input filename if it contains '-%(md5)s-'\n md5\n num\n epoch_ticks\n target_names\n doc_ids_8\n date_hour\n rand8\n date_now\n time_now\n date_time_now", "scope": {"holder": "trec-kba-streamcorpus-pipeline", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:treycucco/pyebnf:pyebnf/compiler.py:Compiler._ast_op_concat_to_code#18357", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pyebnf/compiler.py", "symbol": "Compiler._ast_op_concat_to_code"}, "source_id": "csn:treycucco/pyebnf:pyebnf/compiler.py:Compiler._ast_op_concat_to_code#18357"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/treycucco/pyebnf/blob/3634ddabbe5d73508bcc20f4a591f86a46634e1d/pyebnf/compiler.py#L396-L406", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:treycucco-pyebnf:Compiler._ast_op_concat_to_code-fff5b4e35b", "question": "Convert an AST concatenate op to python source code.", "scope": {"holder": "treycucco-pyebnf", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:treycucco/pyebnf:pyebnf/primitive.py:ParseNode.position#18428", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pyebnf/primitive.py", "symbol": "ParseNode.position"}, "source_id": "csn:treycucco/pyebnf:pyebnf/primitive.py:ParseNode.position#18428"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/treycucco/pyebnf/blob/3634ddabbe5d73508bcc20f4a591f86a46634e1d/pyebnf/primitive.py#L49-L61", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:treycucco-pyebnf:ParseNode.position-d869835fc7", "question": "Gets the position of the text the ParseNode processed. If the ParseNode does not have its\n own position, it looks to its first child for its position.\n\n 'Value Nodes' (terminals) must have their own position, otherwise this method will throw an\n exception when it tries to get the position property of the string child.", "scope": {"holder": "treycucco-pyebnf", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:trp07/messages:messages/email_.py:Email._add_attachments#17342", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "messages/email_.py", "symbol": "Email._add_attachments"}, "source_id": "csn:trp07/messages:messages/email_.py:Email._add_attachments#17342"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/trp07/messages/blob/7789ebc960335a59ea5d319fceed3dd349023648/messages/email_.py#L210-L222", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:trp07-messages:Email._add_attachments-eaffd9399b", "question": "Add required attachments.", "scope": {"holder": "trp07-messages", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:trp07/messages:messages/_config.py:check_config_file#17302", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "messages/_config.py", "symbol": "check_config_file"}, "source_id": "csn:trp07/messages:messages/_config.py:check_config_file#17302"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/trp07/messages/blob/7789ebc960335a59ea5d319fceed3dd349023648/messages/_config.py#L72-L89", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:trp07-messages:check_config_file-402d89b841", "question": "Checks the config.json file for default settings and auth values.\n\n Args:\n :msg: (Message class) an instance of a message class.", "scope": {"holder": "trp07-messages", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:twaddington/django-gravatar:django_gravatar/helpers.py:get_gravatar_profile_url#10227", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "django_gravatar/helpers.py", "symbol": "get_gravatar_profile_url"}, "source_id": "csn:twaddington/django-gravatar:django_gravatar/helpers.py:get_gravatar_profile_url#10227"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/twaddington/django-gravatar/blob/c4849d93ed43b419eceff0ff2de83d4265597629/django_gravatar/helpers.py#L90-L108", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:twaddington-django-gravatar:get_gravatar_profile_url-bbaa3cb31e", "question": "Builds a url to a gravatar profile from an email address.\n\n :param email: The email to fetch the gravatar for\n :param secure: If True use https, otherwise plain http", "scope": {"holder": "twaddington-django-gravatar", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:twaddington/django-gravatar:django_gravatar/templatetags/gravatar.py:gravatar#10224", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "django_gravatar/templatetags/gravatar.py", "symbol": "gravatar"}, "source_id": "csn:twaddington/django-gravatar:django_gravatar/templatetags/gravatar.py:gravatar#10224"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/twaddington/django-gravatar/blob/c4849d93ed43b419eceff0ff2de83d4265597629/django_gravatar/templatetags/gravatar.py#L24-L41", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:twaddington-django-gravatar:gravatar-f48d40845b", "question": "Builds an gravatar <img> tag from an user or email", "scope": {"holder": "twaddington-django-gravatar", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:ubyssey/dispatch:dispatch/modules/content/models.py:Article.save_subsection#8146", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "dispatch/modules/content/models.py", "symbol": "Article.save_subsection"}, "source_id": "csn:ubyssey/dispatch:dispatch/modules/content/models.py:Article.save_subsection#8146"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/ubyssey/dispatch/blob/8da6084fe61726f20e9cf675190480cfc45ee764/dispatch/modules/content/models.py#L407-L409", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:ubyssey-dispatch:Article.save_subsection-6f7c537d8f", "question": "Save the subsection to the parent article", "scope": {"holder": "ubyssey-dispatch", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:ubyssey/dispatch:dispatch/api/views.py:PageViewSet.get_queryset#8123", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "dispatch/api/views.py", "symbol": "PageViewSet.get_queryset"}, "source_id": "csn:ubyssey/dispatch:dispatch/api/views.py:PageViewSet.get_queryset#8123"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/ubyssey/dispatch/blob/8da6084fe61726f20e9cf675190480cfc45ee764/dispatch/api/views.py#L138-L153", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:ubyssey-dispatch:PageViewSet.get_queryset-3b3e9b02f7", "question": "Only display unpublished content to authenticated users, filter by\n query parameter if present.", "scope": {"holder": "ubyssey-dispatch", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:ui/django-thumbnails:thumbnails/fields.py:ImageField.pre_save#14860", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "thumbnails/fields.py", "symbol": "ImageField.pre_save"}, "source_id": "csn:ui/django-thumbnails:thumbnails/fields.py:ImageField.pre_save#14860"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/ui/django-thumbnails/blob/5cef55e7f167060458709ed760dd43981124796a/thumbnails/fields.py#L30-L44", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:ui-django-thumbnails:ImageField.pre_save-4d2d684b13", "question": "Process the source image through the defined processors.", "scope": {"holder": "ui-django-thumbnails", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:ui/django-thumbnails:thumbnails/images.py:get#14867", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "thumbnails/images.py", "symbol": "get"}, "source_id": "csn:ui/django-thumbnails:thumbnails/images.py:get#14867"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/ui/django-thumbnails/blob/5cef55e7f167060458709ed760dd43981124796a/thumbnails/images.py#L88-L101", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:ui-django-thumbnails:get-87dae1317c", "question": "Returns a Thumbnail instance, or None if thumbnail does not yet exist.", "scope": {"holder": "ui-django-thumbnails", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:umich-brcf-bioinf/Jacquard:jacquard/merge.py:MergeVcfReader.vcf_records#14980", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "jacquard/merge.py", "symbol": "MergeVcfReader.vcf_records"}, "source_id": "csn:umich-brcf-bioinf/Jacquard:jacquard/merge.py:MergeVcfReader.vcf_records#14980"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/umich-brcf-bioinf/Jacquard/blob/83dd61dd2b5e4110468493beec7bc121e6cb3cd1/jacquard/merge.py#L128-L156", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:umich-brcf-bioinf-Jacquard:MergeVcfReader.vcf_records-57cb5a29d5", "question": "Generates parsed VcfRecord objects.\n\n Typically called in a for loop to process each vcf record in a\n VcfReader. VcfReader must be opened in advanced and closed when\n complete. Skips all headers.\n\n Args:\n qualified: When True, sample names are prefixed with file name\n\n Returns:\n Parsed VcfRecord\n\n Raises:\n StopIteration: when reader is exhausted.\n TypeError: if reader is closed.", "scope": {"holder": "umich-brcf-bioinf-Jacquard", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:umich-brcf-bioinf/Jacquard:jacquard/utils/vcf.py:VcfRecord._sample_tag_values#14994", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "jacquard/utils/vcf.py", "symbol": "VcfRecord._sample_tag_values"}, "source_id": "csn:umich-brcf-bioinf/Jacquard:jacquard/utils/vcf.py:VcfRecord._sample_tag_values#14994"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/umich-brcf-bioinf/Jacquard/blob/83dd61dd2b5e4110468493beec7bc121e6cb3cd1/jacquard/utils/vcf.py#L200-L220", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:umich-brcf-bioinf-Jacquard:VcfRecord._sample_tag_values-5f89379127", "question": "Creates a sample dict of tag-value dicts for a single variant record.\n\n Args:\n sample_names: list of sample name strings.\n rformat: record format string (from VCF record).\n sample_fields: list of strings where each string is the ';'\n seperated format values for an individual sample.\n\n Returns:\n An dict of samples, where each key is a sample and each value\n is an dict of format-values. See attribute below for example.\n Will return '.' if no values for sampe field.", "scope": {"holder": "umich-brcf-bioinf-Jacquard", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:un33k/django-toolware:toolware/utils/query.py:CaseInsensitiveQuerySet.case_insensitive#21855", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "toolware/utils/query.py", "symbol": "CaseInsensitiveQuerySet.case_insensitive"}, "source_id": "csn:un33k/django-toolware:toolware/utils/query.py:CaseInsensitiveQuerySet.case_insensitive#21855"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/un33k/django-toolware/blob/973f3e003dc38b812897dab88455bee37dcaf931/toolware/utils/query.py#L62-L70", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:un33k-django-toolware:CaseInsensitiveQuerySet.case_insensitive-f2d2b15733", "question": "Converts queries to case insensitive for special fields.", "scope": {"holder": "un33k-django-toolware", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:un33k/django-toolware:toolware/templatetags/highlight.py:highlight#20518", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "toolware/templatetags/highlight.py", "symbol": "highlight"}, "source_id": "csn:un33k/django-toolware:toolware/templatetags/highlight.py:highlight#20518"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/un33k/django-toolware/blob/973f3e003dc38b812897dab88455bee37dcaf931/toolware/templatetags/highlight.py#L38-L47", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:un33k-django-toolware:highlight-f962224646", "question": "Given an list of words, this function highlights the matched text in the given string.", "scope": {"holder": "un33k-django-toolware", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:unistra/django-rest-framework-custom-exceptions:rest_framework_custom_exceptions/exceptions.py:simple_error_handler#17730", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "rest_framework_custom_exceptions/exceptions.py", "symbol": "simple_error_handler"}, "source_id": "csn:unistra/django-rest-framework-custom-exceptions:rest_framework_custom_exceptions/exceptions.py:simple_error_handler#17730"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/unistra/django-rest-framework-custom-exceptions/blob/b0fdd5c64146c4f25fb893bc84c58d7774ccb5ef/rest_framework_custom_exceptions/exceptions.py#L9-L39", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:unistra-django-rest-framework-custom-exceptions:simple_error_handler-ce2cbbeb09", "question": "Returns the response that should be used for any given exception.\n\n By default we handle the REST framework `APIException`, and also\n Django's builtin `Http404` and `PermissionDenied` exceptions.\n\n Any unhandled exceptions may return `None`, which will cause a 500 error\n to be raised.", "scope": {"holder": "unistra-django-rest-framework-custom-exceptions", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:uogbuji/amara3-xml:pylib/uxml/uxpath/ast.py:_serialize#19157", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pylib/uxml/uxpath/ast.py", "symbol": "_serialize"}, "source_id": "csn:uogbuji/amara3-xml:pylib/uxml/uxpath/ast.py:_serialize#19157"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/uogbuji/amara3-xml/blob/88c18876418cffc89bb85b4a3193e5002b6b39a6/pylib/uxml/uxpath/ast.py#L713-L721", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:uogbuji-amara3-xml:_serialize-a6d41a8649", "question": "Generate token strings which, when joined together, form a valid\n XPath serialization of the AST.", "scope": {"holder": "uogbuji-amara3-xml", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:uogbuji/amara3-xml:pylib/uxml/html5.py:parse#19087", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pylib/uxml/html5.py", "symbol": "parse"}, "source_id": "csn:uogbuji/amara3-xml:pylib/uxml/html5.py:parse#19087"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/uogbuji/amara3-xml/blob/88c18876418cffc89bb85b4a3193e5002b6b39a6/pylib/uxml/html5.py#L230-L250", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:uogbuji-amara3-xml:parse-fede6c24d5", "question": "Parse an input source with HTML text into an Amara 3 tree\n\n >>> from amara3.uxml import html5\n >>> import urllib.request\n >>> with urllib.request.urlopen('http://uche.ogbuji.net/') as response:\n ... html5.parse(response)\n\n\n #Warning: if you pass a string, you must make sure it's a byte string, not a Unicode object. You might also want to wrap it with amara.lib.inputsource.text if it's not obviously XML or HTML (for example it could be confused with a file name)", "scope": {"holder": "uogbuji-amara3-xml", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:uploadcare/pyuploadcare:pyuploadcare/api_resources.py:File.cdn_url#14105", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pyuploadcare/api_resources.py", "symbol": "File.cdn_url"}, "source_id": "csn:uploadcare/pyuploadcare:pyuploadcare/api_resources.py:File.cdn_url#14105"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/uploadcare/pyuploadcare/blob/cefddc0306133a71e37b18e8700df5948ef49b37/pyuploadcare/api_resources.py#L106-L123", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:uploadcare-pyuploadcare:File.cdn_url-a92679515c", "question": "Returns file's CDN url.\n\n Usage example::\n\n >>> file_ = File('a771f854-c2cb-408a-8c36-71af77811f3b')\n >>> file_.cdn_url\n https://ucarecdn.com/a771f854-c2cb-408a-8c36-71af77811f3b/\n\n You can set default effects::\n\n >>> file_.default_effects = 'effect/flip/-/effect/mirror/'\n >>> file_.cdn_url\n https://ucarecdn.com/a771f854-c2cb-408a-8c36-71af77811f3b/-/effect/flip/-/effect/mirror/", "scope": {"holder": "uploadcare-pyuploadcare", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:uploadcare/pyuploadcare:pyuploadcare/api_resources.py:File.upload_from_url_sync#14115", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pyuploadcare/api_resources.py", "symbol": "File.upload_from_url_sync"}, "source_id": "csn:uploadcare/pyuploadcare:pyuploadcare/api_resources.py:File.upload_from_url_sync#14115"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/uploadcare/pyuploadcare/blob/cefddc0306133a71e37b18e8700df5948ef49b37/pyuploadcare/api_resources.py#L437-L468", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:uploadcare-pyuploadcare:File.upload_from_url_sync-fa7268ca1a", "question": "Uploads file from given url and returns ``File`` instance.\n\n Args:\n - url (str): URL of file to upload to\n - store (Optional[bool]): Should the file be automatically stored\n upon upload. Defaults to None.\n - False - do not store file\n - True - store file (can result in error if autostore\n is disabled for project)\n - None - use project settings\n - filename (Optional[str]): Name of the uploaded file. If this not\n specified the filename will be obtained from response headers\n or source URL. Defaults to None.\n - timeout (Optional[int]): seconds to wait for successful upload.\n Defaults to 30.\n - interval (Optional[float]): interval between upload status checks.\n Defaults to 0.3.\n - until_ready (Optional[bool]): should we wait until file is\n available via CDN. Defaults to False.\n\n Returns:\n ``File`` instance\n\n Raises:\n ``TimeoutError`` if file wasn't uploaded in time", "scope": {"holder": "uploadcare-pyuploadcare", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:urda/nistbeacon:scripts/version_manager.py:FileVersionInfo.get_version#15429", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "scripts/version_manager.py", "symbol": "FileVersionInfo.get_version"}, "source_id": "csn:urda/nistbeacon:scripts/version_manager.py:FileVersionInfo.get_version#15429"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/urda/nistbeacon/blob/43e0c3d1e186e71387f072daf98911abb14469dd/scripts/version_manager.py#L58-L83", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:urda-nistbeacon:FileVersionInfo.get_version-5405a355b2", "question": "Open the file referenced in this object, and scrape the version.\n\n :return:\n The version as a string, an empty string if there is no match\n to the magic_line, or any file exception messages encountered.", "scope": {"holder": "urda-nistbeacon", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:urda/nistbeacon:nistbeacon/nistbeaconcrypto.py:NistBeaconCrypto.get_hash#15419", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "nistbeacon/nistbeaconcrypto.py", "symbol": "NistBeaconCrypto.get_hash"}, "source_id": "csn:urda/nistbeacon:nistbeacon/nistbeaconcrypto.py:NistBeaconCrypto.get_hash#15419"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/urda/nistbeacon/blob/43e0c3d1e186e71387f072daf98911abb14469dd/nistbeacon/nistbeaconcrypto.py#L114-L146", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:urda-nistbeacon:NistBeaconCrypto.get_hash-9a7c44a0f2", "question": "Given required properties from a NistBeaconValue,\n compute the SHA512Hash object.\n\n :param version: NistBeaconValue.version\n :param frequency: NistBeaconValue.frequency\n :param timestamp: NistBeaconValue.timestamp\n :param seed_value: NistBeaconValue.seed_value\n :param prev_output: NistBeaconValue.previous_output_value\n :param status_code: NistBeaconValue.status_code\n\n :return: SHA512 Hash for NistBeaconValue signature verification", "scope": {"holder": "urda-nistbeacon", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:urinieto/msaf:msaf/pymf/aa.py:AA.update_w#10788", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "msaf/pymf/aa.py", "symbol": "AA.update_w"}, "source_id": "csn:urinieto/msaf:msaf/pymf/aa.py:AA.update_w#10788"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/urinieto/msaf/blob/9dbb57d77a1310465a65cc40f1641d083ca74385/msaf/pymf/aa.py#L113-L134", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:urinieto-msaf:AA.update_w-64c78ac511", "question": "alternating least squares step, update W under the convexity\n constraint", "scope": {"holder": "urinieto-msaf", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:urinieto/msaf:msaf/eval.py:compute_information_gain#10732", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "msaf/eval.py", "symbol": "compute_information_gain"}, "source_id": "csn:urinieto/msaf:msaf/eval.py:compute_information_gain#10732"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/urinieto/msaf/blob/9dbb57d77a1310465a65cc40f1641d083ca74385/msaf/eval.py#L228-L233", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:urinieto-msaf:compute_information_gain-27ff9c61a0", "question": "Computes the information gain of the est_file from the annotated\n intervals and the estimated intervals.", "scope": {"holder": "urinieto-msaf", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:uucidl/uu.xunitgen:xunitgen/step_recording.py:Recorder.step#18803", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "xunitgen/step_recording.py", "symbol": "Recorder.step"}, "source_id": "csn:uucidl/uu.xunitgen:xunitgen/step_recording.py:Recorder.step#18803"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/uucidl/uu.xunitgen/blob/3c74fe60dfd15a528622195577f2aab3027693f0/xunitgen/step_recording.py#L31-L50", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:uucidl-uu.xunitgen:Recorder.step-453b476b5b", "question": "Start a new step. returns a context manager which allows you to\n report an error", "scope": {"holder": "uucidl-uu.xunitgen", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:uucidl/uu.xunitgen:xunitgen/disk_writing.py:XunitDestination.reserve_file#18745", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "xunitgen/disk_writing.py", "symbol": "XunitDestination.reserve_file"}, "source_id": "csn:uucidl/uu.xunitgen:xunitgen/disk_writing.py:XunitDestination.reserve_file#18745"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/uucidl/uu.xunitgen/blob/3c74fe60dfd15a528622195577f2aab3027693f0/xunitgen/disk_writing.py#L23-L46", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:uucidl-uu.xunitgen:XunitDestination.reserve_file-87e850c083", "question": "reserve a XML file for the slice at <relative_path>.xml\n\n - the relative path will be created for you\n - not writing anything to that file is an error", "scope": {"holder": "uucidl-uu.xunitgen", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:uw-it-aca/uw-restclients-canvas:uw_canvas/accounts.py:Accounts.get_account#13105", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "uw_canvas/accounts.py", "symbol": "Accounts.get_account"}, "source_id": "csn:uw-it-aca/uw-restclients-canvas:uw_canvas/accounts.py:Accounts.get_account#13105"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/uw-it-aca/uw-restclients-canvas/blob/9845faf33d49a8f06908efc22640c001116d6ea2/uw_canvas/accounts.py#L8-L15", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:uw-it-aca-uw-restclients-canvas:Accounts.get_account-46a0b1fd02", "question": "Return account resource for given canvas account id.\n\n https://canvas.instructure.com/doc/api/accounts.html#method.accounts.show", "scope": {"holder": "uw-it-aca-uw-restclients-canvas", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:uw-it-aca/uw-restclients-canvas:uw_canvas/external_tools.py:ExternalTools.get_sessionless_launch_url_from_account_sis_id#13071", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "uw_canvas/external_tools.py", "symbol": "ExternalTools.get_sessionless_launch_url_from_account_sis_id"}, "source_id": "csn:uw-it-aca/uw-restclients-canvas:uw_canvas/external_tools.py:ExternalTools.get_sessionless_launch_url_from_account_sis_id#13071"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/uw-it-aca/uw-restclients-canvas/blob/9845faf33d49a8f06908efc22640c001116d6ea2/uw_canvas/external_tools.py#L135-L143", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:uw-it-aca-uw-restclients-canvas:ExternalTools.get_sessionless_launch_url_from_account_sis_id-678c68cd56", "question": "Get a sessionless launch url for an external tool.\n\n https://canvas.instructure.com/doc/api/external_tools.html#method.external_tools.generate_sessionless_launch", "scope": {"holder": "uw-it-aca-uw-restclients-canvas", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:uw-it-aca/uw-restclients-gws:uw_gws/__init__.py:GWS.create_group#12243", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "uw_gws/__init__.py", "symbol": "GWS.create_group"}, "source_id": "csn:uw-it-aca/uw-restclients-gws:uw_gws/__init__.py:GWS.create_group#12243"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/uw-it-aca/uw-restclients-gws/blob/2aa6038d5f83027bae680e52fc38c2ec0cd192c5/uw_gws/__init__.py#L93-L104", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:uw-it-aca-uw-restclients-gws:GWS.create_group-6c076e14e8", "question": "Creates a group from the passed restclients.Group object.", "scope": {"holder": "uw-it-aca-uw-restclients-gws", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:uw-it-aca/uw-restclients-gws:uw_gws/__init__.py:GWS.get_members#12245", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "uw_gws/__init__.py", "symbol": "GWS.get_members"}, "source_id": "csn:uw-it-aca/uw-restclients-gws:uw_gws/__init__.py:GWS.get_members#12245"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/uw-it-aca/uw-restclients-gws/blob/2aa6038d5f83027bae680e52fc38c2ec0cd192c5/uw_gws/__init__.py#L132-L146", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:uw-it-aca-uw-restclients-gws:GWS.get_members-17fa41bef2", "question": "Returns a list of restclients.GroupMember objects for the group\n identified by the passed group ID.", "scope": {"holder": "uw-it-aca-uw-restclients-gws", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:vaexio/vaex:packages/vaex-core/vaex/dataframe.py:DataFrame._evaluate_selection_mask#3162", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "packages/vaex-core/vaex/dataframe.py", "symbol": "DataFrame._evaluate_selection_mask"}, "source_id": "csn:vaexio/vaex:packages/vaex-core/vaex/dataframe.py:DataFrame._evaluate_selection_mask#3162"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/vaexio/vaex/blob/a45b672f8287afca2ada8e36b74b604b9b28dd85/packages/vaex-core/vaex/dataframe.py#L2529-L2534", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:vaexio-vaex:DataFrame._evaluate_selection_mask-5e6daa03fa", "question": "Internal use, ignores the filter", "scope": {"holder": "vaexio-vaex", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:vaexio/vaex:packages/vaex-core/vaex/dataframe.py:DataFrameLocal.join#3233", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "packages/vaex-core/vaex/dataframe.py", "symbol": "DataFrameLocal.join"}, "source_id": "csn:vaexio/vaex:packages/vaex-core/vaex/dataframe.py:DataFrameLocal.join#3233"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/vaexio/vaex/blob/a45b672f8287afca2ada8e36b74b604b9b28dd85/packages/vaex-core/vaex/dataframe.py#L4970-L5078", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:vaexio-vaex:DataFrameLocal.join-b5faae153b", "question": "Return a DataFrame joined with other DataFrames, matched by columns/expression on/left_on/right_on\n\n If neither on/left_on/right_on is given, the join is done by simply adding the columns (i.e. on the implicit\n row index).\n\n Note: The filters will be ignored when joining, the full DataFrame will be joined (since filters may\n change). If either DataFrame is heavily filtered (contains just a small number of rows) consider running\n :func:`DataFrame.extract` first.\n\n Example:\n\n >>> a = np.array(['a', 'b', 'c'])\n >>> x = np.arange(1,4)\n >>> ds1 = vaex.from_arrays(a=a, x=x)\n >>> b = np.array(['a', 'b', 'd'])\n >>> y = x**2\n >>> ds2 = vaex.from_arrays(b=b, y=y)\n >>> ds1.join(ds2, left_on='a', right_on='b')\n\n :param other: Other DataFrame to join with (the right side)\n :param on: default key for the left table (self)\n :param left_on: key for the left table (self), overrides on\n :param right_on: default key for the right table (other), overrides on\n :param lsuffix: suffix to add to the left column names in case of a name collision\n :param rsuffix: similar for the right\n :param how: how to join, 'left' keeps all rows on the left, and adds columns (with possible missing values)\n 'right' is similar with self and other swapped.\n :param inplace: {inplace}\n :return:", "scope": {"holder": "vaexio-vaex", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:vahtras/findifftool:findifftool/core.py:clgrad#21009", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "findifftool/core.py", "symbol": "clgrad"}, "source_id": "csn:vahtras/findifftool:findifftool/core.py:clgrad#21009"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/vahtras/findifftool/blob/d1b36cc852acc2594c95a4bf7a786d68369802b3/findifftool/core.py#L125-L148", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:vahtras-findifftool:clgrad-61e02cbdb3", "question": "Returns numerical gradient function of given class method\n with respect to a class attribute\n Input: obj, general object\n exe (str), name of object method\n arg (str), name of object atribute\n delta(float, optional), finite difference step\n Output: gradient function object", "scope": {"holder": "vahtras-findifftool", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:vahtras/findifftool:findifftool/core.py:hessian#21006", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "findifftool/core.py", "symbol": "hessian"}, "source_id": "csn:vahtras/findifftool:findifftool/core.py:hessian#21006"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/vahtras/findifftool/blob/d1b36cc852acc2594c95a4bf7a786d68369802b3/findifftool/core.py#L40-L70", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:vahtras-findifftool:hessian-8ec4e6704f", "question": "Returns numerical hessian function of given input function\n Input: f, scalar function of one or two variables\n delta(optional), finite difference step\n Output: hessian function object", "scope": {"holder": "vahtras-findifftool", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:valentinalexeev/pwaqi:pwaqi/__init__.py:findStationCodesByCity#17690", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pwaqi/__init__.py", "symbol": "findStationCodesByCity"}, "source_id": "csn:valentinalexeev/pwaqi:pwaqi/__init__.py:findStationCodesByCity#17690"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/valentinalexeev/pwaqi/blob/81a1fa1ad87be7ba015c1cb07c52c7760ca99d8c/pwaqi/__init__.py#L16-L28", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:valentinalexeev-pwaqi:findStationCodesByCity-5034d7071e", "question": "Lookup AQI database for station codes in a given city.", "scope": {"holder": "valentinalexeev-pwaqi", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:valentinalexeev/pwaqi:pwaqi/__init__.py:get_station_observation#17693", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pwaqi/__init__.py", "symbol": "get_station_observation"}, "source_id": "csn:valentinalexeev/pwaqi:pwaqi/__init__.py:get_station_observation#17693"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/valentinalexeev/pwaqi/blob/81a1fa1ad87be7ba015c1cb07c52c7760ca99d8c/pwaqi/__init__.py#L61-L76", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:valentinalexeev-pwaqi:get_station_observation-49bc0df280", "question": "Request station data for a specific station identified by code.\n\n A language parameter can also be specified to translate location\n information (default: \"en\")", "scope": {"holder": "valentinalexeev-pwaqi", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:valsaven/md5hash:md5hash/md5hash.py:calculate#17778", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "md5hash/md5hash.py", "symbol": "calculate"}, "source_id": "csn:valsaven/md5hash:md5hash/md5hash.py:calculate#17778"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/valsaven/md5hash/blob/83208769a8e9c74bd9e4ce72ac1df00615af82f2/md5hash/md5hash.py#L46-L66", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:valsaven-md5hash:calculate-922de2227e", "question": "Split the tuple (obtained from scan) to separate files.\r\n Alternately send full paths to the files in md5 and call it.\r\n :param directory: tuple of files in the directory.", "scope": {"holder": "valsaven-md5hash", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:valsaven/md5hash:md5hash/md5hash.py:scan#17779", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "md5hash/md5hash.py", "symbol": "scan"}, "source_id": "csn:valsaven/md5hash:md5hash/md5hash.py:scan#17779"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/valsaven/md5hash/blob/83208769a8e9c74bd9e4ce72ac1df00615af82f2/md5hash/md5hash.py#L70-L93", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:valsaven-md5hash:scan-8745ccc0c1", "question": "Scan the directory and send the obtained tuple to calculate.\r\n :param tree: path to file or directory", "scope": {"holder": "valsaven-md5hash", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:varikin/Tigre:tigre/tigre.py:Tigre.sync#19702", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "tigre/tigre.py", "symbol": "Tigre.sync"}, "source_id": "csn:varikin/Tigre:tigre/tigre.py:Tigre.sync#19702"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/varikin/Tigre/blob/6ffac1de52f087cf92cbf368997b336c35a0e3c0/tigre/tigre.py#L108-L116", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:varikin-Tigre:Tigre.sync-e88a9184f7", "question": "Syncs a list of folders to their assicated buckets.\n \n folders: A list of 2-tuples in the form (folder, bucket)", "scope": {"holder": "varikin-Tigre", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:varikin/Tigre:tigre/tigre.py:Tigre.sync_folder#19701", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "tigre/tigre.py", "symbol": "Tigre.sync_folder"}, "source_id": "csn:varikin/Tigre:tigre/tigre.py:Tigre.sync_folder#19701"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/varikin/Tigre/blob/6ffac1de52f087cf92cbf368997b336c35a0e3c0/tigre/tigre.py#L87-L106", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:varikin-Tigre:Tigre.sync_folder-603895c822", "question": "Syncs a local directory with an S3 bucket.\n \n Currently does not delete files from S3 that are not in the local directory.\n\n path: The path to the directory to sync to S3\n bucket: The name of the bucket on S3", "scope": {"holder": "varikin-Tigre", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:versae/ipython-cypher:src/cypher/run.py:ResultSet.bar#16868", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "src/cypher/run.py", "symbol": "ResultSet.bar"}, "source_id": "csn:versae/ipython-cypher:src/cypher/run.py:ResultSet.bar#16868"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/versae/ipython-cypher/blob/1e88bd8227743e70b78af42e0e713ae8803485e1/src/cypher/run.py#L395-L422", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:versae-ipython-cypher:ResultSet.bar-a2911a7ed9", "question": "Generates a pylab bar plot from the result set.\n\n ``matplotlib`` must be installed, and in an\n IPython Notebook, inlining must be on::\n\n %%matplotlib inline\n\n The last quantitative column is taken as the Y values;\n all other columns are combined to label the X axis.\n\n :param title: plot title, defaults to names of Y value columns\n :param key_word_sep: string used to separate column values\n from each other in labels\n\n Any additional keyword arguments will be passsed\n through to ``matplotlib.pylab.bar``.", "scope": {"holder": "versae-ipython-cypher", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:versae/ipython-cypher:src/cypher/run.py:ResultSet.pie#16866", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "src/cypher/run.py", "symbol": "ResultSet.pie"}, "source_id": "csn:versae/ipython-cypher:src/cypher/run.py:ResultSet.pie#16866"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/versae/ipython-cypher/blob/1e88bd8227743e70b78af42e0e713ae8803485e1/src/cypher/run.py#L341-L364", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:versae-ipython-cypher:ResultSet.pie-6c5e1cd409", "question": "Generates a pylab pie chart from the result set.\n\n ``matplotlib`` must be installed, and in an\n IPython Notebook, inlining must be on::\n\n %%matplotlib inline\n\n Values (pie slice sizes) are taken from the\n rightmost column (numerical values required).\n All other columns are used to label the pie slices.\n\n :param key_word_sep: string used to separate column values\n from each other in pie labels\n :param title: plot title, defaults to name of value column\n :kwargs: any additional keyword arguments will be passsed\n through to ``matplotlib.pylab.pie``.", "scope": {"holder": "versae-ipython-cypher", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:victor-o-silva/db_file_storage:db_file_storage/form_widgets.py:db_file_widget#9858", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "db_file_storage/form_widgets.py", "symbol": "db_file_widget"}, "source_id": "csn:victor-o-silva/db_file_storage:db_file_storage/form_widgets.py:db_file_widget#9858"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/victor-o-silva/db_file_storage/blob/ff5375422246c42b8a7bba558f1c3b49bb985f36/db_file_storage/form_widgets.py#L14-L40", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:victor-o-silva-db_file_storage:db_file_widget-c471cb5427", "question": "Edit the download-link inner text.", "scope": {"holder": "victor-o-silva-db_file_storage", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:victor-o-silva/db_file_storage:db_file_storage/model_utils.py:delete_file#9857", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "db_file_storage/model_utils.py", "symbol": "delete_file"}, "source_id": "csn:victor-o-silva/db_file_storage:db_file_storage/model_utils.py:delete_file#9857"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/victor-o-silva/db_file_storage/blob/ff5375422246c42b8a7bba558f1c3b49bb985f36/db_file_storage/model_utils.py#L39-L46", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:victor-o-silva-db_file_storage:delete_file-580ba8c1bb", "question": "Delete the file (if any) from the database.\n\n Call this function immediately AFTER deleting the instance.", "scope": {"holder": "victor-o-silva-db_file_storage", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:vint21h/nagios-check-supervisord:check_supervisord.py:get_status#12902", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "check_supervisord.py", "symbol": "get_status"}, "source_id": "csn:vint21h/nagios-check-supervisord:check_supervisord.py:get_status#12902"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/vint21h/nagios-check-supervisord/blob/a40a542499197a4b5658bd6cc3b34326fe8d0ada/check_supervisord.py#L146-L188", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:vint21h-nagios-check-supervisord:get_status-b4a0819b7a", "question": "Get programs statuses.\n\n :param options: parsed commandline arguments.\n :type options: optparse.Values.\n :return: supervisord XML-RPC call result.\n :rtype: dict.", "scope": {"holder": "vint21h-nagios-check-supervisord", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:vint21h/nagios-check-supervisord:check_supervisord.py:parse_options#12901", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "check_supervisord.py", "symbol": "parse_options"}, "source_id": "csn:vint21h/nagios-check-supervisord:check_supervisord.py:parse_options#12901"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/vint21h/nagios-check-supervisord/blob/a40a542499197a4b5658bd6cc3b34326fe8d0ada/check_supervisord.py#L91-L143", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:vint21h-nagios-check-supervisord:parse_options-0a166f71a8", "question": "Commandline options arguments parsing.\n\n :return: parsed commandline arguments.\n :rtype: optparse.Values.", "scope": {"holder": "vint21h-nagios-check-supervisord", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:vint21h/nagios-notification-google-calendar:notification_google_calendar.py:create_event#19100", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "notification_google_calendar.py", "symbol": "create_event"}, "source_id": "csn:vint21h/nagios-notification-google-calendar:notification_google_calendar.py:create_event#19100"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/vint21h/nagios-notification-google-calendar/blob/ef2b58c939d9d55a69a54b4e6a3fd9b61bde50d4/notification_google_calendar.py#L192-L220", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:vint21h-nagios-notification-google-calendar:create_event-695a2af8bd", "question": "Create event in calendar with sms reminder.", "scope": {"holder": "vint21h-nagios-notification-google-calendar", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:vint21h/nagios-notification-google-calendar:notification_google_calendar.py:parse_config#19097", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "notification_google_calendar.py", "symbol": "parse_config"}, "source_id": "csn:vint21h/nagios-notification-google-calendar:notification_google_calendar.py:parse_config#19097"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/vint21h/nagios-notification-google-calendar/blob/ef2b58c939d9d55a69a54b4e6a3fd9b61bde50d4/notification_google_calendar.py#L107-L145", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:vint21h-nagios-notification-google-calendar:parse_config-c885609ffb", "question": "Get settings from config file.", "scope": {"holder": "vint21h-nagios-notification-google-calendar", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:vkorn/pyvizio:custom_components/vizio/media_player.py:VizioDevice.mute_volume#9773", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "custom_components/vizio/media_player.py", "symbol": "VizioDevice.mute_volume"}, "source_id": "csn:vkorn/pyvizio:custom_components/vizio/media_player.py:VizioDevice.mute_volume#9773"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/vkorn/pyvizio/blob/7153c9ad544195c867c14f8f03c97dba416c0a7a/custom_components/vizio/media_player.py#L201-L206", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:vkorn-pyvizio:VizioDevice.mute_volume-eec6700014", "question": "Mute the volume.", "scope": {"holder": "vkorn-pyvizio", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:vkorn/pyvizio:custom_components/vizio/media_player.py:VizioDevice.volume_down#9775", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "custom_components/vizio/media_player.py", "symbol": "VizioDevice.volume_down"}, "source_id": "csn:vkorn/pyvizio:custom_components/vizio/media_player.py:VizioDevice.volume_down#9775"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/vkorn/pyvizio/blob/7153c9ad544195c867c14f8f03c97dba416c0a7a/custom_components/vizio/media_player.py#L233-L236", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:vkorn-pyvizio:VizioDevice.volume_down-1619687500", "question": "Decreasing volume of the device.", "scope": {"holder": "vkorn-pyvizio", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:voidfiles/lark:lark/ext/flask/flask_redis.py:Redis.init_app#17820", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "lark/ext/flask/flask_redis.py", "symbol": "Redis.init_app"}, "source_id": "csn:voidfiles/lark:lark/ext/flask/flask_redis.py:Redis.init_app#17820"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/voidfiles/lark/blob/e3f202d88b97f7b985a358fe28df7e52204f7846/lark/ext/flask/flask_redis.py#L14-L26", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:voidfiles-lark:Redis.init_app-f185548324", "question": "Used to initialize redis with app object", "scope": {"holder": "voidfiles-lark", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:voidpp/vcp:vcp/project.py:Project.get_dependent_projects#13677", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "vcp/project.py", "symbol": "Project.get_dependent_projects"}, "source_id": "csn:voidpp/vcp:vcp/project.py:Project.get_dependent_projects#13677"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/voidpp/vcp/blob/5538cdb7b43029db9aac9edad823cd87afd89ab5/vcp/project.py#L238-L257", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:voidpp-vcp:Project.get_dependent_projects-efe7c75106", "question": "Get the dependencies of the Project\n\n Args:\n recursive (bool): add the dependant project's dependencies too\n\n Returns:\n dict of project name and project instances", "scope": {"holder": "voidpp-vcp", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:voidpp/vcp:vcp/project_handler_base.py:ProjectHandlerFactory.create#13673", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "vcp/project_handler_base.py", "symbol": "ProjectHandlerFactory.create"}, "source_id": "csn:voidpp/vcp:vcp/project_handler_base.py:ProjectHandlerFactory.create#13673"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/voidpp/vcp/blob/5538cdb7b43029db9aac9edad823cd87afd89ab5/vcp/project_handler_base.py#L18-L37", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:voidpp-vcp:ProjectHandlerFactory.create-e0c737a0ad", "question": "Create a project handler\n\n Args:\n uri (str): schema://something formatted uri\n local_path (str): the project configs directory\n\n Return:\n ProjectHandler derived class instance", "scope": {"holder": "voidpp-vcp", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:vpelletier/python-libaio:libaio/__init__.py:AIOBlock.buffer_list#17762", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "libaio/__init__.py", "symbol": "AIOBlock.buffer_list"}, "source_id": "csn:vpelletier/python-libaio:libaio/__init__.py:AIOBlock.buffer_list#17762"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/vpelletier/python-libaio/blob/5b5a2fed5418e2bd1ac9197fa46c69dae86c6fe3/libaio/__init__.py#L221-L232", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:vpelletier-python-libaio:AIOBlock.buffer_list-534cf69c92", "question": "The buffer list this instance operates on.\n\n Only available in mode != AIOBLOCK_MODE_POLL.\n\n Changes on a submitted transfer are not fully applied until its\n next submission: kernel will still be using original buffer list.", "scope": {"holder": "vpelletier-python-libaio", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:vpelletier/python-libaio:libaio/__init__.py:AIOContext.cancelAll#17767", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "libaio/__init__.py", "symbol": "AIOContext.cancelAll"}, "source_id": "csn:vpelletier/python-libaio:libaio/__init__.py:AIOContext.cancelAll#17767"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/vpelletier/python-libaio/blob/5b5a2fed5418e2bd1ac9197fa46c69dae86c6fe3/libaio/__init__.py#L475-L496", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:vpelletier-python-libaio:AIOContext.cancelAll-d7d7f4a98e", "question": "Cancel all submitted IO blocks.\n\n Blocks until all submitted transfers have been finalised.\n Submitting more transfers or processing completion events while this\n method is running produces undefined behaviour.\n Returns the list of values returned by individual cancellations.\n See \"cancel\" documentation.", "scope": {"holder": "vpelletier-python-libaio", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:wagtail/django-modelcluster:modelcluster/forms.py:ClusterForm.has_changed#7534", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "modelcluster/forms.py", "symbol": "ClusterForm.has_changed"}, "source_id": "csn:wagtail/django-modelcluster:modelcluster/forms.py:ClusterForm.has_changed#7534"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/wagtail/django-modelcluster/blob/bfc8bd755af0ddd49e2aee2f2ca126921573d38b/modelcluster/forms.py#L361-L371", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:wagtail-django-modelcluster:ClusterForm.has_changed-6ba0c7b4a2", "question": "Return True if data differs from initial.", "scope": {"holder": "wagtail-django-modelcluster", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:wagtail/django-modelcluster:modelcluster/fields.py:create_deferring_foreign_related_manager#7535", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "modelcluster/fields.py", "symbol": "create_deferring_foreign_related_manager"}, "source_id": "csn:wagtail/django-modelcluster:modelcluster/fields.py:create_deferring_foreign_related_manager#7535"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/wagtail/django-modelcluster/blob/bfc8bd755af0ddd49e2aee2f2ca126921573d38b/modelcluster/fields.py#L17-L212", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:wagtail-django-modelcluster:create_deferring_foreign_related_manager-c18e07d109", "question": "Create a DeferringRelatedManager class that wraps an ordinary RelatedManager\n with 'deferring' behaviour: any updates to the object set (via e.g. add() or clear())\n are written to a holding area rather than committed to the database immediately.\n Writing to the database is deferred until the model is saved.", "scope": {"holder": "wagtail-django-modelcluster", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:wangwenpei/fantasy:fantasy/utils.py:config_value#13202", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "fantasy/utils.py", "symbol": "config_value"}, "source_id": "csn:wangwenpei/fantasy:fantasy/utils.py:config_value#13202"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/wangwenpei/fantasy/blob/0fe92059bd868f14da84235beb05b217b1d46e4a/fantasy/utils.py#L29-L38", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:wangwenpei-fantasy:config_value-c9d8286aa4", "question": "Get a Flask-Security configuration value.\n\n :param key: The configuration key without the prefix `SECURITY_`\n :param app: An optional specific application to inspect. Defaults to\n Flask's `current_app`\n :param default: An optional default value if the value is not set", "scope": {"holder": "wangwenpei-fantasy", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:wangwenpei/fantasy:fantasy/cli.py:queue#13195", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "fantasy/cli.py", "symbol": "queue"}, "source_id": "csn:wangwenpei/fantasy:fantasy/cli.py:queue#13195"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/wangwenpei/fantasy/blob/0fe92059bd868f14da84235beb05b217b1d46e4a/fantasy/cli.py#L321-L335", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:wangwenpei-fantasy:queue-92c6ba8d9a", "question": "启动队列服务[开发中]", "scope": {"holder": "wangwenpei-fantasy", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:wdecoster/nanogui:nanogui/nanogui.py:init_logs#17478", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "nanogui/nanogui.py", "symbol": "init_logs"}, "source_id": "csn:wdecoster/nanogui:nanogui/nanogui.py:init_logs#17478"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/wdecoster/nanogui/blob/78e4f8ca511c5ca9fd7ccd6ff03e8edd1a5db54d/nanogui/nanogui.py#L77-L88", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:wdecoster-nanogui:init_logs-6d24a6108e", "question": "Initiate log file.", "scope": {"holder": "wdecoster-nanogui", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:wdecoster/nanogui:nanogui/nanoguis.py:nanoPlotGui.validate_integer#17479", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "nanogui/nanoguis.py", "symbol": "nanoPlotGui.validate_integer"}, "source_id": "csn:wdecoster/nanogui:nanogui/nanoguis.py:nanoPlotGui.validate_integer#17479"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/wdecoster/nanogui/blob/78e4f8ca511c5ca9fd7ccd6ff03e8edd1a5db54d/nanogui/nanoguis.py#L454-L471", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:wdecoster-nanogui:nanoPlotGui.validate_integer-bbdec974ef", "question": "Check if text Entry is valid (number).\n\n I have no idea what all these arguments are doing here but took this from\n https://stackoverflow.com/questions/8959815/restricting-the-value-in-tkinter-entry-widget", "scope": {"holder": "wdecoster-nanogui", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:wildfish/argparsetree:argparsetree/cmd.py:BaseCommand.get_description#19492", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "argparsetree/cmd.py", "symbol": "BaseCommand.get_description"}, "source_id": "csn:wildfish/argparsetree:argparsetree/cmd.py:BaseCommand.get_description#19492"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/wildfish/argparsetree/blob/424fb13847c4788cad7084233d008d14e17b901c/argparsetree/cmd.py#L103-L112", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:wildfish-argparsetree:BaseCommand.get_description-316abfe922", "question": "Gets the description of the command. If its not supplied the first sentence of the doc string is used.", "scope": {"holder": "wildfish-argparsetree", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:wildfish/argparsetree:argparsetree/cmd.py:BaseCommand.register_sub_commands#19490", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "argparsetree/cmd.py", "symbol": "BaseCommand.register_sub_commands"}, "source_id": "csn:wildfish/argparsetree:argparsetree/cmd.py:BaseCommand.register_sub_commands#19490"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/wildfish/argparsetree/blob/424fb13847c4788cad7084233d008d14e17b901c/argparsetree/cmd.py#L71-L87", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:wildfish-argparsetree:BaseCommand.register_sub_commands-396bce5945", "question": "Add any sub commands to the argument parser.\n\n :param parser: The argument parser object", "scope": {"holder": "wildfish-argparsetree", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:williamFalcon/test-tube:examples/hpc_cpu_example.py:train#5390", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "examples/hpc_cpu_example.py", "symbol": "train"}, "source_id": "csn:williamFalcon/test-tube:examples/hpc_cpu_example.py:train#5390"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/williamFalcon/test-tube/blob/db5a47067a854f76d89f8066582023c1e184bccb/examples/hpc_cpu_example.py#L5-L31", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:williamFalcon-test-tube:train-bb01e3b57c", "question": "Train your awesome model.\n\n :param hparams: The arguments to run the model with.", "scope": {"holder": "williamFalcon-test-tube", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:williballenthin/ida-settings:ida_settings/ida_settings.py:IDASettings.directory#17726", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "ida_settings/ida_settings.py", "symbol": "IDASettings.directory"}, "source_id": "csn:williballenthin/ida-settings:ida_settings/ida_settings.py:IDASettings.directory#17726"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/williballenthin/ida-settings/blob/ddfeab5bd0b6f6f177d0d50f8078c585602b1d9e/ida_settings/ida_settings.py#L599-L607", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:williballenthin-ida-settings:IDASettings.directory-5abb2ccf16", "question": "Fetch the IDASettings instance for the curren plugin with directory scope.\n\n rtype: IDASettingsInterface", "scope": {"holder": "williballenthin-ida-settings", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:williballenthin/ida-settings:ida_settings/ida_settings.py:add_netnode_plugin_name#17722", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "ida_settings/ida_settings.py", "symbol": "add_netnode_plugin_name"}, "source_id": "csn:williballenthin/ida-settings:ida_settings/ida_settings.py:add_netnode_plugin_name#17722"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/williballenthin/ida-settings/blob/ddfeab5bd0b6f6f177d0d50f8078c585602b1d9e/ida_settings/ida_settings.py#L486-L498", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:williballenthin-ida-settings:add_netnode_plugin_name-1ebff3b27b", "question": "Add the given plugin name to the list of plugin names registered in\n the current IDB.\n Note that this implicitly uses the open IDB via the idc iterface.", "scope": {"holder": "williballenthin-ida-settings", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:willkg/markus:markus/backends/datadog.py:DatadogMetrics.gauge#10349", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "markus/backends/datadog.py", "symbol": "DatadogMetrics.gauge"}, "source_id": "csn:willkg/markus:markus/backends/datadog.py:DatadogMetrics.gauge#10349"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/willkg/markus/blob/0cfbe67fb7ccfa7488b0120d21ddc0cdc1f8ed33/markus/backends/datadog.py#L76-L78", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:willkg-markus:DatadogMetrics.gauge-5f4393361a", "question": "Set a gauge.", "scope": {"holder": "willkg-markus", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:willkg/markus:markus/backends/logging.py:LoggingRollupMetrics.incr#10358", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "markus/backends/logging.py", "symbol": "LoggingRollupMetrics.incr"}, "source_id": "csn:willkg/markus:markus/backends/logging.py:LoggingRollupMetrics.incr#10358"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/willkg/markus/blob/0cfbe67fb7ccfa7488b0120d21ddc0cdc1f8ed33/markus/backends/logging.py#L212-L217", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:willkg-markus:LoggingRollupMetrics.incr-b4d7e95f7a", "question": "Increment a counter.", "scope": {"holder": "willkg-markus", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:willthames/ansible-review:lib/ansiblereview/vars.py:hunt_repeated_yaml_keys#10871", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "lib/ansiblereview/vars.py", "symbol": "hunt_repeated_yaml_keys"}, "source_id": "csn:willthames/ansible-review:lib/ansiblereview/vars.py:hunt_repeated_yaml_keys#10871"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/willthames/ansible-review/blob/c55c8f1d1c009f48c289160a28188ff2f3152486/lib/ansiblereview/vars.py#L7-L38", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:willthames-ansible-review:hunt_repeated_yaml_keys-9d2f2d96ca", "question": "Parses yaml and returns a list of repeated variables and\n the line on which they occur", "scope": {"holder": "willthames-ansible-review", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:wimglenn/wimpy:wimpy/util.py:is_subsequence#18941", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "wimpy/util.py", "symbol": "is_subsequence"}, "source_id": "csn:wimglenn/wimpy:wimpy/util.py:is_subsequence#18941"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/wimglenn/wimpy/blob/4e8ebe4e7052d88c9f88ac7dcaa1b587cc2cf86e/wimpy/util.py#L110-L117", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:wimglenn-wimpy:is_subsequence-da4aa2d953", "question": "Are all the elements of needle contained in haystack, and in the same order?\n There may be other elements interspersed throughout", "scope": {"holder": "wimglenn-wimpy", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:wimglenn/wimpy:wimpy/util.py:strip_suffix#18940", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "wimpy/util.py", "symbol": "strip_suffix"}, "source_id": "csn:wimglenn/wimpy:wimpy/util.py:strip_suffix#18940"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/wimglenn/wimpy/blob/4e8ebe4e7052d88c9f88ac7dcaa1b587cc2cf86e/wimpy/util.py#L61-L68", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:wimglenn-wimpy:strip_suffix-51626eed99", "question": "Removes the suffix, if it's there, otherwise returns input string unchanged.\n If strict is True, also ensures the suffix was present", "scope": {"holder": "wimglenn-wimpy", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:wreckage/django-happenings:happenings/utils/handlers.py:CountHandler._handle_single_chunk#11189", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "happenings/utils/handlers.py", "symbol": "CountHandler._handle_single_chunk"}, "source_id": "csn:wreckage/django-happenings:happenings/utils/handlers.py:CountHandler._handle_single_chunk#11189"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/wreckage/django-happenings/blob/7bca5576efa6cd4c4e87356bf9e5b8cd538ae91d/happenings/utils/handlers.py#L369-L401", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:wreckage-django-happenings:CountHandler._handle_single_chunk-0870f1cb11", "question": "This handles either a non-repeating event chunk, or the first\n month of a repeating event chunk.", "scope": {"holder": "wreckage-django-happenings", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:wreckage/django-happenings:happenings/utils/handlers.py:Repeater.repeat_reverse#11182", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "happenings/utils/handlers.py", "symbol": "Repeater.repeat_reverse"}, "source_id": "csn:wreckage/django-happenings:happenings/utils/handlers.py:Repeater.repeat_reverse#11182"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/wreckage/django-happenings/blob/7bca5576efa6cd4c4e87356bf9e5b8cd538ae91d/happenings/utils/handlers.py#L78-L100", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:wreckage-django-happenings:Repeater.repeat_reverse-c48b8eed87", "question": "Starts from 'start' day and counts backwards until 'end' day.\n 'start' should be >= 'end'. If it's equal to, does nothing.\n If a day falls outside of end_repeat, it won't be counted.", "scope": {"holder": "wreckage-django-happenings", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:wzpan/MusicBoxApi:MusicBoxApi/api.py:geturls_new_api#9843", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "MusicBoxApi/api.py", "symbol": "geturls_new_api"}, "source_id": "csn:wzpan/MusicBoxApi:MusicBoxApi/api.py:geturls_new_api#9843"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/wzpan/MusicBoxApi/blob/d539d4b06c59bdf79b8d44756c325e39fde81f13/MusicBoxApi/api.py#L180-L185", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:wzpan-MusicBoxApi:geturls_new_api-9f9045ea4e", "question": "批量获取音乐的地址", "scope": {"holder": "wzpan-MusicBoxApi", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:wzpan/MusicBoxApi:MusicBoxApi/utils.py:notify#9842", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "MusicBoxApi/utils.py", "symbol": "notify"}, "source_id": "csn:wzpan/MusicBoxApi:MusicBoxApi/utils.py:notify#9842"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/wzpan/MusicBoxApi/blob/d539d4b06c59bdf79b8d44756c325e39fde81f13/MusicBoxApi/utils.py#L38-L44", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:wzpan-MusicBoxApi:notify-abeb0068a5", "question": "Show system notification with duration t (ms)", "scope": {"holder": "wzpan-MusicBoxApi", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:xmartlabs/benderthon:benderthon/caffe_freeze.py:caffe_to_tensorflow_session#15317", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "benderthon/caffe_freeze.py", "symbol": "caffe_to_tensorflow_session"}, "source_id": "csn:xmartlabs/benderthon:benderthon/caffe_freeze.py:caffe_to_tensorflow_session#15317"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/xmartlabs/benderthon/blob/810b6fb90f56136257e7ed12e5a30d17ad7ce6ba/benderthon/caffe_freeze.py#L21-L45", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:xmartlabs-benderthon:caffe_to_tensorflow_session-812cd0535d", "question": "Create a TensorFlow Session from a Caffe model.", "scope": {"holder": "xmartlabs-benderthon", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:xmartlabs/benderthon:benderthon/tf_freeze.py:save_graph_only#15302", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "benderthon/tf_freeze.py", "symbol": "save_graph_only"}, "source_id": "csn:xmartlabs/benderthon:benderthon/tf_freeze.py:save_graph_only#15302"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/xmartlabs/benderthon/blob/810b6fb90f56136257e7ed12e5a30d17ad7ce6ba/benderthon/tf_freeze.py#L42-L48", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:xmartlabs-benderthon:save_graph_only-5a89069f48", "question": "Save a small version of the graph based on a session and the output node names.", "scope": {"holder": "xmartlabs-benderthon", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:xmikos/soapy_power:soapypower/writer.py:BaseWriter.write_async#16747", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "soapypower/writer.py", "symbol": "BaseWriter.write_async"}, "source_id": "csn:xmikos/soapy_power:soapypower/writer.py:BaseWriter.write_async#16747"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/xmikos/soapy_power/blob/46e12659b8d08af764dc09a1f31b0e85a68f808f/soapypower/writer.py#L44-L46", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:xmikos-soapy_power:BaseWriter.write_async-b24aec435c", "question": "Write PSD of one frequncy hop (asynchronously in another thread)", "scope": {"holder": "xmikos-soapy_power", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:xmikos/soapy_power:soapypower/power.py:SoapyPower.sweep#16762", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "soapypower/power.py", "symbol": "SoapyPower.sweep"}, "source_id": "csn:xmikos/soapy_power:soapypower/power.py:SoapyPower.sweep#16762"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/xmikos/soapy_power/blob/46e12659b8d08af764dc09a1f31b0e85a68f808f/soapypower/power.py#L274-L330", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:xmikos-soapy_power:SoapyPower.sweep-85fdbc8568", "question": "Sweep spectrum using frequency hopping", "scope": {"holder": "xmikos-soapy_power", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:xtuml/pyxtuml:xtuml/meta.py:Association.formalize#20075", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "xtuml/meta.py", "symbol": "Association.formalize"}, "source_id": "csn:xtuml/pyxtuml:xtuml/meta.py:Association.formalize#20075"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/xtuml/pyxtuml/blob/7dd9343b9a0191d1db1887ab9288d0a026608d9a/xtuml/meta.py#L204-L238", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:xtuml-pyxtuml:Association.formalize-3ada578e0a", "question": "Formalize the association and expose referential attributes\n on instances.", "scope": {"holder": "xtuml-pyxtuml", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:xtuml/pyxtuml:bridgepoint/oal.py:OALParser.t_DOT#19983", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "bridgepoint/oal.py", "symbol": "OALParser.t_DOT"}, "source_id": "csn:xtuml/pyxtuml:bridgepoint/oal.py:OALParser.t_DOT#19983"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/xtuml/pyxtuml/blob/7dd9343b9a0191d1db1887ab9288d0a026608d9a/bridgepoint/oal.py#L1045-L1048", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:xtuml-pyxtuml:OALParser.t_DOT-1be95ec524", "question": "r\"\\.", "scope": {"holder": "xtuml-pyxtuml", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:xvzf/asyncserial-py:asyncserial/abstract_async_wrapper.py:AbstractAsyncWrapper.read#14932", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "asyncserial/abstract_async_wrapper.py", "symbol": "AbstractAsyncWrapper.read"}, "source_id": "csn:xvzf/asyncserial-py:asyncserial/abstract_async_wrapper.py:AbstractAsyncWrapper.read#14932"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/xvzf/asyncserial-py/blob/36b5867f44ad78ac3d96debb001e8145afef2366/asyncserial/abstract_async_wrapper.py#L138-L149", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:xvzf-asyncserial-py:AbstractAsyncWrapper.read-4aa6c77dd1", "question": "Reads a given number of bytes\n\n :param bytecount: How many bytes to read, leave it at default\n to read everything that is available\n :returns: incoming bytes", "scope": {"holder": "xvzf-asyncserial-py", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:xvzf/asyncserial-py:asyncserial/async_serial_wrapper.py:Serial._read#14933", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "asyncserial/async_serial_wrapper.py", "symbol": "Serial._read"}, "source_id": "csn:xvzf/asyncserial-py:asyncserial/async_serial_wrapper.py:Serial._read#14933"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/xvzf/asyncserial-py/blob/36b5867f44ad78ac3d96debb001e8145afef2366/asyncserial/async_serial_wrapper.py#L94-L114", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:xvzf-asyncserial-py:Serial._read-42b95e73ae", "question": "Reads a given number of bytes\n\n :param num_bytes: How many bytes to read\n :returns: incoming bytes", "scope": {"holder": "xvzf-asyncserial-py", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:yandex/yandex-tank:yandextank/plugins/DataUploader/client.py:APIClient.__make_writer_request#4510", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "yandextank/plugins/DataUploader/client.py", "symbol": "APIClient.__make_writer_request"}, "source_id": "csn:yandex/yandex-tank:yandextank/plugins/DataUploader/client.py:APIClient.__make_writer_request#4510"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/yandex/yandex-tank/blob/d71d63b6ab5de8b8a5ea2b728b6ab9ac0b1ba71b/yandextank/plugins/DataUploader/client.py#L221-L264", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:yandex-yandex-tank:APIClient.__make_writer_request-334b7cf89d", "question": "Send request to writer service.", "scope": {"holder": "yandex-yandex-tank", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:yandex/yandex-tank:yandextank/plugins/Phantom/plugin.py:Plugin.phantom#4529", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "yandextank/plugins/Phantom/plugin.py", "symbol": "Plugin.phantom"}, "source_id": "csn:yandex/yandex-tank:yandextank/plugins/Phantom/plugin.py:Plugin.phantom#4529"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/yandex/yandex-tank/blob/d71d63b6ab5de8b8a5ea2b728b6ab9ac0b1ba71b/yandextank/plugins/Phantom/plugin.py#L75-L82", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:yandex-yandex-tank:Plugin.phantom-0894ad9efc", "question": ":rtype: PhantomConfig", "scope": {"holder": "yandex-yandex-tank", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:yashaka/selene:selene/browser.py:open_url#6552", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "selene/browser.py", "symbol": "open_url"}, "source_id": "csn:yashaka/selene:selene/browser.py:open_url#6552"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/yashaka/selene/blob/123d6142047c3f0a9f0a67da6be0b916e630fd6a/selene/browser.py#L38-L55", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:yashaka-selene:open_url-daf240860e", "question": "Loads a web page in the current browser session.\n :param absolgenerateute_or_relative_url:\n an absolute url to web page in case of config.base_url is not specified,\n otherwise - relative url correspondingly\n\n :Usage:\n open_url('http://mydomain.com/subpage1')\n open_url('http://mydomain.com/subpage2')\n # OR\n config.base_url = 'http://mydomain.com'\n open_url('/subpage1')\n open_url('/subpage2')", "scope": {"holder": "yashaka-selene", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:ybrs/single-beat:singlebeat/beat.py:Config.get_host_identifier#7809", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "singlebeat/beat.py", "symbol": "Config.get_host_identifier"}, "source_id": "csn:ybrs/single-beat:singlebeat/beat.py:Config.get_host_identifier#7809"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/ybrs/single-beat/blob/d036b62d2531710dfd806e9dc2a8d67c77616082/singlebeat/beat.py#L89-L101", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:ybrs-single-beat:Config.get_host_identifier-c0c8871088", "question": "\\\n we try to return IPADDR:PID form to identify where any singlebeat instance is\n running.\n\n :return:", "scope": {"holder": "ybrs-single-beat", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:ybrs/single-beat:singlebeat/beat.py:Process.cli_command_quit#7811", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "singlebeat/beat.py", "symbol": "Process.cli_command_quit"}, "source_id": "csn:ybrs/single-beat:singlebeat/beat.py:Process.cli_command_quit#7811"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/ybrs/single-beat/blob/d036b62d2531710dfd806e9dc2a8d67c77616082/singlebeat/beat.py#L318-L325", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:ybrs-single-beat:Process.cli_command_quit-26470b136f", "question": "\\\n kills the child and exits", "scope": {"holder": "ybrs-single-beat", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:yeonghoey/yhy:yhy/commands/__init__.py:build#19707", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "yhy/commands/__init__.py", "symbol": "build"}, "source_id": "csn:yeonghoey/yhy:yhy/commands/__init__.py:build#19707"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/yeonghoey/yhy/blob/4bce1482c31aeeccff96c4cfd1803b83932604e7/yhy/commands/__init__.py#L5-L15", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:yeonghoey-yhy:build-2aefb26417", "question": "Build CLI dynamically based on the package structure.", "scope": {"holder": "yeonghoey-yhy", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:yougov/motivation:motivation/commands.py:danke#19438", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "motivation/commands.py", "symbol": "danke"}, "source_id": "csn:yougov/motivation:motivation/commands.py:danke#19438"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/yougov/motivation/blob/6239c750ef2180b7d89fcbf9867e87a1ee33af16/motivation/commands.py#L100-L108", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:yougov-motivation:danke-4f2db05fbe", "question": "Danke schön!", "scope": {"holder": "yougov-motivation", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:yougov/motivation:motivation/commands.py:lm#19435", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "motivation/commands.py", "symbol": "lm"}, "source_id": "csn:yougov/motivation:motivation/commands.py:lm#19435"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/yougov/motivation/blob/6239c750ef2180b7d89fcbf9867e87a1ee33af16/motivation/commands.py#L30-L38", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:yougov-motivation:lm-2f90f941e3", "question": "Rico Suave", "scope": {"holder": "yougov-motivation", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:yougov/openpack:openpack/basepack.py:ContentType.from_element#19406", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "openpack/basepack.py", "symbol": "ContentType.from_element"}, "source_id": "csn:yougov/openpack:openpack/basepack.py:ContentType.from_element#19406"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/yougov/openpack/blob/1412ec34c1bab6ba6c8ae5490c2205d696f13717/openpack/basepack.py#L507-L518", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:yougov-openpack:ContentType.from_element-1d68f488aa", "question": "given an element, parse out the proper ContentType", "scope": {"holder": "yougov-openpack", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:yougov/openpack:openpack/basepack.py:Relational.related#19400", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "openpack/basepack.py", "symbol": "Relational.related"}, "source_id": "csn:yougov/openpack:openpack/basepack.py:Relational.related#19400"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/yougov/openpack/blob/1412ec34c1bab6ba6c8ae5490c2205d696f13717/openpack/basepack.py#L46-L52", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:yougov-openpack:Relational.related-c2253bb508", "question": "Return a list of parts related to this one via reltype.", "scope": {"holder": "yougov-openpack", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:youtux/pypebbleapi:pypebbleapi/timeline.py:Timeline.delete_user_pin#20818", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pypebbleapi/timeline.py", "symbol": "Timeline.delete_user_pin"}, "source_id": "csn:youtux/pypebbleapi:pypebbleapi/timeline.py:Timeline.delete_user_pin#20818"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/youtux/pypebbleapi/blob/fe7b49da9c30e4a359cc6245a416862ccb3aa589/pypebbleapi/timeline.py#L157-L171", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:youtux-pypebbleapi:Timeline.delete_user_pin-0df4cdce80", "question": "Delete a user pin.\n\n :param str user_token: The token of the user.\n :param str pin_id: The id of the pin to delete.\n :raises `requests.exceptions.HTTPError`: If an HTTP error occurred.", "scope": {"holder": "youtux-pypebbleapi", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:youtux/pypebbleapi:pypebbleapi/timeline.py:Timeline.send_user_pin#20817", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pypebbleapi/timeline.py", "symbol": "Timeline.send_user_pin"}, "source_id": "csn:youtux/pypebbleapi:pypebbleapi/timeline.py:Timeline.send_user_pin#20817"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/youtux/pypebbleapi/blob/fe7b49da9c30e4a359cc6245a416862ccb3aa589/pypebbleapi/timeline.py#L136-L155", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:youtux-pypebbleapi:Timeline.send_user_pin-ce4e4f45af", "question": "Send a user pin.\n\n :param str user_token: The token of the user.\n :param dict pin: The pin.\n :param bool skip_validation: Whether to skip the validation.\n :raises pypebbleapi.schemas.DocumentError: If the validation process failed.\n :raises `requests.exceptions.HTTPError`: If an HTTP error occurred.", "scope": {"holder": "youtux-pypebbleapi", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:zartstrom/snaptime:snaptime/main.py:SnapTransformation.apply_to_with_tz#13738", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "snaptime/main.py", "symbol": "SnapTransformation.apply_to_with_tz"}, "source_id": "csn:zartstrom/snaptime:snaptime/main.py:SnapTransformation.apply_to_with_tz#13738"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/zartstrom/snaptime/blob/b05ae09d4dccb1b5c8c4ace9c1937b8139672a3c/snaptime/main.py#L119-L131", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:zartstrom-snaptime:SnapTransformation.apply_to_with_tz-7a5c1c773f", "question": "We make sure that after truncating we use the correct timezone,\n even if we 'jump' over a daylight saving time switch.\n\n I.e. if we apply \"@d\" to `Sun Oct 30 04:30:00 CET 2016` (1477798200)\n we want to have `Sun Oct 30 00:00:00 CEST 2016` (1477778400)\n but not `Sun Oct 30 00:00:00 CET 2016` (1477782000)", "scope": {"holder": "zartstrom-snaptime", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:zartstrom/snaptime:snaptime/main.py:snap#13736", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "snaptime/main.py", "symbol": "snap"}, "source_id": "csn:zartstrom/snaptime:snaptime/main.py:snap#13736"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/zartstrom/snaptime/blob/b05ae09d4dccb1b5c8c4ace9c1937b8139672a3c/snaptime/main.py#L169-L182", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:zartstrom-snaptime:snap-769970df77", "question": "Args:\n instruction (string): a string that encodes 0 to n transformations of a time, i.e. \"-1h@h\", \"@mon+2d+4h\", ...\n dttm (datetime):\n Returns:\n datetime: The datetime resulting from applying all transformations to the input datetime.\n\n Example:\n >>> snap(datetime(2016, 1, 1, 15, 30), \"-1h@h\")\n datetime(2016, 1, 1, 14)", "scope": {"holder": "zartstrom-snaptime", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:ze-phyr-us/django-libretto:django_libretto/templatetags/navigation.py:current#20349", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "django_libretto/templatetags/navigation.py", "symbol": "current"}, "source_id": "csn:ze-phyr-us/django-libretto:django_libretto/templatetags/navigation.py:current#20349"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/ze-phyr-us/django-libretto/blob/b19d8aa21b9579ee91e81967a44d1c40f5588b17/django_libretto/templatetags/navigation.py#L11-L22", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:ze-phyr-us-django-libretto:current-0e29415ba7", "question": "Return a class name (string) if the current URL matches the route name specified in ``className``.\n\tIf any URL keyword arguments are provided, they must be matched as well.\n\n\t:param urlName: The route name that the current URL should match. Example: 'accounts:login'.\n\t:param className: The string that is returned if the current URL matches the specified one.\n\t:param kwargs: Any extra URL keyword arguments that must also be present in the current URL for it to match.\n\t:returns: ``className`` if the current URL matches, or an empty string otherwise.", "scope": {"holder": "ze-phyr-us-django-libretto", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:ze-phyr-us/django-libretto:django_libretto/templatetags/navigation.py:pathMatches#20350", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "django_libretto/templatetags/navigation.py", "symbol": "pathMatches"}, "source_id": "csn:ze-phyr-us/django-libretto:django_libretto/templatetags/navigation.py:pathMatches#20350"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/ze-phyr-us/django-libretto/blob/b19d8aa21b9579ee91e81967a44d1c40f5588b17/django_libretto/templatetags/navigation.py#L26-L45", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:ze-phyr-us-django-libretto:pathMatches-936758f20e", "question": ":param path: str\n\t:param urlName: str\n\t:returns: bool.", "scope": {"holder": "ze-phyr-us-django-libretto", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:zenodo/zenodo-accessrequests:zenodo_accessrequests/models.py:AccessRequest.accept#15416", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "zenodo_accessrequests/models.py", "symbol": "AccessRequest.accept"}, "source_id": "csn:zenodo/zenodo-accessrequests:zenodo_accessrequests/models.py:AccessRequest.accept#15416"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/zenodo/zenodo-accessrequests/blob/ce2cf3f1425d02ba4f3ad3202cfca43a1892558a/zenodo_accessrequests/models.py#L344-L350", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:zenodo-zenodo-accessrequests:AccessRequest.accept-9b034c4e75", "question": "Accept request.", "scope": {"holder": "zenodo-zenodo-accessrequests", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:zenodo/zenodo-accessrequests:zenodo_accessrequests/tokens.py:SecretLinkFactory.validate_token#15381", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "zenodo_accessrequests/tokens.py", "symbol": "SecretLinkFactory.validate_token"}, "source_id": "csn:zenodo/zenodo-accessrequests:zenodo_accessrequests/tokens.py:SecretLinkFactory.validate_token#15381"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/zenodo/zenodo-accessrequests/blob/ce2cf3f1425d02ba4f3ad3202cfca43a1892558a/zenodo_accessrequests/tokens.py#L206-L221", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:zenodo-zenodo-accessrequests:SecretLinkFactory.validate_token-17919a8c07", "question": "Validate a secret link token (non-expiring + expiring).", "scope": {"holder": "zenodo-zenodo-accessrequests", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:zinic/pynsive:pynsive/plugin/loader.py:ModuleFinder.add_path#16487", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "pynsive/plugin/loader.py", "symbol": "ModuleFinder.add_path"}, "source_id": "csn:zinic/pynsive:pynsive/plugin/loader.py:ModuleFinder.add_path#16487"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/zinic/pynsive/blob/15bc8b35a91be5817979eb327427b6235b1b411e/pynsive/plugin/loader.py#L93-L100", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:zinic-pynsive:ModuleFinder.add_path-2058a96947", "question": "Adds a path to search through when attempting to look up a module.\n\n :param path: the path the add to the list of searchable paths", "scope": {"holder": "zinic-pynsive", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
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{"answer": "csn:zloidemon/aiohttp_jrpc:aiohttp_jrpc/errors.py:JError.custom#17517", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "aiohttp_jrpc/errors.py", "symbol": "JError.custom"}, "source_id": "csn:zloidemon/aiohttp_jrpc:aiohttp_jrpc/errors.py:JError.custom#17517"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/zloidemon/aiohttp_jrpc/blob/f2ced214844041aa6f18b6bf6e5abeef7b47735e/aiohttp_jrpc/errors.py#L60-L71", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:zloidemon-aiohttp_jrpc:JError.custom-02559fb801", "question": "Specific server side errors use: -32000 to -32099\n reserved for implementation-defined server-errors", "scope": {"holder": "zloidemon-aiohttp_jrpc", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:zloidemon/aiohttp_jrpc:aiohttp_jrpc/__init__.py:Service.valid#17519", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "aiohttp_jrpc/__init__.py", "symbol": "Service.valid"}, "source_id": "csn:zloidemon/aiohttp_jrpc:aiohttp_jrpc/__init__.py:Service.valid#17519"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/zloidemon/aiohttp_jrpc/blob/f2ced214844041aa6f18b6bf6e5abeef7b47735e/aiohttp_jrpc/__init__.py#L87-L100", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:zloidemon-aiohttp_jrpc:Service.valid-79c8346b9e", "question": "Validation data by specific validictory configuration", "scope": {"holder": "zloidemon-aiohttp_jrpc", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:zomux/deepy:deepy/layers/attention.py:Attention.compute_alignments#9221", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "deepy/layers/attention.py", "symbol": "Attention.compute_alignments"}, "source_id": "csn:zomux/deepy:deepy/layers/attention.py:Attention.compute_alignments#9221"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/zomux/deepy/blob/090fbad22a08a809b12951cd0d4984f5bd432698/deepy/layers/attention.py#L29-L50", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:zomux-deepy:Attention.compute_alignments-ee458f2d86", "question": "Compute the alignment weights based on the previous state.", "scope": {"holder": "zomux-deepy", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:zomux/deepy:deepy/networks/network.py:NeuralNetwork.compute#9280", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "deepy/networks/network.py", "symbol": "NeuralNetwork.compute"}, "source_id": "csn:zomux/deepy:deepy/networks/network.py:NeuralNetwork.compute#9280"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/zomux/deepy/blob/090fbad22a08a809b12951cd0d4984f5bd432698/deepy/networks/network.py#L198-L207", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:zomux-deepy:NeuralNetwork.compute-e402211d87", "question": "Return network output.", "scope": {"holder": "zomux-deepy", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:zorg/zorg-network-camera:zorg_network_camera/adaptor.py:Camera.download_image#19803", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "zorg_network_camera/adaptor.py", "symbol": "Camera.download_image"}, "source_id": "csn:zorg/zorg-network-camera:zorg_network_camera/adaptor.py:Camera.download_image#19803"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/zorg/zorg-network-camera/blob/e2d15725e50370e2df0c38be6b039215873e4278/zorg_network_camera/adaptor.py#L22-L40", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:zorg-zorg-network-camera:Camera.download_image-21d54c31be", "question": "Download the image and return the\n local path to the image file.", "scope": {"holder": "zorg-zorg-network-camera", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:zorg/zorg-network-camera:zorg_network_camera/adaptor.py:Camera.has_changed#19804", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "zorg_network_camera/adaptor.py", "symbol": "Camera.has_changed"}, "source_id": "csn:zorg/zorg-network-camera:zorg_network_camera/adaptor.py:Camera.has_changed#19804"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/zorg/zorg-network-camera/blob/e2d15725e50370e2df0c38be6b039215873e4278/zorg_network_camera/adaptor.py#L42-L67", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:zorg-zorg-network-camera:Camera.has_changed-7c8629d988", "question": "Method to check if an image has changed\n since it was last downloaded. By making\n a head request, this check can be done\n quicker that downloading and processing\n the whole file.", "scope": {"holder": "zorg-zorg-network-camera", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": "csn:zqfang/GSEApy:gseapy/parser.py:Biomart.get_datasets#6252", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "gseapy/parser.py", "symbol": "Biomart.get_datasets"}, "source_id": "csn:zqfang/GSEApy:gseapy/parser.py:Biomart.get_datasets#6252"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/zqfang/GSEApy/blob/673e9ec1391e3b14d3e8a4353117151fd2cb9345/gseapy/parser.py#L219-L223", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:zqfang-GSEApy:Biomart.get_datasets-9a6d155862", "question": "Get available datasets from mart you've selected", "scope": {"holder": "zqfang-GSEApy", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:zqfang/GSEApy:gseapy/__main__.py:add_output_option#6228", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "gseapy/__main__.py", "symbol": "add_output_option"}, "source_id": "csn:zqfang/GSEApy:gseapy/__main__.py:add_output_option#6228"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/zqfang/GSEApy/blob/673e9ec1391e3b14d3e8a4353117151fd2cb9345/gseapy/__main__.py#L112-L131", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:zqfang-GSEApy:add_output_option-b181308d86", "question": "output option", "scope": {"holder": "zqfang-GSEApy", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": false}
{"answer": "csn:zsennenga/module-discovery-utils:module_discovery_utils/module_discovery_utils.py:load_all_modules_in_packages#22080", "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [{"region": {"path": "module_discovery_utils/module_discovery_utils.py", "symbol": "load_all_modules_in_packages"}, "source_id": "csn:zsennenga/module-discovery-utils:module_discovery_utils/module_discovery_utils.py:load_all_modules_in_packages#22080"}], "modality": "code", "origin": {"dataset": "code-search-net/code_search_net", "item": "url:https://github.com/zsennenga/module-discovery-utils/blob/146d31051915f2347483fff9549eb272bd6b7d45/module_discovery_utils/module_discovery_utils.py#L8-L50", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:zsennenga-module-discovery-utils:load_all_modules_in_packages-ebaf9085f9", "question": "Recursively loads all modules from a package object, or set of package objects\n\n :param package_or_set_of_packages: package object, or iterable of package objects\n :return: list of all unique modules discovered by the function", "scope": {"holder": "zsennenga-module-discovery-utils", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": false}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/soimort/you-get/blob/b746ac01c9f39de94cac2d56f665285b0523b974/src/you_get/extractors/sina.py#L41-L52", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:soimort-you-get:sina_download_by_vid-10e4c0fef2@held-out", "question": "Downloads a Sina video by its unique vid.\n http://video.sina.com.cn/", "scope": {"holder": "soimort-you-get", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/soimort/you-get/blob/b746ac01c9f39de94cac2d56f665285b0523b974/src/you_get/util/log.py#L72-L74", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:soimort-you-get:print_log-07dfe0bd07@held-out", "question": "Print a log message to standard error.", "scope": {"holder": "soimort-you-get", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/soimort/you-get/blob/b746ac01c9f39de94cac2d56f665285b0523b974/src/you_get/extractors/vimeo.py#L15-L19", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:soimort-you-get:vimeo_download_by_channel-4832d30729@held-out", "question": "str->None", "scope": {"holder": "soimort-you-get", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
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{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/soimort/you-get/blob/b746ac01c9f39de94cac2d56f665285b0523b974/src/you_get/__main__.py#L24-L85", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:soimort-you-get:main_dev-59fb06672e@held-out", "question": "Main entry point.\n you-get-dev", "scope": {"holder": "soimort-you-get", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
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{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/soimort/you-get/blob/b746ac01c9f39de94cac2d56f665285b0523b974/src/you_get/extractors/wanmen.py#L69-L84", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:soimort-you-get:wanmen_download_by_course_topic_part-8f134fd40b@held-out", "question": "int, int, int->None\n \n Download ONE PART of the course.", "scope": {"holder": "soimort-you-get", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/hooks/mysql_hook.py#L62-L105", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:MySqlHook.get_conn-cfac5930d6@held-out", "question": "Returns a mysql connection object", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/hooks/gcp_translate_hook.py#L45-L97", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:CloudTranslateHook.translate-b151950448@held-out", "question": "Translate a string or list of strings.\n\n See https://cloud.google.com/translate/docs/translating-text\n\n :type values: str or list\n :param values: String or list of strings to translate.\n\n :type target_language: str\n :param target_language: The language to translate results into. This\n is required by the API and defaults to\n the target language of the current instance.\n\n :type format_: str\n :param format_: (Optional) One of ``text`` or ``html``, to specify\n if the input text is plain text or HTML.\n\n :type source_language: str or None\n :param source_language: (Optional) The language of the text to\n be translated.\n\n :type model: str or None\n :param model: (Optional) The model used to translate the text, such\n as ``'base'`` or ``'nmt'``.\n\n :rtype: str or list\n :returns: A list of dictionaries for each queried value. Each\n dictionary typically contains three keys (though not\n all will be present in all cases)\n\n * ``detectedSourceLanguage``: The detected language (as an\n ISO 639-1 language code) of the text.\n * ``translatedText``: The translation of the text into the\n target language.\n * ``input``: The corresponding input value.\n * ``model``: The model used to translate the text.\n\n If only a single value is passed, then only a single\n dictionary will be returned.\n :raises: :class:`~exceptions.ValueError` if the number of\n values and translations differ.", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/operators/bash_operator.py#L86-L144", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:BashOperator.execute-2a50a1f858@held-out", "question": "Execute the bash command in a temporary directory\n which will be cleaned afterwards", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/hooks/gcp_sql_hook.py#L163-L180", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:CloudSqlHook.delete_instance-d0a7571d16@held-out", "question": "Deletes a Cloud SQL instance.\n\n :param project_id: Project ID of the project that contains the instance. If set\n to None or missing, the default project_id from the GCP connection is used.\n :type project_id: str\n :param instance: Cloud SQL instance ID. This does not include the project ID.\n :type instance: str\n :return: None", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/hooks/gcp_sql_hook.py#L282-L310", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:CloudSqlHook.export_instance-3d0f944c62@held-out", "question": "Exports data from a Cloud SQL instance to a Cloud Storage bucket as a SQL dump\n or CSV file.\n\n :param instance: Database instance ID of the Cloud SQL instance. This does not include the\n project ID.\n :type instance: str\n :param body: The request body, as described in\n https://cloud.google.com/sql/docs/mysql/admin-api/v1beta4/instances/export#request-body\n :type body: dict\n :param project_id: Project ID of the project that contains the instance. If set\n to None or missing, the default project_id from the GCP connection is used.\n :type project_id: str\n :return: None", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/hooks/gcp_sql_hook.py#L343-L368", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:CloudSqlHook._wait_for_operation_to_complete-d045076559@held-out", "question": "Waits for the named operation to complete - checks status of the\n asynchronous call.\n\n :param project_id: Project ID of the project that contains the instance.\n :type project_id: str\n :param operation_name: Name of the operation.\n :type operation_name: str\n :return: None", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/scripts/perf/scheduler_ops_metrics.py#L151-L166", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:clear_dag_task_instances-d6fc35092b@held-out", "question": "Remove any existing task instances for the perf test DAGs.", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/scripts/perf/scheduler_ops_metrics.py#L65-L101", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:SchedulerMetricsJob.print_stats-c9d6ee7055@held-out", "question": "Print operational metrics for the scheduler test.", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/scripts/perf/scheduler_ops_metrics.py#L103-L135", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:SchedulerMetricsJob.heartbeat-79f55c0f6f@held-out", "question": "Override the scheduler heartbeat to determine when the test is complete", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/utils/timezone.py#L160-L169", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:datetime-139d50e1c7@held-out", "question": "Wrapper around datetime.datetime that adds settings.TIMEZONE if tzinfo not specified\n\n :return: datetime.datetime", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/hooks/http_hook.py#L183-L211", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:HttpHook.run_with_advanced_retry-8579b5c4cd@held-out", "question": "Runs Hook.run() with a Tenacity decorator attached to it. This is useful for\n connectors which might be disturbed by intermittent issues and should not\n instantly fail.\n\n :param _retry_args: Arguments which define the retry behaviour.\n See Tenacity documentation at https://github.com/jd/tenacity\n :type _retry_args: dict\n\n\n :Example::\n\n hook = HttpHook(http_conn_id='my_conn',method='GET')\n retry_args = dict(\n wait=tenacity.wait_exponential(),\n stop=tenacity.stop_after_attempt(10),\n retry=requests.exceptions.ConnectionError\n )\n hook.run_with_advanced_retry(\n endpoint='v1/test',\n _retry_args=retry_args\n )", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/hooks/azure_cosmos_hook.py#L162-L169", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:AzureCosmosDBHook.delete_database-85caeb0739@held-out", "question": "Deletes an existing database in CosmosDB.", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/hooks/azure_cosmos_hook.py#L255-L275", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:AzureCosmosDBHook.get_documents-520d94439b@held-out", "question": "Get a list of documents from an existing collection in the CosmosDB database via SQL query.", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/hooks/gcp_function_hook.py#L130-L159", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:GcfHook.upload_function_zip-93c31808f4@held-out", "question": "Uploads zip file with sources.\n\n :param location: The location where the function is created.\n :type location: str\n :param zip_path: The path of the valid .zip file to upload.\n :type zip_path: str\n :param project_id: Optional, Google Cloud Project project_id where the function belongs.\n If set to None or missing, the default project_id from the GCP connection is used.\n :type project_id: str\n :return: The upload URL that was returned by generateUploadUrl method.", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/hooks/gcp_function_hook.py#L161-L172", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:GcfHook.delete_function-9effb87c25@held-out", "question": "Deletes the specified Cloud Function.\n\n :param name: The name of the function.\n :type name: str\n :return: None", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/hooks/gcp_pubsub_hook.py#L139-L194", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:PubSubHook.create_subscription-5172a20c23@held-out", "question": "Creates a Pub/Sub subscription, if it does not already exist.\n\n :param topic_project: the GCP project ID of the topic that the\n subscription will be bound to.\n :type topic_project: str\n :param topic: the Pub/Sub topic name that the subscription will be bound\n to create; do not include the ``projects/{project}/subscriptions/``\n prefix.\n :type topic: str\n :param subscription: the Pub/Sub subscription name. If empty, a random\n name will be generated using the uuid module\n :type subscription: str\n :param subscription_project: the GCP project ID where the subscription\n will be created. If unspecified, ``topic_project`` will be used.\n :type subscription_project: str\n :param ack_deadline_secs: Number of seconds that a subscriber has to\n acknowledge each message pulled from the subscription\n :type ack_deadline_secs: int\n :param fail_if_exists: if set, raise an exception if the topic\n already exists\n :type fail_if_exists: bool\n :return: subscription name which will be the system-generated value if\n the ``subscription`` parameter is not supplied\n :rtype: str", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/ti_deps/deps/base_ti_dep.py#L128-L142", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:BaseTIDep.get_failure_reasons-68551db498@held-out", "question": "Returns an iterable of strings that explain why this dependency wasn't met.\n\n :param ti: the task instance to see if this dependency is met for\n :type ti: airflow.models.TaskInstance\n :param session: database session\n :type session: sqlalchemy.orm.session.Session\n :param dep_context: The context this dependency is being checked under that stores\n state that can be used by this dependency.\n :type dep_context: BaseDepContext", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/hooks/vertica_hook.py#L35-L53", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:VerticaHook.get_conn-f0b559e239@held-out", "question": "Returns verticaql connection object", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/utils/dag_processing.py#L900-L918", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:DagFileProcessorManager._refresh_dag_dir-7545466899@held-out", "question": "Refresh file paths from dag dir if we haven't done it for too long.", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/utils/dag_processing.py#L946-L1020", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:DagFileProcessorManager._log_file_processing_stats-98c7cab758@held-out", "question": "Print out stats about how files are getting processed.\n\n :param known_file_paths: a list of file paths that may contain Airflow\n DAG definitions\n :type known_file_paths: list[unicode]\n :return: None", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/utils/dag_processing.py#L1126-L1227", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:DagFileProcessorManager.heartbeat-377fabab58@held-out", "question": "This should be periodically called by the manager loop. This method will\n kick off new processes to process DAG definition files and read the\n results from the finished processors.\n\n :return: a list of SimpleDags that were produced by processors that\n have finished since the last time this was called\n :rtype: list[airflow.utils.dag_processing.SimpleDag]", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/utils/dag_processing.py#L1264-L1275", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:DagFileProcessorManager.max_runs_reached-d6505bf59b@held-out", "question": ":return: whether all file paths have been processed max_runs times", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/utils/dag_processing.py#L1285-L1320", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:DagFileProcessorManager.end-ebbba1ab73@held-out", "question": "Kill all child processes on exit since we don't want to leave\n them as orphaned.", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/hooks/gcp_transfer_hook.py#L235-L243", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:GCPTransferServiceHook.cancel_transfer_operation-26eae5de2d@held-out", "question": "Cancels an transfer operation in Google Storage Transfer Service.\n\n :param operation_name: Name of the transfer operation.\n :type operation_name: str\n :rtype: None", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/hooks/gcp_transfer_hook.py#L301-L309", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:GCPTransferServiceHook.pause_transfer_operation-133232e196@held-out", "question": "Pauses an transfer operation in Google Storage Transfer Service.\n\n :param operation_name: (Required) Name of the transfer operation.\n :type operation_name: str\n :rtype: None", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/hooks/gcp_transfer_hook.py#L361-L397", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:GCPTransferServiceHook.operations_contain_expected_statuses-2a87d5bef1@held-out", "question": "Checks whether the operation list has an operation with the\n expected status, then returns true\n If it encounters operations in FAILED or ABORTED state\n throw :class:`airflow.exceptions.AirflowException`.\n\n :param operations: (Required) List of transfer operations to check.\n :type operations: list[dict]\n :param expected_statuses: (Required) status that is expected\n See:\n https://cloud.google.com/storage-transfer/docs/reference/rest/v1/transferOperations#Status\n :type expected_statuses: set[str]\n :return: If there is an operation with the expected state\n in the operation list, returns true,\n :raises: airflow.exceptions.AirflowException If it encounters operations\n with a state in the list,\n :rtype: bool", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/models/taskreschedule.py#L67-L85", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:TaskReschedule.find_for_task_instance-79b46a272b@held-out", "question": "Returns all task reschedules for the task instance and try number,\n in ascending order.\n\n :param task_instance: the task instance to find task reschedules for\n :type task_instance: airflow.models.TaskInstance", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/configuration.py#L297-L307", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:AirflowConfigParser.remove_option-f757175c0c@held-out", "question": "Remove an option if it exists in config from a file or\n default config. If both of config have the same option, this removes\n the option in both configs unless remove_default=False.", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/hooks/gcp_natural_language_hook.py#L44-L53", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:CloudNaturalLanguageHook.get_conn-2011e81a7e@held-out", "question": "Retrieves connection to Cloud Natural Language service.\n\n :return: Cloud Natural Language service object\n :rtype: google.cloud.language_v1.LanguageServiceClient", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/settings.py#L166-L177", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:dispose_orm-6744742f12@held-out", "question": "Properly close pooled database connections", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/operators/__init__.py#L21-L27", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:_integrate_plugins-245f821917@held-out", "question": "Integrate plugins to the context", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/hooks/gcp_dataproc_hook.py#L243-L247", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:DataProcHook.wait-2c755fd882@held-out", "question": "Awaits for Google Cloud Dataproc Operation to complete.", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/hooks/gcp_mlengine_hook.py#L257-L273", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:MLEngineHook.get_model-4889447edd@held-out", "question": "Gets a Model. Blocks until finished.", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/executors/__init__.py#L64-L95", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:_get_executor-85ab2e22cd@held-out", "question": "Creates a new instance of the named executor.\n In case the executor name is not know in airflow,\n look for it in the plugins", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/hooks/segment_hook.py#L83-L90", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:SegmentHook.on_error-a7c39e4d3b@held-out", "question": "Handles error callbacks when using Segment with segment_debug_mode set to True", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/operators/spark_submit_operator.py#L147-L176", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:SparkSubmitOperator.execute-c2ff962625@held-out", "question": "Call the SparkSubmitHook to run the provided spark job", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/www/api/experimental/endpoints.py#L47-L92", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:trigger_dag-4b01ff524c@held-out", "question": "Trigger a new dag run for a Dag with an execution date of now unless\n specified in the data.", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/www/api/experimental/endpoints.py#L198-L232", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:task_instance_info-5874a16493@held-out", "question": "Returns a JSON with a task instance's public instance variables.\n The format for the exec_date is expected to be\n \"YYYY-mm-DDTHH:MM:SS\", for example: \"2016-11-16T11:34:15\". This will\n of course need to have been encoded for URL in the request.", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/hooks/azure_container_instance_hook.py#L118-L131", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:AzureContainerInstanceHook.get_messages-23b18ff0ef@held-out", "question": "Get the messages of a container group\n\n :param resource_group: the name of the resource group\n :type resource_group: str\n :param name: the name of the container group\n :type name: str\n :return: A list of the event messages\n :rtype: list[str]", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/hooks/azure_container_instance_hook.py#L133-L147", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:AzureContainerInstanceHook.get_logs-6be4b7df90@held-out", "question": "Get the tail from logs of a container group\n\n :param resource_group: the name of the resource group\n :type resource_group: str\n :param name: the name of the container group\n :type name: str\n :param tail: the size of the tail\n :type tail: int\n :return: A list of log messages\n :rtype: list[str]", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/operators/hive_to_druid.py#L157-L244", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:HiveToDruidTransfer.construct_ingest_query-6a66e65afb@held-out", "question": "Builds an ingest query for an HDFS TSV load.\n\n :param static_path: The path on hdfs where the data is\n :type static_path: str\n :param columns: List of all the columns that are available\n :type columns: list", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/utils/operator_helpers.py#L33-L66", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:context_to_airflow_vars-5e5414e5fd@held-out", "question": "Given a context, this function provides a dictionary of values that can be used to\n externally reconstruct relations between dags, dag_runs, tasks and task_instances.\n Default to abc.def.ghi format and can be made to ABC_DEF_GHI format if\n in_env_var_format is set to True.\n\n :param context: The context for the task_instance of interest.\n :type context: dict\n :param in_env_var_format: If returned vars should be in ABC_DEF_GHI format.\n :type in_env_var_format: bool\n :return: task_instance context as dict.", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/utils/cli_action_loggers.py#L57-L69", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:on_pre_execution-e62c8d81ae@held-out", "question": "Calls callbacks before execution.\n Note that any exception from callback will be logged but won't be propagated.\n :param kwargs:\n :return: None", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/utils/cli_action_loggers.py#L72-L86", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:on_post_execution-ee8f846e45@held-out", "question": "Calls callbacks after execution.\n As it's being called after execution, it can capture status of execution,\n duration, etc. Note that any exception from callback will be logged but\n won't be propagated.\n :param kwargs:\n :return: None", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/macros/__init__.py#L49-L66", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:ds_format-02ce56e251@held-out", "question": "Takes an input string and outputs another string\n as specified in the output format\n\n :param ds: input string which contains a date\n :type ds: str\n :param input_format: input string format. E.g. %Y-%m-%d\n :type input_format: str\n :param output_format: output string format E.g. %Y-%m-%d\n :type output_format: str\n\n >>> ds_format('2015-01-01', \"%Y-%m-%d\", \"%m-%d-%y\")\n '01-01-15'\n >>> ds_format('1/5/2015', \"%m/%d/%Y\", \"%Y-%m-%d\")\n '2015-01-05'", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/models/taskinstance.py#L1271-L1301", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:TaskInstance.xcom_push-237aec314f@held-out", "question": "Make an XCom available for tasks to pull.\n\n :param key: A key for the XCom\n :type key: str\n :param value: A value for the XCom. The value is pickled and stored\n in the database.\n :type value: any pickleable object\n :param execution_date: if provided, the XCom will not be visible until\n this date. This can be used, for example, to send a message to a\n task on a future date without it being immediately visible.\n :type execution_date: datetime", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/hooks/gcp_compute_hook.py#L55-L66", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:GceHook.get_conn-05ab7b94be@held-out", "question": "Retrieves connection to Google Compute Engine.\n\n :return: Google Compute Engine services object\n :rtype: dict", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/hooks/gcp_compute_hook.py#L131-L159", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:GceHook.set_machine_type-de5d0dfd84@held-out", "question": "Sets machine type of an instance defined by project_id, zone and resource_id.\n Must be called with keyword arguments rather than positional.\n\n :param zone: Google Cloud Platform zone where the instance exists.\n :type zone: str\n :param resource_id: Name of the Compute Engine instance resource\n :type resource_id: str\n :param body: Body required by the Compute Engine setMachineType API,\n as described in\n https://cloud.google.com/compute/docs/reference/rest/v1/instances/setMachineType\n :type body: dict\n :param project_id: Optional, Google Cloud Platform project ID where the\n Compute Engine Instance exists. If set to None or missing,\n the default project_id from the GCP connection is used.\n :type project_id: str\n :return: None", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/hooks/S3_hook.py#L185-L202", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:S3Hook.check_for_key-d734f4dbb0@held-out", "question": "Checks if a key exists in a bucket\n\n :param key: S3 key that will point to the file\n :type key: str\n :param bucket_name: Name of the bucket in which the file is stored\n :type bucket_name: str", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/hooks/S3_hook.py#L424-L457", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:S3Hook.load_file_obj-b728c0b92b@held-out", "question": "Loads a file object to S3\n\n :param file_obj: The file-like object to set as the content for the S3 key.\n :type file_obj: file-like object\n :param key: S3 key that will point to the file\n :type key: str\n :param bucket_name: Name of the bucket in which to store the file\n :type bucket_name: str\n :param replace: A flag that indicates whether to overwrite the key\n if it already exists.\n :type replace: bool\n :param encrypt: If True, S3 encrypts the file on the server,\n and the file is stored in encrypted form at rest in S3.\n :type encrypt: bool", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/operators/cassandra_to_gcs.py#L258-L266", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:CassandraToGoogleCloudStorageOperator.convert_tuple_type-733bc90bfd@held-out", "question": "Converts a tuple to RECORD that contains n fields, each will be converted\n to its corresponding data type in bq and will be named 'field_<index>', where\n index is determined by the order of the tuple elements defined in cassandra.", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/utils/sendgrid.py#L33-L102", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:send_email-13295b69a8@held-out", "question": "Send an email with html content using sendgrid.\n\n To use this plugin:\n 0. include sendgrid subpackage as part of your Airflow installation, e.g.,\n pip install 'apache-airflow[sendgrid]'\n 1. update [email] backend in airflow.cfg, i.e.,\n [email]\n email_backend = airflow.contrib.utils.sendgrid.send_email\n 2. configure Sendgrid specific environment variables at all Airflow instances:\n SENDGRID_MAIL_FROM={your-mail-from}\n SENDGRID_API_KEY={your-sendgrid-api-key}.", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/hooks/azure_data_lake_hook.py#L106-L141", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:AzureDataLakeHook.download_file-b3163ad3f3@held-out", "question": "Download a file from Azure Blob Storage.\n\n :param local_path: local path. If downloading a single file, will write to this\n specific file, unless it is an existing directory, in which case a file is\n created within it. If downloading multiple files, this is the root\n directory to write within. Will create directories as required.\n :type local_path: str\n :param remote_path: remote path/globstring to use to find remote files.\n Recursive glob patterns using `**` are not supported.\n :type remote_path: str\n :param nthreads: Number of threads to use. If None, uses the number of cores.\n :type nthreads: int\n :param overwrite: Whether to forcibly overwrite existing files/directories.\n If False and remote path is a directory, will quit regardless if any files\n would be overwritten or not. If True, only matching filenames are actually\n overwritten.\n :type overwrite: bool\n :param buffersize: int [2**22]\n Number of bytes for internal buffer. This block cannot be bigger than\n a chunk and cannot be smaller than a block.\n :type buffersize: int\n :param blocksize: int [2**22]\n Number of bytes for a block. Within each chunk, we write a smaller\n block for each API call. This block cannot be bigger than a chunk.\n :type blocksize: int", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/utils/compression.py#L26-L43", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:uncompress_file-a2145e00a4@held-out", "question": "Uncompress gz and bz2 files", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/operators/mssql_to_gcs.py#L214-L222", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:MsSqlToGoogleCloudStorageOperator.convert_types-0cb08f8f2c@held-out", "question": "Takes a value from MSSQL, and converts it to a value that's safe for\n JSON/Google Cloud Storage/BigQuery.", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/hooks/salesforce_hook.py#L95-L108", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:SalesforceHook.describe_object-b13243e69a@held-out", "question": "Get the description of an object from Salesforce.\n This description is the object's schema and\n some extra metadata that Salesforce stores for each object.\n\n :param obj: The name of the Salesforce object that we are getting a description of.\n :type obj: str\n :return: the description of the Salesforce object.\n :rtype: dict", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/hooks/salesforce_hook.py#L125-L145", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:SalesforceHook.get_object_from_salesforce-11d1eebc20@held-out", "question": "Get all instances of the `object` from Salesforce.\n For each model, only get the fields specified in fields.\n\n All we really do underneath the hood is run:\n SELECT <fields> FROM <obj>;\n\n :param obj: The object name to get from Salesforce.\n :type obj: str\n :param fields: The fields to get from the object.\n :type fields: iterable\n :return: all instances of the object from Salesforce.\n :rtype: dict", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/hooks/mongo_hook.py#L93-L102", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:MongoHook.get_collection-5ecdfcc6d5@held-out", "question": "Fetches a mongo collection object for querying.\n\n Uses connection schema as DB unless specified.", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/hooks/mongo_hook.py#L104-L112", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:MongoHook.aggregate-9ff0cc15ca@held-out", "question": "Runs an aggregation pipeline and returns the results\n https://api.mongodb.com/python/current/api/pymongo/collection.html#pymongo.collection.Collection.aggregate\n https://api.mongodb.com/python/current/examples/aggregation.html", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/ti_deps/deps/ready_to_reschedule.py#L34-L69", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:ReadyToRescheduleDep._get_dep_statuses-fc04da92e2@held-out", "question": "Determines whether a task is ready to be rescheduled. Only tasks in\n NONE state with at least one row in task_reschedule table are\n handled by this dependency class, otherwise this dependency is\n considered as passed. This dependency fails if the latest reschedule\n request's reschedule date is still in future.", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/hooks/wasb_hook.py#L84-L100", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:WasbHook.load_file-f839e25fd4@held-out", "question": "Upload a file to Azure Blob Storage.\n\n :param file_path: Path to the file to load.\n :type file_path: str\n :param container_name: Name of the container.\n :type container_name: str\n :param blob_name: Name of the blob.\n :type blob_name: str\n :param kwargs: Optional keyword arguments that\n `BlockBlobService.create_blob_from_path()` takes.\n :type kwargs: object", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/hooks/wasb_hook.py#L120-L135", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:WasbHook.get_file-347d4a04ff@held-out", "question": "Download a file from Azure Blob Storage.\n\n :param file_path: Path to the file to download.\n :type file_path: str\n :param container_name: Name of the container.\n :type container_name: str\n :param blob_name: Name of the blob.\n :type blob_name: str\n :param kwargs: Optional keyword arguments that\n `BlockBlobService.create_blob_from_path()` takes.\n :type kwargs: object", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/api/common/experimental/mark_tasks.py#L30-L53", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:_create_dagruns-c01eb30b0e@held-out", "question": "Infers from the dates which dag runs need to be created and does so.\n :param dag: the dag to create dag runs for\n :param execution_dates: list of execution dates to evaluate\n :param state: the state to set the dag run to\n :param run_id_template:the template for run id to be with the execution date\n :return: newly created and existing dag runs for the execution dates supplied", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/hooks/azure_fileshare_hook.py#L47-L62", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:AzureFileShareHook.check_for_directory-0ed4e9718d@held-out", "question": "Check if a directory exists on Azure File Share.\n\n :param share_name: Name of the share.\n :type share_name: str\n :param directory_name: Name of the directory.\n :type directory_name: str\n :param kwargs: Optional keyword arguments that\n `FileService.exists()` takes.\n :type kwargs: object\n :return: True if the file exists, False otherwise.\n :rtype: bool", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/hooks/gcs_hook.py#L173-L206", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:GoogleCloudStorageHook.upload-0587e1a247@held-out", "question": "Uploads a local file to Google Cloud Storage.\n\n :param bucket_name: The bucket to upload to.\n :type bucket_name: str\n :param object_name: The object name to set when uploading the local file.\n :type object_name: str\n :param filename: The local file path to the file to be uploaded.\n :type filename: str\n :param mime_type: The MIME type to set when uploading the file.\n :type mime_type: str\n :param gzip: Option to compress file for upload\n :type gzip: bool", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/hooks/sagemaker_hook.py#L180-L201", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:SageMakerHook.check_s3_url-7596b977ce@held-out", "question": "Check if an S3 URL exists\n\n :param s3url: S3 url\n :type s3url: str\n :rtype: bool", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/hooks/sagemaker_hook.py#L368-L396", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:SageMakerHook.create_tuning_job-accaf0dcad@held-out", "question": "Create a tuning job\n\n :param config: the config for tuning\n :type config: dict\n :param wait_for_completion: if the program should keep running until job finishes\n :type wait_for_completion: bool\n :param check_interval: the time interval in seconds which the operator\n will check the status of any SageMaker job\n :type check_interval: int\n :param max_ingestion_time: the maximum ingestion time in seconds. Any\n SageMaker jobs that run longer than this will fail. Setting this to\n None implies no timeout for any SageMaker job.\n :type max_ingestion_time: int\n :return: A response to tuning job creation", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/hooks/sagemaker_hook.py#L450-L477", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:SageMakerHook.create_endpoint-62ebaf704f@held-out", "question": "Create an endpoint\n\n :param config: the config for endpoint\n :type config: dict\n :param wait_for_completion: if the program should keep running until job finishes\n :type wait_for_completion: bool\n :param check_interval: the time interval in seconds which the operator\n will check the status of any SageMaker job\n :type check_interval: int\n :param max_ingestion_time: the maximum ingestion time in seconds. Any\n SageMaker jobs that run longer than this will fail. Setting this to\n None implies no timeout for any SageMaker job.\n :type max_ingestion_time: int\n :return: A response to endpoint creation", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/hooks/hive_hooks.py#L374-L457", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:HiveCliHook.load_file-94d34a4d8c@held-out", "question": "Loads a local file into Hive\n\n Note that the table generated in Hive uses ``STORED AS textfile``\n which isn't the most efficient serialization format. If a\n large amount of data is loaded and/or if the tables gets\n queried considerably, you may want to use this operator only to\n stage the data into a temporary table before loading it into its\n final destination using a ``HiveOperator``.\n\n :param filepath: local filepath of the file to load\n :type filepath: str\n :param table: target Hive table, use dot notation to target a\n specific database\n :type table: str\n :param delimiter: field delimiter in the file\n :type delimiter: str\n :param field_dict: A dictionary of the fields name in the file\n as keys and their Hive types as values.\n Note that it must be OrderedDict so as to keep columns' order.\n :type field_dict: collections.OrderedDict\n :param create: whether to create the table if it doesn't exist\n :type create: bool\n :param overwrite: whether to overwrite the data in table or partition\n :type overwrite: bool\n :param partition: target partition as a dict of partition columns\n and values\n :type partition: dict\n :param recreate: whether to drop and recreate the table at every\n execution\n :type recreate: bool\n :param tblproperties: TBLPROPERTIES of the hive table being created\n :type tblproperties: dict", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/hooks/hive_hooks.py#L578-L591", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:HiveMetastoreHook.get_table-1a5bccd8ae@held-out", "question": "Get a metastore table object\n\n >>> hh = HiveMetastoreHook()\n >>> t = hh.get_table(db='airflow', table_name='static_babynames')\n >>> t.tableName\n 'static_babynames'\n >>> [col.name for col in t.sd.cols]\n ['state', 'year', 'name', 'gender', 'num']", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/hooks/hive_hooks.py#L608-L638", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:HiveMetastoreHook.get_partitions-74a442b69e@held-out", "question": "Returns a list of all partitions in a table. Works only\n for tables with less than 32767 (java short max val).\n For subpartitioned table, the number might easily exceed this.\n\n >>> hh = HiveMetastoreHook()\n >>> t = 'static_babynames_partitioned'\n >>> parts = hh.get_partitions(schema='airflow', table_name=t)\n >>> len(parts)\n 1\n >>> parts\n [{'ds': '2015-01-01'}]", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/hooks/hive_hooks.py#L758-L789", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:HiveServer2Hook.get_conn-253fb5a314@held-out", "question": "Returns a Hive connection object.", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/hooks/gcp_vision_hook.py#L226-L252", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:CloudVisionHook.create_product-953c7e5832@held-out", "question": "For the documentation see:\n :class:`~airflow.contrib.operators.gcp_vision_operator.CloudVisionProductCreateOperator`", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/hooks/dingding_hook.py#L115-L134", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:DingdingHook.send-78f8ac3ce5@held-out", "question": "Send Dingding message", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/utils/log/es_task_handler.py#L126-L152", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:ElasticsearchTaskHandler.es_read-fa3e46b7ac@held-out", "question": "Returns the logs matching log_id in Elasticsearch and next offset.\n Returns '' if no log is found or there was an error.\n :param log_id: the log_id of the log to read.\n :type log_id: str\n :param offset: the offset start to read log from.\n :type offset: str", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/hooks/bigquery_hook.py#L2071-L2076", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:_validate_value-0970f18aa1@held-out", "question": "function to check expected type and raise\n error if type is not correct", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/hooks/bigquery_hook.py#L95-L122", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:BigQueryHook.get_pandas_df-924fd54670@held-out", "question": "Returns a Pandas DataFrame for the results produced by a BigQuery\n query. The DbApiHook method must be overridden because Pandas\n doesn't support PEP 249 connections, except for SQLite. See:\n\n https://github.com/pydata/pandas/blob/master/pandas/io/sql.py#L447\n https://github.com/pydata/pandas/issues/6900\n\n :param sql: The BigQuery SQL to execute.\n :type sql: str\n :param parameters: The parameters to render the SQL query with (not\n used, leave to override superclass method)\n :type parameters: mapping or iterable\n :param dialect: Dialect of BigQuery SQL – legacy SQL or standard SQL\n defaults to use `self.use_legacy_sql` if not specified\n :type dialect: str in {'legacy', 'standard'}", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/hooks/bigquery_hook.py#L1387-L1419", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:BigQueryBaseCursor.run_table_delete-ece128ef39@held-out", "question": "Delete an existing table from the dataset;\n If the table does not exist, return an error unless ignore_if_missing\n is set to True.\n\n :param deletion_dataset_table: A dotted\n ``(<project>.|<project>:)<dataset>.<table>`` that indicates which table\n will be deleted.\n :type deletion_dataset_table: str\n :param ignore_if_missing: if True, then return success even if the\n requested table does not exist.\n :type ignore_if_missing: bool\n :return:", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/task/task_runner/base_task_runner.py#L157-L165", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:BaseTaskRunner.on_finish-c39eba32f8@held-out", "question": "A callback that should be called when this is done running.", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/_vendor/nvd3/NVD3Chart.py#L363-L371", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:NVD3Chart.buildhtml-d0936c8eb8@held-out", "question": "Build the HTML page\n Create the htmlheader with css / js\n Create html page\n Add Js code for nvd3", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/_vendor/nvd3/NVD3Chart.py#L419-L448", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:NVD3Chart.create_x_axis-bdb16d22e6@held-out", "question": "Create X-axis", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/hooks/sqlite_hook.py#L35-L41", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:SqliteHook.get_conn-6bb26365f2@held-out", "question": "Returns a sqlite connection object", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/hooks/opsgenie_alert_hook.py#L50-L59", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:OpsgenieAlertHook._get_api_key-4ed6eed83b@held-out", "question": "Get Opsgenie api_key for creating alert", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/hooks/aws_athena_hook.py#L43-L51", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:AWSAthenaHook.get_conn-60bedcec66@held-out", "question": "check if aws conn exists already or create one and return it\n\n :return: boto3 session", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/hooks/sftp_hook.py#L189-L200", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:SFTPHook.store_file-c6b65a09ae@held-out", "question": "Transfers a local file to the remote location.\n If local_full_path_or_buffer is a string path, the file will be read\n from that location\n :param remote_full_path: full path to the remote file\n :type remote_full_path: str\n :param local_full_path: full path to the local file\n :type local_full_path: str", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/hooks/aws_glue_catalog_hook.py#L95-L118", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:AwsGlueCatalogHook.check_for_partition-45cead3d10@held-out", "question": "Checks whether a partition exists\n\n :param database_name: Name of hive database (schema) @table belongs to\n :type database_name: str\n :param table_name: Name of hive table @partition belongs to\n :type table_name: str\n :expression: Expression that matches the partitions to check for\n (eg `a = 'b' AND c = 'd'`)\n :type expression: str\n :rtype: bool\n\n >>> hook = AwsGlueCatalogHook()\n >>> t = 'static_babynames_partitioned'\n >>> hook.check_for_partition('airflow', t, \"ds='2015-01-01'\")\n True", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/hooks/redshift_hook.py#L68-L83", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:RedshiftHook.describe_cluster_snapshots-e8ba8928b2@held-out", "question": "Gets a list of snapshots for a cluster\n\n :param cluster_identifier: unique identifier of a cluster\n :type cluster_identifier: str", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/operators/mongo_to_s3.py#L106-L113", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:MongoToS3Operator._stringify-a3d58a3cc0@held-out", "question": "Takes an iterable (pymongo Cursor or Array) containing dictionaries and\n returns a stringified version using python join", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/api/common/experimental/pool.py#L26-L35", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:get_pool-e5b8aa03f8@held-out", "question": "Get pool by a given name.", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/hooks/discord_webhook_hook.py#L102-L124", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:DiscordWebhookHook._build_discord_payload-09d2c136ad@held-out", "question": "Construct the Discord JSON payload. All relevant parameters are combined here\n to a valid Discord JSON payload.\n\n :return: Discord payload (str) to send", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/kubernetes/worker_configuration.py#L45-L131", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:WorkerConfiguration._get_init_containers-4bc7414d70@held-out", "question": "When using git to retrieve the DAGs, use the GitSync Init Container", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/jobs.py#L473-L504", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:DagFileProcessor.done-2565ba6ac6@held-out", "question": "Check if the process launched to process this file is done.\n\n :return: whether the process is finished running\n :rtype: bool", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/jobs.py#L1015-L1039", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:SchedulerJob.__get_concurrency_maps-3993884c16@held-out", "question": "Get the concurrency maps.\n\n :param states: List of states to query for\n :type states: list[airflow.utils.state.State]\n :return: A map from (dag_id, task_id) to # of task instances and\n a map from (dag_id, task_id) to # of task instances in the given state list\n :rtype: dict[tuple[str, str], int]", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/jobs.py#L1526-L1666", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:SchedulerJob._execute_helper-4e08c1fbe1@held-out", "question": "The actual scheduler loop. The main steps in the loop are:\n #. Harvest DAG parsing results through DagFileProcessorAgent\n #. Find and queue executable tasks\n #. Change task instance state in DB\n #. Queue tasks in executor\n #. Heartbeat executor\n #. Execute queued tasks in executor asynchronously\n #. Sync on the states of running tasks\n\n Following is a graphic representation of these steps.\n\n .. image:: ../docs/img/scheduler_loop.jpg\n\n :rtype: None", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/jobs.py#L1669-L1787", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:SchedulerJob.process_file-c18d30d3d1@held-out", "question": "Process a Python file containing Airflow DAGs.\n\n This includes:\n\n 1. Execute the file and look for DAG objects in the namespace.\n 2. Pickle the DAG and save it to the DB (if necessary).\n 3. For each DAG, see what tasks should run and create appropriate task\n instances in the DB.\n 4. Record any errors importing the file into ORM\n 5. Kill (in ORM) any task instances belonging to the DAGs that haven't\n issued a heartbeat in a while.\n\n Returns a list of SimpleDag objects that represent the DAGs found in\n the file\n\n :param file_path: the path to the Python file that should be executed\n :type file_path: unicode\n :param zombies: zombie task instances to kill.\n :type zombies: list[airflow.utils.dag_processing.SimpleTaskInstance]\n :param pickle_dags: whether serialize the DAGs found in the file and\n save them to the db\n :type pickle_dags: bool\n :return: a list of SimpleDags made from the Dags found in the file\n :rtype: list[airflow.utils.dag_processing.SimpleDagBag]", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/jobs.py#L2405-L2442", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:BackfillJob._execute_for_run_dates-eeff4e4f38@held-out", "question": "Computes the dag runs and their respective task instances for\n the given run dates and executes the task instances.\n Returns a list of execution dates of the dag runs that were executed.\n\n :param run_dates: Execution dates for dag runs\n :type run_dates: list\n :param ti_status: internal BackfillJob status structure to tis track progress\n :type ti_status: BackfillJob._DagRunTaskStatus\n :param executor: the executor to use, it must be previously started\n :type executor: BaseExecutor\n :param pickle_id: numeric id of the pickled dag, None if not pickled\n :type pickle_id: int\n :param start_date: backfill start date\n :type start_date: datetime.datetime\n :param session: the current session object\n :type session: sqlalchemy.orm.session.Session", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/hooks/gcp_spanner_hook.py#L109-L133", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:CloudSpannerHook.create_instance-782589aca9@held-out", "question": "Creates a new Cloud Spanner instance.\n\n :param instance_id: The ID of the Cloud Spanner instance.\n :type instance_id: str\n :param configuration_name: The name of the instance configuration defining how the\n instance will be created. Possible configuration values can be retrieved via\n https://cloud.google.com/spanner/docs/reference/rest/v1/projects.instanceConfigs/list\n :type configuration_name: str\n :param node_count: (Optional) The number of nodes allocated to the Cloud Spanner\n instance.\n :type node_count: int\n :param display_name: (Optional) The display name for the instance in the GCP\n Console. Must be between 4 and 30 characters. If this value is not set in\n the constructor, the name falls back to the instance ID.\n :type display_name: str\n :param project_id: Optional, the ID of the GCP project that owns the Cloud Spanner\n database. If set to None or missing, the default project_id from the GCP connection is used.\n :type project_id: str\n :return: None", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/hooks/gcp_spanner_hook.py#L184-L209", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:CloudSpannerHook.get_database-216e5a54f5@held-out", "question": "Retrieves a database in Cloud Spanner. If the database does not exist\n in the specified instance, it returns None.\n\n :param instance_id: The ID of the Cloud Spanner instance.\n :type instance_id: str\n :param database_id: The ID of the database in Cloud Spanner.\n :type database_id: str\n :param project_id: Optional, the ID of the GCP project that owns the Cloud Spanner\n database. If set to None or missing, the default project_id from the GCP connection is used.\n :type project_id: str\n :return: Database object or None if database does not exist\n :rtype: google.cloud.spanner_v1.database.Database or None", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/hooks/gcp_spanner_hook.py#L247-L288", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:CloudSpannerHook.update_database-ac8d735315@held-out", "question": "Updates DDL of a database in Cloud Spanner.\n\n :type project_id: str\n :param instance_id: The ID of the Cloud Spanner instance.\n :type instance_id: str\n :param database_id: The ID of the database in Cloud Spanner.\n :type database_id: str\n :param ddl_statements: The string list containing DDL for the new database.\n :type ddl_statements: list[str]\n :param project_id: Optional, the ID of the GCP project that owns the Cloud Spanner\n database. If set to None or missing, the default project_id from the GCP connection is used.\n :param operation_id: (Optional) The unique per database operation ID that can be\n specified to implement idempotency check.\n :type operation_id: str\n :return: None", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/hooks/gcp_spanner_hook.py#L328-L344", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:CloudSpannerHook.execute_dml-12c23117e5@held-out", "question": "Executes an arbitrary DML query (INSERT, UPDATE, DELETE).\n\n :param instance_id: The ID of the Cloud Spanner instance.\n :type instance_id: str\n :param database_id: The ID of the database in Cloud Spanner.\n :type database_id: str\n :param queries: The queries to execute.\n :type queries: str\n :param project_id: Optional, the ID of the GCP project that owns the Cloud Spanner\n database. If set to None or missing, the default project_id from the GCP connection is used.\n :type project_id: str", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/hooks/spark_submit_hook.py#L431-L446", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:SparkSubmitHook._process_spark_status_log-7f81018de4@held-out", "question": "parses the logs of the spark driver status query process\n\n :param itr: An iterator which iterates over the input of the subprocess", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/hooks/spark_submit_hook.py#L513-L537", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:SparkSubmitHook._build_spark_driver_kill_command-495c4d9727@held-out", "question": "Construct the spark-submit command to kill a driver.\n :return: full command to kill a driver", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/operators/mysql_to_gcs.py#L210-L253", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:MySqlToGoogleCloudStorageOperator._write_local_schema_file-8994d83d9a@held-out", "question": "Takes a cursor, and writes the BigQuery schema in .json format for the\n results to a local file system.\n\n :return: A dictionary where key is a filename to be used as an object\n name in GCS, and values are file handles to local files that\n contains the BigQuery schema fields in .json format.", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/operators/mysql_to_gcs.py#L269-L288", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:MySqlToGoogleCloudStorageOperator._convert_types-b5afa0bfc2@held-out", "question": "Takes a value from MySQLdb, and converts it to a value that's safe for\n JSON/Google cloud storage/BigQuery. Dates are converted to UTC seconds.\n Decimals are converted to floats. Binary type fields are encoded with base64,\n as imported BYTES data must be base64-encoded according to Bigquery SQL\n date type documentation: https://cloud.google.com/bigquery/data-types", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/operators/sqoop_operator.py#L166-L234", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:SqoopOperator.execute-4b25235a2c@held-out", "question": "Execute sqoop job", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/www/security.py#L455-L477", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:AirflowSecurityManager.sync_roles-2f39480fe4@held-out", "question": "1. Init the default role(Admin, Viewer, User, Op, public)\n with related permissions.\n 2. Init the custom role(dag-user) with related permissions.\n\n :return: None.", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/www/security.py#L479-L498", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:AirflowSecurityManager.sync_perm_for_dag-3e6f0d4764@held-out", "question": "Sync permissions for given dag id. The dag id surely exists in our dag bag\n as only / refresh button or cli.sync_perm will call this function\n\n :param dag_id: the ID of the DAG whose permissions should be updated\n :type dag_id: string\n :param access_control: a dict where each key is a rolename and\n each value is a set() of permission names (e.g.,\n {'can_dag_read'}\n :type access_control: dict\n :return:", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/utils/configuration.py#L27-L41", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:tmp_configuration_copy-fd0be22b99@held-out", "question": "Returns a path for a temporary file including a full copy of the configuration\n settings.\n :return: a path to a temporary file", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/hooks/hdfs_hook.py#L57-L98", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:HDFSHook.get_conn-08b3a50b91@held-out", "question": "Returns a snakebite HDFSClient object.", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/hooks/webhdfs_hook.py#L92-L104", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:WebHDFSHook.check_for_path-2a0aba4fa8@held-out", "question": "Check for the existence of a path in HDFS by querying FileStatus.\n\n :param hdfs_path: The path to check.\n :type hdfs_path: str\n :return: True if the path exists and False if not.\n :rtype: bool", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/hooks/redis_hook.py#L45-L66", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:RedisHook.get_conn-3a398d824c@held-out", "question": "Returns a Redis connection.", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/www/views.py#L2492-L2500", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:DagModelView.get_count_query-0b588e986c@held-out", "question": "Default filters for model", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/hooks/gcp_api_base_hook.py#L137-L146", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:GoogleCloudBaseHook._authorize-32d8768489@held-out", "question": "Returns an authorized HTTP object to be used to build a Google cloud\n service hook connection.", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/hooks/gcp_api_base_hook.py#L148-L159", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:GoogleCloudBaseHook._get_field-53b17c888c@held-out", "question": "Fetches a field from extras, and returns it. This is some Airflow\n magic. The google_cloud_platform hook type adds custom UI elements\n to the hook page, which allow admins to specify service_account,\n key_path, etc. They get formatted as shown below.", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/hooks/gcp_api_base_hook.py#L195-L220", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:apache-airflow:GoogleCloudBaseHook.fallback_to_default_project_id-05feec5848@held-out", "question": "Decorator that provides fallback for Google Cloud Platform project id. If\n the project is None it will be replaced with the project_id from the\n service account the Hook is authenticated with. Project id can be specified\n either via project_id kwarg or via first parameter in positional args.\n\n :param func: function to wrap\n :return: result of the function call", "scope": {"holder": "apache-airflow", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/pytorch/vision/blob/3afcf3cd49661c466c75ea536b0b2a7ff57f9a05/torchvision/models/vgg.py#L100-L111", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:pytorch-vision:vgg11_bn-6a0a9cfb3c@held-out", "question": "VGG 11-layer model (configuration \"A\") with batch normalization\n\n Args:\n pretrained (bool): If True, returns a model pre-trained on ImageNet", "scope": {"holder": "pytorch-vision", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/pytorch/vision/blob/3afcf3cd49661c466c75ea536b0b2a7ff57f9a05/torchvision/transforms/functional.py#L453-L465", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:pytorch-vision:vflip-6188f8734c@held-out", "question": "Vertically flip the given PIL Image.\n\n Args:\n img (PIL Image): Image to be flipped.\n\n Returns:\n PIL Image: Vertically flipped image.", "scope": {"holder": "pytorch-vision", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/pytorch/vision/blob/3afcf3cd49661c466c75ea536b0b2a7ff57f9a05/torchvision/transforms/functional.py#L680-L705", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:pytorch-vision:rotate-42e28b0705@held-out", "question": "Rotate the image by angle.\n\n\n Args:\n img (PIL Image): PIL Image to be rotated.\n angle (float or int): In degrees degrees counter clockwise order.\n resample (``PIL.Image.NEAREST`` or ``PIL.Image.BILINEAR`` or ``PIL.Image.BICUBIC``, optional):\n An optional resampling filter. See `filters`_ for more information.\n If omitted, or if the image has mode \"1\" or \"P\", it is set to ``PIL.Image.NEAREST``.\n expand (bool, optional): Optional expansion flag.\n If true, expands the output image to make it large enough to hold the entire rotated image.\n If false or omitted, make the output image the same size as the input image.\n Note that the expand flag assumes rotation around the center and no translation.\n center (2-tuple, optional): Optional center of rotation.\n Origin is the upper left corner.\n Default is the center of the image.\n\n .. _filters: https://pillow.readthedocs.io/en/latest/handbook/concepts.html#filters", "scope": {"holder": "pytorch-vision", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/pytorch/vision/blob/3afcf3cd49661c466c75ea536b0b2a7ff57f9a05/torchvision/datasets/utils.py#L54-L90", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:pytorch-vision:download_url-4226442330@held-out", "question": "Download a file from a url and place it in root.\n\n Args:\n url (str): URL to download file from\n root (str): Directory to place downloaded file in\n filename (str, optional): Name to save the file under. If None, use the basename of the URL\n md5 (str, optional): MD5 checksum of the download. If None, do not check", "scope": {"holder": "pytorch-vision", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/pytorch/vision/blob/3afcf3cd49661c466c75ea536b0b2a7ff57f9a05/torchvision/datasets/mnist.py#L132-L164", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:pytorch-vision:MNIST.download-626b50b9ac@held-out", "question": "Download the MNIST data if it doesn't exist in processed_folder already.", "scope": {"holder": "pytorch-vision", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/asciimoo/searx/blob/a84caa22cf947e973c10aa968d35fb2bdda6d048/searx/utils.py#L190-L195", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:asciimoo-searx:get_themes-6d9f51724e@held-out", "question": "Returns available themes list.", "scope": {"holder": "asciimoo-searx", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/edward2/generated_random_variables.py#L97-L145", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:as_random_variable-f2b47b29dc@held-out", "question": "Wrap an existing distribution as a traceable random variable.\n\n This enables the use of custom or user-provided distributions in\n Edward models. Unlike a bare `RandomVariable` object, this method\n wraps the constructor so it is included in the Edward trace and its\n values can be properly intercepted and overridden.\n\n Where possible, you should prefer the built-in constructors\n (`ed.Normal`, etc); these simultaneously construct a Distribution\n and a RandomVariable object so that the distribution parameters\n themselves may be intercepted and overridden. RVs constructed via\n `as_random_variable()` have a fixed distribution and may not support\n program transformations (e.g, conjugate marginalization) that rely\n on overriding distribution parameters.\n\n Args:\n distribution: tfd.Distribution governing the distribution of the random\n variable, such as sampling and log-probabilities.\n sample_shape: tf.TensorShape of samples to draw from the random variable.\n Default is `()` corresponding to a single sample.\n value: Fixed tf.Tensor to associate with random variable. Must have shape\n `sample_shape + distribution.batch_shape + distribution.event_shape`.\n Default is to sample from random variable according to `sample_shape`.\n\n Returns:\n rv: a `RandomVariable` wrapping the provided distribution.\n\n #### Example\n\n ```python\n from tensorflow_probability import distributions as tfd\n from tensorflow_probability import edward2 as ed\n\n def model():\n # equivalent to ed.Normal(0., 1., name='x')\n return ed.as_random_variable(tfd.Normal(0., 1., name='x'))\n\n log_joint = ed.make_log_joint_fn(model)\n output = log_joint(x=2.)\n ```", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/internal/backend/numpy/math.py#L191-L202", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:_reduce_logsumexp-ea71073d0b@held-out", "question": "Computes `log(sum(exp(input_tensor))) along the specified axis.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/internal/assert_util.py#L44-L73", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:assert_finite-dd2c9a7d21@held-out", "question": "Assert all elements of `x` are finite.\n\n Args:\n x: Numeric `Tensor`.\n data: The tensors to print out if the condition is False. Defaults to\n error message and first few entries of `x`.\n summarize: Print this many entries of each tensor.\n message: A string to prefix to the default message.\n name: A name for this operation (optional).\n Defaults to \"assert_finite\".\n\n Returns:\n Op raising `InvalidArgumentError` unless `x` has specified rank or lower.\n If static checks determine `x` has correct rank, a `no_op` is returned.\n\n Raises:\n ValueError: If static checks determine `x` has wrong rank.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/layers/distribution_layer.py#L754-L768", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:_eval_all_one_hot-87c0c7aa99@held-out", "question": "OneHotCategorical helper computing probs, cdf, etc over its support.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/layers/distribution_layer.py#L1912-L1930", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:_get_convert_to_tensor_fn-2acfa41495@held-out", "question": "Return a convert-to-tensor func, given a name, config, callable, etc.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/layers/distribution_layer.py#L834-L855", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:IndependentLogistic.new-f71ee311c6@held-out", "question": "Create the distribution instance from a `params` vector.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/layers/distribution_layer.py#L1084-L1103", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:IndependentPoisson.new-17e29ea271@held-out", "question": "Create the distribution instance from a `params` vector.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/experimental/fun_mcmc/fun_mcmc_lib.py#L140-L157", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:call_and_grads-06545c9d7e@held-out", "question": "Calls `fn` and returns the gradients with respect to `fn`'s first output.\n\n Args:\n fn: A `TransitionOperator`.\n args: Arguments to `fn`\n\n Returns:\n ret: First output of `fn`.\n extra: Second output of `fn`.\n grads: Gradients of `ret` with respect to `args`.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/distributions/dirichlet.py#L317-L327", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:Dirichlet._maybe_assert_valid_sample-bc289e44ad@held-out", "question": "Checks the validity of a sample.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/stats/sample_stats.py#L552-L599", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:stddev-7e301bb431@held-out", "question": "Estimate standard deviation using samples.\n\n Given `N` samples of scalar valued random variable `X`, standard deviation may\n be estimated as\n\n ```none\n Stddev[X] := Sqrt[Var[X]],\n Var[X] := N^{-1} sum_{n=1}^N (X_n - Xbar) Conj{(X_n - Xbar)},\n Xbar := N^{-1} sum_{n=1}^N X_n\n ```\n\n ```python\n x = tf.random_normal(shape=(100, 2, 3))\n\n # stddev[i, j] is the sample standard deviation of the (i, j) batch member.\n stddev = tfp.stats.stddev(x, sample_axis=0)\n ```\n\n Scaling a unit normal by a standard deviation produces normal samples\n with that standard deviation.\n\n ```python\n observed_data = read_data_samples(...)\n stddev = tfp.stats.stddev(observed_data)\n\n # Make fake_data with the same standard deviation as observed_data.\n fake_data = stddev * tf.random_normal(shape=(100,))\n ```\n\n Notice we divide by `N` (the numpy default), which does not create `NaN`\n when `N = 1`, but is slightly biased.\n\n Args:\n x: A numeric `Tensor` holding samples.\n sample_axis: Scalar or vector `Tensor` designating axis holding samples, or\n `None` (meaning all axis hold samples).\n Default value: `0` (leftmost dimension).\n keepdims: Boolean. Whether to keep the sample axis as singletons.\n name: Python `str` name prefixed to Ops created by this function.\n Default value: `None` (i.e., `'stddev'`).\n\n Returns:\n stddev: A `Tensor` of same `dtype` as the `x`, and rank equal to\n `rank(x) - len(sample_axis)`", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/optimizer/linesearch/hager_zhang.py#L666-L680", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:_print-07dc28d1d9@held-out", "question": "Wrapper for tf.Print which supports lists and namedtuples for printing.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/distributions/vector_diffeomixture.py#L46-L105", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:quadrature_scheme_softmaxnormal_gauss_hermite-ce3523c4d1@held-out", "question": "Use Gauss-Hermite quadrature to form quadrature on `K - 1` simplex.\n\n A `SoftmaxNormal` random variable `Y` may be generated via\n\n ```\n Y = SoftmaxCentered(X),\n X = Normal(normal_loc, normal_scale)\n ```\n\n Note: for a given `quadrature_size`, this method is generally less accurate\n than `quadrature_scheme_softmaxnormal_quantiles`.\n\n Args:\n normal_loc: `float`-like `Tensor` with shape `[b1, ..., bB, K-1]`, B>=0.\n The location parameter of the Normal used to construct the SoftmaxNormal.\n normal_scale: `float`-like `Tensor`. Broadcastable with `normal_loc`.\n The scale parameter of the Normal used to construct the SoftmaxNormal.\n quadrature_size: Python `int` scalar representing the number of quadrature\n points.\n validate_args: Python `bool`, default `False`. When `True` distribution\n parameters are checked for validity despite possibly degrading runtime\n performance. When `False` invalid inputs may silently render incorrect\n outputs.\n name: Python `str` name prefixed to Ops created by this class.\n\n Returns:\n grid: Shape `[b1, ..., bB, K, quadrature_size]` `Tensor` representing the\n convex combination of affine parameters for `K` components.\n `grid[..., :, n]` is the `n`-th grid point, living in the `K - 1` simplex.\n probs: Shape `[b1, ..., bB, K, quadrature_size]` `Tensor` representing the\n associated with each grid point.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/distributions/vector_diffeomixture.py#L882-L896", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:interpolate_scale-d07b4831b2@held-out", "question": "Helper which interpolates between two scales.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/distributions/vector_diffeomixture.py#L899-L933", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:linop_scale-c632adc8ca@held-out", "question": "Creates weighted `LinOp` from existing `LinOp`.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/distributions/vector_diffeomixture.py#L958-L972", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:softmax-97c92bdc95@held-out", "question": "Equivalent to tf.nn.softmax but works around b/70297725.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/distributions/hidden_markov_model.py#L623-L734", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:HiddenMarkovModel.posterior_marginals-3f864149b2@held-out", "question": "Compute marginal posterior distribution for each state.\n\n This function computes, for each time step, the marginal\n conditional probability that the hidden Markov model was in\n each possible state given the observations that were made\n at each time step.\n So if the hidden states are `z[0],...,z[num_steps - 1]` and\n the observations are `x[0], ..., x[num_steps - 1]`, then\n this function computes `P(z[i] | x[0], ..., x[num_steps - 1])`\n for all `i` from `0` to `num_steps - 1`.\n\n This operation is sometimes called smoothing. It uses a form\n of the forward-backward algorithm.\n\n Note: the behavior of this function is undefined if the\n `observations` argument represents impossible observations\n from the model.\n\n Args:\n observations: A tensor representing a batch of observations\n made on the hidden Markov model. The rightmost dimension of this tensor\n gives the steps in a sequence of observations from a single sample from\n the hidden Markov model. The size of this dimension should match the\n `num_steps` parameter of the hidden Markov model object. The other\n dimensions are the dimensions of the batch and these are broadcast with\n the hidden Markov model's parameters.\n name: Python `str` name prefixed to Ops created by this class.\n Default value: \"HiddenMarkovModel\".\n\n Returns:\n posterior_marginal: A `Categorical` distribution object representing the\n marginal probability of the hidden Markov model being in each state at\n each step. The rightmost dimension of the `Categorical` distributions\n batch will equal the `num_steps` parameter providing one marginal\n distribution for each step. The other dimensions are the dimensions\n corresponding to the batch of observations.\n\n Raises:\n ValueError: if rightmost dimension of `observations` does not\n have size `num_steps`.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/distributions/hidden_markov_model.py#L736-L905", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:HiddenMarkovModel.posterior_mode-4fbe80fbf9@held-out", "question": "Compute maximum likelihood sequence of hidden states.\n\n When this function is provided with a sequence of observations\n `x[0], ..., x[num_steps - 1]`, it returns the sequence of hidden\n states `z[0], ..., z[num_steps - 1]`, drawn from the underlying\n Markov chain, that is most likely to yield those observations.\n\n It uses the [Viterbi algorithm](\n https://en.wikipedia.org/wiki/Viterbi_algorithm).\n\n Note: the behavior of this function is undefined if the\n `observations` argument represents impossible observations\n from the model.\n\n Note: if there isn't a unique most likely sequence then one\n of the equally most likely sequences is chosen.\n\n Args:\n observations: A tensor representing a batch of observations made on the\n hidden Markov model. The rightmost dimensions of this tensor correspond\n to the dimensions of the observation distributions of the underlying\n Markov chain. The next dimension from the right indexes the steps in a\n sequence of observations from a single sample from the hidden Markov\n model. The size of this dimension should match the `num_steps`\n parameter of the hidden Markov model object. The other dimensions are\n the dimensions of the batch and these are broadcast with the hidden\n Markov model's parameters.\n name: Python `str` name prefixed to Ops created by this class.\n Default value: \"HiddenMarkovModel\".\n\n Returns:\n posterior_mode: A `Tensor` representing the most likely sequence of hidden\n states. The rightmost dimension of this tensor will equal the\n `num_steps` parameter providing one hidden state for each step. The\n other dimensions are those of the batch.\n\n Raises:\n ValueError: if the `observations` tensor does not consist of\n sequences of `num_steps` observations.\n\n #### Examples\n\n ```python\n tfd = tfp.distributions\n\n # A simple weather model.\n\n # Represent a cold day with 0 and a hot day with 1.\n # Suppose the first day of a sequence has a 0.8 chance of being cold.\n\n initial_distribution = tfd.Categorical(probs=[0.8, 0.2])\n\n # Suppose a cold day has a 30% chance of being followed by a hot day\n # and a hot day has a 20% chance of being followed by a cold day.\n\n transition_distribution = tfd.Categorical(probs=[[0.7, 0.3],\n [0.2, 0.8]])\n\n # Suppose additionally that on each day the temperature is\n # normally distributed with mean and standard deviation 0 and 5 on\n # a cold day and mean and standard deviation 15 and 10 on a hot day.\n\n observation_distribution = tfd.Normal(loc=[0., 15.], scale=[5., 10.])\n\n # This gives the hidden Markov model:\n\n model = tfd.HiddenMarkovModel(\n initial_distribution=initial_distribution,\n transition_distribution=transition_distribution,\n observation_distribution=observation_distribution,\n num_steps=7)\n\n # Suppose we observe gradually rising temperatures over a week:\n temps = [-2., 0., 2., 4., 6., 8., 10.]\n\n # We can now compute the most probable sequence of hidden states:\n\n model.posterior_mode(temps)\n\n # The result is [0 0 0 0 0 1 1] telling us that the transition\n # from \"cold\" to \"hot\" most likely happened between the\n # 5th and 6th days.\n ```", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/mcmc/slice_sampler_kernel.py#L259-L336", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:SliceSampler.one_step-2230537836@held-out", "question": "Runs one iteration of Slice Sampler.\n\n Args:\n current_state: `Tensor` or Python `list` of `Tensor`s representing the\n current state(s) of the Markov chain(s). The first `r` dimensions\n index independent chains,\n `r = tf.rank(target_log_prob_fn(*current_state))`.\n previous_kernel_results: `collections.namedtuple` containing `Tensor`s\n representing values from previous calls to this function (or from the\n `bootstrap_results` function.)\n\n Returns:\n next_state: Tensor or Python list of `Tensor`s representing the state(s)\n of the Markov chain(s) after taking exactly one step. Has same type and\n shape as `current_state`.\n kernel_results: `collections.namedtuple` of internal calculations used to\n advance the chain.\n\n Raises:\n ValueError: if there isn't one `step_size` or a list with same length as\n `current_state`.\n TypeError: if `not target_log_prob.dtype.is_floating`.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/sts/internal/missing_values_util.py#L137-L162", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:initial_value_of_masked_time_series-9e624c0f7e@held-out", "question": "Get the first unmasked entry of each time series in the batch.\n\n Args:\n time_series_tensor: float `Tensor` of shape [..., num_timesteps].\n broadcast_mask: bool `Tensor` of same shape as `time_series`.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/sts/internal/util.py#L332-L375", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:mix_over_posterior_draws-769dd877d3@held-out", "question": "Construct a predictive normal distribution that mixes over posterior draws.\n\n Args:\n means: float `Tensor` of shape\n `[num_posterior_draws, ..., num_timesteps]`.\n variances: float `Tensor` of shape\n `[num_posterior_draws, ..., num_timesteps]`.\n\n Returns:\n mixture_dist: `tfd.MixtureSameFamily(tfd.Independent(tfd.Normal))` instance\n representing a uniform mixture over the posterior samples, with\n `batch_shape = ...` and `event_shape = [num_timesteps]`.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/distributions/joint_distribution_sequential.py#L38-L46", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:_make_summary_statistic-ac61e4b9ad@held-out", "question": "Factory for making summary statistics, eg, mean, mode, stddev.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/distributions/half_cauchy.py#L228-L259", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:HalfCauchy._extend_support_with_default_value-a2e3d5d94d@held-out", "question": "Returns `f(x)` if x is in the support, and `default_value` otherwise.\n\n Given `f` which is defined on the support of this distribution\n (`x >= loc`), extend the function definition to the real line\n by defining `f(x) = default_value` for `x < loc`.\n\n Args:\n x: Floating-point `Tensor` to evaluate `f` at.\n f: Callable that takes in a `Tensor` and returns a `Tensor`. This\n represents the function whose domain of definition we want to extend.\n default_value: Python or numpy literal representing the value to use for\n extending the domain.\n Returns:\n `Tensor` representing an extension of `f(x)`.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/examples/disentangled_vae.py#L1001-L1032", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:visualize_qualitative_analysis-7887a97d61@held-out", "question": "Visualizes a qualitative analysis of a given model.\n\n Args:\n inputs: A tensor of the original inputs, of shape [batch, timesteps,\n h, w, c].\n model: A DisentangledSequentialVAE model.\n samples: Number of samples to draw from the latent distributions.\n batch_size: Number of sequences to generate.\n length: Number of timesteps to generate for each sequence.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/examples/disentangled_vae.py#L1055-L1078", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:summarize_mean_in_nats_and_bits-0c5ec372c8@held-out", "question": "Summarize the mean of a tensor in nats and bits per unit.\n\n Args:\n inputs: A tensor of values measured in nats.\n units: The units of the tensor with which to compute the mean bits\n per unit.\n name: The name of the tensor.\n nats_name_scope: The name scope of the nats summary.\n bits_name_scope: The name scope of the bits summary.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/examples/disentangled_vae.py#L421-L441", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:Compressor.call-2eff239ebc@held-out", "question": "Runs the model to generate an intermediate representation of x_t.\n\n Args:\n inputs: A batch of image sequences `x_{1:T}` of shape\n `[sample_shape, batch_size, timesteps, height, width,\n channels]`.\n\n Returns:\n A batch of intermediate representations of shape [sample_shape,\n batch_size, timesteps, hidden_size].", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/examples/disentangled_vae.py#L614-L663", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:EncoderDynamicFull.call-65f43e086d@held-out", "question": "Runs the model to generate a distribution `q(z_{1:T} | x_{1:T}, f)`.\n\n This generates a list of batched MultivariateNormalDiag\n distributions using the output of the recurrent model at each\n timestep to parameterize each distribution.\n\n Args:\n inputs: A tuple of a batch of intermediate representations of\n image frames across all timesteps of shape [..., batch_size,\n timesteps, dimensions], and a sample of the static latent\n variable `f` of shape [..., batch_size, latent_size].\n\n Returns:\n A batch of MultivariateNormalDiag distributions with event shape\n [latent_size], batch shape [broadcasted_shape, batch_size,\n timesteps], and sample shape [sample_shape, broadcasted_shape,\n batch_size, timesteps, latent_size], where `broadcasted_shape` is\n the broadcasted sampled shape between the inputs and static\n sample.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/examples/disentangled_vae.py#L887-L927", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:DisentangledSequentialVAE.sample_dynamic_prior-7411f1053f@held-out", "question": "Sample the dynamic latent prior.\n\n Args:\n samples: Number of samples to draw from the latent distribution.\n batch_size: Number of sequences to sample.\n length: Number of timesteps to sample for each sequence.\n fixed: Boolean for whether or not to share the same random\n sample across all sequences.\n\n Returns:\n A tuple of a sample tensor of shape [samples, batch_size, length\n latent_size], and a MultivariateNormalDiag distribution from which\n the tensor was sampled, with event shape [latent_size], and batch\n shape [samples, 1, length] if fixed or [samples, batch_size,\n length] otherwise.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/sts/structural_time_series.py#L161-L209", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:StructuralTimeSeries.prior_sample-ddaa5570ce@held-out", "question": "Sample from the joint prior over model parameters and trajectories.\n\n Args:\n num_timesteps: Scalar `int` `Tensor` number of timesteps to model.\n initial_step: Optional scalar `int` `Tensor` specifying the starting\n timestep.\n Default value: 0.\n params_sample_shape: Number of possible worlds to sample iid from the\n parameter prior, or more generally, `Tensor` `int` shape to fill with\n iid samples.\n Default value: [] (i.e., draw a single sample and don't expand the\n shape).\n trajectories_sample_shape: For each sampled set of parameters, number\n of trajectories to sample, or more generally, `Tensor` `int` shape to\n fill with iid samples.\n Default value: [] (i.e., draw a single sample and don't expand the\n shape).\n seed: Python `int` random seed.\n\n Returns:\n trajectories: `float` `Tensor` of shape\n `trajectories_sample_shape + params_sample_shape + [num_timesteps, 1]`\n containing all sampled trajectories.\n param_samples: list of sampled parameter value `Tensor`s, in order\n corresponding to `self.parameters`, each of shape\n `params_sample_shape + prior.batch_shape + prior.event_shape`.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/bijectors/fill_triangular.py#L135-L153", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:vector_size_to_square_matrix_size-944d36cd4b@held-out", "question": "Convert a vector size to a matrix size.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/distributions/gaussian_process.py#L286-L307", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:GaussianProcess._is_univariate_marginal-d9c2ced4f0@held-out", "question": "True if the given index_points would yield a univariate marginal.\n\n Args:\n index_points: the set of index set locations at which to compute the\n marginal Gaussian distribution. If this set is of size 1, the marginal is\n univariate.\n\n Returns:\n is_univariate: Boolean indicating whether the marginal is univariate or\n multivariate. In the case of dynamic shape in the number of index points,\n defaults to \"multivariate\" since that's the best we can do.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/distributions/quantized_distribution.py#L372-L394", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:QuantizedDistribution._log_prob_with_logsf_and_logcdf-5cf6b1aaa0@held-out", "question": "Compute log_prob(y) using log survival_function and cdf together.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/distributions/mixture_same_family.py#L469-L533", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:MixtureSameFamily._distributional_transform-4111d821af@held-out", "question": "Performs distributional transform of the mixture samples.\n\n Distributional transform removes the parameters from samples of a\n multivariate distribution by applying conditional CDFs:\n (F(x_1), F(x_2 | x1_), ..., F(x_d | x_1, ..., x_d-1))\n (the indexing is over the \"flattened\" event dimensions).\n The result is a sample of product of Uniform[0, 1] distributions.\n\n We assume that the components are factorized, so the conditional CDFs become\n F(x_i | x_1, ..., x_i-1) = sum_k w_i^k F_k (x_i),\n where w_i^k is the posterior mixture weight: for i > 0\n w_i^k = w_k prob_k(x_1, ..., x_i-1) / sum_k' w_k' prob_k'(x_1, ..., x_i-1)\n and w_0^k = w_k is the mixture probability of the k-th component.\n\n Arguments:\n x: Sample of mixture distribution\n\n Returns:\n Result of the distributional transform", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/sts/decomposition.py#L40-L106", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:_decompose_from_posterior_marginals-ddef170dbb@held-out", "question": "Utility method to decompose a joint posterior into components.\n\n Args:\n model: `tfp.sts.Sum` instance defining an additive STS model.\n posterior_means: float `Tensor` of shape `concat(\n [[num_posterior_draws], batch_shape, num_timesteps, latent_size])`\n representing the posterior mean over latents in an\n `AdditiveStateSpaceModel`.\n posterior_covs: float `Tensor` of shape `concat(\n [[num_posterior_draws], batch_shape, num_timesteps,\n latent_size, latent_size])`\n representing the posterior marginal covariances over latents in an\n `AdditiveStateSpaceModel`.\n parameter_samples: Python `list` of `Tensors` representing posterior\n samples of model parameters, with shapes `[concat([\n [num_posterior_draws], param.prior.batch_shape,\n param.prior.event_shape]) for param in model.parameters]`. This may\n optionally also be a map (Python `dict`) of parameter names to\n `Tensor` values.\n\n Returns:\n component_dists: A `collections.OrderedDict` instance mapping\n component StructuralTimeSeries instances (elements of `model.components`)\n to `tfd.Distribution` instances representing the posterior marginal\n distributions on the process modeled by each component. Each distribution\n has batch shape matching that of `posterior_means`/`posterior_covs`, and\n event shape of `[num_timesteps]`.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/sts/decomposition.py#L109-L219", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:decompose_by_component-69ccd58fb6@held-out", "question": "Decompose an observed time series into contributions from each component.\n\n This method decomposes a time series according to the posterior represention\n of a structural time series model. In particular, it:\n - Computes the posterior marginal mean and covariances over the additive\n model's latent space.\n - Decomposes the latent posterior into the marginal blocks for each\n model component.\n - Maps the per-component latent posteriors back through each component's\n observation model, to generate the time series modeled by that component.\n\n Args:\n model: An instance of `tfp.sts.Sum` representing a structural time series\n model.\n observed_time_series: `float` `Tensor` of shape\n `batch_shape + [num_timesteps, 1]` (omitting the trailing unit dimension\n is also supported when `num_timesteps > 1`), specifying an observed time\n series. May optionally be an instance of `tfp.sts.MaskedTimeSeries`, which\n includes a mask `Tensor` to specify timesteps with missing observations.\n parameter_samples: Python `list` of `Tensors` representing posterior\n samples of model parameters, with shapes `[concat([\n [num_posterior_draws], param.prior.batch_shape,\n param.prior.event_shape]) for param in model.parameters]`. This may\n optionally also be a map (Python `dict`) of parameter names to\n `Tensor` values.\n Returns:\n component_dists: A `collections.OrderedDict` instance mapping\n component StructuralTimeSeries instances (elements of `model.components`)\n to `tfd.Distribution` instances representing the posterior marginal\n distributions on the process modeled by each component. Each distribution\n has batch shape matching that of `posterior_means`/`posterior_covs`, and\n event shape of `[num_timesteps]`.\n\n #### Examples\n\n Suppose we've built a model and fit it to data:\n\n ```python\n day_of_week = tfp.sts.Seasonal(\n num_seasons=7,\n observed_time_series=observed_time_series,\n name='day_of_week')\n local_linear_trend = tfp.sts.LocalLinearTrend(\n observed_time_series=observed_time_series,\n name='local_linear_trend')\n model = tfp.sts.Sum(components=[day_of_week, local_linear_trend],\n observed_time_series=observed_time_series)\n\n num_steps_forecast = 50\n samples, kernel_results = tfp.sts.fit_with_hmc(model, observed_time_series)\n ```\n\n To extract the contributions of individual components, pass the time series\n and sampled parameters into `decompose_by_component`:\n\n ```python\n component_dists = decompose_by_component(\n model,\n observed_time_series=observed_time_series,\n parameter_samples=samples)\n\n # Component mean and stddev have shape `[len(observed_time_series)]`.\n day_of_week_effect_mean = component_dists[day_of_week].mean()\n day_of_week_effect_stddev = component_dists[day_of_week].stddev()\n ```\n\n Using the component distributions, we can visualize the uncertainty for\n each component:\n\n ```\n from matplotlib import pylab as plt\n num_components = len(component_dists)\n xs = np.arange(len(observed_time_series))\n fig = plt.figure(figsize=(12, 3 * num_components))\n for i, (component, component_dist) in enumerate(component_dists.items()):\n\n # If in graph mode, replace `.numpy()` with `.eval()` or `sess.run()`.\n component_mean = component_dist.mean().numpy()\n component_stddev = component_dist.stddev().numpy()\n\n ax = fig.add_subplot(num_components, 1, 1 + i)\n ax.plot(xs, component_mean, lw=2)\n ax.fill_between(xs,\n component_mean - 2 * component_stddev,\n component_mean + 2 * component_stddev,\n alpha=0.5)\n ax.set_title(component.name)\n ```", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/edward2/random_variable.py#L139-L152", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:RandomVariable.sample_shape_tensor-54216732fa@held-out", "question": "Sample shape of random variable as a 1-D `Tensor`.\n\n Args:\n name: name to give to the op\n\n Returns:\n sample_shape: `Tensor`.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/edward2/random_variable.py#L160-L170", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:RandomVariable.value-0316c00e30@held-out", "question": "Get tensor that the random variable corresponds to.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/edward2/random_variable.py#L236-L268", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:RandomVariable.eval-9fe50be321@held-out", "question": "In a session, computes and returns the value of this random variable.\n\n This is not a graph construction method, it does not add ops to the graph.\n\n This convenience method requires a session where the graph\n containing this variable has been launched. If no session is\n passed, the default session is used.\n\n Args:\n session: tf.BaseSession.\n The `tf.Session` to use to evaluate this random variable. If\n none, the default session is used.\n feed_dict: dict.\n A dictionary that maps `tf.Tensor` objects to feed values. See\n `tf.Session.run()` for a description of the valid feed values.\n\n Returns:\n Value of the random variable.\n\n #### Examples\n\n ```python\n x = Normal(0.0, 1.0)\n with tf.Session() as sess:\n # Usage passing the session explicitly.\n print(x.eval(sess))\n # Usage with the default session. The 'with' block\n # above makes 'sess' the default session.\n print(x.eval())\n ```", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/edward2/random_variable.py#L270-L275", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:RandomVariable.numpy-2fc5a97ac4@held-out", "question": "Value as NumPy array, only available for TF Eager.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/distributions/normal_conjugate_posteriors.py#L25-L81", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:normal_conjugates_known_scale_posterior-51b7e2e379@held-out", "question": "Posterior Normal distribution with conjugate prior on the mean.\n\n This model assumes that `n` observations (with sum `s`) come from a\n Normal with unknown mean `loc` (described by the Normal `prior`)\n and known variance `scale**2`. The \"known scale posterior\" is\n the distribution of the unknown `loc`.\n\n Accepts a prior Normal distribution object, having parameters\n `loc0` and `scale0`, as well as known `scale` values of the predictive\n distribution(s) (also assumed Normal),\n and statistical estimates `s` (the sum(s) of the observations) and\n `n` (the number(s) of observations).\n\n Returns a posterior (also Normal) distribution object, with parameters\n `(loc', scale'**2)`, where:\n\n ```\n mu ~ N(mu', sigma'**2)\n sigma'**2 = 1/(1/sigma0**2 + n/sigma**2),\n mu' = (mu0/sigma0**2 + s/sigma**2) * sigma'**2.\n ```\n\n Distribution parameters from `prior`, as well as `scale`, `s`, and `n`.\n will broadcast in the case of multidimensional sets of parameters.\n\n Args:\n prior: `Normal` object of type `dtype`:\n the prior distribution having parameters `(loc0, scale0)`.\n scale: tensor of type `dtype`, taking values `scale > 0`.\n The known stddev parameter(s).\n s: Tensor of type `dtype`. The sum(s) of observations.\n n: Tensor of type `int`. The number(s) of observations.\n\n Returns:\n A new Normal posterior distribution object for the unknown observation\n mean `loc`.\n\n Raises:\n TypeError: if dtype of `s` does not match `dtype`, or `prior` is not a\n Normal object.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/distributions/lkj.py#L371-L410", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:LKJ._log_unnorm_prob-80bd109631@held-out", "question": "Returns the unnormalized log density of an LKJ distribution.\n\n Args:\n x: `float` or `double` `Tensor` of correlation matrices. The shape of `x`\n must be `B + [D, D]`, where `B` broadcasts with the shape of\n `concentration`.\n name: Python `str` name prefixed to Ops created by this function.\n\n Returns:\n log_p: A Tensor of the unnormalized log density of each matrix element of\n `x`, with respect to an LKJ distribution with parameter the\n corresponding element of `concentration`.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/distributions/lkj.py#L412-L432", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:LKJ._log_normalization-6305dafd87@held-out", "question": "Returns the log normalization of an LKJ distribution.\n\n Args:\n name: Python `str` name prefixed to Ops created by this function.\n\n Returns:\n log_z: A Tensor of the same shape and dtype as `concentration`, containing\n the corresponding log normalizers.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/distributions/sample.py#L34-L52", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:_make_summary_statistic-bcc26e7a84@held-out", "question": "Factory for implementing summary statistics, eg, mean, stddev, mode.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/distributions/sample.py#L241-L278", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:_kl_sample-7f578ed5dc@held-out", "question": "Batched KL divergence `KL(a || b)` for Sample distributions.\n\n We can leverage the fact that:\n\n ```\n KL(Sample(a) || Sample(b)) = sum(KL(a || b))\n ```\n\n where the sum is over the `sample_shape` dims.\n\n Args:\n a: Instance of `Sample` distribution.\n b: Instance of `Sample` distribution.\n name: (optional) name to use for created ops.\n Default value: `\"kl_sample\"`'.\n\n Returns:\n kldiv: Batchwise `KL(a || b)`.\n\n Raises:\n ValueError: If the `sample_shape` of `a` and `b` don't match.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/distributions/triangular.py#L33-L38", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:_broadcast_to-65482a134a@held-out", "question": "Helper to broadcast a tensor using a list of target tensors.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/mcmc/diagnostic.py#L203-L332", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:potential_scale_reduction-98f4dc8945@held-out", "question": "Gelman and Rubin (1992)'s potential scale reduction for chain convergence.\n\n Given `N > 1` states from each of `C > 1` independent chains, the potential\n scale reduction factor, commonly referred to as R-hat, measures convergence of\n the chains (to the same target) by testing for equality of means.\n Specifically, R-hat measures the degree to which variance (of the means)\n between chains exceeds what one would expect if the chains were identically\n distributed. See [Gelman and Rubin (1992)][1]; [Brooks and Gelman (1998)][2].\n\n Some guidelines:\n\n * The initial state of the chains should be drawn from a distribution\n overdispersed with respect to the target.\n * If all chains converge to the target, then as `N --> infinity`, R-hat --> 1.\n Before that, R-hat > 1 (except in pathological cases, e.g. if the chain\n paths were identical).\n * The above holds for any number of chains `C > 1`. Increasing `C` does\n improves effectiveness of the diagnostic.\n * Sometimes, R-hat < 1.2 is used to indicate approximate convergence, but of\n course this is problem dependent. See [Brooks and Gelman (1998)][2].\n * R-hat only measures non-convergence of the mean. If higher moments, or\n other statistics are desired, a different diagnostic should be used. See\n [Brooks and Gelman (1998)][2].\n\n Args:\n chains_states: `Tensor` or Python `list` of `Tensor`s representing the\n state(s) of a Markov Chain at each result step. The `ith` state is\n assumed to have shape `[Ni, Ci1, Ci2,...,CiD] + A`.\n Dimension `0` indexes the `Ni > 1` result steps of the Markov Chain.\n Dimensions `1` through `D` index the `Ci1 x ... x CiD` independent\n chains to be tested for convergence to the same target.\n The remaining dimensions, `A`, can have any shape (even empty).\n independent_chain_ndims: Integer type `Tensor` with value `>= 1` giving the\n number of giving the number of dimensions, from `dim = 1` to `dim = D`,\n holding independent chain results to be tested for convergence.\n name: `String` name to prepend to created tf. Default:\n `potential_scale_reduction`.\n\n Returns:\n `Tensor` or Python `list` of `Tensor`s representing the R-hat statistic for\n the state(s). Same `dtype` as `state`, and shape equal to\n `state.shape[1 + independent_chain_ndims:]`.\n\n Raises:\n ValueError: If `independent_chain_ndims < 1`.\n\n #### Examples\n\n Diagnosing convergence by monitoring 10 chains that each attempt to\n sample from a 2-variate normal.\n\n ```python\n import tensorflow as tf\n import tensorflow_probability as tfp\n tfd = tfp.distributions\n\n target = tfd.MultivariateNormalDiag(scale_diag=[1., 2.])\n\n # Get 10 (2x) overdispersed initial states.\n initial_state = target.sample(10) * 2.\n ==> (10, 2)\n\n # Get 1000 samples from the 10 independent chains.\n chains_states, _ = tfp.mcmc.sample_chain(\n num_burnin_steps=200,\n num_results=1000,\n current_state=initial_state,\n kernel=tfp.mcmc.HamiltonianMonteCarlo(\n target_log_prob_fn=target.log_prob,\n step_size=0.05,\n num_leapfrog_steps=20))\n chains_states.shape\n ==> (1000, 10, 2)\n\n rhat = tfp.mcmc.diagnostic.potential_scale_reduction(\n chains_states, independent_chain_ndims=1)\n\n # The second dimension needed a longer burn-in.\n rhat.eval()\n ==> [1.05, 1.3]\n ```\n\n To see why R-hat is reasonable, let `X` be a random variable drawn uniformly\n from the combined states (combined over all chains). Then, in the limit\n `N, C --> infinity`, with `E`, `Var` denoting expectation and variance,\n\n ```R-hat = ( E[Var[X | chain]] + Var[E[X | chain]] ) / E[Var[X | chain]].```\n\n Using the law of total variance, the numerator is the variance of the combined\n states, and the denominator is the total variance minus the variance of the\n the individual chain means. If the chains are all drawing from the same\n distribution, they will have the same mean, and thus the ratio should be one.\n\n #### References\n\n [1]: Stephen P. Brooks and Andrew Gelman. General Methods for Monitoring\n Convergence of Iterative Simulations. _Journal of Computational and\n Graphical Statistics_, 7(4), 1998.\n\n [2]: Andrew Gelman and Donald B. Rubin. Inference from Iterative Simulation\n Using Multiple Sequences. _Statistical Science_, 7(4):457-472, 1992.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/mcmc/diagnostic.py#L335-L370", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:_potential_scale_reduction_single_state-6030a9f4f2@held-out", "question": "potential_scale_reduction for one single state `Tensor`.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/bijectors/bijector.py#L104-L110", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:_Mapping.remove-b644375de8@held-out", "question": "To support weak referencing, removes cache key from the cache value.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/bijectors/bijector.py#L112-L120", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:_Mapping._merge-ac3c68f30f@held-out", "question": "Helper to merge which handles merging one value.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/mcmc/internal/slice_sampler_utils.py#L26-L87", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:_left_doubling_increments-bcacd1b1de@held-out", "question": "Computes the doubling increments for the left end point.\n\n The doubling procedure expands an initial interval to find a superset of the\n true slice. At each doubling iteration, the interval width is doubled to\n either the left or the right hand side with equal probability.\n If, initially, the left end point is at `L(0)` and the width of the\n interval is `w(0)`, then the left end point and the width at the\n k-th iteration (denoted L(k) and w(k) respectively) are given by the following\n recursions:\n\n ```none\n w(k) = 2 * w(k-1)\n L(k) = L(k-1) - w(k-1) * X_k, X_k ~ Bernoulli(0.5)\n or, L(0) - L(k) = w(0) Sum(2^i * X(i+1), 0 <= i < k)\n ```\n\n This function computes the sequence of `L(0)-L(k)` and `w(k)` for k between 0\n and `max_doublings` independently for each chain.\n\n Args:\n batch_shape: Positive int32 `tf.Tensor`. The batch shape.\n max_doublings: Scalar positive int32 `tf.Tensor`. The maximum number of\n doublings to consider.\n step_size: A real `tf.Tensor` with shape compatible with [num_chains].\n The size of the initial interval.\n seed: (Optional) positive int. The random seed. If None, no seed is set.\n name: Python `str` name prefixed to Ops created by this function.\n Default value: `None` (i.e., 'find_slice_bounds').\n\n Returns:\n left_increments: A tensor of shape (max_doublings+1, batch_shape). The\n relative position of the left end point after the doublings.\n widths: A tensor of shape (max_doublings+1, ones_like(batch_shape)). The\n widths of the intervals at each stage of the doubling.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/edward2/program_transformations.py#L34-L135", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:make_value_setter-1587415a77@held-out", "question": "Creates a value-setting interceptor.\n\n This function creates an interceptor that sets values of Edward2 random\n variable objects. This is useful for a range of tasks, including conditioning\n on observed data, sampling from posterior predictive distributions, and as a\n building block of inference primitives such as computing log joint\n probabilities (see examples below).\n\n Args:\n **model_kwargs: dict of str to Tensor. Keys are the names of random\n variables in the model to which this interceptor is being applied. Values\n are Tensors to set their value to. Variables not included in this dict\n will not be set and will maintain their existing value semantics (by\n default, a sample from the parent-conditional distribution).\n\n Returns:\n set_values: function that sets the value of intercepted ops.\n\n #### Examples\n\n Consider for illustration a model with latent `z` and\n observed `x`, and a corresponding trainable posterior model:\n\n ```python\n num_observations = 10\n def model():\n z = ed.Normal(loc=0, scale=1., name='z') # log rate\n x = ed.Poisson(rate=tf.exp(z) * tf.ones(num_observations), name='x')\n return x\n\n def variational_model():\n return ed.Normal(loc=tf.Variable(0.),\n scale=tf.nn.softplus(tf.Variable(-4.)),\n name='z') # for simplicity, match name of the model RV.\n ```\n\n We can use a value-setting interceptor to condition the model on observed\n data. This approach is slightly more cumbersome than that of partially\n evaluating the complete log-joint function, but has the potential advantage\n that it returns a new model callable, which may be used to sample downstream\n variables, passed into additional transformations, etc.\n\n ```python\n x_observed = np.array([6, 3, 1, 8, 7, 0, 6, 4, 7, 5])\n def observed_model():\n with ed.interception(make_value_setter(x=x_observed)):\n model()\n observed_log_joint_fn = ed.make_log_joint_fn(observed_model)\n\n # After fixing 'x', the observed log joint is now only a function of 'z'.\n # This enables us to define a variational lower bound,\n # `E_q[ log p(x, z) - log q(z)]`, simply by evaluating the observed and\n # variational log joints at variational samples.\n variational_log_joint_fn = ed.make_log_joint_fn(variational_model)\n with ed.tape() as variational_sample: # Sample trace from variational model.\n variational_model()\n elbo_loss = -(observed_log_joint_fn(**variational_sample) -\n variational_log_joint_fn(**variational_sample))\n ```\n\n After performing inference by minimizing the variational loss, a value-setting\n interceptor enables simulation from the posterior predictive distribution:\n\n ```python\n with ed.tape() as posterior_samples: # tape is a map {rv.name : rv}\n variational_model()\n with ed.interception(ed.make_value_setter(**posterior_samples)):\n x = model()\n # x is a sample from p(X | Z = z') where z' ~ q(z) (the variational model)\n ```\n\n As another example, using a value setter inside of `ed.tape` enables\n computing the log joint probability, by setting all variables to\n posterior values and then accumulating the log probs of those values under\n the induced parent-conditional distributions. This is one way that we could\n have implemented `ed.make_log_joint_fn`:\n\n ```python\n def make_log_joint_fn_demo(model):\n def log_joint_fn(**model_kwargs):\n with ed.tape() as model_tape:\n with ed.make_value_setter(**model_kwargs):\n model()\n\n # accumulate sum_i log p(X_i = x_i | X_{:i-1} = x_{:i-1})\n log_prob = 0.\n for rv in model_tape.values():\n log_prob += tf.reduce_sum(rv.log_prob(rv.value))\n\n return log_prob\n return log_joint_fn\n ```", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/edward2/program_transformations.py#L138-L223", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:make_log_joint_fn-1ae7e2a894@held-out", "question": "Takes Edward probabilistic program and returns its log joint function.\n\n Args:\n model: Python callable which executes the generative process of a\n computable probability distribution using `ed.RandomVariable`s.\n\n Returns:\n A log-joint probability function. Its inputs are `model`'s original inputs\n and random variables which appear during the program execution. Its output\n is a scalar tf.Tensor.\n\n #### Examples\n\n Below we define Bayesian logistic regression as an Edward program,\n representing the model's generative process. We apply `make_log_joint_fn` in\n order to represent the model in terms of its joint probability function.\n\n ```python\n from tensorflow_probability import edward2 as ed\n\n def logistic_regression(features):\n coeffs = ed.Normal(loc=0., scale=1.,\n sample_shape=features.shape[1], name=\"coeffs\")\n outcomes = ed.Bernoulli(logits=tf.tensordot(features, coeffs, [[1], [0]]),\n name=\"outcomes\")\n return outcomes\n\n log_joint = ed.make_log_joint_fn(logistic_regression)\n\n features = tf.random_normal([3, 2])\n coeffs_value = tf.random_normal([2])\n outcomes_value = tf.round(tf.random_uniform([3]))\n output = log_joint(features, coeffs=coeffs_value, outcomes=outcomes_value)\n ```", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/layers/util.py#L119-L193", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:default_mean_field_normal_fn-ad139dd973@held-out", "question": "Creates a function to build Normal distributions with trainable params.\n\n This function produces a closure which produces `tfd.Normal`\n parameterized by a loc` and `scale` each created using `tf.get_variable`.\n\n Args:\n is_singular: Python `bool` if `True`, forces the special case limit of\n `scale->0`, i.e., a `Deterministic` distribution.\n loc_initializer: Initializer function for the `loc` parameters.\n The default is `tf.random_normal_initializer(mean=0., stddev=0.1)`.\n untransformed_scale_initializer: Initializer function for the `scale`\n parameters. Default value: `tf.random_normal_initializer(mean=-3.,\n stddev=0.1)`. This implies the softplus transformed result is initialized\n near `0`. It allows a `Normal` distribution with `scale` parameter set to\n this value to approximately act like a point mass.\n loc_regularizer: Regularizer function for the `loc` parameters.\n untransformed_scale_regularizer: Regularizer function for the `scale`\n parameters.\n loc_constraint: An optional projection function to be applied to the\n loc after being updated by an `Optimizer`. The function must take as input\n the unprojected variable and must return the projected variable (which\n must have the same shape). Constraints are not safe to use when doing\n asynchronous distributed training.\n untransformed_scale_constraint: An optional projection function to be\n applied to the `scale` parameters after being updated by an `Optimizer`\n (e.g. used to implement norm constraints or value constraints). The\n function must take as input the unprojected variable and must return the\n projected variable (which must have the same shape). Constraints are not\n safe to use when doing asynchronous distributed training.\n\n Returns:\n make_normal_fn: Python `callable` which creates a `tfd.Normal`\n using from args: `dtype, shape, name, trainable, add_variable_fn`.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/examples/vae.py#L479-L494", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:build_input_fns-650ba8890b@held-out", "question": "Builds an Iterator switching between train and heldout data.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/distributions/joint_distribution.py#L324-L341", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:maybe_check_wont_broadcast-3b5900bb54@held-out", "question": "Verifies that `parts` don't broadcast.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/math/root_search.py#L44-L321", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:secant_root-2e2a2db923@held-out", "question": "r\"\"\"Finds root(s) of a function of single variable using the secant method.\n\n The [secant method](https://en.wikipedia.org/wiki/Secant_method) is a\n root-finding algorithm that uses a succession of roots of secant lines to\n better approximate a root of a function. The secant method can be thought of\n as a finite-difference approximation of Newton's method.\n\n Args:\n objective_fn: Python callable for which roots are searched. It must be a\n callable of a single variable. `objective_fn` must return a `Tensor` of\n the same shape and dtype as `initial_position`.\n initial_position: `Tensor` or Python float representing the starting\n position. The function will search for roots in the neighborhood of each\n point. The shape of `initial_position` should match that of the input to\n `objective_fn`.\n next_position: Optional `Tensor` representing the next position in the\n search. If specified, this argument must broadcast with the shape of\n `initial_position` and have the same dtype. It will be used to compute the\n first step to take when searching for roots. If not specified, a default\n value will be used instead.\n Default value: `initial_position * (1 + 1e-4) + sign(initial_position) *\n 1e-4`.\n value_at_position: Optional `Tensor` or Pyhon float representing the value\n of `objective_fn` at `initial_position`. If specified, this argument must\n have the same shape and dtype as `initial_position`. If not specified, the\n value will be evaluated during the search.\n Default value: None.\n position_tolerance: Optional `Tensor` representing the tolerance for the\n estimated roots. If specified, this argument must broadcast with the shape\n of `initial_position` and have the same dtype.\n Default value: `1e-8`.\n value_tolerance: Optional `Tensor` representing the tolerance used to check\n for roots. If the absolute value of `objective_fn` is smaller than\n `value_tolerance` at a given position, then that position is considered a\n root for the function. If specified, this argument must broadcast with the\n shape of `initial_position` and have the same dtype.\n Default value: `1e-8`.\n max_iterations: Optional `Tensor` or Python integer specifying the maximum\n number of steps to perform for each initial position. Must broadcast with\n the shape of `initial_position`.\n Default value: `50`.\n stopping_policy_fn: Python `callable` controlling the algorithm termination.\n It must be a callable accepting a `Tensor` of booleans with the shape of\n `initial_position` (each denoting whether the search is finished for each\n starting point), and returning a scalar boolean `Tensor` (indicating\n whether the overall search should stop). Typical values are\n `tf.reduce_all` (which returns only when the search is finished for all\n points), and `tf.reduce_any` (which returns as soon as the search is\n finished for any point).\n Default value: `tf.reduce_all` (returns only when the search is finished\n for all points).\n validate_args: Python `bool` indicating whether to validate arguments such\n as `position_tolerance`, `value_tolerance`, and `max_iterations`.\n Default value: `False`.\n name: Python `str` name prefixed to ops created by this function.\n\n Returns:\n root_search_results: A Python `namedtuple` containing the following items:\n estimated_root: `Tensor` containing the last position explored. If the\n search was successful within the specified tolerance, this position is\n a root of the objective function.\n objective_at_estimated_root: `Tensor` containing the value of the\n objective function at `position`. If the search was successful within\n the specified tolerance, then this is close to 0.\n num_iterations: The number of iterations performed.\n\n Raises:\n ValueError: if a non-callable `stopping_policy_fn` is passed.\n\n #### Examples\n\n ```python\n import tensorflow as tf\n import tensorflow_probability as tfp\n tf.enable_eager_execution()\n\n # Example 1: Roots of a single function from two different starting points.\n\n f = lambda x: (63 * x**5 - 70 * x**3 + 15 * x) / 8.\n x = tf.constant([-1, 10], dtype=tf.float64)\n\n tfp.math.secant_root(objective_fn=f, initial_position=x))\n # ==> RootSearchResults(\n estimated_root=array([-0.90617985, 0.90617985]),\n objective_at_estimated_root=array([-4.81727769e-10, 7.44957651e-10]),\n num_iterations=array([ 7, 24], dtype=int32))\n\n tfp.math.secant_root(objective_fn=f,\n initial_position=x,\n stopping_policy_fn=tf.reduce_any)\n # ==> RootSearchResults(\n estimated_root=array([-0.90617985, 3.27379206]),\n objective_at_estimated_root=array([-4.81727769e-10, 2.66058312e+03]),\n num_iterations=array([7, 8], dtype=int32))\n\n # Example 2: Roots of a multiplex function from a single starting point.\n\n def f(x):\n return tf.constant([0., 63. / 8], dtype=tf.float64) * x**5 \\\n + tf.constant([5. / 2, -70. / 8], dtype=tf.float64) * x**3 \\\n + tf.constant([-3. / 2, 15. / 8], dtype=tf.float64) * x\n\n x = tf.constant([-1, -1], dtype=tf.float64)\n\n tfp.math.secant_root(objective_fn=f, initial_position=x)\n # ==> RootSearchResults(\n estimated_root=array([-0.77459667, -0.90617985]),\n objective_at_estimated_root=array([-7.81339438e-11, -4.81727769e-10]),\n num_iterations=array([7, 7], dtype=int32))\n\n # Example 3: Roots of a multiplex function from two starting points.\n\n def f(x):\n return tf.constant([0., 63. / 8], dtype=tf.float64) * x**5 \\\n + tf.constant([5. / 2, -70. / 8], dtype=tf.float64) * x**3 \\\n + tf.constant([-3. / 2, 15. / 8], dtype=tf.float64) * x\n\n x = tf.constant([[-1, -1], [10, 10]], dtype=tf.float64)\n\n tfp.math.secant_root(objective_fn=f, initial_position=x)\n # ==> RootSearchResults(\n estimated_root=array([\n [-0.77459667, -0.90617985],\n [ 0.77459667, 0.90617985]]),\n objective_at_estimated_root=array([\n [-7.81339438e-11, -4.81727769e-10],\n [6.66025013e-11, 7.44957651e-10]]),\n num_iterations=array([\n [7, 7],\n [16, 24]], dtype=int32))\n ```", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/mcmc/langevin.py#L691-L745", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:_get_drift-a9d132c4de@held-out", "question": "Compute diffusion drift at the current location `current_state`.\n\n The drift of the diffusion at is computed as\n\n ```none\n 0.5 * `step_size` * volatility_parts * `target_log_prob_fn(current_state)`\n + `step_size` * `grads_volatility`\n ```\n\n where `volatility_parts` = `volatility_fn(current_state)**2` and\n `grads_volatility` is a gradient of `volatility_parts` at the `current_state`.\n\n Args:\n step_size_parts: Python `list` of `Tensor`s representing the step size for\n Euler-Maruyama method. Must broadcast with the shape of\n `volatility_parts`. Larger step sizes lead to faster progress, but\n too-large step sizes make rejection exponentially more likely. When\n possible, it's often helpful to match per-variable step sizes to the\n standard deviations of the target distribution in each variable.\n volatility_parts: Python `list` of `Tensor`s representing the value of\n `volatility_fn(*state_parts)`.\n grads_volatility: Python list of `Tensor`s representing the value of the\n gradient of `volatility_parts**2` wrt the state of the chain.\n grads_target_log_prob: Python list of `Tensor`s representing\n gradient of `target_log_prob_fn(*state_parts`) wrt `state_parts`. Must\n have same shape as `volatility_parts`.\n name: Python `str` name prefixed to Ops created by this function.\n Default value: `None` (i.e., 'mala_get_drift').\n\n Returns:\n drift_parts: Tensor or Python list of `Tensor`s representing the\n state(s) of the Markov chain(s) at each result step. Has same shape as\n input `current_state_parts`.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/math/diag_jacobian.py#L32-L248", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:diag_jacobian-821f1c8333@held-out", "question": "Computes diagonal of the Jacobian matrix of `ys=fn(xs)` wrt `xs`.\n\n If `ys` is a tensor or a list of tensors of the form `(ys_1, .., ys_n)` and\n `xs` is of the form `(xs_1, .., xs_n)`, the function `jacobians_diag`\n computes the diagonal of the Jacobian matrix, i.e., the partial derivatives\n `(dys_1/dxs_1,.., dys_n/dxs_n`). For definition details, see\n https://en.wikipedia.org/wiki/Jacobian_matrix_and_determinant\n #### Example\n\n ##### Diagonal Hessian of the log-density of a 3D Gaussian distribution\n\n In this example we sample from a standard univariate normal\n distribution using MALA with `step_size` equal to 0.75.\n\n ```python\n import tensorflow as tf\n import tensorflow_probability as tfp\n import numpy as np\n\n tfd = tfp.distributions\n\n dtype = np.float32\n with tf.Session(graph=tf.Graph()) as sess:\n true_mean = dtype([0, 0, 0])\n true_cov = dtype([[1, 0.25, 0.25], [0.25, 2, 0.25], [0.25, 0.25, 3]])\n chol = tf.linalg.cholesky(true_cov)\n target = tfd.MultivariateNormalTriL(loc=true_mean, scale_tril=chol)\n\n # Assume that the state is passed as a list of tensors `x` and `y`.\n # Then the target function is defined as follows:\n def target_fn(x, y):\n # Stack the input tensors together\n z = tf.concat([x, y], axis=-1) - true_mean\n return target.log_prob(z)\n\n sample_shape = [3, 5]\n state = [tf.ones(sample_shape + [2], dtype=dtype),\n tf.ones(sample_shape + [1], dtype=dtype)]\n fn_val, grads = tfp.math.value_and_gradient(target_fn, state)\n\n # We can either pass the `sample_shape` of the `state` or not, which impacts\n # computational speed of `diag_jacobian`\n _, diag_jacobian_shape_passed = diag_jacobian(\n xs=state, ys=grads, sample_shape=tf.shape(fn_val))\n _, diag_jacobian_shape_none = diag_jacobian(\n xs=state, ys=grads)\n\n diag_jacobian_shape_passed_ = sess.run(diag_jacobian_shape_passed)\n diag_jacobian_shape_none_ = sess.run(diag_jacobian_shape_none)\n\n print('hessian computed through `diag_jacobian`, sample_shape passed: ',\n np.concatenate(diag_jacobian_shape_passed_, -1))\n print('hessian computed through `diag_jacobian`, sample_shape skipped',\n np.concatenate(diag_jacobian_shape_none_, -1))\n\n ```\n\n Args:\n xs: `Tensor` or a python `list` of `Tensors` of real-like dtypes and shapes\n `sample_shape` + `event_shape_i`, where `event_shape_i` can be different\n for different tensors.\n ys: `Tensor` or a python `list` of `Tensors` of the same dtype as `xs`. Must\n broadcast with the shape of `xs`. Can be omitted if `fn` is provided.\n sample_shape: A common `sample_shape` of the input tensors of `xs`. If not,\n provided, assumed to be `[1]`, which may result in a slow performance of\n `jacobians_diag`.\n fn: Python callable that takes `xs` as an argument (or `*xs`, if it is a\n list) and returns `ys`. Might be skipped if `ys` is provided and\n `tf.enable_eager_execution()` is disabled.\n parallel_iterations: `int` that specifies the allowed number of coordinates\n of the input tensor `xs`, for which the partial derivatives `dys_i/dxs_i`\n can be computed in parallel.\n name: Python `str` name prefixed to `Ops` created by this function.\n Default value: `None` (i.e., \"diag_jacobian\").\n\n Returns:\n ys: a list, which coincides with the input `ys`, when provided.\n If the input `ys` is None, `fn(*xs)` gets computed and returned as a list.\n jacobians_diag_res: a `Tensor` or a Python list of `Tensor`s of the same\n dtypes and shapes as the input `xs`. This is the diagonal of the Jacobian\n of ys wrt xs.\n\n Raises:\n ValueError: if lists `xs` and `ys` have different length or both `ys` and\n `fn` are `None`, or `fn` is None in the eager execution mode.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/distributions/batch_reshape.py#L210-L232", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:BatchReshape._sample_shape-625cf55295@held-out", "question": "Computes graph and static `sample_shape`.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/distributions/binomial.py#L299-L309", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:Binomial._maybe_assert_valid_sample-4259ec5ad1@held-out", "question": "Check counts for proper shape, values, then return tensor version.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/distributions/pareto.py#L249-L276", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:_kl_pareto_pareto-e6d7f6184b@held-out", "question": "Calculate the batched KL divergence KL(a || b) with a and b Pareto.\n\n Args:\n a: instance of a Pareto distribution object.\n b: instance of a Pareto distribution object.\n name: (optional) Name to use for created operations.\n default is \"kl_pareto_pareto\".\n\n Returns:\n Batchwise KL(a || b)", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/examples/latent_dirichlet_allocation_edward2.py#L419-L457", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:newsgroups_dataset-d17a96f1a8@held-out", "question": "20 newsgroups as a tf.data.Dataset.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/internal/dtype_util.py#L52-L57", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:base_dtype-ffb84d6826@held-out", "question": "Returns a non-reference `dtype` based on this `dtype`.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/internal/dtype_util.py#L150-L198", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:_assert_same_base_type-1bb8ce3958@held-out", "question": "r\"\"\"Asserts all items are of the same base type.\n\n Args:\n items: List of graph items (e.g., `Variable`, `Tensor`, `SparseTensor`,\n `Operation`, or `IndexedSlices`). Can include `None` elements, which\n will be ignored.\n expected_type: Expected type. If not specified, assert all items are\n of the same base type.\n\n Returns:\n Validated type, or none if neither expected_type nor items provided.\n\n Raises:\n ValueError: If any types do not match.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/distributions/onehot_categorical.py#L241-L258", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:_kl_categorical_categorical-d408c9d232@held-out", "question": "Calculate the batched KL divergence KL(a || b) with a, b OneHotCategorical.\n\n Args:\n a: instance of a OneHotCategorical distribution object.\n b: instance of a OneHotCategorical distribution object.\n name: (optional) Name to use for created operations.\n default is \"kl_categorical_categorical\".\n\n Returns:\n Batchwise KL(a || b)", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/optimizer/nelder_mead.py#L343-L456", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:nelder_mead_one_step-ad4b7ede25@held-out", "question": "A single iteration of the Nelder Mead algorithm.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/optimizer/nelder_mead.py#L754-L762", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:_default_step_sizes-e150cb5bcd@held-out", "question": "Chooses default step sizes according to [Gao and Han(2010)][3].", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/optimizer/nelder_mead.py#L847-L880", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:_evaluate_objective_multiple-5f511f7d0c@held-out", "question": "Evaluates the objective function on a batch of points.\n\n If `batch_evaluate_objective` is True, returns\n `objective function(arg_batch)` else it maps the `objective_function`\n across the `arg_batch`.\n\n Args:\n objective_function: A Python callable that accepts a single `Tensor` of\n rank 'R > 1' and any shape 's' and returns a scalar `Tensor` of real dtype\n containing the value of the function at that point. If\n `batch a `Tensor` of shape `[batch_size] + s ` where `batch_size` is the\n size of the batch of args. In this case, the expected return value is a\n `Tensor` of shape `[batch_size]`.\n arg_batch: A `Tensor` of real dtype. The batch of arguments at which to\n evaluate the `objective_function`. If `batch_evaluate_objective` is False,\n `arg_batch` will be unpacked along the zeroth axis and the\n `objective_function` will be applied to each element.\n batch_evaluate_objective: `bool`. Whether the `objective_function` can\n evaluate a batch of arguments at once.\n\n Returns:\n A tuple containing:\n objective_values: A `Tensor` of real dtype and shape `[batch_size]`.\n The value of the objective function evaluated at the supplied\n `arg_batch`.\n num_evaluations: An `int32` scalar `Tensor`containing the number of\n points on which the objective function was evaluated (i.e `batch_size`).", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/layers/initializers.py#L119-L126", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:BlockwiseInitializer.from_config-3ae86925d7@held-out", "question": "Instantiates an initializer from a configuration dictionary.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/distributions/internal/moving_stats.py#L31-L110", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:assign_moving_mean_variance-23a8c0eb21@held-out", "question": "Compute exponentially weighted moving {mean,variance} of a streaming value.\n\n The `value` updated exponentially weighted moving `mean_var` and\n `variance_var` are given by the following recurrence relations:\n\n ```python\n variance_var = decay * (variance_var + (1 - decay) * (value - mean_var)**2)\n mean_var = decay * mean_var + (1 - decay) * value\n ```\n\n Note: `mean_var` is updated *after* `variance_var`, i.e., `variance_var` uses\n the lag-1 mean.\n\n For derivation justification, see [Finch (2009; Eq. 143)][1].\n Parameterization: Finch's `alpha` is `1 - decay`.\n\n Args:\n mean_var: `float`-like `Variable` representing the exponentially weighted\n moving mean. Same shape as `variance_var` and `value`.\n variance_var: `float`-like `Variable` representing the\n exponentially weighted moving variance. Same shape as `mean_var` and\n `value`.\n value: `float`-like `Tensor`. Same shape as `mean_var` and `variance_var`.\n decay: A `float`-like `Tensor`. The moving mean decay. Typically close to\n `1.`, e.g., `0.999`.\n name: Optional name of the returned operation.\n\n Returns:\n mean_var: `Variable` representing the `value`-updated exponentially weighted\n moving mean.\n variance_var: `Variable` representing the `value`-updated\n exponentially weighted moving variance.\n\n Raises:\n TypeError: if `mean_var` does not have float type `dtype`.\n TypeError: if `mean_var`, `variance_var`, `value`, `decay` have different\n `base_dtype`.\n\n #### References\n\n [1]: Tony Finch. Incremental calculation of weighted mean and variance.\n _Technical Report_, 2009.\n http://people.ds.cam.ac.uk/fanf2/hermes/doc/antiforgery/stats.pdf", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/distributions/transformed_distribution.py#L415-L430", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:TransformedDistribution._finish_log_prob_for_one_fiber-6a894c8938@held-out", "question": "Finish computation of log_prob on one element of the inverse image.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/distributions/internal/slicing.py#L46-L104", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:_slice_single_param-b7423ee1c4@held-out", "question": "Slices a single parameter of a distribution.\n\n Args:\n param: A `Tensor`, the original parameter to slice.\n param_event_ndims: `int` event parameterization rank for this parameter.\n slices: A `tuple` of normalized slices.\n dist_batch_shape: The distribution's batch shape `Tensor`.\n\n Returns:\n new_param: A `Tensor`, batch-sliced according to slices.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/distributions/internal/slicing.py#L107-L142", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:_slice_params_to_dict-90604fee7b@held-out", "question": "Computes the override dictionary of sliced parameters.\n\n Args:\n dist: The tfd.Distribution being batch-sliced.\n params_event_ndims: Per-event parameter ranks, a `str->int` `dict`.\n slices: Slices as received by __getitem__.\n\n Returns:\n overrides: `str->Tensor` `dict` of batch-sliced parameter overrides.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/internal/distribution_util.py#L281-L351", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:shapes_from_loc_and_scale-145977c2c9@held-out", "question": "Infer distribution batch and event shapes from a location and scale.\n\n Location and scale family distributions determine their batch/event shape by\n broadcasting the `loc` and `scale` args. This helper does that broadcast,\n statically if possible.\n\n Batch shape broadcasts as per the normal rules.\n We allow the `loc` event shape to broadcast up to that of `scale`. We do not\n allow `scale`'s event shape to change. Therefore, the last dimension of `loc`\n must either be size `1`, or the same as `scale.range_dimension`.\n\n See `MultivariateNormalLinearOperator` for a usage example.\n\n Args:\n loc: `Tensor` (already converted to tensor) or `None`. If `None`, or\n `rank(loc)==0`, both batch and event shape are determined by `scale`.\n scale: A `LinearOperator` instance.\n name: A string name to prepend to created ops.\n\n Returns:\n batch_shape: `TensorShape` (if broadcast is done statically), or `Tensor`.\n event_shape: `TensorShape` (if broadcast is done statically), or `Tensor`.\n\n Raises:\n ValueError: If the last dimension of `loc` is determined statically to be\n different than the range of `scale`.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/internal/distribution_util.py#L465-L503", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:pad_mixture_dimensions-cc52487ac5@held-out", "question": "Pad dimensions of event tensors for mixture distributions.\n\n See `Mixture._sample_n` and `MixtureSameFamily._sample_n` for usage examples.\n\n Args:\n x: event tensor to pad.\n mixture_distribution: Base distribution of the mixture.\n categorical_distribution: `Categorical` distribution that mixes the base\n distribution.\n event_ndims: Integer specifying the number of event dimensions in the event\n tensor.\n\n Returns:\n A padded version of `x` that can broadcast with `categorical_distribution`.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/internal/distribution_util.py#L642-L683", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:assert_integer_form-7bbe754a59@held-out", "question": "Assert that x has integer components (or floats equal to integers).\n\n Args:\n x: Floating-point `Tensor`\n data: The tensors to print out if the condition is `False`. Defaults to\n error message and first few entries of `x` and `y`.\n summarize: Print this many entries of each tensor.\n message: A string to prefix to the default message.\n int_dtype: A `tf.dtype` used to cast the float to. The default (`None`)\n implies the smallest possible signed int will be used for casting.\n name: A name for this operation (optional).\n\n Returns:\n Op raising `InvalidArgumentError` if `cast(x, int_dtype) != x`.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/internal/distribution_util.py#L848-L854", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:_is_known_unsigned_by_dtype-5b396a6319@held-out", "question": "Helper returning True if dtype is known to be unsigned.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/internal/distribution_util.py#L889-L895", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:_smallest_integer_by_dtype-f175615cd5@held-out", "question": "Helper returning the smallest integer exactly representable by dtype.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/internal/distribution_util.py#L1136-L1195", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:matrix_diag_transform-6e57dd858d@held-out", "question": "Transform diagonal of [batch-]matrix, leave rest of matrix unchanged.\n\n Create a trainable covariance defined by a Cholesky factor:\n\n ```python\n # Transform network layer into 2 x 2 array.\n matrix_values = tf.contrib.layers.fully_connected(activations, 4)\n matrix = tf.reshape(matrix_values, (batch_size, 2, 2))\n\n # Make the diagonal positive. If the upper triangle was zero, this would be a\n # valid Cholesky factor.\n chol = matrix_diag_transform(matrix, transform=tf.nn.softplus)\n\n # LinearOperatorLowerTriangular ignores the upper triangle.\n operator = LinearOperatorLowerTriangular(chol)\n ```\n\n Example of heteroskedastic 2-D linear regression.\n\n ```python\n tfd = tfp.distributions\n\n # Get a trainable Cholesky factor.\n matrix_values = tf.contrib.layers.fully_connected(activations, 4)\n matrix = tf.reshape(matrix_values, (batch_size, 2, 2))\n chol = matrix_diag_transform(matrix, transform=tf.nn.softplus)\n\n # Get a trainable mean.\n mu = tf.contrib.layers.fully_connected(activations, 2)\n\n # This is a fully trainable multivariate normal!\n dist = tfd.MultivariateNormalTriL(mu, chol)\n\n # Standard log loss. Minimizing this will \"train\" mu and chol, and then dist\n # will be a distribution predicting labels as multivariate Gaussians.\n loss = -1 * tf.reduce_mean(dist.log_prob(labels))\n ```\n\n Args:\n matrix: Rank `R` `Tensor`, `R >= 2`, where the last two dimensions are\n equal.\n transform: Element-wise function mapping `Tensors` to `Tensors`. To be\n applied to the diagonal of `matrix`. If `None`, `matrix` is returned\n unchanged. Defaults to `None`.\n name: A name to give created ops. Defaults to \"matrix_diag_transform\".\n\n Returns:\n A `Tensor` with same shape and `dtype` as `matrix`.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/internal/distribution_util.py#L1198-L1271", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:rotate_transpose-af23c88b04@held-out", "question": "Circularly moves dims left or right.\n\n Effectively identical to:\n\n ```python\n numpy.transpose(x, numpy.roll(numpy.arange(len(x.shape)), shift))\n ```\n\n When `validate_args=False` additional graph-runtime checks are\n performed. These checks entail moving data from to GPU to CPU.\n\n Example:\n\n ```python\n x = tf.random_normal([1, 2, 3, 4]) # Tensor of shape [1, 2, 3, 4].\n rotate_transpose(x, -1).shape == [2, 3, 4, 1]\n rotate_transpose(x, -2).shape == [3, 4, 1, 2]\n rotate_transpose(x, 1).shape == [4, 1, 2, 3]\n rotate_transpose(x, 2).shape == [3, 4, 1, 2]\n rotate_transpose(x, 7).shape == rotate_transpose(x, 3).shape # [2, 3, 4, 1]\n rotate_transpose(x, -7).shape == rotate_transpose(x, -3).shape # [4, 1, 2, 3]\n ```\n\n Args:\n x: `Tensor`.\n shift: `Tensor`. Number of dimensions to transpose left (shift<0) or\n transpose right (shift>0).\n name: Python `str`. The name to give this op.\n\n Returns:\n rotated_x: Input `Tensor` with dimensions circularly rotated by shift.\n\n Raises:\n TypeError: if shift is not integer type.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/internal/distribution_util.py#L1415-L1561", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:fill_triangular-587ee9aabd@held-out", "question": "r\"\"\"Creates a (batch of) triangular matrix from a vector of inputs.\n\n Created matrix can be lower- or upper-triangular. (It is more efficient to\n create the matrix as upper or lower, rather than transpose.)\n\n Triangular matrix elements are filled in a clockwise spiral. See example,\n below.\n\n If `x.shape` is `[b1, b2, ..., bB, d]` then the output shape is\n `[b1, b2, ..., bB, n, n]` where `n` is such that `d = n(n+1)/2`, i.e.,\n `n = int(np.sqrt(0.25 + 2. * m) - 0.5)`.\n\n Example:\n\n ```python\n fill_triangular([1, 2, 3, 4, 5, 6])\n # ==> [[4, 0, 0],\n # [6, 5, 0],\n # [3, 2, 1]]\n\n fill_triangular([1, 2, 3, 4, 5, 6], upper=True)\n # ==> [[1, 2, 3],\n # [0, 5, 6],\n # [0, 0, 4]]\n ```\n\n The key trick is to create an upper triangular matrix by concatenating `x`\n and a tail of itself, then reshaping.\n\n Suppose that we are filling the upper triangle of an `n`-by-`n` matrix `M`\n from a vector `x`. The matrix `M` contains n**2 entries total. The vector `x`\n contains `n * (n+1) / 2` entries. For concreteness, we'll consider `n = 5`\n (so `x` has `15` entries and `M` has `25`). We'll concatenate `x` and `x` with\n the first (`n = 5`) elements removed and reversed:\n\n ```python\n x = np.arange(15) + 1\n xc = np.concatenate([x, x[5:][::-1]])\n # ==> array([1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 15, 14, 13,\n # 12, 11, 10, 9, 8, 7, 6])\n\n # (We add one to the arange result to disambiguate the zeros below the\n # diagonal of our upper-triangular matrix from the first entry in `x`.)\n\n # Now, when reshapedlay this out as a matrix:\n y = np.reshape(xc, [5, 5])\n # ==> array([[ 1, 2, 3, 4, 5],\n # [ 6, 7, 8, 9, 10],\n # [11, 12, 13, 14, 15],\n # [15, 14, 13, 12, 11],\n # [10, 9, 8, 7, 6]])\n\n # Finally, zero the elements below the diagonal:\n y = np.triu(y, k=0)\n # ==> array([[ 1, 2, 3, 4, 5],\n # [ 0, 7, 8, 9, 10],\n # [ 0, 0, 13, 14, 15],\n # [ 0, 0, 0, 12, 11],\n # [ 0, 0, 0, 0, 6]])\n ```\n\n From this example we see that the resuting matrix is upper-triangular, and\n contains all the entries of x, as desired. The rest is details:\n - If `n` is even, `x` doesn't exactly fill an even number of rows (it fills\n `n / 2` rows and half of an additional row), but the whole scheme still\n works.\n - If we want a lower triangular matrix instead of an upper triangular,\n we remove the first `n` elements from `x` rather than from the reversed\n `x`.\n\n For additional comparisons, a pure numpy version of this function can be found\n in `distribution_util_test.py`, function `_fill_triangular`.\n\n Args:\n x: `Tensor` representing lower (or upper) triangular elements.\n upper: Python `bool` representing whether output matrix should be upper\n triangular (`True`) or lower triangular (`False`, default).\n name: Python `str`. The name to give this op.\n\n Returns:\n tril: `Tensor` with lower (or upper) triangular elements filled from `x`.\n\n Raises:\n ValueError: if `x` cannot be mapped to a triangular matrix.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/internal/distribution_util.py#L1633-L1698", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:tridiag-ed85fa813c@held-out", "question": "Creates a matrix with values set above, below, and on the diagonal.\n\n Example:\n\n ```python\n tridiag(below=[1., 2., 3.],\n diag=[4., 5., 6., 7.],\n above=[8., 9., 10.])\n # ==> array([[ 4., 8., 0., 0.],\n # [ 1., 5., 9., 0.],\n # [ 0., 2., 6., 10.],\n # [ 0., 0., 3., 7.]], dtype=float32)\n ```\n\n Warning: This Op is intended for convenience, not efficiency.\n\n Args:\n below: `Tensor` of shape `[B1, ..., Bb, d-1]` corresponding to the below\n diagonal part. `None` is logically equivalent to `below = 0`.\n diag: `Tensor` of shape `[B1, ..., Bb, d]` corresponding to the diagonal\n part. `None` is logically equivalent to `diag = 0`.\n above: `Tensor` of shape `[B1, ..., Bb, d-1]` corresponding to the above\n diagonal part. `None` is logically equivalent to `above = 0`.\n name: Python `str`. The name to give this op.\n\n Returns:\n tridiag: `Tensor` with values set above, below and on the diagonal.\n\n Raises:\n ValueError: if all inputs are `None`.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/internal/distribution_util.py#L1701-L1793", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:reduce_weighted_logsumexp-863ccab200@held-out", "question": "Computes `log(abs(sum(weight * exp(elements across tensor dimensions))))`.\n\n If all weights `w` are known to be positive, it is more efficient to directly\n use `reduce_logsumexp`, i.e., `tf.reduce_logsumexp(logx + tf.log(w))` is more\n efficient than `du.reduce_weighted_logsumexp(logx, w)`.\n\n Reduces `input_tensor` along the dimensions given in `axis`.\n Unless `keep_dims` is true, the rank of the tensor is reduced by 1 for each\n entry in `axis`. If `keep_dims` is true, the reduced dimensions\n are retained with length 1.\n\n If `axis` has no entries, all dimensions are reduced, and a\n tensor with a single element is returned.\n\n This function is more numerically stable than log(sum(w * exp(input))). It\n avoids overflows caused by taking the exp of large inputs and underflows\n caused by taking the log of small inputs.\n\n For example:\n\n ```python\n x = tf.constant([[0., 0, 0],\n [0, 0, 0]])\n\n w = tf.constant([[-1., 1, 1],\n [1, 1, 1]])\n\n du.reduce_weighted_logsumexp(x, w)\n # ==> log(-1*1 + 1*1 + 1*1 + 1*1 + 1*1 + 1*1) = log(4)\n\n du.reduce_weighted_logsumexp(x, w, axis=0)\n # ==> [log(-1+1), log(1+1), log(1+1)]\n\n du.reduce_weighted_logsumexp(x, w, axis=1)\n # ==> [log(-1+1+1), log(1+1+1)]\n\n du.reduce_weighted_logsumexp(x, w, axis=1, keep_dims=True)\n # ==> [[log(-1+1+1)], [log(1+1+1)]]\n\n du.reduce_weighted_logsumexp(x, w, axis=[0, 1])\n # ==> log(-1+5)\n ```\n\n Args:\n logx: The tensor to reduce. Should have numeric type.\n w: The weight tensor. Should have numeric type identical to `logx`.\n axis: The dimensions to reduce. If `None` (the default), reduces all\n dimensions. Must be in the range `[-rank(input_tensor),\n rank(input_tensor))`.\n keep_dims: If true, retains reduced dimensions with length 1.\n return_sign: If `True`, returns the sign of the result.\n name: A name for the operation (optional).\n\n Returns:\n lswe: The `log(abs(sum(weight * exp(x))))` reduced tensor.\n sign: (Optional) The sign of `sum(weight * exp(x))`.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/internal/tensorshape_util.py#L192-L211", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:merge_with-0350fc02c7@held-out", "question": "Returns a shape combining the information in `x` and `other`.\n\n The dimensions in `x` and `other` are merged elementwise, according to the\n rules defined for `tf.Dimension.merge_with()`.\n\n For more details, see `help(tf.TensorShape.merge_with)`.\n\n Args:\n x: object representing a shape; convertible to `tf.TensorShape`.\n other: object representing a shape; convertible to `tf.TensorShape`.\n\n Returns:\n merged_shape: shape having `type(x)` containing the combined information of\n `x` and `other`.\n\n Raises:\n ValueError: If `x` and `other` are not compatible.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/distributions/linear_gaussian_ssm.py#L44-L69", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:_check_equal_shape-c66a2370be@held-out", "question": "Check that source and target shape match, statically if possible.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/distributions/linear_gaussian_ssm.py#L72-L155", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:_augment_sample_shape-010bb4fbc2@held-out", "question": "Augment a sample shape to broadcast batch dimensions.\n\n Computes an augmented sample shape, so that any batch dimensions not\n part of the distribution `partial_batch_dist` are treated as identical\n distributions.\n\n # partial_batch_dist.batch_shape = [ 7]\n # full_sample_and_batch_shape = [3, 4, 7]\n # => return an augmented sample shape of [3, 4] so that\n # partial_batch_dist.sample(augmented_sample_shape) has combined\n # sample and batch shape of [3, 4, 7].\n\n Args:\n partial_batch_dist: `tfd.Distribution` instance with batch shape a\n prefix of `full_sample_and_batch_shape`.\n full_sample_and_batch_shape: a Tensor or Tensor-like shape.\n validate_args: if True, check for shape errors at runtime.\n Returns:\n augmented_sample_shape: sample shape such that\n `partial_batch_dist.sample(augmented_sample_shape)` has combined\n sample and batch shape of `full_sample_and_batch_shape`.\n\n Raises:\n ValueError: if `partial_batch_dist.batch_shape` has more dimensions than\n `full_sample_and_batch_shape`.\n NotImplementedError: if broadcasting would be required to make\n `partial_batch_dist.batch_shape` into a prefix of\n `full_sample_and_batch_shape` .", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/distributions/linear_gaussian_ssm.py#L1158-L1195", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:build_backward_pass_step-05a798fa35@held-out", "question": "Build a callable that perform one step for backward smoothing.\n\n Args:\n get_transition_matrix_for_timestep: callable taking a timestep\n as an integer `Tensor` argument, and returning a `LinearOperator`\n of shape `[latent_size, latent_size]`.\n\n Returns:\n backward_pass_step: a callable that updates a BackwardPassState\n from timestep `t` to `t-1`.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/distributions/von_mises_fisher.py#L36-L73", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:_bessel_ive-f2549d0cb5@held-out", "question": "Computes I_v(z)*exp(-abs(z)) using a recurrence relation, where z > 0.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/distributions/von_mises_fisher.py#L262-L280", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:VonMisesFisher._log_normalization-c2ca01df1b@held-out", "question": "Computes the log-normalizer of the distribution.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/distributions/von_mises_fisher.py#L302-L305", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:VonMisesFisher._mode-27422d53fd@held-out", "question": "The mode of the von Mises-Fisher distribution is the mean direction.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/distributions/distribution.py#L129-L170", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:_convert_to_tensor-64768741bc@held-out", "question": "Converts the given `value` to a (structure of) `Tensor`.\n\n This function converts Python objects of various types to a (structure of)\n `Tensor` objects. It accepts `Tensor` objects, numpy arrays, Python lists, and\n Python scalars. For example:\n\n Args:\n value: An object whose structure matches that of `dtype ` and/or\n `dtype_hint` and for which each leaf has a registered `Tensor` conversion\n function.\n dtype: Optional (structure of) element type for the returned tensor. If\n missing, the type is inferred from the type of `value`.\n dtype_hint: Optional (structure of) element type for the returned tensor,\n used when dtype is None. In some cases, a caller may not have a dtype in\n mind when converting to a tensor, so dtype_hint can be used as a soft\n preference. If the conversion to `dtype_hint` is not possible, this\n argument has no effect.\n name: Optional name to use if a new `Tensor` is created.\n\n Returns:\n tensor: A (structure of) `Tensor` based on `value`.\n\n Raises:\n TypeError: If no conversion function is registered for `value` to `dtype`.\n RuntimeError: If a registered conversion function returns an invalid value.\n ValueError: If the `value` is a tensor not of given `dtype` in graph mode.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/mcmc/internal/util.py#L66-L71", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:make_name-64772f1cf0@held-out", "question": "Helper which makes a `str` name; useful for tf.compat.v1.name_scope.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/optimizer/bfgs_utils.py#L47-L91", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:get_initial_state_args-f947df34a6@held-out", "question": "Returns a dictionary to populate the initial state of the search procedure.\n\n Performs an initial convergence check and the first evaluation of the\n objective function.\n\n Args:\n value_and_gradients_function: A Python callable that accepts a tensor and\n returns a tuple of two tensors: the objective function value and its\n derivative.\n initial_position: The starting point of the search procedure.\n grad_tolerance: The gradient tolerance for the procedure.\n control_inputs: Optional ops used to assert the validity of inputs, these\n are added as control dependencies to execute before the objective\n function is evaluated for the first time.\n\n Returns:\n An dictionary with values for the following keys:\n converged: True if the convergence check finds that the initial position\n is already an argmin of the objective function.\n failed: Initialized to False.\n num_objective_evaluations: Initialized to 1.\n position: Initialized to the initial position.\n objective_value: Initialized to the value of the objective function at\n the initial position.\n objective_gradient: Initialized to the gradient of the objective\n function at the initial position.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/mcmc/replica_exchange_mc.py#L316-L417", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:ReplicaExchangeMC.one_step-ad7066a5a7@held-out", "question": "Takes one step of the TransitionKernel.\n\n Args:\n current_state: `Tensor` or Python `list` of `Tensor`s representing the\n current state(s) of the Markov chain(s).\n previous_kernel_results: A (possibly nested) `tuple`, `namedtuple` or\n `list` of `Tensor`s representing internal calculations made within the\n previous call to this function (or as returned by `bootstrap_results`).\n\n Returns:\n next_state: `Tensor` or Python `list` of `Tensor`s representing the\n next state(s) of the Markov chain(s).\n kernel_results: A (possibly nested) `tuple`, `namedtuple` or `list` of\n `Tensor`s representing internal calculations made within this function.\n This inculdes replica states.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/mcmc/replica_exchange_mc.py#L519-L556", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:ReplicaExchangeMC.bootstrap_results-e150afa12c@held-out", "question": "Returns an object with the same type as returned by `one_step`.\n\n Args:\n init_state: `Tensor` or Python `list` of `Tensor`s representing the\n initial state(s) of the Markov chain(s).\n\n Returns:\n kernel_results: A (possibly nested) `tuple`, `namedtuple` or `list` of\n `Tensor`s representing internal calculations made within this function.\n This inculdes replica states.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/mcmc/transformed_kernel.py#L275-L347", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:TransformedTransitionKernel.bootstrap_results-e26fc18d0e@held-out", "question": "Returns an object with the same type as returned by `one_step`.\n\n Unlike other `TransitionKernel`s,\n `TransformedTransitionKernel.bootstrap_results` has the option of\n initializing the `TransformedTransitionKernelResults` from either an initial\n state, eg, requiring computing `bijector.inverse(init_state)`, or\n directly from `transformed_init_state`, i.e., a `Tensor` or list\n of `Tensor`s which is interpretted as the `bijector.inverse`\n transformed state.\n\n Args:\n init_state: `Tensor` or Python `list` of `Tensor`s representing the a\n state(s) of the Markov chain(s). Must specify `init_state` or\n `transformed_init_state` but not both.\n transformed_init_state: `Tensor` or Python `list` of `Tensor`s\n representing the a state(s) of the Markov chain(s). Must specify\n `init_state` or `transformed_init_state` but not both.\n\n Returns:\n kernel_results: A (possibly nested) `tuple`, `namedtuple` or `list` of\n `Tensor`s representing internal calculations made within this function.\n\n Raises:\n ValueError: if `inner_kernel` results doesn't contain the member\n \"target_log_prob\".\n\n #### Examples\n\n To use `transformed_init_state` in context of\n `tfp.mcmc.sample_chain`, you need to explicitly pass the\n `previous_kernel_results`, e.g.,\n\n ```python\n transformed_kernel = tfp.mcmc.TransformedTransitionKernel(...)\n init_state = ... # Doesnt matter.\n transformed_init_state = ... # Does matter.\n results, _ = tfp.mcmc.sample_chain(\n num_results=...,\n current_state=init_state,\n previous_kernel_results=transformed_kernel.bootstrap_results(\n transformed_init_state=transformed_init_state),\n kernel=transformed_kernel)\n ```", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/optimizer/linesearch/internal/hager_zhang_lib.py#L60-L174", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:secant2-3c08a536b1@held-out", "question": "Performs the secant square procedure of Hager Zhang.\n\n Given an interval that brackets a root, this procedure performs an update of\n both end points using two intermediate points generated using the secant\n interpolation. For details see the steps S1-S4 in [Hager and Zhang (2006)][2].\n\n The interval [a, b] must satisfy the opposite slope conditions described in\n the documentation for `update`.\n\n Args:\n value_and_gradients_function: A Python callable that accepts a real scalar\n tensor and returns an object that can be converted to a namedtuple.\n The namedtuple should have fields 'f' and 'df' that correspond to scalar\n tensors of real dtype containing the value of the function and its\n derivative at that point. The other namedtuple fields, if present,\n should be tensors or sequences (possibly nested) of tensors.\n In usual optimization application, this function would be generated by\n projecting the multivariate objective function along some specific\n direction. The direction is determined by some other procedure but should\n be a descent direction (i.e. the derivative of the projected univariate\n function must be negative at 0.).\n Alternatively, the function may represent the batching of `n` such line\n functions (e.g. projecting a single multivariate objective function along\n `n` distinct directions at once) accepting n points as input, i.e. a\n tensor of shape [n], and the fields 'f' and 'df' in the returned\n namedtuple should each be a tensor of shape [n], with the corresponding\n function values and derivatives at the input points.\n val_0: A namedtuple, as returned by value_and_gradients_function evaluated\n at `0.`.\n search_interval: A namedtuple describing the current search interval,\n must include the fields:\n - converged: Boolean `Tensor` of shape [n], indicating batch members\n where search has already converged. Interval for these batch members\n won't be modified.\n - failed: Boolean `Tensor` of shape [n], indicating batch members\n where search has already failed. Interval for these batch members\n wont be modified.\n - iterations: Scalar int32 `Tensor`. Number of line search iterations\n so far.\n - func_evals: Scalar int32 `Tensor`. Number of function evaluations\n so far.\n - left: A namedtuple, as returned by value_and_gradients_function,\n of the left end point of the current search interval.\n - right: A namedtuple, as returned by value_and_gradients_function,\n of the right end point of the current search interval.\n f_lim: Scalar `Tensor` of real dtype. The function value threshold for\n the approximate Wolfe conditions to be checked.\n sufficient_decrease_param: Positive scalar `Tensor` of real dtype.\n Bounded above by the curvature param. Corresponds to 'delta' in the\n terminology of [Hager and Zhang (2006)][2].\n curvature_param: Positive scalar `Tensor` of real dtype. Bounded above\n by `1.`. Corresponds to 'sigma' in the terminology of\n [Hager and Zhang (2006)][2].\n name: (Optional) Python str. The name prefixed to the ops created by this\n function. If not supplied, the default name 'secant2' is used.\n\n Returns:\n A namedtuple containing the following fields.\n active: A boolean `Tensor` of shape [n]. Used internally by the procedure\n to indicate batch members on which there is work left to do.\n converged: A boolean `Tensor` of shape [n]. Indicates whether a point\n satisfying the Wolfe conditions has been found. If this is True, the\n interval will be degenerate (i.e. `left` and `right` below will be\n identical).\n failed: A boolean `Tensor` of shape [n]. Indicates if invalid function or\n gradient values were encountered (i.e. infinity or NaNs).\n num_evals: A scalar int32 `Tensor`. The total number of function\n evaluations made.\n left: Return value of value_and_gradients_function at the updated left\n end point of the interval.\n right: Return value of value_and_gradients_function at the updated right\n end point of the interval.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/optimizer/linesearch/internal/hager_zhang_lib.py#L177-L238", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:_secant2_inner-859339ccc1@held-out", "question": "Helper function for secant square.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/optimizer/linesearch/internal/hager_zhang_lib.py#L426-L545", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:bracket-02222692a0@held-out", "question": "Brackets the minimum given an initial starting point.\n\n Applies the Hager Zhang bracketing algorithm to find an interval containing\n a region with points satisfying Wolfe conditions. Uses the supplied initial\n step size 'c', the right end point of the provided search interval, to find\n such an interval. The only condition on 'c' is that it should be positive.\n For more details see steps B0-B3 in [Hager and Zhang (2006)][2].\n\n Args:\n value_and_gradients_function: A Python callable that accepts a real scalar\n tensor and returns a namedtuple containing the value filed `f` of the\n function and its derivative value field `df` at that point.\n Alternatively, the function may representthe batching of `n` such line\n functions (e.g. projecting a single multivariate objective function along\n `n` distinct directions at once) accepting n points as input, i.e. a\n tensor of shape [n], and return a tuple of two tensors of shape [n], the\n function values and the corresponding derivatives at the input points.\n search_interval: A namedtuple describing the current search interval,\n must include the fields:\n - converged: Boolean `Tensor` of shape [n], indicating batch members\n where search has already converged. Interval for these batch members\n wont be modified.\n - failed: Boolean `Tensor` of shape [n], indicating batch members\n where search has already failed. Interval for these batch members\n wont be modified.\n - iterations: Scalar int32 `Tensor`. Number of line search iterations\n so far.\n - func_evals: Scalar int32 `Tensor`. Number of function evaluations\n so far.\n - left: A namedtuple, as returned by value_and_gradients_function\n evaluated at 0, the left end point of the current interval.\n - right: A namedtuple, as returned by value_and_gradients_function,\n of the right end point of the current interval (labelled 'c' above).\n f_lim: real `Tensor` of shape [n]. The function value threshold for\n the approximate Wolfe conditions to be checked for each batch member.\n max_iterations: Int32 scalar `Tensor`. The maximum number of iterations\n permitted. The limit applies equally to all batch members.\n expansion_param: Scalar positive `Tensor` of real dtype. Must be greater\n than `1.`. Used to expand the initial interval in case it does not bracket\n a minimum.\n\n Returns:\n A namedtuple with the following fields.\n iteration: An int32 scalar `Tensor`. The number of iterations performed.\n Bounded above by `max_iterations` parameter.\n stopped: A boolean `Tensor` of shape [n]. True for those batch members\n where the algorithm terminated before reaching `max_iterations`.\n failed: A boolean `Tensor` of shape [n]. True for those batch members\n where an error was encountered during bracketing.\n num_evals: An int32 scalar `Tensor`. The number of times the objective\n function was evaluated.\n left: Return value of value_and_gradients_function at the updated left\n end point of the interval found.\n right: Return value of value_and_gradients_function at the updated right\n end point of the interval found.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/mcmc/hmc.py#L556-L564", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:HamiltonianMonteCarlo.bootstrap_results-c9a39b434c@held-out", "question": "Creates initial `previous_kernel_results` using a supplied `state`.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/examples/latent_dirichlet_allocation_distributions.py#L225-L255", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:make_prior-8f5df07ea8@held-out", "question": "Create the prior distribution.\n\n Args:\n num_topics: Number of topics.\n initial_value: The starting value for the prior parameters.\n\n Returns:\n prior: A `callable` that returns a `tf.distribution.Distribution`\n instance, the prior distribution.\n prior_variables: A `list` of `Variable` objects, the trainable parameters\n of the prior.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/mcmc/sample.py#L81-L372", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:sample_chain-3feed45e52@held-out", "question": "Implements Markov chain Monte Carlo via repeated `TransitionKernel` steps.\n\n This function samples from an Markov chain at `current_state` and whose\n stationary distribution is governed by the supplied `TransitionKernel`\n instance (`kernel`).\n\n This function can sample from multiple chains, in parallel. (Whether or not\n there are multiple chains is dictated by the `kernel`.)\n\n The `current_state` can be represented as a single `Tensor` or a `list` of\n `Tensors` which collectively represent the current state.\n\n Since MCMC states are correlated, it is sometimes desirable to produce\n additional intermediate states, and then discard them, ending up with a set of\n states with decreased autocorrelation. See [Owen (2017)][1]. Such \"thinning\"\n is made possible by setting `num_steps_between_results > 0`. The chain then\n takes `num_steps_between_results` extra steps between the steps that make it\n into the results. The extra steps are never materialized (in calls to\n `sess.run`), and thus do not increase memory requirements.\n\n Warning: when setting a `seed` in the `kernel`, ensure that `sample_chain`'s\n `parallel_iterations=1`, otherwise results will not be reproducible.\n\n In addition to returning the chain state, this function supports tracing of\n auxiliary variables used by the kernel. The traced values are selected by\n specifying `trace_fn`. By default, all kernel results are traced but in the\n future the default will be changed to no results being traced, so plan\n accordingly. See below for some examples of this feature.\n\n Args:\n num_results: Integer number of Markov chain draws.\n current_state: `Tensor` or Python `list` of `Tensor`s representing the\n current state(s) of the Markov chain(s).\n previous_kernel_results: A `Tensor` or a nested collection of `Tensor`s\n representing internal calculations made within the previous call to this\n function (or as returned by `bootstrap_results`).\n kernel: An instance of `tfp.mcmc.TransitionKernel` which implements one step\n of the Markov chain.\n num_burnin_steps: Integer number of chain steps to take before starting to\n collect results.\n Default value: 0 (i.e., no burn-in).\n num_steps_between_results: Integer number of chain steps between collecting\n a result. Only one out of every `num_steps_between_samples + 1` steps is\n included in the returned results. The number of returned chain states is\n still equal to `num_results`. Default value: 0 (i.e., no thinning).\n trace_fn: A callable that takes in the current chain state and the previous\n kernel results and return a `Tensor` or a nested collection of `Tensor`s\n that is then traced along with the chain state.\n return_final_kernel_results: If `True`, then the final kernel results are\n returned alongside the chain state and the trace specified by the\n `trace_fn`.\n parallel_iterations: The number of iterations allowed to run in parallel. It\n must be a positive integer. See `tf.while_loop` for more details.\n name: Python `str` name prefixed to Ops created by this function.\n Default value: `None` (i.e., \"mcmc_sample_chain\").\n\n Returns:\n checkpointable_states_and_trace: if `return_final_kernel_results` is\n `True`. The return value is an instance of\n `CheckpointableStatesAndTrace`.\n all_states: if `return_final_kernel_results` is `False` and `trace_fn` is\n `None`. The return value is a `Tensor` or Python list of `Tensor`s\n representing the state(s) of the Markov chain(s) at each result step. Has\n same shape as input `current_state` but with a prepended\n `num_results`-size dimension.\n states_and_trace: if `return_final_kernel_results` is `False` and\n `trace_fn` is not `None`. The return value is an instance of\n `StatesAndTrace`.\n\n #### Examples\n\n ##### Sample from a diagonal-variance Gaussian.\n\n I.e.,\n\n ```none\n for i=1..n:\n x[i] ~ MultivariateNormal(loc=0, scale=diag(true_stddev)) # likelihood\n ```\n\n ```python\n import tensorflow as tf\n import tensorflow_probability as tfp\n tfd = tfp.distributions\n\n dims = 10\n true_stddev = np.sqrt(np.linspace(1., 3., dims))\n likelihood = tfd.MultivariateNormalDiag(loc=0., scale_diag=true_stddev)\n\n states = tfp.mcmc.sample_chain(\n num_results=1000,\n num_burnin_steps=500,\n current_state=tf.zeros(dims),\n kernel=tfp.mcmc.HamiltonianMonteCarlo(\n target_log_prob_fn=likelihood.log_prob,\n step_size=0.5,\n num_leapfrog_steps=2),\n trace_fn=None)\n\n sample_mean = tf.reduce_mean(states, axis=0)\n # ==> approx all zeros\n\n sample_stddev = tf.sqrt(tf.reduce_mean(\n tf.squared_difference(states, sample_mean),\n axis=0))\n # ==> approx equal true_stddev\n ```\n\n ##### Sampling from factor-analysis posteriors with known factors.\n\n I.e.,\n\n ```none\n # prior\n w ~ MultivariateNormal(loc=0, scale=eye(d))\n for i=1..n:\n # likelihood\n x[i] ~ Normal(loc=w^T F[i], scale=1)\n ```\n\n where `F` denotes factors.\n\n ```python\n import tensorflow as tf\n import tensorflow_probability as tfp\n tfd = tfp.distributions\n\n # Specify model.\n def make_prior(dims):\n return tfd.MultivariateNormalDiag(\n loc=tf.zeros(dims))\n\n def make_likelihood(weights, factors):\n return tfd.MultivariateNormalDiag(\n loc=tf.matmul(weights, factors, adjoint_b=True))\n\n def joint_log_prob(num_weights, factors, x, w):\n return (make_prior(num_weights).log_prob(w) +\n make_likelihood(w, factors).log_prob(x))\n\n def unnormalized_log_posterior(w):\n # Posterior is proportional to: `p(W, X=x | factors)`.\n return joint_log_prob(num_weights, factors, x, w)\n\n # Setup data.\n num_weights = 10 # == d\n num_factors = 40 # == n\n num_chains = 100\n\n weights = make_prior(num_weights).sample(1)\n factors = tf.random_normal([num_factors, num_weights])\n x = make_likelihood(weights, factors).sample()\n\n # Sample from Hamiltonian Monte Carlo Markov Chain.\n\n # Get `num_results` samples from `num_chains` independent chains.\n chains_states, kernels_results = tfp.mcmc.sample_chain(\n num_results=1000,\n num_burnin_steps=500,\n current_state=tf.zeros([num_chains, num_weights], name='init_weights'),\n kernel=tfp.mcmc.HamiltonianMonteCarlo(\n target_log_prob_fn=unnormalized_log_posterior,\n step_size=0.1,\n num_leapfrog_steps=2))\n\n # Compute sample stats.\n sample_mean = tf.reduce_mean(chains_states, axis=[0, 1])\n # ==> approx equal to weights\n\n sample_var = tf.reduce_mean(\n tf.squared_difference(chains_states, sample_mean),\n axis=[0, 1])\n # ==> less than 1\n ```\n\n ##### Custom tracing functions.\n\n ```python\n import tensorflow as tf\n import tensorflow_probability as tfp\n tfd = tfp.distributions\n\n likelihood = tfd.Normal(loc=0., scale=1.)\n\n def sample_chain(trace_fn):\n return tfp.mcmc.sample_chain(\n num_results=1000,\n num_burnin_steps=500,\n current_state=0.,\n kernel=tfp.mcmc.HamiltonianMonteCarlo(\n target_log_prob_fn=likelihood.log_prob,\n step_size=0.5,\n num_leapfrog_steps=2),\n trace_fn=trace_fn)\n\n def trace_log_accept_ratio(states, previous_kernel_results):\n return previous_kernel_results.log_accept_ratio\n\n def trace_everything(states, previous_kernel_results):\n return previous_kernel_results\n\n _, log_accept_ratio = sample_chain(trace_fn=trace_log_accept_ratio)\n _, kernel_results = sample_chain(trace_fn=trace_everything)\n\n acceptance_prob = tf.exp(tf.minimum(log_accept_ratio_, 0.))\n # Equivalent to, but more efficient than:\n acceptance_prob = tf.exp(tf.minimum(kernel_results.log_accept_ratio_, 0.))\n ```\n\n #### References\n\n [1]: Art B. Owen. Statistically efficient thinning of a Markov chain sampler.\n _Technical Report_, 2017.\n http://statweb.stanford.edu/~owen/reports/bestthinning.pdf", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/stats/quantiles.py#L39-L155", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:count_integers-e2686c4547@held-out", "question": "Counts the number of occurrences of each value in an integer array `arr`.\n\n Works like `tf.math.bincount`, but provides an `axis` kwarg that specifies\n dimensions to reduce over. With\n `~axis = [i for i in range(arr.ndim) if i not in axis]`,\n this function returns a `Tensor` of shape `[K] + arr.shape[~axis]`.\n\n If `minlength` and `maxlength` are not given, `K = tf.reduce_max(arr) + 1`\n if `arr` is non-empty, and 0 otherwise.\n If `weights` are non-None, then index `i` of the output stores the sum of the\n value in `weights` at each index where the corresponding value in `arr` is\n `i`.\n\n Args:\n arr: An `int32` `Tensor` of non-negative values.\n weights: If non-None, must be the same shape as arr. For each value in\n `arr`, the bin will be incremented by the corresponding weight instead of\n 1.\n minlength: If given, ensures the output has length at least `minlength`,\n padding with zeros at the end if necessary.\n maxlength: If given, skips values in `arr` that are equal or greater than\n `maxlength`, ensuring that the output has length at most `maxlength`.\n axis: A `0-D` or `1-D` `int32` `Tensor` (with static values) designating\n dimensions in `arr` to reduce over.\n `Default value:` `None`, meaning reduce over all dimensions.\n dtype: If `weights` is None, determines the type of the output bins.\n name: A name scope for the associated operations (optional).\n\n Returns:\n A vector with the same dtype as `weights` or the given `dtype`. The bin\n values.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/stats/quantiles.py#L847-L884", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:_move_dims_to_flat_end-16a5a2cae0@held-out", "question": "Move dims corresponding to `axis` in `x` to the end, then flatten.\n\n Args:\n x: `Tensor` with shape `[B0,B1,...,Bb]`.\n axis: Python list of indices into dimensions of `x`.\n x_ndims: Python integer holding number of dimensions in `x`.\n right_end: Python bool. Whether to move dims to the right end (else left).\n\n Returns:\n `Tensor` with value from `x` and dims in `axis` moved to end into one single\n dimension.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/vi/csiszar_divergence.py#L462-L503", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:t_power-1cbf829376@held-out", "question": "The T-Power Csiszar-function in log-space.\n\n A Csiszar-function is a member of,\n\n ```none\n F = { f:R_+ to R : f convex }.\n ```\n\n When `self_normalized = True` the T-Power Csiszar-function is:\n\n ```none\n f(u) = s [ u**t - 1 - t(u - 1) ]\n s = { -1 0 < t < 1\n { +1 otherwise\n ```\n\n When `self_normalized = False` the `- t(u - 1)` term is omitted.\n\n This is similar to the `amari_alpha` Csiszar-function, with the associated\n divergence being the same up to factors depending only on `t`.\n\n Args:\n logu: `float`-like `Tensor` representing `log(u)` from above.\n t: `Tensor` of same `dtype` as `logu` and broadcastable shape.\n self_normalized: Python `bool` indicating whether `f'(u=1)=0`.\n name: Python `str` name prefixed to Ops created by this function.\n\n Returns:\n t_power_of_u: `float`-like `Tensor` of the Csiszar-function evaluated\n at `u = exp(logu)`.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/math/interpolation.py#L240-L368", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:interp_regular_1d_grid-7d8b486f5c@held-out", "question": "Linear `1-D` interpolation on a regular (constant spacing) grid.\n\n Given reference values, this function computes a piecewise linear interpolant\n and evaluates it on a new set of `x` values.\n\n The interpolant is built from `C` reference values indexed by one dimension\n of `y_ref` (specified by the `axis` kwarg).\n\n If `y_ref` is a vector, then each value `y_ref[i]` is considered to be equal\n to `f(x_ref[i])`, for `C` (implicitly defined) reference values between\n `x_ref_min` and `x_ref_max`:\n\n ```none\n x_ref[i] = x_ref_min + i * (x_ref_max - x_ref_min) / (C - 1),\n i = 0, ..., C - 1.\n ```\n\n If `rank(y_ref) > 1`, then dimension `axis` indexes `C` reference values of\n a shape `y_ref.shape[:axis] + y_ref.shape[axis + 1:]` `Tensor`.\n\n If `rank(x) > 1`, then the output is obtained by effectively flattening `x`,\n interpolating along `axis`, then expanding the result to shape\n `y_ref.shape[:axis] + x.shape + y_ref.shape[axis + 1:]`.\n\n These shape semantics are equivalent to `scipy.interpolate.interp1d`.\n\n Args:\n x: Numeric `Tensor` The x-coordinates of the interpolated output values.\n x_ref_min: Scalar `Tensor` of same `dtype` as `x`. The minimum value of\n the (implicitly defined) reference `x_ref`.\n x_ref_max: Scalar `Tensor` of same `dtype` as `x`. The maximum value of\n the (implicitly defined) reference `x_ref`.\n y_ref: `N-D` `Tensor` (`N > 0`) of same `dtype` as `x`. The reference\n output values.\n axis: Scalar `Tensor` designating the dimension of `y_ref` that indexes\n values of the interpolation table.\n Default value: `-1`, the rightmost axis.\n fill_value: Determines what values output should take for `x` values that\n are below `x_ref_min` or above `x_ref_max`. `Tensor` or one of the strings\n \"constant_extension\" ==> Extend as constant function. \"extrapolate\" ==>\n Extrapolate in a linear fashion.\n Default value: `\"constant_extension\"`\n fill_value_below: Optional override of `fill_value` for `x < x_ref_min`.\n fill_value_above: Optional override of `fill_value` for `x > x_ref_max`.\n grid_regularizing_transform: Optional transformation `g` which regularizes\n the implied spacing of the x reference points. In other words, if\n provided, we assume `g(x_ref_i)` is a regular grid between `g(x_ref_min)`\n and `g(x_ref_max)`.\n name: A name to prepend to created ops.\n Default value: `\"interp_regular_1d_grid\"`.\n\n Returns:\n y_interp: Interpolation between members of `y_ref`, at points `x`.\n `Tensor` of same `dtype` as `x`, and shape\n `y.shape[:axis] + x.shape + y.shape[axis + 1:]`\n\n Raises:\n ValueError: If `fill_value` is not an allowed string.\n ValueError: If `axis` is not a scalar.\n\n #### Examples\n\n Interpolate a function of one variable:\n\n ```python\n y_ref = tf.exp(tf.linspace(start=0., stop=10., num=200))\n\n interp_regular_1d_grid(\n x=[6.0, 0.5, 3.3], x_ref_min=0., x_ref_max=1., y_ref=y_ref)\n ==> approx [exp(6.0), exp(0.5), exp(3.3)]\n ```\n\n Interpolate a matrix-valued function of one variable:\n\n ```python\n mat_0 = [[1., 0.], [0., 1.]]\n mat_1 = [[0., -1], [1, 0]]\n y_ref = [mat_0, mat_1]\n\n # Get three output matrices at once.\n tfp.math.interp_regular_1d_grid(\n x=[0., 0.5, 1.], x_ref_min=0., x_ref_max=1., y_ref=y_ref, axis=0)\n ==> [mat_0, 0.5 * mat_0 + 0.5 * mat_1, mat_1]\n ```\n\n Interpolate a scalar valued function, and get a matrix of results:\n\n ```python\n y_ref = tf.exp(tf.linspace(start=0., stop=10., num=200))\n x = [[1.1, 1.2], [2.1, 2.2]]\n tfp.math.interp_regular_1d_grid(x, x_ref_min=0., x_ref_max=10., y_ref=y_ref)\n ==> tf.exp(x)\n ```\n\n Interpolate a function of one variable on a log-spaced grid:\n\n ```python\n x_ref = tf.exp(tf.linspace(tf.log(1.), tf.log(100000.), num_pts))\n y_ref = tf.log(x_ref + x_ref**2)\n\n interp_regular_1d_grid(x=[1.1, 2.2], x_ref_min=1., x_ref_max=100000., y_ref,\n grid_regularizing_transform=tf.log)\n ==> [tf.log(1.1 + 1.1**2), tf.log(2.2 + 2.2**2)]\n ```", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/math/interpolation.py#L893-L927", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:_make_expand_x_fn_for_batch_interpolation-f09daad40e@held-out", "question": "Make func to expand left/right (of axis) dims of tensors shaped like x.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/distributions/empirical.py#L35-L49", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:_broadcast_event_and_samples-8abb9f5729@held-out", "question": "Broadcasts the event or samples.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/mcmc/metropolis_hastings.py#L165-L245", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:MetropolisHastings.one_step-dba7080dfd@held-out", "question": "Takes one step of the TransitionKernel.\n\n Args:\n current_state: `Tensor` or Python `list` of `Tensor`s representing the\n current state(s) of the Markov chain(s).\n previous_kernel_results: A (possibly nested) `tuple`, `namedtuple` or\n `list` of `Tensor`s representing internal calculations made within the\n previous call to this function (or as returned by `bootstrap_results`).\n\n Returns:\n next_state: `Tensor` or Python `list` of `Tensor`s representing the\n next state(s) of the Markov chain(s).\n kernel_results: A (possibly nested) `tuple`, `namedtuple` or `list` of\n `Tensor`s representing internal calculations made within this function.\n\n Raises:\n ValueError: if `inner_kernel` results doesn't contain the member\n \"target_log_prob\".", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/optimizer/bfgs.py#L436-L473", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:_mul_right-ac1dbf7722@held-out", "question": "Computes the product of a matrix with a vector on the right.\n\n Note this supports dynamic shapes and batched computation.\n\n Examples:\n\n M = tf.reshape(tf.range(6), shape=(3, 2))\n # => [[0, 1],\n # [2, 3],\n # [4, 5]]\n v = tf.constant([1, 2]) # Shape: (2,)\n _mul_right(M, v)\n # => [ 2, 8, 14] # Shape: (3,)\n\n M = tf.reshape(tf.range(30), shape=(2, 3, 5))\n # => [[[ 0, 1, 2, 3, 4],\n # [ 5, 6, 7, 8, 9],\n # [10, 11, 12, 13, 14]],\n #\n # [[15, 16, 17, 18, 19],\n # [20, 21, 22, 23, 24],\n # [25, 26, 27, 28, 29]]]\n v = tf.reshape(tf.range(10), shape=(2, 5))\n # => [[0, 1, 2, 3, 4],\n # [5, 6, 7, 8, 9]]\n _mul_right(M, v)\n # => [[ 30, 80, 130],\n # [605, 780, 955]] # Shape: (2, 3)\n\n Args:\n mat: A `tf.Tensor` of shape `[..., n, m]`.\n vec: A `tf.Tensor` of shape `[..., m]`.\n\n Returns:\n A tensor of shape `[..., n]` with matching batch dimensions.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/optimizer/lbfgs.py#L403-L466", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:_queue_push-4999c83eb9@held-out", "question": "Conditionally push new vectors into a batch of first-in-first-out queues.\n\n The `queue` of shape `[k, ..., n]` can be thought of as a batch of queues,\n each holding `k` n-D vectors; while `new_vecs` of shape `[..., n]` is a\n fresh new batch of n-D vectors. The `should_update` batch of Boolean scalars,\n i.e. shape `[...]`, indicates batch members whose corresponding n-D vector in\n `new_vecs` should be added at the back of its queue, pushing out the\n corresponding n-D vector from the front. Batch members in `new_vecs` for\n which `should_update` is False are ignored.\n\n Note: the choice of placing `k` at the dimension 0 of the queue is\n constrained by the L-BFGS two-loop algorithm above. The algorithm uses\n tf.scan to iterate over the `k` correction pairs simulatneously across all\n batches, and tf.scan itself can only iterate over dimension 0.\n\n For example:\n\n ```python\n k, b, n = (3, 2, 5)\n queue = tf.reshape(tf.range(30), (k, b, n))\n # => [[[ 0, 1, 2, 3, 4],\n # [ 5, 6, 7, 8, 9]],\n #\n # [[10, 11, 12, 13, 14],\n # [15, 16, 17, 18, 19]],\n #\n # [[20, 21, 22, 23, 24],\n # [25, 26, 27, 28, 29]]]\n\n element = tf.reshape(tf.range(30, 40), (b, n))\n # => [[30, 31, 32, 33, 34],\n [35, 36, 37, 38, 39]]\n\n should_update = tf.constant([True, False]) # Shape: (b,)\n\n _queue_add(should_update, queue, element)\n # => [[[10, 11, 12, 13, 14],\n # [ 5, 6, 7, 8, 9]],\n #\n # [[20, 21, 22, 23, 24],\n # [15, 16, 17, 18, 19]],\n #\n # [[30, 31, 32, 33, 34],\n # [25, 26, 27, 28, 29]]]\n ```\n\n Args:\n queue: A `tf.Tensor` of shape `[k, ..., n]`; a batch of queues each with\n `k` n-D vectors.\n should_update: A Boolean `tf.Tensor` of shape `[...]` indicating batch\n members where new vectors should be added to their queues.\n new_vecs: A `tf.Tensor` of shape `[..., n]`; a batch of n-D vectors to add\n at the end of their respective queues, pushing out the first element from\n each.\n\n Returns:\n A new `tf.Tensor` of shape `[k, ..., n]`.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/distributions/internal/correlation_matrix_volumes_lib.py#L172-L216", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:correlation_matrix_volume_rejection_samples-ec4c7a7927@held-out", "question": "Returns rejection samples from trying to get good correlation matrices.\n\n The proposal being rejected from is the uniform distribution on\n \"correlation-like\" matrices. We say a matrix is \"correlation-like\"\n if it is a symmetric square matrix with all entries between -1 and 1\n (inclusive) and 1s on the main diagonal. Of these, the ones that\n are positive semi-definite are exactly the correlation matrices.\n\n The rejection algorithm, then, is to sample a `Tensor` of\n `sample_shape` correlation-like matrices of dimensions `dim` by\n `dim`, and check each one for (i) being a correlation matrix (i.e.,\n PSD), and (ii) having determinant at least the corresponding entry\n of `det_bounds`.\n\n Args:\n det_bounds: A `Tensor` of lower bounds on the determinants of\n acceptable matrices. The shape must broadcast with `sample_shape`.\n dim: A Python `int` dimension of correlation matrices to sample.\n sample_shape: Python `tuple` of `int` shape of the samples to\n compute, excluding the two matrix dimensions.\n dtype: The `dtype` in which to do the computation.\n seed: Random seed.\n\n Returns:\n weights: A `Tensor` of shape `sample_shape`. Each entry is 0 if the\n corresponding matrix was not a correlation matrix, or had too\n small of a determinant. Otherwise, the entry is the\n multiplicative inverse of the density of proposing that matrix\n uniformly, i.e., the volume of the set of `dim` by `dim`\n correlation-like matrices.\n volume: The volume of the set of `dim` by `dim` correlation-like\n matrices.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/distributions/von_mises.py#L450-L582", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:random_von_mises-5c9f5a7209@held-out", "question": "Samples from the standardized von Mises distribution.\n\n The distribution is vonMises(loc=0, concentration=concentration), so the mean\n is zero.\n The location can then be changed by adding it to the samples.\n\n The sampling algorithm is rejection sampling with wrapped Cauchy proposal [1].\n The samples are pathwise differentiable using the approach of [2].\n\n Arguments:\n shape: The output sample shape.\n concentration: The concentration parameter of the von Mises distribution.\n dtype: The data type of concentration and the outputs.\n seed: (optional) The random seed.\n\n Returns:\n Differentiable samples of standardized von Mises.\n\n References:\n [1] Luc Devroye \"Non-Uniform Random Variate Generation\", Springer-Verlag,\n 1986; Chapter 9, p. 473-476.\n http://www.nrbook.com/devroye/Devroye_files/chapter_nine.pdf\n + corrections http://www.nrbook.com/devroye/Devroye_files/errors.pdf\n [2] Michael Figurnov, Shakir Mohamed, Andriy Mnih. \"Implicit\n Reparameterization Gradients\", 2018.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/optimizer/differential_evolution.py#L214-L456", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:minimize-83bd33099f@held-out", "question": "Applies the Differential evolution algorithm to minimize a function.\n\n Differential Evolution is an evolutionary optimization algorithm which works\n on a set of candidate solutions called the population. It iteratively\n improves the population by applying genetic operators of mutation and\n recombination. The objective function `f` supplies the fitness of each\n candidate. A candidate `s_1` is considered better than `s_2` if\n `f(s_1) < f(s_2)`.\n\n This method allows the user to either specify an initial population or a\n single candidate solution. If a single solution is specified, a population\n of the specified size is initialized by adding independent normal noise\n to the candidate solution.\n\n The implementation also supports a multi-part specification of the state. For\n example, consider the objective function:\n\n ```python\n # x is a tensor of shape [n, m] while y is of shape [n].\n def objective(x, y):\n return tf.math.reduce_sum(x ** 2, axis=-1) + y ** 2\n ```\n The state in this case is specified by two input tensors `x` and `y`. To\n apply the algorithm to this objective function, one would need to specify\n either an initial population as a list of two tensors of shapes\n `[population_size, k]` and `[population_size]`. The following code shows the\n complete example:\n\n ```python\n population_size = 40\n # With an initial population and a multi-part state.\n initial_population = (tf.random.normal([population_size]),\n tf.random.normal([population_size]))\n def easom_fn(x, y):\n return -(tf.math.cos(x) * tf.math.cos(y) *\n tf.math.exp(-(x-np.pi)**2 - (y-np.pi)**2))\n\n optim_results = tfp.optimizers.differential_evolution_minimize(\n easom_fn,\n initial_population=initial_population,\n seed=43210)\n\n print (optim_results.converged)\n print (optim_results.position) # Should be (close to) [pi, pi].\n print (optim_results.objective_value) # Should be -1.\n\n\n # With a single starting point\n initial_position = (tf.constant(1.0), tf.constant(1.0))\n\n optim_results = tfp.optimizers.differential_evolution_minimize(\n easom_fn,\n initial_position=initial_position,\n population_size=40,\n population_stddev=2.0,\n seed=43210)\n ```\n\n Args:\n objective_function: A Python callable that accepts a batch of possible\n solutions and returns the values of the objective function at those\n arguments as a rank 1 real `Tensor`. This specifies the function to be\n minimized. The input to this callable may be either a single `Tensor`\n or a Python `list` of `Tensor`s. The signature must match the format of\n the argument `population`. (i.e. objective_function(*population) must\n return the value of the function to be minimized).\n initial_population: A real `Tensor` or Python list of `Tensor`s.\n If a list, each `Tensor` must be of rank at least 1 and with a common\n first dimension. The first dimension indexes into the candidate solutions\n while the rest of the dimensions (if any) index into an individual\n solution. The size of the population must be at least 4. This is a\n requirement of the DE algorithm.\n initial_position: A real `Tensor` of any shape. The seed solution used\n to initialize the population of solutions. If this parameter is specified\n then `initial_population` must not be specified.\n population_size: A positive scalar int32 `Tensor` greater than 4. The\n size of the population to evolve. This parameter is ignored if\n `initial_population` is specified.\n Default value: 50.\n population_stddev: A positive scalar real `Tensor` of the same dtype\n as `initial_position`. This parameter is ignored if `initial_population`\n is specified. Used to generate the population from the `initial_position`\n by adding random normal noise with zero mean and the specified standard\n deviation.\n Default value: 1.0\n max_iterations: Positive scalar int32 `Tensor`. The maximum number of\n generations to evolve the population for.\n Default value: 100\n func_tolerance: Scalar `Tensor` of the same dtype as the output of the\n `objective_function`. The algorithm stops if the absolute difference\n between the largest and the smallest objective function value in the\n population is below this number.\n Default value: 0\n position_tolerance: Scalar `Tensor` of the same real dtype as\n `initial_position` or `initial_population`. The algorithm terminates if\n the largest absolute difference between the coordinates of the population\n members is below this threshold.\n Default value: 1e-8\n differential_weight: Real scalar `Tensor`. Must be positive and less than\n 2.0. The parameter controlling the strength of mutation in the algorithm.\n Default value: 0.5\n crossover_prob: Real scalar `Tensor`. Must be between 0 and 1. The\n probability of recombination per site.\n Default value: 0.9\n seed: `int` or None. The random seed for this `Op`. If `None`, no seed is\n applied.\n Default value: None.\n name: (Optional) Python str. The name prefixed to the ops created by this\n function. If not supplied, the default name\n 'differential_evolution_minimize' is used.\n Default value: None\n\n Returns:\n optimizer_results: An object containing the following attributes:\n converged: Scalar boolean `Tensor` indicating whether the minimum was\n found within the specified tolerances.\n num_objective_evaluations: The total number of objective\n evaluations performed.\n position: A `Tensor` containing the best point found during the search.\n If the search converged, then this value is the argmin of the\n objective function within the specified tolerances.\n objective_value: A `Tensor` containing the value of the objective\n function at the `position`. If the search\n converged, then this is the (local) minimum of\n the objective function.\n final_population: The final state of the population.\n final_objective_values: The objective function evaluated at the\n final population.\n initial_population: The starting population.\n initial_objective_values: The objective function evaluated at the\n initial population.\n num_iterations: The number of iterations of the main algorithm body.\n\n Raises:\n ValueError: If neither the initial population, nor the initial position\n are specified or if both are specified.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/optimizer/differential_evolution.py#L674-L709", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:_get_mutants-7c3176d91a@held-out", "question": "Computes the mutatated vectors for each population member.\n\n Args:\n population: Python `list` of `Tensor`s representing the\n current population vectors. Each `Tensor` must be of the same real dtype.\n The first dimension of each `Tensor` indexes individual\n population members. For example, if the population is a list with a\n single `Tensor` of shape [n, m1, m2], then `n` is the population size and\n the shape of an individual solution is [m1, m2].\n If there is more than one element in the population, then each `Tensor`\n in the list should have the first axis of the same size.\n population_size: Scalar integer `Tensor`. The size of the population.\n mixing_indices: `Tensor` of integral dtype and shape [n, 3] where `n` is the\n number of members in the population. Each element of the `Tensor` must be\n a valid index into the first dimension of the population (i.e range\n between `0` and `n-1` inclusive).\n differential_weight: Real scalar `Tensor`. Must be positive and less than\n 2.0. The parameter controlling the strength of mutation.\n\n Returns:\n mutants: `Tensor` or Python `list` of `Tensor`s of the same shape and dtype\n as the input population. The mutated vectors.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/examples/grammar_vae.py#L137-L164", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:SmilesGrammar.convert_to_string-33bf21d9cc@held-out", "question": "Converts a sequence of productions into a string of terminal symbols.\n\n Args:\n productions: Tensor of shape [1, num_productions, num_production_rules].\n Slices along the `num_productions` dimension represent one-hot vectors.\n\n Returns:\n str that concatenates all terminal symbols from `productions`.\n\n Raises:\n ValueError: If the first production rule does not begin with\n `self.start_symbol`.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/math/linalg.py#L48-L81", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:matrix_rank-bbd2fd8d3a@held-out", "question": "Compute the matrix rank; the number of non-zero SVD singular values.\n\n Arguments:\n a: (Batch of) `float`-like matrix-shaped `Tensor`(s) which are to be\n pseudo-inverted.\n tol: Threshold below which the singular value is counted as \"zero\".\n Default value: `None` (i.e., `eps * max(rows, cols) * max(singular_val)`).\n validate_args: When `True`, additional assertions might be embedded in the\n graph.\n Default value: `False` (i.e., no graph assertions are added).\n name: Python `str` prefixed to ops created by this function.\n Default value: \"matrix_rank\".\n\n Returns:\n matrix_rank: (Batch of) `int32` scalars representing the number of non-zero\n singular values.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/math/linalg.py#L738-L788", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:sparse_or_dense_matmul-e03d7fbbbf@held-out", "question": "Returns (batched) matmul of a SparseTensor (or Tensor) with a Tensor.\n\n Args:\n sparse_or_dense_a: `SparseTensor` or `Tensor` representing a (batch of)\n matrices.\n dense_b: `Tensor` representing a (batch of) matrices, with the same batch\n shape as `sparse_or_dense_a`. The shape must be compatible with the shape\n of `sparse_or_dense_a` and kwargs.\n validate_args: When `True`, additional assertions might be embedded in the\n graph.\n Default value: `False` (i.e., no graph assertions are added).\n name: Python `str` prefixed to ops created by this function.\n Default value: \"sparse_or_dense_matmul\".\n **kwargs: Keyword arguments to `tf.sparse_tensor_dense_matmul` or\n `tf.matmul`.\n\n Returns:\n product: A dense (batch of) matrix-shaped Tensor of the same batch shape and\n dtype as `sparse_or_dense_a` and `dense_b`. If `sparse_or_dense_a` or\n `dense_b` is adjointed through `kwargs` then the shape is adjusted\n accordingly.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/math/linalg.py#L837-L871", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:_sparse_tensor_dense_matmul-2a5fdd4746@held-out", "question": "Returns (batched) matmul of a SparseTensor with a Tensor.\n\n Args:\n sp_a: `SparseTensor` representing a (batch of) matrices.\n b: `Tensor` representing a (batch of) matrices, with the same batch shape of\n `sp_a`. The shape must be compatible with the shape of `sp_a` and kwargs.\n **kwargs: Keyword arguments to `tf.sparse_tensor_dense_matmul`.\n\n Returns:\n product: A dense (batch of) matrix-shaped Tensor of the same batch shape and\n dtype as `sp_a` and `b`. If `sp_a` or `b` is adjointed through `kwargs` then\n the shape is adjusted accordingly.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/glm/proximal_hessian.py#L41-L107", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:_grad_neg_log_likelihood_and_fim-99ec4b673f@held-out", "question": "Computes the neg-log-likelihood gradient and Fisher information for a GLM.\n\n Note that Fisher information is related to the Hessian of the log-likelihood\n by the equation\n\n ```none\n FisherInfo = E[Hessian with respect to model_coefficients of -LogLikelihood(\n Y | model_matrix, model_coefficients)]\n ```\n\n where `LogLikelihood` is the log-likelihood of a generalized linear model\n parameterized by `model_matrix` and `model_coefficients`, and the expectation\n is taken over Y, distributed according to the same GLM with the same parameter\n values.\n\n Args:\n model_matrix: (Batch of) matrix-shaped, `float` `Tensor` or `SparseTensor`\n where each row represents a sample's features. Has shape `[N, n]` where\n `N` is the number of data samples and `n` is the number of features per\n sample.\n linear_response: (Batch of) vector-shaped `Tensor` with the same dtype as\n `model_matrix`, equal to `model_matix @ model_coefficients` where\n `model_coefficients` are the coefficients of the linear component of the\n GLM.\n response: (Batch of) vector-shaped `Tensor` with the same dtype as\n `model_matrix` where each element represents a sample's observed response\n (to the corresponding row of features).\n model: `tfp.glm.ExponentialFamily`-like instance, which specifies the link\n function and distribution of the GLM, and thus characterizes the negative\n log-likelihood. Must have sufficient statistic equal to the response, that\n is, `T(y) = y`.\n\n Returns:\n grad_neg_log_likelihood: (Batch of) vector-shaped `Tensor` with the same\n shape and dtype as a single row of `model_matrix`, representing the\n gradient of the negative log likelihood of `response` given linear\n response `linear_response`.\n fim_middle: (Batch of) vector-shaped `Tensor` with the same shape and dtype\n as a single column of `model_matrix`, satisfying the equation\n `Fisher information =\n Transpose(model_matrix)\n @ diag(fim_middle)\n @ model_matrix`.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/bijectors/masked_autoregressive.py#L306-L320", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:_gen_slices-ab7c3f315b@held-out", "question": "Generate the slices for building an autoregressive mask.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/bijectors/masked_autoregressive.py#L903-L954", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:_create_degrees-40d0c285e7@held-out", "question": "Returns a list of degree vectors, one for each input and hidden layer.\n\n A unit with degree d can only receive input from units with degree < d. Output\n units always have the same degree as their associated input unit.\n\n Args:\n input_size: Number of inputs.\n hidden_units: list with the number of hidden units per layer. It does not\n include the output layer. Each hidden unit size must be at least the size\n of length (otherwise autoregressivity is not possible).\n input_order: Order of degrees to the input units: 'random', 'left-to-right',\n 'right-to-left', or an array of an explicit order. For example,\n 'left-to-right' builds an autoregressive model\n p(x) = p(x1) p(x2 | x1) ... p(xD | x<D).\n hidden_degrees: Method for assigning degrees to the hidden units:\n 'equal', 'random'. If 'equal', hidden units in each layer are allocated\n equally (up to a remainder term) to each degree. Default: 'equal'.\n\n Raises:\n ValueError: invalid input order.\n ValueError: invalid hidden degrees.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/distributions/multinomial.py#L285-L355", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:draw_sample-36dace467d@held-out", "question": "Sample a multinomial.\n\n The batch shape is given by broadcasting num_trials with\n remove_last_dimension(logits).\n\n Args:\n num_samples: Python int or singleton integer Tensor: number of multinomial\n samples to draw.\n num_classes: Python int or singleton integer Tensor: number of classes.\n logits: Floating Tensor with last dimension k, of (unnormalized) logit\n probabilities per class.\n num_trials: Tensor of number of categorical trials each multinomial consists\n of. num_trials[..., tf.newaxis] must broadcast with logits.\n dtype: dtype at which to emit samples.\n seed: Random seed.\n\n Returns:\n samples: Tensor of given dtype and shape [n] + batch_shape + [k].", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/sts/regression.py#L474-L486", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:SparseLinearRegression.params_to_weights-d1faac0d3c@held-out", "question": "Build regression weights from model parameters.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/distributions/joint_distribution_named.py#L245-L267", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tensorflow-probability:_prob_chain_rule_flatten-0c039d6f65@held-out", "question": "Creates lists of callables suitable for JDSeq.", "scope": {"holder": "tensorflow-probability", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/intel-analytics/BigDL/blob/e9c19788285986ab789a2e2998f9a85d7524779f/pyspark/bigdl/optim/optimizer.py#L760-L766", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:intel-analytics-BigDL:BaseOptimizer.optimize-213797fc05@held-out", "question": "Do an optimization.", "scope": {"holder": "intel-analytics-BigDL", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/intel-analytics/BigDL/blob/e9c19788285986ab789a2e2998f9a85d7524779f/pyspark/bigdl/nn/keras/topology.py#L238-L246", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:intel-analytics-BigDL:Model.from_jvalue-dfb52cad08@held-out", "question": "Create a Python Model base on the given java value\n :param jvalue: Java object create by Py4j\n :return: A Python Model", "scope": {"holder": "intel-analytics-BigDL", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/intel-analytics/BigDL/blob/e9c19788285986ab789a2e2998f9a85d7524779f/pyspark/bigdl/util/common.py#L268-L275", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:intel-analytics-BigDL:JTensor.to_ndarray-cbbf8e3213@held-out", "question": "Transfer JTensor to ndarray.\n As SparseTensor may generate an very big ndarray, so we don't support this function for SparseTensor.\n :return: a ndarray", "scope": {"holder": "intel-analytics-BigDL", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/intel-analytics/BigDL/blob/e9c19788285986ab789a2e2998f9a85d7524779f/pyspark/bigdl/transform/vision/image.py#L130-L134", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:intel-analytics-BigDL:ImageFrame.read_parquet-88db6f0ebc@held-out", "question": "Read parquet file as DistributedImageFrame", "scope": {"holder": "intel-analytics-BigDL", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/intel-analytics/BigDL/blob/e9c19788285986ab789a2e2998f9a85d7524779f/pyspark/bigdl/examples/keras/mnist_cnn.py#L34-L48", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:intel-analytics-BigDL:get_mnist-1e681da5f4@held-out", "question": "Download or load MNIST dataset to/from the specified path.\n Normalize and transform input data into an RDD of Sample", "scope": {"holder": "intel-analytics-BigDL", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/intel-analytics/BigDL/blob/e9c19788285986ab789a2e2998f9a85d7524779f/pyspark/bigdl/examples/keras/mnist_cnn.py#L51-L73", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:intel-analytics-BigDL:build_keras_model-0ab347a310@held-out", "question": "Define a convnet model in Keras 1.2.2", "scope": {"holder": "intel-analytics-BigDL", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/intel-analytics/BigDL/blob/e9c19788285986ab789a2e2998f9a85d7524779f/pyspark/bigdl/nn/layer.py#L68-L76", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:intel-analytics-BigDL:SharedStaticUtils.load-4964f44d6d@held-out", "question": "Load a pre-trained Bigdl model.\n\n :param path: The path containing the pre-trained model.\n :return: A pre-trained model.", "scope": {"holder": "intel-analytics-BigDL", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/intel-analytics/BigDL/blob/e9c19788285986ab789a2e2998f9a85d7524779f/pyspark/bigdl/nn/layer.py#L263-L284", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:intel-analytics-BigDL:Layer.backward-07b047d571@held-out", "question": "NB: It's for debug only, please use optimizer.optimize() in production.\n Performs a back-propagation step through the module, with respect to the given input. In\n general this method makes the assumption forward(input) has been called before, with the same\n input. This is necessary for optimization reasons. If you do not respect this rule, backward()\n will compute incorrect gradients.\n\n :param input: ndarray or list of ndarray or JTensor or list of JTensor.\n :param grad_output: ndarray or list of ndarray or JTensor or list of JTensor.\n :return: ndarray or list of ndarray", "scope": {"holder": "intel-analytics-BigDL", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/intel-analytics/BigDL/blob/e9c19788285986ab789a2e2998f9a85d7524779f/pyspark/bigdl/nn/layer.py#L329-L360", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:intel-analytics-BigDL:Layer.evaluate-1fd347186b@held-out", "question": "No argument passed in:\n Evaluate the model to set train = false, useful when doing test/forward\n :return: layer itself\n\n Three arguments passed in:\n A method to benchmark the model quality.\n\n :param dataset: the input data\n :param batch_size: batch size\n :param val_methods: a list of validation methods. i.e: Top1Accuracy,Top5Accuracy and Loss.\n :return: a list of the metrics result", "scope": {"holder": "intel-analytics-BigDL", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/intel-analytics/BigDL/blob/e9c19788285986ab789a2e2998f9a85d7524779f/pyspark/bigdl/nn/layer.py#L813-L824", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:intel-analytics-BigDL:Model.load_caffe-bfd491c228@held-out", "question": "Load a pre-trained Caffe model.\n\n\n :param model: A bigdl model definition \\which equivalent to the pre-trained caffe model.\n :param defPath: The path containing the caffe model definition.\n :param modelPath: The path containing the pre-trained caffe model.\n :return: A pre-trained model.", "scope": {"holder": "intel-analytics-BigDL", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/intel-analytics/BigDL/blob/e9c19788285986ab789a2e2998f9a85d7524779f/pyspark/bigdl/nn/layer.py#L840-L854", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:intel-analytics-BigDL:Model.load_tensorflow-3a1eb20ce5@held-out", "question": "Load a pre-trained Tensorflow model.\n :param path: The path containing the pre-trained model.\n :param inputs: The input node of this graph\n :param outputs: The output node of this graph\n :param byte_order: byte_order of the file, `little_endian` or `big_endian`\n :param bin_file: the optional bin file produced by bigdl dump_model util function to store the weights\n :param generated_backward: if generate backward graph\n :return: A pre-trained model.", "scope": {"holder": "intel-analytics-BigDL", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/intel-analytics/BigDL/blob/e9c19788285986ab789a2e2998f9a85d7524779f/pyspark/bigdl/keras/converter.py#L54-L63", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:intel-analytics-BigDL:WeightLoader.load_weights_from_json_hdf5-436e04cbbf@held-out", "question": "The file path can be stored in a local file system, HDFS, S3,\n or any Hadoop-supported file system.", "scope": {"holder": "intel-analytics-BigDL", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/intel-analytics/BigDL/blob/e9c19788285986ab789a2e2998f9a85d7524779f/pyspark/bigdl/keras/converter.py#L67-L83", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:intel-analytics-BigDL:WeightLoader.load_weights_from_hdf5-2c8fe609a2@held-out", "question": "Loads all layer weights from a HDF5 save file.\n filepath can be stored in a local file system, HDFS, S3,\n or any Hadoop-supported file system.\n If `by_name` is False (default) weights are loaded\n based on the network's execution order topology,\n meaning layers in the execution seq should be exactly the same\n the architecture\n\n If `by_name` is True, weights are loaded into layers\n only if they share the same name. This is useful\n for fine-tuning or transfer-learning models where\n some of the layers have changed.", "scope": {"holder": "intel-analytics-BigDL", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/intel-analytics/BigDL/blob/e9c19788285986ab789a2e2998f9a85d7524779f/pyspark/bigdl/keras/converter.py#L292-L308", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:intel-analytics-BigDL:DefinitionLoader.__build_node_id_2_klayer-58dc611dd1@held-out", "question": "The result would contain all of the layers including nested layers.\n :param kmodel: a keras model which can be Sequential or Model\n :param node_id_to_config_layer: a container to store the result", "scope": {"holder": "intel-analytics-BigDL", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/intel-analytics/BigDL/blob/e9c19788285986ab789a2e2998f9a85d7524779f/pyspark/bigdl/nn/keras/layer.py#L41-L48", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:intel-analytics-BigDL:InferShape.get_input_shape-47f8e2d4f2@held-out", "question": "Return a list of shape tuples if there are multiple inputs.\n Return one shape tuple otherwise.", "scope": {"holder": "intel-analytics-BigDL", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/intel-analytics/BigDL/blob/e9c19788285986ab789a2e2998f9a85d7524779f/pyspark/bigdl/util/engine.py#L128-L151", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:intel-analytics-BigDL:compare_version-f3ceff3ef0@held-out", "question": "Compare version strings.\n :param version1;\n :param version2;\n :return: 1 if version1 is after version2; -1 if version1 is before version2; 0 if two versions are the same.", "scope": {"holder": "intel-analytics-BigDL", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/deepmipt/DeepPavlov/blob/f3e4a69a3764d25d2f5bad4f1f1aebc872b00f9c/deeppavlov/agents/default_agent/default_agent.py#L56-L95", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:deepmipt-DeepPavlov:DefaultAgent._call-65b720f1d3@held-out", "question": "Processes batch of utterances and returns corresponding responses batch.\n\n Each call of Agent passes incoming utterances batch through skills filter,\n agent skills, skills processor. Batch of dialog IDs can be provided, in\n other case utterances indexes in incoming batch are used as dialog IDs.\n\n Args:\n utterances_batch: Batch of incoming utterances.\n utterances_ids: Batch of dialog IDs corresponding to incoming utterances.\n\n Returns:\n responses: A batch of responses corresponding to the\n utterance batch received by agent.", "scope": {"holder": "deepmipt-DeepPavlov", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/deepmipt/DeepPavlov/blob/f3e4a69a3764d25d2f5bad4f1f1aebc872b00f9c/deeppavlov/models/spelling_correction/levenshtein/tabled_trie.py#L465-L488", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:deepmipt-DeepPavlov:precompute_future_symbols-23cb1061cc@held-out", "question": "Collecting possible continuations of length <= n for every node", "scope": {"holder": "deepmipt-DeepPavlov", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/deepmipt/DeepPavlov/blob/f3e4a69a3764d25d2f5bad4f1f1aebc872b00f9c/deeppavlov/models/spelling_correction/levenshtein/tabled_trie.py#L61-L82", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:deepmipt-DeepPavlov:Trie.save-340e9935b0@held-out", "question": "Сохраняет дерево для дальнейшего использования", "scope": {"holder": "deepmipt-DeepPavlov", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/deepmipt/DeepPavlov/blob/f3e4a69a3764d25d2f5bad4f1f1aebc872b00f9c/deeppavlov/models/spelling_correction/levenshtein/tabled_trie.py#L224-L233", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:deepmipt-DeepPavlov:Trie._add_empty_child-97989c416c@held-out", "question": "Добавление ребёнка к вершине parent по символу с кодом code", "scope": {"holder": "deepmipt-DeepPavlov", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/deepmipt/DeepPavlov/blob/f3e4a69a3764d25d2f5bad4f1f1aebc872b00f9c/deeppavlov/models/spelling_correction/levenshtein/tabled_trie.py#L235-L243", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:deepmipt-DeepPavlov:Trie._descend_simple-42cd488d0f@held-out", "question": "Спуск из вершины curr по строке s", "scope": {"holder": "deepmipt-DeepPavlov", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/deepmipt/DeepPavlov/blob/f3e4a69a3764d25d2f5bad4f1f1aebc872b00f9c/deeppavlov/models/spelling_correction/levenshtein/tabled_trie.py#L271-L282", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:deepmipt-DeepPavlov:Trie._get_letters-cb6c2131c0@held-out", "question": "Извлекает все метки выходных рёбер вершины с номером index", "scope": {"holder": "deepmipt-DeepPavlov", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/deepmipt/DeepPavlov/blob/f3e4a69a3764d25d2f5bad4f1f1aebc872b00f9c/deeppavlov/models/squad/utils.py#L186-L198", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:deepmipt-DeepPavlov:simple_attention-bcc29e79d0@held-out", "question": "Simple attention without any conditions.\n\n Computes weighted sum of memory elements.", "scope": {"holder": "deepmipt-DeepPavlov", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/deepmipt/DeepPavlov/blob/f3e4a69a3764d25d2f5bad4f1f1aebc872b00f9c/deeppavlov/models/squad/utils.py#L201-L209", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:deepmipt-DeepPavlov:attention-9091ad399b@held-out", "question": "Computes weighted sum of inputs conditioned on state", "scope": {"holder": "deepmipt-DeepPavlov", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/deepmipt/DeepPavlov/blob/f3e4a69a3764d25d2f5bad4f1f1aebc872b00f9c/deeppavlov/core/models/keras_model.py#L271-L294", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:deepmipt-DeepPavlov:LRScheduledKerasModel.process_event-5f0d451ceb@held-out", "question": "Process event after epoch\n Args:\n event_name: whether event is send after epoch or batch.\n Set of values: ``\"after_epoch\", \"after_batch\"``\n data: event data (dictionary)\n\n Returns:\n None", "scope": {"holder": "deepmipt-DeepPavlov", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/deepmipt/DeepPavlov/blob/f3e4a69a3764d25d2f5bad4f1f1aebc872b00f9c/deeppavlov/core/layers/tf_layers.py#L30-L71", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:deepmipt-DeepPavlov:stacked_cnn-a9caedb923@held-out", "question": "Number of convolutional layers stacked on top of each other\n\n Args:\n units: a tensorflow tensor with dimensionality [None, n_tokens, n_features]\n n_hidden_list: list with number of hidden units at the ouput of each layer\n filter_width: width of the kernel in tokens\n use_batch_norm: whether to use batch normalization between layers\n use_dilation: use power of 2 dilation scheme [1, 2, 4, 8 .. ] for layers 1, 2, 3, 4 ...\n training_ph: boolean placeholder determining whether is training phase now or not.\n It is used only for batch normalization to determine whether to use\n current batch average (std) or memory stored average (std)\n add_l2_losses: whether to add l2 losses on network kernels to\n tf.GraphKeys.REGULARIZATION_LOSSES or not\n\n Returns:\n units: tensor at the output of the last convolutional layer", "scope": {"holder": "deepmipt-DeepPavlov", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/deepmipt/DeepPavlov/blob/f3e4a69a3764d25d2f5bad4f1f1aebc872b00f9c/deeppavlov/core/layers/tf_layers.py#L116-L181", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:deepmipt-DeepPavlov:bi_rnn-a5d7bb41e5@held-out", "question": "Bi directional recurrent neural network. GRU or LSTM\n\n Args:\n units: a tensorflow tensor with dimensionality [None, n_tokens, n_features]\n n_hidden: list with number of hidden units at the ouput of each layer\n seq_lengths: length of sequences for different length sequences in batch\n can be None for maximum length as a length for every sample in the batch\n cell_type: 'lstm' or 'gru'\n trainable_initial_states: whether to create a special trainable variable\n to initialize the hidden states of the network or use just zeros\n use_peepholes: whether to use peephole connections (only 'lstm' case affected)\n name: what variable_scope to use for the network parameters\n\n Returns:\n units: tensor at the output of the last recurrent layer\n with dimensionality [None, n_tokens, n_hidden_list[-1]]\n last_units: tensor of last hidden states for GRU and tuple\n of last hidden stated and last cell states for LSTM\n dimensionality of cell states and hidden states are\n similar and equal to [B x 2 * H], where B - batch\n size and H is number of hidden units", "scope": {"holder": "deepmipt-DeepPavlov", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/deepmipt/DeepPavlov/blob/f3e4a69a3764d25d2f5bad4f1f1aebc872b00f9c/deeppavlov/core/layers/tf_layers.py#L552-L604", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:deepmipt-DeepPavlov:cudnn_compatible_gru-85326d0d78@held-out", "question": "CuDNN Compatible GRU implementation.\n It should be used to load models saved with CudnnGRUCell to run on CPU.\n\n Args:\n units: tf.Tensor with dimensions [B x T x F], where\n B - batch size\n T - number of tokens\n F - features\n\n n_hidden: dimensionality of hidden state\n trainable_initial_states: whether to create a special trainable variable\n to initialize the hidden states of the network or use just zeros\n seq_lengths: tensor of sequence lengths with dimension [B]\n n_layers: number of layers\n input_initial_h: initial hidden state, tensor\n name: name of the variable scope to use\n reuse:whether to reuse already initialized variable\n\n Returns:\n h - all hidden states along T dimension,\n tf.Tensor with dimensionality [B x T x F]\n h_last - last hidden state, tf.Tensor with dimensionality [B x H]", "scope": {"holder": "deepmipt-DeepPavlov", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/deepmipt/DeepPavlov/blob/f3e4a69a3764d25d2f5bad4f1f1aebc872b00f9c/deeppavlov/core/layers/tf_layers.py#L820-L869", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:deepmipt-DeepPavlov:cudnn_bi_lstm-8f916bf692@held-out", "question": "Fast CuDNN Bi-LSTM implementation\n\n Args:\n units: tf.Tensor with dimensions [B x T x F], where\n B - batch size\n T - number of tokens\n F - features\n n_hidden: dimensionality of hidden state\n seq_lengths: number of tokens in each sample in the batch\n n_layers: number of layers\n trainable_initial_states: whether to create a special trainable variable\n to initialize the hidden states of the network or use just zeros\n name: name of the variable scope to use\n reuse:whether to reuse already initialized variable\n\n Returns:\n h - all hidden states along T dimension,\n tf.Tensor with dimensionality [B x T x F]\n h_last - last hidden state, tf.Tensor with dimensionality [B x H * 2]\n where H - number of hidden units\n c_last - last cell state, tf.Tensor with dimensionality [B x H * 2]\n where H - number of hidden units", "scope": {"holder": "deepmipt-DeepPavlov", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/deepmipt/DeepPavlov/blob/f3e4a69a3764d25d2f5bad4f1f1aebc872b00f9c/deeppavlov/core/layers/tf_layers.py#L872-L927", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:deepmipt-DeepPavlov:cudnn_stacked_bi_gru-a279b6bea9@held-out", "question": "Fast CuDNN Stacked Bi-GRU implementation\n\n Args:\n units: tf.Tensor with dimensions [B x T x F], where\n B - batch size\n T - number of tokens\n F - features\n n_hidden: dimensionality of hidden state\n seq_lengths: number of tokens in each sample in the batch\n n_stacks: number of stacked Bi-GRU\n keep_prob: dropout keep_prob between Bi-GRUs (intra-layer dropout)\n concat_stacked_outputs: return last Bi-GRU output or concat outputs from every Bi-GRU,\n trainable_initial_states: whether to create a special trainable variable\n to initialize the hidden states of the network or use just zeros\n name: name of the variable scope to use\n reuse: whether to reuse already initialized variable\n\n\n Returns:\n h - all hidden states along T dimension,\n tf.Tensor with dimensionality [B x T x ((n_hidden * 2) * n_stacks)]", "scope": {"holder": "deepmipt-DeepPavlov", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/deepmipt/DeepPavlov/blob/f3e4a69a3764d25d2f5bad4f1f1aebc872b00f9c/deeppavlov/models/morpho_tagger/network.py#L140-L160", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:deepmipt-DeepPavlov:CharacterTagger.build-ccfbc245df@held-out", "question": "Builds the network using Keras.", "scope": {"holder": "deepmipt-DeepPavlov", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/deepmipt/DeepPavlov/blob/f3e4a69a3764d25d2f5bad4f1f1aebc872b00f9c/deeppavlov/models/morpho_tagger/network.py#L268-L288", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:deepmipt-DeepPavlov:CharacterTagger._make_sent_vector-959dc117b4@held-out", "question": "Transforms a sentence to Numpy array, which will be the network input.\n\n Args:\n sent: input sentence\n bucket_length: the width of the bucket\n\n Returns:\n A 3d array, answer[i][j][k] contains the index of k-th letter\n in j-th word of i-th input sentence.", "scope": {"holder": "deepmipt-DeepPavlov", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/deepmipt/DeepPavlov/blob/f3e4a69a3764d25d2f5bad4f1f1aebc872b00f9c/deeppavlov/models/morpho_tagger/network.py#L290-L304", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:deepmipt-DeepPavlov:CharacterTagger._make_tags_vector-1908383fbc@held-out", "question": "Transforms a sentence of tags to Numpy array, which will be the network target.\n\n Args:\n tags: input sentence of tags\n bucket_length: the width of the bucket\n\n Returns:\n A 2d array, answer[i][j] contains the index of j-th tag in i-th input sentence.", "scope": {"holder": "deepmipt-DeepPavlov", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/deepmipt/DeepPavlov/blob/f3e4a69a3764d25d2f5bad4f1f1aebc872b00f9c/deeppavlov/core/agent/rich_content.py#L126-L135", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:deepmipt-DeepPavlov:RichMessage.ms_bot_framework-6afd9a999f@held-out", "question": "Returns list of MS Bot Framework compatible states of the\n RichMessage instance nested controls.\n\n Returns:\n ms_bf_controls: MS Bot Framework representation of RichMessage instance\n nested controls.", "scope": {"holder": "deepmipt-DeepPavlov", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/deepmipt/DeepPavlov/blob/f3e4a69a3764d25d2f5bad4f1f1aebc872b00f9c/deeppavlov/models/elmo/elmo_model.py#L597-L728", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:deepmipt-DeepPavlov:weight_layers-93d70d163d@held-out", "question": "Weight the layers of a biLM with trainable scalar weights to\n compute ELMo representations.\n\n For each output layer, this returns two ops. The first computes\n a layer specific weighted average of the biLM layers, and\n the second the l2 regularizer loss term.\n The regularization terms are also add to tf.GraphKeys.REGULARIZATION_LOSSES\n\n Input:\n name = a string prefix used for the trainable variable names\n bilm_ops = the tensorflow ops returned to compute internal\n representations from a biLM. This is the return value\n from BidirectionalLanguageModel(...)(ids_placeholder)\n l2_coef: the l2 regularization coefficient $\\lambda$.\n Pass None or 0.0 for no regularization.\n use_top_only: if True, then only use the top layer.\n do_layer_norm: if True, then apply layer normalization to each biLM\n layer before normalizing\n reuse: reuse an aggregation variable scope.\n\n Output:\n {\n 'weighted_op': op to compute weighted average for output,\n 'regularization_op': op to compute regularization term\n }", "scope": {"holder": "deepmipt-DeepPavlov", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/deepmipt/DeepPavlov/blob/f3e4a69a3764d25d2f5bad4f1f1aebc872b00f9c/deeppavlov/core/data/dataset_reader.py#L21-L25", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:deepmipt-DeepPavlov:DatasetReader.read-b3a6b335e8@held-out", "question": "Reads a file from a path and returns data as a list of tuples of inputs and correct outputs\n for every data type in ``train``, ``valid`` and ``test``.", "scope": {"holder": "deepmipt-DeepPavlov", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/deepmipt/DeepPavlov/blob/f3e4a69a3764d25d2f5bad4f1f1aebc872b00f9c/deeppavlov/core/models/tf_model.py#L97-L149", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:deepmipt-DeepPavlov:TFModel.get_train_op-363e432151@held-out", "question": "Get train operation for given loss\n\n Args:\n loss: loss, tf tensor or scalar\n learning_rate: scalar or placeholder.\n clip_norm: clip gradients norm by clip_norm.\n learnable_scopes: which scopes are trainable (None for all).\n optimizer: instance of tf.train.Optimizer, default Adam.\n **kwargs: parameters passed to tf.train.Optimizer object\n (scalars or placeholders).\n\n Returns:\n train_op", "scope": {"holder": "deepmipt-DeepPavlov", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/deepmipt/DeepPavlov/blob/f3e4a69a3764d25d2f5bad4f1f1aebc872b00f9c/deeppavlov/core/models/tf_model.py#L152-L167", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:deepmipt-DeepPavlov:TFModel.print_number_of_parameters-030d53bbfe@held-out", "question": "Print number of *trainable* parameters in the network", "scope": {"holder": "deepmipt-DeepPavlov", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/deepmipt/DeepPavlov/blob/f3e4a69a3764d25d2f5bad4f1f1aebc872b00f9c/deeppavlov/models/spelling_correction/levenshtein/levenshtein_searcher.py#L44-L53", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:deepmipt-DeepPavlov:LevenshteinSearcher.search-7fac862f2b@held-out", "question": "Finds all dictionary words in d-window from word", "scope": {"holder": "deepmipt-DeepPavlov", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/deepmipt/DeepPavlov/blob/f3e4a69a3764d25d2f5bad4f1f1aebc872b00f9c/deeppavlov/models/spelling_correction/levenshtein/levenshtein_searcher.py#L164-L199", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:deepmipt-DeepPavlov:LevenshteinSearcher._euristic_h_function-6420f30ed9@held-out", "question": "Вычисление h-эвристики из работы Hulden,2009 для текущей вершины словаря\n\n Аргументы:\n ----------\n suffix : string\n непрочитанный суффикс входного слова\n index : int\n индекс текущего узла в словаре\n\n Возвращает:\n -----------\n cost : float\n оценка снизу для стоимости замены,\n приводящей к входному слову с суффиксом suffix,\n если прочитанный префикс слова без опечатки\n привёл в вершину с номером index", "scope": {"holder": "deepmipt-DeepPavlov", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/deepmipt/DeepPavlov/blob/f3e4a69a3764d25d2f5bad4f1f1aebc872b00f9c/deeppavlov/models/spelling_correction/levenshtein/levenshtein_searcher.py#L330-L342", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:deepmipt-DeepPavlov:SegmentTransducer.inverse-be429b2da4@held-out", "question": "Строит пробразователь, задающий обратное конечное преобразование", "scope": {"holder": "deepmipt-DeepPavlov", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/deepmipt/DeepPavlov/blob/f3e4a69a3764d25d2f5bad4f1f1aebc872b00f9c/deeppavlov/models/elmo/elmo2tfhub.py#L23-L187", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:deepmipt-DeepPavlov:make_module_spec-117e67eae2@held-out", "question": "Makes a module spec.\n\n Args:\n options: LM hyperparameters.\n weight_file: location of the hdf5 file with LM weights.\n\n Returns:\n A module spec object used for constructing a TF-Hub module.", "scope": {"holder": "deepmipt-DeepPavlov", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/deepmipt/DeepPavlov/blob/f3e4a69a3764d25d2f5bad4f1f1aebc872b00f9c/deeppavlov/agents/ecommerce_agent/ecommerce_agent.py#L158-L173", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:deepmipt-DeepPavlov:show_details-03181214cd@held-out", "question": "Format catalog item output\n\n Parameters:\n item_data: item's attributes values\n\n Returns:\n [rich_message]: list of formatted rich message", "scope": {"holder": "deepmipt-DeepPavlov", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/deepmipt/DeepPavlov/blob/f3e4a69a3764d25d2f5bad4f1f1aebc872b00f9c/deeppavlov/agents/ecommerce_agent/ecommerce_agent.py#L176-L186", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:deepmipt-DeepPavlov:make_agent-d2d8486ba4@held-out", "question": "Make an agent\n\n Returns:\n agent: created Ecommerce agent", "scope": {"holder": "deepmipt-DeepPavlov", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/deepmipt/DeepPavlov/blob/f3e4a69a3764d25d2f5bad4f1f1aebc872b00f9c/deeppavlov/models/morpho_tagger/cells.py#L141-L155", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:deepmipt-DeepPavlov:TemporalDropout-87c908ee43@held-out", "question": "Drops with :dropout probability temporal steps of input 3D tensor", "scope": {"holder": "deepmipt-DeepPavlov", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/deepmipt/DeepPavlov/blob/f3e4a69a3764d25d2f5bad4f1f1aebc872b00f9c/deeppavlov/core/data/utils.py#L83-L125", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:deepmipt-DeepPavlov:download-e01be0cca9@held-out", "question": "Download a file from URL to one or several target locations\n\n Args:\n dest_file_path: path or list of paths to the file destination files (including file name)\n source_url: the source URL\n force_download: download file if it already exists, or not", "scope": {"holder": "deepmipt-DeepPavlov", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/h2oai/h2o-3/blob/dd62aaa1e7f680a8b16ee14bc66b0fb5195c2ad8/h2o-py/h2o/estimators/generic.py#L62-L75", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:h2oai-h2o-3:H2OGenericEstimator.from_file-e79dbcac11@held-out", "question": "Creates new Generic model by loading existing embedded model into library, e.g. from H2O MOJO.\n The imported model must be supported by H2O.\n :param file: A string containing path to the file to create the model from\n :return: H2OGenericEstimator instance representing the generic model", "scope": {"holder": "h2oai-h2o-3", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/h2oai/h2o-3/blob/dd62aaa1e7f680a8b16ee14bc66b0fb5195c2ad8/h2o-py/h2o/backend/cluster.py#L211-L258", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:h2oai-h2o-3:H2OCluster.show_status-4205d34d09@held-out", "question": "Print current cluster status information.\n\n :param detailed: if True, then also print detailed information about each node.", "scope": {"holder": "h2oai-h2o-3", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/h2oai/h2o-3/blob/dd62aaa1e7f680a8b16ee14bc66b0fb5195c2ad8/h2o-py/h2o/backend/cluster.py#L303-L306", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:h2oai-h2o-3:H2OCluster.list_timezones-c543eb194b@held-out", "question": "Return the list of all known timezones.", "scope": {"holder": "h2oai-h2o-3", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/h2oai/h2o-3/blob/dd62aaa1e7f680a8b16ee14bc66b0fb5195c2ad8/py2/h2o_ray.py#L11-L20", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:h2oai-h2o-3:jobs-356fcfa528@held-out", "question": "Fetch all the jobs or a single job from the /Jobs endpoint.", "scope": {"holder": "h2oai-h2o-3", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/h2oai/h2o-3/blob/dd62aaa1e7f680a8b16ee14bc66b0fb5195c2ad8/py2/h2o_ray.py#L82-L93", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:h2oai-h2o-3:import_files-02ea55e6d2@held-out", "question": "Import a file or files into h2o. The 'file' parameter accepts a directory or a single file.\n 192.168.0.37:54323/ImportFiles.html?file=%2Fhome%2F0xdiag%2Fdatasets", "scope": {"holder": "h2oai-h2o-3", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/h2oai/h2o-3/blob/dd62aaa1e7f680a8b16ee14bc66b0fb5195c2ad8/py2/ec2_cmd.py#L232-L245", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:h2oai-h2o-3:wait_for_ssh-9268eb405d@held-out", "question": "Wait for ssh service to appear on given hosts", "scope": {"holder": "h2oai-h2o-3", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/h2oai/h2o-3/blob/dd62aaa1e7f680a8b16ee14bc66b0fb5195c2ad8/h2o-py/h2o/utils/debugging.py#L238-L265", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:h2oai-h2o-3:_get_method_full_name-5e4d760be6@held-out", "question": "Return fully qualified function name.\n\n This method will attempt to find \"full name\" of the given function object. This full name is either of\n the form \"<class name>.<method name>\" if the function is a class method, or \"<module name>.<func name>\"\n if it's a regular function. Thus, this is an attempt to back-port func.__qualname__ to Python 2.\n\n :param func: a function object.\n\n :returns: string with the function's full name as explained above.", "scope": {"holder": "h2oai-h2o-3", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/h2oai/h2o-3/blob/dd62aaa1e7f680a8b16ee14bc66b0fb5195c2ad8/h2o-py/h2o/estimators/estimator_base.py#L325-L350", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:h2oai-h2o-3:H2OEstimator.fit-b2ee36f737@held-out", "question": "Fit an H2O model as part of a scikit-learn pipeline or grid search.\n\n A warning will be issued if a caller other than sklearn attempts to use this method.\n\n :param H2OFrame X: An H2OFrame consisting of the predictor variables.\n :param H2OFrame y: An H2OFrame consisting of the response variable.\n :param params: Extra arguments.\n :returns: The current instance of H2OEstimator for method chaining.", "scope": {"holder": "h2oai-h2o-3", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/h2oai/h2o-3/blob/dd62aaa1e7f680a8b16ee14bc66b0fb5195c2ad8/h2o-py/h2o/estimators/estimator_base.py#L353-L369", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:h2oai-h2o-3:H2OEstimator.get_params-1c9a8430aa@held-out", "question": "Obtain parameters for this estimator.\n\n Used primarily for sklearn Pipelines and sklearn grid search.\n\n :param deep: If True, return parameters of all sub-objects that are estimators.\n\n :returns: A dict of parameters", "scope": {"holder": "h2oai-h2o-3", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/h2oai/h2o-3/blob/dd62aaa1e7f680a8b16ee14bc66b0fb5195c2ad8/h2o-py/h2o/estimators/estimator_base.py#L470-L479", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:h2oai-h2o-3:H2OEstimator._check_and_save_parm-8a97374806@held-out", "question": "If a parameter is not stored in parms dict save it there (even though the value is None).\n Else check if the parameter has been already set during initialization of estimator. If yes, check the new value is the same or not. If the values are different, set the last passed value to params dict and throw UserWarning.", "scope": {"holder": "h2oai-h2o-3", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/h2oai/h2o-3/blob/dd62aaa1e7f680a8b16ee14bc66b0fb5195c2ad8/scripts/run.py#L2073-L2089", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:h2oai-h2o-3:signal_handler-b673e141fb@held-out", "question": "Helper function to handle caught signals.", "scope": {"holder": "h2oai-h2o-3", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/h2oai/h2o-3/blob/dd62aaa1e7f680a8b16ee14bc66b0fb5195c2ad8/scripts/run.py#L591-L602", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:h2oai-h2o-3:H2OCloud.start-97d980442d@held-out", "question": "Start H2O cluster.\n The cluster is not up until wait_for_cloud_to_be_up() is called and returns.\n\n :return none", "scope": {"holder": "h2oai-h2o-3", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/h2oai/h2o-3/blob/dd62aaa1e7f680a8b16ee14bc66b0fb5195c2ad8/scripts/grabGLRMrunLogs.py#L48-L70", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:h2oai-h2o-3:get_file_out-f8871ef48a@held-out", "question": "This function will grab one log file from Jenkins and save it to local user directory\n :param g_jenkins_url:\n :param build_index:\n :param airline_java:\n :param airline_java_tail:\n :return:", "scope": {"holder": "h2oai-h2o-3", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/h2oai/h2o-3/blob/dd62aaa1e7f680a8b16ee14bc66b0fb5195c2ad8/h2o-py/h2o/utils/typechecks.py#L246-L248", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:h2oai-h2o-3:Tuple.check-aef14f1e18@held-out", "question": "Return True if the variable matches this type, and False otherwise.", "scope": {"holder": "h2oai-h2o-3", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/h2oai/h2o-3/blob/dd62aaa1e7f680a8b16ee14bc66b0fb5195c2ad8/h2o-py/h2o/utils/typechecks.py#L312-L320", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:h2oai-h2o-3:BoundInt.name-5c56b02ca5@held-out", "question": "Return string representing the name of this type.", "scope": {"holder": "h2oai-h2o-3", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/h2oai/h2o-3/blob/dd62aaa1e7f680a8b16ee14bc66b0fb5195c2ad8/h2o-py/h2o/utils/config.py#L24-L29", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:h2oai-h2o-3:H2OConfigReader.get_config-d84b54459d@held-out", "question": "Retrieve the config as a dictionary of key-value pairs.", "scope": {"holder": "h2oai-h2o-3", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/h2oai/h2o-3/blob/dd62aaa1e7f680a8b16ee14bc66b0fb5195c2ad8/h2o-py/h2o/utils/progressbar.py#L134-L210", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:h2oai-h2o-3:ProgressBar.execute-3da896c325@held-out", "question": "Start the progress bar, and return only when the progress reaches 100%.\n\n :param progress_fn: the executor function (or a generator). This function should take no arguments\n and return either a single number -- the current progress level, or a tuple (progress level, delay),\n where delay is the time interval for when the progress should be checked again. This function may at\n any point raise the ``StopIteration(message)`` exception, which will interrupt the progress bar,\n display the ``message`` in red font, and then re-raise the exception.\n :raises StopIteration: if the job is interrupted. The reason for interruption is provided in the exception's\n message. The message will say \"cancelled\" if the job was interrupted by the user by pressing Ctrl+C.", "scope": {"holder": "h2oai-h2o-3", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/h2oai/h2o-3/blob/dd62aaa1e7f680a8b16ee14bc66b0fb5195c2ad8/h2o-py/h2o/frame.py#L265-L270", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:h2oai-h2o-3:H2OFrame.types-fffa7a7148@held-out", "question": "The dictionary of column name/type pairs.", "scope": {"holder": "h2oai-h2o-3", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/h2oai/h2o-3/blob/dd62aaa1e7f680a8b16ee14bc66b0fb5195c2ad8/h2o-py/h2o/frame.py#L697-L707", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:h2oai-h2o-3:H2OFrame.mult-fcbc7e3d9e@held-out", "question": "Multiply this frame, viewed as a matrix, by another matrix.\n\n :param matrix: another frame that you want to multiply the current frame by; must be compatible with the\n current frame (i.e. its number of rows must be the same as number of columns in the current frame).\n :returns: new H2OFrame, which is the result of multiplying the current frame by ``matrix``.", "scope": {"holder": "h2oai-h2o-3", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/h2oai/h2o-3/blob/dd62aaa1e7f680a8b16ee14bc66b0fb5195c2ad8/h2o-py/h2o/frame.py#L885-L976", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:h2oai-h2o-3:H2OFrame.moment-e21d8776ba@held-out", "question": "Create a time column from individual components.\n\n Each parameter should be either an integer, or a single-column H2OFrame\n containing the corresponding time parts for each row.\n\n The \"date\" part of the timestamp can be specified using either the tuple ``(year, month, day)``, or an\n explicit ``date`` parameter. The \"time\" part of the timestamp is optional, but can be specified either via\n the ``time`` parameter, or via the ``(hour, minute, second, msec)`` tuple.\n\n :param year: the year part of the constructed date\n :param month: the month part of the constructed date\n :param day: the day-of-the-month part of the constructed date\n :param hour: the hours part of the constructed date\n :param minute: the minutes part of the constructed date\n :param second: the seconds part of the constructed date\n :param msec: the milliseconds part of the constructed date\n :param date date: construct the timestamp from the Python's native ``datetime.date`` (or ``datetime.datetime``)\n object. If the object passed is of type ``date``, then you can specify the time part using either the\n ``time`` argument, or ``hour`` ... ``msec`` arguments (but not both). If the object passed is of type\n ``datetime``, then no other arguments can be provided.\n :param time time: construct the timestamp from this Python's native ``datetime.time`` object. This argument\n cannot be used alone, it should be supplemented with either ``date`` argument, or ``year`` ... ``day``\n tuple.\n\n :returns: H2OFrame with one column containing the date constructed from the provided arguments.", "scope": {"holder": "h2oai-h2o-3", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/h2oai/h2o-3/blob/dd62aaa1e7f680a8b16ee14bc66b0fb5195c2ad8/h2o-py/h2o/frame.py#L1286-L1305", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:h2oai-h2o-3:H2OFrame.as_data_frame-34dc0fe22b@held-out", "question": "Obtain the dataset as a python-local object.\n\n :param bool use_pandas: If True (default) then return the H2OFrame as a pandas DataFrame (requires that the\n ``pandas`` library was installed). If False, then return the contents of the H2OFrame as plain nested\n list, in a row-wise order.\n :param bool header: If True (default), then column names will be appended as the first row in list\n\n :returns: A python object (a list of lists of strings, each list is a row, if use_pandas=False, otherwise\n a pandas DataFrame) containing this H2OFrame instance's data.", "scope": {"holder": "h2oai-h2o-3", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/h2oai/h2o-3/blob/dd62aaa1e7f680a8b16ee14bc66b0fb5195c2ad8/h2o-py/h2o/frame.py#L1650-L1673", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:h2oai-h2o-3:H2OFrame.quantile-c1493c6ee7@held-out", "question": "Compute quantiles.\n\n :param List[float] prob: list of probabilities for which quantiles should be computed.\n :param str combine_method: for even samples this setting determines how to combine quantiles. This can be\n one of ``\"interpolate\"``, ``\"average\"``, ``\"low\"``, ``\"high\"``.\n :param weights_column: optional weights for each row. If not given, all rows are assumed to have equal\n importance. This parameter can be either the name of column containing the observation weights in\n this frame, or a single-column separate H2OFrame of observation weights.\n\n :returns: a new H2OFrame containing the quantiles and probabilities.", "scope": {"holder": "h2oai-h2o-3", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/h2oai/h2o-3/blob/dd62aaa1e7f680a8b16ee14bc66b0fb5195c2ad8/h2o-py/h2o/frame.py#L1676-L1692", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:h2oai-h2o-3:H2OFrame.concat-0a231deb58@held-out", "question": "Append multiple H2OFrames to this frame, column-wise or row-wise.\n\n :param List[H2OFrame] frames: list of frames that should be appended to the current frame.\n :param int axis: if 1 then append column-wise (default), if 0 then append row-wise.\n\n :returns: an H2OFrame of the combined datasets.", "scope": {"holder": "h2oai-h2o-3", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/h2oai/h2o-3/blob/dd62aaa1e7f680a8b16ee14bc66b0fb5195c2ad8/h2o-py/h2o/frame.py#L1730-L1747", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:h2oai-h2o-3:H2OFrame.rbind-a5c9e11d09@held-out", "question": "Append data to this frame row-wise.\n\n :param data: an H2OFrame or a list of H2OFrame's to be combined with current frame row-wise.\n :returns: this H2OFrame with all frames in data appended row-wise.", "scope": {"holder": "h2oai-h2o-3", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/h2oai/h2o-3/blob/dd62aaa1e7f680a8b16ee14bc66b0fb5195c2ad8/h2o-py/h2o/frame.py#L1978-L1988", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:h2oai-h2o-3:H2OFrame.relevel-28faeac883@held-out", "question": "Reorder levels of an H2O factor for one single column of a H2O frame\n\n The levels of a factor are reordered such that the reference level is at level 0, all remaining levels are\n moved down as needed.\n\n :param str y: The reference level\n :returns: New reordered factor column", "scope": {"holder": "h2oai-h2o-3", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/h2oai/h2o-3/blob/dd62aaa1e7f680a8b16ee14bc66b0fb5195c2ad8/h2o-py/h2o/frame.py#L2024-L2059", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:h2oai-h2o-3:H2OFrame.sum-9773125c5b@held-out", "question": "Compute the frame's sum by-column (or by-row).\n\n :param bool skipna: If True (default), then NAs are ignored during the computation. Otherwise presence\n of NAs renders the entire result NA.\n :param int axis: Direction of sum computation. If 0 (default), then sum is computed columnwise, and the result\n is a frame with 1 row and number of columns as in the original frame. If 1, then sum is computed rowwise\n and the result is a frame with 1 column (called \"sum\"), and number of rows equal to the number of rows\n in the original frame. For row or column sums, the ``return_frame`` parameter must be True.\n :param bool return_frame: A boolean parameter that indicates whether to return an H2O frame or one single aggregated value. Default is False.\n :returns: either an aggregated value with sum of values per-column (old semantic); or an H2OFrame containing sum of values\n per-column/per-row in the original frame (new semantic). The new semantic is triggered by either\n providing the ``return_frame=True`` parameter, or having the ``general.allow_breaking_changed`` config\n option turned on.", "scope": {"holder": "h2oai-h2o-3", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/h2oai/h2o-3/blob/dd62aaa1e7f680a8b16ee14bc66b0fb5195c2ad8/h2o-py/h2o/frame.py#L2547-L2566", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:h2oai-h2o-3:H2OFrame.isax-0c9692e64b@held-out", "question": "Compute the iSAX index for DataFrame which is assumed to be numeric time series data.\n\n References:\n\n - http://www.cs.ucr.edu/~eamonn/SAX.pdf\n - http://www.cs.ucr.edu/~eamonn/iSAX_2.0.pdf\n\n :param int num_words: Number of iSAX words for the timeseries, i.e. granularity along the time series\n :param int max_cardinality: Maximum cardinality of the iSAX word. Each word can have less than the max\n :param bool optimized_card: An optimization flag that will find the max cardinality regardless of what is\n passed in for ``max_cardinality``.\n\n :returns: An H2OFrame with the name of time series, string representation of iSAX word, followed by\n binary representation.", "scope": {"holder": "h2oai-h2o-3", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/h2oai/h2o-3/blob/dd62aaa1e7f680a8b16ee14bc66b0fb5195c2ad8/h2o-py/h2o/frame.py#L2675-L2700", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:h2oai-h2o-3:H2OFrame.pivot-f490296f76@held-out", "question": "Pivot the frame designated by the three columns: index, column, and value. Index and column should be\n of type enum, int, or time.\n For cases of multiple indexes for a column label, the aggregation method is to pick the first occurrence in the data frame\n\n :param index: Index is a column that will be the row label\n :param column: The labels for the columns in the pivoted Frame\n :param value: The column of values for the given index and column label\n :returns:", "scope": {"holder": "h2oai-h2o-3", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/h2oai/h2o-3/blob/dd62aaa1e7f680a8b16ee14bc66b0fb5195c2ad8/h2o-py/h2o/frame.py#L2824-L2853", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:h2oai-h2o-3:H2OFrame.topNBottomN-32dfbb77f7@held-out", "question": "Given a column name or one column index, a percent N, this function will return the top or bottom N% of the\n values of the column of a frame. The column must be a numerical column.\n \n :param column: a string for column name or an integer index\n :param nPercent: a top or bottom percentage of the column values to return\n :param grabTopN: -1 to grab bottom N percent and 1 to grab top N percent\n :returns: a H2OFrame containing two columns. The first column contains the original row indices where\n the top/bottom values are extracted from. The second column contains the values.", "scope": {"holder": "h2oai-h2o-3", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/h2oai/h2o-3/blob/dd62aaa1e7f680a8b16ee14bc66b0fb5195c2ad8/h2o-py/h2o/frame.py#L2879-L2888", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:h2oai-h2o-3:H2OFrame.sub-2c93f287b7@held-out", "question": "Substitute the first occurrence of pattern in a string with replacement.\n\n :param str pattern: A regular expression.\n :param str replacement: A replacement string.\n :param bool ignore_case: If True then pattern will match case-insensitively.\n :returns: an H2OFrame with all values matching ``pattern`` replaced with ``replacement``.", "scope": {"holder": "h2oai-h2o-3", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/h2oai/h2o-3/blob/dd62aaa1e7f680a8b16ee14bc66b0fb5195c2ad8/h2o-py/h2o/frame.py#L3041-L3053", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:h2oai-h2o-3:H2OFrame.difflag1-66954d2d1b@held-out", "question": "Conduct a diff-1 transform on a numeric frame column.\n\n :returns: an H2OFrame where each element is equal to the corresponding element in the source\n frame minus the previous-row element in the same frame.", "scope": {"holder": "h2oai-h2o-3", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/h2oai/h2o-3/blob/dd62aaa1e7f680a8b16ee14bc66b0fb5195c2ad8/h2o-py/h2o/frame.py#L3219-L3241", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:h2oai-h2o-3:H2OFrame.cut-9f000ad480@held-out", "question": "Cut a numeric vector into categorical \"buckets\".\n\n This method is only applicable to a single-column numeric frame.\n\n :param List[float] breaks: The cut points in the numeric vector.\n :param List[str] labels: Labels for categorical levels produced. Defaults to set notation of\n intervals defined by the breaks.\n :param bool include_lowest: By default, cuts are defined as intervals ``(lo, hi]``. If this parameter\n is True, then the interval becomes ``[lo, hi]``.\n :param bool right: Include the high value: ``(lo, hi]``. If False, get ``(lo, hi)``.\n :param int dig_lab: Number of digits following the decimal point to consider.\n\n :returns: Single-column H2OFrame of categorical data.", "scope": {"holder": "h2oai-h2o-3", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/h2oai/h2o-3/blob/dd62aaa1e7f680a8b16ee14bc66b0fb5195c2ad8/h2o-py/h2o/frame.py#L3326-L3334", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:h2oai-h2o-3:H2OFrame.mktime-5fb23671ec@held-out", "question": "Deprecated, use :func:`moment` instead.\n\n This function was left for backward-compatibility purposes only. It is\n not very stable, and counterintuitively uses 0-based months and days,\n so \"January 4th, 2001\" should be entered as ``mktime(2001, 0, 3)``.", "scope": {"holder": "h2oai-h2o-3", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/h2oai/h2o-3/blob/dd62aaa1e7f680a8b16ee14bc66b0fb5195c2ad8/h2o-bindings/bin/pyparser.py#L62-L169", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:h2oai-h2o-3:_tokenize-8659f03c52@held-out", "question": "Parse any object accessible through a readline interface into a list of :class:`Token`s.\n\n This function is very similar to :func:`tokenize.generate_tokens`, with few differences. First, the returned list\n is a list of :class:`Token` objects instead of 5-tuples. This may be slightly less efficient, but far more\n convenient for subsequent parsing. Second, the list of tokens is **normalized** to better match the way humans\n understand the code, not what is more suitable for the compiler.\n\n To better understand the normalization process, consider the following code example::\n\n def test():\n pass\n\n # funny function\n def test_funny():\n # not so funny\n pass\n\n Normally, Python will parse it as the following sequence of tokens:\n\n ['def', 'test', '(', ')', ':', NEWLINE, INDENT, 'pass', NEWLINE, NL, '# funny function', NL, DEDENT,\n 'def', 'test_funny', '(', ')', ':', NEWLINE, '# not so funny', NL, INDENT, 'pass', NEWLINE, DEDENT, END]\n\n The problem here is that the DEDENT token is generated not after the first 'pass' but after the comment, which\n means that if we treat INDENTs / DEDENTs as block boundaries, then the comment \"belongs\" to the first function.\n This is contrary to how most people would understand this code. Similarly, the second comment visually goes\n after the INDENT, not before. Consequently, after \"normalization\" this function will return the following list\n of tokens:\n\n ['def', 'test', '(', ')', ':', NEWLINE, INDENT, 'pass', NEWLINE, DEDENT, NL, '# funny function', NL,\n 'def', 'test_funny', '(', ')', ':', NEWLINE, INDENT, '# not so funny', NL, 'pass', NEWLINE, DEDENT, END]\n\n :param readline: a function that allows access to the code being parsed in a line-by-line fashion.\n\n :returns: a list of :class:`Token`s.", "scope": {"holder": "h2oai-h2o-3", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/h2oai/h2o-3/blob/dd62aaa1e7f680a8b16ee14bc66b0fb5195c2ad8/h2o-py/h2o/model/clustering.py#L143-L148", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:h2oai-h2o-3:H2OClusteringModel.centers-4cc5ae23e5@held-out", "question": "The centers for the KMeans model.", "scope": {"holder": "h2oai-h2o-3", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/h2oai/h2o-3/blob/dd62aaa1e7f680a8b16ee14bc66b0fb5195c2ad8/h2o-py/h2o/h2o.py#L287-L299", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:h2oai-h2o-3:lazy_import-57ea37a578@held-out", "question": "Import a single file or collection of files.\n\n :param path: A path to a data file (remote or local).\n :param pattern: Character string containing a regular expression to match file(s) in the folder.\n :returns: either a :class:`H2OFrame` with the content of the provided file, or a list of such frames if\n importing multiple files.", "scope": {"holder": "h2oai-h2o-3", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/h2oai/h2o-3/blob/dd62aaa1e7f680a8b16ee14bc66b0fb5195c2ad8/h2o-py/h2o/h2o.py#L1297-L1316", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:h2oai-h2o-3:as_list-825b164c6a@held-out", "question": "Convert an H2O data object into a python-specific object.\n\n WARNING! This will pull all data local!\n\n If Pandas is available (and use_pandas is True), then pandas will be used to parse the\n data frame. Otherwise, a list-of-lists populated by character data will be returned (so\n the types of data will all be str).\n\n :param data: an H2O data object.\n :param use_pandas: If True, try to use pandas for reading in the data.\n :param header: If True, return column names as first element in list\n\n :returns: List of lists (Rows x Columns).", "scope": {"holder": "h2oai-h2o-3", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/h2oai/h2o-3/blob/dd62aaa1e7f680a8b16ee14bc66b0fb5195c2ad8/h2o-py/h2o/h2o.py#L1388-L1398", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:h2oai-h2o-3:_put_key-11315a24e2@held-out", "question": "Upload given file into DKV and save it under give key as raw object.\n\n :param dest_key: name of destination key in DKV\n :param file_path: path to file to upload\n :return: key name if object was uploaded successfully", "scope": {"holder": "h2oai-h2o-3", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/h2oai/h2o-3/blob/dd62aaa1e7f680a8b16ee14bc66b0fb5195c2ad8/h2o-py/h2o/utils/shared_utils.py#L331-L338", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:h2oai-h2o-3:print2-ccac4200fb@held-out", "question": "This function exists here ONLY because Sphinx.ext.autodoc gets into a bad state when seeing the print()\n function. When in that state, autodoc doesn't display any errors or warnings, but instead completely\n ignores the \"bysource\" member-order option.", "scope": {"holder": "h2oai-h2o-3", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/h2oai/h2o-3/blob/dd62aaa1e7f680a8b16ee14bc66b0fb5195c2ad8/h2o-py/h2o/grid/grid_search.py#L358-L366", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:h2oai-h2o-3:H2OGridSearch.deepfeatures-450e79358d@held-out", "question": "Obtain a hidden layer's details on a dataset.\n\n :param test_data: Data to create a feature space on.\n :param int layer: Index of the hidden layer.\n :returns: A dictionary of hidden layer details for each model.", "scope": {"holder": "h2oai-h2o-3", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/h2oai/h2o-3/blob/dd62aaa1e7f680a8b16ee14bc66b0fb5195c2ad8/h2o-bindings/bin/gen_java.py#L42-L69", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:h2oai-h2o-3:translate_name-617513a037@held-out", "question": "Convert names with underscores into camelcase.\n\n For example:\n \"num_rows\" => \"numRows\"\n \"very_long_json_name\" => \"veryLongJsonName\"\n \"build_GBM_model\" => \"buildGbmModel\"\n \"KEY\" => \"key\"\n \"middle___underscores\" => \"middleUnderscores\"\n \"_exclude_fields\" => \"_excludeFields\" (retain initial/trailing underscores)\n \"__http_status__\" => \"__httpStatus__\"\n\n :param name: name to be converted", "scope": {"holder": "h2oai-h2o-3", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/h2oai/h2o-3/blob/dd62aaa1e7f680a8b16ee14bc66b0fb5195c2ad8/h2o-r/scripts/build_dataset_from_parse_log.py#L100-L106", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:h2oai-h2o-3:Dataset.parse-4a42617e1f@held-out", "question": "Parse file specified by constructor.", "scope": {"holder": "h2oai-h2o-3", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/h2oai/h2o-3/blob/dd62aaa1e7f680a8b16ee14bc66b0fb5195c2ad8/h2o-r/scripts/build_dataset_from_parse_log.py#L108-L208", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:h2oai-h2o-3:Dataset.parse2-9dc3466124@held-out", "question": "Parse file specified by constructor.", "scope": {"holder": "h2oai-h2o-3", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/h2oai/h2o-3/blob/dd62aaa1e7f680a8b16ee14bc66b0fb5195c2ad8/scripts/logscrapedaily.py#L845-L858", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:h2oai-h2o-3:update_summary_file-60a8b9c8a9@held-out", "question": "Concatecate all log file into a summary text file to be sent to users\n at the end of a daily log scraping.\n\n :return: none", "scope": {"holder": "h2oai-h2o-3", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/h2oai/h2o-3/blob/dd62aaa1e7f680a8b16ee14bc66b0fb5195c2ad8/h2o-py/h2o/model/model_base.py#L77-L89", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:h2oai-h2o-3:ModelBase.actual_params-f7bec5673c@held-out", "question": "Dictionary of actual parameters of the model.", "scope": {"holder": "h2oai-h2o-3", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/h2oai/h2o-3/blob/dd62aaa1e7f680a8b16ee14bc66b0fb5195c2ad8/h2o-py/h2o/model/model_base.py#L801-L821", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:h2oai-h2o-3:ModelBase.download_mojo-4bc6e6b4ea@held-out", "question": "Download the model in MOJO format.\n\n :param path: the path where MOJO file should be saved.\n :param get_genmodel_jar: if True, then also download h2o-genmodel.jar and store it in folder ``path``.\n :param genmodel_name Custom name of genmodel jar\n :returns: name of the MOJO file written.", "scope": {"holder": "h2oai-h2o-3", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/h2oai/h2o-3/blob/dd62aaa1e7f680a8b16ee14bc66b0fb5195c2ad8/h2o-py/h2o/model/model_base.py#L823-L838", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:h2oai-h2o-3:ModelBase.save_mojo-c9657427fd@held-out", "question": "Save an H2O Model as MOJO (Model Object, Optimized) to disk.\n\n :param model: The model object to save.\n :param path: a path to save the model at (hdfs, s3, local)\n :param force: if True overwrite destination directory in case it exists, or throw exception if set to False.\n\n :returns str: the path of the saved model", "scope": {"holder": "h2oai-h2o-3", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/h2oai/h2o-3/blob/dd62aaa1e7f680a8b16ee14bc66b0fb5195c2ad8/h2o-py/h2o/model/model_base.py#L840-L853", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:h2oai-h2o-3:ModelBase.save_model_details-d5a2fdbac7@held-out", "question": "Save Model Details of an H2O Model in JSON Format to disk.\n\n :param model: The model object to save.\n :param path: a path to save the model details at (hdfs, s3, local)\n :param force: if True overwrite destination directory in case it exists, or throw exception if set to False.\n\n :returns str: the path of the saved model details", "scope": {"holder": "h2oai-h2o-3", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/h2oai/h2o-3/blob/dd62aaa1e7f680a8b16ee14bc66b0fb5195c2ad8/h2o-py/h2o/model/model_base.py#L1095-L1178", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:h2oai-h2o-3:ModelBase.varimp_plot-c494cae6a5@held-out", "question": "Plot the variable importance for a trained model.\n\n :param num_of_features: the number of features shown in the plot (default is 10 or all if less than 10).\n :param server: ?\n\n :returns: None.", "scope": {"holder": "h2oai-h2o-3", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/h2oai/h2o-3/blob/dd62aaa1e7f680a8b16ee14bc66b0fb5195c2ad8/h2o-py/h2o/two_dim_table.py#L45-L62", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:h2oai-h2o-3:H2OTwoDimTable.make-de75a0835e@held-out", "question": "Create new H2OTwoDimTable object from list of (key,value) tuples which are a pre-cursor to JSON dict.\n\n :param keyvals: list of (key, value) tuples\n :return: new H2OTwoDimTable object", "scope": {"holder": "h2oai-h2o-3", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/h2oai/h2o-3/blob/dd62aaa1e7f680a8b16ee14bc66b0fb5195c2ad8/h2o-py/h2o/backend/server.py#L231-L263", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:h2oai-h2o-3:H2OLocalServer._jar_paths-6e9dd7768e@held-out", "question": "Produce potential paths for an h2o.jar executable.", "scope": {"holder": "h2oai-h2o-3", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/h2oai/h2o-3/blob/dd62aaa1e7f680a8b16ee14bc66b0fb5195c2ad8/h2o-py/h2o/backend/server.py#L414-L435", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:h2oai-h2o-3:H2OLocalServer._tmp_file-b790487e43@held-out", "question": "Generate names for temporary files (helper method for `._launch_server()`).\n\n :param kind: one of \"stdout\", \"stderr\" or \"salt\". The \"salt\" kind is used for process name, not for a\n file, so it doesn't contain a path. All generated names are based on the user name of the currently\n logged-in user.", "scope": {"holder": "h2oai-h2o-3", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/h2oai/h2o-3/blob/dd62aaa1e7f680a8b16ee14bc66b0fb5195c2ad8/h2o-docs/src/product/sphinxext/apigen.py#L172-L191", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:h2oai-h2o-3:ApiDocWriter._parse_lines-074cbe1b66@held-out", "question": "Parse lines of text for functions and classes", "scope": {"holder": "h2oai-h2o-3", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/h2oai/h2o-3/blob/dd62aaa1e7f680a8b16ee14bc66b0fb5195c2ad8/h2o-docs/src/product/sphinxext/apigen.py#L268-L307", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:h2oai-h2o-3:ApiDocWriter._survives_exclude-fd8c824695@held-out", "question": "Returns True if *matchstr* does not match patterns\n\n ``self.package_name`` removed from front of string if present\n\n Examples\n --------\n >>> dw = ApiDocWriter('sphinx')\n >>> dw._survives_exclude('sphinx.okpkg', 'package')\n True\n >>> dw.package_skip_patterns.append('^\\\\.badpkg$')\n >>> dw._survives_exclude('sphinx.badpkg', 'package')\n False\n >>> dw._survives_exclude('sphinx.badpkg', 'module')\n True\n >>> dw._survives_exclude('sphinx.badmod', 'module')\n True\n >>> dw.module_skip_patterns.append('^\\\\.badmod$')\n >>> dw._survives_exclude('sphinx.badmod', 'module')\n False", "scope": {"holder": "h2oai-h2o-3", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/h2oai/h2o-3/blob/dd62aaa1e7f680a8b16ee14bc66b0fb5195c2ad8/scripts/jira.py#L313-L337", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:h2oai-h2o-3:main-4c28c32a82@held-out", "question": "Main program.\n\n @return: none", "scope": {"holder": "h2oai-h2o-3", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/h2oai/h2o-3/blob/dd62aaa1e7f680a8b16ee14bc66b0fb5195c2ad8/scripts/addjavamessage2ignore.py#L87-L101", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:h2oai-h2o-3:load_dict-73a8b7859e@held-out", "question": "Load java messages that can be ignored pickle file into a dict structure g_ok_java_messages.\n\n :return: none", "scope": {"holder": "h2oai-h2o-3", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/h2oai/h2o-3/blob/dd62aaa1e7f680a8b16ee14bc66b0fb5195c2ad8/scripts/addjavamessage2ignore.py#L273-L285", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:h2oai-h2o-3:save_dict-d0208fccef@held-out", "question": "Save the ignored java message dict stored in g_ok_java_messages into a pickle file for future use.\n\n :return: none", "scope": {"holder": "h2oai-h2o-3", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/h2oai/h2o-3/blob/dd62aaa1e7f680a8b16ee14bc66b0fb5195c2ad8/h2o-py/h2o/estimators/pca.py#L289-L301", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:h2oai-h2o-3:H2OPrincipalComponentAnalysisEstimator.init_for_pipeline-d29beb18f7@held-out", "question": "Returns H2OPCA object which implements fit and transform method to be used in sklearn.Pipeline properly.\n All parameters defined in self.__params, should be input parameters in H2OPCA.__init__ method.\n\n :returns: H2OPCA object", "scope": {"holder": "h2oai-h2o-3", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/h2oai/h2o-3/blob/dd62aaa1e7f680a8b16ee14bc66b0fb5195c2ad8/h2o-py/h2o/model/metrics_base.py#L510-L524", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:h2oai-h2o-3:H2OBinomialModelMetrics.metric-16c2b7bf4c@held-out", "question": ":param str metric: The desired metric.\n :param thresholds: thresholds parameter must be a list (i.e. [0.01, 0.5, 0.99]). If None, then\n the thresholds in this set of metrics will be used.\n :returns: The set of metrics for the list of thresholds.", "scope": {"holder": "h2oai-h2o-3", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/h2oai/h2o-3/blob/dd62aaa1e7f680a8b16ee14bc66b0fb5195c2ad8/h2o-bindings/bin/bindings.py#L458-L505", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:h2oai-h2o-3:_request_or_exit-ed4eb51d5d@held-out", "question": "Internal function: retrieve and return json data from the provided endpoint, or die with an error message if the\n URL cannot be retrieved.", "scope": {"holder": "h2oai-h2o-3", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/h2oai/h2o-3/blob/dd62aaa1e7f680a8b16ee14bc66b0fb5195c2ad8/h2o-bindings/bin/gen_thrift.py#L32-L52", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:h2oai-h2o-3:add_schema_to_dependency_array-06a7891759@held-out", "question": "This is a helper function to order all schemas according to their usage. For example, if schema A uses schemas B\n and C, then they should be reordered as {B, C, A}.\n :param schema: schema object that we are processing right now\n :param ordered_schemas: an OrderedDict of schemas that were already encountered. This is also the \"output\"\n variable -- all schemas/enums that are needed will be recorded here in the correct order of their supposed\n declaration.\n :param schemas_map: dictionary(schemaname => schemaobject)", "scope": {"holder": "h2oai-h2o-3", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/instagrambot/instabot/blob/d734f892ac4cc35d22746a4f2680425ffaff0927/instabot/bot/bot_direct.py#L128-L157", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:instagrambot-instabot:send_profile-adb9aa34f7@held-out", "question": ":param profile_user_id: profile_id\n :param self: bot\n :param text: text of message\n :param user_ids: list of user_ids for creating group or one user_id for send to one person\n :param thread_id: thread_id", "scope": {"holder": "instagrambot-instabot", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/instagrambot/instabot/blob/d734f892ac4cc35d22746a4f2680425ffaff0927/instabot/api/api.py#L849-L866", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:instagrambot-instabot:API.get_users_reel-0c671e062e@held-out", "question": "Input: user_ids - a list of user_id\n Output: dictionary: user_id - stories data.\n Basically, for each user output the same as after self.get_user_reel", "scope": {"holder": "instagrambot-instabot", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/kennethreitz/twitter-scraper/blob/6e5631ab478e1066f6cb1bb9e9633d4928f6a550/twitter_scraper.py#L8-L115", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:kennethreitz-twitter-scraper:get_tweets-cf8d9cdc60@held-out", "question": "Gets tweets for a given user, via the Twitter frontend API.", "scope": {"holder": "kennethreitz-twitter-scraper", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Azure/azure-sdk-for-python/blob/d7306fde32f60a293a7567678692bdad31e4b667/azure-mgmt-compute/azure/mgmt/compute/compute_management_client.py#L423-L457", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Azure-azure-sdk-for-python:ComputeManagementClient.usage-296a239d07@held-out", "question": "Instance depends on the API version:\n\n * 2015-06-15: :class:`UsageOperations<azure.mgmt.compute.v2015_06_15.operations.UsageOperations>`\n * 2016-03-30: :class:`UsageOperations<azure.mgmt.compute.v2016_03_30.operations.UsageOperations>`\n * 2016-04-30-preview: :class:`UsageOperations<azure.mgmt.compute.v2016_04_30_preview.operations.UsageOperations>`\n * 2017-03-30: :class:`UsageOperations<azure.mgmt.compute.v2017_03_30.operations.UsageOperations>`\n * 2017-12-01: :class:`UsageOperations<azure.mgmt.compute.v2017_12_01.operations.UsageOperations>`\n * 2018-04-01: :class:`UsageOperations<azure.mgmt.compute.v2018_04_01.operations.UsageOperations>`\n * 2018-06-01: :class:`UsageOperations<azure.mgmt.compute.v2018_06_01.operations.UsageOperations>`\n * 2018-10-01: :class:`UsageOperations<azure.mgmt.compute.v2018_10_01.operations.UsageOperations>`\n * 2019-03-01: :class:`UsageOperations<azure.mgmt.compute.v2019_03_01.operations.UsageOperations>`", "scope": {"holder": "Azure-azure-sdk-for-python", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Azure/azure-sdk-for-python/blob/d7306fde32f60a293a7567678692bdad31e4b667/azure-servicebus/azure/servicebus/control_client/_http/httpclient.py#L64-L80", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Azure-azure-sdk-for-python:_HTTPClient.set_proxy-33deceede2@held-out", "question": "Sets the proxy server host and port for the HTTP CONNECT Tunnelling.\n\n host:\n Address of the proxy. Ex: '192.168.0.100'\n port:\n Port of the proxy. Ex: 6000\n user:\n User for proxy authorization.\n password:\n Password for proxy authorization.", "scope": {"holder": "Azure-azure-sdk-for-python", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Azure/azure-sdk-for-python/blob/d7306fde32f60a293a7567678692bdad31e4b667/azure-mgmt-eventhub/azure/mgmt/eventhub/event_hub_management_client.py#L170-L180", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Azure-azure-sdk-for-python:EventHubManagementClient.disaster_recovery_configs-7420ac41b4@held-out", "question": "Instance depends on the API version:\n\n * 2017-04-01: :class:`DisasterRecoveryConfigsOperations<azure.mgmt.eventhub.v2017_04_01.operations.DisasterRecoveryConfigsOperations>`", "scope": {"holder": "Azure-azure-sdk-for-python", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Azure/azure-sdk-for-python/blob/d7306fde32f60a293a7567678692bdad31e4b667/azure-mgmt-frontdoor/azure/mgmt/frontdoor/front_door_management_client.py#L126-L188", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Azure-azure-sdk-for-python:FrontDoorManagementClient.check_front_door_name_availability-b0a31c2f0f@held-out", "question": "Check the availability of a Front Door resource name.\n\n :param name: The resource name to validate.\n :type name: str\n :param type: The type of the resource whose name is to be validated.\n Possible values include: 'Microsoft.Network/frontDoors',\n 'Microsoft.Network/frontDoors/frontendEndpoints'\n :type type: str or ~azure.mgmt.frontdoor.models.ResourceType\n :param dict custom_headers: headers that will be added to the request\n :param bool raw: returns the direct response alongside the\n deserialized response\n :param operation_config: :ref:`Operation configuration\n overrides<msrest:optionsforoperations>`.\n :return: CheckNameAvailabilityOutput or ClientRawResponse if raw=true\n :rtype: ~azure.mgmt.frontdoor.models.CheckNameAvailabilityOutput or\n ~msrest.pipeline.ClientRawResponse\n :raises:\n :class:`ErrorResponseException<azure.mgmt.frontdoor.models.ErrorResponseException>`", "scope": {"holder": "Azure-azure-sdk-for-python", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Azure/azure-sdk-for-python/blob/d7306fde32f60a293a7567678692bdad31e4b667/azure-mgmt-keyvault/azure/mgmt/keyvault/v2016_10_01/operations/vaults_operations.py#L718-L757", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Azure-azure-sdk-for-python:VaultsOperations.purge_deleted-249d0f5a5d@held-out", "question": "Permanently deletes the specified vault. aka Purges the deleted Azure\n key vault.\n\n :param vault_name: The name of the soft-deleted vault.\n :type vault_name: str\n :param location: The location of the soft-deleted vault.\n :type location: str\n :param dict custom_headers: headers that will be added to the request\n :param bool raw: The poller return type is ClientRawResponse, the\n direct response alongside the deserialized response\n :param polling: True for ARMPolling, False for no polling, or a\n polling object for personal polling strategy\n :return: An instance of LROPoller that returns None or\n ClientRawResponse<None> if raw==True\n :rtype: ~msrestazure.azure_operation.AzureOperationPoller[None] or\n ~msrestazure.azure_operation.AzureOperationPoller[~msrest.pipeline.ClientRawResponse[None]]\n :raises: :class:`CloudError<msrestazure.azure_exceptions.CloudError>`", "scope": {"holder": "Azure-azure-sdk-for-python", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Azure/azure-sdk-for-python/blob/d7306fde32f60a293a7567678692bdad31e4b667/azure-keyvault/azure/keyvault/http_challenge.py#L103-L115", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Azure-azure-sdk-for-python:HttpChallenge._validate_request_uri-d227a45e67@held-out", "question": "Extracts the host authority from the given URI.", "scope": {"holder": "Azure-azure-sdk-for-python", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Azure/azure-sdk-for-python/blob/d7306fde32f60a293a7567678692bdad31e4b667/azure-mgmt-alertsmanagement/azure/mgmt/alertsmanagement/operations/alerts_operations.py#L393-L521", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Azure-azure-sdk-for-python:AlertsOperations.get_summary-b3bd9ca0bf@held-out", "question": "Summary of alerts with the count each severity.\n\n :param groupby: This parameter allows the result set to be aggregated\n by input fields. For example, groupby=severity,alertstate. Possible\n values include: 'severity', 'alertState', 'monitorCondition',\n 'monitorService', 'signalType', 'alertRule'\n :type groupby: str or\n ~azure.mgmt.alertsmanagement.models.AlertsSummaryGroupByFields\n :param include_smart_groups_count: Include count of the SmartGroups as\n part of the summary. Default value is 'false'.\n :type include_smart_groups_count: bool\n :param target_resource: Filter by target resource( which is full ARM\n ID) Default value is select all.\n :type target_resource: str\n :param target_resource_type: Filter by target resource type. Default\n value is select all.\n :type target_resource_type: str\n :param target_resource_group: Filter by target resource group name.\n Default value is select all.\n :type target_resource_group: str\n :param monitor_service: Filter by monitor service which is the source\n of the alert instance. Default value is select all. Possible values\n include: 'Application Insights', 'ActivityLog Administrative',\n 'ActivityLog Security', 'ActivityLog Recommendation', 'ActivityLog\n Policy', 'ActivityLog Autoscale', 'Log Analytics', 'Nagios',\n 'Platform', 'SCOM', 'ServiceHealth', 'SmartDetector', 'VM Insights',\n 'Zabbix'\n :type monitor_service: str or\n ~azure.mgmt.alertsmanagement.models.MonitorService\n :param monitor_condition: Filter by monitor condition which is the\n state of the monitor(alertRule) at monitor service. Default value is\n to select all. Possible values include: 'Fired', 'Resolved'\n :type monitor_condition: str or\n ~azure.mgmt.alertsmanagement.models.MonitorCondition\n :param severity: Filter by severity. Defaut value is select all.\n Possible values include: 'Sev0', 'Sev1', 'Sev2', 'Sev3', 'Sev4'\n :type severity: str or ~azure.mgmt.alertsmanagement.models.Severity\n :param alert_state: Filter by state of the alert instance. Default\n value is to select all. Possible values include: 'New',\n 'Acknowledged', 'Closed'\n :type alert_state: str or\n ~azure.mgmt.alertsmanagement.models.AlertState\n :param alert_rule: Filter by alert rule(monitor) which fired alert\n instance. Default value is to select all.\n :type alert_rule: str\n :param time_range: Filter by time range by below listed values.\n Default value is 1 day. Possible values include: '1h', '1d', '7d',\n '30d'\n :type time_range: str or ~azure.mgmt.alertsmanagement.models.TimeRange\n :param custom_time_range: Filter by custom time range in the format\n <start-time>/<end-time> where time is in (ISO-8601 format)'.\n Permissible values is within 30 days from query time. Either\n timeRange or customTimeRange could be used but not both. Default is\n none.\n :type custom_time_range: str\n :param dict custom_headers: headers that will be added to the request\n :param bool raw: returns the direct response alongside the\n deserialized response\n :param operation_config: :ref:`Operation configuration\n overrides<msrest:optionsforoperations>`.\n :return: AlertsSummary or ClientRawResponse if raw=true\n :rtype: ~azure.mgmt.alertsmanagement.models.AlertsSummary or\n ~msrest.pipeline.ClientRawResponse\n :raises:\n :class:`ErrorResponseException<azure.mgmt.alertsmanagement.models.ErrorResponseException>`", "scope": {"holder": "Azure-azure-sdk-for-python", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Azure/azure-sdk-for-python/blob/d7306fde32f60a293a7567678692bdad31e4b667/azure-cognitiveservices-vision-face/azure/cognitiveservices/vision/face/operations/snapshot_operations.py#L366-L463", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Azure-azure-sdk-for-python:SnapshotOperations.apply-692e251edc@held-out", "question": "Submit an operation to apply a snapshot to current subscription. For\n each snapshot, only subscriptions included in the applyScope of\n Snapshot - Take can apply it.<br />\n The snapshot interfaces are for users to backup and restore their face\n data from one face subscription to another, inside same region or\n across regions. The workflow contains two phases, user first calls\n Snapshot - Take to create a copy of the source object and store it as a\n snapshot, then calls Snapshot - Apply to paste the snapshot to target\n subscription. The snapshots are stored in a centralized location (per\n Azure instance), so that they can be applied cross accounts and\n regions.<br />\n Applying snapshot is an asynchronous operation. An operation id can be\n obtained from the \"Operation-Location\" field in response header, to be\n used in OperationStatus - Get for tracking the progress of applying the\n snapshot. The target object id will be included in the\n \"resourceLocation\" field in OperationStatus - Get response when the\n operation status is \"succeeded\".<br />\n Snapshot applying time depends on the number of person and face entries\n in the snapshot object. It could be in seconds, or up to 1 hour for\n 1,000,000 persons with multiple faces.<br />\n Snapshots will be automatically expired and cleaned in 48 hours after\n it is created by Snapshot - Take. So the target subscription is\n required to apply the snapshot in 48 hours since its creation.<br />\n Applying a snapshot will not block any other operations against the\n target object, however it is not recommended because the correctness\n cannot be guaranteed during snapshot applying. After snapshot applying\n is completed, all operations towards the target object can work as\n normal. Snapshot also includes the training results of the source\n object, which means target subscription the snapshot applied to does\n not need re-train the target object before calling\n Identify/FindSimilar.<br />\n One snapshot can be applied multiple times in parallel, while currently\n only CreateNew apply mode is supported, which means the apply operation\n will fail if target subscription already contains an object of same\n type and using the same objectId. Users can specify the \"objectId\" in\n request body to avoid such conflicts.<br />\n * Free-tier subscription quota: 100 apply operations per month.\n * S0-tier subscription quota: 100 apply operations per day.\n\n :param snapshot_id: Id referencing a particular snapshot.\n :type snapshot_id: str\n :param object_id: User specified target object id to be created from\n the snapshot.\n :type object_id: str\n :param mode: Snapshot applying mode. Currently only CreateNew is\n supported, which means the apply operation will fail if target\n subscription already contains an object of same type and using the\n same objectId. Users can specify the \"objectId\" in request body to\n avoid such conflicts. Possible values include: 'CreateNew'\n :type mode: str or\n ~azure.cognitiveservices.vision.face.models.SnapshotApplyMode\n :param dict custom_headers: headers that will be added to the request\n :param bool raw: returns the direct response alongside the\n deserialized response\n :param operation_config: :ref:`Operation configuration\n overrides<msrest:optionsforoperations>`.\n :return: None or ClientRawResponse if raw=true\n :rtype: None or ~msrest.pipeline.ClientRawResponse\n :raises:\n :class:`APIErrorException<azure.cognitiveservices.vision.face.models.APIErrorException>`", "scope": {"holder": "Azure-azure-sdk-for-python", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Azure/azure-sdk-for-python/blob/d7306fde32f60a293a7567678692bdad31e4b667/azure-cognitiveservices-search-imagesearch/azure/cognitiveservices/search/imagesearch/operations/images_operations.py#L900-L1159", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Azure-azure-sdk-for-python:ImagesOperations.trending-e3f4feb94b@held-out", "question": "The Image Trending Search API lets you search on Bing and get back a\n list of images that are trending based on search requests made by\n others. The images are broken out into different categories. For\n example, Popular People Searches. For a list of markets that support\n trending images, see [Trending\n Images](https://docs.microsoft.com/en-us/azure/cognitive-services/bing-image-search/trending-images).\n\n :param accept_language: A comma-delimited list of one or more\n languages to use for user interface strings. The list is in decreasing\n order of preference. For additional information, including expected\n format, see\n [RFC2616](http://www.w3.org/Protocols/rfc2616/rfc2616-sec14.html).\n This header and the\n [setLang](https://docs.microsoft.com/en-us/rest/api/cognitiveservices/bing-images-api-v7-reference#setlang)\n query parameter are mutually exclusive; do not specify both. If you\n set this header, you must also specify the\n [cc](https://docs.microsoft.com/en-us/rest/api/cognitiveservices/bing-images-api-v7-reference#cc)\n query parameter. To determine the market to return results for, Bing\n uses the first supported language it finds from the list and combines\n it with the cc parameter value. If the list does not include a\n supported language, Bing finds the closest language and market that\n supports the request or it uses an aggregated or default market for\n the results. To determine the market that Bing used, see the\n BingAPIs-Market header. Use this header and the cc query parameter\n only if you specify multiple languages. Otherwise, use the\n [mkt](https://docs.microsoft.com/en-us/rest/api/cognitiveservices/bing-images-api-v7-reference#mkt)\n and\n [setLang](https://docs.microsoft.com/en-us/rest/api/cognitiveservices/bing-images-api-v7-reference#setlang)\n query parameters. A user interface string is a string that's used as a\n label in a user interface. There are few user interface strings in the\n JSON response objects. Any links to Bing.com properties in the\n response objects apply the specified language.\n :type accept_language: str\n :param user_agent: The user agent originating the request. Bing uses\n the user agent to provide mobile users with an optimized experience.\n Although optional, you are encouraged to always specify this header.\n The user-agent should be the same string that any commonly used\n browser sends. For information about user agents, see [RFC\n 2616](http://www.w3.org/Protocols/rfc2616/rfc2616-sec14.html). The\n following are examples of user-agent strings. Windows Phone:\n Mozilla/5.0 (compatible; MSIE 10.0; Windows Phone 8.0; Trident/6.0;\n IEMobile/10.0; ARM; Touch; NOKIA; Lumia 822). Android: Mozilla / 5.0\n (Linux; U; Android 2.3.5; en - us; SCH - I500 Build / GINGERBREAD)\n AppleWebKit / 533.1 (KHTML; like Gecko) Version / 4.0 Mobile Safari /\n 533.1. iPhone: Mozilla / 5.0 (iPhone; CPU iPhone OS 6_1 like Mac OS X)\n AppleWebKit / 536.26 (KHTML; like Gecko) Mobile / 10B142 iPhone4; 1\n BingWeb / 3.03.1428.20120423. PC: Mozilla / 5.0 (Windows NT 6.3;\n WOW64; Trident / 7.0; Touch; rv:11.0) like Gecko. iPad: Mozilla / 5.0\n (iPad; CPU OS 7_0 like Mac OS X) AppleWebKit / 537.51.1 (KHTML, like\n Gecko) Version / 7.0 Mobile / 11A465 Safari / 9537.53\n :type user_agent: str\n :param client_id: Bing uses this header to provide users with\n consistent behavior across Bing API calls. Bing often flights new\n features and improvements, and it uses the client ID as a key for\n assigning traffic on different flights. If you do not use the same\n client ID for a user across multiple requests, then Bing may assign\n the user to multiple conflicting flights. Being assigned to multiple\n conflicting flights can lead to an inconsistent user experience. For\n example, if the second request has a different flight assignment than\n the first, the experience may be unexpected. Also, Bing can use the\n client ID to tailor web results to that client ID’s search history,\n providing a richer experience for the user. Bing also uses this header\n to help improve result rankings by analyzing the activity generated by\n a client ID. The relevance improvements help with better quality of\n results delivered by Bing APIs and in turn enables higher\n click-through rates for the API consumer. IMPORTANT: Although\n optional, you should consider this header required. Persisting the\n client ID across multiple requests for the same end user and device\n combination enables 1) the API consumer to receive a consistent user\n experience, and 2) higher click-through rates via better quality of\n results from the Bing APIs. Each user that uses your application on\n the device must have a unique, Bing generated client ID. If you do not\n include this header in the request, Bing generates an ID and returns\n it in the X-MSEdge-ClientID response header. The only time that you\n should NOT include this header in a request is the first time the user\n uses your app on that device. Use the client ID for each Bing API\n request that your app makes for this user on the device. Persist the\n client ID. To persist the ID in a browser app, use a persistent HTTP\n cookie to ensure the ID is used across all sessions. Do not use a\n session cookie. For other apps such as mobile apps, use the device's\n persistent storage to persist the ID. The next time the user uses your\n app on that device, get the client ID that you persisted. Bing\n responses may or may not include this header. If the response includes\n this header, capture the client ID and use it for all subsequent Bing\n requests for the user on that device. If you include the\n X-MSEdge-ClientID, you must not include cookies in the request.\n :type client_id: str\n :param client_ip: The IPv4 or IPv6 address of the client device. The\n IP address is used to discover the user's location. Bing uses the\n location information to determine safe search behavior. Although\n optional, you are encouraged to always specify this header and the\n X-Search-Location header. Do not obfuscate the address (for example,\n by changing the last octet to 0). Obfuscating the address results in\n the location not being anywhere near the device's actual location,\n which may result in Bing serving erroneous results.\n :type client_ip: str\n :param location: A semicolon-delimited list of key/value pairs that\n describe the client's geographical location. Bing uses the location\n information to determine safe search behavior and to return relevant\n local content. Specify the key/value pair as <key>:<value>. The\n following are the keys that you use to specify the user's location.\n lat (required): The latitude of the client's location, in degrees. The\n latitude must be greater than or equal to -90.0 and less than or equal\n to +90.0. Negative values indicate southern latitudes and positive\n values indicate northern latitudes. long (required): The longitude of\n the client's location, in degrees. The longitude must be greater than\n or equal to -180.0 and less than or equal to +180.0. Negative values\n indicate western longitudes and positive values indicate eastern\n longitudes. re (required): The radius, in meters, which specifies the\n horizontal accuracy of the coordinates. Pass the value returned by the\n device's location service. Typical values might be 22m for GPS/Wi-Fi,\n 380m for cell tower triangulation, and 18,000m for reverse IP lookup.\n ts (optional): The UTC UNIX timestamp of when the client was at the\n location. (The UNIX timestamp is the number of seconds since January\n 1, 1970.) head (optional): The client's relative heading or direction\n of travel. Specify the direction of travel as degrees from 0 through\n 360, counting clockwise relative to true north. Specify this key only\n if the sp key is nonzero. sp (optional): The horizontal velocity\n (speed), in meters per second, that the client device is traveling.\n alt (optional): The altitude of the client device, in meters. are\n (optional): The radius, in meters, that specifies the vertical\n accuracy of the coordinates. Specify this key only if you specify the\n alt key. Although many of the keys are optional, the more information\n that you provide, the more accurate the location results are. Although\n optional, you are encouraged to always specify the user's geographical\n location. Providing the location is especially important if the\n client's IP address does not accurately reflect the user's physical\n location (for example, if the client uses VPN). For optimal results,\n you should include this header and the X-MSEdge-ClientIP header, but\n at a minimum, you should include this header.\n :type location: str\n :param country_code: A 2-character country code of the country where\n the results come from. This API supports only the United States,\n Canada, Australia, and China markets. If you specify this query\n parameter, it must be set to us, ca, au, or cn. If you set this\n parameter, you must also specify the Accept-Language header. Bing uses\n the first supported language it finds from the languages list, and\n combine that language with the country code that you specify to\n determine the market to return results for. If the languages list does\n not include a supported language, Bing finds the closest language and\n market that supports the request, or it may use an aggregated or\n default market for the results instead of a specified one. You should\n use this query parameter and the Accept-Language query parameter only\n if you specify multiple languages; otherwise, you should use the mkt\n and setLang query parameters. This parameter and the mkt query\n parameter are mutually exclusive—do not specify both.\n :type country_code: str\n :param market: The market where the results come from. Typically, mkt\n is the country where the user is making the request from. However, it\n could be a different country if the user is not located in a country\n where Bing delivers results. The market must be in the form <language\n code>-<country code>. For example, en-US. The string is case\n insensitive. For a list of possible market values, see [Market\n Codes](https://docs.microsoft.com/en-us/rest/api/cognitiveservices/bing-images-api-v7-reference#market-codes).\n NOTE: If known, you are encouraged to always specify the market.\n Specifying the market helps Bing route the request and return an\n appropriate and optimal response. If you specify a market that is not\n listed in [Market\n Codes](https://docs.microsoft.com/en-us/rest/api/cognitiveservices/bing-images-api-v7-reference#market-codes),\n Bing uses a best fit market code based on an internal mapping that is\n subject to change. This parameter and the\n [cc](https://docs.microsoft.com/en-us/rest/api/cognitiveservices/bing-images-api-v7-reference#cc)\n query parameter are mutually exclusive—do not specify both.\n :type market: str\n :param safe_search: Filter images for adult content. The following are\n the possible filter values. Off: May return images with adult content.\n If the request is through the Image Search API, the response includes\n thumbnail images that are clear (non-fuzzy). However, if the request\n is through the Web Search API, the response includes thumbnail images\n that are pixelated (fuzzy). Moderate: If the request is through the\n Image Search API, the response doesn't include images with adult\n content. If the request is through the Web Search API, the response\n may include images with adult content (the thumbnail images are\n pixelated (fuzzy)). Strict: Do not return images with adult content.\n The default is Moderate. If the request comes from a market that\n Bing's adult policy requires that safeSearch is set to Strict, Bing\n ignores the safeSearch value and uses Strict. If you use the site:\n query operator, there is the chance that the response may contain\n adult content regardless of what the safeSearch query parameter is set\n to. Use site: only if you are aware of the content on the site and\n your scenario supports the possibility of adult content. Possible\n values include: 'Off', 'Moderate', 'Strict'\n :type safe_search: str or\n ~azure.cognitiveservices.search.imagesearch.models.SafeSearch\n :param set_lang: The language to use for user interface strings.\n Specify the language using the ISO 639-1 2-letter language code. For\n example, the language code for English is EN. The default is EN\n (English). Although optional, you should always specify the language.\n Typically, you set setLang to the same language specified by mkt\n unless the user wants the user interface strings displayed in a\n different language. This parameter and the\n [Accept-Language](https://docs.microsoft.com/en-us/rest/api/cognitiveservices/bing-images-api-v7-reference#acceptlanguage)\n header are mutually exclusive; do not specify both. A user interface\n string is a string that's used as a label in a user interface. There\n are few user interface strings in the JSON response objects. Also, any\n links to Bing.com properties in the response objects apply the\n specified language.\n :type set_lang: str\n :param dict custom_headers: headers that will be added to the request\n :param bool raw: returns the direct response alongside the\n deserialized response\n :param operation_config: :ref:`Operation configuration\n overrides<msrest:optionsforoperations>`.\n :return: TrendingImages or ClientRawResponse if raw=true\n :rtype:\n ~azure.cognitiveservices.search.imagesearch.models.TrendingImages or\n ~msrest.pipeline.ClientRawResponse\n :raises:\n :class:`ErrorResponseException<azure.cognitiveservices.search.imagesearch.models.ErrorResponseException>`", "scope": {"holder": "Azure-azure-sdk-for-python", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Azure/azure-sdk-for-python/blob/d7306fde32f60a293a7567678692bdad31e4b667/azure-servicemanagement-legacy/azure/servicemanagement/_http/winhttp.py#L292-L300", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Azure-azure-sdk-for-python:_WinHttpRequest.get_all_response_headers-04bdeb048d@held-out", "question": "Gets back all response headers.", "scope": {"holder": "Azure-azure-sdk-for-python", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Azure/azure-sdk-for-python/blob/d7306fde32f60a293a7567678692bdad31e4b667/azure-servicemanagement-legacy/azure/servicemanagement/_http/winhttp.py#L418-L428", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Azure-azure-sdk-for-python:_HTTPConnection.putrequest-65494997be@held-out", "question": "Connects to host and sends the request.", "scope": {"holder": "Azure-azure-sdk-for-python", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Azure/azure-sdk-for-python/blob/d7306fde32f60a293a7567678692bdad31e4b667/azure-keyvault/azure/keyvault/_internal.py#L114-L120", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Azure-azure-sdk-for-python:_bstr_to_b64url-f89f66e5fa@held-out", "question": "Serialize bytes into base-64 string.\n :param str: Object to be serialized.\n :rtype: str", "scope": {"holder": "Azure-azure-sdk-for-python", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Azure/azure-sdk-for-python/blob/d7306fde32f60a293a7567678692bdad31e4b667/azure-keyvault/azure/keyvault/http_bearer_challenge_cache/__init__.py#L34-L46", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Azure-azure-sdk-for-python:remove_challenge_for_url-84a99773ff@held-out", "question": "Removes the cached challenge for the specified URL.\n :param url: the URL for which to remove the cached challenge", "scope": {"holder": "Azure-azure-sdk-for-python", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Azure/azure-sdk-for-python/blob/d7306fde32f60a293a7567678692bdad31e4b667/azure-mgmt-authorization/azure/mgmt/authorization/authorization_management_client.py#L149-L159", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Azure-azure-sdk-for-python:AuthorizationManagementClient.deny_assignments-1f2dd70ef9@held-out", "question": "Instance depends on the API version:\n\n * 2018-07-01-preview: :class:`DenyAssignmentsOperations<azure.mgmt.authorization.v2018_07_01_preview.operations.DenyAssignmentsOperations>`", "scope": {"holder": "Azure-azure-sdk-for-python", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Azure/azure-sdk-for-python/blob/d7306fde32f60a293a7567678692bdad31e4b667/azure-mgmt-authorization/azure/mgmt/authorization/authorization_management_client.py#L178-L191", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Azure-azure-sdk-for-python:AuthorizationManagementClient.provider_operations_metadata-c283e171cc@held-out", "question": "Instance depends on the API version:\n\n * 2015-07-01: :class:`ProviderOperationsMetadataOperations<azure.mgmt.authorization.v2015_07_01.operations.ProviderOperationsMetadataOperations>`\n * 2018-01-01-preview: :class:`ProviderOperationsMetadataOperations<azure.mgmt.authorization.v2018_01_01_preview.operations.ProviderOperationsMetadataOperations>`", "scope": {"holder": "Azure-azure-sdk-for-python", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Azure/azure-sdk-for-python/blob/d7306fde32f60a293a7567678692bdad31e4b667/azure-servicemanagement-legacy/azure/servicemanagement/_serialization.py#L1559-L1571", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Azure-azure-sdk-for-python:_ServiceBusManagementXmlSerializer.odata_converter-051f53b165@held-out", "question": "Convert odata type\n http://www.odata.org/documentation/odata-version-2-0/overview#AbstractTypeSystem\n To be completed", "scope": {"holder": "Azure-azure-sdk-for-python", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Azure/azure-sdk-for-python/blob/d7306fde32f60a293a7567678692bdad31e4b667/azure-mgmt-resource/azure/mgmt/resource/locks/management_lock_client.py#L124-L137", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Azure-azure-sdk-for-python:ManagementLockClient.management_locks-a89f504f63@held-out", "question": "Instance depends on the API version:\n\n * 2015-01-01: :class:`ManagementLocksOperations<azure.mgmt.resource.locks.v2015_01_01.operations.ManagementLocksOperations>`\n * 2016-09-01: :class:`ManagementLocksOperations<azure.mgmt.resource.locks.v2016_09_01.operations.ManagementLocksOperations>`", "scope": {"holder": "Azure-azure-sdk-for-python", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Azure/azure-sdk-for-python/blob/d7306fde32f60a293a7567678692bdad31e4b667/azure-servicebus/azure/servicebus/aio/async_utils.py#L86-L98", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Azure-azure-sdk-for-python:AutoLockRenew.register-94bb687222@held-out", "question": "Register a renewable entity for automatic lock renewal.\n\n :param renewable: A locked entity that needs to be renewed.\n :type renewable: ~azure.servicebus.aio.async_message.Message or\n ~azure.servicebus.aio.async_receive_handler.SessionReceiver\n :param timeout: A time in seconds that the lock should be maintained for.\n Default value is 300 (5 minutes).\n :type timeout: int", "scope": {"holder": "Azure-azure-sdk-for-python", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Azure/azure-sdk-for-python/blob/d7306fde32f60a293a7567678692bdad31e4b667/azure-keyvault/azure/keyvault/key_vault_id.py#L135-L145", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Azure-azure-sdk-for-python:KeyVaultId.create_certificate_id-da8a8fcf35@held-out", "question": ":param vault: The vault uri.\n :type vault: str\n :param name: The certificate name.\n :type name: str\n :param version: The certificate version.\n :type version: str\n :rtype: KeyVaultId", "scope": {"holder": "Azure-azure-sdk-for-python", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Azure/azure-sdk-for-python/blob/d7306fde32f60a293a7567678692bdad31e4b667/azure-servicebus/azure/servicebus/aio/async_message.py#L102-L117", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Azure-azure-sdk-for-python:Message.abandon-b4b54c1ce9@held-out", "question": "Abandon the message.\n\n This message will be returned to the queue to be reprocessed.\n\n :raises: ~azure.servicebus.common.errors.MessageAlreadySettled if the message has been settled.\n :raises: ~azure.servicebus.common.errors.MessageLockExpired if message lock has already expired.\n :raises: ~azure.servicebus.common.errors.SessionLockExpired if session lock has already expired.\n :raises: ~azure.servicebus.common.errors.MessageSettleFailed if message settle operation fails.", "scope": {"holder": "Azure-azure-sdk-for-python", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Azure/azure-sdk-for-python/blob/d7306fde32f60a293a7567678692bdad31e4b667/azure-servicemanagement-legacy/azure/servicemanagement/servicemanagementservice.py#L152-L170", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Azure-azure-sdk-for-python:ServiceManagementService.regenerate_storage_account_keys-d39ddff804@held-out", "question": "Regenerates the primary or secondary access key for the specified\n storage account.\n\n service_name:\n Name of the storage service account.\n key_type:\n Specifies which key to regenerate. Valid values are:\n Primary, Secondary", "scope": {"holder": "Azure-azure-sdk-for-python", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Azure/azure-sdk-for-python/blob/d7306fde32f60a293a7567678692bdad31e4b667/azure-servicemanagement-legacy/azure/servicemanagement/servicemanagementservice.py#L1090-L1110", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Azure-azure-sdk-for-python:ServiceManagementService.update_affinity_group-6b060edf7b@held-out", "question": "Updates the label and/or the description for an affinity group for the\n specified subscription.\n\n affinity_group_name:\n The name of the affinity group.\n label:\n A name for the affinity group. The name can be up to 100 characters\n in length.\n description:\n A description for the affinity group. The description can be up to\n 1024 characters in length.", "scope": {"holder": "Azure-azure-sdk-for-python", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Azure/azure-sdk-for-python/blob/d7306fde32f60a293a7567678692bdad31e4b667/azure-servicemanagement-legacy/azure/servicemanagement/servicemanagementservice.py#L1813-L1835", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Azure-azure-sdk-for-python:ServiceManagementService.update_dns_server-3470384118@held-out", "question": "Updates the ip address of a DNS server.\n\n service_name:\n The name of the service.\n deployment_name:\n The name of the deployment.\n dns_server_name:\n Specifies the name of the DNS server.\n address:\n Specifies the IP address of the DNS server.", "scope": {"holder": "Azure-azure-sdk-for-python", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Azure/azure-sdk-for-python/blob/d7306fde32f60a293a7567678692bdad31e4b667/azure-mgmt-alertsmanagement/azure/mgmt/alertsmanagement/operations/smart_groups_operations.py#L39-L165", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Azure-azure-sdk-for-python:SmartGroupsOperations.get_all-259e5d3a8f@held-out", "question": "Get all smartGroups within the subscription.\n\n List all the smartGroups within the specified subscription. .\n\n :param target_resource: Filter by target resource( which is full ARM\n ID) Default value is select all.\n :type target_resource: str\n :param target_resource_group: Filter by target resource group name.\n Default value is select all.\n :type target_resource_group: str\n :param target_resource_type: Filter by target resource type. Default\n value is select all.\n :type target_resource_type: str\n :param monitor_service: Filter by monitor service which is the source\n of the alert instance. Default value is select all. Possible values\n include: 'Application Insights', 'ActivityLog Administrative',\n 'ActivityLog Security', 'ActivityLog Recommendation', 'ActivityLog\n Policy', 'ActivityLog Autoscale', 'Log Analytics', 'Nagios',\n 'Platform', 'SCOM', 'ServiceHealth', 'SmartDetector', 'VM Insights',\n 'Zabbix'\n :type monitor_service: str or\n ~azure.mgmt.alertsmanagement.models.MonitorService\n :param monitor_condition: Filter by monitor condition which is the\n state of the monitor(alertRule) at monitor service. Default value is\n to select all. Possible values include: 'Fired', 'Resolved'\n :type monitor_condition: str or\n ~azure.mgmt.alertsmanagement.models.MonitorCondition\n :param severity: Filter by severity. Defaut value is select all.\n Possible values include: 'Sev0', 'Sev1', 'Sev2', 'Sev3', 'Sev4'\n :type severity: str or ~azure.mgmt.alertsmanagement.models.Severity\n :param smart_group_state: Filter by state of the smart group. Default\n value is to select all. Possible values include: 'New',\n 'Acknowledged', 'Closed'\n :type smart_group_state: str or\n ~azure.mgmt.alertsmanagement.models.AlertState\n :param time_range: Filter by time range by below listed values.\n Default value is 1 day. Possible values include: '1h', '1d', '7d',\n '30d'\n :type time_range: str or ~azure.mgmt.alertsmanagement.models.TimeRange\n :param page_count: Determines number of alerts returned per page in\n response. Permissible value is between 1 to 250. When the\n \"includeContent\" filter is selected, maximum value allowed is 25.\n Default value is 25.\n :type page_count: int\n :param sort_by: Sort the query results by input field Default value\n is sort by 'lastModifiedDateTime'. Possible values include:\n 'alertsCount', 'state', 'severity', 'startDateTime',\n 'lastModifiedDateTime'\n :type sort_by: str or\n ~azure.mgmt.alertsmanagement.models.SmartGroupsSortByFields\n :param sort_order: Sort the query results order in either ascending or\n descending. Default value is 'desc' for time fields and 'asc' for\n others. Possible values include: 'asc', 'desc'\n :type sort_order: str\n :param dict custom_headers: headers that will be added to the request\n :param bool raw: returns the direct response alongside the\n deserialized response\n :param operation_config: :ref:`Operation configuration\n overrides<msrest:optionsforoperations>`.\n :return: SmartGroupsList or ClientRawResponse if raw=true\n :rtype: ~azure.mgmt.alertsmanagement.models.SmartGroupsList or\n ~msrest.pipeline.ClientRawResponse\n :raises:\n :class:`ErrorResponseException<azure.mgmt.alertsmanagement.models.ErrorResponseException>`", "scope": {"holder": "Azure-azure-sdk-for-python", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Azure/azure-sdk-for-python/blob/d7306fde32f60a293a7567678692bdad31e4b667/azure-servicebus/azure/servicebus/receive_handler.py#L154-L173", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Azure-azure-sdk-for-python:Receiver._build_receiver-a6c62fc4a5@held-out", "question": "This is a temporary patch pending a fix in uAMQP.", "scope": {"holder": "Azure-azure-sdk-for-python", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Azure/azure-sdk-for-python/blob/d7306fde32f60a293a7567678692bdad31e4b667/azure-servicebus/azure/servicebus/receive_handler.py#L581-L619", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Azure-azure-sdk-for-python:SessionReceiver.peek-6f5ab05545@held-out", "question": "Browse messages currently pending in the queue.\n\n Peeked messages are not removed from queue, nor are they locked. They cannot be completed,\n deferred or dead-lettered.\n This operation will only peek pending messages in the current session.\n\n :param count: The maximum number of messages to try and peek. The default\n value is 1.\n :type count: int\n :param start_from: A message sequence number from which to start browsing messages.\n :type start_from: int\n :rtype: list[~azure.servicebus.common.message.PeekMessage]\n\n Example:\n .. literalinclude:: ../examples/test_examples.py\n :start-after: [START peek_messages]\n :end-before: [END peek_messages]\n :language: python\n :dedent: 4\n :caption: Look at pending messages in the queue", "scope": {"holder": "Azure-azure-sdk-for-python", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Azure/azure-sdk-for-python/blob/d7306fde32f60a293a7567678692bdad31e4b667/azure-mgmt-compute/azure/mgmt/compute/v2019_03_01/operations/virtual_machine_scale_sets_operations.py#L1766-L1829", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Azure-azure-sdk-for-python:VirtualMachineScaleSetsOperations.convert_to_single_placement_group-7dba49b770@held-out", "question": "Converts SinglePlacementGroup property to false for a existing virtual\n machine scale set.\n\n :param resource_group_name: The name of the resource group.\n :type resource_group_name: str\n :param vm_scale_set_name: The name of the virtual machine scale set to\n create or update.\n :type vm_scale_set_name: str\n :param active_placement_group_id: Id of the placement group in which\n you want future virtual machine instances to be placed. To query\n placement group Id, please use Virtual Machine Scale Set VMs - Get\n API. If not provided, the platform will choose one with maximum number\n of virtual machine instances.\n :type active_placement_group_id: str\n :param dict custom_headers: headers that will be added to the request\n :param bool raw: returns the direct response alongside the\n deserialized response\n :param operation_config: :ref:`Operation configuration\n overrides<msrest:optionsforoperations>`.\n :return: None or ClientRawResponse if raw=true\n :rtype: None or ~msrest.pipeline.ClientRawResponse\n :raises: :class:`CloudError<msrestazure.azure_exceptions.CloudError>`", "scope": {"holder": "Azure-azure-sdk-for-python", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Azure/azure-sdk-for-python/blob/d7306fde32f60a293a7567678692bdad31e4b667/azure-mgmt-resource/azure/mgmt/resource/policy/policy_client.py#L127-L152", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Azure-azure-sdk-for-python:PolicyClient.policy_assignments-1b73dce573@held-out", "question": "Instance depends on the API version:\n\n * 2015-10-01-preview: :class:`PolicyAssignmentsOperations<azure.mgmt.resource.policy.v2015_10_01_preview.operations.PolicyAssignmentsOperations>`\n * 2016-04-01: :class:`PolicyAssignmentsOperations<azure.mgmt.resource.policy.v2016_04_01.operations.PolicyAssignmentsOperations>`\n * 2016-12-01: :class:`PolicyAssignmentsOperations<azure.mgmt.resource.policy.v2016_12_01.operations.PolicyAssignmentsOperations>`\n * 2017-06-01-preview: :class:`PolicyAssignmentsOperations<azure.mgmt.resource.policy.v2017_06_01_preview.operations.PolicyAssignmentsOperations>`\n * 2018-03-01: :class:`PolicyAssignmentsOperations<azure.mgmt.resource.policy.v2018_03_01.operations.PolicyAssignmentsOperations>`\n * 2018-05-01: :class:`PolicyAssignmentsOperations<azure.mgmt.resource.policy.v2018_05_01.operations.PolicyAssignmentsOperations>`", "scope": {"holder": "Azure-azure-sdk-for-python", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Azure/azure-sdk-for-python/blob/d7306fde32f60a293a7567678692bdad31e4b667/azure-keyvault/azure/keyvault/v2016_10_01/key_vault_client.py#L311-L393", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Azure-azure-sdk-for-python:KeyVaultClient.update_key-e022f787ec@held-out", "question": "The update key operation changes specified attributes of a stored key\n and can be applied to any key type and key version stored in Azure Key\n Vault.\n\n In order to perform this operation, the key must already exist in the\n Key Vault. Note: The cryptographic material of a key itself cannot be\n changed. This operation requires the keys/update permission.\n\n :param vault_base_url: The vault name, for example\n https://myvault.vault.azure.net.\n :type vault_base_url: str\n :param key_name: The name of key to update.\n :type key_name: str\n :param key_version: The version of the key to update.\n :type key_version: str\n :param key_ops: Json web key operations. For more information on\n possible key operations, see JsonWebKeyOperation.\n :type key_ops: list[str or\n ~azure.keyvault.v2016_10_01.models.JsonWebKeyOperation]\n :param key_attributes:\n :type key_attributes: ~azure.keyvault.v2016_10_01.models.KeyAttributes\n :param tags: Application specific metadata in the form of key-value\n pairs.\n :type tags: dict[str, str]\n :param dict custom_headers: headers that will be added to the request\n :param bool raw: returns the direct response alongside the\n deserialized response\n :param operation_config: :ref:`Operation configuration\n overrides<msrest:optionsforoperations>`.\n :return: KeyBundle or ClientRawResponse if raw=true\n :rtype: ~azure.keyvault.v2016_10_01.models.KeyBundle or\n ~msrest.pipeline.ClientRawResponse\n :raises:\n :class:`KeyVaultErrorException<azure.keyvault.v2016_10_01.models.KeyVaultErrorException>`", "scope": {"holder": "Azure-azure-sdk-for-python", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Azure/azure-sdk-for-python/blob/d7306fde32f60a293a7567678692bdad31e4b667/azure-mgmt-storage/azure/mgmt/storage/storage_management_client.py#L179-L189", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Azure-azure-sdk-for-python:StorageManagementClient.management_policies-817a58fa70@held-out", "question": "Instance depends on the API version:\n\n * 2018-07-01: :class:`ManagementPoliciesOperations<azure.mgmt.storage.v2018_07_01.operations.ManagementPoliciesOperations>`", "scope": {"holder": "Azure-azure-sdk-for-python", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Azure/azure-sdk-for-python/blob/d7306fde32f60a293a7567678692bdad31e4b667/azure-servicemanagement-legacy/azure/servicemanagement/servicemanagementclient.py#L422-L434", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Azure-azure-sdk-for-python:parse_response_for_async_op-1529274732@held-out", "question": "Extracts request id from response header.", "scope": {"holder": "Azure-azure-sdk-for-python", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Azure/azure-sdk-for-python/blob/d7306fde32f60a293a7567678692bdad31e4b667/azure-servicemanagement-legacy/azure/servicemanagement/servicemanagementclient.py#L343-L362", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Azure-azure-sdk-for-python:_ServiceManagementClient._update_management_header-99200f8f86@held-out", "question": "Add additional headers for management.", "scope": {"holder": "Azure-azure-sdk-for-python", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Azure/azure-sdk-for-python/blob/d7306fde32f60a293a7567678692bdad31e4b667/azure-keyvault/azure/keyvault/v7_0/key_vault_client.py#L2415-L2493", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Azure-azure-sdk-for-python:KeyVaultClient.get_certificates-371c5a9e75@held-out", "question": "List certificates in a specified key vault.\n\n The GetCertificates operation returns the set of certificates resources\n in the specified key vault. This operation requires the\n certificates/list permission.\n\n :param vault_base_url: The vault name, for example\n https://myvault.vault.azure.net.\n :type vault_base_url: str\n :param maxresults: Maximum number of results to return in a page. If\n not specified the service will return up to 25 results.\n :type maxresults: int\n :param include_pending: Specifies whether to include certificates\n which are not completely provisioned.\n :type include_pending: bool\n :param dict custom_headers: headers that will be added to the request\n :param bool raw: returns the direct response alongside the\n deserialized response\n :param operation_config: :ref:`Operation configuration\n overrides<msrest:optionsforoperations>`.\n :return: An iterator like instance of CertificateItem\n :rtype:\n ~azure.keyvault.v7_0.models.CertificateItemPaged[~azure.keyvault.v7_0.models.CertificateItem]\n :raises:\n :class:`KeyVaultErrorException<azure.keyvault.v7_0.models.KeyVaultErrorException>`", "scope": {"holder": "Azure-azure-sdk-for-python", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Azure/azure-sdk-for-python/blob/d7306fde32f60a293a7567678692bdad31e4b667/azure-servicemanagement-legacy/azure/servicemanagement/servicebusmanagementservice.py#L93-L103", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Azure-azure-sdk-for-python:ServiceBusManagementService.list_namespaces-5b02ab6e44@held-out", "question": "List the service bus namespaces defined on the account.", "scope": {"holder": "Azure-azure-sdk-for-python", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Azure/azure-sdk-for-python/blob/d7306fde32f60a293a7567678692bdad31e4b667/azure-servicemanagement-legacy/azure/servicemanagement/servicebusmanagementservice.py#L407-L432", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Azure-azure-sdk-for-python:ServiceBusManagementService.get_metrics_data_relay-bccc0287a8@held-out", "question": "Retrieves the list of supported metrics for this namespace and relay\n\n name:\n Name of the service bus namespace.\n relay_name:\n Name of the service bus relay in this namespace.\n metric:\n name of a supported metric\n rollup:\n name of a supported rollup\n filter_expression:\n filter, for instance \"$filter=Timestamp gt datetime'2014-10-01T00:00:00Z'\"", "scope": {"holder": "Azure-azure-sdk-for-python", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Azure/azure-sdk-for-python/blob/d7306fde32f60a293a7567678692bdad31e4b667/azure-servicemanagement-legacy/azure/servicemanagement/servicebusmanagementservice.py#L509-L532", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Azure-azure-sdk-for-python:ServiceBusManagementService.get_metrics_rollups_relay-9f421f8868@held-out", "question": "This operation gets rollup data for Service Bus metrics relay.\n Rollup data includes the time granularity for the telemetry aggregation as well as\n the retention settings for each time granularity.\n\n name:\n Name of the service bus namespace.\n relay_name:\n Name of the service bus relay in this namespace.\n metric:\n name of a supported metric", "scope": {"holder": "Azure-azure-sdk-for-python", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Azure/azure-sdk-for-python/blob/d7306fde32f60a293a7567678692bdad31e4b667/azure-servicemanagement-legacy/azure/servicemanagement/sqldatabasemanagementservice.py#L103-L119", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Azure-azure-sdk-for-python:SqlDatabaseManagementService.set_server_admin_password-f263a3e63b@held-out", "question": "Reset the administrator password for a server.\n\n server_name:\n Name of the server to change the password.\n admin_password:\n The new administrator password for the server.", "scope": {"holder": "Azure-azure-sdk-for-python", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Azure/azure-sdk-for-python/blob/d7306fde32f60a293a7567678692bdad31e4b667/azure-servicemanagement-legacy/azure/servicemanagement/sqldatabasemanagementservice.py#L262-L273", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Azure-azure-sdk-for-python:SqlDatabaseManagementService.list_firewall_rules-6698b4bc4a@held-out", "question": "Retrieves the set of firewall rules for an Azure SQL Database Server.\n\n server_name:\n Name of the server.", "scope": {"holder": "Azure-azure-sdk-for-python", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Azure/azure-sdk-for-python/blob/d7306fde32f60a293a7567678692bdad31e4b667/azure-servicemanagement-legacy/azure/servicemanagement/sqldatabasemanagementservice.py#L381-L388", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Azure-azure-sdk-for-python:SqlDatabaseManagementService.list_databases-b87a1eef9d@held-out", "question": "List the SQL databases defined on the specified server name", "scope": {"holder": "Azure-azure-sdk-for-python", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Azure/azure-sdk-for-python/blob/d7306fde32f60a293a7567678692bdad31e4b667/azure-servicebus/azure/servicebus/control_client/servicebusservice.py#L226-L255", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Azure-azure-sdk-for-python:ServiceBusService.create_queue-185fda755b@held-out", "question": "Creates a new queue. Once created, this queue's resource manifest is\n immutable.\n\n queue_name:\n Name of the queue to create.\n queue:\n Queue object to create.\n fail_on_exist:\n Specify whether to throw an exception when the queue exists.", "scope": {"holder": "Azure-azure-sdk-for-python", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Azure/azure-sdk-for-python/blob/d7306fde32f60a293a7567678692bdad31e4b667/azure-servicebus/azure/servicebus/control_client/servicebusservice.py#L257-L283", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Azure-azure-sdk-for-python:ServiceBusService.delete_queue-59a15c59b1@held-out", "question": "Deletes an existing queue. This operation will also remove all\n associated state including messages in the queue.\n\n queue_name:\n Name of the queue to delete.\n fail_not_exist:\n Specify whether to throw an exception if the queue doesn't exist.", "scope": {"holder": "Azure-azure-sdk-for-python", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Azure/azure-sdk-for-python/blob/d7306fde32f60a293a7567678692bdad31e4b667/azure-servicebus/azure/servicebus/control_client/servicebusservice.py#L485-L509", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Azure-azure-sdk-for-python:ServiceBusService.get_rule-c96473b2c3@held-out", "question": "Retrieves the description for the specified rule.\n\n topic_name:\n Name of the topic.\n subscription_name:\n Name of the subscription.\n rule_name:\n Name of the rule.", "scope": {"holder": "Azure-azure-sdk-for-python", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Azure/azure-sdk-for-python/blob/d7306fde32f60a293a7567678692bdad31e4b667/azure-servicebus/azure/servicebus/control_client/servicebusservice.py#L511-L533", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Azure-azure-sdk-for-python:ServiceBusService.list_rules-b25f56b5a8@held-out", "question": "Retrieves the rules that exist under the specified subscription.\n\n topic_name:\n Name of the topic.\n subscription_name:\n Name of the subscription.", "scope": {"holder": "Azure-azure-sdk-for-python", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Azure/azure-sdk-for-python/blob/d7306fde32f60a293a7567678692bdad31e4b667/azure-servicebus/azure/servicebus/control_client/servicebusservice.py#L694-L730", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Azure-azure-sdk-for-python:ServiceBusService.peek_lock_subscription_message-160fc48a3f@held-out", "question": "This operation is used to atomically retrieve and lock a message for\n processing. The message is guaranteed not to be delivered to other\n receivers during the lock duration period specified in buffer\n description. Once the lock expires, the message will be available to\n other receivers (on the same subscription only) during the lock\n duration period specified in the topic description. Once the lock\n expires, the message will be available to other receivers. In order to\n complete processing of the message, the receiver should issue a delete\n command with the lock ID received from this operation. To abandon\n processing of the message and unlock it for other receivers, an Unlock\n Message command should be issued, or the lock duration period can\n expire.\n\n topic_name:\n Name of the topic.\n subscription_name:\n Name of the subscription.\n timeout:\n Optional. The timeout parameter is expressed in seconds.", "scope": {"holder": "Azure-azure-sdk-for-python", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Azure/azure-sdk-for-python/blob/d7306fde32f60a293a7567678692bdad31e4b667/azure-servicebus/azure/servicebus/control_client/servicebusservice.py#L1181-L1197", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Azure-azure-sdk-for-python:ServiceBusService.get_event_hub-31bd7bdf8e@held-out", "question": "Retrieves an existing event hub.\n\n hub_name:\n Name of the event hub.", "scope": {"holder": "Azure-azure-sdk-for-python", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Azure/azure-sdk-for-python/blob/d7306fde32f60a293a7567678692bdad31e4b667/azure-servicebus/azure/servicebus/control_client/servicebusservice.py#L1231-L1250", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Azure-azure-sdk-for-python:ServiceBusService._update_service_bus_header-1345d274b8@held-out", "question": "Add additional headers for Service Bus.", "scope": {"holder": "Azure-azure-sdk-for-python", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Azure/azure-sdk-for-python/blob/d7306fde32f60a293a7567678692bdad31e4b667/azure-servicebus/azure/servicebus/control_client/servicebusservice.py#L1283-L1318", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Azure-azure-sdk-for-python:ServiceBusWrapTokenAuthentication._get_token-8bb74bdc3b@held-out", "question": "Returns token for the request.\n\n host:\n the Service Bus service request.\n path:\n the Service Bus service request.", "scope": {"holder": "Azure-azure-sdk-for-python", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Azure/azure-sdk-for-python/blob/d7306fde32f60a293a7567678692bdad31e4b667/azure-servicemanagement-legacy/azure/servicemanagement/_http/httpclient.py#L144-L169", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Azure-azure-sdk-for-python:_HTTPClient._update_request_uri_query-218c09a565@held-out", "question": "pulls the query string out of the URI and moves it into\n the query portion of the request object. If there are already\n query parameters on the request the parameters in the URI will\n appear after the existing parameters", "scope": {"holder": "Azure-azure-sdk-for-python", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Azure/azure-sdk-for-python/blob/d7306fde32f60a293a7567678692bdad31e4b667/azure-servicebus/azure/servicebus/control_client/models.py#L185-L200", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Azure-azure-sdk-for-python:Message.delete-422e8085b9@held-out", "question": "Deletes itself if find queue name or topic name and subscription\n name.", "scope": {"holder": "Azure-azure-sdk-for-python", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Azure/azure-sdk-for-python/blob/d7306fde32f60a293a7567678692bdad31e4b667/azure-mgmt-containerservice/azure/mgmt/containerservice/container_service_client.py#L174-L184", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Azure-azure-sdk-for-python:ContainerServiceClient.open_shift_managed_clusters-5f9438e5d9@held-out", "question": "Instance depends on the API version:\n\n * 2018-09-30-preview: :class:`OpenShiftManagedClustersOperations<azure.mgmt.containerservice.v2018_09_30_preview.operations.OpenShiftManagedClustersOperations>`", "scope": {"holder": "Azure-azure-sdk-for-python", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Azure/azure-sdk-for-python/blob/d7306fde32f60a293a7567678692bdad31e4b667/azure-common/azure/profiles/__init__.py#L47-L51", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Azure-azure-sdk-for-python:DefaultProfile.use-b521f3465a@held-out", "question": "Define a new default profile.", "scope": {"holder": "Azure-azure-sdk-for-python", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Azure/azure-sdk-for-python/blob/d7306fde32f60a293a7567678692bdad31e4b667/azure-servicebus/azure/servicebus/send_handler.py#L291-L314", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Azure-azure-sdk-for-python:SessionSender.schedule-4bfdbb1e7a@held-out", "question": "Send one or more messages to be enqueued at a specific time.\n\n Returns a list of the sequence numbers of the enqueued messages.\n\n :param schedule_time: The date and time to enqueue the messages.\n :type schedule_time: ~datetime.datetime\n :param messages: The messages to schedule.\n :type messages: ~azure.servicebus.common.message.Message\n :rtype: list[int]\n\n Example:\n .. literalinclude:: ../examples/test_examples.py\n :start-after: [START scheduling_messages]\n :end-before: [END scheduling_messages]\n :language: python\n :dedent: 4\n :caption: Schedule a message to be sent in future", "scope": {"holder": "Azure-azure-sdk-for-python", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Azure/azure-sdk-for-python/blob/d7306fde32f60a293a7567678692bdad31e4b667/azure-servicebus/azure/servicebus/common/mixins.py#L96-L114", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Azure-azure-sdk-for-python:ServiceBusMixin.delete_queue-4601730e0c@held-out", "question": "Delete a queue entity.\n\n :param queue_name: The name of the queue to delete.\n :type queue_name: str\n :param fail_not_exist: Whether to raise an exception if the named queue is not\n found. If set to True, a ServiceBusResourceNotFound will be raised.\n Default value is False.\n :type fail_not_exist: bool\n :raises: ~azure.servicebus.common.errors.ServiceBusConnectionError if the namesapce is not found.\n :raises: ~azure.servicebus.common.errors.ServiceBusResourceNotFound if the queue is not found\n and `fail_not_exist` is set to True.", "scope": {"holder": "Azure-azure-sdk-for-python", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Azure/azure-sdk-for-python/blob/d7306fde32f60a293a7567678692bdad31e4b667/azure-servicebus/azure/servicebus/common/mixins.py#L174-L222", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Azure-azure-sdk-for-python:ServiceBusMixin.create_subscription-6305e2259d@held-out", "question": "Create a subscription entity.\n\n :param topic_name: The name of the topic under which to create the subscription.\n :param subscription_name: The name of the new subscription.\n :type subscription_name: str\n :param lock_duration: The lock durection in seconds for each message in the subscription.\n :type lock_duration: int\n :param requires_session: Whether the subscription will be sessionful, and therefore require all\n message to have a Session ID and be received by a sessionful receiver.\n Default value is False.\n :type requires_session: bool\n :param default_message_time_to_live: The length of time a message will remain in the subscription\n before it is either discarded or moved to the dead letter queue.\n :type default_message_time_to_live: ~datetime.timedelta\n :param dead_lettering_on_message_expiration: Whether to move expired messages to the\n dead letter queue. Default value is False.\n :type dead_lettering_on_message_expiration: bool\n :param dead_lettering_on_filter_evaluation_exceptions: Whether to move messages that error on\n filtering into the dead letter queue. Default is False, and the messages will be discarded.\n :type dead_lettering_on_filter_evaluation_exceptions: bool\n :param max_delivery_count: The maximum number of times a message will attempt to be delivered\n before it is moved to the dead letter queue.\n :type max_delivery_count: int\n :param enable_batched_operations:\n :type: enable_batched_operations: bool\n :raises: ~azure.servicebus.common.errors.ServiceBusConnectionError if the namespace is not found.\n :raises: ~azure.common.AzureConflictHttpError if a queue of the same name already exists.", "scope": {"holder": "Azure-azure-sdk-for-python", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Azure/azure-sdk-for-python/blob/d7306fde32f60a293a7567678692bdad31e4b667/azure-servicebus/azure/servicebus/common/utils.py#L154-L165", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Azure-azure-sdk-for-python:AutoLockRenew.register-63cbb23861@held-out", "question": "Register a renewable entity for automatic lock renewal.\n\n :param renewable: A locked entity that needs to be renewed.\n :type renewable: ~azure.servicebus.common.message.Message or\n ~azure.servicebus.receive_handler.SessionReceiver\n :param timeout: A time in seconds that the lock should be maintained for.\n Default value is 300 (5 minutes).\n :type timeout: int", "scope": {"holder": "Azure-azure-sdk-for-python", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Azure/azure-sdk-for-python/blob/d7306fde32f60a293a7567678692bdad31e4b667/azure-mgmt-batch/azure/mgmt/batch/operations/certificate_operations.py#L194-L281", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Azure-azure-sdk-for-python:CertificateOperations.create-4dd4edd8b6@held-out", "question": "Creates a new certificate inside the specified account.\n\n :param resource_group_name: The name of the resource group that\n contains the Batch account.\n :type resource_group_name: str\n :param account_name: The name of the Batch account.\n :type account_name: str\n :param certificate_name: The identifier for the certificate. This must\n be made up of algorithm and thumbprint separated by a dash, and must\n match the certificate data in the request. For example SHA1-a3d1c5.\n :type certificate_name: str\n :param parameters: Additional parameters for certificate creation.\n :type parameters:\n ~azure.mgmt.batch.models.CertificateCreateOrUpdateParameters\n :param if_match: The entity state (ETag) version of the certificate to\n update. A value of \"*\" can be used to apply the operation only if the\n certificate already exists. If omitted, this operation will always be\n applied.\n :type if_match: str\n :param if_none_match: Set to '*' to allow a new certificate to be\n created, but to prevent updating an existing certificate. Other values\n will be ignored.\n :type if_none_match: str\n :param dict custom_headers: headers that will be added to the request\n :param bool raw: returns the direct response alongside the\n deserialized response\n :return: An instance of AzureOperationPoller that returns Certificate\n or ClientRawResponse if raw=true\n :rtype:\n ~msrestazure.azure_operation.AzureOperationPoller[~azure.mgmt.batch.models.Certificate]\n or ~msrest.pipeline.ClientRawResponse\n :raises: :class:`CloudError<msrestazure.azure_exceptions.CloudError>`", "scope": {"holder": "Azure-azure-sdk-for-python", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Azure/azure-sdk-for-python/blob/d7306fde32f60a293a7567678692bdad31e4b667/azure-mgmt-network/azure/mgmt/network/network_management_client.py#L997-L1019", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Azure-azure-sdk-for-python:NetworkManagementClient.express_route_connections-c149258c02@held-out", "question": "Instance depends on the API version:\n\n * 2018-08-01: :class:`ExpressRouteConnectionsOperations<azure.mgmt.network.v2018_08_01.operations.ExpressRouteConnectionsOperations>`\n * 2018-10-01: :class:`ExpressRouteConnectionsOperations<azure.mgmt.network.v2018_10_01.operations.ExpressRouteConnectionsOperations>`\n * 2018-11-01: :class:`ExpressRouteConnectionsOperations<azure.mgmt.network.v2018_11_01.operations.ExpressRouteConnectionsOperations>`\n * 2018-12-01: :class:`ExpressRouteConnectionsOperations<azure.mgmt.network.v2018_12_01.operations.ExpressRouteConnectionsOperations>`\n * 2019-02-01: :class:`ExpressRouteConnectionsOperations<azure.mgmt.network.v2019_02_01.operations.ExpressRouteConnectionsOperations>`", "scope": {"holder": "Azure-azure-sdk-for-python", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Azure/azure-sdk-for-python/blob/d7306fde32f60a293a7567678692bdad31e4b667/azure-mgmt-network/azure/mgmt/network/network_management_client.py#L3423-L3436", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Azure-azure-sdk-for-python:NetworkManagementClient.web_application_firewall_policies-a35889eaa3@held-out", "question": "Instance depends on the API version:\n\n * 2018-12-01: :class:`WebApplicationFirewallPoliciesOperations<azure.mgmt.network.v2018_12_01.operations.WebApplicationFirewallPoliciesOperations>`\n * 2019-02-01: :class:`WebApplicationFirewallPoliciesOperations<azure.mgmt.network.v2019_02_01.operations.WebApplicationFirewallPoliciesOperations>`", "scope": {"holder": "Azure-azure-sdk-for-python", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Azure/azure-sdk-for-python/blob/d7306fde32f60a293a7567678692bdad31e4b667/azure-servicebus/azure/servicebus/servicebus_client.py#L135-L162", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Azure-azure-sdk-for-python:ServiceBusClient.list_queues-6fb4334ed5@held-out", "question": "Get clients for all queue entities in the namespace.\n\n :rtype: list[~azure.servicebus.servicebus_client.QueueClient]\n :raises: ~azure.servicebus.common.errors.ServiceBusConnectionError if the namespace is not found.\n\n Example:\n .. literalinclude:: ../examples/test_examples.py\n :start-after: [START list_queues]\n :end-before: [END list_queues]\n :language: python\n :dedent: 4\n :caption: List the queues from Service Bus client", "scope": {"holder": "Azure-azure-sdk-for-python", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Azure/azure-sdk-for-python/blob/d7306fde32f60a293a7567678692bdad31e4b667/azure-servicebus/azure/servicebus/servicebus_client.py#L433-L469", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Azure-azure-sdk-for-python:ReceiveClientMixin.list_sessions-d84426ec99@held-out", "question": "List session IDs.\n\n List the Session IDs with pending messages in the queue where the state of the session\n has been updated since the timestamp provided. If no timestamp is provided, all will be returned.\n If the state of a session has never been set, it will not be returned regardless of whether\n there are messages pending.\n\n :param updated_since: The UTC datetime from which to return updated pending Session IDs.\n :type updated_since: datetime.datetime\n :param max_results: The maximum number of Session IDs to return. Default value is 100.\n :type max_results: int\n :param skip: The page value to jump to. Default value is 0.\n :type skip: int\n :rtype: list[str]\n\n Example:\n .. literalinclude:: ../examples/test_examples.py\n :start-after: [START list_sessions_service_bus]\n :end-before: [END list_sessions_service_bus]\n :language: python\n :dedent: 4\n :caption: Get the Ids of session which have messages pending in the queue", "scope": {"holder": "Azure-azure-sdk-for-python", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Azure/azure-sdk-for-python/blob/d7306fde32f60a293a7567678692bdad31e4b667/azure-keyvault/azure/keyvault/http_message_security.py#L88-L127", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Azure-azure-sdk-for-python:HttpMessageSecurity.unprotect_response-04a8c264cb@held-out", "question": "Removes protection from the specified response\n :param request: response from the key vault service\n :return: unprotected response with any security protocal encryption removed", "scope": {"holder": "Azure-azure-sdk-for-python", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Azure/azure-sdk-for-python/blob/d7306fde32f60a293a7567678692bdad31e4b667/azure-servicemanagement-legacy/azure/servicemanagement/schedulermanagementservice.py#L87-L113", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Azure-azure-sdk-for-python:SchedulerManagementService.create_cloud_service-e5c78df280@held-out", "question": "The Create Cloud Service request creates a new cloud service. When job\n collections are created, they are hosted within a cloud service.\n A cloud service groups job collections together in a given region.\n Once a cloud service has been created, job collections can then be\n created and contained within it.\n\n cloud_service_id:\n The cloud service id\n label:\n The name of the cloud service.\n description:\n The description of the cloud service.\n geo_region:\n The geographical region of the webspace that will be created.", "scope": {"holder": "Azure-azure-sdk-for-python", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Azure/azure-sdk-for-python/blob/d7306fde32f60a293a7567678692bdad31e4b667/azure-servicebus/azure/servicebus/aio/async_send_handler.py#L99-L125", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Azure-azure-sdk-for-python:Sender.schedule-91403f3848@held-out", "question": "Send one or more messages to be enqueued at a specific time.\n\n Returns a list of the sequence numbers of the enqueued messages.\n\n :param schedule_time: The date and time to enqueue the messages.\n :type schedule_time: ~datetime.datetime\n :param messages: The messages to schedule.\n :type messages: ~azure.servicebus.aio.async_message.Message\n :rtype: list[int]\n\n Example:\n .. literalinclude:: ../examples/async_examples/test_examples_async.py\n :start-after: [START schedule_messages]\n :end-before: [END schedule_messages]\n :language: python\n :dedent: 4\n :caption: Schedule messages.", "scope": {"holder": "Azure-azure-sdk-for-python", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/streamlink/streamlink/blob/c8ed1daff14ac03195870238b9b900c1109dd5c1/src/streamlink_cli/compat.py#L27-L43", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:streamlink-streamlink:shlex_quote-d9f98ef5bc@held-out", "question": "Return a shell-escaped version of the string *s*.\n\n Backported from Python 3.3 standard library module shlex.", "scope": {"holder": "streamlink-streamlink", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/streamlink/streamlink/blob/c8ed1daff14ac03195870238b9b900c1109dd5c1/src/streamlink/packages/flashmedia/ordereddict.py#L80-L90", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:streamlink-streamlink:OrderedDict.clear-a85a3ab334@held-out", "question": "od.clear() -> None. Remove all items from od.", "scope": {"holder": "streamlink-streamlink", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/streamlink/streamlink/blob/c8ed1daff14ac03195870238b9b900c1109dd5c1/src/streamlink/stream/segmented.py#L100-L109", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:streamlink-streamlink:SegmentedStreamWriter.close-c3e5097f15@held-out", "question": "Shuts down the thread.", "scope": {"holder": "streamlink-streamlink", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/streamlink/streamlink/blob/c8ed1daff14ac03195870238b9b900c1109dd5c1/src/streamlink/plugins/bbciplayer.py#L122-L138", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:streamlink-streamlink:BBCiPlayer.find_vpid-621d989cf1@held-out", "question": "Find the Video Packet ID in the HTML for the provided URL\n\n :param url: URL to download, if res is not provided.\n :param res: Provide a cached version of the HTTP response to search\n :type url: string\n :type res: requests.Response\n :return: Video Packet ID for a Programme in iPlayer\n :rtype: string", "scope": {"holder": "streamlink-streamlink", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/streamlink/streamlink/blob/c8ed1daff14ac03195870238b9b900c1109dd5c1/src/streamlink/utils/__init__.py#L43-L49", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:streamlink-streamlink:prepend_www-f4f0d07300@held-out", "question": "Changes google.com to www.google.com", "scope": {"holder": "streamlink-streamlink", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/streamlink/streamlink/blob/c8ed1daff14ac03195870238b9b900c1109dd5c1/src/streamlink/plugin/api/utils.py#L16-L28", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:streamlink-streamlink:itertags-b58e15d1c8@held-out", "question": "Brute force regex based HTML tag parser. This is a rough-and-ready searcher to find HTML tags when\n standards compliance is not required. Will find tags that are commented out, or inside script tag etc.\n\n :param html: HTML page\n :param tag: tag name to find\n :return: generator with Tags", "scope": {"holder": "streamlink-streamlink", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/streamlink/streamlink/blob/c8ed1daff14ac03195870238b9b900c1109dd5c1/src/streamlink/plugin/api/http_session.py#L110-L116", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:streamlink-streamlink:HTTPSession.parse_cookies-0c05470ba7@held-out", "question": "Parses a semi-colon delimited list of cookies.\n\n Example: foo=bar;baz=qux", "scope": {"holder": "streamlink-streamlink", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/streamlink/streamlink/blob/c8ed1daff14ac03195870238b9b900c1109dd5c1/src/streamlink/packages/requests_file.py#L33-L148", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:streamlink-streamlink:FileAdapter.send-9dec5bf15c@held-out", "question": "Wraps a file, described in request, in a Response object.\n\n :param request: The PreparedRequest` being \"sent\".\n :returns: a Response object containing the file", "scope": {"holder": "streamlink-streamlink", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/streamlink/streamlink/blob/c8ed1daff14ac03195870238b9b900c1109dd5c1/src/streamlink_cli/main.py#L53-L70", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:streamlink-streamlink:check_file_output-fd774c6b7b@held-out", "question": "Checks if file already exists and ask the user if it should\n be overwritten if it does.", "scope": {"holder": "streamlink-streamlink", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/streamlink/streamlink/blob/c8ed1daff14ac03195870238b9b900c1109dd5c1/src/streamlink_cli/main.py#L73-L129", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:streamlink-streamlink:create_output-990a5b32b4@held-out", "question": "Decides where to write the stream.\n\n Depending on arguments it can be one of these:\n - The stdout pipe\n - A subprocess' stdin pipe\n - A named pipe that the subprocess reads from\n - A regular file", "scope": {"holder": "streamlink-streamlink", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/streamlink/streamlink/blob/c8ed1daff14ac03195870238b9b900c1109dd5c1/src/streamlink_cli/main.py#L626-L647", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:streamlink-streamlink:authenticate_twitch_oauth-28814f16ac@held-out", "question": "Opens a web browser to allow the user to grant Streamlink\n access to their Twitch account.", "scope": {"holder": "streamlink-streamlink", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/streamlink/streamlink/blob/c8ed1daff14ac03195870238b9b900c1109dd5c1/src/streamlink_cli/main.py#L718-L760", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:streamlink-streamlink:setup_http_session-b039b219ba@held-out", "question": "Sets the global HTTP settings, such as proxy and headers.", "scope": {"holder": "streamlink-streamlink", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/streamlink/streamlink/blob/c8ed1daff14ac03195870238b9b900c1109dd5c1/src/streamlink_cli/main.py#L888-L914", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:streamlink-streamlink:setup_plugin_options-d5b960c60b@held-out", "question": "Sets Streamlink plugin options.", "scope": {"holder": "streamlink-streamlink", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/streamlink/streamlink/blob/c8ed1daff14ac03195870238b9b900c1109dd5c1/src/streamlink/plugins/viasat.py#L127-L131", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:streamlink-streamlink:Viasat._get_iframe-3cdbc7c1af@held-out", "question": "Fallback if no stream_id was found before", "scope": {"holder": "streamlink-streamlink", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/streamlink/streamlink/blob/c8ed1daff14ac03195870238b9b900c1109dd5c1/src/streamlink/plugin/api/validate.py#L219-L241", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:streamlink-streamlink:map-f3ba3fdf7e@held-out", "question": "Apply function to each value inside the sequence or dict.\n\n Supports both dicts and sequences, key/value pairs are\n expanded when applied to a dict.", "scope": {"holder": "streamlink-streamlink", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/streamlink/streamlink/blob/c8ed1daff14ac03195870238b9b900c1109dd5c1/src/streamlink/plugins/huomao.py#L64-L85", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:streamlink-streamlink:Huomao.get_stream_info-794b066098@held-out", "question": "Returns a nested list of different stream options.\n\n Each entry in the list will contain a stream_url and stream_quality_name\n for each stream occurrence that was found in the JS.", "scope": {"holder": "streamlink-streamlink", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/streamlink/streamlink/blob/c8ed1daff14ac03195870238b9b900c1109dd5c1/src/streamlink/plugins/crunchyroll.py#L346-L389", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:streamlink-streamlink:Crunchyroll._create_api-7255898e60@held-out", "question": "Creates a new CrunchyrollAPI object, initiates it's session and\n tries to authenticate it either by using saved credentials or the\n user's username and password.", "scope": {"holder": "streamlink-streamlink", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/google/brotli/blob/4b2b2d4f83ffeaac7708e44409fe34896a01a278/research/brotlidump.py#L32-L43", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:google-brotli:outputFormatter-690301c7d1@held-out", "question": "Show string or char.", "scope": {"holder": "google-brotli", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/google/brotli/blob/4b2b2d4f83ffeaac7708e44409fe34896a01a278/research/brotlidump.py#L412-L433", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:google-brotli:Code.showCode-1ed64d25e3@held-out", "question": "Show all words of the code in a nice format.", "scope": {"holder": "google-brotli", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/google/brotli/blob/4b2b2d4f83ffeaac7708e44409fe34896a01a278/research/brotlidump.py#L540-L547", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:google-brotli:Enumerator.value-096387876a@held-out", "question": "Override if you don't define value0 and extraTable", "scope": {"holder": "google-brotli", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/google/brotli/blob/4b2b2d4f83ffeaac7708e44409fe34896a01a278/research/brotlidump.py#L1145-L1165", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:google-brotli:DistanceAlphabet.value-cf3270b73d@held-out", "question": "Decode value of symbol together with the extra bits.\n >>> d = DistanceAlphabet('D', NPOSTFIX=2, NDIRECT=10)\n >>> d[34].value(2)\n (0, 35)", "scope": {"holder": "google-brotli", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/google/brotli/blob/4b2b2d4f83ffeaac7708e44409fe34896a01a278/research/brotlidump.py#L1385-L1422", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:google-brotli:Layout.formatBitData-6bf67d5713@held-out", "question": "Show formatted bit data:\n Bytes are separated by commas\n whole bytes are displayed in hex\n >>> Layout(olleke).formatBitData(6, 2, 16)\n '|00h|2Eh,|00'\n >>> Layout(olleke).formatBitData(4, 1, 0)\n '1'", "scope": {"holder": "google-brotli", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/google/brotli/blob/4b2b2d4f83ffeaac7708e44409fe34896a01a278/research/brotlidump.py#L1781-L1791", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:google-brotli:Layout.readPrefixArray-1378cfcd21@held-out", "question": "Read prefix code array", "scope": {"holder": "google-brotli", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/vaexio/vaex/blob/a45b672f8287afca2ada8e36b74b604b9b28dd85/packages/vaex-astro/vaex/astro/transformations.py#L5-L9", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:vaexio-vaex:patch-43e14cde51@held-out", "question": "Adds method f to the Dataset class", "scope": {"holder": "vaexio-vaex", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/vaexio/vaex/blob/a45b672f8287afca2ada8e36b74b604b9b28dd85/packages/vaex-astro/vaex/astro/transformations.py#L23-L35", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:vaexio-vaex:add_virtual_columns_eq2ecl-f7a459dbf8@held-out", "question": "Add ecliptic coordates (long_out, lat_out) from equatorial coordinates.\n\n :param long_in: Name/expression for right ascension\n :param lat_in: Name/expression for declination\n :param long_out: Output name for lambda coordinate\n :param lat_out: Output name for beta coordinate\n :param name_prefix:\n :param radians: input and output in radians (True), or degrees (False)\n :return:", "scope": {"holder": "vaexio-vaex", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/vaexio/vaex/blob/a45b672f8287afca2ada8e36b74b604b9b28dd85/packages/vaex-astro/vaex/astro/transformations.py#L141-L186", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:vaexio-vaex:add_virtual_columns_proper_motion_eq2gal-56b2ddd912@held-out", "question": "Transform/rotate proper motions from equatorial to galactic coordinates\n\n Taken from http://arxiv.org/abs/1306.2945\n\n :param long_in: Name/expression for right ascension\n :param lat_in: Name/expression for declination\n :param pm_long: Proper motion for ra\n :param pm_lat: Proper motion for dec\n :param pm_long_out: Output name for output proper motion on l direction\n :param pm_lat_out: Output name for output proper motion on b direction\n :param name_prefix:\n :param radians: input and output in radians (True), or degrees (False)\n :parap inverse: (For internal use) convert from galactic to equatorial instead\n :return:", "scope": {"holder": "vaexio-vaex", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/vaexio/vaex/blob/a45b672f8287afca2ada8e36b74b604b9b28dd85/packages/vaex-core/vaex/expression.py#L191-L217", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:vaexio-vaex:Expression._graph-962ed61447@held-out", "question": "Return a graph containing the dependencies of this expression\n Structure is:\n [<string expression>, <function name if callable>, <function object if callable>, [subgraph/dependencies, ....]]", "scope": {"holder": "vaexio-vaex", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/vaexio/vaex/blob/a45b672f8287afca2ada8e36b74b604b9b28dd85/packages/vaex-core/vaex/expression.py#L371-L434", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:vaexio-vaex:Expression.value_counts-b001d6175f@held-out", "question": "Computes counts of unique values.\n\n WARNING:\n * If the expression/column is not categorical, it will be converted on the fly\n * dropna is False by default, it is True by default in pandas\n\n :param dropna: when True, it will not report the missing values\n :param ascending: when False (default) it will report the most frequent occuring item first\n :returns: Pandas series containing the counts", "scope": {"holder": "vaexio-vaex", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/vaexio/vaex/blob/a45b672f8287afca2ada8e36b74b604b9b28dd85/packages/vaex-core/vaex/__init__.py#L280-L317", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:vaexio-vaex:from_arrays-6fbc0baf4b@held-out", "question": "Create an in memory DataFrame from numpy arrays.\n\n Example\n\n >>> import vaex, numpy as np\n >>> x = np.arange(5)\n >>> y = x ** 2\n >>> vaex.from_arrays(x=x, y=y)\n # x y\n 0 0 0\n 1 1 1\n 2 2 4\n 3 3 9\n 4 4 16\n >>> some_dict = {'x': x, 'y': y}\n >>> vaex.from_arrays(**some_dict) # in case you have your columns in a dict\n # x y\n 0 0 0\n 1 1 1\n 2 2 4\n 3 3 9\n 4 4 16\n\n :param arrays: keyword arguments with arrays\n :rtype: DataFrame", "scope": {"holder": "vaexio-vaex", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/vaexio/vaex/blob/a45b672f8287afca2ada8e36b74b604b9b28dd85/packages/vaex-core/vaex/__init__.py#L421-L462", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:vaexio-vaex:read_csv_and_convert-d7c9b882ed@held-out", "question": "Convert a path (or glob pattern) to a single hdf5 file, will open the hdf5 file if exists.\n\n Example:\n >>> vaex.read_csv_and_convert('test-*.csv', shuffle=True) # this may take a while\n >>> vaex.read_csv_and_convert('test-*.csv', shuffle=True) # 2nd time it is instant\n\n :param str path: path of file or glob pattern for multiple files\n :param bool shuffle: shuffle DataFrame when converting to hdf5\n :param bool copy_index: by default pandas will create an index (row number), set to false if you want to drop that\n :param kwargs: parameters passed to pandas' read_cvs", "scope": {"holder": "vaexio-vaex", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/vaexio/vaex/blob/a45b672f8287afca2ada8e36b74b604b9b28dd85/packages/vaex-ui/vaex/ui/main.py#L1608-L1617", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:vaexio-vaex:VaexApp.open-e02d2b20b3@held-out", "question": "Add a dataset and add it to the UI", "scope": {"holder": "vaexio-vaex", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/vaexio/vaex/blob/a45b672f8287afca2ada8e36b74b604b9b28dd85/packages/vaex-core/vaex/legacy.py#L1047-L1071", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:vaexio-vaex:SubspaceLocal._task-509e00f9ad@held-out", "question": "Helper function for returning tasks results, result when immediate is True, otherwise the task itself, which is a promise", "scope": {"holder": "vaexio-vaex", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/vaexio/vaex/blob/a45b672f8287afca2ada8e36b74b604b9b28dd85/packages/vaex-ui/vaex/ui/plot_windows.py#L121-L128", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:vaexio-vaex:Slicer.clear-f2ab92ca7d@held-out", "question": "clear the cursor", "scope": {"holder": "vaexio-vaex", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/vaexio/vaex/blob/a45b672f8287afca2ada8e36b74b604b9b28dd85/packages/vaex-core/vaex/utils.py#L588-L595", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:vaexio-vaex:write_to-5232505cbe@held-out", "question": "Flexible writing, where f can be a filename or f object, if filename, closed after writing", "scope": {"holder": "vaexio-vaex", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/vaexio/vaex/blob/a45b672f8287afca2ada8e36b74b604b9b28dd85/packages/vaex-core/vaex/utils.py#L832-L841", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:vaexio-vaex:_split_and_combine_mask-a068de1c97@held-out", "question": "Combines all masks from a list of arrays, and logically ors them into a single mask", "scope": {"holder": "vaexio-vaex", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/vaexio/vaex/blob/a45b672f8287afca2ada8e36b74b604b9b28dd85/packages/vaex-core/vaex/dataframe.py#L840-L891", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:vaexio-vaex:DataFrame.covar-de5e4cb55e@held-out", "question": "Calculate the covariance cov[x,y] between and x and y, possibly on a grid defined by binby.\n\n Example:\n\n >>> df.covar(\"x**2+y**2+z**2\", \"-log(-E+1)\")\n array(52.69461456005138)\n >>> df.covar(\"x**2+y**2+z**2\", \"-log(-E+1)\")/(df.std(\"x**2+y**2+z**2\") * df.std(\"-log(-E+1)\"))\n 0.63666373822156686\n >>> df.covar(\"x**2+y**2+z**2\", \"-log(-E+1)\", binby=\"Lz\", shape=4)\n array([ 10.17387143, 51.94954078, 51.24902796, 20.2163929 ])\n\n\n\n :param x: {expression}\n :param y: {expression}\n :param binby: {binby}\n :param limits: {limits}\n :param shape: {shape}\n :param selection: {selection}\n :param delay: {delay}\n :param progress: {progress}\n :return: {return_stat_scalar}", "scope": {"holder": "vaexio-vaex", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/vaexio/vaex/blob/a45b672f8287afca2ada8e36b74b604b9b28dd85/packages/vaex-core/vaex/dataframe.py#L1047-L1104", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:vaexio-vaex:DataFrame.minmax-eb33b9acc6@held-out", "question": "Calculate the minimum and maximum for expressions, possibly on a grid defined by binby.\n\n\n Example:\n\n >>> df.minmax(\"x\")\n array([-128.293991, 271.365997])\n >>> df.minmax([\"x\", \"y\"])\n array([[-128.293991 , 271.365997 ],\n [ -71.5523682, 146.465836 ]])\n >>> df.minmax(\"x\", binby=\"x\", shape=5, limits=[-10, 10])\n array([[-9.99919128, -6.00010443],\n [-5.99972439, -2.00002384],\n [-1.99991322, 1.99998057],\n [ 2.0000093 , 5.99983597],\n [ 6.0004878 , 9.99984646]])\n\n :param expression: {expression}\n :param binby: {binby}\n :param limits: {limits}\n :param shape: {shape}\n :param selection: {selection}\n :param delay: {delay}\n :param progress: {progress}\n :return: {return_stat_scalar}, the last dimension is of shape (2)", "scope": {"holder": "vaexio-vaex", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/vaexio/vaex/blob/a45b672f8287afca2ada8e36b74b604b9b28dd85/packages/vaex-core/vaex/dataframe.py#L1391-L1562", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:vaexio-vaex:DataFrame.limits-4ff4b1e3e8@held-out", "question": "Calculate the [min, max] range for expression, as described by value, which is '99.7%' by default.\n\n If value is a list of the form [minvalue, maxvalue], it is simply returned, this is for convenience when using mixed\n forms.\n\n Example:\n\n >>> df.limits(\"x\")\n array([-28.86381927, 28.9261226 ])\n >>> df.limits([\"x\", \"y\"])\n (array([-28.86381927, 28.9261226 ]), array([-28.60476934, 28.96535249]))\n >>> df.limits([\"x\", \"y\"], \"minmax\")\n (array([-128.293991, 271.365997]), array([ -71.5523682, 146.465836 ]))\n >>> df.limits([\"x\", \"y\"], [\"minmax\", \"90%\"])\n (array([-128.293991, 271.365997]), array([-13.37438402, 13.4224423 ]))\n >>> df.limits([\"x\", \"y\"], [\"minmax\", [0, 10]])\n (array([-128.293991, 271.365997]), [0, 10])\n\n :param expression: {expression_limits}\n :param value: {limits}\n :param selection: {selection}\n :param delay: {delay}\n :return: {return_limits}", "scope": {"holder": "vaexio-vaex", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/vaexio/vaex/blob/a45b672f8287afca2ada8e36b74b604b9b28dd85/packages/vaex-core/vaex/dataframe.py#L1835-L1852", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:vaexio-vaex:DataFrame.plot3d-f75a982082@held-out", "question": "Use at own risk, requires ipyvolume", "scope": {"holder": "vaexio-vaex", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/vaexio/vaex/blob/a45b672f8287afca2ada8e36b74b604b9b28dd85/packages/vaex-core/vaex/dataframe.py#L1930-L1933", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:vaexio-vaex:DataFrame.dtypes-78aca0bb59@held-out", "question": "Gives a Pandas series object containing all numpy dtypes of all columns (except hidden).", "scope": {"holder": "vaexio-vaex", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/vaexio/vaex/blob/a45b672f8287afca2ada8e36b74b604b9b28dd85/packages/vaex-core/vaex/dataframe.py#L2929-L2989", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:vaexio-vaex:DataFrame.propagate_uncertainties-fd3dc04e77@held-out", "question": "Propagates uncertainties (full covariance matrix) for a set of virtual columns.\n\n Covariance matrix of the depending variables is guessed by finding columns prefixed by \"e\"\n or `\"e_\"` or postfixed by \"_error\", \"_uncertainty\", \"e\" and `\"_e\"`.\n Off diagonals (covariance or correlation) by postfixes with \"_correlation\" or \"_corr\" for\n correlation or \"_covariance\" or \"_cov\" for covariances.\n (Note that x_y_cov = x_e * y_e * x_y_correlation.)\n\n\n Example\n\n >>> df = vaex.from_scalars(x=1, y=2, e_x=0.1, e_y=0.2)\n >>> df[\"u\"] = df.x + df.y\n >>> df[\"v\"] = np.log10(df.x)\n >>> df.propagate_uncertainties([df.u, df.v])\n >>> df.u_uncertainty, df.v_uncertainty\n\n :param columns: list of columns for which to calculate the covariance matrix.\n :param depending_variables: If not given, it is found out automatically, otherwise a list of columns which have uncertainties.\n :param cov_matrix: List of list with expressions giving the covariance matrix, in the same order as depending_variables. If 'full' or 'auto',\n the covariance matrix for the depending_variables will be guessed, where 'full' gives an error if an entry was not found.", "scope": {"holder": "vaexio-vaex", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/vaexio/vaex/blob/a45b672f8287afca2ada8e36b74b604b9b28dd85/packages/vaex-core/vaex/dataframe.py#L3050-L3074", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:vaexio-vaex:DataFrame.add_virtual_columns_cartesian_velocities_to_polar-71f6005aa2@held-out", "question": "Convert cartesian to polar velocities.\n\n :param x:\n :param y:\n :param vx:\n :param radius_polar: Optional expression for the radius, may lead to a better performance when given.\n :param vy:\n :param vr_out:\n :param vazimuth_out:\n :param propagate_uncertainties: {propagate_uncertainties}\n :return:", "scope": {"holder": "vaexio-vaex", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/vaexio/vaex/blob/a45b672f8287afca2ada8e36b74b604b9b28dd85/packages/vaex-core/vaex/dataframe.py#L3105-L3126", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:vaexio-vaex:DataFrame.add_virtual_columns_rotation-1f338d2568@held-out", "question": "Rotation in 2d.\n\n :param str x: Name/expression of x column\n :param str y: idem for y\n :param str xnew: name of transformed x column\n :param str ynew:\n :param float angle_degrees: rotation in degrees, anti clockwise\n :return:", "scope": {"holder": "vaexio-vaex", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/vaexio/vaex/blob/a45b672f8287afca2ada8e36b74b604b9b28dd85/packages/vaex-core/vaex/dataframe.py#L3300-L3320", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:vaexio-vaex:DataFrame.add_variable-ce73b28c27@held-out", "question": "Add a variable to to a DataFrame.\n\n A variable may refer to other variables, and virtual columns and expression may refer to variables.\n\n Example\n\n >>> df.add_variable('center', 0)\n >>> df.add_virtual_column('x_prime', 'x-center')\n >>> df.select('x_prime < 0')\n\n :param: str name: name of virtual varible\n :param: expression: expression for the variable", "scope": {"holder": "vaexio-vaex", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/vaexio/vaex/blob/a45b672f8287afca2ada8e36b74b604b9b28dd85/packages/vaex-core/vaex/dataframe.py#L3410-L3413", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:vaexio-vaex:DataFrame.head_and_tail_print-1982a45f65@held-out", "question": "Display the first and last n elements of a DataFrame.", "scope": {"holder": "vaexio-vaex", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/vaexio/vaex/blob/a45b672f8287afca2ada8e36b74b604b9b28dd85/packages/vaex-core/vaex/dataframe.py#L4288-L4298", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:vaexio-vaex:DataFrame.select_inverse-2282ebe7bc@held-out", "question": "Invert the selection, i.e. what is selected will not be, and vice versa\n\n :param str name:\n :param executor:\n :return:", "scope": {"holder": "vaexio-vaex", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/vaexio/vaex/blob/a45b672f8287afca2ada8e36b74b604b9b28dd85/packages/vaex-core/vaex/dataframe.py#L4312-L4338", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:vaexio-vaex:DataFrame._selection-26df85c89e@held-out", "question": "select_lasso and select almost share the same code", "scope": {"holder": "vaexio-vaex", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/vaexio/vaex/blob/a45b672f8287afca2ada8e36b74b604b9b28dd85/packages/vaex-core/vaex/dataframe.py#L4457-L4471", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:vaexio-vaex:DataFrame._depending_columns-baaa63eddb@held-out", "question": "Find all depending column for a set of column (default all), minus the excluded ones", "scope": {"holder": "vaexio-vaex", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/vaexio/vaex/blob/a45b672f8287afca2ada8e36b74b604b9b28dd85/packages/vaex-core/vaex/dataframe.py#L4483-L4514", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:vaexio-vaex:DataFrame._root_nodes-36a6f5ff4b@held-out", "question": "Returns a list of string which are the virtual columns that are not used in any other virtual column.", "scope": {"holder": "vaexio-vaex", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/vaexio/vaex/blob/a45b672f8287afca2ada8e36b74b604b9b28dd85/packages/vaex-core/vaex/dataframe.py#L4569-L4613", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:vaexio-vaex:DataFrameLocal.ordinal_encode-9af2c36a19@held-out", "question": "Encode column as ordinal values and mark it as categorical.\n\n The existing column is renamed to a hidden column and replaced by a numerical columns\n with values between [0, len(values)-1].", "scope": {"holder": "vaexio-vaex", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/vaexio/vaex/blob/a45b672f8287afca2ada8e36b74b604b9b28dd85/packages/vaex-core/vaex/dataframe.py#L4767-L4775", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:vaexio-vaex:DataFrameLocal._hstack-bca7bafe4f@held-out", "question": "Join the columns of the other DataFrame to this one, assuming the ordering is the same", "scope": {"holder": "vaexio-vaex", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/vaexio/vaex/blob/a45b672f8287afca2ada8e36b74b604b9b28dd85/packages/vaex-core/vaex/dataframe.py#L4777-L4795", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:vaexio-vaex:DataFrameLocal.concat-f63c87b1ae@held-out", "question": "Concatenates two DataFrames, adding the rows of one the other DataFrame to the current, returned in a new DataFrame.\n\n No copy of the data is made.\n\n :param other: The other DataFrame that is concatenated with this DataFrame\n :return: New DataFrame with the rows concatenated\n :rtype: DataFrameConcatenated", "scope": {"holder": "vaexio-vaex", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/vaexio/vaex/blob/a45b672f8287afca2ada8e36b74b604b9b28dd85/packages/vaex-core/vaex/dataframe.py#L5202-L5258", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:vaexio-vaex:DataFrameLocal.groupby-7f7abc7987@held-out", "question": "Return a :class:`GroupBy` or :class:`DataFrame` object when agg is not None\n\n Examples:\n\n >>> import vaex\n >>> import numpy as np\n >>> np.random.seed(42)\n >>> x = np.random.randint(1, 5, 10)\n >>> y = x**2\n >>> df = vaex.from_arrays(x=x, y=y)\n >>> df.groupby(df.x, agg='count')\n # x y_count\n 0 3 4\n 1 4 2\n 2 1 3\n 3 2 1\n >>> df.groupby(df.x, agg=[vaex.agg.count('y'), vaex.agg.mean('y')])\n # x y_count y_mean\n 0 3 4 9\n 1 4 2 16\n 2 1 3 1\n 3 2 1 4\n >>> df.groupby(df.x, agg={'z': [vaex.agg.count('y'), vaex.agg.mean('y')]})\n # x z_count z_mean\n 0 3 4 9\n 1 4 2 16\n 2 1 3 1\n 3 2 1 4\n\n Example using datetime:\n\n >>> import vaex\n >>> import numpy as np\n >>> t = np.arange('2015-01-01', '2015-02-01', dtype=np.datetime64)\n >>> y = np.arange(len(t))\n >>> df = vaex.from_arrays(t=t, y=y)\n >>> df.groupby(vaex.BinnerTime.per_week(df.t)).agg({'y' : 'sum'})\n # t y\n 0 2015-01-01 00:00:00 21\n 1 2015-01-08 00:00:00 70\n 2 2015-01-15 00:00:00 119\n 3 2015-01-22 00:00:00 168\n 4 2015-01-29 00:00:00 87\n\n\n :param dict, list or agg agg: Aggregate operation in the form of a string, vaex.agg object, a dictionary\n where the keys indicate the target column names, and the values the operations, or the a list of aggregates.\n When not given, it will return the groupby object.\n :return: :class:`DataFrame` or :class:`GroupBy` object.", "scope": {"holder": "vaexio-vaex", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/vaexio/vaex/blob/a45b672f8287afca2ada8e36b74b604b9b28dd85/packages/vaex-viz/vaex/viz/mpl.py#L188-L284", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:vaexio-vaex:scatter-7220a0ab6e@held-out", "question": "Viz (small amounts) of data in 2d using a scatter plot\n\n Convenience wrapper around pylab.scatter when for working with small DataFrames or selections\n\n :param x: Expression for x axis\n :param y: Idem for y\n :param s_expr: When given, use if for the s (size) argument of pylab.scatter\n :param c_expr: When given, use if for the c (color) argument of pylab.scatter\n :param labels: Annotate the points with these text values\n :param selection: Single selection expression, or None\n :param length_limit: maximum number of rows it will plot\n :param length_check: should we do the maximum row check or not?\n :param label: label for the legend\n :param xlabel: label for x axis, if None .label(x) is used\n :param ylabel: label for y axis, if None .label(y) is used\n :param errorbar_kwargs: extra dict with arguments passed to plt.errorbar\n :param kwargs: extra arguments passed to pylab.scatter\n :return:", "scope": {"holder": "vaexio-vaex", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/vaexio/vaex/blob/a45b672f8287afca2ada8e36b74b604b9b28dd85/packages/vaex-core/vaex/functions.py#L646-L676", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:vaexio-vaex:str_count-094dbfce7a@held-out", "question": "Count the occurences of a pattern in sample of a string column.\n\n :param str pat: A string or regex pattern\n :param bool regex: If True,\n :returns: an expression containing the number of times a pattern is found in each sample.\n\n Example:\n\n >>> import vaex\n >>> text = ['Something', 'very pretty', 'is coming', 'our', 'way.']\n >>> df = vaex.from_arrays(text=text)\n >>> df\n # text\n 0 Something\n 1 very pretty\n 2 is coming\n 3 our\n 4 way.\n\n >>> df.text.str.count(pat=\"et\", regex=False)\n Expression = str_count(text, pat='et', regex=False)\n Length: 5 dtype: int64 (expression)\n -----------------------------------\n 0 1\n 1 1\n 2 0\n 3 0\n 4 0", "scope": {"holder": "vaexio-vaex", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/vaexio/vaex/blob/a45b672f8287afca2ada8e36b74b604b9b28dd85/packages/vaex-core/vaex/functions.py#L731-L763", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:vaexio-vaex:str_find-cf35cc83e2@held-out", "question": "Returns the lowest indices in each string in a column, where the provided substring is fully contained between within a\n sample. If the substring is not found, -1 is returned.\n\n :param str sub: A substring to be found in the samples\n :param int start:\n :param int end:\n :returns: an expression containing the lowest indices specifying the start of the substring.\n\n Example:\n\n >>> import vaex\n >>> text = ['Something', 'very pretty', 'is coming', 'our', 'way.']\n >>> df = vaex.from_arrays(text=text)\n >>> df\n # text\n 0 Something\n 1 very pretty\n 2 is coming\n 3 our\n 4 way.\n\n >>> df.text.str.find(sub=\"et\")\n Expression = str_find(text, sub='et')\n Length: 5 dtype: int64 (expression)\n -----------------------------------\n 0 3\n 1 7\n 2 -1\n 3 -1\n 4 -1", "scope": {"holder": "vaexio-vaex", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/vaexio/vaex/blob/a45b672f8287afca2ada8e36b74b604b9b28dd85/packages/vaex-core/vaex/functions.py#L1113-L1147", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:vaexio-vaex:str_replace-3979eb22a7@held-out", "question": "Replace occurences of a pattern/regex in a column with some other string.\n\n :param str pattern: string or a regex pattern\n :param str replace: a replacement string\n :param int n: number of replacements to be made from the start. If -1 make all replacements.\n :param int flags: ??\n :param bool regex: If True, ...?\n :returns: an expression containing the string replacements.\n\n Example:\n\n >>> import vaex\n >>> text = ['Something', 'very pretty', 'is coming', 'our', 'way.']\n >>> df = vaex.from_arrays(text=text)\n >>> df\n # text\n 0 Something\n 1 very pretty\n 2 is coming\n 3 our\n 4 way.\n\n >>> df.text.str.replace(pat='et', repl='__')\n Expression = str_replace(text, pat='et', repl='__')\n Length: 5 dtype: str (expression)\n ---------------------------------\n 0 Som__hing\n 1 very pr__ty\n 2 is coming\n 3 our\n 4 way.", "scope": {"holder": "vaexio-vaex", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/vaexio/vaex/blob/a45b672f8287afca2ada8e36b74b604b9b28dd85/packages/vaex-core/vaex/functions.py#L1220-L1251", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:vaexio-vaex:str_rjust-8d41d88b90@held-out", "question": "Fills the left side of string samples with a specified character such that the strings are left-hand justified.\n\n :param int width: The minimal width of the strings.\n :param str fillchar: The character used for filling.\n :returns: an expression containing the filled strings.\n\n Example:\n\n >>> import vaex\n >>> text = ['Something', 'very pretty', 'is coming', 'our', 'way.']\n >>> df = vaex.from_arrays(text=text)\n >>> df\n # text\n 0 Something\n 1 very pretty\n 2 is coming\n 3 our\n 4 way.\n\n >>> df.text.str.rjust(width=10, fillchar='!')\n Expression = str_rjust(text, width=10, fillchar='!')\n Length: 5 dtype: str (expression)\n ---------------------------------\n 0 !Something\n 1 very pretty\n 2 !is coming\n 3 !!!!!!!our\n 4 !!!!!!way.", "scope": {"holder": "vaexio-vaex", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/vaexio/vaex/blob/a45b672f8287afca2ada8e36b74b604b9b28dd85/packages/vaex-hdf5/vaex/hdf5/dataset.py#L70-L98", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:vaexio-vaex:Hdf5MemoryMapped.write_meta-61d9d94891@held-out", "question": "ucds, descriptions and units are written as attributes in the hdf5 file, instead of a seperate file as\n the default :func:`Dataset.write_meta`.", "scope": {"holder": "vaexio-vaex", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/vaexio/vaex/blob/a45b672f8287afca2ada8e36b74b604b9b28dd85/packages/vaex-core/vaex/ext/readcol.py#L270-L281", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:vaexio-vaex:readff-40302e0042@held-out", "question": "Fixed-format reader\n Pass in a single line string (s) and a format list, \n which needs to be a python list of string lengths", "scope": {"holder": "vaexio-vaex", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/vaexio/vaex/blob/a45b672f8287afca2ada8e36b74b604b9b28dd85/packages/vaex-core/vaex/ext/jprops.py#L260-L273", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:vaexio-vaex:_universal_newlines-8998e14fbe@held-out", "question": "Wrap a file to convert newlines regardless of whether the file was opened\n with the \"universal newlines\" option or not.", "scope": {"holder": "vaexio-vaex", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/librosa/librosa/blob/180e8e6eb8f958fa6b20b8cba389f7945d508247/examples/adjust_tuning.py#L15-L32", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:librosa-librosa:adjust_tuning-68a2d390b4@held-out", "question": "Load audio, estimate tuning, apply pitch correction, and save.", "scope": {"holder": "librosa-librosa", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/librosa/librosa/blob/180e8e6eb8f958fa6b20b8cba389f7945d508247/librosa/core/time_frequency.py#L830-L914", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:librosa-librosa:mel_frequencies-c2f3aacc42@held-out", "question": "Compute an array of acoustic frequencies tuned to the mel scale.\n\n The mel scale is a quasi-logarithmic function of acoustic frequency\n designed such that perceptually similar pitch intervals (e.g. octaves)\n appear equal in width over the full hearing range.\n\n Because the definition of the mel scale is conditioned by a finite number\n of subjective psychoaoustical experiments, several implementations coexist\n in the audio signal processing literature [1]_. By default, librosa replicates\n the behavior of the well-established MATLAB Auditory Toolbox of Slaney [2]_.\n According to this default implementation, the conversion from Hertz to mel is\n linear below 1 kHz and logarithmic above 1 kHz. Another available implementation\n replicates the Hidden Markov Toolkit [3]_ (HTK) according to the following formula:\n\n `mel = 2595.0 * np.log10(1.0 + f / 700.0).`\n\n The choice of implementation is determined by the `htk` keyword argument: setting\n `htk=False` leads to the Auditory toolbox implementation, whereas setting it `htk=True`\n leads to the HTK implementation.\n\n .. [1] Umesh, S., Cohen, L., & Nelson, D. Fitting the mel scale.\n In Proc. International Conference on Acoustics, Speech, and Signal Processing\n (ICASSP), vol. 1, pp. 217-220, 1998.\n\n .. [2] Slaney, M. Auditory Toolbox: A MATLAB Toolbox for Auditory\n Modeling Work. Technical Report, version 2, Interval Research Corporation, 1998.\n\n .. [3] Young, S., Evermann, G., Gales, M., Hain, T., Kershaw, D., Liu, X.,\n Moore, G., Odell, J., Ollason, D., Povey, D., Valtchev, V., & Woodland, P.\n The HTK book, version 3.4. Cambridge University, March 2009.\n\n\n See Also\n --------\n hz_to_mel\n mel_to_hz\n librosa.feature.melspectrogram\n librosa.feature.mfcc\n\n\n Parameters\n ----------\n n_mels : int > 0 [scalar]\n Number of mel bins.\n\n fmin : float >= 0 [scalar]\n Minimum frequency (Hz).\n\n fmax : float >= 0 [scalar]\n Maximum frequency (Hz).\n\n htk : bool\n If True, use HTK formula to convert Hz to mel.\n Otherwise (False), use Slaney's Auditory Toolbox.\n\n Returns\n -------\n bin_frequencies : ndarray [shape=(n_mels,)]\n Vector of n_mels frequencies in Hz which are uniformly spaced on the Mel\n axis.\n\n Examples\n --------\n >>> librosa.mel_frequencies(n_mels=40)\n array([ 0. , 85.317, 170.635, 255.952,\n 341.269, 426.586, 511.904, 597.221,\n 682.538, 767.855, 853.173, 938.49 ,\n 1024.856, 1119.114, 1222.042, 1334.436,\n 1457.167, 1591.187, 1737.532, 1897.337,\n 2071.84 , 2262.393, 2470.47 , 2697.686,\n 2945.799, 3216.731, 3512.582, 3835.643,\n 4188.417, 4573.636, 4994.285, 5453.621,\n 5955.205, 6502.92 , 7101.009, 7754.107,\n 8467.272, 9246.028, 10096.408, 11025. ])", "scope": {"holder": "librosa-librosa", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/librosa/librosa/blob/180e8e6eb8f958fa6b20b8cba389f7945d508247/librosa/core/time_frequency.py#L917-L953", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:librosa-librosa:tempo_frequencies-2ab545075a@held-out", "question": "Compute the frequencies (in beats-per-minute) corresponding\n to an onset auto-correlation or tempogram matrix.\n\n Parameters\n ----------\n n_bins : int > 0\n The number of lag bins\n\n hop_length : int > 0\n The number of samples between each bin\n\n sr : number > 0\n The audio sampling rate\n\n Returns\n -------\n bin_frequencies : ndarray [shape=(n_bins,)]\n vector of bin frequencies measured in BPM.\n\n .. note:: `bin_frequencies[0] = +np.inf` corresponds to 0-lag\n\n Examples\n --------\n Get the tempo frequencies corresponding to a 384-bin (8-second) tempogram\n\n >>> librosa.tempo_frequencies(384)\n array([ inf, 2583.984, 1291.992, ..., 6.782,\n 6.764, 6.747])", "scope": {"holder": "librosa-librosa", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/librosa/librosa/blob/180e8e6eb8f958fa6b20b8cba389f7945d508247/librosa/core/time_frequency.py#L1014-L1067", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:librosa-librosa:times_like-e20a29f234@held-out", "question": "Return an array of time values to match the time axis from a feature matrix.\n\n Parameters\n ----------\n X : np.ndarray or scalar\n - If ndarray, X is a feature matrix, e.g. STFT, chromagram, or mel spectrogram.\n - If scalar, X represents the number of frames.\n\n sr : number > 0 [scalar]\n audio sampling rate\n\n hop_length : int > 0 [scalar]\n number of samples between successive frames\n\n n_fft : None or int > 0 [scalar]\n Optional: length of the FFT window.\n If given, time conversion will include an offset of `n_fft / 2`\n to counteract windowing effects when using a non-centered STFT.\n\n axis : int [scalar]\n The axis representing the time axis of X.\n By default, the last axis (-1) is taken.\n\n Returns\n -------\n times : np.ndarray [shape=(n,)]\n ndarray of times (in seconds) corresponding to each frame of X.\n\n See Also\n --------\n samples_like : Return an array of sample indices to match the time axis from a feature matrix.\n\n Examples\n --------\n Provide a feature matrix input:\n\n >>> y, sr = librosa.load(librosa.util.example_audio_file())\n >>> X = librosa.stft(y)\n >>> times = librosa.times_like(X)\n >>> times\n array([ 0.00000000e+00, 2.32199546e-02, 4.64399093e-02, ...,\n 6.13935601e+01, 6.14167800e+01, 6.14400000e+01])\n\n Provide a scalar input:\n\n >>> n_frames = 2647\n >>> times = librosa.times_like(n_frames)\n >>> times\n array([ 0.00000000e+00, 2.32199546e-02, 4.64399093e-02, ...,\n 6.13935601e+01, 6.14167800e+01, 6.14400000e+01])", "scope": {"holder": "librosa-librosa", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/librosa/librosa/blob/180e8e6eb8f958fa6b20b8cba389f7945d508247/librosa/core/constantq.py#L426-L534", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:librosa-librosa:pseudo_cqt-ac49ab4de8@held-out", "question": "Compute the pseudo constant-Q transform of an audio signal.\n\n This uses a single fft size that is the smallest power of 2 that is greater\n than or equal to the max of:\n\n 1. The longest CQT filter\n 2. 2x the hop_length\n\n Parameters\n ----------\n y : np.ndarray [shape=(n,)]\n audio time series\n\n sr : number > 0 [scalar]\n sampling rate of `y`\n\n hop_length : int > 0 [scalar]\n number of samples between successive CQT columns.\n\n fmin : float > 0 [scalar]\n Minimum frequency. Defaults to C1 ~= 32.70 Hz\n\n n_bins : int > 0 [scalar]\n Number of frequency bins, starting at `fmin`\n\n bins_per_octave : int > 0 [scalar]\n Number of bins per octave\n\n tuning : None or float in `[-0.5, 0.5)`\n Tuning offset in fractions of a bin (cents).\n\n If `None`, tuning will be automatically estimated from the signal.\n\n filter_scale : float > 0\n Filter filter_scale factor. Larger values use longer windows.\n\n sparsity : float in [0, 1)\n Sparsify the CQT basis by discarding up to `sparsity`\n fraction of the energy in each basis.\n\n Set `sparsity=0` to disable sparsification.\n\n window : str, tuple, number, or function\n Window specification for the basis filters.\n See `filters.get_window` for details.\n\n pad_mode : string\n Padding mode for centered frame analysis.\n\n See also: `librosa.core.stft` and `np.pad`.\n\n Returns\n -------\n CQT : np.ndarray [shape=(n_bins, t), dtype=np.float]\n Pseudo Constant-Q energy for each frequency at each time.\n\n Raises\n ------\n ParameterError\n If `hop_length` is not an integer multiple of\n `2**(n_bins / bins_per_octave)`\n\n Or if `y` is too short to support the frequency range of the CQT.\n\n Notes\n -----\n This function caches at level 20.", "scope": {"holder": "librosa-librosa", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/librosa/librosa/blob/180e8e6eb8f958fa6b20b8cba389f7945d508247/librosa/core/constantq.py#L707-L740", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:librosa-librosa:__cqt_filter_fft-cba5a6849b@held-out", "question": "Generate the frequency domain constant-Q filter basis.", "scope": {"holder": "librosa-librosa", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/librosa/librosa/blob/180e8e6eb8f958fa6b20b8cba389f7945d508247/librosa/sequence.py#L897-L958", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:librosa-librosa:transition_loop-2a31722295@held-out", "question": "Construct a self-loop transition matrix over `n_states`.\n\n The transition matrix will have the following properties:\n\n - `transition[i, i] = p` for all i\n - `transition[i, j] = (1 - p) / (n_states - 1)` for all `j != i`\n\n This type of transition matrix is appropriate when states tend to be\n locally stable, and there is no additional structure between different\n states. This is primarily useful for de-noising frame-wise predictions.\n\n Parameters\n ----------\n n_states : int > 1\n The number of states\n\n prob : float in [0, 1] or iterable, length=n_states\n If a scalar, this is the probability of a self-transition.\n\n If a vector of length `n_states`, `p[i]` is the probability of state `i`'s self-transition.\n\n Returns\n -------\n transition : np.ndarray [shape=(n_states, n_states)]\n The transition matrix\n\n Examples\n --------\n >>> librosa.sequence.transition_loop(3, 0.5)\n array([[0.5 , 0.25, 0.25],\n [0.25, 0.5 , 0.25],\n [0.25, 0.25, 0.5 ]])\n\n >>> librosa.sequence.transition_loop(3, [0.8, 0.5, 0.25])\n array([[0.8 , 0.1 , 0.1 ],\n [0.25 , 0.5 , 0.25 ],\n [0.375, 0.375, 0.25 ]])", "scope": {"holder": "librosa-librosa", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/librosa/librosa/blob/180e8e6eb8f958fa6b20b8cba389f7945d508247/librosa/display.py#L293-L349", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:librosa-librosa:cmap-4871349a83@held-out", "question": "Get a default colormap from the given data.\n\n If the data is boolean, use a black and white colormap.\n\n If the data has both positive and negative values,\n use a diverging colormap.\n\n Otherwise, use a sequential colormap.\n\n Parameters\n ----------\n data : np.ndarray\n Input data\n\n robust : bool\n If True, discard the top and bottom 2% of data when calculating\n range.\n\n cmap_seq : str\n The sequential colormap name\n\n cmap_bool : str\n The boolean colormap name\n\n cmap_div : str\n The diverging colormap name\n\n Returns\n -------\n cmap : matplotlib.colors.Colormap\n The colormap to use for `data`\n\n See Also\n --------\n matplotlib.pyplot.colormaps", "scope": {"holder": "librosa-librosa", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/librosa/librosa/blob/180e8e6eb8f958fa6b20b8cba389f7945d508247/librosa/display.py#L935-L946", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:librosa-librosa:__coord_mel_hz-3774f52458@held-out", "question": "Get the frequencies for Mel bins", "scope": {"holder": "librosa-librosa", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/librosa/librosa/blob/180e8e6eb8f958fa6b20b8cba389f7945d508247/librosa/effects.py#L310-L387", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:librosa-librosa:remix-9efbf5c2dd@held-out", "question": "Remix an audio signal by re-ordering time intervals.\n\n\n Parameters\n ----------\n y : np.ndarray [shape=(t,) or (2, t)]\n Audio time series\n\n intervals : iterable of tuples (start, end)\n An iterable (list-like or generator) where the `i`th item\n `intervals[i]` indicates the start and end (in samples)\n of a slice of `y`.\n\n align_zeros : boolean\n If `True`, interval boundaries are mapped to the closest\n zero-crossing in `y`. If `y` is stereo, zero-crossings\n are computed after converting to mono.\n\n\n Returns\n -------\n y_remix : np.ndarray [shape=(d,) or (2, d)]\n `y` remixed in the order specified by `intervals`\n\n\n Examples\n --------\n Load in the example track and reverse the beats\n\n >>> y, sr = librosa.load(librosa.util.example_audio_file())\n\n\n Compute beats\n\n >>> _, beat_frames = librosa.beat.beat_track(y=y, sr=sr,\n ... hop_length=512)\n\n\n Convert from frames to sample indices\n\n >>> beat_samples = librosa.frames_to_samples(beat_frames)\n\n\n Generate intervals from consecutive events\n\n >>> intervals = librosa.util.frame(beat_samples, frame_length=2,\n ... hop_length=1).T\n\n\n Reverse the beat intervals\n\n >>> y_out = librosa.effects.remix(y, intervals[::-1])", "scope": {"holder": "librosa-librosa", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/librosa/librosa/blob/180e8e6eb8f958fa6b20b8cba389f7945d508247/librosa/core/spectrum.py#L573-L657", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:librosa-librosa:phase_vocoder-d09f146be5@held-out", "question": "Phase vocoder. Given an STFT matrix D, speed up by a factor of `rate`\n\n Based on the implementation provided by [1]_.\n\n .. [1] Ellis, D. P. W. \"A phase vocoder in Matlab.\"\n Columbia University, 2002.\n http://www.ee.columbia.edu/~dpwe/resources/matlab/pvoc/\n\n Examples\n --------\n >>> # Play at double speed\n >>> y, sr = librosa.load(librosa.util.example_audio_file())\n >>> D = librosa.stft(y, n_fft=2048, hop_length=512)\n >>> D_fast = librosa.phase_vocoder(D, 2.0, hop_length=512)\n >>> y_fast = librosa.istft(D_fast, hop_length=512)\n\n >>> # Or play at 1/3 speed\n >>> y, sr = librosa.load(librosa.util.example_audio_file())\n >>> D = librosa.stft(y, n_fft=2048, hop_length=512)\n >>> D_slow = librosa.phase_vocoder(D, 1./3, hop_length=512)\n >>> y_slow = librosa.istft(D_slow, hop_length=512)\n\n Parameters\n ----------\n D : np.ndarray [shape=(d, t), dtype=complex]\n STFT matrix\n\n rate : float > 0 [scalar]\n Speed-up factor: `rate > 1` is faster, `rate < 1` is slower.\n\n hop_length : int > 0 [scalar] or None\n The number of samples between successive columns of `D`.\n\n If None, defaults to `n_fft/4 = (D.shape[0]-1)/2`\n\n Returns\n -------\n D_stretched : np.ndarray [shape=(d, t / rate), dtype=complex]\n time-stretched STFT", "scope": {"holder": "librosa-librosa", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/librosa/librosa/blob/180e8e6eb8f958fa6b20b8cba389f7945d508247/librosa/core/spectrum.py#L661-L811", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:librosa-librosa:iirt-7c878556cd@held-out", "question": "r'''Time-frequency representation using IIR filters [1]_.\n\n This function will return a time-frequency representation\n using a multirate filter bank consisting of IIR filters.\n First, `y` is resampled as needed according to the provided `sample_rates`.\n Then, a filterbank with with `n` band-pass filters is designed.\n The resampled input signals are processed by the filterbank as a whole.\n (`scipy.signal.filtfilt` resp. `sosfiltfilt` is used to make the phase linear.)\n The output of the filterbank is cut into frames.\n For each band, the short-time mean-square power (STMSP) is calculated by\n summing `win_length` subsequent filtered time samples.\n\n When called with the default set of parameters, it will generate the TF-representation\n as described in [1]_ (pitch filterbank):\n\n * 85 filters with MIDI pitches [24, 108] as `center_freqs`.\n * each filter having a bandwith of one semitone.\n\n .. [1] Müller, Meinard.\n \"Information Retrieval for Music and Motion.\"\n Springer Verlag. 2007.\n\n\n Parameters\n ----------\n y : np.ndarray [shape=(n,)]\n audio time series\n\n sr : number > 0 [scalar]\n sampling rate of `y`\n\n win_length : int > 0, <= n_fft\n Window length.\n\n hop_length : int > 0 [scalar]\n Hop length, number samples between subsequent frames.\n If not supplied, defaults to `win_length / 4`.\n\n center : boolean\n - If `True`, the signal `y` is padded so that frame\n `D[:, t]` is centered at `y[t * hop_length]`.\n - If `False`, then `D[:, t]` begins at `y[t * hop_length]`\n\n tuning : float in `[-0.5, +0.5)` [scalar]\n Tuning deviation from A440 in fractions of a bin.\n\n pad_mode : string\n If `center=True`, the padding mode to use at the edges of the signal.\n By default, this function uses reflection padding.\n\n flayout : string\n - If `ba`, the standard difference equation is used for filtering with `scipy.signal.filtfilt`.\n Can be unstable for high-order filters.\n - If `sos`, a series of second-order filters is used for filtering with `scipy.signal.sosfiltfilt`.\n Minimizes numerical precision errors for high-order filters, but is slower.\n\n kwargs : additional keyword arguments\n Additional arguments for `librosa.filters.semitone_filterbank()`\n (e.g., could be used to provide another set of `center_freqs` and `sample_rates`).\n\n Returns\n -------\n bands_power : np.ndarray [shape=(n, t), dtype=dtype]\n Short-time mean-square power for the input signal.\n\n Raises\n ------\n ParameterError\n If `flayout` is not None, `ba`, or `sos`.\n\n See Also\n --------\n librosa.filters.semitone_filterbank\n librosa.filters._multirate_fb\n librosa.filters.mr_frequencies\n librosa.core.cqt\n scipy.signal.filtfilt\n scipy.signal.sosfiltfilt\n\n Examples\n --------\n >>> import matplotlib.pyplot as plt\n >>> y, sr = librosa.load(librosa.util.example_audio_file())\n >>> D = np.abs(librosa.iirt(y))\n >>> librosa.display.specshow(librosa.amplitude_to_db(D, ref=np.max),\n ... y_axis='cqt_hz', x_axis='time')\n >>> plt.title('Semitone spectrogram')\n >>> plt.colorbar(format='%+2.0f dB')\n >>> plt.tight_layout()", "scope": {"holder": "librosa-librosa", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/librosa/librosa/blob/180e8e6eb8f958fa6b20b8cba389f7945d508247/librosa/decompose.py#L30-L187", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:librosa-librosa:decompose-084b9a41ef@held-out", "question": "Decompose a feature matrix.\n\n Given a spectrogram `S`, produce a decomposition into `components`\n and `activations` such that `S ~= components.dot(activations)`.\n\n By default, this is done with with non-negative matrix factorization (NMF),\n but any `sklearn.decomposition`-type object will work.\n\n\n Parameters\n ----------\n S : np.ndarray [shape=(n_features, n_samples), dtype=float]\n The input feature matrix (e.g., magnitude spectrogram)\n\n n_components : int > 0 [scalar] or None\n number of desired components\n\n if None, then `n_features` components are used\n\n transformer : None or object\n If None, use `sklearn.decomposition.NMF`\n\n Otherwise, any object with a similar interface to NMF should work.\n `transformer` must follow the scikit-learn convention, where\n input data is `(n_samples, n_features)`.\n\n `transformer.fit_transform()` will be run on `S.T` (not `S`),\n the return value of which is stored (transposed) as `activations`\n\n The components will be retrieved as `transformer.components_.T`\n\n `S ~= np.dot(activations, transformer.components_).T`\n\n or equivalently:\n `S ~= np.dot(transformer.components_.T, activations.T)`\n\n sort : bool\n If `True`, components are sorted by ascending peak frequency.\n\n .. note:: If used with `transformer`, sorting is applied to copies\n of the decomposition parameters, and not to `transformer`'s\n internal parameters.\n\n fit : bool\n If `True`, components are estimated from the input ``S``.\n\n If `False`, components are assumed to be pre-computed and stored\n in ``transformer``, and are not changed.\n\n kwargs : Additional keyword arguments to the default transformer\n `sklearn.decomposition.NMF`\n\n\n Returns\n -------\n components: np.ndarray [shape=(n_features, n_components)]\n matrix of components (basis elements).\n\n activations: np.ndarray [shape=(n_components, n_samples)]\n transformed matrix/activation matrix\n\n\n Raises\n ------\n ParameterError\n if `fit` is False and no `transformer` object is provided.\n\n\n See Also\n --------\n sklearn.decomposition : SciKit-Learn matrix decomposition modules\n\n\n Examples\n --------\n Decompose a magnitude spectrogram into 32 components with NMF\n\n >>> y, sr = librosa.load(librosa.util.example_audio_file())\n >>> S = np.abs(librosa.stft(y))\n >>> comps, acts = librosa.decompose.decompose(S, n_components=8)\n >>> comps\n array([[ 1.876e-01, 5.559e-02, ..., 1.687e-01, 4.907e-02],\n [ 3.148e-01, 1.719e-01, ..., 2.314e-01, 9.493e-02],\n ...,\n [ 1.561e-07, 8.564e-08, ..., 7.167e-08, 4.997e-08],\n [ 1.531e-07, 7.880e-08, ..., 5.632e-08, 4.028e-08]])\n >>> acts\n array([[ 4.197e-05, 8.512e-03, ..., 3.056e-05, 9.159e-06],\n [ 9.568e-06, 1.718e-02, ..., 3.322e-05, 7.869e-06],\n ...,\n [ 5.982e-05, 1.311e-02, ..., -0.000e+00, 6.323e-06],\n [ 3.782e-05, 7.056e-03, ..., 3.290e-05, -0.000e+00]])\n\n\n Sort components by ascending peak frequency\n\n >>> comps, acts = librosa.decompose.decompose(S, n_components=16,\n ... sort=True)\n\n\n Or with sparse dictionary learning\n\n >>> import sklearn.decomposition\n >>> T = sklearn.decomposition.MiniBatchDictionaryLearning(n_components=16)\n >>> scomps, sacts = librosa.decompose.decompose(S, transformer=T, sort=True)\n\n >>> import matplotlib.pyplot as plt\n >>> plt.figure(figsize=(10,8))\n >>> plt.subplot(3, 1, 1)\n >>> librosa.display.specshow(librosa.amplitude_to_db(S,\n ... ref=np.max),\n ... y_axis='log', x_axis='time')\n >>> plt.title('Input spectrogram')\n >>> plt.colorbar(format='%+2.0f dB')\n >>> plt.subplot(3, 2, 3)\n >>> librosa.display.specshow(librosa.amplitude_to_db(comps,\n ... ref=np.max),\n ... y_axis='log')\n >>> plt.colorbar(format='%+2.0f dB')\n >>> plt.title('Components')\n >>> plt.subplot(3, 2, 4)\n >>> librosa.display.specshow(acts, x_axis='time')\n >>> plt.ylabel('Components')\n >>> plt.title('Activations')\n >>> plt.colorbar()\n >>> plt.subplot(3, 1, 3)\n >>> S_approx = comps.dot(acts)\n >>> librosa.display.specshow(librosa.amplitude_to_db(S_approx,\n ... ref=np.max),\n ... y_axis='log', x_axis='time')\n >>> plt.colorbar(format='%+2.0f dB')\n >>> plt.title('Reconstructed spectrogram')\n >>> plt.tight_layout()", "scope": {"holder": "librosa-librosa", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/librosa/librosa/blob/180e8e6eb8f958fa6b20b8cba389f7945d508247/librosa/filters.py#L362-L387", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:librosa-librosa:__float_window-bf947c8d5b@held-out", "question": "Decorator function for windows with fractional input.\n\n This function guarantees that for fractional `x`, the following hold:\n\n 1. `__float_window(window_function)(x)` has length `np.ceil(x)`\n 2. all values from `np.floor(x)` are set to 0.\n\n For integer-valued `x`, there should be no change in behavior.", "scope": {"holder": "librosa-librosa", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/librosa/librosa/blob/180e8e6eb8f958fa6b20b8cba389f7945d508247/librosa/filters.py#L794-L856", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:librosa-librosa:get_window-90403ea181@held-out", "question": "Compute a window function.\n\n This is a wrapper for `scipy.signal.get_window` that additionally\n supports callable or pre-computed windows.\n\n Parameters\n ----------\n window : string, tuple, number, callable, or list-like\n The window specification:\n\n - If string, it's the name of the window function (e.g., `'hann'`)\n - If tuple, it's the name of the window function and any parameters\n (e.g., `('kaiser', 4.0)`)\n - If numeric, it is treated as the beta parameter of the `'kaiser'`\n window, as in `scipy.signal.get_window`.\n - If callable, it's a function that accepts one integer argument\n (the window length)\n - If list-like, it's a pre-computed window of the correct length `Nx`\n\n Nx : int > 0\n The length of the window\n\n fftbins : bool, optional\n If True (default), create a periodic window for use with FFT\n If False, create a symmetric window for filter design applications.\n\n Returns\n -------\n get_window : np.ndarray\n A window of length `Nx` and type `window`\n\n See Also\n --------\n scipy.signal.get_window\n\n Notes\n -----\n This function caches at level 10.\n\n Raises\n ------\n ParameterError\n If `window` is supplied as a vector of length != `n_fft`,\n or is otherwise mis-specified.", "scope": {"holder": "librosa-librosa", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/librosa/librosa/blob/180e8e6eb8f958fa6b20b8cba389f7945d508247/librosa/filters.py#L860-L954", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:librosa-librosa:_multirate_fb-350cf77e22@held-out", "question": "r'''Helper function to construct a multirate filterbank.\n\n A filter bank consists of multiple band-pass filters which divide the input signal\n into subbands. In the case of a multirate filter bank, the band-pass filters\n operate with resampled versions of the input signal, e.g. to keep the length\n of a filter constant while shifting its center frequency.\n\n This implementation uses `scipy.signal.iirdesign` to design the filters.\n\n\n Parameters\n ----------\n center_freqs : np.ndarray [shape=(n,), dtype=float]\n Center frequencies of the filter kernels.\n Also defines the number of filters in the filterbank.\n\n sample_rates : np.ndarray [shape=(n,), dtype=float]\n Samplerate for each filter (used for multirate filterbank).\n\n Q : float\n Q factor (influences the filter bandwith).\n\n passband_ripple : float\n The maximum loss in the passband (dB)\n See `scipy.signal.iirdesign` for details.\n\n stopband_attenuation : float\n The minimum attenuation in the stopband (dB)\n See `scipy.signal.iirdesign` for details.\n\n ftype : str\n The type of IIR filter to design\n See `scipy.signal.iirdesign` for details.\n\n flayout : string\n Valid `output` argument for `scipy.signal.iirdesign`.\n - If `ba`, returns numerators/denominators of the transfer functions,\n used for filtering with `scipy.signal.filtfilt`.\n Can be unstable for high-order filters.\n - If `sos`, returns a series of second-order filters,\n used for filtering with `scipy.signal.sosfiltfilt`.\n Minimizes numerical precision errors for high-order filters, but is slower.\n - If `zpk`, returns zeros, poles, and system gains of the transfer functions.\n\n Returns\n -------\n filterbank : list [shape=(n,), dtype=float]\n Each list entry comprises the filter coefficients for a single filter.\n\n sample_rates : np.ndarray [shape=(n,), dtype=float]\n Samplerate for each filter.\n\n Notes\n -----\n This function caches at level 10.\n\n See Also\n --------\n scipy.signal.iirdesign\n\n Raises\n ------\n ParameterError\n If `center_freqs` is `None`.\n If `sample_rates` is `None`.\n If `center_freqs.shape` does not match `sample_rates.shape`.", "scope": {"holder": "librosa-librosa", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/librosa/librosa/blob/180e8e6eb8f958fa6b20b8cba389f7945d508247/librosa/feature/spectral.py#L171-L311", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:librosa-librosa:spectral_bandwidth-a3bcbd90db@held-out", "question": "Compute p'th-order spectral bandwidth:\n\n (sum_k S[k] * (freq[k] - centroid)**p)**(1/p)\n\n Parameters\n ----------\n y : np.ndarray [shape=(n,)] or None\n audio time series\n\n sr : number > 0 [scalar]\n audio sampling rate of `y`\n\n S : np.ndarray [shape=(d, t)] or None\n (optional) spectrogram magnitude\n\n n_fft : int > 0 [scalar]\n FFT window size\n\n hop_length : int > 0 [scalar]\n hop length for STFT. See `librosa.core.stft` for details.\n\n win_length : int <= n_fft [scalar]\n Each frame of audio is windowed by `window()`.\n The window will be of length `win_length` and then padded\n with zeros to match `n_fft`.\n\n If unspecified, defaults to ``win_length = n_fft``.\n\n window : string, tuple, number, function, or np.ndarray [shape=(n_fft,)]\n - a window specification (string, tuple, or number);\n see `scipy.signal.get_window`\n - a window function, such as `scipy.signal.hanning`\n - a vector or array of length `n_fft`\n\n .. see also:: `filters.get_window`\n\n center : boolean\n - If `True`, the signal `y` is padded so that frame\n `t` is centered at `y[t * hop_length]`.\n - If `False`, then frame `t` begins at `y[t * hop_length]`\n\n pad_mode : string\n If `center=True`, the padding mode to use at the edges of the signal.\n By default, STFT uses reflection padding.\n\n freq : None or np.ndarray [shape=(d,) or shape=(d, t)]\n Center frequencies for spectrogram bins.\n If `None`, then FFT bin center frequencies are used.\n Otherwise, it can be a single array of `d` center frequencies,\n or a matrix of center frequencies as constructed by\n `librosa.core.ifgram`\n\n centroid : None or np.ndarray [shape=(1, t)]\n pre-computed centroid frequencies\n\n norm : bool\n Normalize per-frame spectral energy (sum to one)\n\n p : float > 0\n Power to raise deviation from spectral centroid.\n\n\n Returns\n -------\n bandwidth : np.ndarray [shape=(1, t)]\n frequency bandwidth for each frame\n\n\n Examples\n --------\n From time-series input\n\n >>> y, sr = librosa.load(librosa.util.example_audio_file())\n >>> spec_bw = librosa.feature.spectral_bandwidth(y=y, sr=sr)\n >>> spec_bw\n array([[ 3379.878, 1429.486, ..., 3235.214, 3080.148]])\n\n From spectrogram input\n\n >>> S, phase = librosa.magphase(librosa.stft(y=y))\n >>> librosa.feature.spectral_bandwidth(S=S)\n array([[ 3379.878, 1429.486, ..., 3235.214, 3080.148]])\n\n Using variable bin center frequencies\n\n >>> if_gram, D = librosa.ifgram(y)\n >>> librosa.feature.spectral_bandwidth(S=np.abs(D), freq=if_gram)\n array([[ 3380.011, 1429.11 , ..., 3235.22 , 3080.148]])\n\n Plot the result\n\n >>> import matplotlib.pyplot as plt\n >>> plt.figure()\n >>> plt.subplot(2, 1, 1)\n >>> plt.semilogy(spec_bw.T, label='Spectral bandwidth')\n >>> plt.ylabel('Hz')\n >>> plt.xticks([])\n >>> plt.xlim([0, spec_bw.shape[-1]])\n >>> plt.legend()\n >>> plt.subplot(2, 1, 2)\n >>> librosa.display.specshow(librosa.amplitude_to_db(S, ref=np.max),\n ... y_axis='log', x_axis='time')\n >>> plt.title('log Power spectrogram')\n >>> plt.tight_layout()", "scope": {"holder": "librosa-librosa", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/librosa/librosa/blob/180e8e6eb8f958fa6b20b8cba389f7945d508247/librosa/feature/spectral.py#L1023-L1162", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:librosa-librosa:chroma_stft-70a31bfb34@held-out", "question": "Compute a chromagram from a waveform or power spectrogram.\n\n This implementation is derived from `chromagram_E` [1]_\n\n .. [1] Ellis, Daniel P.W. \"Chroma feature analysis and synthesis\"\n 2007/04/21\n http://labrosa.ee.columbia.edu/matlab/chroma-ansyn/\n\n Parameters\n ----------\n y : np.ndarray [shape=(n,)] or None\n audio time series\n\n sr : number > 0 [scalar]\n sampling rate of `y`\n\n S : np.ndarray [shape=(d, t)] or None\n power spectrogram\n\n norm : float or None\n Column-wise normalization.\n See `librosa.util.normalize` for details.\n\n If `None`, no normalization is performed.\n\n n_fft : int > 0 [scalar]\n FFT window size if provided `y, sr` instead of `S`\n\n hop_length : int > 0 [scalar]\n hop length if provided `y, sr` instead of `S`\n\n win_length : int <= n_fft [scalar]\n Each frame of audio is windowed by `window()`.\n The window will be of length `win_length` and then padded\n with zeros to match `n_fft`.\n\n If unspecified, defaults to ``win_length = n_fft``.\n\n window : string, tuple, number, function, or np.ndarray [shape=(n_fft,)]\n - a window specification (string, tuple, or number);\n see `scipy.signal.get_window`\n - a window function, such as `scipy.signal.hanning`\n - a vector or array of length `n_fft`\n\n .. see also:: `filters.get_window`\n\n center : boolean\n - If `True`, the signal `y` is padded so that frame\n `t` is centered at `y[t * hop_length]`.\n - If `False`, then frame `t` begins at `y[t * hop_length]`\n\n pad_mode : string\n If `center=True`, the padding mode to use at the edges of the signal.\n By default, STFT uses reflection padding.\n\n\n tuning : float in `[-0.5, 0.5)` [scalar] or None.\n Deviation from A440 tuning in fractional bins (cents).\n If `None`, it is automatically estimated.\n\n kwargs : additional keyword arguments\n Arguments to parameterize chroma filters.\n See `librosa.filters.chroma` for details.\n\n Returns\n -------\n chromagram : np.ndarray [shape=(n_chroma, t)]\n Normalized energy for each chroma bin at each frame.\n\n See Also\n --------\n librosa.filters.chroma\n Chroma filter bank construction\n librosa.util.normalize\n Vector normalization\n\n Examples\n --------\n >>> y, sr = librosa.load(librosa.util.example_audio_file())\n >>> librosa.feature.chroma_stft(y=y, sr=sr)\n array([[ 0.974, 0.881, ..., 0.925, 1. ],\n [ 1. , 0.841, ..., 0.882, 0.878],\n ...,\n [ 0.658, 0.985, ..., 0.878, 0.764],\n [ 0.969, 0.92 , ..., 0.974, 0.915]])\n\n Use an energy (magnitude) spectrum instead of power spectrogram\n\n >>> S = np.abs(librosa.stft(y))\n >>> chroma = librosa.feature.chroma_stft(S=S, sr=sr)\n >>> chroma\n array([[ 0.884, 0.91 , ..., 0.861, 0.858],\n [ 0.963, 0.785, ..., 0.968, 0.896],\n ...,\n [ 0.871, 1. , ..., 0.928, 0.829],\n [ 1. , 0.982, ..., 0.93 , 0.878]])\n\n Use a pre-computed power spectrogram with a larger frame\n\n >>> S = np.abs(librosa.stft(y, n_fft=4096))**2\n >>> chroma = librosa.feature.chroma_stft(S=S, sr=sr)\n >>> chroma\n array([[ 0.685, 0.477, ..., 0.961, 0.986],\n [ 0.674, 0.452, ..., 0.952, 0.926],\n ...,\n [ 0.844, 0.575, ..., 0.934, 0.869],\n [ 0.793, 0.663, ..., 0.964, 0.972]])\n\n >>> import matplotlib.pyplot as plt\n >>> plt.figure(figsize=(10, 4))\n >>> librosa.display.specshow(chroma, y_axis='chroma', x_axis='time')\n >>> plt.colorbar()\n >>> plt.title('Chromagram')\n >>> plt.tight_layout()", "scope": {"holder": "librosa-librosa", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/librosa/librosa/blob/180e8e6eb8f958fa6b20b8cba389f7945d508247/librosa/feature/spectral.py#L1429-L1528", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:librosa-librosa:tonnetz-d3ffbb019b@held-out", "question": "Computes the tonal centroid features (tonnetz), following the method of\n [1]_.\n\n .. [1] Harte, C., Sandler, M., & Gasser, M. (2006). \"Detecting Harmonic\n Change in Musical Audio.\" In Proceedings of the 1st ACM Workshop\n on Audio and Music Computing Multimedia (pp. 21-26).\n Santa Barbara, CA, USA: ACM Press. doi:10.1145/1178723.1178727.\n\n Parameters\n ----------\n y : np.ndarray [shape=(n,)] or None\n Audio time series.\n\n sr : number > 0 [scalar]\n sampling rate of `y`\n\n chroma : np.ndarray [shape=(n_chroma, t)] or None\n Normalized energy for each chroma bin at each frame.\n\n If `None`, a cqt chromagram is performed.\n\n Returns\n -------\n tonnetz : np.ndarray [shape(6, t)]\n Tonal centroid features for each frame.\n\n Tonnetz dimensions:\n - 0: Fifth x-axis\n - 1: Fifth y-axis\n - 2: Minor x-axis\n - 3: Minor y-axis\n - 4: Major x-axis\n - 5: Major y-axis\n\n See Also\n --------\n chroma_cqt\n Compute a chromagram from a constant-Q transform.\n\n chroma_stft\n Compute a chromagram from an STFT spectrogram or waveform.\n\n Examples\n --------\n Compute tonnetz features from the harmonic component of a song\n\n >>> y, sr = librosa.load(librosa.util.example_audio_file())\n >>> y = librosa.effects.harmonic(y)\n >>> tonnetz = librosa.feature.tonnetz(y=y, sr=sr)\n >>> tonnetz\n array([[-0.073, -0.053, ..., -0.054, -0.073],\n [ 0.001, 0.001, ..., -0.054, -0.062],\n ...,\n [ 0.039, 0.034, ..., 0.044, 0.064],\n [ 0.005, 0.002, ..., 0.011, 0.017]])\n\n Compare the tonnetz features to `chroma_cqt`\n\n >>> import matplotlib.pyplot as plt\n >>> plt.subplot(2, 1, 1)\n >>> librosa.display.specshow(tonnetz, y_axis='tonnetz')\n >>> plt.colorbar()\n >>> plt.title('Tonal Centroids (Tonnetz)')\n >>> plt.subplot(2, 1, 2)\n >>> librosa.display.specshow(librosa.feature.chroma_cqt(y, sr=sr),\n ... y_axis='chroma', x_axis='time')\n >>> plt.colorbar()\n >>> plt.title('Chroma')\n >>> plt.tight_layout()", "scope": {"holder": "librosa-librosa", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/librosa/librosa/blob/180e8e6eb8f958fa6b20b8cba389f7945d508247/examples/estimate_tuning.py#L15-L28", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:librosa-librosa:estimate_tuning-313e61d116@held-out", "question": "Load an audio file and estimate tuning (in cents)", "scope": {"holder": "librosa-librosa", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/librosa/librosa/blob/180e8e6eb8f958fa6b20b8cba389f7945d508247/librosa/core/harmonic.py#L13-L104", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:librosa-librosa:salience-366ab5da31@held-out", "question": "Harmonic salience function.\n\n Parameters\n ----------\n S : np.ndarray [shape=(d, n)]\n input time frequency magnitude representation (stft, ifgram, etc).\n Must be real-valued and non-negative.\n freqs : np.ndarray, shape=(S.shape[axis])\n The frequency values corresponding to S's elements along the\n chosen axis.\n h_range : list-like, non-negative\n Harmonics to include in salience computation. The first harmonic (1)\n corresponds to `S` itself. Values less than one (e.g., 1/2) correspond\n to sub-harmonics.\n weights : list-like\n The weight to apply to each harmonic in the summation. (default:\n uniform weights). Must be the same length as `harmonics`.\n aggregate : function\n aggregation function (default: `np.average`)\n If `aggregate=np.average`, then a weighted average is\n computed per-harmonic according to the specified weights.\n For all other aggregation functions, all harmonics\n are treated equally.\n filter_peaks : bool\n If true, returns harmonic summation only on frequencies of peak\n magnitude. Otherwise returns harmonic summation over the full spectrum.\n Defaults to True.\n fill_value : float\n The value to fill non-peaks in the output representation. (default:\n np.nan) Only used if `filter_peaks == True`.\n kind : str\n Interpolation type for harmonic estimation.\n See `scipy.interpolate.interp1d`.\n axis : int\n The axis along which to compute harmonics\n\n Returns\n -------\n S_sal : np.ndarray, shape=(len(h_range), [x.shape])\n `S_sal` will have the same shape as `S`, and measure\n the overal harmonic energy at each frequency.\n\n See Also\n --------\n interp_harmonics\n\n Examples\n --------\n >>> y, sr = librosa.load(librosa.util.example_audio_file(),\n ... duration=15, offset=30)\n >>> S = np.abs(librosa.stft(y))\n >>> freqs = librosa.core.fft_frequencies(sr)\n >>> harms = [1, 2, 3, 4]\n >>> weights = [1.0, 0.5, 0.33, 0.25]\n >>> S_sal = librosa.salience(S, freqs, harms, weights, fill_value=0)\n >>> print(S_sal.shape)\n (1025, 646)\n >>> import matplotlib.pyplot as plt\n >>> plt.figure()\n >>> librosa.display.specshow(librosa.amplitude_to_db(S_sal,\n ... ref=np.max),\n ... sr=sr, y_axis='log', x_axis='time')\n >>> plt.colorbar()\n >>> plt.title('Salience spectrogram')\n >>> plt.tight_layout()", "scope": {"holder": "librosa-librosa", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/librosa/librosa/blob/180e8e6eb8f958fa6b20b8cba389f7945d508247/librosa/core/harmonic.py#L221-L328", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:librosa-librosa:harmonics_1d-51c53f9c9b@held-out", "question": "Populate a harmonic tensor from a time-frequency representation.\n\n Parameters\n ----------\n harmonic_out : np.ndarray, shape=(len(h_range), X.shape)\n The output array to store harmonics\n\n X : np.ndarray\n The input energy\n\n freqs : np.ndarray, shape=(x.shape[axis])\n The frequency values corresponding to x's elements along the\n chosen axis.\n\n h_range : list-like, non-negative\n Harmonics to compute. The first harmonic (1) corresponds to `x`\n itself.\n Values less than one (e.g., 1/2) correspond to sub-harmonics.\n\n kind : str\n Interpolation type. See `scipy.interpolate.interp1d`.\n\n fill_value : float\n The value to fill when extrapolating beyond the observed\n frequency range.\n\n axis : int\n The axis along which to compute harmonics\n\n See Also\n --------\n harmonics\n scipy.interpolate.interp1d\n\n\n Examples\n --------\n Estimate the harmonics of a time-averaged tempogram\n\n >>> y, sr = librosa.load(librosa.util.example_audio_file(),\n ... duration=15, offset=30)\n >>> # Compute the time-varying tempogram and average over time\n >>> tempi = np.mean(librosa.feature.tempogram(y=y, sr=sr), axis=1)\n >>> # We'll measure the first five harmonics\n >>> h_range = [1, 2, 3, 4, 5]\n >>> f_tempo = librosa.tempo_frequencies(len(tempi), sr=sr)\n >>> # Build the harmonic tensor\n >>> t_harmonics = librosa.interp_harmonics(tempi, f_tempo, h_range)\n >>> print(t_harmonics.shape)\n (5, 384)\n\n >>> # And plot the results\n >>> import matplotlib.pyplot as plt\n >>> plt.figure()\n >>> librosa.display.specshow(t_harmonics, x_axis='tempo', sr=sr)\n >>> plt.yticks(0.5 + np.arange(len(h_range)),\n ... ['{:.3g}'.format(_) for _ in h_range])\n >>> plt.ylabel('Harmonic')\n >>> plt.xlabel('Tempo (BPM)')\n >>> plt.tight_layout()\n\n We can also compute frequency harmonics for spectrograms.\n To calculate subharmonic energy, use values < 1.\n\n >>> h_range = [1./3, 1./2, 1, 2, 3, 4]\n >>> S = np.abs(librosa.stft(y))\n >>> fft_freqs = librosa.fft_frequencies(sr=sr)\n >>> S_harm = librosa.interp_harmonics(S, fft_freqs, h_range, axis=0)\n >>> print(S_harm.shape)\n (6, 1025, 646)\n\n >>> plt.figure()\n >>> for i, _sh in enumerate(S_harm, 1):\n ... plt.subplot(3,2,i)\n ... librosa.display.specshow(librosa.amplitude_to_db(_sh,\n ... ref=S.max()),\n ... sr=sr, y_axis='log')\n ... plt.title('h={:.3g}'.format(h_range[i-1]))\n ... plt.yticks([])\n >>> plt.tight_layout()", "scope": {"holder": "librosa-librosa", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/librosa/librosa/blob/180e8e6eb8f958fa6b20b8cba389f7945d508247/librosa/core/audio.py#L952-L1017", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:librosa-librosa:tone-8012f8abcb@held-out", "question": "Returns a pure tone signal. The signal generated is a cosine wave.\n\n Parameters\n ----------\n frequency : float > 0\n frequency\n\n sr : number > 0\n desired sampling rate of the output signal\n\n length : int > 0\n desired number of samples in the output signal. When both `duration` and `length` are defined,\n `length` would take priority.\n\n duration : float > 0\n desired duration in seconds. When both `duration` and `length` are defined, `length` would take priority.\n\n phi : float or None\n phase offset, in radians. If unspecified, defaults to `-np.pi * 0.5`.\n\n\n Returns\n -------\n tone_signal : np.ndarray [shape=(length,), dtype=float64]\n Synthesized pure sine tone signal\n\n\n Raises\n ------\n ParameterError\n - If `frequency` is not provided.\n - If neither `length` nor `duration` are provided.\n\n\n Examples\n --------\n >>> # Generate a pure sine tone A4\n >>> tone = librosa.tone(440, duration=1)\n\n >>> # Or generate the same signal using `length`\n >>> tone = librosa.tone(440, sr=22050, length=22050)\n\n Display spectrogram\n\n >>> import matplotlib.pyplot as plt\n >>> plt.figure()\n >>> S = librosa.feature.melspectrogram(y=tone)\n >>> librosa.display.specshow(librosa.power_to_db(S, ref=np.max),\n ... x_axis='time', y_axis='mel')", "scope": {"holder": "librosa-librosa", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/librosa/librosa/blob/180e8e6eb8f958fa6b20b8cba389f7945d508247/librosa/segment.py#L54-L287", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:librosa-librosa:recurrence_matrix-bd22456f6d@held-out", "question": "Compute a recurrence matrix from a data matrix.\n\n `rec[i, j]` is non-zero if (`data[:, i]`, `data[:, j]`) are\n k-nearest-neighbors and `|i - j| >= width`\n\n The specific value of `rec[i, j]` can have several forms, governed\n by the `mode` parameter below:\n\n - Connectivity: `rec[i, j] = 1 or 0` indicates that frames `i` and `j` are repetitions\n\n - Affinity: `rec[i, j] > 0` measures how similar frames `i` and `j` are. This is also\n known as a (sparse) self-similarity matrix.\n\n - Distance: `rec[, j] > 0` measures how distant frames `i` and `j` are. This is also\n known as a (sparse) self-distance matrix.\n\n The general term *recurrence matrix* can refer to any of the three forms above.\n\n\n Parameters\n ----------\n data : np.ndarray\n A feature matrix\n\n k : int > 0 [scalar] or None\n the number of nearest-neighbors for each sample\n\n Default: `k = 2 * ceil(sqrt(t - 2 * width + 1))`,\n or `k = 2` if `t <= 2 * width + 1`\n\n width : int >= 1 [scalar]\n only link neighbors `(data[:, i], data[:, j])`\n if `|i - j| >= width`\n\n `width` cannot exceed the length of the data.\n\n metric : str\n Distance metric to use for nearest-neighbor calculation.\n\n See `sklearn.neighbors.NearestNeighbors` for details.\n\n sym : bool [scalar]\n set `sym=True` to only link mutual nearest-neighbors\n\n sparse : bool [scalar]\n if False, returns a dense type (ndarray)\n if True, returns a sparse type (scipy.sparse.csr_matrix)\n\n mode : str, {'connectivity', 'distance', 'affinity'}\n If 'connectivity', a binary connectivity matrix is produced.\n\n If 'distance', then a non-zero entry contains the distance between\n points.\n\n If 'affinity', then non-zero entries are mapped to\n `exp( - distance(i, j) / bandwidth)` where `bandwidth` is\n as specified below.\n\n bandwidth : None or float > 0\n If using ``mode='affinity'``, this can be used to set the\n bandwidth on the affinity kernel.\n\n If no value is provided, it is set automatically to the median\n distance between furthest nearest neighbors.\n\n self : bool\n If `True`, then the main diagonal is populated with self-links:\n 0 if ``mode='distance'``, and 1 otherwise.\n\n If `False`, the main diagonal is left empty.\n\n axis : int\n The axis along which to compute recurrence.\n By default, the last index (-1) is taken.\n\n Returns\n -------\n rec : np.ndarray or scipy.sparse.csr_matrix, [shape=(t, t)]\n Recurrence matrix\n\n See Also\n --------\n sklearn.neighbors.NearestNeighbors\n scipy.spatial.distance.cdist\n librosa.feature.stack_memory\n recurrence_to_lag\n\n Notes\n -----\n This function caches at level 30.\n\n Examples\n --------\n Find nearest neighbors in MFCC space\n\n >>> y, sr = librosa.load(librosa.util.example_audio_file())\n >>> mfcc = librosa.feature.mfcc(y=y, sr=sr)\n >>> R = librosa.segment.recurrence_matrix(mfcc)\n\n Or fix the number of nearest neighbors to 5\n\n >>> R = librosa.segment.recurrence_matrix(mfcc, k=5)\n\n Suppress neighbors within +- 7 samples\n\n >>> R = librosa.segment.recurrence_matrix(mfcc, width=7)\n\n Use cosine similarity instead of Euclidean distance\n\n >>> R = librosa.segment.recurrence_matrix(mfcc, metric='cosine')\n\n Require mutual nearest neighbors\n\n >>> R = librosa.segment.recurrence_matrix(mfcc, sym=True)\n\n Use an affinity matrix instead of binary connectivity\n\n >>> R_aff = librosa.segment.recurrence_matrix(mfcc, mode='affinity')\n\n Plot the feature and recurrence matrices\n\n >>> import matplotlib.pyplot as plt\n >>> plt.figure(figsize=(8, 4))\n >>> plt.subplot(1, 2, 1)\n >>> librosa.display.specshow(R, x_axis='time', y_axis='time')\n >>> plt.title('Binary recurrence (symmetric)')\n >>> plt.subplot(1, 2, 2)\n >>> librosa.display.specshow(R_aff, x_axis='time', y_axis='time',\n ... cmap='magma_r')\n >>> plt.title('Affinity recurrence')\n >>> plt.tight_layout()", "scope": {"holder": "librosa-librosa", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/librosa/librosa/blob/180e8e6eb8f958fa6b20b8cba389f7945d508247/librosa/segment.py#L563-L655", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:librosa-librosa:subsegment-ac1a00a338@held-out", "question": "Sub-divide a segmentation by feature clustering.\n\n Given a set of frame boundaries (`frames`), and a data matrix (`data`),\n each successive interval defined by `frames` is partitioned into\n `n_segments` by constrained agglomerative clustering.\n\n .. note::\n If an interval spans fewer than `n_segments` frames, then each\n frame becomes a sub-segment.\n\n Parameters\n ----------\n data : np.ndarray\n Data matrix to use in clustering\n\n frames : np.ndarray [shape=(n_boundaries,)], dtype=int, non-negative]\n Array of beat or segment boundaries, as provided by\n `librosa.beat.beat_track`,\n `librosa.onset.onset_detect`,\n or `agglomerative`.\n\n n_segments : int > 0\n Maximum number of frames to sub-divide each interval.\n\n axis : int\n Axis along which to apply the segmentation.\n By default, the last index (-1) is taken.\n\n Returns\n -------\n boundaries : np.ndarray [shape=(n_subboundaries,)]\n List of sub-divided segment boundaries\n\n See Also\n --------\n agglomerative : Temporal segmentation\n librosa.onset.onset_detect : Onset detection\n librosa.beat.beat_track : Beat tracking\n\n Notes\n -----\n This function caches at level 30.\n\n Examples\n --------\n Load audio, detect beat frames, and subdivide in twos by CQT\n\n >>> y, sr = librosa.load(librosa.util.example_audio_file(), duration=8)\n >>> tempo, beats = librosa.beat.beat_track(y=y, sr=sr, hop_length=512)\n >>> beat_times = librosa.frames_to_time(beats, sr=sr, hop_length=512)\n >>> cqt = np.abs(librosa.cqt(y, sr=sr, hop_length=512))\n >>> subseg = librosa.segment.subsegment(cqt, beats, n_segments=2)\n >>> subseg_t = librosa.frames_to_time(subseg, sr=sr, hop_length=512)\n >>> subseg\n array([ 0, 2, 4, 21, 23, 26, 43, 55, 63, 72, 83,\n 97, 102, 111, 122, 137, 142, 153, 162, 180, 182, 185,\n 202, 210, 221, 231, 241, 256, 261, 271, 281, 296, 301,\n 310, 320, 339, 341, 344, 361, 368, 382, 389, 401, 416,\n 420, 430, 436, 451, 456, 465, 476, 489, 496, 503, 515,\n 527, 535, 544, 553, 558, 571, 578, 590, 607, 609, 638])\n\n >>> import matplotlib.pyplot as plt\n >>> plt.figure()\n >>> librosa.display.specshow(librosa.amplitude_to_db(cqt,\n ... ref=np.max),\n ... y_axis='cqt_hz', x_axis='time')\n >>> lims = plt.gca().get_ylim()\n >>> plt.vlines(beat_times, lims[0], lims[1], color='lime', alpha=0.9,\n ... linewidth=2, label='Beats')\n >>> plt.vlines(subseg_t, lims[0], lims[1], color='linen', linestyle='--',\n ... linewidth=1.5, alpha=0.5, label='Sub-beats')\n >>> plt.legend(frameon=True, shadow=True)\n >>> plt.title('CQT + Beat and sub-beat markers')\n >>> plt.tight_layout()", "scope": {"holder": "librosa-librosa", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/librosa/librosa/blob/180e8e6eb8f958fa6b20b8cba389f7945d508247/librosa/util/utils.py#L34-L107", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:librosa-librosa:frame-686cc859b5@held-out", "question": "Slice a time series into overlapping frames.\n\n This implementation uses low-level stride manipulation to avoid\n redundant copies of the time series data.\n\n Parameters\n ----------\n y : np.ndarray [shape=(n,)]\n Time series to frame. Must be one-dimensional and contiguous\n in memory.\n\n frame_length : int > 0 [scalar]\n Length of the frame in samples\n\n hop_length : int > 0 [scalar]\n Number of samples to hop between frames\n\n Returns\n -------\n y_frames : np.ndarray [shape=(frame_length, N_FRAMES)]\n An array of frames sampled from `y`:\n `y_frames[i, j] == y[j * hop_length + i]`\n\n Raises\n ------\n ParameterError\n If `y` is not contiguous in memory, not an `np.ndarray`, or\n not one-dimensional. See `np.ascontiguous()` for details.\n\n If `hop_length < 1`, frames cannot advance.\n\n If `len(y) < frame_length`.\n\n Examples\n --------\n Extract 2048-sample frames from `y` with a hop of 64 samples per frame\n\n >>> y, sr = librosa.load(librosa.util.example_audio_file())\n >>> librosa.util.frame(y, frame_length=2048, hop_length=64)\n array([[ -9.216e-06, 7.710e-06, ..., -2.117e-06, -4.362e-07],\n [ 2.518e-06, -6.294e-06, ..., -1.775e-05, -6.365e-06],\n ...,\n [ -7.429e-04, 5.173e-03, ..., 1.105e-05, -5.074e-06],\n [ 2.169e-03, 4.867e-03, ..., 3.666e-06, -5.571e-06]], dtype=float32)", "scope": {"holder": "librosa-librosa", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/librosa/librosa/blob/180e8e6eb8f958fa6b20b8cba389f7945d508247/librosa/util/utils.py#L455-L549", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:librosa-librosa:axis_sort-001409eac3@held-out", "question": "Sort an array along its rows or columns.\n\n Examples\n --------\n Visualize NMF output for a spectrogram S\n\n >>> # Sort the columns of W by peak frequency bin\n >>> y, sr = librosa.load(librosa.util.example_audio_file())\n >>> S = np.abs(librosa.stft(y))\n >>> W, H = librosa.decompose.decompose(S, n_components=32)\n >>> W_sort = librosa.util.axis_sort(W)\n\n Or sort by the lowest frequency bin\n\n >>> W_sort = librosa.util.axis_sort(W, value=np.argmin)\n\n Or sort the rows instead of the columns\n\n >>> W_sort_rows = librosa.util.axis_sort(W, axis=0)\n\n Get the sorting index also, and use it to permute the rows of H\n\n >>> W_sort, idx = librosa.util.axis_sort(W, index=True)\n >>> H_sort = H[idx, :]\n\n >>> import matplotlib.pyplot as plt\n >>> plt.figure()\n >>> plt.subplot(2, 2, 1)\n >>> librosa.display.specshow(librosa.amplitude_to_db(W, ref=np.max),\n ... y_axis='log')\n >>> plt.title('W')\n >>> plt.subplot(2, 2, 2)\n >>> librosa.display.specshow(H, x_axis='time')\n >>> plt.title('H')\n >>> plt.subplot(2, 2, 3)\n >>> librosa.display.specshow(librosa.amplitude_to_db(W_sort,\n ... ref=np.max),\n ... y_axis='log')\n >>> plt.title('W sorted')\n >>> plt.subplot(2, 2, 4)\n >>> librosa.display.specshow(H_sort, x_axis='time')\n >>> plt.title('H sorted')\n >>> plt.tight_layout()\n\n\n Parameters\n ----------\n S : np.ndarray [shape=(d, n)]\n Array to be sorted\n\n axis : int [scalar]\n The axis along which to compute the sorting values\n\n - `axis=0` to sort rows by peak column index\n - `axis=1` to sort columns by peak row index\n\n index : boolean [scalar]\n If true, returns the index array as well as the permuted data.\n\n value : function\n function to return the index corresponding to the sort order.\n Default: `np.argmax`.\n\n Returns\n -------\n S_sort : np.ndarray [shape=(d, n)]\n `S` with the columns or rows permuted in sorting order\n\n idx : np.ndarray (optional) [shape=(d,) or (n,)]\n If `index == True`, the sorting index used to permute `S`.\n Length of `idx` corresponds to the selected `axis`.\n\n Raises\n ------\n ParameterError\n If `S` does not have exactly 2 dimensions (`S.ndim != 2`)", "scope": {"holder": "librosa-librosa", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/librosa/librosa/blob/180e8e6eb8f958fa6b20b8cba389f7945d508247/librosa/util/utils.py#L1101-L1167", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:librosa-librosa:roll_sparse-5bbbfdca1f@held-out", "question": "Sparse matrix roll\n\n This operation is equivalent to ``numpy.roll``, but operates on sparse matrices.\n\n Parameters\n ----------\n x : scipy.sparse.spmatrix or np.ndarray\n The sparse matrix input\n\n shift : int\n The number of positions to roll the specified axis\n\n axis : (0, 1, -1)\n The axis along which to roll.\n\n Returns\n -------\n x_rolled : same type as `x`\n The rolled matrix, with the same format as `x`\n\n See Also\n --------\n numpy.roll\n\n Examples\n --------\n >>> # Generate a random sparse binary matrix\n >>> X = scipy.sparse.lil_matrix(np.random.randint(0, 2, size=(5,5)))\n >>> X_roll = roll_sparse(X, 2, axis=0) # Roll by 2 on the first axis\n >>> X_dense_r = roll_sparse(X.toarray(), 2, axis=0) # Equivalent dense roll\n >>> np.allclose(X_roll, X_dense_r.toarray())\n True", "scope": {"holder": "librosa-librosa", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/librosa/librosa/blob/180e8e6eb8f958fa6b20b8cba389f7945d508247/librosa/util/utils.py#L1510-L1574", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:librosa-librosa:tiny-2aca64dc5d@held-out", "question": "Compute the tiny-value corresponding to an input's data type.\n\n This is the smallest \"usable\" number representable in `x`'s\n data type (e.g., float32).\n\n This is primarily useful for determining a threshold for\n numerical underflow in division or multiplication operations.\n\n Parameters\n ----------\n x : number or np.ndarray\n The array to compute the tiny-value for.\n All that matters here is `x.dtype`.\n\n Returns\n -------\n tiny_value : float\n The smallest positive usable number for the type of `x`.\n If `x` is integer-typed, then the tiny value for `np.float32`\n is returned instead.\n\n See Also\n --------\n numpy.finfo\n\n Examples\n --------\n\n For a standard double-precision floating point number:\n\n >>> librosa.util.tiny(1.0)\n 2.2250738585072014e-308\n\n Or explicitly as double-precision\n\n >>> librosa.util.tiny(np.asarray(1e-5, dtype=np.float64))\n 2.2250738585072014e-308\n\n Or complex numbers\n\n >>> librosa.util.tiny(1j)\n 2.2250738585072014e-308\n\n Single-precision floating point:\n\n >>> librosa.util.tiny(np.asarray(1e-5, dtype=np.float32))\n 1.1754944e-38\n\n Integer\n\n >>> librosa.util.tiny(5)\n 1.1754944e-38", "scope": {"holder": "librosa-librosa", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/open-mmlab/mmcv/blob/0d77f61450aab4dde8b8585a577cc496acb95d7f/mmcv/video/io.py#L288-L332", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:open-mmlab-mmcv:frames2video-575b49aff3@held-out", "question": "Read the frame images from a directory and join them as a video\n\n Args:\n frame_dir (str): The directory containing video frames.\n video_file (str): Output filename.\n fps (float): FPS of the output video.\n fourcc (str): Fourcc of the output video, this should be compatible\n with the output file type.\n filename_tmpl (str): Filename template with the index as the variable.\n start (int): Starting frame index.\n end (int): Ending frame index.\n show_progress (bool): Whether to show a progress bar.", "scope": {"holder": "open-mmlab-mmcv", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/open-mmlab/mmcv/blob/0d77f61450aab4dde8b8585a577cc496acb95d7f/mmcv/video/io.py#L207-L250", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:open-mmlab-mmcv:VideoReader.cvt2frames-a92eed5714@held-out", "question": "Convert a video to frame images\n\n Args:\n frame_dir (str): Output directory to store all the frame images.\n file_start (int): Filenames will start from the specified number.\n filename_tmpl (str): Filename template with the index as the\n placeholder.\n start (int): The starting frame index.\n max_num (int): Maximum number of frames to be written.\n show_progress (bool): Whether to show a progress bar.", "scope": {"holder": "open-mmlab-mmcv", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/open-mmlab/mmcv/blob/0d77f61450aab4dde8b8585a577cc496acb95d7f/mmcv/fileio/io.py#L13-L40", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:open-mmlab-mmcv:load-2dc2a99dd8@held-out", "question": "Load data from json/yaml/pickle files.\n\n This method provides a unified api for loading data from serialized files.\n\n Args:\n file (str or file-like object): Filename or a file-like object.\n file_format (str, optional): If not specified, the file format will be\n inferred from the file extension, otherwise use the specified one.\n Currently supported formats include \"json\", \"yaml/yml\" and\n \"pickle/pkl\".\n\n Returns:\n The content from the file.", "scope": {"holder": "open-mmlab-mmcv", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/open-mmlab/mmcv/blob/0d77f61450aab4dde8b8585a577cc496acb95d7f/mmcv/runner/priority.py#L35-L53", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:open-mmlab-mmcv:get_priority-af060fb4c2@held-out", "question": "Get priority value.\n\n Args:\n priority (int or str or :obj:`Priority`): Priority.\n\n Returns:\n int: The priority value.", "scope": {"holder": "open-mmlab-mmcv", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/open-mmlab/mmcv/blob/0d77f61450aab4dde8b8585a577cc496acb95d7f/mmcv/visualization/image.py#L69-L132", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:open-mmlab-mmcv:imshow_det_bboxes-aa7c4d7fc7@held-out", "question": "Draw bboxes and class labels (with scores) on an image.\n\n Args:\n img (str or ndarray): The image to be displayed.\n bboxes (ndarray): Bounding boxes (with scores), shaped (n, 4) or\n (n, 5).\n labels (ndarray): Labels of bboxes.\n class_names (list[str]): Names of each classes.\n score_thr (float): Minimum score of bboxes to be shown.\n bbox_color (str or tuple or :obj:`Color`): Color of bbox lines.\n text_color (str or tuple or :obj:`Color`): Color of texts.\n thickness (int): Thickness of lines.\n font_scale (float): Font scales of texts.\n show (bool): Whether to show the image.\n win_name (str): The window name.\n wait_time (int): Value of waitKey param.\n out_file (str or None): The filename to write the image.", "scope": {"holder": "open-mmlab-mmcv", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/open-mmlab/mmcv/blob/0d77f61450aab4dde8b8585a577cc496acb95d7f/mmcv/video/optflow.py#L8-L57", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:open-mmlab-mmcv:flowread-9388896d28@held-out", "question": "Read an optical flow map.\n\n Args:\n flow_or_path (ndarray or str): A flow map or filepath.\n quantize (bool): whether to read quantized pair, if set to True,\n remaining args will be passed to :func:`dequantize_flow`.\n concat_axis (int): The axis that dx and dy are concatenated,\n can be either 0 or 1. Ignored if quantize is False.\n\n Returns:\n ndarray: Optical flow represented as a (h, w, 2) numpy array", "scope": {"holder": "open-mmlab-mmcv", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/open-mmlab/mmcv/blob/0d77f61450aab4dde8b8585a577cc496acb95d7f/mmcv/runner/checkpoint.py#L142-L154", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:open-mmlab-mmcv:weights_to_cpu-3f4758c043@held-out", "question": "Copy a model state_dict to cpu.\n\n Args:\n state_dict (OrderedDict): Model weights on GPU.\n\n Returns:\n OrderedDict: Model weights on GPU.", "scope": {"holder": "open-mmlab-mmcv", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/open-mmlab/mmcv/blob/0d77f61450aab4dde8b8585a577cc496acb95d7f/mmcv/image/io.py#L23-L44", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:open-mmlab-mmcv:imread-1dfe850b02@held-out", "question": "Read an image.\n\n Args:\n img_or_path (ndarray or str): Either a numpy array or image path.\n If it is a numpy array (loaded image), then it will be returned\n as is.\n flag (str): Flags specifying the color type of a loaded image,\n candidates are `color`, `grayscale` and `unchanged`.\n\n Returns:\n ndarray: Loaded image array.", "scope": {"holder": "open-mmlab-mmcv", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/open-mmlab/mmcv/blob/0d77f61450aab4dde8b8585a577cc496acb95d7f/mmcv/image/io.py#L63-L79", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:open-mmlab-mmcv:imwrite-1ba269b9f5@held-out", "question": "Write image to file\n\n Args:\n img (ndarray): Image array to be written.\n file_path (str): Image file path.\n params (None or list): Same as opencv's :func:`imwrite` interface.\n auto_mkdir (bool): If the parent folder of `file_path` does not exist,\n whether to create it automatically.\n\n Returns:\n bool: Successful or not.", "scope": {"holder": "open-mmlab-mmcv", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/open-mmlab/mmcv/blob/0d77f61450aab4dde8b8585a577cc496acb95d7f/mmcv/utils/misc.py#L138-L173", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:open-mmlab-mmcv:check_prerequisites-67a0a36501@held-out", "question": "A decorator factory to check if prerequisites are satisfied.\n\n Args:\n prerequisites (str of list[str]): Prerequisites to be checked.\n checker (callable): The checker method that returns True if a\n prerequisite is meet, False otherwise.\n msg_tmpl (str): The message template with two variables.\n\n Returns:\n decorator: A specific decorator.", "scope": {"holder": "open-mmlab-mmcv", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/open-mmlab/mmcv/blob/0d77f61450aab4dde8b8585a577cc496acb95d7f/mmcv/utils/timer.py#L56-L61", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:open-mmlab-mmcv:Timer.start-b874376d3c@held-out", "question": "Start the timer.", "scope": {"holder": "open-mmlab-mmcv", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/open-mmlab/mmcv/blob/0d77f61450aab4dde8b8585a577cc496acb95d7f/mmcv/parallel/scatter_gather.py#L44-L54", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:open-mmlab-mmcv:scatter_kwargs-9fe1e026db@held-out", "question": "Scatter with support for kwargs dictionary", "scope": {"holder": "open-mmlab-mmcv", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/howie6879/ruia/blob/2dc5262fc9c3e902a8faa7d5fa2f046f9d9ee1fa/ruia/spider.py#L327-L347", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:howie6879-ruia:Spider.handle_request-85e8c1550f@held-out", "question": "Wrap request with middleware.\n :param request:\n :return:", "scope": {"holder": "howie6879-ruia", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/howie6879/ruia/blob/2dc5262fc9c3e902a8faa7d5fa2f046f9d9ee1fa/ruia/spider.py#L410-L427", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:howie6879-ruia:Spider.start_master-df6efa3b39@held-out", "question": "Actually start crawling.", "scope": {"holder": "howie6879-ruia", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/ansible/ansible-lint/blob/b4a8743794e592698c32e760bc774a85f8eebeb5/lib/ansiblelint/utils.py#L599-L634", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:ansible-ansible-lint:append_skipped_rules-5be23fbf24@held-out", "question": "Uses ruamel.yaml to parse comments then adds a\n skipped_rules list to the task (or meta yaml block)", "scope": {"holder": "ansible-ansible-lint", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Microsoft/botbuilder-python/blob/274663dd91c811bae6ac4488915ba5880771b0a7/libraries/botbuilder-core/botbuilder/core/bot_state.py#L122-L135", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Microsoft-botbuilder-python:BotState.delete-d713553f93@held-out", "question": "Delete any state currently stored in this state scope.\n \n :param turn_context: The context object for this turn.\n :return: None", "scope": {"holder": "Microsoft-botbuilder-python", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Microsoft/botbuilder-python/blob/274663dd91c811bae6ac4488915ba5880771b0a7/libraries/botbuilder-core/botbuilder/core/bot_framework_adapter.py#L49-L75", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Microsoft-botbuilder-python:BotFrameworkAdapter.create_conversation-bf5e6c76c1@held-out", "question": "Starts a new conversation with a user. This is typically used to Direct Message (DM) a member\n of a group.\n :param reference:\n :param logic:\n :return:", "scope": {"holder": "Microsoft-botbuilder-python", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Microsoft/botbuilder-python/blob/274663dd91c811bae6ac4488915ba5880771b0a7/libraries/botframework-connector/azure_bdist_wheel.py#L153-L156", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Microsoft-botbuilder-python:bdist_wheel.wheel_dist_name-0bc76c20ad@held-out", "question": "Return distribution full name with - replaced with _", "scope": {"holder": "Microsoft-botbuilder-python", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Microsoft/botbuilder-python/blob/274663dd91c811bae6ac4488915ba5880771b0a7/libraries/botframework-connector/azure_bdist_wheel.py#L355-L366", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Microsoft-botbuilder-python:bdist_wheel.add_requirements-48f6710b71@held-out", "question": "Add additional requirements from setup.cfg to file metadata_path", "scope": {"holder": "Microsoft-botbuilder-python", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Microsoft/botbuilder-python/blob/274663dd91c811bae6ac4488915ba5880771b0a7/libraries/botframework-connector/botframework/connector/operations/_conversations_operations.py#L41-L98", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Microsoft-botbuilder-python:ConversationsOperations.get_conversations-4318d94c2f@held-out", "question": "GetConversations.\n\n List the Conversations in which this bot has participated.\n GET from this method with a skip token\n The return value is a ConversationsResult, which contains an array of\n ConversationMembers and a skip token. If the skip token is not empty,\n then\n there are further values to be returned. Call this method again with\n the returned token to get more values.\n Each ConversationMembers object contains the ID of the conversation and\n an array of ChannelAccounts that describe the members of the\n conversation.\n\n :param continuation_token: skip or continuation token\n :type continuation_token: str\n :param dict custom_headers: headers that will be added to the request\n :param bool raw: returns the direct response alongside the\n deserialized response\n :param operation_config: :ref:`Operation configuration\n overrides<msrest:optionsforoperations>`.\n :return: ConversationsResult or ClientRawResponse if raw=true\n :rtype: ~botframework.connector.models.ConversationsResult or\n ~msrest.pipeline.ClientRawResponse\n :raises:\n :class:`ErrorResponseException<botframework.connector.models.ErrorResponseException>`", "scope": {"holder": "Microsoft-botbuilder-python", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Microsoft/botbuilder-python/blob/274663dd91c811bae6ac4488915ba5880771b0a7/libraries/botframework-connector/botframework/connector/operations/_conversations_operations.py#L101-L173", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Microsoft-botbuilder-python:ConversationsOperations.create_conversation-04d24b922e@held-out", "question": "CreateConversation.\n\n Create a new Conversation.\n POST to this method with a\n * Bot being the bot creating the conversation\n * IsGroup set to true if this is not a direct message (default is\n false)\n * Array containing the members to include in the conversation\n The return value is a ResourceResponse which contains a conversation id\n which is suitable for use\n in the message payload and REST API uris.\n Most channels only support the semantics of bots initiating a direct\n message conversation. An example of how to do that would be:\n ```\n var resource = await connector.conversations.CreateConversation(new\n ConversationParameters(){ Bot = bot, members = new ChannelAccount[] {\n new ChannelAccount(\"user1\") } );\n await connect.Conversations.SendToConversationAsync(resource.Id, new\n Activity() ... ) ;\n ```.\n\n :param parameters: Parameters to create the conversation from\n :type parameters:\n ~botframework.connector.models.ConversationParameters\n :param dict custom_headers: headers that will be added to the request\n :param bool raw: returns the direct response alongside the\n deserialized response\n :param operation_config: :ref:`Operation configuration\n overrides<msrest:optionsforoperations>`.\n :return: ConversationResourceResponse or ClientRawResponse if raw=true\n :rtype: ~botframework.connector.models.ConversationResourceResponse or\n ~msrest.pipeline.ClientRawResponse\n :raises:\n :class:`ErrorResponseException<botframework.connector.models.ErrorResponseException>`", "scope": {"holder": "Microsoft-botbuilder-python", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Microsoft/botbuilder-python/blob/274663dd91c811bae6ac4488915ba5880771b0a7/libraries/botbuilder-core/botbuilder/core/bot_telemetry_client.py#L29-L39", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Microsoft-botbuilder-python:BotTelemetryClient.track_exception-bfe1367dff@held-out", "question": "Send information about a single exception that occurred in the application.\n :param type: the type of the exception that was thrown.\n :param value: the exception that the client wants to send.\n :param tb: the traceback information as returned by :func:`sys.exc_info`.\n :param properties: the set of custom properties the client wants attached to this data item. (defaults to: None)\n :param measurements: the set of custom measurements the client wants to attach to this data item. (defaults to: None)", "scope": {"holder": "Microsoft-botbuilder-python", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Microsoft/botbuilder-python/blob/274663dd91c811bae6ac4488915ba5880771b0a7/libraries/botbuilder-core/botbuilder/core/message_factory.py#L73-L90", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Microsoft-botbuilder-python:MessageFactory.attachment-7935fb2185@held-out", "question": "Returns a single message activity containing an attachment.\n\n :Example:\n message = MessageFactory.attachment(CardFactory.hero_card(HeroCard(title='White T-Shirt',\n images=[CardImage(url='https://example.com/whiteShirt.jpg')],\n buttons=[CardAction(title='buy')])))\n await context.send_activity(message)\n\n :param attachment:\n :param text:\n :param speak:\n :param input_hint:\n :return:", "scope": {"holder": "Microsoft-botbuilder-python", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Microsoft/botbuilder-python/blob/274663dd91c811bae6ac4488915ba5880771b0a7/libraries/botbuilder-dialogs/botbuilder/dialogs/dialog.py#L33-L40", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Microsoft-botbuilder-python:Dialog.telemetry_client-43476a0629@held-out", "question": "Sets the telemetry client for logging events.", "scope": {"holder": "Microsoft-botbuilder-python", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Microsoft/botbuilder-python/blob/274663dd91c811bae6ac4488915ba5880771b0a7/libraries/botbuilder-dialogs/botbuilder/dialogs/dialog.py#L63-L76", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Microsoft-botbuilder-python:Dialog.resume_dialog-39e1a01b69@held-out", "question": "Method called when an instance of the dialog is being returned to from another\n dialog that was started by the current instance using `begin_dialog()`.\n If this method is NOT implemented then the dialog will be automatically ended with a call\n to `end_dialog()`. Any result passed from the called dialog will be passed\n to the current dialog's parent. \n :param dc: The dialog context for the current turn of conversation.\n :param reason: Reason why the dialog resumed.\n :param result: (Optional) value returned from the dialog that was called. The type of the value returned is dependent on the dialog that was called.\n :return:", "scope": {"holder": "Microsoft-botbuilder-python", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Microsoft/botbuilder-python/blob/274663dd91c811bae6ac4488915ba5880771b0a7/libraries/botbuilder-ai/botbuilder/ai/luis/luis_recognizer.py#L152-L172", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Microsoft-botbuilder-python:LuisRecognizer.recognize-41a9ef6bd7@held-out", "question": "Return results of the analysis (Suggested actions and intents).\n \n :param turn_context: Context object containing information for a single turn of conversation with a user.\n :type turn_context: TurnContext\n :param telemetry_properties: Additional properties to be logged to telemetry with the LuisResult event, defaults to None\n :param telemetry_properties: Dict[str, str], optional\n :param telemetry_metrics: Additional metrics to be logged to telemetry with the LuisResult event, defaults to None\n :param telemetry_metrics: Dict[str, float], optional\n :return: The LUIS results of the analysis of the current message text in the current turn's context activity.\n :rtype: RecognizerResult", "scope": {"holder": "Microsoft-botbuilder-python", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Microsoft/botbuilder-python/blob/274663dd91c811bae6ac4488915ba5880771b0a7/libraries/botbuilder-ai/botbuilder/ai/luis/luis_recognizer.py#L174-L200", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Microsoft-botbuilder-python:LuisRecognizer.on_recognizer_result-fc2cd051e8@held-out", "question": "Invoked prior to a LuisResult being logged.\n \n :param recognizer_result: The Luis Results for the call.\n :type recognizer_result: RecognizerResult\n :param turn_context: Context object containing information for a single turn of conversation with a user.\n :type turn_context: TurnContext\n :param telemetry_properties: Additional properties to be logged to telemetry with the LuisResult event, defaults to None\n :param telemetry_properties: Dict[str, str], optional\n :param telemetry_metrics: Additional metrics to be logged to telemetry with the LuisResult event, defaults to None\n :param telemetry_metrics: Dict[str, float], optional", "scope": {"holder": "Microsoft-botbuilder-python", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Microsoft/botbuilder-python/blob/274663dd91c811bae6ac4488915ba5880771b0a7/libraries/botbuilder-azure/botbuilder/azure/cosmosdb_storage.py#L163-L174", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Microsoft-botbuilder-python:CosmosDbStorage.__create_si-1e7a7fbb03@held-out", "question": "Create a StoreItem from a result out of CosmosDB.\n\n :param result:\n :return StoreItem:", "scope": {"holder": "Microsoft-botbuilder-python", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Microsoft/botbuilder-python/blob/274663dd91c811bae6ac4488915ba5880771b0a7/libraries/botbuilder-core/botbuilder/core/storage.py#L62-L71", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Microsoft-botbuilder-python:calculate_change_hash-fa0ddf16ad@held-out", "question": "Utility function to calculate a change hash for a `StoreItem`.\n :param item:\n :return:", "scope": {"holder": "Microsoft-botbuilder-python", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Microsoft/botbuilder-python/blob/274663dd91c811bae6ac4488915ba5880771b0a7/libraries/botbuilder-dialogs/botbuilder/dialogs/dialog_context.py#L149-L173", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Microsoft-botbuilder-python:DialogContext.end_dialog-0d0eb9de73@held-out", "question": "Ends a dialog by popping it off the stack and returns an optional result to the dialog's\n parent. The parent dialog is the dialog that started the dialog being ended via a call to\n either \"begin_dialog\" or \"prompt\".\n The parent dialog will have its `Dialog.resume_dialog()` method invoked with any returned\n result. If the parent dialog hasn't implemented a `resume_dialog()` method then it will be\n automatically ended as well and the result passed to its parent. If there are no more\n parent dialogs on the stack then processing of the turn will end. \n :param result: (Optional) result to pass to the parent dialogs.\n :return:", "scope": {"holder": "Microsoft-botbuilder-python", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Microsoft/botbuilder-python/blob/274663dd91c811bae6ac4488915ba5880771b0a7/libraries/botbuilder-dialogs/botbuilder/dialogs/choices/channel.py#L93-L106", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Microsoft-botbuilder-python:Channel.get_channel_id-b8dd854e02@held-out", "question": "Get the Channel Id from the current Activity on the Turn Context.\n\n Args:\n turn_context (TurnContext): The Turn Context to retrieve the Activity's Channel Id from.\n\n Returns:\n str: The Channel Id from the Turn Context's Activity.", "scope": {"holder": "Microsoft-botbuilder-python", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Microsoft/botbuilder-python/blob/274663dd91c811bae6ac4488915ba5880771b0a7/samples/Console-EchoBot/adapter/console_adapter.py#L63-L86", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Microsoft-botbuilder-python:ConsoleAdapter.process_activity-1166415733@held-out", "question": "Begins listening to console input.\n :param logic:\n :return:", "scope": {"holder": "Microsoft-botbuilder-python", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Microsoft/botbuilder-python/blob/274663dd91c811bae6ac4488915ba5880771b0a7/libraries/botbuilder-core/botbuilder/core/card_factory.py#L101-L112", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Microsoft-botbuilder-python:CardFactory.receipt_card-95aa72d053@held-out", "question": "Returns an attachment for a receipt card. Will raise a TypeError if 'card' argument is not a ReceiptCard.\n :param card:\n :return:", "scope": {"holder": "Microsoft-botbuilder-python", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/circuit/instruction.py#L169-L192", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:Instruction.assemble-784cc7f0c4@held-out", "question": "Assemble a QasmQobjInstruction", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/extensions/standard/ubase.py#L50-L52", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:u_base-070355df53@held-out", "question": "Apply U to q.", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/extensions/standard/ubase.py#L33-L45", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:UBase.to_matrix-544cd1c9ba@held-out", "question": "Return a Numpy.array for the U3 gate.", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/tools/qcvv/fitters.py#L75-L90", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:shape_rb_data-97257d2346@held-out", "question": "Take the raw rb data and convert it into averages and std dev\n\n Args:\n raw_rb (numpy.array): m x n x l list where m is the number of seeds, n\n is the number of Clifford sequences and l is the number of qubits\n\n Return:\n numpy_array: 2 x n x l list where index 0 is the mean over seeds, 1 is\n the std dev overseeds", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/transpiler/passes/optimize_1q_gates.py#L194-L209", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:Optimize1qGates.compose_u3-4b733ae097@held-out", "question": "Return a triple theta, phi, lambda for the product.\n\n u3(theta, phi, lambda)\n = u3(theta1, phi1, lambda1).u3(theta2, phi2, lambda2)\n = Rz(phi1).Ry(theta1).Rz(lambda1+phi2).Ry(theta2).Rz(lambda2)\n = Rz(phi1).Rz(phi').Ry(theta').Rz(lambda').Rz(lambda2)\n = u3(theta', phi1 + phi', lambda2 + lambda')\n\n Return theta, phi, lambda.", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/quantum_info/analyzation/average.py#L13-L38", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:average_data-4ac5b69737@held-out", "question": "Compute the mean value of an diagonal observable.\n\n Takes in a diagonal observable in dictionary, list or matrix format and then\n calculates the sum_i value(i) P(i) where value(i) is the value of the\n observable for state i.\n\n Args:\n counts (dict): a dict of outcomes from an experiment\n observable (dict or matrix or list): The observable to be averaged over.\n As an example, ZZ on qubits can be given as:\n * dict: {\"00\": 1, \"11\": 1, \"01\": -1, \"10\": -1}\n * matrix: [[1, 0, 0, 0], [0, -1, 0, 0, ], [0, 0, -1, 0], [0, 0, 0, 1]]\n * matrix diagonal (list): [1, -1, -1, 1]\n\n Returns:\n Double: Average of the observable", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/pulse/ops.py#L67-L77", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:insert-2ba73b4eb8@held-out", "question": "Return a new schedule with the `child` schedule inserted into the `parent` at `start_time`.\n\n Args:\n parent: Schedule to be inserted into\n time: Time to be inserted defined with respect to `parent`\n child: Schedule to insert\n name: Name of the new schedule. Defaults to name of parent", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/extensions/standard/u3.py#L62-L64", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:u3-7b31290231@held-out", "question": "Apply u3 to q.", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/circuit/gate.py#L41-L46", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:Gate.assemble-bfaab2b329@held-out", "question": "Assemble a QasmQobjInstruction", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/quantum_info/operators/predicates.py#L98-L107", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:is_hermitian_matrix-e1e41f39d3@held-out", "question": "Test if an array is a Hermitian matrix", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/transpiler/passes/optimize_swap_before_measure.py#L23-L50", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:OptimizeSwapBeforeMeasure.run-62688ce2c5@held-out", "question": "Return a new circuit that has been optimized.", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/quantum_info/operators/channel/transformations.py#L127-L148", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:_from_operator-b7de1eab39@held-out", "question": "Transform Operator representation to other representation.", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/quantum_info/operators/channel/transformations.py#L174-L177", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:_choi_to_superop-6020d2ac47@held-out", "question": "Transform Choi to SuperOp representation.", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/quantum_info/operators/channel/transformations.py#L244-L254", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:_stinespring_to_choi-566014624a@held-out", "question": "Transform Stinespring representation to Choi representation.", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/quantum_info/operators/channel/transformations.py#L323-L363", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:_bipartite_tensor-7f338484cc@held-out", "question": "Tensor product (A ⊗ B) to bipartite matrices and reravel indicies.\n\n This is used for tensor product of superoperators and Choi matrices.\n\n Args:\n mat1 (matrix_like): a bipartite matrix A\n mat2 (matrix_like): a bipartite matrix B\n shape1 (tuple): bipartite-shape for matrix A (a0, a1, a2, a3)\n shape2 (tuple): bipartite-shape for matrix B (b0, b1, b2, b3)\n\n Returns:\n np.array: a bipartite matrix for reravel(A ⊗ B).\n\n Raises:\n QiskitError: if input matrices are wrong shape.", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/visualization/bloch.py#L295-L301", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:Bloch.clear-58fa290bdf@held-out", "question": "Resets Bloch sphere data sets to empty.", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/visualization/bloch.py#L344-L372", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:Bloch.add_annotation-97238fa62a@held-out", "question": "Add a text or LaTeX annotation to Bloch sphere,\n parametrized by a qubit state or a vector.\n\n Args:\n state_or_vector (array_like):\n Position for the annotation.\n Qobj of a qubit or a vector of 3 elements.\n text (str):\n Annotation text.\n You can use LaTeX, but remember to use raw string\n e.g. r\"$\\\\langle x \\\\rangle$\"\n or escape backslashes\n e.g. \"$\\\\\\\\langle x \\\\\\\\rangle$\".\n **kwargs:\n Options as for mplot3d.axes3d.text, including:\n fontsize, color, horizontalalignment, verticalalignment.\n Raises:\n Exception: If input not array_like or tuple.", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/visualization/bloch.py#L586-L592", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:Bloch.show-a6b54e4e76@held-out", "question": "Display Bloch sphere and corresponding data sets.", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/visualization/bloch.py#L594-L622", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:Bloch.save-86df40a286@held-out", "question": "Saves Bloch sphere to file of type ``format`` in directory ``dirc``.\n Args:\n name (str):\n Name of saved image. Must include path and format as well.\n i.e. '/Users/Paul/Desktop/bloch.png'\n This overrides the 'format' and 'dirc' arguments.\n output (str):\n Format of output image.\n dirc (str):\n Directory for output images. Defaults to current working directory.", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/visualization/text.py#L60-L69", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:DrawElement.bot-756b4018d7@held-out", "question": "Constructs the bottom line of the element", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/visualization/text.py#L367-L379", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:EmptyWire.fillup_layer-264e6f3ba3@held-out", "question": "Given a layer, replace the Nones in it with EmptyWire elements.\n Args:\n layer (list): The layer that contains Nones.\n first_clbit (int): The first wire that is classic.\n\n Returns:\n list: The new layer, with no Nones.", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/visualization/text.py#L416-L429", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:InputWire.fillup_layer-77f895afad@held-out", "question": "Creates a layer with InputWire elements.\n Args:\n names (list): List of names for the wires.\n\n Returns:\n list: The new layer", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/util.py#L28-L56", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:_filter_deprecation_warnings-603bdb3a2a@held-out", "question": "Apply filters to deprecation warnings.\n\n Force the `DeprecationWarning` warnings to be displayed for the qiskit\n module, overriding the system configuration as they are ignored by default\n [1] for end-users. Additionally, silence the `ChangedInMarshmallow3Warning`\n messages.\n\n TODO: on Python 3.7, this might not be needed due to PEP-0565 [2].\n\n [1] https://docs.python.org/3/library/warnings.html#default-warning-filters\n [2] https://www.python.org/dev/peps/pep-0565/", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/quantum_info/operators/channel/ptm.py#L131-L170", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:PTM.compose-5c1511a88f@held-out", "question": "Return the composition channel self∘other.\n\n Args:\n other (QuantumChannel): a quantum channel.\n qargs (list): a list of subsystem positions to compose other on.\n front (bool): If False compose in standard order other(self(input))\n otherwise compose in reverse order self(other(input))\n [default: False]\n\n Returns:\n PTM: The composition channel as a PTM object.\n\n Raises:\n QiskitError: if other cannot be converted to a channel or\n has incompatible dimensions.", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/pulse/pulse_lib/continuous.py#L63-L72", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:triangle-24f59e878e@held-out", "question": "Continuous triangle wave.\n\n Args:\n times: Times to output wave for.\n amp: Pulse amplitude. Wave range is [-amp, amp].\n period: Pulse period, units of dt.\n phase: Pulse phase.", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/pulse/pulse_lib/continuous.py#L75-L84", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:cos-124208c9cd@held-out", "question": "Continuous cosine wave.\n\n Args:\n times: Times to output wave for.\n amp: Pulse amplitude.\n freq: Pulse frequency, units of 1/dt.\n phase: Pulse phase.", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/pulse/pulse_lib/continuous.py#L132-L165", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:gaussian-b040b172b8@held-out", "question": "r\"\"\"Continuous unnormalized gaussian pulse.\n\n Integrated area under curve is $\\Omega_g(amp, sigma) = amp \\times np.sqrt(2\\pi \\sigma^2)$\n\n Args:\n times: Times to output pulse for.\n amp: Pulse amplitude at `center`. If `zeroed_width` is set pulse amplitude at center\n will be $amp-\\Omega_g(center\\pm zeroed_width/2)$ unless `rescale_amp` is set,\n in which case all samples will be rescaled such that the center\n amplitude will be `amp`.\n center: Center (mean) of pulse.\n sigma: Width (standard deviation) of pulse.\n zeroed_width: Subtract baseline to gaussian pulses to make sure\n $\\Omega_g(center \\pm zeroed_width/2)=0$ is satisfied. This is used to avoid\n large discontinuities at the start of a gaussian pulse.\n rescale_amp: If `zeroed_width` is not `None` and `rescale_amp=True` the pulse will\n be rescaled so that $\\Omega_g(center)-\\Omega_g(center\\pm zeroed_width/2)=amp$.\n ret_x: Return centered and standard deviation normalized pulse location.\n $x=(times-center)/sigma.", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/circuit/quantumcircuit.py#L408-L467", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:QuantumCircuit.draw-df7f72253f@held-out", "question": "Draw the quantum circuit\n\n Using the output parameter you can specify the format. The choices are:\n 0. text: ASCII art string\n 1. latex: high-quality images, but heavy external software dependencies\n 2. matplotlib: purely in Python with no external dependencies\n\n Defaults to an overcomplete basis, in order to not alter gates.\n\n Args:\n scale (float): scale of image to draw (shrink if < 1)\n filename (str): file path to save image to\n style (dict or str): dictionary of style or file name of style\n file. You can refer to the\n :ref:`Style Dict Doc <style-dict-doc>` for more information\n on the contents.\n output (str): Select the output method to use for drawing the\n circuit. Valid choices are `text`, `latex`, `latex_source`,\n `mpl`.\n interactive (bool): when set true show the circuit in a new window\n (for `mpl` this depends on the matplotlib backend being used\n supporting this). Note when used with either the `text` or the\n `latex_source` output type this has no effect and will be\n silently ignored.\n line_length (int): sets the length of the lines generated by `text`\n reverse_bits (bool): When set to True reverse the bit order inside\n registers for the output visualization.\n plot_barriers (bool): Enable/disable drawing barriers in the output\n circuit. Defaults to True.\n justify (string): Options are `left`, `right` or `none`, if anything\n else is supplied it defaults to left justified. It refers to where\n gates should be placed in the output circuit if there is an option.\n `none` results in each gate being placed in its own column. Currently\n only supported by text drawer.\n\n Returns:\n PIL.Image or matplotlib.figure or str or TextDrawing:\n * PIL.Image: (output `latex`) an in-memory representation of the\n image of the circuit diagram.\n * matplotlib.figure: (output `mpl`) a matplotlib figure object\n for the circuit diagram.\n * str: (output `latex_source`). The LaTeX source code.\n * TextDrawing: (output `text`). A drawing that can be printed as\n ascii art\n\n Raises:\n VisualizationError: when an invalid output method is selected", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/transpiler/passes/mapping/lookahead_swap.py#L126-L181", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:_search_forward_n_swaps-6a2f2920f2@held-out", "question": "Search for SWAPs which allow for application of largest number of gates.\n\n Arguments:\n layout (Layout): Map from virtual qubit index to physical qubit index.\n gates (list): Gates to be mapped.\n coupling_map (CouplingMap): CouplingMap of the target backend.\n depth (int): Number of SWAP layers to search before choosing a result.\n width (int): Number of SWAPs to consider at each layer.\n Returns:\n dict: Describes solution step found.\n layout (Layout): Virtual to physical qubit map after SWAPs.\n gates_remaining (list): Gates that could not be mapped.\n gates_mapped (list): Gates that were mapped, including added SWAPs.", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/transpiler/coupling.py#L82-L94", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:CouplingMap.add_edge-72daf2d3dd@held-out", "question": "Add directed edge to coupling graph.\n\n src (int): source physical qubit\n dst (int): destination physical qubit", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/tools/events/pubsub.py#L77-L90", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:_Broker.dispatch-24fb14f132@held-out", "question": "Emits an event if there are any subscribers.\n\n Args\n event (String): The event to be emitted\n args: Arguments linked with the event\n kwargs: Named arguments linked with the event", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/extensions/standard/ccx.py#L32-L62", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:ToffoliGate._define-f1f555da4b@held-out", "question": "gate ccx a,b,c\n {\n h c; cx b,c; tdg c; cx a,c;\n t c; cx b,c; tdg c; cx a,c;\n t b; t c; h c; cx a,b;\n t a; tdg b; cx a,b;}", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/transpiler/passes/collect_2q_blocks.py#L30-L189", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:Collect2qBlocks.run-0e7ae8e1ed@held-out", "question": "collect blocks of adjacent gates acting on a pair of \"cx\" qubits.\n\n The blocks contain \"op\" nodes in topological sort order\n such that all gates in a block act on the same pair of\n qubits and are adjacent in the circuit. the blocks are built\n by examining predecessors and successors of \"cx\" gates in\n the circuit. u1, u2, u3, cx, id gates will be included.\n\n Return a list of tuples of \"op\" node labels.", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/pulse/commands/instruction.py#L154-L161", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:Instruction.insert-3ff1d08f12@held-out", "question": "Return a new schedule with `schedule` inserted within `self` at `start_time`.\n\n Args:\n start_time: time to be inserted\n schedule: schedule to be inserted", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/quantum_info/operators/channel/stinespring.py#L371-L434", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:Stinespring._tensor_product-634a97f668@held-out", "question": "Return the tensor product channel.\n\n Args:\n other (QuantumChannel): a quantum channel subclass.\n reverse (bool): If False return self ⊗ other, if True return\n if True return (other ⊗ self) [Default: False]\n Returns:\n Stinespring: the tensor product channel as a Stinespring object.\n\n Raises:\n QiskitError: if other cannot be converted to a channel.", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/quantum_info/operators/pauli.py#L228-L244", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:Pauli.sgn_prod-8518902b44@held-out", "question": "r\"\"\"\n Multiply two Paulis and track the phase.\n\n $P_3 = P_1 \\otimes P_2$: X*Y\n\n Args:\n p1 (Pauli): pauli 1\n p2 (Pauli): pauli 2\n\n Returns:\n Pauli: the multiplied pauli\n complex: the sign of the multiplication, 1, -1, 1j or -1j", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/quantum_info/operators/pauli.py#L344-L370", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:Pauli.update_x-77b1262a8b@held-out", "question": "Update partial or entire x.\n\n Args:\n x (numpy.ndarray or list): to-be-updated x\n indices (numpy.ndarray or list or optional): to-be-updated qubit indices\n\n Returns:\n Pauli: self\n\n Raises:\n QiskitError: when updating whole x, the number of qubits must be the same.", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/providers/basicaer/unitary_simulator.py#L125-L142", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:UnitarySimulatorPy._add_unitary_two-37f672ea5b@held-out", "question": "Apply a two-qubit unitary matrix.\n\n Args:\n gate (matrix_like): a the two-qubit gate matrix\n qubit0 (int): gate qubit-0\n qubit1 (int): gate qubit-1", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/providers/basicaer/unitary_simulator.py#L352-L379", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:UnitarySimulatorPy._validate-c39d134311@held-out", "question": "Semantic validations of the qobj which cannot be done via schemas.\n Some of these may later move to backend schemas.\n 1. No shots\n 2. No measurements in the middle", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/transpiler/passes/mapping/noise_adaptive_layout.py#L79-L125", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:NoiseAdaptiveLayout._initialize_backend_prop-ee2ac79dff@held-out", "question": "Extract readout and CNOT errors and compute swap costs.", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/transpiler/passes/mapping/noise_adaptive_layout.py#L155-L166", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:NoiseAdaptiveLayout._select_next_edge-f32a277996@held-out", "question": "If there is an edge with one endpoint mapped, return it.\n Else return in the first edge", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/transpiler/passes/mapping/noise_adaptive_layout.py#L206-L245", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:NoiseAdaptiveLayout.run-597aad4263@held-out", "question": "Main run method for the noise adaptive layout.", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/circuit/compositegate.py#L76-L79", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:CompositeGate.q_if-9ddda13ec7@held-out", "question": "Add controls to this gate.", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/quantum_info/operators/operator.py#L106-L109", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:Operator.conjugate-d63ed35383@held-out", "question": "Return the conjugate of the operator.", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/quantum_info/operators/operator.py#L111-L114", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:Operator.transpose-f826d22779@held-out", "question": "Return the transpose of the operator.", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/quantum_info/operators/operator.py#L159-L180", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:Operator.power-c6eb2306e4@held-out", "question": "Return the matrix power of the operator.\n\n Args:\n n (int): the power to raise the matrix to.\n\n Returns:\n BaseOperator: the n-times composed operator.\n\n Raises:\n QiskitError: if the input and output dimensions of the operator\n are not equal, or the power is not a positive integer.", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/transpiler/passes/mapping/legacy_swap.py#L206-L355", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:LegacySwap.layer_permutation-2ff1fb164b@held-out", "question": "Find a swap circuit that implements a permutation for this layer.\n\n The goal is to swap qubits such that qubits in the same two-qubit gates\n are adjacent.\n\n Based on Sergey Bravyi's algorithm.\n\n The layer_partition is a list of (qu)bit lists and each qubit is a\n tuple (qreg, index).\n The layout is a dict mapping qubits in the circuit to qubits in the\n coupling graph and represents the current positions of the data.\n The qubit_subset is the subset of qubits in the coupling graph that\n we have chosen to map into.\n The coupling is a CouplingGraph.\n TRIALS is the number of attempts the randomized algorithm makes.\n\n Returns: success_flag, best_circ, best_d, best_layout, trivial_flag\n\n If success_flag is True, then best_circ contains a DAGCircuit with\n the swap circuit, best_d contains the depth of the swap circuit, and\n best_layout contains the new positions of the data qubits after the\n swap circuit has been applied. The trivial_flag is set if the layer\n has no multi-qubit gates.", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/qasm/node/prefix.py#L36-L40", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:Prefix.real-f298d03c39@held-out", "question": "Return the correspond floating point number.", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/result/postprocess.py#L26-L33", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:_separate_bitstring-741389ff8b@held-out", "question": "Separate a bitstring according to the registers defined in the result header.", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/result/postprocess.py#L67-L83", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:_list_to_complex_array-851714b027@held-out", "question": "Convert nested list of shape (..., 2) to complex numpy array with shape (...)\n\n Args:\n complex_list (list): List to convert.\n\n Returns:\n np.ndarray: Complex numpy aray\n\n Raises:\n QiskitError: If inner most array of input nested list is not of length 2.", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/result/postprocess.py#L86-L104", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:format_level_0_memory-d5732f602e@held-out", "question": "Format an experiment result memory object for measurement level 0.\n\n Args:\n memory (list): Memory from experiment with `meas_level==1`. `avg` or\n `single` will be inferred from shape of result memory.\n\n Returns:\n np.ndarray: Measurement level 0 complex numpy array\n\n Raises:\n QiskitError: If the returned numpy array does not have 2 (avg) or 3 (single)\n indicies.", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/result/postprocess.py#L107-L125", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:format_level_1_memory-02247f2f43@held-out", "question": "Format an experiment result memory object for measurement level 1.\n\n Args:\n memory (list): Memory from experiment with `meas_level==1`. `avg` or\n `single` will be inferred from shape of result memory.\n\n Returns:\n np.ndarray: Measurement level 1 complex numpy array\n\n Raises:\n QiskitError: If the returned numpy array does not have 1 (avg) or 2 (single)\n indicies.", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/result/postprocess.py#L128-L142", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:format_level_2_memory-65b475ba6d@held-out", "question": "Format an experiment result memory object for measurement level 2.\n\n Args:\n memory (list): Memory from experiment with `meas_level==2` and `memory==True`.\n header (dict): the experiment header dictionary containing\n useful information for postprocessing.\n\n Returns:\n list[str]: List of bitstrings", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/providers/basicaer/basicaerjob.py#L58-L71", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:BasicAerJob.submit-505203f578@held-out", "question": "Submit the job to the backend for execution.\n\n Raises:\n QobjValidationError: if the JSON serialization of the Qobj passed\n during construction does not validate against the Qobj schema.\n\n JobError: if trying to re-submit the job.", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/providers/basicaer/basicaerjob.py#L98-L122", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:BasicAerJob.status-11646a8e43@held-out", "question": "Gets the status of the job by querying the Python's future\n\n Returns:\n qiskit.providers.JobStatus: The current JobStatus\n\n Raises:\n JobError: If the future is in unexpected state\n concurrent.futures.TimeoutError: if timeout occurred.", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/visualization/state_visualization.py#L713-L749", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:_generate_normals-858b11e9b7@held-out", "question": "Takes a list of polygons and return an array of their normals.\n Normals point towards the viewer for a face with its vertices in\n counterclockwise order, following the right hand rule.\n Uses three points equally spaced around the polygon.\n This normal of course might not make sense for polygons with more than\n three points not lying in a plane, but it's a plausible and fast\n approximation.\n Args:\n polygons (list): list of (M_i, 3) array_like, or (..., M, 3) array_like\n A sequence of polygons to compute normals for, which can have\n varying numbers of vertices. If the polygons all have the same\n number of vertices and array is passed, then the operation will\n be vectorized.\n Returns:\n normals: (..., 3) array_like\n A normal vector estimated for the polygon.", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/visualization/state_visualization.py#L752-L779", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:_shade_colors-4a82a212ad@held-out", "question": "Shade *color* using normal vectors given by *normals*.\n *color* can also be an array of the same length as *normals*.", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/pulse/pulse_lib/discrete.py#L74-L88", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:sawtooth-ec9bf67da6@held-out", "question": "Generates sawtooth wave `SamplePulse`.\n\n Args:\n duration: Duration of pulse. Must be greater than zero.\n amp: Pulse amplitude. Wave range is [-amp, amp].\n period: Pulse period, units of dt. If `None` defaults to single cycle.\n phase: Pulse phase.\n name: Name of pulse.", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/pulse/pulse_lib/discrete.py#L138-L152", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:sin-e4322e5b0e@held-out", "question": "Generates sine wave `SamplePulse`.\n\n Args:\n duration: Duration of pulse. Must be greater than zero.\n amp: Pulse amplitude.\n freq: Pulse frequency, units of 1/dt. If `None` defaults to single cycle.\n phase: Pulse phase.\n name: Name of pulse.", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/dagcircuit/dagcircuit.py#L104-L106", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:DAGCircuit.qubits-288d2602cd@held-out", "question": "Return a list of qubits as (QuantumRegister, index) pairs.", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/dagcircuit/dagcircuit.py#L257-L273", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:DAGCircuit._check_bits-2291daab74@held-out", "question": "Check the values of a list of (qu)bit arguments.\n\n For each element of args, check that amap contains it.\n\n Args:\n args (list): (register,idx) tuples\n amap (dict): a dictionary keyed on (register,idx) tuples\n\n Raises:\n DAGCircuitError: if a qubit is not contained in amap", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/dagcircuit/dagcircuit.py#L495-L509", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:DAGCircuit.extend_back-e3b66da0e3@held-out", "question": "Add `dag` at the end of `self`, using `edge_map`.", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/dagcircuit/dagcircuit.py#L641-L652", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:DAGCircuit.depth-fbb4aef0bf@held-out", "question": "Return the circuit depth.\n Returns:\n int: the circuit depth\n Raises:\n DAGCircuitError: if not a directed acyclic graph", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/dagcircuit/dagcircuit.py#L719-L756", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:DAGCircuit._full_pred_succ_maps-599f8bd5d5@held-out", "question": "Map all wires of the input circuit.\n\n Map all wires of the input circuit to predecessor and\n successor nodes in self, keyed on wires in self.\n\n Args:\n pred_map (dict): comes from _make_pred_succ_maps\n succ_map (dict): comes from _make_pred_succ_maps\n input_circuit (DAGCircuit): the input circuit\n wire_map (dict): the map from wires of input_circuit to wires of self\n\n Returns:\n tuple: full_pred_map, full_succ_map (dict, dict)\n\n Raises:\n DAGCircuitError: if more than one predecessor for output nodes", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/dagcircuit/dagcircuit.py#L1136-L1151", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:DAGCircuit.quantum_successors-056f7022ee@held-out", "question": "Returns list of the successors of a node that are\n connected by a quantum edge as DAGNodes.", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/dagcircuit/dagcircuit.py#L1177-L1190", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:DAGCircuit.remove_ancestors_of-f9855ac726@held-out", "question": "Remove all of the ancestor operation nodes of node.", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/tools/qcvv/tomography.py#L266-L389", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:tomography_set-41072ab510@held-out", "question": "Generate a dictionary of tomography experiment configurations.\n\n This returns a data structure that is used by other tomography functions\n to generate state and process tomography circuits, and extract tomography\n data from results after execution on a backend.\n\n Quantum State Tomography:\n Be default it will return a set for performing Quantum State\n Tomography where individual qubits are measured in the Pauli basis.\n A custom measurement basis may also be used by defining a user\n `tomography_basis` and passing this in for the `meas_basis` argument.\n\n Quantum Process Tomography:\n A quantum process tomography set is created by specifying a preparation\n basis along with a measurement basis. The preparation basis may be a\n user defined `tomography_basis`, or one of the two built in basis 'SIC'\n or 'Pauli'.\n - SIC: Is a minimal symmetric informationally complete preparation\n basis for 4 states for each qubit (4 ^ number of qubits total\n preparation states). These correspond to the |0> state and the 3\n other vertices of a tetrahedron on the Bloch-sphere.\n - Pauli: Is a tomographically overcomplete preparation basis of the six\n eigenstates of the 3 Pauli operators (6 ^ number of qubits\n total preparation states).\n\n Args:\n meas_qubits (list): The qubits being measured.\n meas_basis (tomography_basis or str): The qubit measurement basis.\n The default value is 'Pauli'.\n prep_qubits (list or None): The qubits being prepared. If None then\n meas_qubits will be used for process tomography experiments.\n prep_basis (tomography_basis or None): The optional qubit preparation\n basis. If no basis is specified state tomography will be performed\n instead of process tomography. A built in basis may be specified by\n 'SIC' or 'Pauli' (SIC basis recommended for > 2 qubits).\n\n Returns:\n dict: A dict of tomography configurations that can be parsed by\n `create_tomography_circuits` and `tomography_data` functions\n for implementing quantum tomography experiments. This output contains\n fields \"qubits\", \"meas_basis\", \"circuits\". It may also optionally\n contain a field \"prep_basis\" for process tomography experiments.\n ```\n {\n 'qubits': qubits (list[ints]),\n 'meas_basis': meas_basis (tomography_basis),\n 'circuit_labels': (list[string]),\n 'circuits': (list[dict]) # prep and meas configurations\n # optionally for process tomography experiments:\n 'prep_basis': prep_basis (tomography_basis)\n }\n ```\n Raises:\n QiskitError: if the Qubits argument is not a list.", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/tools/qcvv/tomography.py#L600-L641", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:tomography_data-95973a9697@held-out", "question": "Return a results dict for a state or process tomography experiment.\n\n Args:\n results (Result): Results from execution of a process tomography\n circuits on a backend.\n name (string): The name of the circuit being reconstructed.\n tomoset (tomography_set): the dict of tomography configurations.\n\n Returns:\n list: A list of dicts for the outcome of each process tomography\n measurement circuit.", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/tools/qcvv/tomography.py#L644-L684", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:marginal_counts-d091a86dad@held-out", "question": "Compute the marginal counts for a subset of measured qubits.\n\n Args:\n counts (dict): the counts returned from a backend ({str: int}).\n meas_qubits (list[int]): the qubits to return the marginal\n counts distribution for.\n\n Returns:\n dict: A counts dict for the meas_qubits.abs\n Example: if `counts = {'00': 10, '01': 5}`\n `marginal_counts(counts, [0])` returns `{'0': 15, '1': 0}`.\n `marginal_counts(counts, [0])` returns `{'0': 10, '1': 5}`.", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/tools/qcvv/tomography.py#L131-L143", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:TomographyBasis.meas_gate-e7385e64c6@held-out", "question": "Add measurement gates to a circuit.\n\n Args:\n circuit (QuantumCircuit): circuit to add measurement to.\n qreg (tuple(QuantumRegister,int)): quantum register being measured.\n op (str): the basis label for the measurement.", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/tools/jupyter/backend_monitor.py#L497-L573", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:plot_job_history-48d4d823f0@held-out", "question": "Plots the job history of the user from the given list of jobs.\n\n Args:\n jobs (list): A list of jobs with type IBMQjob.\n interval (str): Interval over which to examine.\n\n Returns:\n fig: A Matplotlib figure instance.", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/transpiler/passes/remove_reset_in_zero_state.py#L20-L27", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:RemoveResetInZeroState.run-71444b41fa@held-out", "question": "Return a new circuit that has been optimized.", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/extensions/standard/cu3.py#L56-L58", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:cu3-c21cf57730@held-out", "question": "Apply cu3 from ctl to tgt with angle theta, phi, lam.", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/compiler/transpiler.py#L153-L178", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:_transpile_circuit-f056d9e768@held-out", "question": "Select a PassManager and run a single circuit through it.\n\n Args:\n circuit_config_tuple (tuple):\n circuit (QuantumCircuit): circuit to transpile\n transpile_config (TranspileConfig): configuration dictating how to transpile\n\n Returns:\n QuantumCircuit: transpiled circuit", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/pulse/channels/qubit.py#L65-L70", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:Qubit.control-7b89adea2e@held-out", "question": "Return the primary control channel of this qubit.", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/compiler/assembler.py#L29-L150", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:assemble_circuits-d3f39ef70f@held-out", "question": "Assembles a list of circuits into a qobj which can be run on the backend.\n\n Args:\n circuits (list[QuantumCircuits]): circuit(s) to assemble\n qobj_id (int): identifier for the generated qobj\n qobj_header (QobjHeader): header to pass to the results\n run_config (RunConfig): configuration of the runtime environment\n\n Returns:\n QasmQobj: the Qobj to be run on the backends", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/qasm/qasmlexer.py#L172-L178", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:QasmLexer.t_ID-c3daa410b3@held-out", "question": "r'[a-z][a-zA-Z0-9_]*", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/qobj/converters/pulse_instruction.py#L196-L210", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:PulseQobjConverter.convert_drive-a1f217cef7@held-out", "question": "Return converted `PulseInstruction`.\n\n Args:\n shift(int): Offset time.\n instruction (PulseInstruction): drive instruction.\n Returns:\n dict: Dictionary of required parameters.", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/providers/providerutils.py#L15-L62", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:filter_backends-e71252b68a@held-out", "question": "Return the backends matching the specified filtering.\n\n Filter the `backends` list by their `configuration` or `status`\n attributes, or from a boolean callable. The criteria for filtering can\n be specified via `**kwargs` or as a callable via `filters`, and the\n backends must fulfill all specified conditions.\n\n Args:\n backends (list[BaseBackend]): list of backends.\n filters (callable): filtering conditions as a callable.\n **kwargs (dict): dict of criteria.\n\n Returns:\n list[BaseBackend]: a list of backend instances matching the\n conditions.", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/converters/dag_to_circuit.py#L16-L55", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:dag_to_circuit-ab8d89aea3@held-out", "question": "Build a ``QuantumCircuit`` object from a ``DAGCircuit``.\n\n Args:\n dag (DAGCircuit): the input dag.\n\n Return:\n QuantumCircuit: the circuit representing the input dag.", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/quantum_info/analyzation/make_observable.py#L13-L37", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:make_dict_observable-4eac854e08@held-out", "question": "Convert an observable in matrix form to dictionary form.\n\n Takes in a diagonal observable as a matrix and converts it to a dictionary\n form. Can also handle a list sorted of the diagonal elements.\n\n Args:\n matrix_observable (list): The observable to be converted to dictionary\n form. Can be a matrix or just an ordered list of observed values\n\n Returns:\n Dict: A dictionary with all observable states as keys, and corresponding\n values being the observed value for that state", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/qasm/qasmparser.py#L57-L73", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:QasmParser.update_symtab-462124af07@held-out", "question": "Update a node in the symbol table.\n\n Everything in the symtab must be a node with these attributes:\n name - the string name of the object\n type - the string type of the object\n line - the source line where the type was first found\n file - the source file where the type was first found", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/qasm/qasmparser.py#L189-L205", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:QasmParser.id_tuple_list-6b1849a8d1@held-out", "question": "Return a list of (name, index) tuples for this id node.", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/qasm/qasmparser.py#L291-L304", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:QasmParser.p_statement-4fab90d324@held-out", "question": "statement : decl\n | quantum_op ';'\n | format ';'\n | ignore\n | quantum_op error\n | format error", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/qasm/qasmparser.py#L482-L492", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:QasmParser.p_creg_decl-ad7f725d32@held-out", "question": "creg_decl : CREG indexed_id", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/qasm/qasmparser.py#L637-L644", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:QasmParser.p_unitary_op_3-58a723a56b@held-out", "question": "unitary_op : id '(' ')' primary_list", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/qasm/qasmparser.py#L764-L770", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:QasmParser.p_gate_op_5-a289c36920@held-out", "question": "gate_op : BARRIER id_list ';'", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/qasm/qasmparser.py#L797-L803", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:QasmParser.p_opaque_1-ae4151c4b2@held-out", "question": "opaque : OPAQUE id gate_scope '(' ')' bit_list", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/qasm/qasmparser.py#L866-L891", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:QasmParser.p_if-65cb3a84cb@held-out", "question": "if : IF '(' id MATCHES NNINTEGER ')' quantum_op\n if : IF '(' id error\n if : IF '(' id MATCHES error\n if : IF '(' id MATCHES NNINTEGER error\n if : IF error", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/quantum_info/states/states.py#L22-L40", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:basis_state-0506e1ae60@held-out", "question": "Return a basis state ndarray.\n\n Args:\n str_state (string): a string representing the state.\n num (int): the number of qubits\n Returns:\n ndarray: state(2**num) a quantum state with basis basis state.\n Raises:\n QiskitError: if the dimensions is wrong", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/tools/jupyter/backend_overview.py#L170-L224", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:update_backend_info-7e367f199c@held-out", "question": "Updates the monitor info\n Called from another thread.", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/quantum_info/operators/channel/choi.py#L187-L202", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:Choi.power-bcf7357345@held-out", "question": "The matrix power of the channel.\n\n Args:\n n (int): compute the matrix power of the superoperator matrix.\n\n Returns:\n Choi: the matrix power of the SuperOp converted to a Choi channel.\n\n Raises:\n QiskitError: if the input and output dimensions of the\n QuantumChannel are not equal, or the power is not an integer.", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/validation/jsonschema/schema_validation.py#L100-L105", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:_load_schemas_and_validators-37bec2e209@held-out", "question": "Load all default schemas into `_SCHEMAS`.", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/examples/python/rippleadd.py#L40-L44", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:majority-167fa2fe04@held-out", "question": "Majority gate.", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/quantum_info/random/utils.py#L82-L104", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:random_density_matrix-3295b7448b@held-out", "question": "Generate a random density matrix rho.\n\n Args:\n length (int): the length of the density matrix.\n rank (int or None): the rank of the density matrix. The default\n value is full-rank.\n method (string): the method to use.\n 'Hilbert-Schmidt': sample rho from the Hilbert-Schmidt metric.\n 'Bures': sample rho from the Bures metric.\n seed (int): Optional. To set a random seed.\n Returns:\n ndarray: rho (length, length) a density matrix.\n Raises:\n QiskitError: if the method is not valid.", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/quantum_info/random/utils.py#L107-L125", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:__ginibre_matrix-8871f50e40@held-out", "question": "Return a normally distributed complex random matrix.\n\n Args:\n nrow (int): number of rows in output matrix.\n ncol (int): number of columns in output matrix.\n seed (int): Optional. To set a random seed.\n Returns:\n ndarray: A complex rectangular matrix where each real and imaginary\n entry is sampled from the normal distribution.", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/quantum_info/operators/channel/superop.py#L226-L245", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:SuperOp.add-8ffcd9dcf0@held-out", "question": "Return the QuantumChannel self + other.\n\n Args:\n other (QuantumChannel): a quantum channel.\n\n Returns:\n SuperOp: the linear addition self + other as a SuperOp object.\n\n Raises:\n QiskitError: if other cannot be converted to a channel or\n has incompatible dimensions.", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/visualization/dag_visualization.py#L18-L83", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:dag_drawer-5677c88b77@held-out", "question": "Plot the directed acyclic graph (dag) to represent operation dependencies\n in a quantum circuit.\n\n Note this function leverages\n `pydot <https://github.com/erocarrera/pydot>`_ (via\n `nxpd <https://github.com/chebee7i/nxpd`_) to generate the graph, which\n means that having `Graphviz <https://www.graphviz.org/>`_ installed on your\n system is required for this to work.\n\n Args:\n dag (DAGCircuit): The dag to draw.\n scale (float): scaling factor\n filename (str): file path to save image to (format inferred from name)\n style (str): 'plain': B&W graph\n 'color' (default): color input/output/op nodes\n\n Returns:\n Ipython.display.Image: if in Jupyter notebook and not saving to file,\n otherwise None.\n\n Raises:\n VisualizationError: when style is not recognized.\n ImportError: when nxpd or pydot not installed.", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/quantum_info/operators/base_operator.py#L105-L131", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:BaseOperator._reshape-e58ccc6c75@held-out", "question": "Reshape input and output dimensions of operator.\n\n Arg:\n input_dims (tuple): new subsystem input dimensions.\n output_dims (tuple): new subsystem output dimensions.\n\n Returns:\n Operator: returns self with reshaped input and output dimensions.\n\n Raises:\n QiskitError: if combined size of all subsystem input dimension or\n subsystem output dimensions is not constant.", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/quantum_info/operators/base_operator.py#L133-L137", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:BaseOperator.input_dims-3a1d4523f1@held-out", "question": "Return tuple of input dimension for specified subsystems.", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/validation/fields/polymorphic.py#L61-L68", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:BasePolyField._deserialize-15b4e07bbc@held-out", "question": "Override ``_deserialize`` for customizing the exception raised.", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/quantum_info/operators/channel/quantum_channel.py#L90-L96", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Qiskit-qiskit-terra:QuantumChannel._is_cp_helper-b141686a01@held-out", "question": "Test if a channel is completely-positive (CP)", "scope": {"holder": "Qiskit-qiskit-terra", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/graphql-python/graphene-sqlalchemy/blob/e362e3fc4993d7e95873044bb4d00185b1d3dd8b/graphene_sqlalchemy/utils.py#L103-L110", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:graphql-python-graphene-sqlalchemy:sort_argument_for_model-057df87939@held-out", "question": "Returns a Graphene argument for the sort field that accepts a list of sorting directions for a model.\n If `has_default` is True (the default) it will sort the result by the primary key(s)", "scope": {"holder": "graphql-python-graphene-sqlalchemy", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/scrapinghub/dateparser/blob/11a761c99d3ee522a3c63756b70c106a579e8b5c/dateparser/languages/locale.py#L53-L77", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:scrapinghub-dateparser:Locale.is_applicable-c3b7ba00d3@held-out", "question": "Check if the locale is applicable to translate date string.\n\n :param date_string:\n A string representing date and/or time in a recognizably valid format.\n :type date_string: str|unicode\n\n :param strip_timezone:\n If True, timezone is stripped from date string.\n :type strip_timezone: bool\n\n :return: boolean value representing if the locale is applicable for the date string or not.", "scope": {"holder": "scrapinghub-dateparser", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/yandex/yandex-tank/blob/d71d63b6ab5de8b8a5ea2b728b6ab9ac0b1ba71b/yandextank/common/util.py#L344-L367", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:yandex-yandex-tank:log_stdout_stderr-4eaab4d020@held-out", "question": "This function polls stdout and stderr streams and writes their contents\n to log", "scope": {"holder": "yandex-yandex-tank", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/yandex/yandex-tank/blob/d71d63b6ab5de8b8a5ea2b728b6ab9ac0b1ba71b/yandextank/stepper/main.py#L136-L141", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:yandex-yandex-tank:StepperWrapper.get_option-537431861e@held-out", "question": "get_option wrapper", "scope": {"holder": "yandex-yandex-tank", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/yandex/yandex-tank/blob/d71d63b6ab5de8b8a5ea2b728b6ab9ac0b1ba71b/yandextank/stepper/main.py#L246-L279", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:yandex-yandex-tank:StepperWrapper.__get_stpd_filename-cec15968d7@held-out", "question": "Choose the name for stepped data file", "scope": {"holder": "yandex-yandex-tank", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/yandex/yandex-tank/blob/d71d63b6ab5de8b8a5ea2b728b6ab9ac0b1ba71b/yandextank/stepper/load_plan.py#L83-L89", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:yandex-yandex-tank:Line.rps_at-ec58fbdf03@held-out", "question": "Return rps for second t", "scope": {"holder": "yandex-yandex-tank", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/yandex/yandex-tank/blob/d71d63b6ab5de8b8a5ea2b728b6ab9ac0b1ba71b/yandextank/plugins/InfluxUploader/decoder.py#L82-L134", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:yandex-yandex-tank:Decoder.__make_points_for_label-0300b115dc@held-out", "question": "x\n Make a set of points for `this` label\n\n overall_quantiles, overall_meta, net_codes, proto_codes, histograms", "scope": {"holder": "yandex-yandex-tank", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/yandex/yandex-tank/blob/d71d63b6ab5de8b8a5ea2b728b6ab9ac0b1ba71b/yandextank/plugins/InfluxUploader/decoder.py#L166-L191", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:yandex-yandex-tank:Decoder.__make_points-395fccb537@held-out", "question": "Parameters\n ----------\n measurement : string\n measurement type (e.g. monitoring, overall_meta, net_codes, proto_codes, overall_quantiles)\n additional_tags : dict\n custom additional tags for this points\n ts : integer\n timestamp\n fields : dict\n influxdb columns\n\n Returns\n -------\n dict\n points for InfluxDB client", "scope": {"holder": "yandex-yandex-tank", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/yandex/yandex-tank/blob/d71d63b6ab5de8b8a5ea2b728b6ab9ac0b1ba71b/yandextank/api/apiworker.py#L22-L58", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:yandex-yandex-tank:ApiWorker.init_logging-bbed2a9ea4@held-out", "question": "Set up logging", "scope": {"holder": "yandex-yandex-tank", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/yandex/yandex-tank/blob/d71d63b6ab5de8b8a5ea2b728b6ab9ac0b1ba71b/yandextank/api/apiworker.py#L135-L152", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:yandex-yandex-tank:ApiWorker.get_default_configs-ac547fa798@held-out", "question": "returns default configs list, from /etc, home dir and package_data", "scope": {"holder": "yandex-yandex-tank", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/yandex/yandex-tank/blob/d71d63b6ab5de8b8a5ea2b728b6ab9ac0b1ba71b/yandextank/plugins/NeUploader/plugin.py#L81-L93", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:yandex-yandex-tank:get_uploader-7ffac1c5ae@held-out", "question": ":type column_mapping: dict\n :type data_session: DataSession", "scope": {"holder": "yandex-yandex-tank", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/yandex/yandex-tank/blob/d71d63b6ab5de8b8a5ea2b728b6ab9ac0b1ba71b/yandextank/stepper/util.py#L67-L73", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:yandex-yandex-tank:proper_round-1ddf83a1b0@held-out", "question": "rounds float to closest int\n :rtype: int\n :param n: float", "scope": {"holder": "yandex-yandex-tank", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/yandex/yandex-tank/blob/d71d63b6ab5de8b8a5ea2b728b6ab9ac0b1ba71b/yandextank/plugins/Telegraf/client.py#L198-L309", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:yandex-yandex-tank:SSHClient.install-de6255f206@held-out", "question": "Create folder and copy agent and metrics scripts to remote host", "scope": {"holder": "yandex-yandex-tank", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/yandex/yandex-tank/blob/d71d63b6ab5de8b8a5ea2b728b6ab9ac0b1ba71b/yandextank/plugins/JMeter/plugin.py#L199-L263", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:yandex-yandex-tank:Plugin.__add_jmeter_components-6dc22e0b90@held-out", "question": "Genius idea by Alexey Lavrenyuk", "scope": {"holder": "yandex-yandex-tank", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/yandex/yandex-tank/blob/d71d63b6ab5de8b8a5ea2b728b6ab9ac0b1ba71b/yandextank/plugins/Telegraf/config.py#L30-L42", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:yandex-yandex-tank:ConfigManager.getconfig-d5a5eb74f6@held-out", "question": "Prepare config data.", "scope": {"holder": "yandex-yandex-tank", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/yandex/yandex-tank/blob/d71d63b6ab5de8b8a5ea2b728b6ab9ac0b1ba71b/yandextank/plugins/Console/plugin.py#L119-L124", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:yandex-yandex-tank:Plugin.add_info_widget-486c1d443a@held-out", "question": "add right panel widget", "scope": {"holder": "yandex-yandex-tank", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/yandex/yandex-tank/blob/d71d63b6ab5de8b8a5ea2b728b6ab9ac0b1ba71b/yandextank/core/tankcore.py#L637-L650", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:yandex-yandex-tank:ConfigManager.get_options-4a88bb4633@held-out", "question": "Get options list with requested prefix", "scope": {"holder": "yandex-yandex-tank", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/alpacahq/alpaca-trade-api-python/blob/9c9dea3b4a37c909f88391b202e86ff356a8b4d7/alpaca_trade_api/entity.py#L102-L115", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:alpacahq-alpaca-trade-api-python:BarSet.df-b50a26e553@held-out", "question": "## Experimental", "scope": {"holder": "alpacahq-alpaca-trade-api-python", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/alpacahq/alpaca-trade-api-python/blob/9c9dea3b4a37c909f88391b202e86ff356a8b4d7/alpaca_trade_api/rest.py#L234-L263", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:alpacahq-alpaca-trade-api-python:REST.get_barset-c66c6e4b30@held-out", "question": "Get BarSet(dict[str]->list[Bar])\n The parameter symbols can be either a comma-split string\n or a list of string. Each symbol becomes the key of\n the returned value.", "scope": {"holder": "alpacahq-alpaca-trade-api-python", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/dagster-io/dagster/blob/4119f8c773089de64831b1dfb9e168e353d401dc/python_modules/dagster/dagster/core/definitions/decorators.py#L135-L170", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:dagster-io-dagster:lambda_solid-6a404e99b7@held-out", "question": "(decorator) Create a simple solid.\n\n This shortcut allows the creation of simple solids that do not require\n configuration and whose implementations do not require a context.\n\n Lambda solids take inputs and produce a single output. The body of the function\n should return a single value.\n\n Args:\n name (str): Name of solid.\n inputs (list[InputDefinition]): List of inputs.\n output (OutputDefinition): The output of the solid. Defaults to ``OutputDefinition()``.\n description (str): Solid description.\n\n Examples:\n\n .. code-block:: python\n\n @lambda_solid\n def hello_world():\n return 'hello'\n\n @lambda_solid(inputs=[InputDefinition(name='foo')])\n def hello_world(foo):\n return foo", "scope": {"holder": "dagster-io-dagster", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/dagster-io/dagster/blob/4119f8c773089de64831b1dfb9e168e353d401dc/python_modules/dagster/dagster/core/events/logging.py#L134-L146", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:dagster-io-dagster:construct_event_logger-5a85bb2815@held-out", "question": "Callback receives a stream of event_records", "scope": {"holder": "dagster-io-dagster", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/dagster-io/dagster/blob/4119f8c773089de64831b1dfb9e168e353d401dc/python_modules/dagster/dagster/core/definitions/repository.py#L56-L100", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:dagster-io-dagster:RepositoryDefinition.get_pipeline-c13994bd9c@held-out", "question": "Get a pipeline by name. Only constructs that pipeline and caches it.\n\n Args:\n name (str): Name of the pipeline to retriever\n\n Returns:\n PipelineDefinition: Instance of PipelineDefinition with that name.", "scope": {"holder": "dagster-io-dagster", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/dagster-io/dagster/blob/4119f8c773089de64831b1dfb9e168e353d401dc/python_modules/dagster/dagster/core/definitions/pipeline.py#L185-L201", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:dagster-io-dagster:PipelineDefinition.solid_named-d7e9962cf4@held-out", "question": "Return the solid named \"name\". Throws if it does not exist.\n\n Args:\n name (str): Name of solid\n\n Returns:\n SolidDefinition: SolidDefinition with correct name.", "scope": {"holder": "dagster-io-dagster", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/dagster-io/dagster/blob/4119f8c773089de64831b1dfb9e168e353d401dc/bin/publish.py#L50-L63", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:dagster-io-dagster:construct_publish_comands-719d9a6e09@held-out", "question": "Get the shell commands we'll use to actually build and publish a package to PyPI.", "scope": {"holder": "dagster-io-dagster", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/dagster-io/dagster/blob/4119f8c773089de64831b1dfb9e168e353d401dc/examples/airline-demo/airline_demo/utils.py#L10-L17", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:dagster-io-dagster:mkdir_p-4418aa9e12@held-out", "question": "The missing mkdir -p functionality in os.", "scope": {"holder": "dagster-io-dagster", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/dagster-io/dagster/blob/4119f8c773089de64831b1dfb9e168e353d401dc/python_modules/dagster/dagster/core/execution.py#L196-L207", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:dagster-io-dagster:SolidExecutionResult.success-74b2bce60d@held-out", "question": "Whether the solid execution was successful", "scope": {"holder": "dagster-io-dagster", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/dagster-io/dagster/blob/4119f8c773089de64831b1dfb9e168e353d401dc/python_modules/dagster/dagster/core/types/field_utils.py#L284-L308", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:dagster-io-dagster:PermissiveDict-b11a051d20@held-out", "question": "A permissive dict will permit the user to partially specify the permitted fields. Any fields\n that are specified and passed in will be type checked. Other fields will be allowed, but\n will be ignored by the type checker.", "scope": {"holder": "dagster-io-dagster", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/dagster-io/dagster/blob/4119f8c773089de64831b1dfb9e168e353d401dc/python_modules/dagster/dagster/core/types/decorator.py#L42-L76", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:dagster-io-dagster:dagster_type-825f5fc0c1@held-out", "question": "Decorator version of as_dagster_type. See documentation for :py:func:`as_dagster_type` .", "scope": {"holder": "dagster-io-dagster", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/ekzhu/datasketch/blob/b3e4129987890a2beb04f2c0b6dc618ae35f2e14/datasketch/lshensemble_partition.py#L35-L54", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:ekzhu-datasketch:_compute_nfps_uniform-4c0a0cf667@held-out", "question": "Computes the matrix of expected false positives for all possible\n sub-intervals of the complete domain of set sizes, assuming uniform\n distribution of set_sizes within each sub-intervals.\n\n Args:\n cum_counts: the complete cummulative distribution of set sizes.\n sizes: the complete domain of set sizes.\n\n Return (np.array): the 2-D array of expected number of false positives\n for every pair of [l, u] interval, where l is axis-0 and u is\n axis-1.", "scope": {"holder": "ekzhu-datasketch", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/ekzhu/datasketch/blob/b3e4129987890a2beb04f2c0b6dc618ae35f2e14/datasketch/lshensemble_partition.py#L75-L93", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:ekzhu-datasketch:_compute_nfps_real-8d18005a9e@held-out", "question": "Computes the matrix of expected false positives for all possible\n sub-intervals of the complete domain of set sizes.\n\n Args:\n counts: the complete distribution of set sizes.\n sizes: the complete domain of set sizes.\n\n Return (np.array): the 2-D array of expected number of false positives\n for every pair of [l, u] interval, where l is axis-0 and u is\n axis-1.", "scope": {"holder": "ekzhu-datasketch", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/ekzhu/datasketch/blob/b3e4129987890a2beb04f2c0b6dc618ae35f2e14/datasketch/lean_minhash.py#L148-L184", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:ekzhu-datasketch:LeanMinHash.deserialize-3fb89e2129@held-out", "question": "Deserialize a lean MinHash from a buffer.\n\n Args:\n buf (buffer): `buf` must implement the `buffer`_ interface.\n One such example is the built-in `bytearray`_ class.\n byteorder (str. optional): This is byte order of the serialized data. Use one\n of the `byte order characters\n <https://docs.python.org/3/library/struct.html#byte-order-size-and-alignment>`_:\n ``@``, ``=``, ``<``, ``>``, and ``!``.\n Default is ``@`` -- the native order.\n\n Return:\n datasketch.LeanMinHash: The deserialized lean MinHash\n\n Example:\n To deserialize a lean MinHash from a buffer.\n\n .. code-block:: python\n\n lean_minhash = LeanMinHash.deserialize(buf)", "scope": {"holder": "ekzhu-datasketch", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/ekzhu/datasketch/blob/b3e4129987890a2beb04f2c0b6dc618ae35f2e14/datasketch/lshensemble.py#L34-L53", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:ekzhu-datasketch:_optimal_param-90207b8be7@held-out", "question": "Compute the optimal parameters that minimizes the weighted sum\n of probabilities of false positive and false negative.\n xq is the ratio of x/q.", "scope": {"holder": "ekzhu-datasketch", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/ekzhu/datasketch/blob/b3e4129987890a2beb04f2c0b6dc618ae35f2e14/datasketch/lshensemble.py#L179-L198", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:ekzhu-datasketch:MinHashLSHEnsemble.query-4394ddf7ab@held-out", "question": "Giving the MinHash and size of the query set, retrieve\n keys that references sets with containment with respect to\n the query set greater than the threshold.\n\n Args:\n minhash (datasketch.MinHash): The MinHash of the query set.\n size (int): The size (number of unique items) of the query set.\n\n Returns:\n `iterator` of keys.", "scope": {"holder": "ekzhu-datasketch", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/ekzhu/datasketch/blob/b3e4129987890a2beb04f2c0b6dc618ae35f2e14/datasketch/lshensemble.py#L211-L217", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:ekzhu-datasketch:MinHashLSHEnsemble.is_empty-12d8c807cc@held-out", "question": "Returns:\n bool: Check if the index is empty.", "scope": {"holder": "ekzhu-datasketch", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/ekzhu/datasketch/blob/b3e4129987890a2beb04f2c0b6dc618ae35f2e14/datasketch/lsh.py#L213-L229", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:ekzhu-datasketch:MinHashLSH.remove-6e8863d3c6@held-out", "question": "Remove the key from the index.\n\n Args:\n key (hashable): The unique identifier of a set.", "scope": {"holder": "ekzhu-datasketch", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/ekzhu/datasketch/blob/b3e4129987890a2beb04f2c0b6dc618ae35f2e14/datasketch/hyperloglog.py#L89-L124", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:ekzhu-datasketch:HyperLogLog.update-5d985e115b@held-out", "question": "Update the HyperLogLog with a new data value in bytes.\n The value will be hashed using the hash function specified by\n the `hashfunc` argument in the constructor.\n\n Args:\n b: The value to be hashed using the hash function specified.\n\n Example:\n To update with a new string value (using the default SHA1 hash\n function, which requires bytes as input):\n\n .. code-block:: python\n\n hll = HyperLogLog()\n hll.update(\"new value\".encode('utf-8'))\n\n We can also use a different hash function, for example, `pyfarmhash`:\n\n .. code-block:: python\n\n import farmhash\n def _hash_32(b):\n return farmhash.hash32(b)\n hll = HyperLogLog(hashfunc=_hash_32)\n hll.update(\"new value\")", "scope": {"holder": "ekzhu-datasketch", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/ekzhu/datasketch/blob/b3e4129987890a2beb04f2c0b6dc618ae35f2e14/datasketch/hyperloglog.py#L126-L143", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:ekzhu-datasketch:HyperLogLog.count-0c3d975e4f@held-out", "question": "Estimate the cardinality of the data values seen so far.\n\n Returns:\n int: The estimated cardinality.", "scope": {"holder": "ekzhu-datasketch", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/ekzhu/datasketch/blob/b3e4129987890a2beb04f2c0b6dc618ae35f2e14/datasketch/storage.py#L191-L196", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:ekzhu-datasketch:DictListStorage.itemcounts-d77f4dbba8@held-out", "question": "Returns a dict where the keys are the keys of the container.\n The values are the *lengths* of the value sequences stored\n in this container.", "scope": {"holder": "ekzhu-datasketch", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Tivix/django-rest-auth/blob/624ad01afbc86fa15b4e652406f3bdcd01f36e00/rest_auth/social_serializers.py#L24-L38", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Tivix-django-rest-auth:TwitterLoginSerializer.get_social_login-e52a0a8931@held-out", "question": ":param adapter: allauth.socialaccount Adapter subclass.\n Usually OAuthAdapter or Auth2Adapter\n :param app: `allauth.socialaccount.SocialApp` instance\n :param token: `allauth.socialaccount.SocialToken` instance\n :param response: Provider's response for OAuth1. Not used in the\n :returns: A populated instance of the\n `allauth.socialaccount.SocialLoginView` instance", "scope": {"holder": "Tivix-django-rest-auth", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/google/gin-config/blob/17a170e0a6711005d1c78e67cf493dc44674d44f/gin/config_parser.py#L236-L250", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:google-gin-config:ConfigParser.parse_value-84a93efd77@held-out", "question": "Parse a single literal value.\n\n Returns:\n The parsed value.", "scope": {"holder": "google-gin-config", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/google/gin-config/blob/17a170e0a6711005d1c78e67cf493dc44674d44f/gin/config.py#L155-L161", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:google-gin-config:_find_class_construction_fn-650685eba0@held-out", "question": "Find the first __init__ or __new__ method in the given class's MRO.", "scope": {"holder": "google-gin-config", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/google/gin-config/blob/17a170e0a6711005d1c78e67cf493dc44674d44f/gin/config.py#L635-L663", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:google-gin-config:_might_have_parameter-2f584be869@held-out", "question": "Returns True if `arg_name` might be a valid parameter for `fn_or_cls`.\n\n Specifically, this means that `fn_or_cls` either has a parameter named\n `arg_name`, or has a `**kwargs` parameter.\n\n Args:\n fn_or_cls: The function or class to check.\n arg_name: The name fo the parameter.\n\n Returns:\n Whether `arg_name` might be a valid argument of `fn`.", "scope": {"holder": "google-gin-config", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/google/gin-config/blob/17a170e0a6711005d1c78e67cf493dc44674d44f/gin/config.py#L704-L743", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:google-gin-config:_get_default_configurable_parameter_values-8ce7e293d5@held-out", "question": "Retrieve all default values for configurable parameters of a function.\n\n Any parameters included in the supplied blacklist, or not included in the\n supplied whitelist, are excluded.\n\n Args:\n fn: The function whose parameter values should be retrieved.\n whitelist: The whitelist (or `None`) associated with the function.\n blacklist: The blacklist (or `None`) associated with the function.\n\n Returns:\n A dictionary mapping configurable parameter names to their default values.", "scope": {"holder": "google-gin-config", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/google/gin-config/blob/17a170e0a6711005d1c78e67cf493dc44674d44f/gin/config.py#L1534-L1566", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:google-gin-config:finalize-7f2e200c6f@held-out", "question": "A function that should be called after parsing all Gin config files.\n\n Calling this function allows registered \"finalize hooks\" to inspect (and\n potentially modify) the Gin config, to provide additional functionality. Hooks\n should not modify the configuration object they receive directly; instead,\n they should return a dictionary mapping Gin binding keys to (new or updated)\n values. This way, all hooks see the config as originally parsed.\n\n Raises:\n RuntimeError: If the config is already locked.\n ValueError: If two or more hooks attempt to modify or introduce bindings for\n the same key. Since it is difficult to control the order in which hooks\n are registered, allowing this could yield unpredictable behavior.", "scope": {"holder": "google-gin-config", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/google/gin-config/blob/17a170e0a6711005d1c78e67cf493dc44674d44f/gin/selector_map.py#L185-L214", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:google-gin-config:SelectorMap.minimal_selector-37c93c3a78@held-out", "question": "Returns the minimal selector that uniquely matches `complete_selector`.\n\n Args:\n complete_selector: A complete selector stored in the map.\n\n Returns:\n A partial selector that unambiguously matches `complete_selector`.\n\n Raises:\n KeyError: If `complete_selector` is not in the map.", "scope": {"holder": "google-gin-config", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/mozilla-iot/webthing-python/blob/65d467c89ed79d0bbc42b8b3c8f9e5a320edd237/webthing/server.py#L343-L361", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:mozilla-iot-webthing-python:PropertyHandler.get-fb6f7b2663@held-out", "question": "Handle a GET request.\n\n thing_id -- ID of the thing this request is for\n property_name -- the name of the property from the URL path", "scope": {"holder": "mozilla-iot-webthing-python", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/mozilla-iot/webthing-python/blob/65d467c89ed79d0bbc42b8b3c8f9e5a320edd237/webthing/server.py#L363-L397", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:mozilla-iot-webthing-python:PropertyHandler.put-dfc2ecfc04@held-out", "question": "Handle a PUT request.\n\n thing_id -- ID of the thing this request is for\n property_name -- the name of the property from the URL path", "scope": {"holder": "mozilla-iot-webthing-python", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/mozilla-iot/webthing-python/blob/65d467c89ed79d0bbc42b8b3c8f9e5a320edd237/webthing/server.py#L767-L782", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:mozilla-iot-webthing-python:WebThingServer.start-a228a3db51@held-out", "question": "Start listening for incoming connections.", "scope": {"holder": "mozilla-iot-webthing-python", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/mozilla-iot/webthing-python/blob/65d467c89ed79d0bbc42b8b3c8f9e5a320edd237/webthing/utils.py#L35-L59", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:mozilla-iot-webthing-python:get_addresses-1e7a07481b@held-out", "question": "Get all IP addresses.\n\n Returns list of addresses.", "scope": {"holder": "mozilla-iot-webthing-python", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/SectorLabs/django-postgres-extra/blob/eef2ed5504d225858d4e4f5d77a838082ca6053e/psqlextra/manager/manager.py#L91-L118", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:SectorLabs-django-postgres-extra:PostgresQuerySet.update-e76481ff52@held-out", "question": "Updates all rows that match the filter.", "scope": {"holder": "SectorLabs-django-postgres-extra", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/SectorLabs/django-postgres-extra/blob/eef2ed5504d225858d4e4f5d77a838082ca6053e/psqlextra/manager/manager.py#L197-L236", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:SectorLabs-django-postgres-extra:PostgresQuerySet.insert_and_get-b811cc21a7@held-out", "question": "Creates a new record in the database and then gets\n the entire row.\n\n This allows specifying custom conflict behavior using .on_conflict().\n If no special behavior was specified, this uses the normal Django create(..)\n\n Arguments:\n fields:\n The fields of the row to create.\n\n Returns:\n The model instance representing the row that was created.", "scope": {"holder": "SectorLabs-django-postgres-extra", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/SectorLabs/django-postgres-extra/blob/eef2ed5504d225858d4e4f5d77a838082ca6053e/psqlextra/manager/manager.py#L527-L546", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:SectorLabs-django-postgres-extra:PostgresManager.upsert_and_get-01c6d2393d@held-out", "question": "Creates a new record or updates the existing one\n with the specified data and then gets the row.\n\n Arguments:\n conflict_target:\n Fields to pass into the ON CONFLICT clause.\n\n fields:\n Fields to insert/update.\n\n index_predicate:\n The index predicate to satisfy an arbiter partial index.\n\n Returns:\n The model instance representing the row\n that was created/updated.", "scope": {"holder": "SectorLabs-django-postgres-extra", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/SectorLabs/django-postgres-extra/blob/eef2ed5504d225858d4e4f5d77a838082ca6053e/psqlextra/manager/manager.py#L566-L574", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:SectorLabs-django-postgres-extra:PostgresManager._on_model_save-eaea5f72d6@held-out", "question": "When a model gets created or updated.", "scope": {"holder": "SectorLabs-django-postgres-extra", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/SectorLabs/django-postgres-extra/blob/eef2ed5504d225858d4e4f5d77a838082ca6053e/psqlextra/expressions.py#L178-L182", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:SectorLabs-django-postgres-extra:DateTimeEpochColumn.as_sql-5c7893f822@held-out", "question": "Compiles this expression into SQL.", "scope": {"holder": "SectorLabs-django-postgres-extra", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/SectorLabs/django-postgres-extra/blob/eef2ed5504d225858d4e4f5d77a838082ca6053e/psqlextra/query.py#L53-L88", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:SectorLabs-django-postgres-extra:PostgresQuery.add_join_conditions-f2d5e48eb8@held-out", "question": "Adds an extra condition to an existing JOIN.\n\n This allows you to for example do:\n\n INNER JOIN othertable ON (mytable.id = othertable.other_id AND [extra conditions])\n\n This does not work if nothing else in your query doesn't already generate the\n initial join in the first place.", "scope": {"holder": "SectorLabs-django-postgres-extra", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/SectorLabs/django-postgres-extra/blob/eef2ed5504d225858d4e4f5d77a838082ca6053e/psqlextra/indexes/conditional_unique_index.py#L26-L39", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:SectorLabs-django-postgres-extra:ConditionalUniqueIndex.create_sql-400bc1640c@held-out", "question": "Creates the actual SQL used when applying the migration.", "scope": {"holder": "SectorLabs-django-postgres-extra", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/SectorLabs/django-postgres-extra/blob/eef2ed5504d225858d4e4f5d77a838082ca6053e/psqlextra/backend/base.py#L81-L87", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:SectorLabs-django-postgres-extra:SchemaEditor.create_model-cccfc1d56d@held-out", "question": "Ran when a new model is created.", "scope": {"holder": "SectorLabs-django-postgres-extra", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/SectorLabs/django-postgres-extra/blob/eef2ed5504d225858d4e4f5d77a838082ca6053e/psqlextra/backend/hstore_unique.py#L117-L131", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:SectorLabs-django-postgres-extra:HStoreUniqueSchemaEditorMixin._create_hstore_unique-08572ab31e@held-out", "question": "Creates a UNIQUE constraint for the specified hstore keys.", "scope": {"holder": "SectorLabs-django-postgres-extra", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/SectorLabs/django-postgres-extra/blob/eef2ed5504d225858d4e4f5d77a838082ca6053e/psqlextra/backend/hstore_unique.py#L188-L204", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:SectorLabs-django-postgres-extra:HStoreUniqueSchemaEditorMixin._iterate_uniqueness_keys-7b5247b953@held-out", "question": "Iterates over the keys marked as \"unique\"\n in the specified field.\n\n Arguments:\n field:\n The field of which key's to\n iterate over.", "scope": {"holder": "SectorLabs-django-postgres-extra", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/python/performance/blob/2a9524c0a5714e85106671bc61d750e800fe17db/performance/benchmarks/bm_nqueens.py#L9-L30", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:python-performance:permutations-198d131e0d@held-out", "question": "permutations(range(3), 2) --> (0,1) (0,2) (1,0) (1,2) (2,0) (2,1)", "scope": {"holder": "python-performance", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/python/performance/blob/2a9524c0a5714e85106671bc61d750e800fe17db/performance/benchmarks/bm_go.py#L372-L385", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:python-performance:UCTNode.update_path-2f8f04cfcb@held-out", "question": "update win/loss count along path", "scope": {"holder": "python-performance", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/python/performance/blob/2a9524c0a5714e85106671bc61d750e800fe17db/performance/benchmarks/bm_regex_effbot.py#L60-L94", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:python-performance:gen_string_table-e01bb53b79@held-out", "question": "Generates the list of strings that will be used in the benchmarks.\n\n All strings have repeated prefixes and suffices, and n specifies the\n number of repetitions.", "scope": {"holder": "python-performance", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/chaoss/grimoirelab-perceval/blob/41c908605e88b7ebc3a536c643fa0f212eaf9e0e/perceval/backends/core/mattermost.py#L358-L372", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:chaoss-grimoirelab-perceval:MattermostClient._fetch-ca0f4c0b46@held-out", "question": "Fetch a resource.\n\n :param entrypoint: entrypoint to access\n :param params: dict with the HTTP parameters needed to access the\n given entry point", "scope": {"holder": "chaoss-grimoirelab-perceval", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/chaoss/grimoirelab-perceval/blob/41c908605e88b7ebc3a536c643fa0f212eaf9e0e/perceval/backends/core/bugzillarest.py#L368-L381", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:chaoss-grimoirelab-perceval:BugzillaRESTClient.history-1d2f88ea9d@held-out", "question": "Get the history of the given bugs.\n\n :param bug_ids: list of bug identifiers", "scope": {"holder": "chaoss-grimoirelab-perceval", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/chaoss/grimoirelab-perceval/blob/41c908605e88b7ebc3a536c643fa0f212eaf9e0e/perceval/backends/core/gitlab.py#L507-L519", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:chaoss-grimoirelab-perceval:GitLabClient.note_emojis-54ca16c306@held-out", "question": "Get emojis of a note", "scope": {"holder": "chaoss-grimoirelab-perceval", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/chaoss/grimoirelab-perceval/blob/41c908605e88b7ebc3a536c643fa0f212eaf9e0e/perceval/backends/core/gitlab.py#L588-L601", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:chaoss-grimoirelab-perceval:GitLabClient.sanitize_for_archive-5a69415143@held-out", "question": "Sanitize payload of a HTTP request by removing the token information\n before storing/retrieving archived items\n\n :param: url: HTTP url request\n :param: headers: HTTP headers request\n :param: payload: HTTP payload request\n\n :returns url, headers and the sanitized payload", "scope": {"holder": "chaoss-grimoirelab-perceval", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/chaoss/grimoirelab-perceval/blob/41c908605e88b7ebc3a536c643fa0f212eaf9e0e/perceval/backends/core/slack.py#L177-L193", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:chaoss-grimoirelab-perceval:Slack.metadata_id-4e1338e4e6@held-out", "question": "Extracts the identifier from a Slack item.\n\n This identifier will be the mix of two fields because Slack\n messages does not have any unique identifier. In this case,\n 'ts' and 'user' values (or 'bot_id' when the message is sent by a bot)\n are combined because there have been cases where two messages were sent\n by different users at the same time.", "scope": {"holder": "chaoss-grimoirelab-perceval", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/chaoss/grimoirelab-perceval/blob/41c908605e88b7ebc3a536c643fa0f212eaf9e0e/perceval/backends/core/bugzilla.py#L99-L132", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:chaoss-grimoirelab-perceval:Bugzilla.fetch_items-cb8935ff8e@held-out", "question": "Fetch the bugs\n\n :param category: the category of items to fetch\n :param kwargs: backend arguments\n\n :returns: a generator of items", "scope": {"holder": "chaoss-grimoirelab-perceval", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/chaoss/grimoirelab-perceval/blob/41c908605e88b7ebc3a536c643fa0f212eaf9e0e/perceval/backends/core/meetup.py#L124-L168", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:chaoss-grimoirelab-perceval:Meetup.fetch_items-769ab5a27e@held-out", "question": "Fetch the events\n\n :param category: the category of items to fetch\n :param kwargs: backend arguments\n\n :returns: a generator of items", "scope": {"holder": "chaoss-grimoirelab-perceval", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/chaoss/grimoirelab-perceval/blob/41c908605e88b7ebc3a536c643fa0f212eaf9e0e/perceval/backends/core/meetup.py#L361-L393", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:chaoss-grimoirelab-perceval:MeetupClient.events-966303fef3@held-out", "question": "Fetch the events pages of a given group.", "scope": {"holder": "chaoss-grimoirelab-perceval", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/chaoss/grimoirelab-perceval/blob/41c908605e88b7ebc3a536c643fa0f212eaf9e0e/perceval/backends/core/askbot.py#L87-L112", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:chaoss-grimoirelab-perceval:Askbot.fetch_items-a627d511ca@held-out", "question": "Fetch the questions\n\n :param category: the category of items to fetch\n :param kwargs: backend arguments\n\n :returns: a generator of items", "scope": {"holder": "chaoss-grimoirelab-perceval", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/chaoss/grimoirelab-perceval/blob/41c908605e88b7ebc3a536c643fa0f212eaf9e0e/perceval/backends/core/gerrit.py#L327-L355", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:chaoss-grimoirelab-perceval:GerritClient.version-a9ac341269@held-out", "question": "Return the Gerrit server version.", "scope": {"holder": "chaoss-grimoirelab-perceval", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/chaoss/grimoirelab-perceval/blob/41c908605e88b7ebc3a536c643fa0f212eaf9e0e/perceval/backends/core/gerrit.py#L368-L388", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:chaoss-grimoirelab-perceval:GerritClient.next_retrieve_group_item-7a3402f114@held-out", "question": "Return the item to start from in next reviews group.", "scope": {"holder": "chaoss-grimoirelab-perceval", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/chaoss/grimoirelab-perceval/blob/41c908605e88b7ebc3a536c643fa0f212eaf9e0e/perceval/backends/core/gerrit.py#L495-L522", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:chaoss-grimoirelab-perceval:GerritCommand.setup_cmd_parser-14385b231a@held-out", "question": "Returns the Gerrit argument parser.", "scope": {"holder": "chaoss-grimoirelab-perceval", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/chaoss/grimoirelab-perceval/blob/41c908605e88b7ebc3a536c643fa0f212eaf9e0e/perceval/backends/core/launchpad.py#L172-L176", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:chaoss-grimoirelab-perceval:Launchpad._init_client-bd8624e5ae@held-out", "question": "Init client", "scope": {"holder": "chaoss-grimoirelab-perceval", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/chaoss/grimoirelab-perceval/blob/41c908605e88b7ebc3a536c643fa0f212eaf9e0e/perceval/backends/core/launchpad.py#L307-L331", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:chaoss-grimoirelab-perceval:LaunchpadClient.user-d1eb50c46b@held-out", "question": "Get the user data by URL", "scope": {"holder": "chaoss-grimoirelab-perceval", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/chaoss/grimoirelab-perceval/blob/41c908605e88b7ebc3a536c643fa0f212eaf9e0e/perceval/backends/core/groupsio.py#L229-L240", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:chaoss-grimoirelab-perceval:GroupsioClient.__find_group_id-2184e2410b@held-out", "question": "Find the id of a group given its name by iterating on the list of subscriptions", "scope": {"holder": "chaoss-grimoirelab-perceval", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/chaoss/grimoirelab-perceval/blob/41c908605e88b7ebc3a536c643fa0f212eaf9e0e/perceval/backends/core/groupsio.py#L242-L251", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:chaoss-grimoirelab-perceval:GroupsioClient.__fetch-2aa6230f6b@held-out", "question": "Fetch requests from groupsio API", "scope": {"holder": "chaoss-grimoirelab-perceval", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/chaoss/grimoirelab-perceval/blob/41c908605e88b7ebc3a536c643fa0f212eaf9e0e/perceval/backend.py#L404-L412", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:chaoss-grimoirelab-perceval:BackendCommandArgumentParser._set_output_arguments-e2e095ac88@held-out", "question": "Activate output arguments parsing", "scope": {"holder": "chaoss-grimoirelab-perceval", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/chaoss/grimoirelab-perceval/blob/41c908605e88b7ebc3a536c643fa0f212eaf9e0e/perceval/backends/core/git.py#L134-L164", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:chaoss-grimoirelab-perceval:Git.fetch_items-2bdb940f6e@held-out", "question": "Fetch the commits\n\n :param category: the category of items to fetch\n :param kwargs: backend arguments\n\n :returns: a generator of items", "scope": {"holder": "chaoss-grimoirelab-perceval", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/chaoss/grimoirelab-perceval/blob/41c908605e88b7ebc3a536c643fa0f212eaf9e0e/perceval/backends/core/git.py#L345-L377", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:chaoss-grimoirelab-perceval:GitCommand.setup_cmd_parser-2c4586fe9b@held-out", "question": "Returns the Git argument parser.", "scope": {"holder": "chaoss-grimoirelab-perceval", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/chaoss/grimoirelab-perceval/blob/41c908605e88b7ebc3a536c643fa0f212eaf9e0e/perceval/backends/core/git.py#L804-L829", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:chaoss-grimoirelab-perceval:GitRepository.clone-6b27baedba@held-out", "question": "Clone a Git repository.\n\n Make a bare copy of the repository stored in `uri` into `dirpath`.\n The repository would be either local or remote.\n\n :param uri: URI of the repository\n :param dirtpath: directory where the repository will be cloned\n\n :returns: a `GitRepository` class having cloned the repository\n\n :raises RepositoryError: when an error occurs cloning the given\n repository", "scope": {"holder": "chaoss-grimoirelab-perceval", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/chaoss/grimoirelab-perceval/blob/41c908605e88b7ebc3a536c643fa0f212eaf9e0e/perceval/backends/core/git.py#L831-L859", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:chaoss-grimoirelab-perceval:GitRepository.count_objects-607465d6e0@held-out", "question": "Count the objects of a repository.\n\n The method returns the total number of objects (packed and unpacked)\n available on the repository.\n\n :raises RepositoryError: when an error occurs counting the objects\n of a repository", "scope": {"holder": "chaoss-grimoirelab-perceval", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/chaoss/grimoirelab-perceval/blob/41c908605e88b7ebc3a536c643fa0f212eaf9e0e/perceval/backends/core/git.py#L984-L1041", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:chaoss-grimoirelab-perceval:GitRepository.log-49376072f4@held-out", "question": "Read the commit log from the repository.\n\n The method returns the Git log of the repository using the\n following options:\n\n git log --raw --numstat --pretty=fuller --decorate=full\n --all --reverse --topo-order --parents -M -C -c\n --remotes=origin\n\n When `from_date` is given, it gets the commits equal or older\n than that date. This date is given in a datetime object.\n\n The list of branches is a list of strings, with the names of the\n branches to fetch. If the list of branches is empty, no commit\n is fetched. If the list of branches is None, all commits\n for all branches will be fetched.\n\n :param from_date: fetch commits newer than a specific\n date (inclusive)\n :param branches: names of branches to fetch from (default: None)\n :param encoding: encode the log using this format\n\n :returns: a generator where each item is a line from the log\n\n :raises EmptyRepositoryError: when the repository is empty and\n the action cannot be performed\n :raises RepositoryError: when an error occurs fetching the log", "scope": {"holder": "chaoss-grimoirelab-perceval", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/chaoss/grimoirelab-perceval/blob/41c908605e88b7ebc3a536c643fa0f212eaf9e0e/perceval/backends/core/git.py#L1083-L1117", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:chaoss-grimoirelab-perceval:GitRepository._fetch_pack-a992f4f034@held-out", "question": "Fetch changes and store them in a pack.", "scope": {"holder": "chaoss-grimoirelab-perceval", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/chaoss/grimoirelab-perceval/blob/41c908605e88b7ebc3a536c643fa0f212eaf9e0e/perceval/backends/core/github.py#L227-L233", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:chaoss-grimoirelab-perceval:GitHub._init_client-44d3d849f9@held-out", "question": "Init client", "scope": {"holder": "chaoss-grimoirelab-perceval", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/chaoss/grimoirelab-perceval/blob/41c908605e88b7ebc3a536c643fa0f212eaf9e0e/perceval/backends/core/github.py#L235-L265", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:chaoss-grimoirelab-perceval:GitHub.__fetch_issues-70ce616360@held-out", "question": "Fetch the issues", "scope": {"holder": "chaoss-grimoirelab-perceval", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/chaoss/grimoirelab-perceval/blob/41c908605e88b7ebc3a536c643fa0f212eaf9e0e/perceval/backends/core/github.py#L267-L294", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:chaoss-grimoirelab-perceval:GitHub.__fetch_pull_requests-77256ab260@held-out", "question": "Fetch the pull requests", "scope": {"holder": "chaoss-grimoirelab-perceval", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/chaoss/grimoirelab-perceval/blob/41c908605e88b7ebc3a536c643fa0f212eaf9e0e/perceval/backends/core/github.py#L429-L445", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:chaoss-grimoirelab-perceval:GitHub.__get_pull_review_comment_reactions-fef58a7491@held-out", "question": "Get pull review comment reactions", "scope": {"holder": "chaoss-grimoirelab-perceval", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/chaoss/grimoirelab-perceval/blob/41c908605e88b7ebc3a536c643fa0f212eaf9e0e/perceval/backends/core/github.py#L643-L651", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:chaoss-grimoirelab-perceval:GitHubClient.pull_commits-6fedcdb212@held-out", "question": "Get pull request commits", "scope": {"holder": "chaoss-grimoirelab-perceval", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/chaoss/grimoirelab-perceval/blob/41c908605e88b7ebc3a536c643fa0f212eaf9e0e/perceval/backends/core/github.py#L786-L800", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:chaoss-grimoirelab-perceval:GitHubClient._get_tokens_rate_limits-dd4a639168@held-out", "question": "Return array of all tokens remaining API points", "scope": {"holder": "chaoss-grimoirelab-perceval", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/chaoss/grimoirelab-perceval/blob/41c908605e88b7ebc3a536c643fa0f212eaf9e0e/perceval/archive.py#L414-L438", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:chaoss-grimoirelab-perceval:ArchiveManager.search-fddbfdae5b@held-out", "question": "Search archives.\n\n Get the archives which store data based on the given parameters.\n These parameters define which the origin was (`origin`), how data\n was fetched (`backend_name`) and data type ('category').\n Only those archives created on or after `archived_after` will be\n returned.\n\n The method returns a list with the file paths to those archives.\n The list is sorted by the date of creation of each archive.\n\n :param origin: data origin\n :param backend_name: backed used to fetch data\n :param category: type of the items fetched by the backend\n :param archived_after: get archives created on or after this date\n\n :returns: a list with archive names which match the search criteria", "scope": {"holder": "chaoss-grimoirelab-perceval", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/chaoss/grimoirelab-perceval/blob/41c908605e88b7ebc3a536c643fa0f212eaf9e0e/perceval/archive.py#L440-L457", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:chaoss-grimoirelab-perceval:ArchiveManager._search_archives-beab4a7e49@held-out", "question": "Search archives using filters.", "scope": {"holder": "chaoss-grimoirelab-perceval", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/chaoss/grimoirelab-perceval/blob/41c908605e88b7ebc3a536c643fa0f212eaf9e0e/perceval/archive.py#L459-L465", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:chaoss-grimoirelab-perceval:ArchiveManager._search_files-cd684ac1d6@held-out", "question": "Retrieve the file paths stored under the base path.", "scope": {"holder": "chaoss-grimoirelab-perceval", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/chaoss/grimoirelab-perceval/blob/41c908605e88b7ebc3a536c643fa0f212eaf9e0e/perceval/utils.py#L50-L76", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:chaoss-grimoirelab-perceval:check_compressed_file_type-13b22ba321@held-out", "question": "Check if filename is a compressed file supported by the tool.\n\n This function uses magic numbers (first four bytes) to determine\n the type of the file. Supported types are 'gz' and 'bz2'. When\n the filetype is not supported, the function returns `None`.\n\n :param filepath: path to the file\n\n :returns: 'gz' or 'bz2'; `None` if the type is not supported", "scope": {"holder": "chaoss-grimoirelab-perceval", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/chaoss/grimoirelab-perceval/blob/41c908605e88b7ebc3a536c643fa0f212eaf9e0e/perceval/utils.py#L192-L221", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:chaoss-grimoirelab-perceval:remove_invalid_xml_chars-adc6065b56@held-out", "question": "Remove control and invalid characters from an xml stream.\n\n Looks for invalid characters and subtitutes them with whitespaces.\n This solution is based on these two posts: Olemis Lang's reponse\n on StackOverflow (http://stackoverflow.com/questions/1707890) and\n lawlesst's on GitHub Gist (https://gist.github.com/lawlesst/4110923),\n that is based on the previous answer.\n\n :param xml: XML stream\n\n :returns: a purged XML stream", "scope": {"holder": "chaoss-grimoirelab-perceval", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/chaoss/grimoirelab-perceval/blob/41c908605e88b7ebc3a536c643fa0f212eaf9e0e/perceval/backends/core/dockerhub.py#L76-L90", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:chaoss-grimoirelab-perceval:DockerHub.fetch-d4465f1fe6@held-out", "question": "Fetch data from a Docker Hub repository.\n\n The method retrieves, from a repository stored in Docker Hub,\n its data which includes number of pulls, stars, description,\n among other data.\n\n :param category: the category of items to fetch\n\n :returns: a generator of data", "scope": {"holder": "chaoss-grimoirelab-perceval", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/chaoss/grimoirelab-perceval/blob/41c908605e88b7ebc3a536c643fa0f212eaf9e0e/perceval/backends/core/jira.py#L346-L352", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:chaoss-grimoirelab-perceval:JiraClient.get_fields-6e8258c0fb@held-out", "question": "Retrieve all the fields available.", "scope": {"holder": "chaoss-grimoirelab-perceval", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/chaoss/grimoirelab-perceval/blob/41c908605e88b7ebc3a536c643fa0f212eaf9e0e/perceval/backends/core/jenkins.py#L74-L88", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:chaoss-grimoirelab-perceval:Jenkins.fetch-242ef1d365@held-out", "question": "Fetch the builds from the url.\n\n The method retrieves, from a Jenkins url, the\n builds updated since the given date.\n\n :param category: the category of items to fetch\n\n :returns: a generator of builds", "scope": {"holder": "chaoss-grimoirelab-perceval", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/chaoss/grimoirelab-perceval/blob/41c908605e88b7ebc3a536c643fa0f212eaf9e0e/perceval/backends/core/stackexchange.py#L305-L324", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:chaoss-grimoirelab-perceval:StackExchangeCommand.setup_cmd_parser-766d057251@held-out", "question": "Returns the StackExchange argument parser.", "scope": {"holder": "chaoss-grimoirelab-perceval", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/chaoss/grimoirelab-perceval/blob/41c908605e88b7ebc3a536c643fa0f212eaf9e0e/perceval/backends/core/mediawiki.py#L178-L181", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:chaoss-grimoirelab-perceval:MediaWiki._init_client-a178fcacf6@held-out", "question": "Init client", "scope": {"holder": "chaoss-grimoirelab-perceval", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/chaoss/grimoirelab-perceval/blob/41c908605e88b7ebc3a536c643fa0f212eaf9e0e/perceval/backends/core/mediawiki.py#L400-L410", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:chaoss-grimoirelab-perceval:MediaWikiClient.call-c9f2d771a0@held-out", "question": "Run an API command.\n :param cgi: cgi command to run on the server\n :param params: dict with the HTTP parameters needed to run\n the given command", "scope": {"holder": "chaoss-grimoirelab-perceval", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/chaoss/grimoirelab-perceval/blob/41c908605e88b7ebc3a536c643fa0f212eaf9e0e/perceval/backends/core/mediawiki.py#L448-L460", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:chaoss-grimoirelab-perceval:MediaWikiClient.get_pages-0ced66d245@held-out", "question": "Retrieve all pages from a namespace starting from apcontinue.", "scope": {"holder": "chaoss-grimoirelab-perceval", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/chaoss/grimoirelab-perceval/blob/41c908605e88b7ebc3a536c643fa0f212eaf9e0e/perceval/backends/core/telegram.py#L232-L235", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:chaoss-grimoirelab-perceval:Telegram._init_client-50703f9c18@held-out", "question": "Init client", "scope": {"holder": "chaoss-grimoirelab-perceval", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/chaoss/grimoirelab-perceval/blob/41c908605e88b7ebc3a536c643fa0f212eaf9e0e/perceval/backends/core/nntp.py#L218-L221", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:chaoss-grimoirelab-perceval:NNTP._init_client-bd832f86db@held-out", "question": "Init client", "scope": {"holder": "chaoss-grimoirelab-perceval", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/chaoss/grimoirelab-perceval/blob/41c908605e88b7ebc3a536c643fa0f212eaf9e0e/perceval/backends/core/nntp.py#L339-L353", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:chaoss-grimoirelab-perceval:NNTTPClient._fetch_from_archive-8e34ab3195@held-out", "question": "Fetch data from the archive\n\n :param method: the name of the command to execute\n :param args: the arguments required by the command", "scope": {"holder": "chaoss-grimoirelab-perceval", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/chaoss/grimoirelab-perceval/blob/41c908605e88b7ebc3a536c643fa0f212eaf9e0e/perceval/client.py#L225-L248", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:chaoss-grimoirelab-perceval:RateLimitHandler.setup_rate_limit_handler-268cba379f@held-out", "question": "Setup the rate limit handler.\n\n :param sleep_for_rate: sleep until rate limit is reset\n :param min_rate_to_sleep: minimun rate needed to make the fecthing process sleep\n :param rate_limit_header: header from where extract the rate limit data\n :param rate_limit_reset_header: header from where extract the rate limit reset data", "scope": {"holder": "chaoss-grimoirelab-perceval", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/chaoss/grimoirelab-perceval/blob/41c908605e88b7ebc3a536c643fa0f212eaf9e0e/perceval/backends/core/supybot.py#L96-L127", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:chaoss-grimoirelab-perceval:Supybot.fetch_items-02975f176a@held-out", "question": "Fetch the messages\n\n :param category: the category of items to fetch\n :param kwargs: backend arguments\n\n :returns: a generator of items", "scope": {"holder": "chaoss-grimoirelab-perceval", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/chaoss/grimoirelab-perceval/blob/41c908605e88b7ebc3a536c643fa0f212eaf9e0e/perceval/backends/core/phabricator.py#L484-L516", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:chaoss-grimoirelab-perceval:ConduitClient.tasks-7eb56858c8@held-out", "question": "Retrieve tasks.\n\n :param from_date: retrieve tasks that where updated from that date;\n dates are converted epoch time.", "scope": {"holder": "chaoss-grimoirelab-perceval", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/chaoss/grimoirelab-perceval/blob/41c908605e88b7ebc3a536c643fa0f212eaf9e0e/perceval/backends/core/confluence.py#L98-L131", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:chaoss-grimoirelab-perceval:Confluence.fetch_items-7ef33d6bf2@held-out", "question": "Fetch the contents\n\n :param category: the category of items to fetch\n :param kwargs: backend arguments\n\n :returns: a generator of items", "scope": {"holder": "chaoss-grimoirelab-perceval", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/chaoss/grimoirelab-perceval/blob/41c908605e88b7ebc3a536c643fa0f212eaf9e0e/perceval/backends/core/confluence.py#L221-L224", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:chaoss-grimoirelab-perceval:Confluence._init_client-b5602fe18a@held-out", "question": "Init client", "scope": {"holder": "chaoss-grimoirelab-perceval", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/geopython/OWSLib/blob/96d47842401a129f1e86fa9f66dccef5a5a6872c/owslib/feature/common.py#L42-L56", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:geopython-OWSLib:WFSCapabilitiesReader.read-3e3ac61fd5@held-out", "question": "Get and parse a WFS capabilities document, returning an\n instance of WFSCapabilitiesInfoset\n\n Parameters\n ----------\n url : string\n The URL to the WFS capabilities document.\n timeout : number\n A timeout value (in seconds) for the request.", "scope": {"holder": "geopython-OWSLib", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/geopython/OWSLib/blob/96d47842401a129f1e86fa9f66dccef5a5a6872c/owslib/feature/schema.py#L66-L121", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:geopython-OWSLib:_construct_schema-0d4cd4ea17@held-out", "question": "Consruct fiona schema based on given elements\n\n :param list Element: list of elements\n :param dict nsmap: namespace map\n\n :return dict: schema", "scope": {"holder": "geopython-OWSLib", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/celiao/tmdbsimple/blob/ff17893110c99771d6398a62c35d36dd9735f4b9/tmdbsimple/movies.py#L342-L358", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:celiao-tmdbsimple:Movies.now_playing-bcbc40b141@held-out", "question": "Get the list of movies playing in theatres. This list refreshes\n every day. The maximum number of items this list will include is 100.\n\n Args:\n page: (optional) Minimum value of 1. Expected value is an integer.\n language: (optional) ISO 639-1 code.\n\n Returns:\n A dict representation of the JSON returned from the API.", "scope": {"holder": "celiao-tmdbsimple", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/celiao/tmdbsimple/blob/ff17893110c99771d6398a62c35d36dd9735f4b9/tmdbsimple/movies.py#L378-L395", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:celiao-tmdbsimple:Movies.top_rated-de039b8918@held-out", "question": "Get the list of top rated movies. By default, this list will only\n include movies that have 10 or more votes. This list refreshes every\n day.\n\n Args:\n page: (optional) Minimum value of 1. Expected value is an integer.\n language: (optional) ISO 639-1 code.\n\n Returns:\n A dict representation of the JSON returned from the API.", "scope": {"holder": "celiao-tmdbsimple", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/celiao/tmdbsimple/blob/ff17893110c99771d6398a62c35d36dd9735f4b9/tmdbsimple/people.py#L90-L109", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:celiao-tmdbsimple:People.combined_credits-0763730007@held-out", "question": "Get the combined (movie and TV) credits for a specific person id.\n\n To get the expanded details for each TV record, call the /credit method \n with the provided credit_id. This will provide details about which \n episode and/or season the credit is for.\n\n Args:\n language: (optional) ISO 639-1 code.\n append_to_response: (optional) Comma separated, any person method.\n\n Returns:\n A dict respresentation of the JSON returned from the API.", "scope": {"holder": "celiao-tmdbsimple", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/celiao/tmdbsimple/blob/ff17893110c99771d6398a62c35d36dd9735f4b9/tmdbsimple/account.py#L298-L316", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:celiao-tmdbsimple:Authentication.session_new-f8a8997281@held-out", "question": "Generate a session id for user based authentication.\n\n A session id is required in order to use any of the write methods.\n\n Args:\n request_token: The token you generated for the user to approve.\n The token needs to be approved before being\n used here.\n\n Returns:\n A dict respresentation of the JSON returned from the API.", "scope": {"holder": "celiao-tmdbsimple", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/celiao/tmdbsimple/blob/ff17893110c99771d6398a62c35d36dd9735f4b9/tmdbsimple/account.py#L318-L329", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:celiao-tmdbsimple:Authentication.guest_session_new-aaf7788e9b@held-out", "question": "Generate a guest session id.\n\n Returns:\n A dict respresentation of the JSON returned from the API.", "scope": {"holder": "celiao-tmdbsimple", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/celiao/tmdbsimple/blob/ff17893110c99771d6398a62c35d36dd9735f4b9/tmdbsimple/tv.py#L373-L384", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:celiao-tmdbsimple:TV_Seasons.credits-e2c0889e4b@held-out", "question": "Get the cast & crew credits for a TV season by season number.\n\n Returns:\n A dict respresentation of the JSON returned from the API.", "scope": {"holder": "celiao-tmdbsimple", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/celiao/tmdbsimple/blob/ff17893110c99771d6398a62c35d36dd9735f4b9/tmdbsimple/tv.py#L481-L492", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:celiao-tmdbsimple:TV_Episodes.credits-4ccb81adc2@held-out", "question": "Get the TV episode credits by combination of season and episode number.\n\n Returns:\n A dict respresentation of the JSON returned from the API.", "scope": {"holder": "celiao-tmdbsimple", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/mordred-descriptor/mordred/blob/2848b088fd7b6735590242b5e22573babc724f10/mordred/surface_area/_sasa.py#L87-L92", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:mordred-descriptor-mordred:SurfaceArea.surface_area-fb336e2a84@held-out", "question": "r\"\"\"Calculate all atomic surface area.\n\n :rtype: [float]", "scope": {"holder": "mordred-descriptor-mordred", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/mordred-descriptor/mordred/blob/2848b088fd7b6735590242b5e22573babc724f10/mordred/_base/result.py#L49-L63", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:mordred-descriptor-mordred:Result.drop_missing-8e707947b4@held-out", "question": "r\"\"\"Delete missing value.\n\n Returns:\n Result", "scope": {"holder": "mordred-descriptor-mordred", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/mordred-descriptor/mordred/blob/2848b088fd7b6735590242b5e22573babc724f10/mordred/_base/result.py#L97-L115", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:mordred-descriptor-mordred:Result.asdict-a7b8587bc7@held-out", "question": "r\"\"\"Convert Result to dict.\n\n Parameters:\n rawkey(bool):\n * True: dict key is Descriptor instance\n * False: dict key is str\n\n Returns:\n dict", "scope": {"holder": "mordred-descriptor-mordred", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/bloomreach/s4cmd/blob/bb51075bf43703e7cd95aa39288cf7732ec13a6d/s4cmd.py#L169-L173", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:bloomreach-s4cmd:message-039397d12a@held-out", "question": "Program message output.", "scope": {"holder": "bloomreach-s4cmd", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/bloomreach/s4cmd/blob/bb51075bf43703e7cd95aa39288cf7732ec13a6d/s4cmd.py#L111-L114", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:bloomreach-s4cmd:S4cmdLoggingClass.get_loggers-ad3ef6efef@held-out", "question": "Return a list of the logger methods: (debug, info, warn, error)", "scope": {"holder": "bloomreach-s4cmd", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/bloomreach/s4cmd/blob/bb51075bf43703e7cd95aa39288cf7732ec13a6d/s4cmd.py#L754-L761", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:bloomreach-s4cmd:S3Handler.get_basename-80490a219a@held-out", "question": "Unix style basename.\n This fuction will return 'bar' for '/foo/bar/' instead of empty string.\n It is used to normalize the input trailing slash.", "scope": {"holder": "bloomreach-s4cmd", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/bloomreach/s4cmd/blob/bb51075bf43703e7cd95aa39288cf7732ec13a6d/s4cmd.py#L824-L834", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:bloomreach-s4cmd:S3Handler.create_bucket-0429979d8f@held-out", "question": "Use the create_bucket API to create a new bucket", "scope": {"holder": "bloomreach-s4cmd", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/bloomreach/s4cmd/blob/bb51075bf43703e7cd95aa39288cf7732ec13a6d/s4cmd.py#L892-L911", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:bloomreach-s4cmd:S3Handler.delete_removed_files-de41ca7196@held-out", "question": "Remove remote files that are not present in the local source.\n (Obsolete) It is used for old sync command now.", "scope": {"holder": "bloomreach-s4cmd", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/bloomreach/s4cmd/blob/bb51075bf43703e7cd95aa39288cf7732ec13a6d/s4cmd.py#L1143-L1164", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:bloomreach-s4cmd:ThreadUtil.partial_match-a8c631b071@held-out", "question": "Partially match a path and a filter_path with wildcards.\n This function will return True if this path partially match a filter path.\n This is used for walking through directories with multiple level wildcard.", "scope": {"holder": "bloomreach-s4cmd", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/bloomreach/s4cmd/blob/bb51075bf43703e7cd95aa39288cf7732ec13a6d/s4cmd.py#L1297-L1307", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:bloomreach-s4cmd:ThreadUtil.read_file_chunk-6da7673036@held-out", "question": "Read local file chunk", "scope": {"holder": "bloomreach-s4cmd", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/bloomreach/s4cmd/blob/bb51075bf43703e7cd95aa39288cf7732ec13a6d/s4cmd.py#L1386-L1442", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:bloomreach-s4cmd:ThreadUtil.download-ab3379a49e@held-out", "question": "Thread worker for download operation.", "scope": {"holder": "bloomreach-s4cmd", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/bloomreach/s4cmd/blob/bb51075bf43703e7cd95aa39288cf7732ec13a6d/s4cmd.py#L1680-L1690", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:bloomreach-s4cmd:CommandHandler.dsync_handler-20cb64cc06@held-out", "question": "Handler for dsync command.", "scope": {"holder": "bloomreach-s4cmd", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/bloomreach/s4cmd/blob/bb51075bf43703e7cd95aa39288cf7732ec13a6d/s4cmd.py#L1763-L1770", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:bloomreach-s4cmd:ExtendedOptParser.match_time-e85da943bf@held-out", "question": "Search for time information in the string", "scope": {"holder": "bloomreach-s4cmd", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Danielhiversen/PyXiaomiGateway/blob/21b38ab972d67402f2124dba02101ddfd8d9e0b4/xiaomi_gateway/__init__.py#L142-L151", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Danielhiversen-PyXiaomiGateway:XiaomiGatewayDiscovery.listen-230528d4e6@held-out", "question": "Start listening.", "scope": {"holder": "Danielhiversen-PyXiaomiGateway", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Danielhiversen/PyXiaomiGateway/blob/21b38ab972d67402f2124dba02101ddfd8d9e0b4/xiaomi_gateway/__init__.py#L153-L163", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Danielhiversen-PyXiaomiGateway:XiaomiGatewayDiscovery.stop_listen-4d9464b6fd@held-out", "question": "Stop listening.", "scope": {"holder": "Danielhiversen-PyXiaomiGateway", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Danielhiversen/PyXiaomiGateway/blob/21b38ab972d67402f2124dba02101ddfd8d9e0b4/xiaomi_gateway/__init__.py#L386-L396", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Danielhiversen-PyXiaomiGateway:XiaomiGateway.push_data-3a070d48bb@held-out", "question": "Push data broadcasted from gateway to device", "scope": {"holder": "Danielhiversen-PyXiaomiGateway", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Danielhiversen/PyXiaomiGateway/blob/21b38ab972d67402f2124dba02101ddfd8d9e0b4/xiaomi_gateway/__init__.py#L398-L406", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Danielhiversen-PyXiaomiGateway:XiaomiGateway._get_key-05670bf30e@held-out", "question": "Get key using token from gateway", "scope": {"holder": "Danielhiversen-PyXiaomiGateway", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/williamFalcon/test-tube/blob/db5a47067a854f76d89f8066582023c1e184bccb/examples/pytorch_hpc_example.py#L8-L30", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:williamFalcon-test-tube:train-2e5d90cbb2@held-out", "question": "Train your awesome model.\n\n :param hparams: The arguments to run the model with.", "scope": {"holder": "williamFalcon-test-tube", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/rollbar/pyrollbar/blob/33ef2e723a33d09dd6302f978f4a3908be95b9d2/rollbar/contrib/rq/__init__.py#L36-L55", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:rollbar-pyrollbar:exception_handler-7e950bd8a7@held-out", "question": "Called by RQ when there is a failure in a worker.\n\n NOTE: Make sure that in your RQ worker process, rollbar.init() has been called with\n handler='blocking'. The default handler, 'thread', does not work from inside an RQ worker.", "scope": {"holder": "rollbar-pyrollbar", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/rollbar/pyrollbar/blob/33ef2e723a33d09dd6302f978f4a3908be95b9d2/rollbar/__init__.py#L1049-L1091", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:rollbar-pyrollbar:_build_request_data-7a353c5cfe@held-out", "question": "Returns a dictionary containing data from the request.\n Can handle webob or werkzeug-based request objects.", "scope": {"holder": "rollbar-pyrollbar", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/PyCQA/pylint/blob/2bf5c61a3ff6ae90613b81679de42c0f19aea600/pylint/checkers/utils.py#L265-L270", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:PyCQA-pylint:is_super-e3e665aa4b@held-out", "question": "return True if the node is referencing the \"super\" builtin function", "scope": {"holder": "PyCQA-pylint", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/PyCQA/pylint/blob/2bf5c61a3ff6ae90613b81679de42c0f19aea600/pylint/checkers/utils.py#L538-L568", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:PyCQA-pylint:collect_string_fields-976130773e@held-out", "question": "Given a format string, return an iterator\n of all the valid format fields. It handles nested fields\n as well.", "scope": {"holder": "PyCQA-pylint", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/PyCQA/pylint/blob/2bf5c61a3ff6ae90613b81679de42c0f19aea600/pylint/checkers/utils.py#L891-L902", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:PyCQA-pylint:node_ignores_exception-2f04717dfe@held-out", "question": "Check if the node is in a TryExcept which handles the given exception.\n\n If the exception is not given, the function is going to look for bare\n excepts.", "scope": {"holder": "PyCQA-pylint", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/PyCQA/pylint/blob/2bf5c61a3ff6ae90613b81679de42c0f19aea600/pylint/checkers/utils.py#L1107-L1125", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:PyCQA-pylint:node_type-543f2e7b59@held-out", "question": "Return the inferred type for `node`\n\n If there is more than one possible type, or if inferred type is Uninferable or None,\n return None", "scope": {"holder": "PyCQA-pylint", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/PyCQA/pylint/blob/2bf5c61a3ff6ae90613b81679de42c0f19aea600/pylint/checkers/imports.py#L791-L813", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:PyCQA-pylint:ImportsChecker._check_relative_import-2515fe05d8@held-out", "question": "check relative import. node is either an Import or From node, modname\n the imported module name.", "scope": {"holder": "PyCQA-pylint", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/PyCQA/pylint/blob/2bf5c61a3ff6ae90613b81679de42c0f19aea600/pylint/checkers/imports.py#L850-L854", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:PyCQA-pylint:ImportsChecker._check_deprecated_module-b333944a38@held-out", "question": "check if the module is deprecated", "scope": {"holder": "PyCQA-pylint", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/PyCQA/pylint/blob/2bf5c61a3ff6ae90613b81679de42c0f19aea600/pylint/pyreverse/utils.py#L135-L139", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:PyCQA-pylint:FilterMixIn.show_attr-733a523307@held-out", "question": "return true if the node should be treated", "scope": {"holder": "PyCQA-pylint", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/PyCQA/pylint/blob/2bf5c61a3ff6ae90613b81679de42c0f19aea600/pylint/checkers/stdlib.py#L286-L312", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:PyCQA-pylint:StdlibChecker.visit_call-945bb5a3b5@held-out", "question": "Visit a Call node.", "scope": {"holder": "PyCQA-pylint", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/PyCQA/pylint/blob/2bf5c61a3ff6ae90613b81679de42c0f19aea600/pylint/pyreverse/diadefslib.py#L55-L69", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:PyCQA-pylint:DiaDefGenerator._set_default_options-1f77a7e6a8@held-out", "question": "set different default options with _default dictionary", "scope": {"holder": "PyCQA-pylint", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/PyCQA/pylint/blob/2bf5c61a3ff6ae90613b81679de42c0f19aea600/pylint/pyreverse/diadefslib.py#L86-L93", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:PyCQA-pylint:DiaDefGenerator.get_ancestors-803630dad3@held-out", "question": "return ancestor nodes of a class node", "scope": {"holder": "PyCQA-pylint", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/PyCQA/pylint/blob/2bf5c61a3ff6ae90613b81679de42c0f19aea600/pylint/pyreverse/diadefslib.py#L109-L119", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:PyCQA-pylint:DiaDefGenerator.extract_classes-4d5c943765@held-out", "question": "extract recursively classes related to klass_node", "scope": {"holder": "PyCQA-pylint", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/PyCQA/pylint/blob/2bf5c61a3ff6ae90613b81679de42c0f19aea600/pylint/pyreverse/diadefslib.py#L145-L152", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:PyCQA-pylint:DefaultDiadefGenerator.leave_project-68ec7be617@held-out", "question": "leave the pyreverse.utils.Project node\n\n return the generated diagram definition", "scope": {"holder": "PyCQA-pylint", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/PyCQA/pylint/blob/2bf5c61a3ff6ae90613b81679de42c0f19aea600/pylint/checkers/typecheck.py#L506-L511", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:PyCQA-pylint:_is_name_used_as_variadic-6cd28d99df@held-out", "question": "Check if the given name is used as a variadic argument.", "scope": {"holder": "PyCQA-pylint", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/PyCQA/pylint/blob/2bf5c61a3ff6ae90613b81679de42c0f19aea600/pylint/checkers/typecheck.py#L948-L983", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:PyCQA-pylint:TypeChecker.visit_assign-95d39dbba7@held-out", "question": "check that if assigning to a function call, the function is\n possibly returning something valuable", "scope": {"holder": "PyCQA-pylint", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/PyCQA/pylint/blob/2bf5c61a3ff6ae90613b81679de42c0f19aea600/pylint/checkers/typecheck.py#L1434-L1439", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:PyCQA-pylint:TypeChecker.visit_unaryop-433daa9b55@held-out", "question": "Detect TypeErrors for unary operands.", "scope": {"holder": "PyCQA-pylint", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/PyCQA/pylint/blob/2bf5c61a3ff6ae90613b81679de42c0f19aea600/pylint/pyreverse/inspector.py#L193-L225", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:PyCQA-pylint:Linker.visit_assignname-72c81fe25d@held-out", "question": "visit an astroid.AssignName node\n\n handle locals_type", "scope": {"holder": "PyCQA-pylint", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/PyCQA/pylint/blob/2bf5c61a3ff6ae90613b81679de42c0f19aea600/pylint/checkers/strings.py#L750-L763", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:PyCQA-pylint:str_eval-143fc0a724@held-out", "question": "Mostly replicate `ast.literal_eval(token)` manually to avoid any performance hit.\n This supports f-strings, contrary to `ast.literal_eval`.\n We have to support all string literal notations:\n https://docs.python.org/3/reference/lexical_analysis.html#string-and-bytes-literals", "scope": {"holder": "PyCQA-pylint", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/PyCQA/pylint/blob/2bf5c61a3ff6ae90613b81679de42c0f19aea600/pylint/checkers/strings.py#L370-L451", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:PyCQA-pylint:StringFormatChecker._check_new_format-f7ca2893a8@held-out", "question": "Check the new string formatting.", "scope": {"holder": "PyCQA-pylint", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/PyCQA/pylint/blob/2bf5c61a3ff6ae90613b81679de42c0f19aea600/pylint/lint.py#L1396-L1416", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:PyCQA-pylint:fix_import_path-43e3e79f3c@held-out", "question": "Prepare sys.path for running the linter checks.\n\n Within this context, each of the given arguments is importable.\n Paths are added to sys.path in corresponding order to the arguments.\n We avoid adding duplicate directories to sys.path.\n `sys.path` is reset to its original value upon exiting this context.", "scope": {"holder": "PyCQA-pylint", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/PyCQA/pylint/blob/2bf5c61a3ff6ae90613b81679de42c0f19aea600/pylint/lint.py#L1158-L1170", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:PyCQA-pylint:PyLinter.set_current_module-f0a481eb42@held-out", "question": "set the name of the currently analyzed module and\n init statistics for it", "scope": {"holder": "PyCQA-pylint", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/PyCQA/pylint/blob/2bf5c61a3ff6ae90613b81679de42c0f19aea600/pylint/lint.py#L1696-L1698", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:PyCQA-pylint:Run.cb_add_plugins-5f25806ad6@held-out", "question": "callback for option preprocessing (i.e. before option parsing)", "scope": {"holder": "PyCQA-pylint", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/PyCQA/pylint/blob/2bf5c61a3ff6ae90613b81679de42c0f19aea600/pylint/lint.py#L1732-L1735", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:PyCQA-pylint:Run.cb_list_messages-d1479c920e@held-out", "question": "optik callback for printing available messages", "scope": {"holder": "PyCQA-pylint", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/PyCQA/pylint/blob/2bf5c61a3ff6ae90613b81679de42c0f19aea600/pylint/utils/utils.py#L187-L213", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:PyCQA-pylint:register_plugins-8829574eaf@held-out", "question": "load all module and package in the given directory, looking for a\n 'register' function in each one, used to register pylint checkers", "scope": {"holder": "PyCQA-pylint", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/PyCQA/pylint/blob/2bf5c61a3ff6ae90613b81679de42c0f19aea600/pylint/utils/utils.py#L335-L355", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:PyCQA-pylint:_ini_format-9914261bef@held-out", "question": "format options using the INI format", "scope": {"holder": "PyCQA-pylint", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/PyCQA/pylint/blob/2bf5c61a3ff6ae90613b81679de42c0f19aea600/pylint/checkers/variables.py#L88-L102", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:PyCQA-pylint:overridden_method-b5dfd8b024@held-out", "question": "get overridden method if any", "scope": {"holder": "PyCQA-pylint", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/PyCQA/pylint/blob/2bf5c61a3ff6ae90613b81679de42c0f19aea600/pylint/checkers/variables.py#L105-L118", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:PyCQA-pylint:_get_unpacking_extra_info-6013f95e7f@held-out", "question": "return extra information to add to the message for unpacking-non-sequence\n and unbalanced-tuple-unpacking errors", "scope": {"holder": "PyCQA-pylint", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/PyCQA/pylint/blob/2bf5c61a3ff6ae90613b81679de42c0f19aea600/pylint/checkers/variables.py#L477-L483", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:PyCQA-pylint:NamesConsumer.mark_as_consumed-6ccd5c12d9@held-out", "question": "Mark the name as consumed and delete it from\n the to_consume dictionary", "scope": {"holder": "PyCQA-pylint", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/PyCQA/pylint/blob/2bf5c61a3ff6ae90613b81679de42c0f19aea600/pylint/checkers/variables.py#L669-L685", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:PyCQA-pylint:VariablesChecker.leave_module-d6ba3ee275@held-out", "question": "leave module: check globals", "scope": {"holder": "PyCQA-pylint", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/PyCQA/pylint/blob/2bf5c61a3ff6ae90613b81679de42c0f19aea600/pylint/checkers/variables.py#L1632-L1647", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:PyCQA-pylint:VariablesChecker.visit_assign-eeaffcb922@held-out", "question": "Check unbalanced tuple unpacking for assignments\n and unpacking non-sequences as well as in case self/cls\n get assigned.", "scope": {"holder": "PyCQA-pylint", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/PyCQA/pylint/blob/2bf5c61a3ff6ae90613b81679de42c0f19aea600/pylint/checkers/variables.py#L1748-L1782", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:PyCQA-pylint:VariablesChecker._check_module_attrs-39a7d501a0@held-out", "question": "check that module_names (list of string) are accessible through the\n given module\n if the latest access name corresponds to a module, return it", "scope": {"holder": "PyCQA-pylint", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/PyCQA/pylint/blob/2bf5c61a3ff6ae90613b81679de42c0f19aea600/setup.py#L71-L79", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:PyCQA-pylint:ensure_scripts-6115ad1c98@held-out", "question": "Creates the proper script names required for each platform\n (taken from 4Suite)", "scope": {"holder": "PyCQA-pylint", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/PyCQA/pylint/blob/2bf5c61a3ff6ae90613b81679de42c0f19aea600/pylint/checkers/similar.py#L116-L144", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:PyCQA-pylint:Similar._find_common-2dcb5d6f27@held-out", "question": "find similarities in the two given linesets", "scope": {"holder": "PyCQA-pylint", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/PyCQA/pylint/blob/2bf5c61a3ff6ae90613b81679de42c0f19aea600/pylint/checkers/classes.py#L633-L640", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:PyCQA-pylint:ScopeAccessMap.set_accessed-4829874873@held-out", "question": "Set the given node as accessed.", "scope": {"holder": "PyCQA-pylint", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/PyCQA/pylint/blob/2bf5c61a3ff6ae90613b81679de42c0f19aea600/pylint/checkers/classes.py#L742-L754", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:PyCQA-pylint:ClassChecker.visit_classdef-cf3c16bed1@held-out", "question": "init visit variable _accessed", "scope": {"holder": "PyCQA-pylint", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/PyCQA/pylint/blob/2bf5c61a3ff6ae90613b81679de42c0f19aea600/pylint/checkers/classes.py#L1539-L1581", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:PyCQA-pylint:ClassChecker._check_signature-bcc84c8a30@held-out", "question": "check that the signature of the two given methods match", "scope": {"holder": "PyCQA-pylint", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/PyCQA/pylint/blob/2bf5c61a3ff6ae90613b81679de42c0f19aea600/pylint/checkers/classes.py#L1590-L1599", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:PyCQA-pylint:ClassChecker._is_mandatory_method_param-178640f6dc@held-out", "question": "Check if astroid.Name corresponds to first attribute variable name\n\n Name is `self` for method, `cls` for classmethod and `mcs` for metaclass.", "scope": {"holder": "PyCQA-pylint", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/PyCQA/pylint/blob/2bf5c61a3ff6ae90613b81679de42c0f19aea600/pylint/extensions/overlapping_exceptions.py#L34-L83", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:PyCQA-pylint:OverlappingExceptionsChecker.visit_tryexcept-b42c8cc9c6@held-out", "question": "check for empty except", "scope": {"holder": "PyCQA-pylint", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/PyCQA/pylint/blob/2bf5c61a3ff6ae90613b81679de42c0f19aea600/pylint/graph.py#L73-L131", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:PyCQA-pylint:DotBackend.generate-11ecefe9d9@held-out", "question": "Generates a graph file.\n\n :param str outputfile: filename and path [defaults to graphname.png]\n :param str dotfile: filename and path [defaults to graphname.dot]\n :param str mapfile: filename and path\n\n :rtype: str\n :return: a path to the generated file", "scope": {"holder": "PyCQA-pylint", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/PyCQA/pylint/blob/2bf5c61a3ff6ae90613b81679de42c0f19aea600/pylint/message/message_handler_mix_in.py#L198-L218", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:PyCQA-pylint:MessagesHandlerMixIn.is_message_enabled-e5d47e7041@held-out", "question": "return true if the message associated to the given message id is\n enabled\n\n msgid may be either a numeric or symbolic message id.", "scope": {"holder": "PyCQA-pylint", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/PyCQA/pylint/blob/2bf5c61a3ff6ae90613b81679de42c0f19aea600/pylint/message/message_handler_mix_in.py#L403-L459", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:PyCQA-pylint:MessagesHandlerMixIn._print_checker_doc-5da0bb16e3@held-out", "question": "Helper method for print_full_documentation.\n\n Also used by doc/exts/pylint_extensions.py.", "scope": {"holder": "PyCQA-pylint", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/PyCQA/pylint/blob/2bf5c61a3ff6ae90613b81679de42c0f19aea600/pylint/checkers/format.py#L393-L402", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:PyCQA-pylint:TokenWrapper.token_indent-704c783ca9@held-out", "question": "Get an indentation string for hanging indentation, consisting of the line-indent plus\n a number of spaces to fill up to the column of this token.\n\n e.g. the token indent for foo\n in \"<TAB><TAB>print(foo)\"\n is \"<TAB><TAB> \"", "scope": {"holder": "PyCQA-pylint", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/PyCQA/pylint/blob/2bf5c61a3ff6ae90613b81679de42c0f19aea600/pylint/checkers/format.py#L530-L554", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:PyCQA-pylint:ContinuedLineState._continuation_inside_bracket-bf4ccf3b41@held-out", "question": "Extracts indentation information for a continued indent.", "scope": {"holder": "PyCQA-pylint", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/PyCQA/pylint/blob/2bf5c61a3ff6ae90613b81679de42c0f19aea600/pylint/checkers/format.py#L730-L804", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:PyCQA-pylint:FormatChecker._check_keyword_parentheses-a51490bb7e@held-out", "question": "Check that there are not unnecessary parens after a keyword.\n\n Parens are unnecessary if there is exactly one balanced outer pair on a\n line, and it is followed by a colon, and contains no commas (i.e. is not a\n tuple).\n\n Args:\n tokens: list of Tokens; the entire list of Tokens.\n start: int; the position of the keyword in the token list.", "scope": {"holder": "PyCQA-pylint", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/PyCQA/pylint/blob/2bf5c61a3ff6ae90613b81679de42c0f19aea600/pylint/checkers/format.py#L898-L900", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:PyCQA-pylint:FormatChecker._check_surrounded_by_space-69ce2c8b05@held-out", "question": "Check that a binary operator is surrounded by exactly one space.", "scope": {"holder": "PyCQA-pylint", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/PyCQA/pylint/blob/2bf5c61a3ff6ae90613b81679de42c0f19aea600/pylint/checkers/format.py#L1207-L1232", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:PyCQA-pylint:FormatChecker._check_multi_statement_line-1ccc0f2356@held-out", "question": "Check for lines containing multiple statements.", "scope": {"holder": "PyCQA-pylint", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/PyCQA/pylint/blob/2bf5c61a3ff6ae90613b81679de42c0f19aea600/pylint/checkers/python3.py#L1226-L1235", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:PyCQA-pylint:Python3Checker.visit_subscript-cbaced8082@held-out", "question": "Look for indexing exceptions.", "scope": {"holder": "PyCQA-pylint", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/PyCQA/pylint/blob/2bf5c61a3ff6ae90613b81679de42c0f19aea600/pylint/checkers/python3.py#L1271-L1316", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:PyCQA-pylint:Python3Checker.visit_excepthandler-380c045424@held-out", "question": "Visit an except handler block and check for exception unpacking.", "scope": {"holder": "PyCQA-pylint", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/PyCQA/pylint/blob/2bf5c61a3ff6ae90613b81679de42c0f19aea600/pylint/config.py#L643-L645", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:PyCQA-pylint:OptionsManagerMixIn.global_set_option-55ff826be2@held-out", "question": "set option on the correct option provider", "scope": {"holder": "PyCQA-pylint", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/PyCQA/pylint/blob/2bf5c61a3ff6ae90613b81679de42c0f19aea600/pylint/config.py#L796-L800", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:PyCQA-pylint:OptionsManagerMixIn.help-8b00d18489@held-out", "question": "return the usage string for available options", "scope": {"holder": "PyCQA-pylint", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/PyCQA/pylint/blob/2bf5c61a3ff6ae90613b81679de42c0f19aea600/pylint/checkers/logging.py#L278-L330", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:PyCQA-pylint:LoggingChecker._check_format_string-6b0c63d4e7@held-out", "question": "Checks that format string tokens match the supplied arguments.\n\n Args:\n node (astroid.node_classes.NodeNG): AST node to be checked.\n format_arg (int): Index of the format string in the node arguments.", "scope": {"holder": "PyCQA-pylint", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/PyCQA/pylint/blob/2bf5c61a3ff6ae90613b81679de42c0f19aea600/pylint/checkers/base.py#L393-L409", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:PyCQA-pylint:redefined_by_decorator-755b9008c1@held-out", "question": "return True if the object is a method redefined via decorator.\n\n For example:\n @property\n def x(self): return self._x\n @x.setter\n def x(self, value): self._x = value", "scope": {"holder": "PyCQA-pylint", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/PyCQA/pylint/blob/2bf5c61a3ff6ae90613b81679de42c0f19aea600/pylint/checkers/base.py#L2021-L2025", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:PyCQA-pylint:_is_one_arg_pos_call-52a2225875@held-out", "question": "Is this a call with exactly 1 argument,\n where that argument is positional?", "scope": {"holder": "PyCQA-pylint", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/PyCQA/pylint/blob/2bf5c61a3ff6ae90613b81679de42c0f19aea600/pylint/checkers/base.py#L2236-L2243", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:PyCQA-pylint:register-3e13cabd5a@held-out", "question": "required method to auto register this checker", "scope": {"holder": "PyCQA-pylint", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/PyCQA/pylint/blob/2bf5c61a3ff6ae90613b81679de42c0f19aea600/pylint/checkers/base.py#L552-L569", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:PyCQA-pylint:BasicErrorChecker.visit_starred-9c1ea0b51b@held-out", "question": "Check that a Starred expression is used in an assignment target.", "scope": {"holder": "PyCQA-pylint", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/PyCQA/pylint/blob/2bf5c61a3ff6ae90613b81679de42c0f19aea600/pylint/checkers/base.py#L803-L813", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:PyCQA-pylint:BasicErrorChecker._check_else_on_loop-c464cdf41e@held-out", "question": "Check that any loop with an else clause has a break statement.", "scope": {"holder": "PyCQA-pylint", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/PyCQA/pylint/blob/2bf5c61a3ff6ae90613b81679de42c0f19aea600/pylint/checkers/base.py#L997-L1001", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:PyCQA-pylint:BasicChecker.open-e8dd937f5e@held-out", "question": "initialize visit variables and statistics", "scope": {"holder": "PyCQA-pylint", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/PyCQA/pylint/blob/2bf5c61a3ff6ae90613b81679de42c0f19aea600/pylint/checkers/base.py#L1379-L1395", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:PyCQA-pylint:BasicChecker._check_not_in_finally-6df9a76217@held-out", "question": "check that a node is not inside a finally clause of a\n try...finally statement.\n If we found before a try...finally bloc a parent which its type is\n in breaker_classes, we skip the whole check.", "scope": {"holder": "PyCQA-pylint", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/PyCQA/pylint/blob/2bf5c61a3ff6ae90613b81679de42c0f19aea600/pylint/pyreverse/diagrams.py#L74-L80", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:PyCQA-pylint:ClassDiagram.get_relationship-e7c7454e00@held-out", "question": "return a relation ship or None", "scope": {"holder": "PyCQA-pylint", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/PyCQA/pylint/blob/2bf5c61a3ff6ae90613b81679de42c0f19aea600/pylint/pyreverse/diagrams.py#L153-L155", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:PyCQA-pylint:ClassDiagram.classes-4296ba8c41@held-out", "question": "return all class nodes in the diagram", "scope": {"holder": "PyCQA-pylint", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/PyCQA/pylint/blob/2bf5c61a3ff6ae90613b81679de42c0f19aea600/pylint/pyreverse/diagrams.py#L241-L247", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:PyCQA-pylint:PackageDiagram.add_from_depend-2f6a615142@held-out", "question": "add dependencies created by from-imports", "scope": {"holder": "PyCQA-pylint", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/PyCQA/pylint/blob/2bf5c61a3ff6ae90613b81679de42c0f19aea600/pylint/extensions/docparams.py#L327-L454", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:PyCQA-pylint:DocstringParameterChecker.check_arguments_in_docstring-ffb014378f@held-out", "question": "Check that all parameters in a function, method or class constructor\n on the one hand and the parameters mentioned in the parameter\n documentation (e.g. the Sphinx tags 'param' and 'type') on the other\n hand are consistent with each other.\n\n * Undocumented parameters except 'self' are noticed.\n * Undocumented parameter types except for 'self' and the ``*<args>``\n and ``**<kwargs>`` parameters are noticed.\n * Parameters mentioned in the parameter documentation that don't or no\n longer exist in the function parameter list are noticed.\n * If the text \"For the parameters, see\" or \"For the other parameters,\n see\" (ignoring additional whitespace) is mentioned in the docstring,\n missing parameter documentation is tolerated.\n * If there's no Sphinx style, Google style or NumPy style parameter\n documentation at all, i.e. ``:param`` is never mentioned etc., the\n checker assumes that the parameters are documented in another format\n and the absence is tolerated.\n\n :param doc: Docstring for the function, method or class.\n :type doc: str\n\n :param arguments_node: Arguments node for the function, method or\n class constructor.\n :type arguments_node: :class:`astroid.scoped_nodes.Arguments`\n\n :param warning_node: The node to assign the warnings to\n :type warning_node: :class:`astroid.scoped_nodes.Node`\n\n :param accept_no_param_doc: Whether or not to allow no parameters\n to be documented.\n If None then this value is read from the configuration.\n :type accept_no_param_doc: bool or None", "scope": {"holder": "PyCQA-pylint", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/lepture/flask-oauthlib/blob/9e6f152a5bb360e7496210da21561c3e6d41b0e1/flask_oauthlib/client.py#L69-L81", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:lepture-flask-oauthlib:OAuth.remote_app-ed5a16aa03@held-out", "question": "Registers a new remote application.\n\n :param name: the name of the remote application\n :param register: whether the remote app will be registered\n\n Find more parameters from :class:`OAuthRemoteApp`.", "scope": {"holder": "lepture-flask-oauthlib", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/lepture/flask-oauthlib/blob/9e6f152a5bb360e7496210da21561c3e6d41b0e1/flask_oauthlib/client.py#L652-L694", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:lepture-flask-oauthlib:OAuthRemoteApp.handle_oauth2_response-3804208b79@held-out", "question": "Handles an oauth2 authorization response.", "scope": {"holder": "lepture-flask-oauthlib", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/lepture/flask-oauthlib/blob/9e6f152a5bb360e7496210da21561c3e6d41b0e1/flask_oauthlib/client.py#L716-L730", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:lepture-flask-oauthlib:OAuthRemoteApp.authorized_handler-31ea1f78d7@held-out", "question": "Handles an OAuth callback.\n\n .. versionchanged:: 0.7\n @authorized_handler is deprecated in favor of authorized_response.", "scope": {"holder": "lepture-flask-oauthlib", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/lepture/flask-oauthlib/blob/9e6f152a5bb360e7496210da21561c3e6d41b0e1/flask_oauthlib/provider/oauth1.py#L696-L700", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:lepture-flask-oauthlib:OAuth1RequestValidator.get_redirect_uri-234d406b89@held-out", "question": "Redirect uri for this request token.", "scope": {"holder": "lepture-flask-oauthlib", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/lepture/flask-oauthlib/blob/9e6f152a5bb360e7496210da21561c3e6d41b0e1/flask_oauthlib/provider/oauth1.py#L765-L775", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:lepture-flask-oauthlib:OAuth1RequestValidator.validate_redirect_uri-6900f7cb4b@held-out", "question": "Validate if the redirect_uri is allowed by the client.", "scope": {"holder": "lepture-flask-oauthlib", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/lepture/flask-oauthlib/blob/9e6f152a5bb360e7496210da21561c3e6d41b0e1/flask_oauthlib/provider/oauth1.py#L841-L858", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:lepture-flask-oauthlib:OAuth1RequestValidator.save_access_token-809da2db2a@held-out", "question": "Save access token to database.\n\n A tokensetter is required, which accepts a token and request\n parameters::\n\n def tokensetter(token, request):\n access_token = Token(\n client=request.client,\n user=request.user,\n token=token['oauth_token'],\n secret=token['oauth_token_secret'],\n realms=token['oauth_authorized_realms'],\n )\n return access_token.save()", "scope": {"holder": "lepture-flask-oauthlib", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/lepture/flask-oauthlib/blob/9e6f152a5bb360e7496210da21561c3e6d41b0e1/flask_oauthlib/provider/oauth2.py#L400-L477", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:lepture-flask-oauthlib:OAuth2Provider.authorize_handler-6c3ea01595@held-out", "question": "Authorization handler decorator.\n\n This decorator will sort the parameters and headers out, and\n pre validate everything::\n\n @app.route('/oauth/authorize', methods=['GET', 'POST'])\n @oauth.authorize_handler\n def authorize(*args, **kwargs):\n if request.method == 'GET':\n # render a page for user to confirm the authorization\n return render_template('oauthorize.html')\n\n confirm = request.form.get('confirm', 'no')\n return confirm == 'yes'", "scope": {"holder": "lepture-flask-oauthlib", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/lepture/flask-oauthlib/blob/9e6f152a5bb360e7496210da21561c3e6d41b0e1/flask_oauthlib/provider/oauth2.py#L663-L691", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:lepture-flask-oauthlib:OAuth2RequestValidator.client_authentication_required-7c9aae8f42@held-out", "question": "Determine if client authentication is required for current request.\n\n According to the rfc6749, client authentication is required in the\n following cases:\n\n Resource Owner Password Credentials Grant: see `Section 4.3.2`_.\n Authorization Code Grant: see `Section 4.1.3`_.\n Refresh Token Grant: see `Section 6`_.\n\n .. _`Section 4.3.2`: http://tools.ietf.org/html/rfc6749#section-4.3.2\n .. _`Section 4.1.3`: http://tools.ietf.org/html/rfc6749#section-4.1.3\n .. _`Section 6`: http://tools.ietf.org/html/rfc6749#section-6", "scope": {"holder": "lepture-flask-oauthlib", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/lepture/flask-oauthlib/blob/9e6f152a5bb360e7496210da21561c3e6d41b0e1/flask_oauthlib/provider/oauth2.py#L777-L792", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:lepture-flask-oauthlib:OAuth2RequestValidator.confirm_scopes-8021737284@held-out", "question": "Ensures the requested scope matches the scope originally granted\n by the resource owner. If the scope is omitted it is treated as equal\n to the scope originally granted by the resource owner.\n\n DEPRECATION NOTE: This method will cease to be used in oauthlib>0.4.2,\n future versions of ``oauthlib`` use the validator method\n ``get_original_scopes`` to determine the scope of the refreshed token.", "scope": {"holder": "lepture-flask-oauthlib", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/lepture/flask-oauthlib/blob/9e6f152a5bb360e7496210da21561c3e6d41b0e1/flask_oauthlib/provider/oauth2.py#L801-L806", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:lepture-flask-oauthlib:OAuth2RequestValidator.get_default_scopes-f5aa8314ac@held-out", "question": "Default scopes for the given client.", "scope": {"holder": "lepture-flask-oauthlib", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/lepture/flask-oauthlib/blob/9e6f152a5bb360e7496210da21561c3e6d41b0e1/flask_oauthlib/provider/oauth2.py#L883-L891", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:lepture-flask-oauthlib:OAuth2RequestValidator.validate_client_id-0503d28601@held-out", "question": "Ensure client_id belong to a valid and active client.", "scope": {"holder": "lepture-flask-oauthlib", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/lepture/flask-oauthlib/blob/9e6f152a5bb360e7496210da21561c3e6d41b0e1/flask_oauthlib/provider/oauth2.py#L913-L949", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:lepture-flask-oauthlib:OAuth2RequestValidator.validate_grant_type-3a54cc2c10@held-out", "question": "Ensure the client is authorized to use the grant type requested.\n\n It will allow any of the four grant types (`authorization_code`,\n `password`, `client_credentials`, `refresh_token`) by default.\n Implemented `allowed_grant_types` for client object to authorize\n the request.\n\n It is suggested that `allowed_grant_types` should contain at least\n `authorization_code` and `refresh_token`.", "scope": {"holder": "lepture-flask-oauthlib", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/lepture/flask-oauthlib/blob/9e6f152a5bb360e7496210da21561c3e6d41b0e1/flask_oauthlib/contrib/cache.py#L79-L84", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:lepture-flask-oauthlib:Cache._filesystem-9de9be37e8@held-out", "question": "Returns a :class:`FileSystemCache` instance", "scope": {"holder": "lepture-flask-oauthlib", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/lepture/flask-oauthlib/blob/9e6f152a5bb360e7496210da21561c3e6d41b0e1/flask_oauthlib/contrib/client/__init__.py#L57-L75", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:lepture-flask-oauthlib:OAuth.remote_app-e20b80053d@held-out", "question": "Creates and adds new remote application.\n\n :param name: the remote application's name.\n :param version: '1' or '2', the version code of OAuth protocol.\n :param kwargs: the attributes of remote application.", "scope": {"holder": "lepture-flask-oauthlib", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/pyca/pyopenssl/blob/1fbe064c50fd030948141d7d630673761525b0d0/leakcheck/crypto.py#L24-L33", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:pyca-pyopenssl:Checker_X509_get_pubkey.check_exception-1342a57aa3@held-out", "question": "Call the method repeatedly such that it will raise an exception.", "scope": {"holder": "pyca-pyopenssl", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/pyca/pyopenssl/blob/1fbe064c50fd030948141d7d630673761525b0d0/leakcheck/crypto.py#L152-L161", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:pyca-pyopenssl:Checker_EllipticCurve.check_to_EC_KEY-f2046692e9@held-out", "question": "Repeatedly create an EC_KEY* from an :py:obj:`_EllipticCurve`. The\n structure should be automatically garbage collected.", "scope": {"holder": "pyca-pyopenssl", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/pyca/pyopenssl/blob/1fbe064c50fd030948141d7d630673761525b0d0/examples/certgen.py#L17-L27", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:pyca-pyopenssl:createKeyPair-6827fd8943@held-out", "question": "Create a public/private key pair.\n\n Arguments: type - Key type, must be one of TYPE_RSA and TYPE_DSA\n bits - Number of bits to use in the key\n Returns: The public/private key pair in a PKey object", "scope": {"holder": "pyca-pyopenssl", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/pyca/pyopenssl/blob/1fbe064c50fd030948141d7d630673761525b0d0/src/OpenSSL/SSL.py#L931-L943", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:pyca-pyopenssl:Context.use_certificate-2ad7e12e65@held-out", "question": "Load a certificate from a X509 object\n\n :param cert: The X509 object\n :return: None", "scope": {"holder": "pyca-pyopenssl", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/pyca/pyopenssl/blob/1fbe064c50fd030948141d7d630673761525b0d0/src/OpenSSL/SSL.py#L1077-L1104", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:pyca-pyopenssl:Context.set_verify-1bc79a4c0f@held-out", "question": "et the verification flags for this Context object to *mode* and specify\n that *callback* should be used for verification callbacks.\n\n :param mode: The verify mode, this should be one of\n :const:`VERIFY_NONE` and :const:`VERIFY_PEER`. If\n :const:`VERIFY_PEER` is used, *mode* can be OR:ed with\n :const:`VERIFY_FAIL_IF_NO_PEER_CERT` and\n :const:`VERIFY_CLIENT_ONCE` to further control the behaviour.\n :param callback: The Python callback to use. This should take five\n arguments: A Connection object, an X509 object, and three integer\n variables, which are in turn potential error number, error depth\n and return code. *callback* should return True if verification\n passes and False otherwise.\n :return: None\n\n See SSL_CTX_set_verify(3SSL) for further details.", "scope": {"holder": "pyca-pyopenssl", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/pyca/pyopenssl/blob/1fbe064c50fd030948141d7d630673761525b0d0/src/OpenSSL/SSL.py#L1210-L1245", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:pyca-pyopenssl:Context.set_client_ca_list-fc0e49e11d@held-out", "question": "Set the list of preferred client certificate signers for this server\n context.\n\n This list of certificate authorities will be sent to the client when\n the server requests a client certificate.\n\n :param certificate_authorities: a sequence of X509Names.\n :return: None\n\n .. versionadded:: 0.10", "scope": {"holder": "pyca-pyopenssl", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/pyca/pyopenssl/blob/1fbe064c50fd030948141d7d630673761525b0d0/src/OpenSSL/SSL.py#L1343-L1354", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:pyca-pyopenssl:Context.set_options-aa2aea4cf9@held-out", "question": "Add options. Options set before are not cleared!\n This method should be used with the :const:`OP_*` constants.\n\n :param options: The options to add.\n :return: The new option bitmask.", "scope": {"holder": "pyca-pyopenssl", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/pyca/pyopenssl/blob/1fbe064c50fd030948141d7d630673761525b0d0/src/OpenSSL/SSL.py#L1389-L1402", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:pyca-pyopenssl:Context.set_tlsext_use_srtp-94b38ba749@held-out", "question": "Enable support for negotiating SRTP keying material.\n\n :param bytes profiles: A colon delimited list of protection profile\n names, like ``b'SRTP_AES128_CM_SHA1_80:SRTP_AES128_CM_SHA1_32'``.\n :return: None", "scope": {"holder": "pyca-pyopenssl", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/pyca/pyopenssl/blob/1fbe064c50fd030948141d7d630673761525b0d0/src/OpenSSL/SSL.py#L1851-L1873", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:pyca-pyopenssl:Connection.bio_read-c479e963e2@held-out", "question": "If the Connection was created with a memory BIO, this method can be\n used to read bytes from the write end of that memory BIO. Many\n Connection methods will add bytes which must be read in this manner or\n the buffer will eventually fill up and the Connection will be able to\n take no further actions.\n\n :param bufsiz: The maximum number of bytes to read\n :return: The string read.", "scope": {"holder": "pyca-pyopenssl", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/pyca/pyopenssl/blob/1fbe064c50fd030948141d7d630673761525b0d0/src/OpenSSL/SSL.py#L1895-L1905", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:pyca-pyopenssl:Connection.renegotiate-e593a04c1f@held-out", "question": "Renegotiate the session.\n\n :return: True if the renegotiation can be started, False otherwise\n :rtype: bool", "scope": {"holder": "pyca-pyopenssl", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/pyca/pyopenssl/blob/1fbe064c50fd030948141d7d630673761525b0d0/src/OpenSSL/SSL.py#L2266-L2281", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:pyca-pyopenssl:Connection.get_session-e4c54976d8@held-out", "question": "Returns the Session currently used.\n\n :return: An instance of :class:`OpenSSL.SSL.Session` or\n :obj:`None` if no session exists.\n\n .. versionadded:: 0.14", "scope": {"holder": "pyca-pyopenssl", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/pyca/pyopenssl/blob/1fbe064c50fd030948141d7d630673761525b0d0/src/OpenSSL/SSL.py#L2357-L2372", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:pyca-pyopenssl:Connection.get_cipher_name-868f0558c1@held-out", "question": "Obtain the name of the currently used cipher.\n\n :returns: The name of the currently used cipher or :obj:`None`\n if no connection has been established.\n :rtype: :class:`unicode` or :class:`NoneType`\n\n .. versionadded:: 0.15", "scope": {"holder": "pyca-pyopenssl", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/pyca/pyopenssl/blob/1fbe064c50fd030948141d7d630673761525b0d0/src/OpenSSL/crypto.py#L165-L202", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:pyca-pyopenssl:_get_asn1_time-02c1001aa9@held-out", "question": "Retrieve the time value of an ASN1 time object.\n\n @param timestamp: An ASN1_GENERALIZEDTIME* (or an object safely castable to\n that type) from which the time value will be retrieved.\n\n @return: The time value from C{timestamp} as a L{bytes} string in a certain\n format. Or C{None} if the object contains no time value.", "scope": {"holder": "pyca-pyopenssl", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/pyca/pyopenssl/blob/1fbe064c50fd030948141d7d630673761525b0d0/src/OpenSSL/crypto.py#L2836-L2869", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:pyca-pyopenssl:verify-3d06e47b7b@held-out", "question": "Verify the signature for a data string.\n\n :param cert: signing certificate (X509 object) corresponding to the\n private key which generated the signature.\n :param signature: signature returned by sign function\n :param data: data to be verified\n :param digest: message digest to use\n :return: ``None`` if the signature is correct, raise exception otherwise.\n\n .. versionadded:: 0.11", "scope": {"holder": "pyca-pyopenssl", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/pyca/pyopenssl/blob/1fbe064c50fd030948141d7d630673761525b0d0/src/OpenSSL/crypto.py#L428-L442", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:pyca-pyopenssl:_EllipticCurve.from_nid-ab50aa29c5@held-out", "question": "Instantiate a new :py:class:`_EllipticCurve` associated with the given\n OpenSSL NID.\n\n :param lib: The OpenSSL library binding object.\n\n :param nid: The OpenSSL NID the resulting curve object will represent.\n This must be a curve NID (and not, for example, a hash NID) or\n subsequent operations will fail in unpredictable ways.\n :type nid: :py:class:`int`\n\n :return: The curve object.", "scope": {"holder": "pyca-pyopenssl", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/pyca/pyopenssl/blob/1fbe064c50fd030948141d7d630673761525b0d0/src/OpenSSL/crypto.py#L464-L472", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:pyca-pyopenssl:_EllipticCurve._to_EC_KEY-1807d68c9f@held-out", "question": "Create a new OpenSSL EC_KEY structure initialized to use this curve.\n\n The structure is automatically garbage collected when the Python object\n is garbage collected.", "scope": {"holder": "pyca-pyopenssl", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/pyca/pyopenssl/blob/1fbe064c50fd030948141d7d630673761525b0d0/src/OpenSSL/crypto.py#L965-L986", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:pyca-pyopenssl:X509Req.add_extensions-35e00fe7d3@held-out", "question": "Add extensions to the certificate signing request.\n\n :param extensions: The X.509 extensions to add.\n :type extensions: iterable of :py:class:`X509Extension`\n :return: ``None``", "scope": {"holder": "pyca-pyopenssl", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/pyca/pyopenssl/blob/1fbe064c50fd030948141d7d630673761525b0d0/src/OpenSSL/crypto.py#L1029-L1048", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:pyca-pyopenssl:X509Req.verify-1c89a5f66f@held-out", "question": "Verifies the signature on this certificate signing request.\n\n :param PKey key: A public key.\n\n :return: ``True`` if the signature is correct.\n :rtype: bool\n\n :raises OpenSSL.crypto.Error: If the signature is invalid or there is a\n problem verifying the signature.", "scope": {"holder": "pyca-pyopenssl", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/pyca/pyopenssl/blob/1fbe064c50fd030948141d7d630673761525b0d0/src/OpenSSL/crypto.py#L1410-L1424", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:pyca-pyopenssl:X509.get_issuer-90b90a5e94@held-out", "question": "Return the issuer of this certificate.\n\n This creates a new :class:`X509Name` that wraps the underlying issuer\n name field on the certificate. Modifying it will modify the underlying\n certificate, and will have the effect of modifying any other\n :class:`X509Name` that refers to this issuer.\n\n :return: The issuer of this certificate.\n :rtype: :class:`X509Name`", "scope": {"holder": "pyca-pyopenssl", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/pyca/pyopenssl/blob/1fbe064c50fd030948141d7d630673761525b0d0/src/OpenSSL/crypto.py#L1438-L1452", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:pyca-pyopenssl:X509.get_subject-e2e7a1bb1c@held-out", "question": "Return the subject of this certificate.\n\n This creates a new :class:`X509Name` that wraps the underlying subject\n name field on the certificate. Modifying it will modify the underlying\n certificate, and will have the effect of modifying any other\n :class:`X509Name` that refers to this subject.\n\n :return: The subject of this certificate.\n :rtype: :class:`X509Name`", "scope": {"holder": "pyca-pyopenssl", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/pyca/pyopenssl/blob/1fbe064c50fd030948141d7d630673761525b0d0/src/OpenSSL/crypto.py#L1693-L1704", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:pyca-pyopenssl:X509StoreContext._init-7abe9c9aa0@held-out", "question": "Set up the store context for a subsequent verification operation.\n\n Calling this method more than once without first calling\n :meth:`_cleanup` will leak memory.", "scope": {"holder": "pyca-pyopenssl", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/pyca/pyopenssl/blob/1fbe064c50fd030948141d7d630673761525b0d0/src/OpenSSL/crypto.py#L1746-L1766", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:pyca-pyopenssl:X509StoreContext.verify_certificate-db16717f52@held-out", "question": "Verify a certificate in a context.\n\n .. versionadded:: 0.15\n\n :raises X509StoreContextError: If an error occurred when validating a\n certificate in the context. Sets ``certificate`` attribute to\n indicate which certificate caused the error.", "scope": {"holder": "pyca-pyopenssl", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/pyca/pyopenssl/blob/1fbe064c50fd030948141d7d630673761525b0d0/src/OpenSSL/crypto.py#L2219-L2242", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:pyca-pyopenssl:CRL.sign-e18ae55bc9@held-out", "question": "Sign the CRL.\n\n Signing a CRL enables clients to associate the CRL itself with an\n issuer. Before a CRL is meaningful to other OpenSSL functions, it must\n be signed by an issuer.\n\n This method implicitly sets the issuer's name based on the issuer\n certificate and private key used to sign the CRL.\n\n .. versionadded:: 16.1.0\n\n :param X509 issuer_cert: The issuer's certificate.\n :param PKey issuer_key: The issuer's private key.\n :param bytes digest: The digest method to sign the CRL with.", "scope": {"holder": "pyca-pyopenssl", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/pyca/pyopenssl/blob/1fbe064c50fd030948141d7d630673761525b0d0/src/OpenSSL/crypto.py#L2408-L2427", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:pyca-pyopenssl:PKCS12.set_ca_certificates-c64e6ca58e@held-out", "question": "Replace or set the CA certificates within the PKCS12 object.\n\n :param cacerts: The new CA certificates, or :py:const:`None` to unset\n them.\n :type cacerts: An iterable of :py:class:`X509` or :py:const:`None`\n\n :return: ``None``", "scope": {"holder": "pyca-pyopenssl", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/pyca/pyopenssl/blob/1fbe064c50fd030948141d7d630673761525b0d0/src/OpenSSL/crypto.py#L2595-L2603", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:pyca-pyopenssl:NetscapeSPKI.set_pubkey-9cadee8c26@held-out", "question": "Set the public key of the certificate\n\n :param pkey: The public key\n :return: ``None``", "scope": {"holder": "pyca-pyopenssl", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/pyca/pyopenssl/blob/1fbe064c50fd030948141d7d630673761525b0d0/src/OpenSSL/_util.py#L34-L54", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:pyca-pyopenssl:exception_from_error_queue-c35b601784@held-out", "question": "Convert an OpenSSL library failure into a Python exception.\n\n When a call to the native OpenSSL library fails, this is usually signalled\n by the return value, and an error code is stored in an error queue\n associated with the current thread. The err library provides functions to\n obtain these error codes and textual error messages.", "scope": {"holder": "pyca-pyopenssl", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/ralphbean/bugwarrior/blob/b2a5108f7b40cb0c437509b64eaa28f941f7ac8b/bugwarrior/services/github.py#L26-L32", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:ralphbean-bugwarrior:GithubClient._api_url-42465d4eb3@held-out", "question": "Build the full url to the API endpoint", "scope": {"holder": "ralphbean-bugwarrior", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/ralphbean/bugwarrior/blob/b2a5108f7b40cb0c437509b64eaa28f941f7ac8b/bugwarrior/services/github.py#L107-L120", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:ralphbean-bugwarrior:GithubClient._link_field_to_dict-d00562b24e@held-out", "question": "Utility for ripping apart github's Link header field.\n It's kind of ugly.", "scope": {"holder": "ralphbean-bugwarrior", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/ralphbean/bugwarrior/blob/b2a5108f7b40cb0c437509b64eaa28f941f7ac8b/bugwarrior/config.py#L98-L108", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:ralphbean-bugwarrior:oracle_eval-60a5651db7@held-out", "question": "Retrieve password from the given command", "scope": {"holder": "ralphbean-bugwarrior", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/ralphbean/bugwarrior/blob/b2a5108f7b40cb0c437509b64eaa28f941f7ac8b/bugwarrior/config.py#L272-L282", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:ralphbean-bugwarrior:BugwarriorConfigParser.getint-a3e5ca419b@held-out", "question": "Accepts both integers and empty values.", "scope": {"holder": "ralphbean-bugwarrior", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/ralphbean/bugwarrior/blob/b2a5108f7b40cb0c437509b64eaa28f941f7ac8b/bugwarrior/services/bitbucket.py#L142-L144", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:ralphbean-bugwarrior:BitbucketService.get_data-05d0551e98@held-out", "question": "Perform a request to the fully qualified url and return json.", "scope": {"holder": "ralphbean-bugwarrior", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/zqfang/GSEApy/blob/673e9ec1391e3b14d3e8a4353117151fd2cb9345/gseapy/utils.py#L63-L69", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:zqfang-GSEApy:log_stop-a0ffb3384a@held-out", "question": "log stop", "scope": {"holder": "zqfang-GSEApy", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/zqfang/GSEApy/blob/673e9ec1391e3b14d3e8a4353117151fd2cb9345/gseapy/parser.py#L33-L62", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:zqfang-GSEApy:gsea_edb_parser-bbe5e013f1@held-out", "question": "Parse results.edb file stored under **edb** file folder.\n\n :param results_path: the .results file located inside edb folder.\n :param index: gene_set index of gmt database, used for iterating items.\n :return: enrichment_term, hit_index,nes, pval, fdr.", "scope": {"holder": "zqfang-GSEApy", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/zqfang/GSEApy/blob/673e9ec1391e3b14d3e8a4353117151fd2cb9345/gseapy/parser.py#L65-L146", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:zqfang-GSEApy:gsea_gmt_parser-8a25e74e65@held-out", "question": "Parse gene_sets.gmt(gene set database) file or download from enrichr server.\n\n :param gmt: the gene_sets.gmt file of GSEA input or an enrichr library name.\n checkout full enrichr library name here: http://amp.pharm.mssm.edu/Enrichr/#stats\n\n :param min_size: Minimum allowed number of genes from gene set also the data set. Default: 3.\n :param max_size: Maximum allowed number of genes from gene set also the data set. Default: 5000.\n :param gene_list: Used for filtering gene set. Only used this argument for :func:`call` method.\n :return: Return a new filtered gene set database dictionary.\n\n **DO NOT** filter gene sets, when use :func:`replot`. Because ``GSEA`` Desktop have already\n done this for you.", "scope": {"holder": "zqfang-GSEApy", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/zqfang/GSEApy/blob/673e9ec1391e3b14d3e8a4353117151fd2cb9345/gseapy/parser.py#L225-L229", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:zqfang-GSEApy:Biomart.get_attributes-1021ee17e7@held-out", "question": "Get available attritbutes from dataset you've selected", "scope": {"holder": "zqfang-GSEApy", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/zqfang/GSEApy/blob/673e9ec1391e3b14d3e8a4353117151fd2cb9345/gseapy/parser.py#L231-L235", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:zqfang-GSEApy:Biomart.get_filters-0080468e70@held-out", "question": "Get available filters from dataset you've selected", "scope": {"holder": "zqfang-GSEApy", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/zqfang/GSEApy/blob/673e9ec1391e3b14d3e8a4353117151fd2cb9345/gseapy/parser.py#L237-L295", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:zqfang-GSEApy:Biomart.query-5aea7cc5d2@held-out", "question": "mapping ids using BioMart. \n\n :param dataset: str, default: 'hsapiens_gene_ensembl'\n :param attributes: str, list, tuple\n :param filters: dict, {'filter name': list(filter value)}\n :param host: www.ensembl.org, asia.ensembl.org, useast.ensembl.org\n :return: a dataframe contains all attributes you selected.\n\n **Note**: it will take a couple of minutes to get the results.\n A xml template for querying biomart. (see https://gist.github.com/keithshep/7776579)\n \n exampleTaxonomy = \"mmusculus_gene_ensembl\"\n exampleGene = \"ENSMUSG00000086981,ENSMUSG00000086982,ENSMUSG00000086983\"\n urlTemplate = \\\n '''http://ensembl.org/biomart/martservice?query=''' \\\n '''<?xml version=\"1.0\" encoding=\"UTF-8\"?>''' \\\n '''<!DOCTYPE Query>''' \\\n '''<Query virtualSchemaName=\"default\" formatter=\"CSV\" header=\"0\" uniqueRows=\"0\" count=\"\" datasetConfigVersion=\"0.6\">''' \\\n '''<Dataset name=\"%s\" interface=\"default\"><Filter name=\"ensembl_gene_id\" value=\"%s\"/>''' \\\n '''<Attribute name=\"ensembl_gene_id\"/><Attribute name=\"ensembl_transcript_id\"/>''' \\\n '''<Attribute name=\"transcript_start\"/><Attribute name=\"transcript_end\"/>''' \\\n '''<Attribute name=\"exon_chrom_start\"/><Attribute name=\"exon_chrom_end\"/>''' \\\n '''</Dataset>''' \\\n '''</Query>''' \n \n exampleURL = urlTemplate % (exampleTaxonomy, exampleGene)\n req = requests.get(exampleURL, stream=True)", "scope": {"holder": "zqfang-GSEApy", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/zqfang/GSEApy/blob/673e9ec1391e3b14d3e8a4353117151fd2cb9345/gseapy/gsea.py#L991-L1031", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:zqfang-GSEApy:prerank-9ec1c31d75@held-out", "question": "Run Gene Set Enrichment Analysis with pre-ranked correlation defined by user.\n\n :param rnk: pre-ranked correlation table or pandas DataFrame. Same input with ``GSEA`` .rnk file.\n :param gene_sets: Enrichr Library name or .gmt gene sets file or dict of gene sets. Same input with GSEA.\n :param outdir: results output directory.\n :param int permutation_num: Number of permutations for significance computation. Default: 1000.\n :param int min_size: Minimum allowed number of genes from gene set also the data set. Default: 15.\n :param int max_size: Maximum allowed number of genes from gene set also the data set. Defaults: 500.\n :param str weighted_score_type: Refer to :func:`algorithm.enrichment_score`. Default:1.\n :param bool ascending: Sorting order of rankings. Default: False.\n :param int processes: Number of Processes you are going to use. Default: 1.\n :param list figsize: Matplotlib figsize, accept a tuple or list, e.g. [width,height]. Default: [6.5,6].\n :param str format: Matplotlib figure format. Default: 'pdf'.\n :param int graph_num: Plot graphs for top sets of each phenotype.\n :param bool no_plot: If equals to True, no figure will be drawn. Default: False.\n :param seed: Random seed. expect an integer. Default:None.\n :param bool verbose: Bool, increase output verbosity, print out progress of your job, Default: False.\n\n :return: Return a Prerank obj. All results store to a dictionary, obj.results,\n where contains::\n\n | {es: enrichment score,\n | nes: normalized enrichment score,\n | p: P-value,\n | fdr: FDR,\n | size: gene set size,\n | matched_size: genes matched to the data,\n | genes: gene names from the data set\n | ledge_genes: leading edge genes}", "scope": {"holder": "zqfang-GSEApy", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/zqfang/GSEApy/blob/673e9ec1391e3b14d3e8a4353117151fd2cb9345/gseapy/gsea.py#L34-L54", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:zqfang-GSEApy:GSEAbase.prepare_outdir-bcd53f6c9e@held-out", "question": "create temp directory.", "scope": {"holder": "zqfang-GSEApy", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/zqfang/GSEApy/blob/673e9ec1391e3b14d3e8a4353117151fd2cb9345/gseapy/gsea.py#L206-L216", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:zqfang-GSEApy:GSEAbase._heatmat-9a49e94cd3@held-out", "question": "only use for gsea heatmap", "scope": {"holder": "zqfang-GSEApy", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/zqfang/GSEApy/blob/673e9ec1391e3b14d3e8a4353117151fd2cb9345/gseapy/enrichr.py#L154-L170", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:zqfang-GSEApy:Enrichr.get_results-00cf90fae3@held-out", "question": "Enrichr API", "scope": {"holder": "zqfang-GSEApy", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/zqfang/GSEApy/blob/673e9ec1391e3b14d3e8a4353117151fd2cb9345/gseapy/enrichr.py#L186-L217", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:zqfang-GSEApy:Enrichr.get_background-42a2a83860@held-out", "question": "get background gene", "scope": {"holder": "zqfang-GSEApy", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/zqfang/GSEApy/blob/673e9ec1391e3b14d3e8a4353117151fd2cb9345/gseapy/enrichr.py#L302-L352", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:zqfang-GSEApy:Enrichr.run-5e89d01cbe@held-out", "question": "run enrichr for one sample gene list but multi-libraries", "scope": {"holder": "zqfang-GSEApy", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/3DLIRIOUS/MeshLabXML/blob/177cce21e92baca500f56a932d66bd9a33257af8/meshlabxml/create.py#L259-L318", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:3DLIRIOUS-MeshLabXML:grid-b6a6c531c1@held-out", "question": "2D square/plane/grid created on XY plane\n\n x_segments # Number of segments in the X direction.\n y_segments # Number of segments in the Y direction.\n center=\"false\" # If true square will be centered on origin;\n otherwise it is place in the positive XY quadrant.", "scope": {"holder": "3DLIRIOUS-MeshLabXML", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/3DLIRIOUS/MeshLabXML/blob/177cce21e92baca500f56a932d66bd9a33257af8/meshlabxml/create.py#L510-L583", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:3DLIRIOUS-MeshLabXML:plane_hires_edges-9edfbd8cb7@held-out", "question": "Creates a plane with a specified number of vertices\n on it sides, but no vertices on the interior.\n\n Currently used to create a simpler bottom for cube_hires.", "scope": {"holder": "3DLIRIOUS-MeshLabXML", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/3DLIRIOUS/MeshLabXML/blob/177cce21e92baca500f56a932d66bd9a33257af8/meshlabxml/create.py#L651-L685", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:3DLIRIOUS-MeshLabXML:annulus_hires-55e141ce50@held-out", "question": "Create a cylinder with user defined number of segments", "scope": {"holder": "3DLIRIOUS-MeshLabXML", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/3DLIRIOUS/MeshLabXML/blob/177cce21e92baca500f56a932d66bd9a33257af8/meshlabxml/subdivide.py#L67-L136", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:3DLIRIOUS-MeshLabXML:ls3loop-92f3cd7d27@held-out", "question": "Apply LS3 Subdivision Surface algorithm using Loop's weights.\n\n This refinement method take normals into account.\n See: Boye', S. Guennebaud, G. & Schlick, C.\n \"Least squares subdivision surfaces\"\n Computer Graphics Forum, 2010.\n\n Alternatives weighting schemes are based on the paper:\n Barthe, L. & Kobbelt, L.\n \"Subdivision scheme tuning around extraordinary vertices\"\n Computer Aided Geometric Design, 2004, 21, 561-583.\n\n The current implementation of these schemes don't handle vertices of\n valence > 12\n\n Args:\n script: the FilterScript object or script filename to write\n the filter to.\n iterations (int): Number of times the model is subdivided.\n loop_weight (int): Change the weights used. Allow to optimize some\n behaviours in spite of others. Valid values are:\n 0 - Loop (default)\n 1 - Enhance regularity\n 2 - Enhance continuity\n edge_threshold (float): All the edges longer than this threshold will\n be refined. Setting this value to zero will force a uniform\n refinement.\n selected (bool): If selected the filter is performed only on the\n selected faces.\n\n Layer stack:\n No impacts\n\n MeshLab versions:\n 2016.12\n 1.3.4BETA", "scope": {"holder": "3DLIRIOUS-MeshLabXML", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/3DLIRIOUS/MeshLabXML/blob/177cce21e92baca500f56a932d66bd9a33257af8/meshlabxml/transform.py#L596-L621", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:3DLIRIOUS-MeshLabXML:curl_rim-36646e6f61@held-out", "question": "flare_radius must be >= z2 (height)\n r2 max = flare_radius + r\n \n r2 (num): radius of mesh at end of flare\n \n +15 r= 8.8205\n -15 r= 1.1795\n \n z=10, 5 +/-15 - +/-15*0.74535599249992989880305788957709", "scope": {"holder": "3DLIRIOUS-MeshLabXML", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/3DLIRIOUS/MeshLabXML/blob/177cce21e92baca500f56a932d66bd9a33257af8/meshlabxml/transfer.py#L116-L193", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:3DLIRIOUS-MeshLabXML:vert_attr_2_meshes-745bbbcb0d@held-out", "question": "Vertex Attribute Transfer (between 2 meshes)\n\n Transfer the chosen per-vertex attributes from one mesh to another. Useful to transfer attributes to different representations of the same object. For each vertex of the target mesh the closest point (not vertex!) on the source mesh is computed, and the requested interpolated attributes from that source point are copied into the target vertex.\n\n The algorithm assumes that the two meshes are reasonably similar and aligned.\n\n UpperBound: absolute value (not percentage)\n\n Args:\n script: the FilterScript object or script filename to write\n the filter to.\n source_mesh (int): The mesh that contains the source data that we want to transfer\n target_mesh (int): The mesh whose vertexes will receive the data from the source\n geometry (bool): If enabled, the position of each vertex of the target mesh will be snapped onto the corresponding closest point on the source mesh\n normal (bool): If enabled, the normal of each vertex of the target mesh will get the (interpolated) normal of the corresponding closest point on the source mesh\n color (bool): If enabled, the color of each vertex of the target mesh will become the color of the corresponding closest point on the source mesh\n quality (bool): If enabled, the quality of each vertex of the target mesh will become the quality of the corresponding closest point on the source mesh\n selection (bool): If enabled, each vertex of the target mesh will be selected if the corresponding closest point on the source mesh falls in a selected face\n quality_distance (bool): If enabled, we store the distance of the transferred value as in the vertex quality\n max_distance (float): Sample points for which we do not find anything within this distance are rejected and not considered for recovering attributes", "scope": {"holder": "3DLIRIOUS-MeshLabXML", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/3DLIRIOUS/MeshLabXML/blob/177cce21e92baca500f56a932d66bd9a33257af8/meshlabxml/transfer.py#L196-L289", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:3DLIRIOUS-MeshLabXML:vert_attr2tex_2_meshes-cc3e65afc9@held-out", "question": "Transfer Vertex Attributes to Texture (between 2 meshes)\n\n Args:\n script: the FilterScript object or script filename to write\n the filter to.\n source_mesh (int): The mesh that contains the source data that we want to transfer\n target_mesh (int): The mesh whose texture will be filled according to source mesh data\n attribute (int): Choose what attribute has to be transferred onto the target texture. You can choose between Per vertex attributes (color, normal, quality) or to transfer color information from source mesh texture\n max_distance (float): Sample points for which we do not find anything within this distance are rejected and not considered for recovering data\n tex_name (str): The texture file to be created\n tex_width (int): The texture width\n tex_height (int): The texture height\n overwrite_tex (bool): If target mesh has a texture will be overwritten (with provided texture dimension)\n assign_tex (bool): Assign the newly created texture to target mesh\n fill_tex (bool): If enabled the unmapped texture space is colored using a pull push filling algorithm, if false is set to black\n\n Layer stack:\n No impacts\n\n MeshLab versions:\n 2016.12\n 1.3.4BETA", "scope": {"holder": "3DLIRIOUS-MeshLabXML", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/3DLIRIOUS/MeshLabXML/blob/177cce21e92baca500f56a932d66bd9a33257af8/meshlabxml/remesh.py#L489-L524", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:3DLIRIOUS-MeshLabXML:voronoi-8b5c819edd@held-out", "question": "Turn a model into a surface with Voronoi style holes in it\n\n References:\n http://meshlabstuff.blogspot.com/2009/03/creating-voronoi-sphere.html\n http://meshlabstuff.blogspot.com/2009/04/creating-voronoi-sphere-2.html\n\n Requires FilterScript object\n\n Args:\n script: the FilterScript object to write the filter to. Does not\n work with a script filename.\n\n Layer stack:\n No impacts\n\n MeshLab versions:\n 2016.12\n 1.3.4BETA", "scope": {"holder": "3DLIRIOUS-MeshLabXML", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/3DLIRIOUS/MeshLabXML/blob/177cce21e92baca500f56a932d66bd9a33257af8/meshlabxml/mlx.py#L572-L620", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:3DLIRIOUS-MeshLabXML:default_output_mask-6e39b41cb9@held-out", "question": "Set default output mask options based on file extension\n Note: v1.34BETA changed -om switch to -m\n Possible options (not all options are available for every format):\n vc -> vertex colors\n vf -> vertex flags\n vq -> vertex quality\n vn -> vertex normals\n vt -> vertex texture coords\n fc -> face colors\n ff -> face flags\n fq -> face quality\n fn -> face normals\n wc -> wedge colors\n wn -> wedge normals\n wt -> wedge texture coords", "scope": {"holder": "3DLIRIOUS-MeshLabXML", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/3DLIRIOUS/MeshLabXML/blob/177cce21e92baca500f56a932d66bd9a33257af8/meshlabxml/delete.py#L53-L74", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:3DLIRIOUS-MeshLabXML:small_parts-1180f56c4b@held-out", "question": "Select & delete the small disconnected parts (components) of a mesh.\n\n Args:\n script: the FilterScript object or script filename to write\n the filter to.\n ratio (float): This ratio (between 0 and 1) defines the meaning of\n 'small' as the threshold ratio between the number of faces of the\n largest component and the other ones. A larger value will select\n more components.\n non_closed_only (bool): Select only non-closed components.\n\n Layer stack:\n No impacts\n\n MeshLab versions:\n 2016.12\n 1.3.4BETA", "scope": {"holder": "3DLIRIOUS-MeshLabXML", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/3DLIRIOUS/MeshLabXML/blob/177cce21e92baca500f56a932d66bd9a33257af8/meshlabxml/texture.py#L261-L336", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:3DLIRIOUS-MeshLabXML:project_rasters-4bb7147542@held-out", "question": "Set texture\n\n Creates new texture file\n tex_file_out = must be png\n fill_atlas_gaps = setting this to false will leave the unprojected area transparent. This can then be easily composed with the original texture with PIL", "scope": {"holder": "3DLIRIOUS-MeshLabXML", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/3DLIRIOUS/MeshLabXML/blob/177cce21e92baca500f56a932d66bd9a33257af8/meshlabxml/vert_color.py#L129-L212", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:3DLIRIOUS-MeshLabXML:cyclic_rainbow-a1601182a2@held-out", "question": "Color mesh vertices in a repeating sinusiodal rainbow pattern\n\n Sine wave follows the following equation for each color channel (RGBA):\n channel = sin(freq*increment + phase)*amplitude + center\n\n Args:\n script: the FilterScript object or script filename to write\n the filter to.\n direction (str) = the direction that the sine wave will travel; this\n and the start_pt determine the 'increment' of the sine function.\n Valid values are:\n 'sphere' - radiate sine wave outward from start_pt (default)\n 'x' - sine wave travels along the X axis\n 'y' - sine wave travels along the Y axis\n 'z' - sine wave travels along the Z axis\n or define the increment directly using a muparser function, e.g.\n '2x + y'. In this case start_pt will not be used; include it in\n the function directly.\n start_pt (3 coordinate tuple or list): start point of the sine wave. For a\n sphere this is the center of the sphere.\n amplitude (float [0, 255], single value or 4 term tuple or list): amplitude\n of the sine wave, with range between 0-255. If a single value is\n specified it will be used for all channels, otherwise specify each\n channel individually.\n center (float [0, 255], single value or 4 term tuple or list): center\n of the sine wave, with range between 0-255. If a single value is\n specified it will be used for all channels, otherwise specify each\n channel individually.\n freq (float, single value or 4 term tuple or list): frequency of the sine\n wave. If a single value is specified it will be used for all channels,\n otherwise specifiy each channel individually.\n phase (float [0, 360], single value or 4 term tuple or list): phase\n of the sine wave in degrees, with range between 0-360. If a single\n value is specified it will be used for all channels, otherwise specify\n each channel individually.\n alpha (bool): if False the alpha channel will be set to 255 (full opacity).\n\n Layer stack:\n No impacts\n\n MeshLab versions:\n 2016.12\n 1.3.4BETA", "scope": {"holder": "3DLIRIOUS-MeshLabXML", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/3DLIRIOUS/MeshLabXML/blob/177cce21e92baca500f56a932d66bd9a33257af8/meshlabxml/mp_func.py#L165-L170", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:3DLIRIOUS-MeshLabXML:v_multiply-95d30e0dc1@held-out", "question": "Multiply vector by scalar", "scope": {"holder": "3DLIRIOUS-MeshLabXML", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/3DLIRIOUS/MeshLabXML/blob/177cce21e92baca500f56a932d66bd9a33257af8/meshlabxml/files.py#L114-L149", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:3DLIRIOUS-MeshLabXML:measure_section-501ad11867@held-out", "question": "Measure a cross section of a mesh\n \n Perform a plane cut in one of the major axes (X, Y, Z). If you want to cut on\n a different plane you will need to rotate the model in place, perform the cut,\n and rotate it back.\n \n Args:\n fbasename (str): filename of input model\n log (str): filename of log file\n axis (str): axis perpendicular to the cutting plane, e.g. specify \"z\" to cut\n parallel to the XY plane.\n offset (float): amount to offset the cutting plane from the origin\n rotate_x_angle (float): degrees to rotate about the X axis. Useful for correcting \"Up\" direction: 90 to rotate Y to Z, and -90 to rotate Z to Y. \n\n Returns:\n dict: dictionary with the following keys for the aabb of the section:\n min (list): list of the x, y & z minimum values\n max (list): list of the x, y & z maximum values\n center (list): the x, y & z coordinates of the center of the aabb\n size (list): list of the x, y & z sizes (max - min)\n diagonal (float): the diagonal of the aabb", "scope": {"holder": "3DLIRIOUS-MeshLabXML", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/3DLIRIOUS/MeshLabXML/blob/177cce21e92baca500f56a932d66bd9a33257af8/meshlabxml/files.py#L152-L190", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:3DLIRIOUS-MeshLabXML:polylinesort-362228ed38@held-out", "question": "Sort separate line segments in obj format into a continuous polyline or polylines.\n NOT FINISHED; DO NOT USE\n\n Also measures the length of each polyline\n\n Return polyline and polylineMeta (lengths)", "scope": {"holder": "3DLIRIOUS-MeshLabXML", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/maxcountryman/flask-uploads/blob/dc24fa0c53d605876e5b4502cadffdf1a4345b1d/flask_uploads.py#L88-L106", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:maxcountryman-flask-uploads:lowercase_ext-51575ed0cf@held-out", "question": "This is a helper used by UploadSet.save to provide lowercase extensions for\n all processed files, to compare with configured extensions in the same\n case.\n\n .. versionchanged:: 0.1.4\n Filenames without extensions are no longer lowercased, only the\n extension is returned in lowercase, if an extension exists.\n\n :param filename: The filename to ensure has a lowercase extension.", "scope": {"holder": "maxcountryman-flask-uploads", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/maxcountryman/flask-uploads/blob/dc24fa0c53d605876e5b4502cadffdf1a4345b1d/flask_uploads.py#L115-L149", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:maxcountryman-flask-uploads:patch_request_class-abe77ee2bd@held-out", "question": "By default, Flask will accept uploads to an arbitrary size. While Werkzeug\n switches uploads from memory to a temporary file when they hit 500 KiB,\n it's still possible for someone to overload your disk space with a\n gigantic file.\n\n This patches the app's request class's\n `~werkzeug.BaseRequest.max_content_length` attribute so that any upload\n larger than the given size is rejected with an HTTP error.\n\n .. note::\n\n In Flask 0.6, you can do this by setting the `MAX_CONTENT_LENGTH`\n setting, without patching the request class. To emulate this behavior,\n you can pass `None` as the size (you must pass it explicitly). That is\n the best way to call this function, as it won't break the Flask 0.6\n functionality if it exists.\n\n .. versionchanged:: 0.1.1\n\n :param app: The app to patch the request class of.\n :param size: The maximum size to accept, in bytes. The default is 64 MiB.\n If it is `None`, the app's `MAX_CONTENT_LENGTH` configuration\n setting will be used to patch.", "scope": {"holder": "maxcountryman-flask-uploads", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/maxcountryman/flask-uploads/blob/dc24fa0c53d605876e5b4502cadffdf1a4345b1d/flask_uploads.py#L372-L381", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:maxcountryman-flask-uploads:UploadSet.extension_allowed-c74c7ff37e@held-out", "question": "This determines whether a specific extension is allowed. It is called\n by `file_allowed`, so if you override that but still want to check\n extensions, call back into this.\n\n :param ext: The extension to check, without the dot.", "scope": {"holder": "maxcountryman-flask-uploads", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/maxcountryman/flask-uploads/blob/dc24fa0c53d605876e5b4502cadffdf1a4345b1d/flask_uploads.py#L433-L452", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:maxcountryman-flask-uploads:UploadSet.resolve_conflict-829cc945e7@held-out", "question": "If a file with the selected name already exists in the target folder,\n this method is called to resolve the conflict. It should return a new\n basename for the file.\n\n The default implementation splits the name and extension and adds a\n suffix to the name consisting of an underscore and a number, and tries\n that until it finds one that doesn't exist.\n\n :param target_folder: The absolute path to the target.\n :param basename: The file's original basename.", "scope": {"holder": "maxcountryman-flask-uploads", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/nvdv/vprof/blob/4c3ff78f8920ab10cb9c00b14143452aa09ff6bb/vprof/memory_profiler.py#L128-L142", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:nvdv-vprof:_CodeEventsTracker.obj_overhead-84fe17abc1@held-out", "question": "Returns all objects that are considered a profiler overhead.\n Objects are hardcoded for convenience.", "scope": {"holder": "nvdv-vprof", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/nvdv/vprof/blob/4c3ff78f8920ab10cb9c00b14143452aa09ff6bb/vprof/flame_graph.py#L75-L79", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:nvdv-vprof:_StatProfiler._fill_sample_count-d73691dec1@held-out", "question": "Counts and fills sample counts inside call tree.", "scope": {"holder": "nvdv-vprof", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/nvdv/vprof/blob/4c3ff78f8920ab10cb9c00b14143452aa09ff6bb/vprof/flame_graph.py#L169-L183", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:nvdv-vprof:FlameGraphProfiler.profile_function-d331397346@held-out", "question": "Runs statistical profiler on a function.", "scope": {"holder": "nvdv-vprof", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/nvdv/vprof/blob/4c3ff78f8920ab10cb9c00b14143452aa09ff6bb/vprof/profiler.py#L60-L78", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:nvdv-vprof:Profiler._profile_module-9ac6cf2cff@held-out", "question": "Runs cProfile on a module.", "scope": {"holder": "nvdv-vprof", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/nvdv/vprof/blob/4c3ff78f8920ab10cb9c00b14143452aa09ff6bb/examples/guestbook.py#L64-L68", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:nvdv-vprof:init_db-6aa6b7d2b2@held-out", "question": "Initializes DB.", "scope": {"holder": "nvdv-vprof", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/nvdv/vprof/blob/4c3ff78f8920ab10cb9c00b14143452aa09ff6bb/vprof/code_heatmap.py#L176-L188", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:nvdv-vprof:CodeHeatmapProfiler._format_heatmap-048bdcd11a@held-out", "question": "Formats heatmap for UI.", "scope": {"holder": "nvdv-vprof", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/lensacom/sparkit-learn/blob/0498502107c1f7dcf33cda0cdb6f5ba4b42524b7/splearn/preprocessing/data.py#L172-L180", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:lensacom-sparkit-learn:SparkStandardScaler.to_scikit-49335a044e@held-out", "question": "Convert to equivalent StandardScaler", "scope": {"holder": "lensacom-sparkit-learn", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/lensacom/sparkit-learn/blob/0498502107c1f7dcf33cda0cdb6f5ba4b42524b7/splearn/linear_model/base.py#L67-L88", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:lensacom-sparkit-learn:SparkLinearModelMixin._spark_fit-20cd471186@held-out", "question": "Wraps a Scikit-learn Linear model's fit method to use with RDD\n input.\n\n Parameters\n ----------\n cls : class object\n The sklearn linear model's class to wrap.\n Z : TupleRDD or DictRDD\n The distributed train data in a DictRDD.\n\n Returns\n -------\n self: the wrapped class", "scope": {"holder": "lensacom-sparkit-learn", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/lensacom/sparkit-learn/blob/0498502107c1f7dcf33cda0cdb6f5ba4b42524b7/splearn/linear_model/base.py#L90-L105", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:lensacom-sparkit-learn:SparkLinearModelMixin._spark_predict-b7b0848311@held-out", "question": "Wraps a Scikit-learn Linear model's predict method to use with RDD\n input.\n\n Parameters\n ----------\n cls : class object\n The sklearn linear model's class to wrap.\n Z : ArrayRDD\n The distributed data to predict in a DictRDD.\n\n Returns\n -------\n self: the wrapped class", "scope": {"holder": "lensacom-sparkit-learn", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/lensacom/sparkit-learn/blob/0498502107c1f7dcf33cda0cdb6f5ba4b42524b7/splearn/linear_model/base.py#L143-L158", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:lensacom-sparkit-learn:SparkLinearRegression.fit-2557ab5163@held-out", "question": "Fit linear model.\n\n Parameters\n ----------\n Z : DictRDD with (X, y) values\n X containing numpy array or sparse matrix - The training data\n y containing the target values\n\n Returns\n -------\n self : returns an instance of self.", "scope": {"holder": "lensacom-sparkit-learn", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/lensacom/sparkit-learn/blob/0498502107c1f7dcf33cda0cdb6f5ba4b42524b7/splearn/pipeline.py#L115-L123", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:lensacom-sparkit-learn:SparkPipeline.fit_transform-4a1d256043@held-out", "question": "Fit all the transforms one after the other and transform the\n data, then use fit_transform on transformed data using the final\n estimator.", "scope": {"holder": "lensacom-sparkit-learn", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/lensacom/sparkit-learn/blob/0498502107c1f7dcf33cda0cdb6f5ba4b42524b7/splearn/cross_validation.py#L29-L35", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:lensacom-sparkit-learn:_score-1f5876f2ef@held-out", "question": "Compute the score of an estimator on a given test set.", "scope": {"holder": "lensacom-sparkit-learn", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/lensacom/sparkit-learn/blob/0498502107c1f7dcf33cda0cdb6f5ba4b42524b7/splearn/feature_extraction/dict_vectorizer.py#L76-L124", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:lensacom-sparkit-learn:SparkDictVectorizer.fit-2f6b7aad22@held-out", "question": "Learn a list of feature name -> indices mappings.\n\n Parameters\n ----------\n Z : DictRDD with column 'X'\n Dict(s) or Mapping(s) from feature names (arbitrary Python\n objects) to feature values (strings or convertible to dtype).\n\n Returns\n -------\n self", "scope": {"holder": "lensacom-sparkit-learn", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/lensacom/sparkit-learn/blob/0498502107c1f7dcf33cda0cdb6f5ba4b42524b7/splearn/feature_extraction/dict_vectorizer.py#L126-L147", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:lensacom-sparkit-learn:SparkDictVectorizer.transform-fc28a4d08b@held-out", "question": "Transform ArrayRDD's (or DictRDD's 'X' column's) feature->value dicts\n to array or sparse matrix.\n Named features not encountered during fit or fit_transform will be\n silently ignored.\n\n Parameters\n ----------\n Z : ArrayRDD or DictRDD with column 'X' containing Mapping or\n iterable over Mappings, length = n_samples\n Dict(s) or Mapping(s) from feature names (arbitrary Python\n objects) to feature values (strings or convertible to dtype).\n\n Returns\n -------\n Z : transformed, containing {array, sparse matrix}\n Feature vectors; always 2-d.", "scope": {"holder": "lensacom-sparkit-learn", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/lensacom/sparkit-learn/blob/0498502107c1f7dcf33cda0cdb6f5ba4b42524b7/splearn/decomposition/truncated_svd.py#L55-L170", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:lensacom-sparkit-learn:svd_em-37f4787fef@held-out", "question": "Calculate the SVD of a blocked RDD using an expectation maximization\n algorithm (from Roweis, NIPS, 1997) that avoids explicitly\n computing the covariance matrix, returning only the leading k\n singular vectors. Assumes n rows and d columns, does not require\n d^2 to fit into memory on a single machine.\n Parameters\n ----------\n blocked_rdd : ArrayRDD\n ArrayRDD with data points in numpy array blocks\n k : Int\n Number of singular vectors to return\n maxiter : Int, optional, default = 20\n Number of iterations to perform\n tol : Double, optional, default = 1e-5\n Tolerance for stopping iterative updates\n seed : Int, optional, default = None\n Seed for random number generator for initializing subspace\n Returns\n ----------\n u : RDD of blocks\n Left eigenvectors\n s : numpy array\n Singular values\n v : numpy array\n Right eigenvectors", "scope": {"holder": "lensacom-sparkit-learn", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/lensacom/sparkit-learn/blob/0498502107c1f7dcf33cda0cdb6f5ba4b42524b7/splearn/rdd.py#L35-L47", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:lensacom-sparkit-learn:_block_collection-4d09e6a7b2@held-out", "question": "Pack rdd with a specific collection constructor.", "scope": {"holder": "lensacom-sparkit-learn", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/lensacom/sparkit-learn/blob/0498502107c1f7dcf33cda0cdb6f5ba4b42524b7/splearn/rdd.py#L72-L111", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:lensacom-sparkit-learn:block-6808bcce8f@held-out", "question": "Block an RDD\n\n Parameters\n ----------\n\n rdd : RDD\n RDD of data points to block into either numpy arrays,\n scipy sparse matrices, or pandas data frames.\n Type of data point will be automatically inferred\n and blocked accordingly.\n\n bsize : int, optional, default None\n Size of each block (number of elements), if None all data points\n from each partition will be combined in a block.\n\n Returns\n -------\n\n rdd : ArrayRDD or TupleRDD or DictRDD\n The transformed rdd with added functionality", "scope": {"holder": "lensacom-sparkit-learn", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/lensacom/sparkit-learn/blob/0498502107c1f7dcf33cda0cdb6f5ba4b42524b7/splearn/rdd.py#L132-L148", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:lensacom-sparkit-learn:BlockRDD._block-a2c085d014@held-out", "question": "Execute the blocking process on the given rdd.\n\n Parameters\n ----------\n rdd : pyspark.rdd.RDD\n Distributed data to block\n bsize : int or None\n The desired size of the blocks\n\n Returns\n -------\n rdd : pyspark.rdd.RDD\n Blocked rdd.", "scope": {"holder": "lensacom-sparkit-learn", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/lensacom/sparkit-learn/blob/0498502107c1f7dcf33cda0cdb6f5ba4b42524b7/splearn/rdd.py#L257-L270", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:lensacom-sparkit-learn:BlockRDD.transform-e0b1a48dca@held-out", "question": "Equivalent to map, compatibility purpose only.\n Column parameter ignored.", "scope": {"holder": "lensacom-sparkit-learn", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/lensacom/sparkit-learn/blob/0498502107c1f7dcf33cda0cdb6f5ba4b42524b7/splearn/rdd.py#L625-L640", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:lensacom-sparkit-learn:DictRDD._block-271e213813@held-out", "question": "Execute the blocking process on the given rdd.\n\n Parameters\n ----------\n rdd : pyspark.rdd.RDD\n Distributed data to block\n bsize : int or None\n The desired size of the blocks\n\n Returns\n -------\n rdd : pyspark.rdd.RDD\n Blocked rdd.", "scope": {"holder": "lensacom-sparkit-learn", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Nekmo/amazon-dash/blob/0e2bdc24ff8ea32cecb2f5f54f5cc1c0f99c197b/amazon_dash/execute.py#L275-L283", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Nekmo-amazon-dash:ExecuteUrlServiceBase.get_headers-4a9b8b0b0e@held-out", "question": "Get HTTP Headers to send. By default default_headers\n\n :return: HTTP Headers\n :rtype: dict", "scope": {"holder": "Nekmo-amazon-dash", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Nekmo/amazon-dash/blob/0e2bdc24ff8ea32cecb2f5f54f5cc1c0f99c197b/amazon_dash/execute.py#L314-L325", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Nekmo-amazon-dash:ExecuteOwnApiBase.get_body-0950439d1d@held-out", "question": "Return \"data\" value on self.data\n\n :return: data to send\n :rtype: str", "scope": {"holder": "Nekmo-amazon-dash", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Nekmo/amazon-dash/blob/0e2bdc24ff8ea32cecb2f5f54f5cc1c0f99c197b/amazon_dash/listener.py#L95-L108", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Nekmo-amazon-dash:Device.send_confirmation-a7d486df7d@held-out", "question": "Send success or error message to configured confirmation\n\n :param str message: Body message to send\n :param bool success: Device executed successfully to personalize message\n :return: None", "scope": {"holder": "Nekmo-amazon-dash", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/google/pybadges/blob/d42c8080adb21b81123ac9540c53127ed2fa1edc/setup.py#L23-L39", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:google-pybadges:get_long_description-1936ad2616@held-out", "question": "Transform README.md into a usable long description.\n\n Replaces relative references to svg images to absolute https references.", "scope": {"holder": "google-pybadges", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/google/pybadges/blob/d42c8080adb21b81123ac9540c53127ed2fa1edc/pybadges/precalculated_text_measurer.py#L52-L59", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:google-pybadges:PrecalculatedTextMeasurer.text_width-ca824e0345@held-out", "question": "Returns the width, in pixels, of a string in DejaVu Sans 110pt.", "scope": {"holder": "google-pybadges", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/google/pybadges/blob/d42c8080adb21b81123ac9540c53127ed2fa1edc/pybadges/precalculate_text.py#L108-L139", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:google-pybadges:calculate_pair_to_kern_mapping-43ccaf45c7@held-out", "question": "Returns a mapping between each *pair* of characters and their kerning.\n\n Args:\n measurer: The TextMeasurer used to measure the width of each pair of\n characters.\n char_to_length: A mapping between characters and their length in pixels.\n Must contain every character in 'characters' e.g.\n {'h': 5.2, 'e': 4.0, 'l', 1.2, 'o': 5.0}.\n characters: The characters to generate the kerning mapping for e.g.\n 'hel'.\n\n Returns:\n A mapping between each pair of given characters\n (e.g. 'hh', he', hl', 'eh', 'ee', 'el', 'lh, 'le', 'll') and the kerning\n adjustment for that pair of characters i.e. the difference between the\n length of the two characters calculated using 'char_to_length' vs.\n the length calculated by `measurer`. Positive values indicate that the\n length is less than using the sum of 'char_to_length'. Zero values are\n excluded from the map e.g. {'hl': 3.1, 'ee': -0.5}.", "scope": {"holder": "google-pybadges", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/jterrace/pyssim/blob/ff9bd90c3eb7525013ad46babf66b7cc78391e89/ssim/utils.py#L11-L17", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:jterrace-pyssim:convolve_gaussian_2d-00a9375952@held-out", "question": "Convolve 2d gaussian.", "scope": {"holder": "jterrace-pyssim", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/bakwc/PySyncObj/blob/be3b0aaa932d5156f5df140c23c962430f51b7b8/pysyncobj/syncobj.py#L664-L668", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:bakwc-PySyncObj:SyncObj.printStatus-8eeaff8272@held-out", "question": "Dumps different debug info about cluster to default logger", "scope": {"holder": "bakwc-PySyncObj", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/bakwc/PySyncObj/blob/be3b0aaa932d5156f5df140c23c962430f51b7b8/pysyncobj/transport.py#L239-L253", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:bakwc-PySyncObj:TCPTransport._createServer-16931d1fb9@held-out", "question": "Create the TCP server (but don't bind yet)", "scope": {"holder": "bakwc-PySyncObj", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/bakwc/PySyncObj/blob/be3b0aaa932d5156f5df140c23c962430f51b7b8/pysyncobj/transport.py#L441-L458", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:bakwc-PySyncObj:TCPTransport._onOutgoingMessageReceived-90d4cf74f4@held-out", "question": "Callback for receiving a message on a new outgoing connection. Used only if encryption is enabled to exchange the random keys.\n Once the key exchange is done, this triggers the onNodeConnected callback, and further messages are deferred to the onMessageReceived callback.\n\n :param conn: connection object\n :type conn: TcpConnection\n :param message: received message\n :type message: any", "scope": {"holder": "bakwc-PySyncObj", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/bakwc/PySyncObj/blob/be3b0aaa932d5156f5df140c23c962430f51b7b8/pysyncobj/transport.py#L490-L509", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:bakwc-PySyncObj:TCPTransport.addNode-bf6a3b5b6a@held-out", "question": "Add a node to the network\n\n :param node: node to add\n :type node: TCPNode", "scope": {"holder": "bakwc-PySyncObj", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/bakwc/PySyncObj/blob/be3b0aaa932d5156f5df140c23c962430f51b7b8/pysyncobj/batteries.py#L389-L394", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:bakwc-PySyncObj:ReplPriorityQueue.get-84978fbca8@held-out", "question": "Extract the smallest item from queue.\n Return default if queue is empty.", "scope": {"holder": "bakwc-PySyncObj", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/domainaware/parsedmarc/blob/ecc9fd434c23d896ccd1f35795ccc047f946ed05/parsedmarc/kafkaclient.py#L90-L132", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:domainaware-parsedmarc:KafkaClient.save_aggregate_reports_to_kafka-7b098735a0@held-out", "question": "Saves aggregate DMARC reports to Kafka\n\n Args:\n aggregate_reports (list): A list of aggregate report dictionaries\n to save to Kafka\n aggregate_topic (str): The name of the Kafka topic", "scope": {"holder": "domainaware-parsedmarc", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/domainaware/parsedmarc/blob/ecc9fd434c23d896ccd1f35795ccc047f946ed05/parsedmarc/__init__.py#L865-L1304", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:domainaware-parsedmarc:get_dmarc_reports_from_inbox-6b02e98e89@held-out", "question": "Fetches and parses DMARC reports from sn inbox\n\n Args:\n host: The mail server hostname or IP address\n user: The mail server user\n password: The mail server password\n connection: An IMAPCLient connection to reuse\n port: The mail server port\n ssl (bool): Use SSL/TLS\n ssl_context (SSLContext): A SSL context\n move_supported: Indicate if the IMAP server supports the MOVE command\n (autodetect if None)\n reports_folder: The IMAP folder where reports can be found\n archive_folder: The folder to move processed mail to\n delete (bool): Delete messages after processing them\n test (bool): Do not move or delete messages after processing them\n nameservers (list): A list of DNS nameservers to query\n dns_timeout (float): Set the DNS query timeout\n strip_attachment_payloads (bool): Remove attachment payloads from\n forensic report results\n results (dict): Results from the previous run\n\n Returns:\n OrderedDict: Lists of ``aggregate_reports`` and ``forensic_reports``", "scope": {"holder": "domainaware-parsedmarc", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/domainaware/parsedmarc/blob/ecc9fd434c23d896ccd1f35795ccc047f946ed05/parsedmarc/__init__.py#L1307-L1366", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:domainaware-parsedmarc:save_output-de013655e5@held-out", "question": "Save report data in the given directory\n\n Args:\n results (OrderedDict): Parsing results\n output_directory: The patch to the directory to save in", "scope": {"holder": "domainaware-parsedmarc", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/domainaware/parsedmarc/blob/ecc9fd434c23d896ccd1f35795ccc047f946ed05/parsedmarc/__init__.py#L1414-L1496", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:domainaware-parsedmarc:email_results-abfb15c159@held-out", "question": "Emails parsing results as a zip file\n\n Args:\n results (OrderedDict): Parsing results\n host: Mail server hostname or IP address\n mail_from: The value of the message from header\n mail_to : A list of addresses to mail to\n port (int): Port to use\n ssl (bool): Require a SSL connection from the start\n user: An optional username\n password: An optional password\n subject: Overrides the default message subject\n attachment_filename: Override the default attachment filename\n message: Override the default plain text body\n ssl_context: SSL context options", "scope": {"holder": "domainaware-parsedmarc", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/domainaware/parsedmarc/blob/ecc9fd434c23d896ccd1f35795ccc047f946ed05/parsedmarc/utils.py#L221-L238", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:domainaware-parsedmarc:human_timestamp_to_datetime-7c0285f6e3@held-out", "question": "Converts a human-readable timestamp into a Python ``DateTime`` object\n\n Args:\n human_timestamp (str): A timestamp string\n to_utc (bool): Convert the timestamp to UTC\n\n Returns:\n DateTime: The converted timestamp", "scope": {"holder": "domainaware-parsedmarc", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/domainaware/parsedmarc/blob/ecc9fd434c23d896ccd1f35795ccc047f946ed05/parsedmarc/utils.py#L461-L564", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:domainaware-parsedmarc:parse_email-aa7b8a77cc@held-out", "question": "A simplified email parser\n\n Args:\n data: The RFC 822 message string, or MSG binary\n strip_attachment_payloads (bool): Remove attachment payloads\n\n Returns (dict): Parsed email data", "scope": {"holder": "domainaware-parsedmarc", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/domainaware/parsedmarc/blob/ecc9fd434c23d896ccd1f35795ccc047f946ed05/parsedmarc/cli.py#L27-L30", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:domainaware-parsedmarc:_str_to_list-651b5b24ee@held-out", "question": "Converts a comma separated string to a list", "scope": {"holder": "domainaware-parsedmarc", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/domainaware/parsedmarc/blob/ecc9fd434c23d896ccd1f35795ccc047f946ed05/parsedmarc/cli.py#L33-L47", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:domainaware-parsedmarc:cli_parse-47bb81f72c@held-out", "question": "Separated this function for multiprocessing", "scope": {"holder": "domainaware-parsedmarc", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/domainaware/parsedmarc/blob/ecc9fd434c23d896ccd1f35795ccc047f946ed05/parsedmarc/cli.py#L55-L599", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:domainaware-parsedmarc:_main-a49ffad796@held-out", "question": "Called when the module is executed", "scope": {"holder": "domainaware-parsedmarc", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/nats-io/asyncio-nats/blob/39e840be0b12ce326edac0bba69aeb1be930dcb8/nats/aio/client.py#L643-L732", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:nats-io-asyncio-nats:Client.request-5396f0e023@held-out", "question": "Implements the request/response pattern via pub/sub\n using a single wildcard subscription that handles\n the responses.", "scope": {"holder": "nats-io-asyncio-nats", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/nats-io/asyncio-nats/blob/39e840be0b12ce326edac0bba69aeb1be930dcb8/nats/aio/client.py#L1157-L1165", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:nats-io-asyncio-nats:Client._process_pong-8772b25ebf@held-out", "question": "Process PONG sent by server.", "scope": {"holder": "nats-io-asyncio-nats", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/neurosynth/neurosynth/blob/948ce7edce15d7df693446e76834e0c23bfe8f11/neurosynth/analysis/decode.py#L154-L157", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:neurosynth-neurosynth:Decoder._load_features_from_array-d86b7a1d05@held-out", "question": "Load feature data from a 2D ndarray on disk.", "scope": {"holder": "neurosynth-neurosynth", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/neurosynth/neurosynth/blob/948ce7edce15d7df693446e76834e0c23bfe8f11/neurosynth/base/lexparser.py#L75-L78", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:neurosynth-neurosynth:Parser.p_list_or-217bbd8483@held-out", "question": "list : list OR list", "scope": {"holder": "neurosynth-neurosynth", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/neurosynth/neurosynth/blob/948ce7edce15d7df693446e76834e0c23bfe8f11/neurosynth/analysis/reduce.py#L17-L111", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:neurosynth-neurosynth:average_within_regions-01181f296d@held-out", "question": "Aggregates over all voxels within each ROI in the input image.\n\n Takes a Dataset and a Nifti image that defines distinct regions, and\n returns a numpy matrix of ROIs x mappables, where the value at each\n ROI is the proportion of active voxels in that ROI. Each distinct ROI\n must have a unique value in the image; non-contiguous voxels with the\n same value will be assigned to the same ROI.\n\n Args:\n dataset: Either a Dataset instance from which image data are\n extracted, or a Numpy array containing image data to use. If\n the latter, the array contains voxels in rows and\n features/studies in columns. The number of voxels must be equal\n to the length of the vectorized image mask in the regions\n image.\n regions: An image defining the boundaries of the regions to use.\n Can be one of:\n 1) A string name of the NIFTI or Analyze-format image\n 2) A NiBabel SpatialImage\n 3) A list of NiBabel images\n 4) A 1D numpy array of the same length as the mask vector in\n the Dataset's current Masker.\n masker: Optional masker used to load image if regions is not a\n numpy array. Must be passed if dataset is a numpy array.\n threshold: An optional float in the range of 0 - 1 or integer. If\n passed, the array will be binarized, with ROI values above the\n threshold assigned to True and values below the threshold\n assigned to False. (E.g., if threshold = 0.05, only ROIs in\n which more than 5% of voxels are active will be considered\n active.) If threshold is integer, studies will only be\n considered active if they activate more than that number of\n voxels in the ROI.\n remove_zero: An optional boolean; when True, assume that voxels\n with value of 0 should not be considered as a separate ROI, and\n will be ignored.\n\n Returns:\n A 2D numpy array with ROIs in rows and mappables in columns.", "scope": {"holder": "neurosynth-neurosynth", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/neurosynth/neurosynth/blob/948ce7edce15d7df693446e76834e0c23bfe8f11/neurosynth/analysis/reduce.py#L145-L163", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:neurosynth-neurosynth:get_random_voxels-22c7316fd8@held-out", "question": "Returns mappable data for a random subset of voxels.\n\n May be useful as a baseline in predictive analyses--e.g., to compare\n performance of a more principled feature selection method with simple\n random selection.\n\n Args:\n dataset: A Dataset instance\n n_voxels: An integer specifying the number of random voxels to select.\n\n Returns:\n A 2D numpy array with (randomly-selected) voxels in rows and mappables\n in columns.", "scope": {"holder": "neurosynth-neurosynth", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/neurosynth/neurosynth/blob/948ce7edce15d7df693446e76834e0c23bfe8f11/neurosynth/analysis/reduce.py#L166-L173", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:neurosynth-neurosynth:_get_top_words-3595b8482c@held-out", "question": "Return top forty words from each topic in trained topic model.", "scope": {"holder": "neurosynth-neurosynth", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/neurosynth/neurosynth/blob/948ce7edce15d7df693446e76834e0c23bfe8f11/neurosynth/analysis/stats.py#L8-L16", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:neurosynth-neurosynth:pearson-236ddddeac@held-out", "question": "Correlates row vector x with each row vector in 2D array y.", "scope": {"holder": "neurosynth-neurosynth", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/neurosynth/neurosynth/blob/948ce7edce15d7df693446e76834e0c23bfe8f11/neurosynth/analysis/stats.py#L19-L40", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:neurosynth-neurosynth:two_way-d03608008d@held-out", "question": "Two-way chi-square test of independence.\n Takes a 3D array as input: N(voxels) x 2 x 2, where the last two dimensions\n are the contingency table for each of N voxels. Returns an array of\n p-values.", "scope": {"holder": "neurosynth-neurosynth", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/neurosynth/neurosynth/blob/948ce7edce15d7df693446e76834e0c23bfe8f11/neurosynth/analysis/stats.py#L43-L59", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:neurosynth-neurosynth:one_way-afaf0e4f70@held-out", "question": "One-way chi-square test of independence.\n Takes a 1D array as input and compares activation at each voxel to\n proportion expected under a uniform distribution throughout the array. Note\n that if you're testing activation with this, make sure that only valid\n voxels (e.g., in-mask gray matter voxels) are included in the array, or\n results won't make any sense!", "scope": {"holder": "neurosynth-neurosynth", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/neurosynth/neurosynth/blob/948ce7edce15d7df693446e76834e0c23bfe8f11/neurosynth/analysis/stats.py#L62-L69", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:neurosynth-neurosynth:fdr-177b33e49c@held-out", "question": "Determine FDR threshold given a p value array and desired false\n discovery rate q.", "scope": {"holder": "neurosynth-neurosynth", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/neurosynth/neurosynth/blob/948ce7edce15d7df693446e76834e0c23bfe8f11/neurosynth/base/dataset.py#L640-L665", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:neurosynth-neurosynth:FeatureTable.get_feature_data-c6394a4859@held-out", "question": "Slices and returns a subset of feature data.\n\n Args:\n ids (list, array): A list or 1D numpy array of study ids to\n return rows for. If None, returns data for all studies\n (i.e., all rows in array).\n features (list, array): A list or 1D numpy array of named features\n to return. If None, returns data for all features (i.e., all\n columns in array).\n dense (bool): Optional boolean. When True (default), convert the\n result to a dense array before returning. When False, keep as\n sparse matrix. Note that if ids is not None, the returned array\n will always be dense.\n Returns:\n A pandas DataFrame with study IDs in rows and features incolumns.", "scope": {"holder": "neurosynth-neurosynth", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/neurosynth/neurosynth/blob/948ce7edce15d7df693446e76834e0c23bfe8f11/neurosynth/analysis/meta.py#L14-L54", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:neurosynth-neurosynth:analyze_features-50ce8ee980@held-out", "question": "Generate meta-analysis images for a set of features.\n Args:\n dataset: A Dataset instance containing feature and activation data.\n features: A list of named features to generate meta-analysis maps for.\n If None, analyzes all features in the current dataset.\n image_type: The type of image to return. Specify one of the extensions\n generated by the MetaAnalysis procedure--e.g., association-test_z,\n uniformity-test_z, etc. By default, will use\n association-test_z (i.e., z-scores reflecting the association\n between presence of activation and presence of feature).\n threshold: The threshold for determining whether or not a Mappable has\n a feature. By default, this is 0.001, which is only sensible in the\n case of term-based features (so be sure to specify it for other\n kinds).\n q: The FDR rate to use for multiple comparisons correction (default =\n 0.05).\n output_dir: Directory to save all meta-analysis images to. If none,\n returns all the data as a matrix.\n prefix: All output images will be prepended with this string (if None,\n defaults to the name of the feature).\n Returns:\n If output_dir is None, an n_voxels x n_features 2D numpy array.", "scope": {"holder": "neurosynth-neurosynth", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/neurosynth/neurosynth/blob/948ce7edce15d7df693446e76834e0c23bfe8f11/neurosynth/base/transformations.py#L10-L15", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:neurosynth-neurosynth:transform-3faeda268f@held-out", "question": "Convert coordinates from one space to another using provided\n transformation matrix.", "scope": {"holder": "neurosynth-neurosynth", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/neurosynth/neurosynth/blob/948ce7edce15d7df693446e76834e0c23bfe8f11/neurosynth/base/imageutils.py#L12-L24", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:neurosynth-neurosynth:get_sphere-4c54c54a77@held-out", "question": "# Return all points within r mm of coordinates. Generates a cube\n and then discards all points outside sphere. Only returns values that\n fall within the dimensions of the image.", "scope": {"holder": "neurosynth-neurosynth", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/neurosynth/neurosynth/blob/948ce7edce15d7df693446e76834e0c23bfe8f11/neurosynth/base/imageutils.py#L73-L95", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:neurosynth-neurosynth:threshold_img-f6886e4bc3@held-out", "question": "Threshold data, setting all values in the array above/below threshold\n to zero.\n Args:\n data (ndarray): The image data to threshold.\n threshold (float): Numeric threshold to apply to image.\n mask (ndarray): Optional 1D-array with the same length as the data. If\n passed, the threshold is first applied to the mask, and the\n resulting indices are used to threshold the data. This is primarily\n useful when, e.g., applying a statistical threshold to a z-value\n image based on a p-value threshold.\n mask_out (str): Thresholding direction. Can be 'below' the threshold\n (default) or 'above' the threshold. Note: use 'above' when masking\n based on p values.", "scope": {"holder": "neurosynth-neurosynth", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/neurosynth/neurosynth/blob/948ce7edce15d7df693446e76834e0c23bfe8f11/neurosynth/base/imageutils.py#L98-L152", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:neurosynth-neurosynth:create_grid-bd74522fbd@held-out", "question": "Creates an image containing labeled cells in a 3D grid.\n Args:\n image: String or nibabel image. The image used to define the grid\n dimensions. Also used to define the mask to apply to the grid.\n Only voxels with non-zero values in the mask will be retained; all\n other voxels will be zeroed out in the returned image.\n scale: The scaling factor which controls the grid size. Value reflects\n diameter of cube in voxels.\n apply_mask: Boolean indicating whether or not to zero out voxels not in\n image.\n save_file: Optional string giving the path to save image to. Image\n written out is a standard Nifti image. If save_file is None, no\n image is written.\n Returns:\n A nibabel image with the same dimensions as the input image. All voxels\n in each cell in the 3D grid are assigned the same non-zero label.", "scope": {"holder": "neurosynth-neurosynth", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/openvenues/pypostal/blob/1c0fd96b5e2463b7015cd3625ac276db520c69fe/postal/normalize.py#L57-L78", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:openvenues-pypostal:normalized_tokens-c7d6f90b07@held-out", "question": "Normalizes a string, tokenizes, and normalizes each token\n with string and token-level options.\n\n This version only uses libpostal's deterministic normalizations\n i.e. methods with a single output. The string tree version will\n return multiple normalized strings, each with tokens.\n\n Usage:\n normalized_tokens(u'St.-Barthélemy')", "scope": {"holder": "openvenues-pypostal", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/openvenues/pypostal/blob/1c0fd96b5e2463b7015cd3625ac276db520c69fe/postal/near_dupe.py#L6-L42", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:openvenues-pypostal:near_dupe_hashes-a212310f4e@held-out", "question": "Hash the given address into normalized strings that can be used to group similar\n addresses together for more detailed pairwise comparison. This can be thought of\n as the blocking function in record linkage or locally-sensitive hashing in the\n document near-duplicate detection.\n\n Required\n --------\n @param labels: array of component labels as either Unicode or UTF-8 encoded strings\n e.g. [\"house_number\", \"road\", \"postcode\"]\n @param values: array of component values as either Unicode or UTF-8 encoded strings\n e.g. [\"123\", \"Broadway\", \"11216\"]. Note len(values) must be equal to\n len(labels).\n\n Options\n -------\n @param languages: a tuple or list of ISO language code strings (e.g. \"en\", \"fr\", \"de\", etc.)\n to use in expansion. If None is passed, use language classifier\n to detect language automatically.\n @param with_name: use name in the hashes\n @param with_address: use house_number & street in the hashes\n @param with_unit: use secondary unit as part of the hashes\n @param with_city_or_equivalent: use the city, city_district, suburb, or island name as one of\n the geo qualifiers\n @param with_small_containing_boundaries: use small containing boundaries (currently state_district)\n as one of the geo qualifiers\n @param with_postal_code: use postal code as one of the geo qualifiers\n @param with_latlon: use geohash + neighbors as one of the geo qualifiers\n @param latitude: latitude (Y coordinate)\n @param longitude: longitude (X coordinate)\n @param geohash_precision: geohash tile size (default = 6)\n @param name_and_address_keys: include keys with name + address + geo\n @param name_only_keys: include keys with name + geo\n @param address_only_keys: include keys with address + geo", "scope": {"holder": "openvenues-pypostal", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/hydrosquall/tiingo-python/blob/9bb98ca9d24f2e4db651cf0590e4b47184546482/tools/api_key_tool.py#L31-L41", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:hydrosquall-tiingo-python:remove_api_key-80163f3ea8@held-out", "question": "Change the api key in the Token object to 40*'0'. See issue #86.\n :param file: path-to-file to change", "scope": {"holder": "hydrosquall-tiingo-python", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/hydrosquall/tiingo-python/blob/9bb98ca9d24f2e4db651cf0590e4b47184546482/tiingo/api.py#L142-L149", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:hydrosquall-tiingo-python:TiingoClient._invalid_frequency-b134fd4ac6@held-out", "question": "Check to see that frequency was specified correctly\n :param frequency (string): frequency string\n :return (boolean):", "scope": {"holder": "hydrosquall-tiingo-python", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/mental32/spotify.py/blob/bb296cac7c3dd289908906b7069bd80f43950515/spotify/models/user.py#L186-L195", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:mental32-spotify.py:User.get_devices-4ff55ff2ca@held-out", "question": "Get information about the users avaliable devices.\n\n Returns\n -------\n devices : List[Device]\n The devices the user has available.", "scope": {"holder": "mental32-spotify.py", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/mental32/spotify.py/blob/bb296cac7c3dd289908906b7069bd80f43950515/spotify/models/user.py#L198-L210", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:mental32-spotify.py:User.recently_played-0b8fd75e06@held-out", "question": "Get tracks from the current users recently played tracks.\n\n Returns\n -------\n playlist_history : List[Dict[str, Union[Track, Context, str]]]\n A list of playlist history object.\n Each object is a dict with a timestamp, track and context field.", "scope": {"holder": "mental32-spotify.py", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/mental32/spotify.py/blob/bb296cac7c3dd289908906b7069bd80f43950515/spotify/models/user.py#L233-L245", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:mental32-spotify.py:User.replace_tracks-fdeebad428@held-out", "question": "Replace all the tracks in a playlist, overwriting its existing tracks. \n This powerful request can be useful for replacing tracks, re-ordering existing tracks, or clearing the playlist.\n\n Parameters\n ----------\n playlist : Union[str, PLaylist]\n The playlist to modify\n tracks : Sequence[Union[str, Track]]\n Tracks to place in the playlist", "scope": {"holder": "mental32-spotify.py", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/mental32/spotify.py/blob/bb296cac7c3dd289908906b7069bd80f43950515/spotify/utils.py#L49-L64", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:mental32-spotify.py:assert_hasattr-8d91cdf524@held-out", "question": "decorator to assert an object has an attribute when run.", "scope": {"holder": "mental32-spotify.py", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/mental32/spotify.py/blob/bb296cac7c3dd289908906b7069bd80f43950515/spotify/utils.py#L134-L147", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:mental32-spotify.py:OAuth2.attrs-4c45463408@held-out", "question": "Attributes used when constructing url parameters.", "scope": {"holder": "mental32-spotify.py", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/mental32/spotify.py/blob/bb296cac7c3dd289908906b7069bd80f43950515/spotify/models/player.py#L162-L197", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:mental32-spotify.py:Player.play-937e64b642@held-out", "question": "Start a new context or resume current playback on the user’s active device.\n\n The method treats a single argument as a Spotify context, such as a Artist, Album and playlist objects/URI.\n When called with multiple positional arguments they are interpreted as a array of Spotify Track objects/URIs.\n\n Parameters\n ----------\n *uris : :obj:`SomeURIs`\n When a single argument is passed in that argument is treated as a context.\n Valid contexts are: albums, artists, playlists.\n Album, Artist and Playlist objects are accepted too.\n Otherwise when multiple arguments are passed in they,\n A sequence of Spotify Tracks or Track URIs to play.\n offset : Optional[:obj:`Offset`]\n Indicates from where in the context playback should start.\n Only available when `context` corresponds to an album or playlist object, \n or when the `uris` parameter is used. when an integer offset is zero based and can’t be negative. \n device : Optional[:obj:`SomeDevice`]\n The Device object or id of the device this command is targeting.\n If not supplied, the user’s currently active device is the target.", "scope": {"holder": "mental32-spotify.py", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/funilrys/PyFunceble/blob/cdf69cbde120199171f7158e1c33635753e6e2f5/PyFunceble/expiration_date.py#L309-L432", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:funilrys-PyFunceble:ExpirationDate._format-e4bc5f6617@held-out", "question": "Format the expiration date into an unified format (01-jan-1970).\n\n :param date_to_convert:\n The date to convert. In other words, the extracted date.\n :type date_to_convert: str\n\n :return: The formatted expiration date.\n :rtype: str", "scope": {"holder": "funilrys-PyFunceble", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/funilrys/PyFunceble/blob/cdf69cbde120199171f7158e1c33635753e6e2f5/PyFunceble/production.py#L320-L337", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:funilrys-PyFunceble:Production._is_version_greater-9b6966e971@held-out", "question": "Check if the current version is greater as the older older one.", "scope": {"holder": "funilrys-PyFunceble", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/funilrys/PyFunceble/blob/cdf69cbde120199171f7158e1c33635753e6e2f5/PyFunceble/adblock.py#L131-L176", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:funilrys-PyFunceble:AdBlock._handle_options-528b4dbec2@held-out", "question": "Handle the data from the options.\n\n :param options: The list of options from the rule.\n :type options: list\n\n :return: The list of domains to return globally.\n :rtype: list", "scope": {"holder": "funilrys-PyFunceble", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/funilrys/PyFunceble/blob/cdf69cbde120199171f7158e1c33635753e6e2f5/PyFunceble/adblock.py#L309-L402", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:funilrys-PyFunceble:AdBlock._format_decoded-94db18fe81@held-out", "question": "Format the exctracted adblock line before passing it to the system.\n\n :param to_format: The extracted line from the file.\n :type to_format: str\n\n :param result: A list of the result of this method.\n :type result: list\n\n :return: The list of domains or IP to test.\n :rtype: list", "scope": {"holder": "funilrys-PyFunceble", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/funilrys/PyFunceble/blob/cdf69cbde120199171f7158e1c33635753e6e2f5/PyFunceble/core.py#L561-L582", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:funilrys-PyFunceble:Core.bypass-907b0f326d@held-out", "question": "Exit the script if :code:`[PyFunceble skip]` is matched into the latest\n commit message.", "scope": {"holder": "funilrys-PyFunceble", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/funilrys/PyFunceble/blob/cdf69cbde120199171f7158e1c33635753e6e2f5/PyFunceble/status.py#L603-L623", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:funilrys-PyFunceble:URLStatus.handle-f749f458f8@held-out", "question": "Handle the backend of the given status.", "scope": {"holder": "funilrys-PyFunceble", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/funilrys/PyFunceble/blob/cdf69cbde120199171f7158e1c33635753e6e2f5/PyFunceble/directory_structure.py#L439-L482", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:funilrys-PyFunceble:DirectoryStructure._create_directory-291a2d0463@held-out", "question": "Creates the given directory if it does not exists.\n\n :param directory: The directory to create.\n :type directory: str\n\n :param loop: Tell us if we are in the creation loop or not.\n :type loop: bool", "scope": {"holder": "funilrys-PyFunceble", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/funilrys/PyFunceble/blob/cdf69cbde120199171f7158e1c33635753e6e2f5/PyFunceble/directory_structure.py#L484-L607", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:funilrys-PyFunceble:DirectoryStructure.restore-c207a8511c@held-out", "question": "Restore the 'output/' directory structure based on the `dir_structure.json` file.", "scope": {"holder": "funilrys-PyFunceble", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/funilrys/PyFunceble/blob/cdf69cbde120199171f7158e1c33635753e6e2f5/PyFunceble/config.py#L195-L225", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:funilrys-PyFunceble:Load._set_path_to_configs-e7b6b8dfae@held-out", "question": "Set the paths to the configuration files.\n\n :param path_to_config: The possible path to the config to load.\n :type path_to_config: str\n\n :return:\n The path to the config to read (0), the path to the default\n configuration to read as fallback.(1)\n :rtype: tuple", "scope": {"holder": "funilrys-PyFunceble", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/funilrys/PyFunceble/blob/cdf69cbde120199171f7158e1c33635753e6e2f5/PyFunceble/config.py#L227-L262", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:funilrys-PyFunceble:Load._load_config_file-f6977089a6@held-out", "question": "Load .PyFunceble.yaml into the system.", "scope": {"holder": "funilrys-PyFunceble", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/funilrys/PyFunceble/blob/cdf69cbde120199171f7158e1c33635753e6e2f5/PyFunceble/config.py#L584-L640", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:funilrys-PyFunceble:Version.check_versions-d0847ee270@held-out", "question": "Compare the given versions.\n\n :param local: The local version converted by split_versions().\n :type local: list\n\n :param upstream: The upstream version converted by split_versions().\n :type upstream: list\n\n :return:\n - True: local < upstream\n - None: local == upstream\n - False: local > upstream\n :rtype: bool|None", "scope": {"holder": "funilrys-PyFunceble", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/funilrys/PyFunceble/blob/cdf69cbde120199171f7158e1c33635753e6e2f5/PyFunceble/publicsuffix.py#L174-L187", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:funilrys-PyFunceble:PublicSuffix.load-ab46ca9b7b@held-out", "question": "Load the public suffix database into the system.", "scope": {"holder": "funilrys-PyFunceble", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/funilrys/PyFunceble/blob/cdf69cbde120199171f7158e1c33635753e6e2f5/PyFunceble/sort.py#L79-L95", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:funilrys-PyFunceble:Sort.standard-cf9f7b0057@held-out", "question": "Implement the standard and alphabetical sorting.\n\n :param element: The element we are currently reading.\n :type element: str\n\n :return: The formatted element.\n :rtype: str", "scope": {"holder": "funilrys-PyFunceble", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/funilrys/PyFunceble/blob/cdf69cbde120199171f7158e1c33635753e6e2f5/PyFunceble/mining.py#L376-L394", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:funilrys-PyFunceble:Mining.process-a22a680983@held-out", "question": "Process the logic and structuration of the mining database.", "scope": {"holder": "funilrys-PyFunceble", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/funilrys/PyFunceble/blob/cdf69cbde120199171f7158e1c33635753e6e2f5/PyFunceble/logs.py#L155-L199", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:funilrys-PyFunceble:Logs.expiration_date-e65f075198@held-out", "question": "Logs the extracted expiration date.\n\n :param extracted: The extracted expiration date (from WHOIS record).\n :type extracted: str", "scope": {"holder": "funilrys-PyFunceble", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/funilrys/PyFunceble/blob/cdf69cbde120199171f7158e1c33635753e6e2f5/PyFunceble/prints.py#L236-L325", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:funilrys-PyFunceble:Prints._header_constructor-ac267f393f@held-out", "question": "Construct header of the table according to template.\n\n :param data_to_print:\n The list of data to print into the header of the table.\n :type data_to_print: list\n\n :param header_separator:\n The separator to use between the table header and our data.\n :type header_separator: str\n\n :param colomn_separator: The separator to use between each colomns.\n :type colomn_separator: str\n\n :return: The data to print in a list format.\n :rtype: list", "scope": {"holder": "funilrys-PyFunceble", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/funilrys/PyFunceble/blob/cdf69cbde120199171f7158e1c33635753e6e2f5/PyFunceble/prints.py#L443-L481", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:funilrys-PyFunceble:Prints._data_constructor-28816c4a25@held-out", "question": "Construct the table of data according to given size.\n\n :param size: The maximal length of each string in the table.\n :type size: list\n\n :return:\n A dict with all information about the data and how to which what\n maximal size to print it.\n :rtype: OrderedDict\n\n :raises:\n :code:`Exception`\n If the data and the size does not have the same length.", "scope": {"holder": "funilrys-PyFunceble", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/funilrys/PyFunceble/blob/cdf69cbde120199171f7158e1c33635753e6e2f5/PyFunceble/helpers.py#L126-L149", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:funilrys-PyFunceble:Hash._hash_file-753862e3f2@held-out", "question": "Get the hash of the given file\n\n :param algo: The algorithm to use.\n :type algo: str\n\n :return: The hexdigest of the data.\n :rtype: str", "scope": {"holder": "funilrys-PyFunceble", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/funilrys/PyFunceble/blob/cdf69cbde120199171f7158e1c33635753e6e2f5/PyFunceble/helpers.py#L473-L542", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:funilrys-PyFunceble:Dict.merge-8b3da985dc@held-out", "question": "Merge the content of to_merge into the given main dictionnary.\n\n :param to_merge: The dictionnary to merge.\n :type to_merge: dict\n\n :param strict:\n Tell us if we have to strictly merge lists.\n\n :code:`True`: We follow index\n :code`False`: We follow element (content)\n :type strict: bool\n\n :return: The merged dict.\n :rtype: dict", "scope": {"holder": "funilrys-PyFunceble", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/funilrys/PyFunceble/blob/cdf69cbde120199171f7158e1c33635753e6e2f5/PyFunceble/helpers.py#L581-L603", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:funilrys-PyFunceble:Dict.to_yaml-d62a543cc2@held-out", "question": "Save a dictionnary into a YAML file.\n\n :param destination:\n A path to a file where we're going to write the\n converted dict into a JSON format.\n :type destination: str", "scope": {"holder": "funilrys-PyFunceble", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/funilrys/PyFunceble/blob/cdf69cbde120199171f7158e1c33635753e6e2f5/PyFunceble/helpers.py#L705-L747", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:funilrys-PyFunceble:File.write-ef6474095b@held-out", "question": "Write or append data into the given file path.\n\n :param data_to_write: The data to write.\n :type data_to_write: str\n\n :param overwrite:\n Tell us if we have to overwrite the\n content of the file we are working with.\n :type overwrite: bool", "scope": {"holder": "funilrys-PyFunceble", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/funilrys/PyFunceble/blob/cdf69cbde120199171f7158e1c33635753e6e2f5/PyFunceble/check.py#L382-L418", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:funilrys-PyFunceble:Check.is_ip_valid-2f155512d6@held-out", "question": "Check if the given IP is a valid IPv4.\n\n :param ip_to_check: The IP to test.\n :type ip_to_check: str\n\n :return: The validity of the IP.\n :rtype: bool\n\n .. note::\n We only test IPv4 because for now we only them for now.", "scope": {"holder": "funilrys-PyFunceble", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/funilrys/PyFunceble/blob/cdf69cbde120199171f7158e1c33635753e6e2f5/PyFunceble/check.py#L420-L458", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:funilrys-PyFunceble:Check.is_ip_range-cb32e1face@held-out", "question": "Check if the given IP is a valid IPv4.\n\n :param ip_to_check: The IP to test.\n :type ip_to_check: str\n\n :return: The validity of the IP.\n :rtype: bool\n\n .. note::\n We only test IPv4 because for now we only them for now.", "scope": {"holder": "funilrys-PyFunceble", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/funilrys/PyFunceble/blob/cdf69cbde120199171f7158e1c33635753e6e2f5/PyFunceble/database.py#L112-L184", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:funilrys-PyFunceble:Inactive._reformat_historical_formating_error-195dd6ab09@held-out", "question": "Format the old format so it can be merged into the newer format.", "scope": {"holder": "funilrys-PyFunceble", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/funilrys/PyFunceble/blob/cdf69cbde120199171f7158e1c33635753e6e2f5/PyFunceble/database.py#L726-L745", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:funilrys-PyFunceble:Whois._retrieve-b82a99bf9a@held-out", "question": "Retrieve the data from the database.", "scope": {"holder": "funilrys-PyFunceble", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/funilrys/PyFunceble/blob/cdf69cbde120199171f7158e1c33635753e6e2f5/PyFunceble/database.py#L789-L814", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:funilrys-PyFunceble:Whois.is_time_older-4b366ffa1c@held-out", "question": "Check if the current time is older than the one in the database.", "scope": {"holder": "funilrys-PyFunceble", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/myint/autoflake/blob/68fea68646922b920d55975f9f2adaeafd84df4f/autoflake.py#L108-L112", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:myint-autoflake:unused_import_line_numbers-b894e64fd0@held-out", "question": "Yield line numbers of unused imports.", "scope": {"holder": "myint-autoflake", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/myint/autoflake/blob/68fea68646922b920d55975f9f2adaeafd84df4f/autoflake.py#L126-L130", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:myint-autoflake:star_import_used_line_numbers-26cffb7d4d@held-out", "question": "Yield line number of star import usage.", "scope": {"holder": "myint-autoflake", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/myint/autoflake/blob/68fea68646922b920d55975f9f2adaeafd84df4f/autoflake.py#L456-L476", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:myint-autoflake:filter_unused_variable-7334646830@held-out", "question": "Return line if used, otherwise return None.", "scope": {"holder": "myint-autoflake", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/myint/autoflake/blob/68fea68646922b920d55975f9f2adaeafd84df4f/autoflake.py#L726-L728", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:myint-autoflake:_split_comma_separated-cc7aa3183b@held-out", "question": "Return a set of strings.", "scope": {"holder": "myint-autoflake", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/OpenKMIP/PyKMIP/blob/b51c5b044bd05f8c85a1d65d13a583a4d8fc1b0e/kmip/core/messages/payloads/cancel.py#L103-L131", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:OpenKMIP-PyKMIP:CancelRequestPayload.write-71c13c2513@held-out", "question": "Write the data encoding the Cancel request payload to a stream.\n\n Args:\n output_stream (stream): A data stream in which to encode object\n data, supporting a write method; usually a BytearrayStream\n object.\n kmip_version (KMIPVersion): An enumeration defining the KMIP\n version with which the object will be encoded. Optional,\n defaults to KMIP 1.0.\n\n Raises:\n ValueError: Raised if the data attribute is not defined.", "scope": {"holder": "OpenKMIP-PyKMIP", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/OpenKMIP/PyKMIP/blob/b51c5b044bd05f8c85a1d65d13a583a4d8fc1b0e/kmip/core/attributes.py#L899-L919", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:OpenKMIP-PyKMIP:Digest.read-3f103f5934@held-out", "question": "Read the data encoding the Digest object and decode it into its\n constituent parts.\n\n Args:\n istream (Stream): A data stream containing encoded object data,\n supporting a read method; usually a BytearrayStream object.\n kmip_version (KMIPVersion): An enumeration defining the KMIP\n version with which the object will be decoded. Optional,\n defaults to KMIP 1.0.", "scope": {"holder": "OpenKMIP-PyKMIP", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/OpenKMIP/PyKMIP/blob/b51c5b044bd05f8c85a1d65d13a583a4d8fc1b0e/kmip/core/attributes.py#L1443-L1493", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:OpenKMIP-PyKMIP:DerivationParameters.read-f939dfe93f@held-out", "question": "Read the data encoding the DerivationParameters struct and decode it\n into its constituent parts.\n\n Args:\n input_stream (stream): A data stream containing encoded object\n data, supporting a read method; usually a BytearrayStream\n object.\n kmip_version (KMIPVersion): An enumeration defining the KMIP\n version with which the object will be decoded. Optional,\n defaults to KMIP 1.0.", "scope": {"holder": "OpenKMIP-PyKMIP", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/OpenKMIP/PyKMIP/blob/b51c5b044bd05f8c85a1d65d13a583a4d8fc1b0e/kmip/core/messages/payloads/get.py#L414-L470", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:OpenKMIP-PyKMIP:GetResponsePayload.read-b86d53bbe1@held-out", "question": "Read the data encoding the Get response payload and decode it\n into its constituent parts.\n\n Args:\n input_stream (stream): A data stream containing encoded object\n data, supporting a read method; usually a BytearrayStream\n object.\n kmip_version (KMIPVersion): An enumeration defining the KMIP\n version with which the object will be decoded. Optional,\n defaults to KMIP 1.0.\n\n Raises:\n ValueError: Raised if the object type, unique identifier, or\n secret attributes are missing from the encoded payload.", "scope": {"holder": "OpenKMIP-PyKMIP", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/OpenKMIP/PyKMIP/blob/b51c5b044bd05f8c85a1d65d13a583a4d8fc1b0e/kmip/core/messages/payloads/signature_verify.py#L323-L381", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:OpenKMIP-PyKMIP:SignatureVerifyRequestPayload.write-5bcc422d97@held-out", "question": "Write the data encoding the SignatureVerify request payload to a\n stream.\n\n Args:\n output_stream (stream): A data stream in which to encode object\n data, supporting a write method; usually a BytearrayStream\n object.\n kmip_version (KMIPVersion): An enumeration defining the KMIP\n version with which the object will be encoded. Optional,\n defaults to KMIP 1.0.\n\n Raises:\n ValueError: Raised if the data attribute is not defined.", "scope": {"holder": "OpenKMIP-PyKMIP", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/OpenKMIP/PyKMIP/blob/b51c5b044bd05f8c85a1d65d13a583a4d8fc1b0e/kmip/core/messages/payloads/signature_verify.py#L568-L630", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:OpenKMIP-PyKMIP:SignatureVerifyResponsePayload.read-7e19f5ea0d@held-out", "question": "Read the data encoding the SignatureVerify response payload and decode\n it into its constituent parts.\n\n Args:\n input_stream (stream): A data stream containing encoded object\n data, supporting a read method; usually a BytearrayStream\n object.\n kmip_version (KMIPVersion): An enumeration defining the KMIP\n version with which the object will be decoded. Optional,\n defaults to KMIP 1.0.\n\n Raises:\n ValueError: Raised if the data attribute is missing from the\n encoded payload.", "scope": {"holder": "OpenKMIP-PyKMIP", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/OpenKMIP/PyKMIP/blob/b51c5b044bd05f8c85a1d65d13a583a4d8fc1b0e/kmip/pie/sqltypes.py#L61-L76", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:OpenKMIP-PyKMIP:UsageMaskType.process_result_value-f4bfe8859b@held-out", "question": "Returns a new list of enums.CryptographicUsageMask Enums. This converts\n the integer value into the list of enums.\n\n Args:\n value(int): The integer value stored in the database that is used\n to create the list of enums.CryptographicUsageMask Enums.\n dialect(string): SQL dialect", "scope": {"holder": "OpenKMIP-PyKMIP", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/OpenKMIP/PyKMIP/blob/b51c5b044bd05f8c85a1d65d13a583a4d8fc1b0e/kmip/core/primitives.py#L786-L796", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:OpenKMIP-PyKMIP:Boolean.validate-2e5775d83e@held-out", "question": "Verify that the value of the Boolean object is valid.\n\n Raises:\n TypeError: if the value is not of type bool.", "scope": {"holder": "OpenKMIP-PyKMIP", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/OpenKMIP/PyKMIP/blob/b51c5b044bd05f8c85a1d65d13a583a4d8fc1b0e/kmip/pie/objects.py#L424-L493", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:OpenKMIP-PyKMIP:Key.key_wrapping_data-8fb6849741@held-out", "question": "Retrieve all of the relevant key wrapping data fields and return them\n as a dictionary.", "scope": {"holder": "OpenKMIP-PyKMIP", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/OpenKMIP/PyKMIP/blob/b51c5b044bd05f8c85a1d65d13a583a4d8fc1b0e/kmip/core/messages/payloads/get_attribute_list.py#L250-L333", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:OpenKMIP-PyKMIP:GetAttributeListResponsePayload.read-56d8508b16@held-out", "question": "Read the data encoding the GetAttributeList response payload and\n decode it into its constituent parts.\n\n Args:\n input_buffer (stream): A data stream containing encoded object\n data, supporting a read method; usually a BytearrayStream\n object.\n kmip_version (KMIPVersion): An enumeration defining the KMIP\n version with which the object will be decoded. Optional,\n defaults to KMIP 1.0.\n\n Raises:\n InvalidKmipEncoding: Raised if the unique identifier or attribute\n names are missing from the encoded payload.", "scope": {"holder": "OpenKMIP-PyKMIP", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/OpenKMIP/PyKMIP/blob/b51c5b044bd05f8c85a1d65d13a583a4d8fc1b0e/kmip/services/server/auth/utils.py#L22-L32", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:OpenKMIP-PyKMIP:get_certificate_from_connection-310c94a0c7@held-out", "question": "Extract an X.509 certificate from a socket connection.", "scope": {"holder": "OpenKMIP-PyKMIP", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/OpenKMIP/PyKMIP/blob/b51c5b044bd05f8c85a1d65d13a583a4d8fc1b0e/kmip/core/messages/payloads/encrypt.py#L394-L448", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:OpenKMIP-PyKMIP:EncryptResponsePayload.read-4e4903c277@held-out", "question": "Read the data encoding the Encrypt response payload and decode it\n into its constituent parts.\n\n Args:\n input_stream (stream): A data stream containing encoded object\n data, supporting a read method; usually a BytearrayStream\n object.\n kmip_version (KMIPVersion): An enumeration defining the KMIP\n version with which the object will be decoded. Optional,\n defaults to KMIP 1.0.\n\n Raises:\n ValueError: Raised if the unique_identifier or data attributes\n are missing from the encoded payload.", "scope": {"holder": "OpenKMIP-PyKMIP", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/OpenKMIP/PyKMIP/blob/b51c5b044bd05f8c85a1d65d13a583a4d8fc1b0e/kmip/services/server/policy.py#L1118-L1136", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:OpenKMIP-PyKMIP:AttributePolicy.is_attribute_applicable_to_object_type-6e78a88f9e@held-out", "question": "Check if the attribute is supported by the given object type.\n\n Args:\n attribute (string): The name of the attribute (e.g., 'Name').\n Required.\n object_type (ObjectType): An ObjectType enumeration\n (e.g., ObjectType.SYMMETRIC_KEY). Required.\n Returns:\n bool: True if the attribute is applicable to the object type.\n False otherwise.", "scope": {"holder": "OpenKMIP-PyKMIP", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/OpenKMIP/PyKMIP/blob/b51c5b044bd05f8c85a1d65d13a583a4d8fc1b0e/kmip/core/messages/payloads/check.py#L469-L512", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:OpenKMIP-PyKMIP:CheckResponsePayload.write-ea51879d2b@held-out", "question": "Write the data encoding the Check response payload to a stream.\n\n Args:\n output_stream (stream): A data stream in which to encode object\n data, supporting a write method; usually a BytearrayStream\n object.\n kmip_version (KMIPVersion): An enumeration defining the KMIP\n version with which the object will be encoded. Optional,\n defaults to KMIP 1.0.\n\n Raises:\n ValueError: Raised if the data attribute is not defined.", "scope": {"holder": "OpenKMIP-PyKMIP", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/OpenKMIP/PyKMIP/blob/b51c5b044bd05f8c85a1d65d13a583a4d8fc1b0e/kmip/core/objects.py#L3574-L3597", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:OpenKMIP-PyKMIP:RevocationReason.read-71f5846a0c@held-out", "question": "Read the data encoding the RevocationReason object and decode it\n into its constituent parts.\n\n Args:\n istream (Stream): A data stream containing encoded object data,\n supporting a read method; usually a BytearrayStream object.\n kmip_version (KMIPVersion): An enumeration defining the KMIP\n version with which the object will be decoded. Optional,\n defaults to KMIP 1.0.", "scope": {"holder": "OpenKMIP-PyKMIP", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/OpenKMIP/PyKMIP/blob/b51c5b044bd05f8c85a1d65d13a583a4d8fc1b0e/kmip/core/objects.py#L4363-L4443", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:OpenKMIP-PyKMIP:RNGParameters.write-5514cd70eb@held-out", "question": "Write the RNGParameters structure encoding to the data stream.\n\n Args:\n output_buffer (stream): A data stream in which to encode\n Attributes structure data, supporting a write method.\n kmip_version (enum): A KMIPVersion enumeration defining the KMIP\n version with which the object will be encoded. Optional,\n defaults to KMIP 2.0.\n\n Raises:\n InvalidField: Raised if the RNG algorithm field is not defined.\n VersionNotSupported: Raised when a KMIP version is provided that\n does not support the RNGParameters structure.", "scope": {"holder": "OpenKMIP-PyKMIP", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/OpenKMIP/PyKMIP/blob/b51c5b044bd05f8c85a1d65d13a583a4d8fc1b0e/kmip/core/objects.py#L5082-L5260", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:OpenKMIP-PyKMIP:ValidationInformation.read-59b31a039d@held-out", "question": "Read the data encoding the ValidationInformation structure and decode\n it into its constituent parts.\n\n Args:\n input_buffer (stream): A data stream containing encoded object\n data, supporting a read method; usually a BytearrayStream\n object.\n kmip_version (KMIPVersion): An enumeration defining the KMIP\n version with which the object will be decoded. Optional,\n defaults to KMIP 2.0.\n\n Raises:\n InvalidKmipEncoding: Raised if the validation authority type,\n validation version major, validation type, and/or validation\n level are missing from the encoding.\n VersionNotSupported: Raised when a KMIP version is provided that\n does not support the ValidationInformation structure.", "scope": {"holder": "OpenKMIP-PyKMIP", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/OpenKMIP/PyKMIP/blob/b51c5b044bd05f8c85a1d65d13a583a4d8fc1b0e/kmip/core/messages/payloads/locate.py#L192-L269", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:OpenKMIP-PyKMIP:LocateRequestPayload.read-92d177acfb@held-out", "question": "Read the data encoding the Locate request payload and decode it into\n its constituent parts.\n\n Args:\n input_buffer (stream): A data buffer containing encoded object\n data, supporting a read method.\n kmip_version (KMIPVersion): An enumeration defining the KMIP\n version with which the object will be decoded. Optional,\n defaults to KMIP 1.0.\n\n Raises:\n InvalidKmipEncoding: Raised if the attributes structure is missing\n from the encoded payload for KMIP 2.0+ encodings.", "scope": {"holder": "OpenKMIP-PyKMIP", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/OpenKMIP/PyKMIP/blob/b51c5b044bd05f8c85a1d65d13a583a4d8fc1b0e/kmip/services/server/crypto/engine.py#L290-L377", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:OpenKMIP-PyKMIP:CryptographyEngine.encrypt-d198b3f251@held-out", "question": "Encrypt data using symmetric or asymmetric encryption.\n\n Args:\n encryption_algorithm (CryptographicAlgorithm): An enumeration\n specifying the encryption algorithm to use for encryption.\n encryption_key (bytes): The bytes of the encryption key to use for\n encryption.\n plain_text (bytes): The bytes to be encrypted.\n cipher_mode (BlockCipherMode): An enumeration specifying the\n block cipher mode to use with the encryption algorithm.\n Required in the general case. Optional if the encryption\n algorithm is RC4 (aka ARC4). If optional, defaults to None.\n padding_method (PaddingMethod): An enumeration specifying the\n padding method to use on the data before encryption. Required\n if the cipher mode is for block ciphers (e.g., CBC, ECB).\n Optional otherwise, defaults to None.\n iv_nonce (bytes): The IV/nonce value to use to initialize the mode\n of the encryption algorithm. Optional, defaults to None. If\n required and not provided, it will be autogenerated and\n returned with the cipher text.\n hashing_algorithm (HashingAlgorithm): An enumeration specifying\n the hashing algorithm to use with the encryption algorithm,\n if needed. Required for OAEP-based asymmetric encryption.\n Optional, defaults to None.\n\n Returns:\n dict: A dictionary containing the encrypted data, with at least\n the following key/value fields:\n * cipher_text - the bytes of the encrypted data\n * iv_nonce - the bytes of the IV/counter/nonce used if it\n was needed by the encryption scheme and if it was\n automatically generated for the encryption\n\n Raises:\n InvalidField: Raised when the algorithm is unsupported or the\n length is incompatible with the algorithm.\n CryptographicFailure: Raised when the key generation process\n fails.\n\n Example:\n >>> engine = CryptographyEngine()\n >>> result = engine.encrypt(\n ... encryption_algorithm=CryptographicAlgorithm.AES,\n ... encryption_key=(\n ... b'\\xF3\\x96\\xE7\\x1C\\xCF\\xCD\\xEC\\x1F'\n ... b'\\xFC\\xE2\\x8E\\xA6\\xF8\\x74\\x28\\xB0'\n ... ),\n ... plain_text=(\n ... b'\\x00\\x01\\x02\\x03\\x04\\x05\\x06\\x07'\n ... b'\\x08\\x09\\x0A\\x0B\\x0C\\x0D\\x0E\\x0F'\n ... ),\n ... cipher_mode=BlockCipherMode.CBC,\n ... padding_method=PaddingMethod.ANSI_X923,\n ... )\n >>> result.get('cipher_text')\n b'\\x18[\\xb9y\\x1bL\\xd1\\x8f\\x9a\\xa0e\\x02b\\xa3=c'\n >>> result.iv_counter_nonce\n b'8qA\\x05\\xc4\\x86\\x03\\xd9=\\xef\\xdf\\xb8ke\\x9a\\xa2'", "scope": {"holder": "OpenKMIP-PyKMIP", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/OpenKMIP/PyKMIP/blob/b51c5b044bd05f8c85a1d65d13a583a4d8fc1b0e/kmip/services/server/crypto/engine.py#L882-L944", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:OpenKMIP-PyKMIP:CryptographyEngine._create_rsa_key_pair-6d16eee4d1@held-out", "question": "Create an RSA key pair.\n\n Args:\n length(int): The length of the keys to be created. This value must\n be compliant with the constraints of the provided algorithm.\n public_exponent(int): The value of the public exponent needed to\n generate the keys. Usually a small Fermat prime number.\n Optional, defaults to 65537.\n\n Returns:\n dict: A dictionary containing the public key data, with the\n following key/value fields:\n * value - the bytes of the key\n * format - a KeyFormatType enumeration for the bytes format\n * public_exponent - the public exponent integer\n dict: A dictionary containing the private key data, identical in\n structure to the one above.\n\n Raises:\n CryptographicFailure: Raised when the key generation process\n fails.", "scope": {"holder": "OpenKMIP-PyKMIP", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/OpenKMIP/PyKMIP/blob/b51c5b044bd05f8c85a1d65d13a583a4d8fc1b0e/kmip/services/server/crypto/engine.py#L1191-L1217", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:OpenKMIP-PyKMIP:CryptographyEngine._create_RSA_private_key-e9e1113dfa@held-out", "question": "Instantiates an RSA key from bytes.\n\n Args:\n bytes (byte string): Bytes of RSA private key.\n Returns:\n private_key\n (cryptography.hazmat.primitives.asymmetric.rsa.RSAPrivateKey):\n RSA private key created from key bytes.", "scope": {"holder": "OpenKMIP-PyKMIP", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/OpenKMIP/PyKMIP/blob/b51c5b044bd05f8c85a1d65d13a583a4d8fc1b0e/kmip/core/messages/contents.py#L146-L182", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:OpenKMIP-PyKMIP:ProtocolVersion.write-e0c4069e5c@held-out", "question": "Write the data encoding the ProtocolVersion struct to a stream.\n\n Args:\n output_stream (stream): A data stream in which to encode object\n data, supporting a write method; usually a BytearrayStream\n object.\n kmip_version (KMIPVersion): An enumeration defining the KMIP\n version with which the object will be encoded. Optional,\n defaults to KMIP 1.0.\n\n Raises:\n ValueError: Raised if the data attribute is not defined.", "scope": {"holder": "OpenKMIP-PyKMIP", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/OpenKMIP/PyKMIP/blob/b51c5b044bd05f8c85a1d65d13a583a4d8fc1b0e/kmip/core/messages/payloads/archive.py#L196-L228", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:OpenKMIP-PyKMIP:ArchiveResponsePayload.read-fc6c6451e3@held-out", "question": "Read the data encoding the Archive response payload and decode it\n into its constituent parts.\n\n Args:\n input_stream (stream): A data stream containing encoded object\n data, supporting a read method; usually a BytearrayStream\n object.\n kmip_version (KMIPVersion): An enumeration defining the KMIP\n version with which the object will be decoded. Optional,\n defaults to KMIP 1.0.\n\n Raises:\n ValueError: Raised if the data attribute is missing from the\n encoded payload.", "scope": {"holder": "OpenKMIP-PyKMIP", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/OpenKMIP/PyKMIP/blob/b51c5b044bd05f8c85a1d65d13a583a4d8fc1b0e/kmip/core/messages/payloads/rekey.py#L300-L344", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:OpenKMIP-PyKMIP:RekeyResponsePayload.read-f0f8da09fa@held-out", "question": "Read the data encoding the Rekey response payload and decode it into\n its constituent parts.\n\n Args:\n input_stream (stream): A data stream containing encoded object\n data, supporting a read method; usually a BytearrayStream\n object.\n kmip_version (KMIPVersion): An enumeration defining the KMIP\n version with which the object will be decoded. Optional,\n defaults to KMIP 1.0.\n\n Raises:\n ValueError: Raised if the unique identifier attribute is missing\n from the encoded payload.", "scope": {"holder": "OpenKMIP-PyKMIP", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/OpenKMIP/PyKMIP/blob/b51c5b044bd05f8c85a1d65d13a583a4d8fc1b0e/kmip/pie/client.py#L176-L191", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:OpenKMIP-PyKMIP:ProxyKmipClient.close-2b5e3abb26@held-out", "question": "Close the client connection.\n\n Raises:\n Exception: if an error occurs while trying to close the connection", "scope": {"holder": "OpenKMIP-PyKMIP", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/OpenKMIP/PyKMIP/blob/b51c5b044bd05f8c85a1d65d13a583a4d8fc1b0e/kmip/pie/client.py#L194-L254", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:OpenKMIP-PyKMIP:ProxyKmipClient.create-1b6b7903ee@held-out", "question": "Create a symmetric key on a KMIP appliance.\n\n Args:\n algorithm (CryptographicAlgorithm): An enumeration defining the\n algorithm to use to generate the symmetric key.\n length (int): The length in bits for the symmetric key.\n operation_policy_name (string): The name of the operation policy\n to use for the new symmetric key. Optional, defaults to None\n name (string): The name to give the key. Optional, defaults to None\n cryptographic_usage_mask (list): list of enumerations of crypto\n usage mask passing to the symmetric key. Optional, defaults to\n None\n\n Returns:\n string: The uid of the newly created symmetric key.\n\n Raises:\n ClientConnectionNotOpen: if the client connection is unusable\n KmipOperationFailure: if the operation result is a failure\n TypeError: if the input arguments are invalid", "scope": {"holder": "OpenKMIP-PyKMIP", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/OpenKMIP/PyKMIP/blob/b51c5b044bd05f8c85a1d65d13a583a4d8fc1b0e/kmip/pie/client.py#L377-L436", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:OpenKMIP-PyKMIP:ProxyKmipClient.register-e71971a391@held-out", "question": "Register a managed object with a KMIP appliance.\n\n Args:\n managed_object (ManagedObject): A managed object to register. An\n instantiatable subclass of ManagedObject from the Pie API.\n\n Returns:\n string: The uid of the newly registered managed object.\n\n Raises:\n ClientConnectionNotOpen: if the client connection is unusable\n KmipOperationFailure: if the operation result is a failure\n TypeError: if the input argument is invalid", "scope": {"holder": "OpenKMIP-PyKMIP", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/OpenKMIP/PyKMIP/blob/b51c5b044bd05f8c85a1d65d13a583a4d8fc1b0e/kmip/pie/client.py#L921-L951", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:OpenKMIP-PyKMIP:ProxyKmipClient.activate-67a9879d1c@held-out", "question": "Activate a managed object stored by a KMIP appliance.\n\n Args:\n uid (string): The unique ID of the managed object to activate.\n Optional, defaults to None.\n\n Returns:\n None\n\n Raises:\n ClientConnectionNotOpen: if the client connection is unusable\n KmipOperationFailure: if the operation result is a failure\n TypeError: if the input argument is invalid", "scope": {"holder": "OpenKMIP-PyKMIP", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/OpenKMIP/PyKMIP/blob/b51c5b044bd05f8c85a1d65d13a583a4d8fc1b0e/kmip/pie/client.py#L1514-L1544", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:OpenKMIP-PyKMIP:ProxyKmipClient._build_mac_signature_key_information-e47f946a1e@held-out", "question": "Build an MACSignatureKeyInformation struct from a dictionary.\n\n Args:\n value (dict): A dictionary containing the key/value pairs for a\n MACSignatureKeyInformation struct.\n\n Returns:\n MACSignatureInformation: a MACSignatureKeyInformation struct\n\n Raises:\n TypeError: if the input argument is invalid", "scope": {"holder": "OpenKMIP-PyKMIP", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/OpenKMIP/PyKMIP/blob/b51c5b044bd05f8c85a1d65d13a583a4d8fc1b0e/kmip/core/messages/payloads/get_attributes.py#L402-L452", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:OpenKMIP-PyKMIP:GetAttributesResponsePayload.write-85015f6eb9@held-out", "question": "Write the data encoding the GetAttributes response payload to a\n stream.\n\n Args:\n output_buffer (stream): A data stream in which to encode object\n data, supporting a write method; usually a BytearrayStream\n object.\n kmip_version (KMIPVersion): An enumeration defining the KMIP\n version with which the object will be encoded. Optional,\n defaults to KMIP 1.0.", "scope": {"holder": "OpenKMIP-PyKMIP", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/takluyver/entrypoints/blob/d7db29fd6136f86498d8c374f531d4c198d66bf6/entrypoints.py#L205-L217", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:takluyver-entrypoints:get_single-1edac3f499@held-out", "question": "Find a single entry point.\n\n Returns an :class:`EntryPoint` object, or raises :exc:`NoSuchEntryPoint`\n if no match is found.", "scope": {"holder": "takluyver-entrypoints", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/takluyver/entrypoints/blob/d7db29fd6136f86498d8c374f531d4c198d66bf6/entrypoints.py#L219-L228", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:takluyver-entrypoints:get_group_named-acf60c93c8@held-out", "question": "Find a group of entry points with unique names.\n\n Returns a dictionary of names to :class:`EntryPoint` objects.", "scope": {"holder": "takluyver-entrypoints", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/hustlzp/Flask-Boost/blob/d0308408ebb248dd752b77123b845f8ec637fab2/flask_boost/project/application/forms/_helper.py#L6-L13", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:hustlzp-Flask-Boost:check_url-b9d8619f32@held-out", "question": "Check url schema.", "scope": {"holder": "hustlzp-Flask-Boost", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/hustlzp/Flask-Boost/blob/d0308408ebb248dd752b77123b845f8ec637fab2/flask_boost/project/application/utils/security.py#L6-L10", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:hustlzp-Flask-Boost:encode-9d65177261@held-out", "question": "Encode something with SECRET_KEY.", "scope": {"holder": "hustlzp-Flask-Boost", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Azure/Azure-MachineLearning-ClientLibrary-Python/blob/d1211b289747671898eb063013e0dc53d3c80acd/azureml/serialization.py#L130-L153", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Azure-Azure-MachineLearning-ClientLibrary-Python:deserialize_dataframe-f539ba8239@held-out", "question": "Deserialize a dataframe.\n\n Parameters\n ----------\n reader : file\n File-like object to read from. Must be opened in binary mode.\n data_type_id : dict\n Serialization format of the raw data.\n See the azureml.DataTypeIds class for constants.\n\n Returns\n -------\n pandas.DataFrame\n Dataframe object.", "scope": {"holder": "Azure-Azure-MachineLearning-ClientLibrary-Python", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Azure/Azure-MachineLearning-ClientLibrary-Python/blob/d1211b289747671898eb063013e0dc53d3c80acd/azureml/__init__.py#L509-L545", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Azure-Azure-MachineLearning-ClientLibrary-Python:Datasets.add_from_raw_data-8ca3e4c719@held-out", "question": "Upload already serialized raw data as a new dataset.\n\n Parameters\n ----------\n raw_data: bytes\n Dataset contents to upload.\n data_type_id : str\n Serialization format of the raw data.\n Supported formats are:\n 'PlainText'\n 'GenericCSV'\n 'GenericTSV'\n 'GenericCSVNoHeader'\n 'GenericTSVNoHeader'\n 'ARFF'\n See the azureml.DataTypeIds class for constants.\n name : str\n Name for the new dataset.\n description : str\n Description for the new dataset.\n\n Returns\n -------\n SourceDataset\n Dataset that was just created.\n Use open(), read_as_binary(), read_as_text() or to_dataframe() on\n the dataset object to get its contents as a stream, bytes, str or\n pandas DataFrame.", "scope": {"holder": "Azure-Azure-MachineLearning-ClientLibrary-Python", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Azure/Azure-MachineLearning-ClientLibrary-Python/blob/d1211b289747671898eb063013e0dc53d3c80acd/azureml/services.py#L588-L602", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Azure-Azure-MachineLearning-ClientLibrary-Python:published.map-1932800b29@held-out", "question": "maps the function onto multiple inputs. The input should be multiple sequences. The\nsequences will be zipped together forming the positional arguments for the call. This is\nequivalent to map(func, ...) but is executed with a single network call.", "scope": {"holder": "Azure-Azure-MachineLearning-ClientLibrary-Python", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/jrfonseca/xdot.py/blob/6248c81c21a0fe825089311b17f2c302eea614a2/xdot/ui/colors.py#L308-L348", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:jrfonseca-xdot.py:lookup_color-6d459c2c4f@held-out", "question": "Return RGBA values of color c\n\n c should be either an X11 color or a brewer color set and index\n e.g. \"navajowhite\", \"greens3/2\"", "scope": {"holder": "jrfonseca-xdot.py", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/jrfonseca/xdot.py/blob/6248c81c21a0fe825089311b17f2c302eea614a2/xdot/ui/elements.py#L357-L383", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:jrfonseca-xdot.py:BezierShape._cubic_bernstein_extrema-61b5277fa0@held-out", "question": "Find extremas of a function of real domain defined by evaluating\n a cubic bernstein polynomial of given bernstein coefficients.", "scope": {"holder": "jrfonseca-xdot.py", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/idlesign/django-sitetree/blob/61de4608e6e415247c75fe8691027d7c4ed0d1e7/sitetree/sitetreeapp.py#L472-L493", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:idlesign-django-sitetree:SiteTree.current_app_is_admin-e46eeb831b@held-out", "question": "Returns boolean whether current application is Admin contrib.\n\n :rtype: bool", "scope": {"holder": "idlesign-django-sitetree", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/idlesign/django-sitetree/blob/61de4608e6e415247c75fe8691027d7c4ed0d1e7/sitetree/sitetreeapp.py#L581-L597", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:idlesign-django-sitetree:SiteTree.calculate_item_depth-7d9b377151@held-out", "question": "Calculates depth of the item in the tree.\n\n :param str|unicode tree_alias:\n :param int item_id:\n :param int depth:\n :rtype: int", "scope": {"holder": "idlesign-django-sitetree", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/idlesign/django-sitetree/blob/61de4608e6e415247c75fe8691027d7c4ed0d1e7/sitetree/sitetreeapp.py#L608-L649", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:idlesign-django-sitetree:SiteTree.get_tree_current_item-4ad93c821a@held-out", "question": "Resolves current tree item of 'tree_alias' tree matching current\n request path against URL of given tree item.\n\n :param str|unicode tree_alias:\n :rtype: TreeItemBase", "scope": {"holder": "idlesign-django-sitetree", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/idlesign/django-sitetree/blob/61de4608e6e415247c75fe8691027d7c4ed0d1e7/sitetree/sitetreeapp.py#L1007-L1022", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:idlesign-django-sitetree:SiteTree.update_has_children-662153b010@held-out", "question": "Updates 'has_children' attribute for tree items inplace.\n\n :param str|unicode tree_alias:\n :param list tree_items:\n :param str|unicode navigation_type: sitetree, breadcrumbs, menu", "scope": {"holder": "idlesign-django-sitetree", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/idlesign/django-sitetree/blob/61de4608e6e415247c75fe8691027d7c4ed0d1e7/sitetree/templatetags/sitetree.py#L209-L219", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:idlesign-django-sitetree:SimpleNode.for_tag-1fe31c8a3f@held-out", "question": "Node constructor to be used in tags.", "scope": {"holder": "idlesign-django-sitetree", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/idlesign/django-sitetree/blob/61de4608e6e415247c75fe8691027d7c4ed0d1e7/sitetree/admin.py#L34-L39", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:idlesign-django-sitetree:get_model_url_name-b135f3ebdf@held-out", "question": "Returns a URL for a given Tree admin page type.", "scope": {"holder": "idlesign-django-sitetree", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/idlesign/django-sitetree/blob/61de4608e6e415247c75fe8691027d7c4ed0d1e7/sitetree/admin.py#L279-L295", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:idlesign-django-sitetree:redirects_handler-e3e6e3d9e2@held-out", "question": "Fixes Admin contrib redirects compatibility problems\n introduced in Django 1.4 by url handling changes.", "scope": {"holder": "idlesign-django-sitetree", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/idlesign/django-sitetree/blob/61de4608e6e415247c75fe8691027d7c4ed0d1e7/sitetree/admin.py#L141-L151", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:idlesign-django-sitetree:TreeItemAdmin.response_add-7a6f51eaec@held-out", "question": "Redirects to the appropriate items' 'continue' page on item add.\n\n As we administer tree items within tree itself, we\n should make some changes to redirection process.", "scope": {"holder": "idlesign-django-sitetree", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/idlesign/django-sitetree/blob/61de4608e6e415247c75fe8691027d7c4ed0d1e7/sitetree/admin.py#L232-L262", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:idlesign-django-sitetree:TreeItemAdmin.item_move-358f807159@held-out", "question": "Moves item up or down by swapping 'sort_order' field values of neighboring items.", "scope": {"holder": "idlesign-django-sitetree", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/pgjones/hypercorn/blob/ef93d741fe246846a127f9318b54505ac65f1ae7/hypercorn/config.py#L239-L253", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:pgjones-hypercorn:Config.from_pyfile-290fb0ca9a@held-out", "question": "Create a configuration from a Python file.\n\n .. code-block:: python\n\n Config.from_pyfile('hypercorn_config.py')\n\n Arguments:\n filename: The filename which gives the path to the file.", "scope": {"holder": "pgjones-hypercorn", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Yelp/py_zipkin/blob/0944d9a3fb1f1798dbb276694aeed99f2b4283ba/py_zipkin/util.py#L17-L29", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Yelp-py_zipkin:generate_random_128bit_string-0cd1e31559@held-out", "question": "Returns a 128 bit UTF-8 encoded string. Follows the same conventions\n as generate_random_64bit_string().\n\n The upper 32 bits are the current time in epoch seconds, and the\n lower 96 bits are random. This allows for AWS X-Ray `interop\n <https://github.com/openzipkin/zipkin/issues/1754>`_\n\n :returns: 32-character hex string", "scope": {"holder": "Yelp-py_zipkin", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Yelp/py_zipkin/blob/0944d9a3fb1f1798dbb276694aeed99f2b4283ba/py_zipkin/encoding/_decoders.py#L82-L108", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Yelp-py_zipkin:_V1ThriftDecoder._convert_from_thrift_endpoint-67fb94b490@held-out", "question": "Accepts a thrift decoded endpoint and converts it to an Endpoint.\n\n :param thrift_endpoint: thrift encoded endpoint\n :type thrift_endpoint: thrift endpoint\n :returns: decoded endpoint\n :rtype: Encoding", "scope": {"holder": "Yelp-py_zipkin", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/WoLpH/mt940/blob/fd71c88f7ec8372f4194f831f4c29c6f9bd9d0eb/mt940/models.py#L375-L458", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:WoLpH-mt940:Transactions.parse-1a2e0267fb@held-out", "question": "Parses mt940 data, expects a string with data\n\n Args:\n data (str): The MT940 data\n\n Returns: :py:class:`list` of :py:class:`Transaction`", "scope": {"holder": "WoLpH-mt940", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/DiscordBotList/DBL-Python-Library/blob/c1461ae0acc644cdeedef8fd6b5e36f76d81c1aa/dbl/http.py#L190-L194", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:DiscordBotList-DBL-Python-Library:HTTPClient.get_bots-1dfa288541@held-out", "question": "Gets an object of bots on DBL", "scope": {"holder": "DiscordBotList-DBL-Python-Library", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/DiscordBotList/DBL-Python-Library/blob/c1461ae0acc644cdeedef8fd6b5e36f76d81c1aa/dbl/client.py#L96-L115", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:DiscordBotList-DBL-Python-Library:Client.post_guild_count-82a9eb42d7@held-out", "question": "This function is a coroutine.\n\n Posts the guild count to discordbots.org\n\n .. _0 based indexing : https://en.wikipedia.org/wiki/Zero-based_numbering\n\n Parameters\n ==========\n\n shard_count: int[Optional]\n The total number of shards.\n shard_no: int[Optional]\n The index of the current shard. DBL uses `0 based indexing`_ for shards.", "scope": {"holder": "DiscordBotList-DBL-Python-Library", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/DiscordBotList/DBL-Python-Library/blob/c1461ae0acc644cdeedef8fd6b5e36f76d81c1aa/dbl/client.py#L159-L179", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:DiscordBotList-DBL-Python-Library:Client.get_bot_info-dffe607a2c@held-out", "question": "This function is a coroutine.\n\n Gets information about a bot from discordbots.org\n\n Parameters\n ==========\n\n bot_id: int[Optional]\n The bot_id of the bot you want to lookup.\n\n Returns\n =======\n\n bot_info: dict\n Information on the bot you looked up.\n https://discordbots.org/api/docs#bots", "scope": {"holder": "DiscordBotList-DBL-Python-Library", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/hdima/erlport/blob/246b7722d62b87b48be66d9a871509a537728962/priv/python3/erlport/erlproto.py#L84-L95", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:hdima-erlport:Port.read-5da3b55397@held-out", "question": "Read incoming message.", "scope": {"holder": "hdima-erlport", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/draios/python-sdc-client/blob/47f83415842048778939b90944f64386a3bcb205/sdcclient/_secure.py#L533-L551", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:draios-python-sdc-client:SdSecureClient.create_default_policies-6f8f675b54@held-out", "question": "**Description**\n Create a set of default policies using the current system falco rules file as a reference. For every falco rule in the system\n falco rules file, one policy will be created. The policy will take the name and description from the name and description of\n the corresponding falco rule. If a policy already exists with the same name, no policy is added or modified. Existing\n policies will be unchanged.\n\n **Arguments**\n - None\n\n **Success Return Value**\n JSON containing details on any new policies that were added.\n\n **Example**\n `examples/create_default_policies.py <https://github.com/draios/python-sdc-client/blob/master/examples/create_default_policies.py>`_", "scope": {"holder": "draios-python-sdc-client", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/draios/python-sdc-client/blob/47f83415842048778939b90944f64386a3bcb205/sdcclient/_secure.py#L631-L657", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:draios-python-sdc-client:SdSecureClient.get_policy-54bf25c2e8@held-out", "question": "**Description**\n Find the policy with name <name> and return its json description.\n\n **Arguments**\n - name: the name of the policy to fetch\n\n **Success Return Value**\n A JSON object containing the description of the policy. If there is no policy with\n the given name, returns False.\n\n **Example**\n `examples/get_policy.py <https://github.com/draios/python-sdc-client/blob/master/examples/get_policy.py>`_", "scope": {"holder": "draios-python-sdc-client", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/draios/python-sdc-client/blob/47f83415842048778939b90944f64386a3bcb205/sdcclient/_secure.py#L712-L735", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:draios-python-sdc-client:SdSecureClient.delete_policy_name-4f76f2eb63@held-out", "question": "**Description**\n Delete the policy with the given name.\n\n **Arguments**\n - name: the name of the policy to delete\n\n **Success Return Value**\n The JSON object representing the now-deleted policy.\n\n **Example**\n `examples/delete_policy.py <https://github.com/draios/python-sdc-client/blob/master/examples/delete_policy.py>`_", "scope": {"holder": "draios-python-sdc-client", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/draios/python-sdc-client/blob/47f83415842048778939b90944f64386a3bcb205/sdcclient/_secure.py#L836-L847", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:draios-python-sdc-client:SdSecureClient.delete_compliance_task-8d47101ea2@held-out", "question": "**Description**\n Delete the compliance task with the given id\n\n **Arguments**\n - id: the id of the compliance task to delete", "scope": {"holder": "draios-python-sdc-client", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/draios/python-sdc-client/blob/47f83415842048778939b90944f64386a3bcb205/sdcclient/_monitor.py#L191-L211", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:draios-python-sdc-client:SdMonitorClient.delete_alert-4202cb75f6@held-out", "question": "**Description**\n Deletes an alert.\n\n **Arguments**\n - **alert**: the alert dictionary as returned by :func:`~SdcClient.get_alerts`.\n\n **Success Return Value**\n ``None``.\n\n **Example**\n `examples/delete_alert.py <https://github.com/draios/python-sdc-client/blob/master/examples/delete_alert.py>`_", "scope": {"holder": "draios-python-sdc-client", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/draios/python-sdc-client/blob/47f83415842048778939b90944f64386a3bcb205/sdcclient/_monitor.py#L811-L866", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:draios-python-sdc-client:SdMonitorClient.convert_scope_string_to_expression-50d3b46be6@held-out", "question": "**Description**\n Internal function to convert a filter string to a filter object to be used with dashboards.", "scope": {"holder": "draios-python-sdc-client", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/draios/python-sdc-client/blob/47f83415842048778939b90944f64386a3bcb205/sdcclient/_common.py#L521-L563", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:draios-python-sdc-client:_SdcCommon.create_sysdig_capture-ce35d1816b@held-out", "question": "**Description**\n Create a new sysdig capture. The capture will be immediately started.\n\n **Arguments**\n - **hostname**: the hostname of the instrumented host where the capture will be taken.\n - **capture_name**: the name of the capture.\n - **duration**: the duration of the capture, in seconds.\n - **capture_filter**: a sysdig filter expression.\n - **folder**: directory in the S3 bucket where the capture will be saved.\n\n **Success Return Value**\n A dictionary showing the details of the new capture.\n\n **Example**\n `examples/create_sysdig_capture.py <https://github.com/draios/python-sdc-client/blob/master/examples/create_sysdig_capture.py>`_", "scope": {"holder": "draios-python-sdc-client", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/draios/python-sdc-client/blob/47f83415842048778939b90944f64386a3bcb205/sdcclient/_common.py#L877-L895", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:draios-python-sdc-client:_SdcCommon.delete_team-ba24e25ded@held-out", "question": "**Description**\n Deletes a team from Sysdig Monitor.\n\n **Arguments**\n - **name**: the name of the team that will be deleted from Sysdig Monitor\n\n **Example**\n `examples/user_team_mgmt.py <https://github.com/draios/python-sdc-client/blob/master/examples/user_team_mgmt.py>`_", "scope": {"holder": "draios-python-sdc-client", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/draios/python-sdc-client/blob/47f83415842048778939b90944f64386a3bcb205/sdcclient/_scanning.py#L122-L137", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:draios-python-sdc-client:SdScanningClient.query_image_content-cf47f5ffaa@held-out", "question": "**Description**\n Find the image with the tag <image> and return its content.\n\n **Arguments**\n - image: Input image can be in the following formats: registry/repo:tag\n - content_type: The content type can be one of the following types:\n - os: Operating System Packages\n - npm: Node.JS NPM Module\n - gem: Ruby GEM\n - files: Files\n\n **Success Return Value**\n A JSON object representing the image content.", "scope": {"holder": "draios-python-sdc-client", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/draios/python-sdc-client/blob/47f83415842048778939b90944f64386a3bcb205/sdcclient/_scanning.py#L152-L164", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:draios-python-sdc-client:SdScanningClient.query_image_vuln-5aa2c095af@held-out", "question": "**Description**\n Find the image with the tag <image> and return its vulnerabilities.\n\n **Arguments**\n - image: Input image can be in the following formats: registry/repo:tag\n - vuln_type: Vulnerability type can be one of the following types:\n - os: CVE/distro vulnerabilities against operating system packages\n\n **Success Return Value**\n A JSON object representing the image vulnerabilities.", "scope": {"holder": "draios-python-sdc-client", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/draios/python-sdc-client/blob/47f83415842048778939b90944f64386a3bcb205/sdcclient/_scanning.py#L654-L683", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:draios-python-sdc-client:SdScanningClient.list_runtime-f9581073e1@held-out", "question": "**Description**\n List runtime containers\n\n **Arguments**\n - scope: An AND-composed string of predicates that selects the scope in which the alert will be applied. (like: 'host.domain = \"example.com\" and container.image != \"alpine:latest\"')\n - skip_policy_evaluation: If true, no policy evaluations will be triggered for the images.\n - start_time: Start of the time range (integer of unix time).\n - end_time: End of the time range (integer of unix time).\n\n **Success Return Value**\n A JSON object representing the list of runtime containers.", "scope": {"holder": "draios-python-sdc-client", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/andreikop/python-ws-discovery/blob/a7b852cf43115c6f986e509b1870d6963e76687f/wsdiscovery/daemon.py#L232-L245", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:andreikop-python-ws-discovery:NetworkingThread._sendPendingMessages-96119d06b0@held-out", "question": "Method sleeps, if nothing to do", "scope": {"holder": "andreikop-python-ws-discovery", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/wagtail/django-modelcluster/blob/bfc8bd755af0ddd49e2aee2f2ca126921573d38b/modelcluster/forms.py#L125-L165", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:wagtail-django-modelcluster:BaseChildFormSet.validate_unique-d27593d751@held-out", "question": "This clean method will check for unique_together condition", "scope": {"holder": "wagtail-django-modelcluster", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/iotaledger/iota.lib.py/blob/97cdd1e241498446b46157b79b2a1ea2ec6d387a/iota/bin/__init__.py#L109-L151", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:iotaledger-iota.lib.py:IotaCommandLineApp.create_argument_parser-87229ef1e0@held-out", "question": "Returns the argument parser that will be used to interpret\n arguments and options from argv.", "scope": {"holder": "iotaledger-iota.lib.py", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/iotaledger/iota.lib.py/blob/97cdd1e241498446b46157b79b2a1ea2ec6d387a/iota/trits.py#L21-L44", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:iotaledger-iota.lib.py:add_trits-22fabf934c@held-out", "question": "Adds two sequences of trits together.\n\n The result is a list of trits equal in length to the longer of the\n two sequences.\n\n .. note::\n Overflow is possible.\n\n For example, ``add_trits([1], [1])`` returns ``[-1]``.", "scope": {"holder": "iotaledger-iota.lib.py", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/iotaledger/iota.lib.py/blob/97cdd1e241498446b46157b79b2a1ea2ec6d387a/iota/trits.py#L57-L90", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:iotaledger-iota.lib.py:trits_from_int-001dca98ec@held-out", "question": "Returns a trit representation of an integer value.\n\n :param n:\n Integer value to convert.\n\n :param pad:\n Ensure the result has at least this many trits.\n\n References:\n\n - https://dev.to/buntine/the-balanced-ternary-machines-of-soviet-russia\n - https://en.wikipedia.org/wiki/Balanced_ternary\n - https://rosettacode.org/wiki/Balanced_ternary#Python", "scope": {"holder": "iotaledger-iota.lib.py", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/iotaledger/iota.lib.py/blob/97cdd1e241498446b46157b79b2a1ea2ec6d387a/iota/api.py#L249-L289", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:iotaledger-iota.lib.py:StrictIota.find_transactions-bd4487e5c0@held-out", "question": "Find the transactions which match the specified input and\n return.\n\n All input values are lists, for which a list of return values\n (transaction hashes), in the same order, is returned for all\n individual elements.\n\n Using multiple of these input fields returns the intersection of\n the values.\n\n :param bundles:\n List of bundle IDs.\n\n :param addresses:\n List of addresses.\n\n :param tags:\n List of tags.\n\n :param approvees:\n List of approvee transaction IDs.\n\n References:\n\n - https://iota.readme.io/docs/findtransactions", "scope": {"holder": "iotaledger-iota.lib.py", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/iotaledger/iota.lib.py/blob/97cdd1e241498446b46157b79b2a1ea2ec6d387a/iota/api.py#L838-L898", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:iotaledger-iota.lib.py:Iota.prepare_transfer-6f91e6bb7e@held-out", "question": "Prepares transactions to be broadcast to the Tangle, by\n generating the correct bundle, as well as choosing and signing\n the inputs (for value transfers).\n\n :param transfers:\n Transaction objects to prepare.\n\n :param inputs:\n List of addresses used to fund the transfer.\n Ignored for zero-value transfers.\n\n If not provided, addresses will be selected automatically by\n scanning the Tangle for unspent inputs. Depending on how\n many transfers you've already sent with your seed, this\n process could take awhile.\n\n :param change_address:\n If inputs are provided, any unspent amount will be sent to\n this address.\n\n If not specified, a change address will be generated\n automatically.\n\n :param security_level:\n Number of iterations to use when generating new addresses\n (see :py:meth:`get_new_addresses`).\n\n This value must be between 1 and 3, inclusive.\n\n If not set, defaults to\n :py:attr:`AddressGenerator.DEFAULT_SECURITY_LEVEL`.\n\n :return:\n Dict with the following structure::\n\n {\n 'trytes': List[TransactionTrytes],\n Raw trytes for the transactions in the bundle,\n ready to be provided to :py:meth:`send_trytes`.\n }\n\n References:\n\n - https://github.com/iotaledger/wiki/blob/master/api-proposal.md#preparetransfers", "scope": {"holder": "iotaledger-iota.lib.py", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/iotaledger/iota.lib.py/blob/97cdd1e241498446b46157b79b2a1ea2ec6d387a/iota/adapter/__init__.py#L171-L191", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:iotaledger-iota.lib.py:BaseAdapter.send_request-a9e6d1a87a@held-out", "question": "Sends an API request to the node.\n\n :param payload:\n JSON payload.\n\n :param kwargs:\n Additional keyword arguments for the adapter.\n\n :return:\n Decoded response from the node.\n\n :raise:\n - :py:class:`BadApiResponse` if a non-success response was\n received.", "scope": {"holder": "iotaledger-iota.lib.py", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/iotaledger/iota.lib.py/blob/97cdd1e241498446b46157b79b2a1ea2ec6d387a/iota/codecs.py#L61-L78", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:iotaledger-iota.lib.py:AsciiTrytesCodec.get_codec_info-69f854594e@held-out", "question": "Returns information used by the codecs library to configure the\n codec for use.", "scope": {"holder": "iotaledger-iota.lib.py", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/iotaledger/iota.lib.py/blob/97cdd1e241498446b46157b79b2a1ea2ec6d387a/iota/codecs.py#L116-L193", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:iotaledger-iota.lib.py:AsciiTrytesCodec.decode-63df24b9d1@held-out", "question": "Decodes a tryte string into bytes.", "scope": {"holder": "iotaledger-iota.lib.py", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/iotaledger/iota.lib.py/blob/97cdd1e241498446b46157b79b2a1ea2ec6d387a/iota/transaction/base.py#L29-L78", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:iotaledger-iota.lib.py:Transaction.from_tryte_string-f772b36bb7@held-out", "question": "Creates a Transaction object from a sequence of trytes.\n\n :param trytes:\n Raw trytes. Should be exactly 2673 trytes long.\n\n :param hash_:\n The transaction hash, if available.\n\n If not provided, it will be computed from the transaction\n trytes.", "scope": {"holder": "iotaledger-iota.lib.py", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/iotaledger/iota.lib.py/blob/97cdd1e241498446b46157b79b2a1ea2ec6d387a/iota/transaction/base.py#L310-L341", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:iotaledger-iota.lib.py:Transaction.as_json_compatible-98d783a8d7@held-out", "question": "Returns a JSON-compatible representation of the object.\n\n References:\n\n - :py:class:`iota.json.JsonEncoder`.", "scope": {"holder": "iotaledger-iota.lib.py", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/iotaledger/iota.lib.py/blob/97cdd1e241498446b46157b79b2a1ea2ec6d387a/iota/transaction/base.py#L366-L379", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:iotaledger-iota.lib.py:Transaction.get_signature_validation_trytes-e20a2703a6@held-out", "question": "Returns the values needed to validate the transaction's\n ``signature_message_fragment`` value.", "scope": {"holder": "iotaledger-iota.lib.py", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/iotaledger/iota.lib.py/blob/97cdd1e241498446b46157b79b2a1ea2ec6d387a/iota/transaction/base.py#L574-L599", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:iotaledger-iota.lib.py:Bundle.group_transactions-22739d148b@held-out", "question": "Groups transactions in the bundle by address.", "scope": {"holder": "iotaledger-iota.lib.py", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/iotaledger/iota.lib.py/blob/97cdd1e241498446b46157b79b2a1ea2ec6d387a/iota/adapter/sandbox.py#L191-L205", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:iotaledger-iota.lib.py:SandboxAdapter.get_jobs_url-39d25ced77@held-out", "question": "Returns the URL to check job status.\n\n :param job_id:\n The ID of the job to check.", "scope": {"holder": "iotaledger-iota.lib.py", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/iotaledger/iota.lib.py/blob/97cdd1e241498446b46157b79b2a1ea2ec6d387a/iota/transaction/validator.py#L68-L186", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:iotaledger-iota.lib.py:BundleValidator._create_validator-dd0a09de85@held-out", "question": "Creates a generator that does all the work.", "scope": {"holder": "iotaledger-iota.lib.py", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/iotaledger/iota.lib.py/blob/97cdd1e241498446b46157b79b2a1ea2ec6d387a/iota/crypto/types.py#L207-L296", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:iotaledger-iota.lib.py:PrivateKey.sign_input_transactions-73686afa37@held-out", "question": "Signs the inputs starting at the specified index.\n\n :param bundle:\n The bundle that contains the input transactions to sign.\n\n :param start_index:\n The index of the first input transaction.\n\n If necessary, the resulting signature will be split across\n subsequent transactions automatically.", "scope": {"holder": "iotaledger-iota.lib.py", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/iotaledger/iota.lib.py/blob/97cdd1e241498446b46157b79b2a1ea2ec6d387a/iota/transaction/creation.py#L72-L92", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:iotaledger-iota.lib.py:ProposedTransaction.as_tryte_string-499a9591e0@held-out", "question": "Returns a TryteString representation of the transaction.", "scope": {"holder": "iotaledger-iota.lib.py", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/iotaledger/iota.lib.py/blob/97cdd1e241498446b46157b79b2a1ea2ec6d387a/iota/transaction/creation.py#L386-L438", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:iotaledger-iota.lib.py:ProposedBundle.sign_inputs-d463fa0e7e@held-out", "question": "Sign inputs in a finalized bundle.", "scope": {"holder": "iotaledger-iota.lib.py", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/iotaledger/iota.lib.py/blob/97cdd1e241498446b46157b79b2a1ea2ec6d387a/iota/transaction/creation.py#L440-L464", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:iotaledger-iota.lib.py:ProposedBundle.sign_input_at-508eeb207c@held-out", "question": "Signs the input at the specified index.\n\n :param start_index:\n The index of the first input transaction.\n\n If necessary, the resulting signature will be split across\n multiple transactions automatically (i.e., if an input has\n ``security_level=2``, you still only need to call\n :py:meth:`sign_input_at` once).\n\n :param private_key:\n The private key that will be used to generate the signature.\n\n .. important::\n Be sure that the private key was generated using the\n correct seed, or the resulting signature will be\n invalid!", "scope": {"holder": "iotaledger-iota.lib.py", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/iotaledger/iota.lib.py/blob/97cdd1e241498446b46157b79b2a1ea2ec6d387a/iota/transaction/creation.py#L466-L490", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:iotaledger-iota.lib.py:ProposedBundle._create_input_transactions-e91d79c653@held-out", "question": "Creates transactions for the specified input address.", "scope": {"holder": "iotaledger-iota.lib.py", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/ethereum/py_ecc/blob/2088796c59574b256dc8e18f8c9351bc3688ca71/py_ecc/bls/utils.py#L118-L140", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:ethereum-py_ecc:decompress_G1-cc15f144b1@held-out", "question": "Recovers x and y coordinates from the compressed point.", "scope": {"holder": "ethereum-py_ecc", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/agile-geoscience/striplog/blob/8033b673a151f96c29802b43763e863519a3124c/striplog/legend.py#L553-L635", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:agile-geoscience-striplog:Legend.from_csv-d918d79ff9@held-out", "question": "Read CSV text and generate a Legend.\n\n Args:\n string (str): The CSV string.\n\n In the first row, list the properties. Precede the properties of the\n component with 'comp ' or 'component '. For example:\n\n colour, width, comp lithology, comp colour\n #FFFFFF, 0, ,\n #F7E9A6, 3, Sandstone, Grey\n #FF99CC, 2, Anhydrite,\n ... etc\n\n Note:\n To edit a legend, the easiest thing to do is probably this:\n\n - `legend.to_csv()`\n - Edit the legend, call it `new_legend`.\n - `legend = Legend.from_csv(text=new_legend)`", "scope": {"holder": "agile-geoscience-striplog", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/agile-geoscience/striplog/blob/8033b673a151f96c29802b43763e863519a3124c/striplog/legend.py#L749-L769", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:agile-geoscience-striplog:Legend.get_colour-7a7d0c8f88@held-out", "question": "Get the display colour of a component. Wraps `getattr()`.\n\n Development note:\n Cannot define this as a `partial()` because I want\n to maintain the order of arguments in `getattr()`.\n\n Args:\n c (component): The component to look up.\n default (str): The colour to return in the event of no match.\n match_only (list of str): The component attributes to include in the\n comparison. Default: All of them.\n\n Returns:\n str. The hex string of the matching Decor in the Legend.", "scope": {"holder": "agile-geoscience-striplog", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/agile-geoscience/striplog/blob/8033b673a151f96c29802b43763e863519a3124c/striplog/component.py#L171-L215", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:agile-geoscience-striplog:Component.summary-03e07b44b5@held-out", "question": "Given a format string, return a summary description of a component.\n\n Args:\n component (dict): A component dictionary.\n fmt (str): Describes the format with a string. If no format is\n given, you will just get a list of attributes. If you give the\n empty string (''), you'll get `default` back. By default this\n gives you the empty string, effectively suppressing the\n summary.\n initial (bool): Whether to capitialize the first letter. Default is\n True.\n default (str): What to give if there's no component defined.\n\n Returns:\n str: A summary string.\n\n Example:\n\n r = Component({'colour': 'Red',\n 'grainsize': 'VF-F',\n 'lithology': 'Sandstone'})\n\n r.summary() --> 'Red, vf-f, sandstone'", "scope": {"holder": "agile-geoscience-striplog", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/agile-geoscience/striplog/blob/8033b673a151f96c29802b43763e863519a3124c/striplog/striplog.py#L1106-L1256", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:agile-geoscience-striplog:Striplog.to_log-2b0b994c3a@held-out", "question": "Return a fully sampled log from a striplog. Useful for crossplotting\n with log data, for example.\n\n Args:\n step (float): The step size. Default: 1.0.\n start (float): The start depth of the new log. You will want to\n match the logs, so use the start depth from the LAS file.\n Default: The basis if provided, else the start of the striplog.\n stop (float): The stop depth of the new log. Use the stop depth\n of the LAS file. Default: The basis if provided, else the stop\n depth of the striplog.\n field (str): If you want the data to come from one of the\n attributes of the components in the striplog, provide it.\n field_function (function): Provide a function to apply to the field\n you are asking for. It's up to you to make sure the function\n does what you want.\n legend (Legend): If you want the codes to come from a legend,\n provide one. Otherwise the codes come from the log, using\n integers in the order of prevalence. If you use a legend,\n they are assigned in the order of the legend.\n legend_field (str): If you want to get a log representing one of\n the fields in the legend, such as 'width' or 'grainsize'.\n match_only (list): If you only want to match some attributes of\n the Components (e.g. lithology), provide a list of those\n you want to match.\n undefined (number): What to fill in where no value can be\n determined, e.g. ``-999.25`` or ``np.null``. Default 0.\n return_meta (bool): If ``True``, also return the depth basis\n (np.linspace), and the component table.\n\n Returns:\n ndarray: If ``return_meta`` was ``True``, you get:\n\n * The log data as an array of ints.\n * The depth basis as an array of floats.\n * A list of the components in the order matching the ints.\n\n If ``return_meta`` was ``False`` (the default), you only get\n the log data.", "scope": {"holder": "agile-geoscience-striplog", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/agile-geoscience/striplog/blob/8033b673a151f96c29802b43763e863519a3124c/striplog/striplog.py#L1314-L1334", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:agile-geoscience-striplog:Striplog.plot_field-c5d4e6e24e@held-out", "question": "Plotting, but only for tops (as opposed to intervals).", "scope": {"holder": "agile-geoscience-striplog", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/agile-geoscience/striplog/blob/8033b673a151f96c29802b43763e863519a3124c/striplog/striplog.py#L1447-L1571", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:agile-geoscience-striplog:Striplog.plot-34f6a36467@held-out", "question": "Hands-free plotting.\n\n Args:\n legend (Legend): The Legend to use for colours, etc.\n width (int): The width of the plot, in inches. Default 1.\n ladder (bool): Whether to use widths or not. Default False.\n aspect (int): The aspect ratio of the plot. Default 10.\n ticks (int or tuple): The (minor,major) tick interval for depth.\n Only the major interval is labeled. Default (1,10).\n match_only (list): A list of strings matching the attributes you\n want to compare when plotting.\n ax (ax): A maplotlib axis to plot onto. If you pass this, it will\n be returned. Optional.\n return_fig (bool): Whether or not to return the maplotlib ``fig``\n object. Default False.\n colour (str): Which data field to use for colours.\n cmap (cmap): Matplotlib colourmap. Default ``viridis``.\n **kwargs are passed through to matplotlib's ``patches.Rectangle``.\n\n Returns:\n None. Unless you specify ``return_fig=True`` or pass in an ``ax``.", "scope": {"holder": "agile-geoscience-striplog", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/agile-geoscience/striplog/blob/8033b673a151f96c29802b43763e863519a3124c/striplog/striplog.py#L1902-L1939", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:agile-geoscience-striplog:Striplog.merge_neighbours-f605ba109e@held-out", "question": "Makes a new striplog in which matching neighbours (for which the\n components are the same) are unioned. That is, they are replaced by\n a new Interval with the same top as the uppermost and the same bottom\n as the lowermost.\n\n Args\n strict (bool): If True, then all of the components must match.\n If False, then only the primary must match.\n\n Returns:\n Striplog. A new striplog.\n\n TODO:\n Might need to be tweaked to deal with 'binary striplogs' if those\n aren't implemented with components.", "scope": {"holder": "agile-geoscience-striplog", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/agile-geoscience/striplog/blob/8033b673a151f96c29802b43763e863519a3124c/striplog/striplog.py#L2124-L2145", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:agile-geoscience-striplog:Striplog.invert-8ffa49fa18@held-out", "question": "Inverts the striplog, changing its order and the order of its contents.\n\n Operates in place by default.\n\n Args:\n copy (bool): Whether to operate in place or make a copy.\n\n Returns:\n None if operating in-place, or an inverted copy of the striplog\n if not.", "scope": {"holder": "agile-geoscience-striplog", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/agile-geoscience/striplog/blob/8033b673a151f96c29802b43763e863519a3124c/striplog/utils.py#L208-L231", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:agile-geoscience-striplog:rgb_to_hex-23f501eb12@held-out", "question": "Utility function to convert (r,g,b) triples to hex.\n http://ageo.co/1CFxXpO\n Args:\n rgb (tuple): A sequence of RGB values in the\n range 0-255 or 0-1.\n Returns:\n str: The hex code for the colour.", "scope": {"holder": "agile-geoscience-striplog", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/jrxFive/python-nomad/blob/37df37e4de21e6f8ac41c6154e7f1f44f1800020/nomad/api/jobs.py#L66-L79", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:jrxFive-python-nomad:Jobs.get_jobs-7dad2e838d@held-out", "question": "Lists all the jobs registered with Nomad.\n\n https://www.nomadproject.io/docs/http/jobs.html\n arguments:\n - prefix :(str) optional, specifies a string to filter jobs on based on an prefix.\n This is specified as a querystring parameter.\n returns: list\n raises:\n - nomad.api.exceptions.BaseNomadException\n - nomad.api.exceptions.URLNotFoundNomadException", "scope": {"holder": "jrxFive-python-nomad", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/jrxFive/python-nomad/blob/37df37e4de21e6f8ac41c6154e7f1f44f1800020/nomad/api/acl.py#L108-L122", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:jrxFive-python-nomad:Acl.update_token-3e8fcc1de3@held-out", "question": "Update token.\n\n https://www.nomadproject.io/api/acl-tokens.html\n\n arguments:\n - AccdesorID\n - token\n returns: dict\n\n raises:\n - nomad.api.exceptions.BaseNomadException\n - nomad.api.exceptions.URLNotFoundNomadException", "scope": {"holder": "jrxFive-python-nomad", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/jrxFive/python-nomad/blob/37df37e4de21e6f8ac41c6154e7f1f44f1800020/nomad/api/deployment.py#L90-L106", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:jrxFive-python-nomad:Deployment.pause_deployment-045b5e3865@held-out", "question": "This endpoint is used to pause or unpause a deployment.\n This is done to pause a rolling upgrade or resume it.\n\n https://www.nomadproject.io/docs/http/deployments.html\n\n arguments:\n - id\n - pause, Specifies whether to pause or resume the deployment.\n returns: dict\n raises:\n - nomad.api.exceptions.BaseNomadException\n - nomad.api.exceptions.URLNotFoundNomadException", "scope": {"holder": "jrxFive-python-nomad", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/jrxFive/python-nomad/blob/37df37e4de21e6f8ac41c6154e7f1f44f1800020/nomad/api/client.py#L146-L166", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:jrxFive-python-nomad:stream_file.stream-ae8986f44b@held-out", "question": "This endpoint streams the contents of a file in an allocation directory.\n\n https://www.nomadproject.io/api/client.html#stream-file\n\n arguments:\n - id: (str) allocation_id required\n - offset: (int) required\n - origin: (str) either start|end\n - path: (str) optional\n returns: (str) text\n raises:\n - nomad.api.exceptions.BaseNomadException\n - nomad.api.exceptions.BadRequestNomadException", "scope": {"holder": "jrxFive-python-nomad", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/jrxFive/python-nomad/blob/37df37e4de21e6f8ac41c6154e7f1f44f1800020/nomad/api/agent.py#L87-L98", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:jrxFive-python-nomad:Agent.force_leave-3e35defa72@held-out", "question": "Force a failed gossip member into the left state.\n\n https://www.nomadproject.io/docs/http/agent-force-leave.html\n\n returns: 200 status code\n raises:\n - nomad.api.exceptions.BaseNomadException\n - nomad.api.exceptions.URLNotFoundNomadException", "scope": {"holder": "jrxFive-python-nomad", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/jrxFive/python-nomad/blob/37df37e4de21e6f8ac41c6154e7f1f44f1800020/nomad/api/job.py#L149-L161", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:jrxFive-python-nomad:Job.register_job-812d419ca1@held-out", "question": "Registers a new job or updates an existing job\n\n https://www.nomadproject.io/docs/http/job.html\n\n arguments:\n - id\n returns: dict\n raises:\n - nomad.api.exceptions.BaseNomadException\n - nomad.api.exceptions.URLNotFoundNomadException", "scope": {"holder": "jrxFive-python-nomad", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/jrxFive/python-nomad/blob/37df37e4de21e6f8ac41c6154e7f1f44f1800020/nomad/api/job.py#L178-L197", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:jrxFive-python-nomad:Job.plan_job-311b25cadc@held-out", "question": "Invoke a dry-run of the scheduler for the job.\n\n https://www.nomadproject.io/docs/http/job.html\n\n arguments:\n - id\n - job, dict\n - diff, boolean\n - policy_override, boolean\n returns: dict\n raises:\n - nomad.api.exceptions.BaseNomadException\n - nomad.api.exceptions.URLNotFoundNomadException", "scope": {"holder": "jrxFive-python-nomad", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/jrxFive/python-nomad/blob/37df37e4de21e6f8ac41c6154e7f1f44f1800020/nomad/api/job.py#L216-L231", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:jrxFive-python-nomad:Job.dispatch_job-8d993e253c@held-out", "question": "Dispatches a new instance of a parameterized job.\n\n https://www.nomadproject.io/docs/http/job.html\n\n arguments:\n - id\n - payload\n - meta\n returns: dict\n raises:\n - nomad.api.exceptions.BaseNomadException\n - nomad.api.exceptions.URLNotFoundNomadException", "scope": {"holder": "jrxFive-python-nomad", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/jrxFive/python-nomad/blob/37df37e4de21e6f8ac41c6154e7f1f44f1800020/nomad/api/job.py#L274-L297", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:jrxFive-python-nomad:Job.deregister_job-0f2f3d1a37@held-out", "question": "Deregisters a job, and stops all allocations part of it.\n\n https://www.nomadproject.io/docs/http/job.html\n\n arguments:\n - id\n - purge (bool), optionally specifies whether the job should be\n stopped and purged immediately (`purge=True`) or deferred to the\n Nomad garbage collector (`purge=False`).\n\n returns: dict\n raises:\n - nomad.api.exceptions.BaseNomadException\n - nomad.api.exceptions.URLNotFoundNomadException\n - nomad.api.exceptions.InvalidParameters", "scope": {"holder": "jrxFive-python-nomad", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/jrxFive/python-nomad/blob/37df37e4de21e6f8ac41c6154e7f1f44f1800020/nomad/api/operator.py#L27-L42", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:jrxFive-python-nomad:Operator.get_configuration-7616a4ed15@held-out", "question": "Query the status of a client node registered with Nomad.\n\n https://www.nomadproject.io/docs/http/operator.html\n\n returns: dict\n optional arguments:\n - stale, (defaults to False), Specifies if the cluster should respond without an active leader.\n This is specified as a querystring parameter.\n raises:\n - nomad.api.exceptions.BaseNomadException\n - nomad.api.exceptions.URLNotFoundNomadException", "scope": {"holder": "jrxFive-python-nomad", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/jrxFive/python-nomad/blob/37df37e4de21e6f8ac41c6154e7f1f44f1800020/nomad/api/deployments.py#L59-L74", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:jrxFive-python-nomad:Deployments.get_deployments-145b7a0955@held-out", "question": "This endpoint lists all deployments.\n\n https://www.nomadproject.io/docs/http/deployments.html\n\n optional_arguments:\n - prefix, (default \"\") Specifies a string to filter deployments on based on an index prefix.\n This is specified as a querystring parameter.\n\n returns: list of dicts\n raises:\n - nomad.api.exceptions.BaseNomadException\n - nomad.api.exceptions.URLNotFoundNomadException", "scope": {"holder": "jrxFive-python-nomad", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/mseclab/PyJFuzz/blob/f777067076f62c9ab74ffea6e90fd54402b7a1b4/pyjfuzz/core/pjf_mutators.py#L133-L140", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:mseclab-PyJFuzz:PJFMutators.get_mutator-871167c110@held-out", "question": "Get a random mutator for the given type", "scope": {"holder": "mseclab-PyJFuzz", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/mseclab/PyJFuzz/blob/f777067076f62c9ab74ffea6e90fd54402b7a1b4/pyjfuzz/core/pjf_mutation.py#L35-L44", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:mseclab-PyJFuzz:PJFMutation.fuzz-02383d7d7b@held-out", "question": "Generic fuzz mutator, use a decorator for the given type", "scope": {"holder": "mseclab-PyJFuzz", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/mseclab/PyJFuzz/blob/f777067076f62c9ab74ffea6e90fd54402b7a1b4/pyjfuzz/core/pjf_executor.py#L90-L104", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:mseclab-PyJFuzz:PJFExecutor.finish_read-07b4e66ccb@held-out", "question": "Wait until we got output or until timeout is over", "scope": {"holder": "mseclab-PyJFuzz", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/mseclab/PyJFuzz/blob/f777067076f62c9ab74ffea6e90fd54402b7a1b4/pyjfuzz/core/pjf_executor.py#L106-L118", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:mseclab-PyJFuzz:PJFExecutor.close-76bf5b6c6f@held-out", "question": "Terminate the newly created process", "scope": {"holder": "mseclab-PyJFuzz", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/mseclab/PyJFuzz/blob/f777067076f62c9ab74ffea6e90fd54402b7a1b4/gramfuzz/gramfuzz/utils.py#L13-L33", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:mseclab-PyJFuzz:val-e48aec8531@held-out", "question": "Build the provided value, while properly handling\n native Python types, :any:`gramfuzz.fields.Field` instances, and :any:`gramfuzz.fields.Field`\n subclasses.\n\n :param list pre: The prerequisites list\n :returns: str", "scope": {"holder": "mseclab-PyJFuzz", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/mseclab/PyJFuzz/blob/f777067076f62c9ab74ffea6e90fd54402b7a1b4/gramfuzz/gramfuzz/fields.py#L385-L411", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:mseclab-PyJFuzz:Join.build-074b86267f@held-out", "question": "Build the ``Join`` field instance.\n \n :param list pre: The prerequisites list\n :param bool shortest: Whether or not the shortest reference-chain (most minimal) version of the field should be generated.", "scope": {"holder": "mseclab-PyJFuzz", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/mseclab/PyJFuzz/blob/f777067076f62c9ab74ffea6e90fd54402b7a1b4/gramfuzz/gramfuzz/fields.py#L491-L504", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:mseclab-PyJFuzz:Q.build-1dfa56bfe4@held-out", "question": "Build the ``Quote`` instance\n\n :param list pre: The prerequisites list\n :param bool shortest: Whether or not the shortest reference-chain (most minimal) version of the field should be generated.", "scope": {"holder": "mseclab-PyJFuzz", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/mseclab/PyJFuzz/blob/f777067076f62c9ab74ffea6e90fd54402b7a1b4/gramfuzz/gramfuzz/fields.py#L526-L541", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:mseclab-PyJFuzz:Or.build-47c4c71a31@held-out", "question": "Build the ``Or`` instance\n\n :param list pre: The prerequisites list\n :param bool shortest: Whether or not the shortest reference-chain (most minimal) version of the field should be generated.", "scope": {"holder": "mseclab-PyJFuzz", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/mseclab/PyJFuzz/blob/f777067076f62c9ab74ffea6e90fd54402b7a1b4/gramfuzz/gramfuzz/fields.py#L654-L685", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:mseclab-PyJFuzz:Def.build-7e2889aa3d@held-out", "question": "Build this rule definition\n \n :param list pre: The prerequisites list\n :param bool shortest: Whether or not the shortest reference-chain (most minimal) version of the field should be generated.", "scope": {"holder": "mseclab-PyJFuzz", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/mseclab/PyJFuzz/blob/f777067076f62c9ab74ffea6e90fd54402b7a1b4/gramfuzz/gramfuzz/fields.py#L785-L799", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:mseclab-PyJFuzz:STAR.build-f45474ab52@held-out", "question": "Build the STAR field.\n\n :param list pre: The prerequisites list\n :param bool shortest: Whether or not the shortest reference-chain (most minimal) version of the field should be generated.", "scope": {"holder": "mseclab-PyJFuzz", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/mseclab/PyJFuzz/blob/f777067076f62c9ab74ffea6e90fd54402b7a1b4/gramfuzz/gramfuzz/rand.py#L50-L70", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:mseclab-PyJFuzz:randfloat-0a8b515b15@held-out", "question": "Return a random float\n\n :param float a: Either the minimum value (inclusive) if ``b`` is set, or\n the maximum value if ``b`` is not set (non-inclusive, in which case the minimum\n is implicitly 0.0)\n :param float b: The maximum value to generate (non-inclusive)\n :returns: float", "scope": {"holder": "mseclab-PyJFuzz", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/mseclab/PyJFuzz/blob/f777067076f62c9ab74ffea6e90fd54402b7a1b4/gramfuzz/gramfuzz/__init__.py#L98-L131", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:mseclab-PyJFuzz:GramFuzzer.load_grammar-bac7537e65@held-out", "question": "Load a grammar file (python file containing grammar definitions) by\n file path. When loaded, the global variable ``GRAMFUZZER`` will be set\n within the module. This is not always needed, but can be useful.\n\n :param str path: The path to the grammar file", "scope": {"holder": "mseclab-PyJFuzz", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/mseclab/PyJFuzz/blob/f777067076f62c9ab74ffea6e90fd54402b7a1b4/gramfuzz/gramfuzz/__init__.py#L350-L358", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:mseclab-PyJFuzz:GramFuzzer.add_to_cat_group-038d03d755@held-out", "question": "Associate the provided rule definition name ``def_name`` with the\n category group ``cat_group`` in the category ``cat``.\n\n :param str cat: The category the rule definition was declared in\n :param str cat_group: The group within the category the rule belongs to\n :param str def_name: The name of the rule definition", "scope": {"holder": "mseclab-PyJFuzz", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/mseclab/PyJFuzz/blob/f777067076f62c9ab74ffea6e90fd54402b7a1b4/pyjfuzz/core/pjf_factory.py#L180-L206", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:mseclab-PyJFuzz:PJFFactory.fuzzed-a81ca3bb40@held-out", "question": "Get a printable fuzzed object", "scope": {"holder": "mseclab-PyJFuzz", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/ybrs/single-beat/blob/d036b62d2531710dfd806e9dc2a8d67c77616082/singlebeat/beat.py#L355-L370", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:ybrs-single-beat:Process.cli_command_stop-e1d2bc2746@held-out", "question": "\\\n stops the running child process - if its running\n it will re-spawn in any single-beat node after sometime\n\n :param msg:\n :return:", "scope": {"holder": "ybrs-single-beat", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Terrance/SkPy/blob/0f9489c94e8ec4d3effab4314497428872a80ad1/skpy/conn.py#L329-L346", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Terrance-SkPy:SkypeConnection.verifyToken-99e66551d8@held-out", "question": "Ensure the authentication token for the given auth method is still valid.\n\n Args:\n auth (Auth): authentication type to check\n\n Raises:\n .SkypeAuthException: if Skype auth is required, and the current token has expired and can't be renewed", "scope": {"holder": "Terrance-SkPy", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Terrance/SkPy/blob/0f9489c94e8ec4d3effab4314497428872a80ad1/skpy/conn.py#L348-L370", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Terrance-SkPy:SkypeConnection.liveLogin-50e976f547@held-out", "question": "Obtain connection parameters from the Microsoft account login page, and perform a login with the given email\n address or Skype username, and its password. This emulates a login to Skype for Web on ``login.live.com``.\n\n .. note::\n Microsoft accounts with two-factor authentication enabled are not supported, and will cause a\n :class:`.SkypeAuthException` to be raised. See the exception definitions for other possible causes.\n\n Args:\n user (str): username or email address of the connecting account\n pwd (str): password of the connecting account\n\n Returns:\n (str, datetime.datetime) tuple: Skype token, and associated expiry if known\n\n Raises:\n .SkypeAuthException: if the login request is rejected\n .SkypeApiException: if the login form can't be processed", "scope": {"holder": "Terrance-SkPy", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Terrance/SkPy/blob/0f9489c94e8ec4d3effab4314497428872a80ad1/skpy/conn.py#L436-L444", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Terrance-SkPy:SkypeConnection.syncEndpoints-bf86a3c604@held-out", "question": "Retrieve all current endpoints for the connected user.", "scope": {"holder": "Terrance-SkPy", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Terrance/SkPy/blob/0f9489c94e8ec4d3effab4314497428872a80ad1/skpy/conn.py#L877-L885", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Terrance-SkPy:SkypeEndpoint.ping-28da1bb825@held-out", "question": "Send a keep-alive request for the endpoint.\n\n Args:\n timeout (int): maximum amount of time for the endpoint to stay active", "scope": {"holder": "Terrance-SkPy", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Terrance/SkPy/blob/0f9489c94e8ec4d3effab4314497428872a80ad1/skpy/util.py#L183-L197", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Terrance-SkPy:SkypeUtils.truthyAttrs-fce69b26f8@held-out", "question": "Class decorator: override __bool__ to set truthiness based on any attr being present.\n\n Args:\n cls (class): class to decorate\n\n Returns:\n class: same, but modified, class", "scope": {"holder": "Terrance-SkPy", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/eyeseast/python-frontmatter/blob/c318e583c48599eb597e0ad59c5d972258c3febc/frontmatter/__init__.py#L52-L91", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:eyeseast-python-frontmatter:parse-ec411a95bc@held-out", "question": "Parse text with frontmatter, return metadata and content.\n Pass in optional metadata defaults as keyword args.\n\n If frontmatter is not found, returns an empty metadata dictionary\n (or defaults) and original text content.\n\n ::\n\n >>> with open('tests/hello-world.markdown') as f:\n ... metadata, content = frontmatter.parse(f.read())\n >>> print(metadata['title'])\n Hello, world!", "scope": {"holder": "eyeseast-python-frontmatter", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/5j9/wikitextparser/blob/1347425814361d7955342c53212edbb27f0ff4b5/wikitextparser/_wikilist.py#L144-L150", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:5j9-wikitextparser:WikiList.convert-df7a2e94c8@held-out", "question": "Convert to another list type by replacing starting pattern.", "scope": {"holder": "5j9-wikitextparser", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/5j9/wikitextparser/blob/1347425814361d7955342c53212edbb27f0ff4b5/wikitextparser/_config.py#L8-L21", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:5j9-wikitextparser:_plant_trie-08e45aecf6@held-out", "question": "Create a Trie out of a list of words and return an atomic regex pattern.\n\n The corresponding Regex should match much faster than a simple Regex union.", "scope": {"holder": "5j9-wikitextparser", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/5j9/wikitextparser/blob/1347425814361d7955342c53212edbb27f0ff4b5/wikitextparser/_wikitext.py#L257-L289", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:5j9-wikitextparser:WikiText.insert-345e0e9f7c@held-out", "question": "Insert the given string before the specified index.\n\n This method has the same effect as ``self[index:index] = string``;\n it only avoids some condition checks as it rules out the possibility\n of the key being an slice, or the need to shrink any of the sub-spans.\n\n If parse is False, don't parse the inserted string.", "scope": {"holder": "5j9-wikitextparser", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/5j9/wikitextparser/blob/1347425814361d7955342c53212edbb27f0ff4b5/wikitextparser/_wikitext.py#L394-L403", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:5j9-wikitextparser:WikiText._insert_update-df6c287489@held-out", "question": "Update self._type_to_spans according to the added length.", "scope": {"holder": "5j9-wikitextparser", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/5j9/wikitextparser/blob/1347425814361d7955342c53212edbb27f0ff4b5/wikitextparser/_wikitext.py#L723-L729", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:5j9-wikitextparser:WikiText.comments-c5812f0d4b@held-out", "question": "Return a list of comment objects.", "scope": {"holder": "5j9-wikitextparser", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/5j9/wikitextparser/blob/1347425814361d7955342c53212edbb27f0ff4b5/wikitextparser/_wikitext.py#L732-L778", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:5j9-wikitextparser:WikiText.external_links-f47d5ec059@held-out", "question": "Return a list of found external link objects.\n\n Note:\n Templates adjacent to external links are considered part of the\n link. In reality, this depends on the contents of the template:\n\n >>> WikiText(\n ... 'http://example.com{{dead link}}'\n ...).external_links[0].url\n 'http://example.com{{dead link}}'\n\n >>> WikiText(\n ... '[http://example.com{{space template}} text]'\n ...).external_links[0].url\n 'http://example.com{{space template}}'", "scope": {"holder": "5j9-wikitextparser", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/5j9/wikitextparser/blob/1347425814361d7955342c53212edbb27f0ff4b5/wikitextparser/_wikitext.py#L781-L839", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:5j9-wikitextparser:WikiText.sections-b46280d861@held-out", "question": "Return a list of section in current wikitext.\n\n The first section will always be the lead section, even if it is an\n empty string.", "scope": {"holder": "5j9-wikitextparser", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/5j9/wikitextparser/blob/1347425814361d7955342c53212edbb27f0ff4b5/wikitextparser/_wikitext.py#L1052-L1062", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:5j9-wikitextparser:SubWikiText._subspans-ad58ca34ce@held-out", "question": "Yield all the sub-span indices excluding self._span.", "scope": {"holder": "5j9-wikitextparser", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/5j9/wikitextparser/blob/1347425814361d7955342c53212edbb27f0ff4b5/wikitextparser/_template.py#L190-L285", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:5j9-wikitextparser:Template.set_arg-62599e711f@held-out", "question": "Set the value for `name` argument. Add it if it doesn't exist.\n\n - Use `positional`, `before` and `after` keyword arguments only when\n adding a new argument.\n - If `before` is given, ignore `after`.\n - If neither `before` nor `after` are given and it's needed to add a\n new argument, then append the new argument to the end.\n - If `positional` is True, try to add the given value as a positional\n argument. Ignore `preserve_spacing` if positional is True.\n If it's None, do what seems more appropriate.", "scope": {"holder": "5j9-wikitextparser", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/karimbahgat/PyCRS/blob/d6a8bb9c28787a25b4a1d59a7e4603db3221eaef/pycrs/elements/cs.py#L171-L179", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:karimbahgat-PyCRS:ProjCS.to_ogc_wkt-88b1a72571@held-out", "question": "Returns the CS as a OGC WKT formatted string.", "scope": {"holder": "karimbahgat-PyCRS", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/karimbahgat/PyCRS/blob/d6a8bb9c28787a25b4a1d59a7e4603db3221eaef/pycrs/load.py#L22-L54", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:karimbahgat-PyCRS:from_url-f93df17981@held-out", "question": "Returns the crs object from a string interpreted as a specified format, located at a given url site.\n\n Arguments:\n\n - *url*: The url where the crs string is to be read from. \n - *format* (optional): Which format to parse the crs string as. One of \"ogc wkt\", \"esri wkt\", or \"proj4\".\n If None, tries to autodetect the format for you (default).\n\n Returns:\n\n - CRS object.", "scope": {"holder": "karimbahgat-PyCRS", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/karimbahgat/PyCRS/blob/d6a8bb9c28787a25b4a1d59a7e4603db3221eaef/pycrs/load.py#L56-L87", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:karimbahgat-PyCRS:from_file-59bddee7d6@held-out", "question": "Returns the crs object from a file, with the format determined from the filename extension.\n\n Arguments:\n\n - *filepath*: filepath to be loaded, including extension.", "scope": {"holder": "karimbahgat-PyCRS", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/karimbahgat/PyCRS/blob/d6a8bb9c28787a25b4a1d59a7e4603db3221eaef/pycrs/parse.py#L24-L41", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:karimbahgat-PyCRS:from_epsg_code-a0392d6f2c@held-out", "question": "Load crs object from epsg code, via spatialreference.org.\n Parses based on the proj4 representation.\n\n Arguments:\n\n - *code*: The EPSG code as an integer.\n\n Returns:\n\n - A CS instance of the indicated type.", "scope": {"holder": "karimbahgat-PyCRS", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tmontaigu/pylas/blob/8335a1a7d7677f0e4bc391bb6fa3c75b42ed5b06/pylas/vlrs/rawvlr.py#L73-L91", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tmontaigu-pylas:RawVLR.read_from-9932512bd9@held-out", "question": "Instantiate a RawVLR by reading the content from the\n data stream\n\n Parameters:\n ----------\n data_stream : {file object}\n The input stream\n Returns\n -------\n RawVLR\n The RawVLR read", "scope": {"holder": "tmontaigu-pylas", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tmontaigu/pylas/blob/8335a1a7d7677f0e4bc391bb6fa3c75b42ed5b06/pylas/point/record.py#L121-L128", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tmontaigu-pylas:PointRecord.from_point_record-7d9b8319ea@held-out", "question": "Construct a new PackedPointRecord from an existing one with the ability to change\n to point format while doing so", "scope": {"holder": "tmontaigu-pylas", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tmontaigu/pylas/blob/8335a1a7d7677f0e4bc391bb6fa3c75b42ed5b06/pylas/point/dims.py#L29-L37", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tmontaigu-pylas:_build_point_formats_dtypes-648b20499c@held-out", "question": "Builds the dict mapping point format id to numpy.dtype\n In the dtypes, bit fields are still packed, and need to be unpacked each time\n you want to access them", "scope": {"holder": "tmontaigu-pylas", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tmontaigu/pylas/blob/8335a1a7d7677f0e4bc391bb6fa3c75b42ed5b06/pylas/point/dims.py#L293-L299", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tmontaigu-pylas:is_point_fmt_compatible_with_version-82b9a618fa@held-out", "question": "Returns true if the file version support the point_format_id", "scope": {"holder": "tmontaigu-pylas", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tmontaigu/pylas/blob/8335a1a7d7677f0e4bc391bb6fa3c75b42ed5b06/pylas/lib.py#L104-L123", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tmontaigu-pylas:create_from_header-bcc75ea701@held-out", "question": "Creates a File from an existing header,\n allocating the array of point according to the provided header.\n The input header is copied.\n\n\n Parameters\n ----------\n header : existing header to be used to create the file\n\n Returns\n -------\n pylas.lasdatas.base.LasBase", "scope": {"holder": "tmontaigu-pylas", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/tmontaigu/pylas/blob/8335a1a7d7677f0e4bc391bb6fa3c75b42ed5b06/pylas/point/format.py#L108-L112", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:tmontaigu-pylas:PointFormat.has_waveform_packet-9c3a4419a1@held-out", "question": "Returns True if the point format has waveform packet dimensions", "scope": {"holder": "tmontaigu-pylas", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/c-soft/satel_integra/blob/3b6d2020d1e10dc5aa40f30ee4ecc0f3a053eb3c/satel_integra/cli.py#L16-L26", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:c-soft-satel_integra:main-64865f2a08@held-out", "question": "Console script for satel_integra.", "scope": {"holder": "c-soft-satel_integra", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/c-soft/satel_integra/blob/3b6d2020d1e10dc5aa40f30ee4ecc0f3a053eb3c/satel_integra/satel_integra.py#L23-L28", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:c-soft-satel_integra:print_hex-37cf077a6f@held-out", "question": "Debugging method to print out frames in hex.", "scope": {"holder": "c-soft-satel_integra", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/c-soft/satel_integra/blob/3b6d2020d1e10dc5aa40f30ee4ecc0f3a053eb3c/satel_integra/satel_integra.py#L311-L322", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:c-soft-satel_integra:AsyncSatel.clear_alarm-5ddb575ed2@held-out", "question": "Send command to clear the alarm.", "scope": {"holder": "c-soft-satel_integra", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/c-soft/satel_integra/blob/3b6d2020d1e10dc5aa40f30ee4ecc0f3a053eb3c/satel_integra/satel_integra.py#L374-L386", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:c-soft-satel_integra:AsyncSatel.keep_alive-f1164cb82e@held-out", "question": "A workaround for Satel Integra disconnecting after 25s.\n\n Every interval it sends some random question to the device, ignoring\n answer - just to keep connection alive.", "scope": {"holder": "c-soft-satel_integra", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/quantopian/pgcontents/blob/ed36268b7917332d16868208e1e565742a8753e1/pgcontents/pgmanager.py#L197-L211", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:quantopian-pgcontents:PostgresContentsManager._notebook_model_from_db-156a5e081a@held-out", "question": "Build a notebook model from database record.", "scope": {"holder": "quantopian-pgcontents", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/quantopian/pgcontents/blob/ed36268b7917332d16868208e1e565742a8753e1/pgcontents/pgmanager.py#L246-L262", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:quantopian-pgcontents:PostgresContentsManager._directory_model_from_db-c2e465d07d@held-out", "question": "Build a directory model from database directory record.", "scope": {"holder": "quantopian-pgcontents", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/quantopian/pgcontents/blob/ed36268b7917332d16868208e1e565742a8753e1/pgcontents/pgmanager.py#L264-L280", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:quantopian-pgcontents:PostgresContentsManager._file_model_from_db-fac46e5227@held-out", "question": "Build a file model from database record.", "scope": {"holder": "quantopian-pgcontents", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/quantopian/pgcontents/blob/ed36268b7917332d16868208e1e565742a8753e1/pgcontents/query.py#L86-L93", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:quantopian-pgcontents:ensure_db_user-c21ff8960b@held-out", "question": "Add a new user if they don't already exist.", "scope": {"holder": "quantopian-pgcontents", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/quantopian/pgcontents/blob/ed36268b7917332d16868208e1e565742a8753e1/pgcontents/query.py#L167-L191", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:quantopian-pgcontents:delete_directory-756ccf724e@held-out", "question": "Delete a directory.", "scope": {"holder": "quantopian-pgcontents", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/quantopian/pgcontents/blob/ed36268b7917332d16868208e1e565742a8753e1/pgcontents/query.py#L454-L508", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:quantopian-pgcontents:rename_directory-66996f1d6a@held-out", "question": "Rename a directory.", "scope": {"holder": "quantopian-pgcontents", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/quantopian/pgcontents/blob/ed36268b7917332d16868208e1e565742a8753e1/pgcontents/query.py#L736-L764", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:quantopian-pgcontents:generate_checkpoints-090816bda4@held-out", "question": "Create a generator of decrypted remote checkpoints.\n\n Checkpoints are yielded in ascending order of their timestamp.\n\n This function selects all notebook checkpoints (optionally, falling within\n a datetime range), decrypts them, and returns a generator yielding dicts,\n each containing a decoded notebook and metadata including the user,\n filepath, and timestamp.\n\n Parameters\n ----------\n engine : SQLAlchemy.engine\n Engine encapsulating database connections.\n crypto_factory : function[str -> Any]\n A function from user_id to an object providing the interface required\n by PostgresContentsManager.crypto. Results of this will be used for\n decryption of the selected notebooks.\n min_dt : datetime.datetime, optional\n Minimum last modified datetime at which a file will be included.\n max_dt : datetime.datetime, optional\n Last modified datetime at and after which a file will be excluded.\n logger : Logger, optional", "scope": {"holder": "quantopian-pgcontents", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/quantopian/pgcontents/blob/ed36268b7917332d16868208e1e565742a8753e1/pgcontents/query.py#L842-L864", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:quantopian-pgcontents:reencrypt_row_content-e0ee252575@held-out", "question": "Re-encrypt a row from ``table`` with ``id`` of ``row_id``.", "scope": {"holder": "quantopian-pgcontents", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/quantopian/pgcontents/blob/ed36268b7917332d16868208e1e565742a8753e1/pgcontents/db_utils.py#L68-L81", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:quantopian-pgcontents:to_dict_no_content-22db6307c5@held-out", "question": "Convert a SQLAlchemy row that does not contain a 'content' field to a dict.\n\n If row is None, return None.\n\n Raises AssertionError if there is a field named 'content' in ``fields``.", "scope": {"holder": "quantopian-pgcontents", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/quantopian/pgcontents/blob/ed36268b7917332d16868208e1e565742a8753e1/pgcontents/checkpoints.py#L51-L68", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:quantopian-pgcontents:PostgresCheckpoints.create_file_checkpoint-b7f7241134@held-out", "question": "Create a checkpoint of the current state of a file\n\n Returns a checkpoint_id for the new checkpoint.", "scope": {"holder": "quantopian-pgcontents", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/quantopian/pgcontents/blob/ed36268b7917332d16868208e1e565742a8753e1/pgcontents/hybridmanager.py#L118-L130", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:quantopian-pgcontents:path_dispatch_kwarg-1849f5f6fd@held-out", "question": "Parameterized decorator for methods that accept path as a second\n argument.", "scope": {"holder": "quantopian-pgcontents", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/quantopian/pgcontents/blob/ed36268b7917332d16868208e1e565742a8753e1/pgcontents/hybridmanager.py#L259-L270", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:quantopian-pgcontents:HybridContentsManager.delete-2689994dbb@held-out", "question": "Ensure that roots of our managers can't be deleted. This should be\n enforced by https://github.com/ipython/ipython/pull/8168, but rogue\n implementations might override this behavior.", "scope": {"holder": "quantopian-pgcontents", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/quantopian/pgcontents/blob/ed36268b7917332d16868208e1e565742a8753e1/pgcontents/utils/sync.py#L53-L67", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:quantopian-pgcontents:walk_dirs-0d0a1b7a91@held-out", "question": "Recursive helper for walk.", "scope": {"holder": "quantopian-pgcontents", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/quantopian/pgcontents/blob/ed36268b7917332d16868208e1e565742a8753e1/pgcontents/utils/sync.py#L96-L148", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:quantopian-pgcontents:reencrypt_all_users-ca698eace6@held-out", "question": "Re-encrypt data for all users.\n\n This function is idempotent, meaning that it should be possible to apply\n the same re-encryption process multiple times without having any effect on\n the database. Idempotency is achieved by first attempting to decrypt with\n the old crypto and falling back to the new crypto on failure.\n\n An important consequence of this strategy is that **decrypting** a database\n is not supported with this function, because ``NoEncryption.decrypt``\n always succeeds. To decrypt an already-encrypted database, use\n ``unencrypt_all_users`` instead.\n\n It is, however, possible to perform an initial encryption of a database by\n passing a function returning a ``NoEncryption`` as ``old_crypto_factory``.\n\n Parameters\n ----------\n engine : SQLAlchemy.engine\n Engine encapsulating database connections.\n old_crypto_factory : function[str -> Any]\n A function from user_id to an object providing the interface required\n by PostgresContentsManager.crypto. Results of this will be used for\n decryption of existing database content.\n new_crypto_factory : function[str -> Any]\n A function from user_id to an object providing the interface required\n by PostgresContentsManager.crypto. Results of this will be used for\n re-encryption of database content.\n\n This **must not** return instances of ``NoEncryption``. Use\n ``unencrypt_all_users`` if you want to unencrypt a database.\n logger : logging.Logger, optional\n A logger to user during re-encryption.\n\n See Also\n --------\n reencrypt_user\n unencrypt_all_users", "scope": {"holder": "quantopian-pgcontents", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/quantopian/pgcontents/blob/ed36268b7917332d16868208e1e565742a8753e1/pgcontents/utils/migrate.py#L17-L31", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:quantopian-pgcontents:temp_alembic_ini-5dd2c62964@held-out", "question": "Temporarily write an alembic.ini file for use with alembic migration\n scripts.", "scope": {"holder": "quantopian-pgcontents", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/ubyssey/dispatch/blob/8da6084fe61726f20e9cf675190480cfc45ee764/dispatch/theme/validators.py#L49-L59", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:ubyssey-dispatch:is_valid_uuid-b88c3e2d4e@held-out", "question": "Return True if id is a valid UUID, False otherwise.", "scope": {"holder": "ubyssey-dispatch", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/ubyssey/dispatch/blob/8da6084fe61726f20e9cf675190480cfc45ee764/dispatch/theme/widgets.py#L142-L154", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:ubyssey-dispatch:Widget.render-6d328ed888@held-out", "question": "Renders the widget as HTML.", "scope": {"holder": "ubyssey-dispatch", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/ubyssey/dispatch/blob/8da6084fe61726f20e9cf675190480cfc45ee764/dispatch/modules/integrations/managers.py#L16-L30", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:ubyssey-dispatch:IntegrationManager.update_settings-9bc29ac1d0@held-out", "question": "Updates settings for given integration.", "scope": {"holder": "ubyssey-dispatch", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/admiralobvious/flask-mysqldb/blob/418c794e9b031addd026f29312865403baea55a0/flask_mysqldb/__init__.py#L13-L37", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:admiralobvious-flask-mysqldb:MySQL.init_app-a410e8a507@held-out", "question": "Initialize the `app` for use with this\n :class:`~flask_mysqldb.MySQL` class.\n This is called automatically if `app` is passed to\n :meth:`~MySQL.__init__`.\n\n :param flask.Flask app: the application to configure for use with\n this :class:`~flask_mysqldb.MySQL` class.", "scope": {"holder": "admiralobvious-flask-mysqldb", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/admiralobvious/flask-mysqldb/blob/418c794e9b031addd026f29312865403baea55a0/flask_mysqldb/__init__.py#L84-L95", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:admiralobvious-flask-mysqldb:MySQL.connection-1ebba1f939@held-out", "question": "Attempts to connect to the MySQL server.\n\n :return: Bound MySQL connection object if successful or ``None`` if\n unsuccessful.", "scope": {"holder": "admiralobvious-flask-mysqldb", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/boto/s3transfer/blob/2aead638c8385d8ae0b1756b2de17e8fad45fffa/s3transfer/utils.py#L69-L95", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:boto-s3transfer:calculate_range_parameter-c96e89f6bd@held-out", "question": "Calculate the range parameter for multipart downloads/copies\n\n :type part_size: int\n :param part_size: The size of the part\n\n :type part_index: int\n :param part_index: The index for which this parts starts. This index starts\n at zero\n\n :type num_parts: int\n :param num_parts: The total number of parts in the transfer\n\n :returns: The value to use for Range parameter on downloads or\n the CopySourceRange parameter for copies", "scope": {"holder": "boto-s3transfer", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/boto/s3transfer/blob/2aead638c8385d8ae0b1756b2de17e8fad45fffa/s3transfer/download.py#L91-L103", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:boto-s3transfer:DownloadOutputManager.queue_file_io_task-0114d2b2c1@held-out", "question": "Queue IO write for submission to the IO executor.\n\n This method accepts an IO executor and information about the\n downloaded data, and handles submitting this to the IO executor.\n\n This method may defer submission to the IO executor if necessary.", "scope": {"holder": "boto-s3transfer", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/boto/s3transfer/blob/2aead638c8385d8ae0b1756b2de17e8fad45fffa/s3transfer/download.py#L566-L574", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:boto-s3transfer:IOWriteTask._main-b85d9ee955@held-out", "question": "Pulls off an io queue to write contents to a file\n\n :param fileobj: The file handle to write content to\n :param data: The data to write\n :param offset: The offset to write the data to.", "scope": {"holder": "boto-s3transfer", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/boto/s3transfer/blob/2aead638c8385d8ae0b1756b2de17e8fad45fffa/s3transfer/download.py#L680-L712", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:boto-s3transfer:DeferQueue.request_writes-3a94ca36e9@held-out", "question": "Request any available writes given new incoming data.\n\n You call this method by providing new data along with the\n offset associated with the data. If that new data unlocks\n any contiguous writes that can now be submitted, this\n method will return all applicable writes.\n\n This is done with 1 method call so you don't have to\n make two method calls (put(), get()) which acquires a lock\n each method call.", "scope": {"holder": "boto-s3transfer", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/boto/s3transfer/blob/2aead638c8385d8ae0b1756b2de17e8fad45fffa/s3transfer/manager.py#L264-L303", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:boto-s3transfer:TransferManager.upload-c1cbcc482b@held-out", "question": "Uploads a file to S3\n\n :type fileobj: str or seekable file-like object\n :param fileobj: The name of a file to upload or a seekable file-like\n object to upload. It is recommended to use a filename because\n file-like objects may result in higher memory usage.\n\n :type bucket: str\n :param bucket: The name of the bucket to upload to\n\n :type key: str\n :param key: The name of the key to upload to\n\n :type extra_args: dict\n :param extra_args: Extra arguments that may be passed to the\n client operation\n\n :type subscribers: list(s3transfer.subscribers.BaseSubscriber)\n :param subscribers: The list of subscribers to be invoked in the\n order provided based on the event emit during the process of\n the transfer request.\n\n :rtype: s3transfer.futures.TransferFuture\n :returns: Transfer future representing the upload", "scope": {"holder": "boto-s3transfer", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/boto/s3transfer/blob/2aead638c8385d8ae0b1756b2de17e8fad45fffa/s3transfer/upload.py#L463-L482", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:boto-s3transfer:UploadNonSeekableInputManager._wrap_data-36d773a5a6@held-out", "question": "Wraps data with the interrupt reader and the file chunk reader.\n\n :type data: bytes\n :param data: The data to wrap.\n\n :type callbacks: list\n :param callbacks: The callbacks associated with the transfer future.\n\n :type close_callbacks: list\n :param close_callbacks: The callbacks to be called when closing the\n wrapper for the data.\n\n :return: Fully wrapped data.", "scope": {"holder": "boto-s3transfer", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/boto/s3transfer/blob/2aead638c8385d8ae0b1756b2de17e8fad45fffa/s3transfer/futures.py#L359-L370", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:boto-s3transfer:TransferCoordinator.announce_done-b7dfea9cc6@held-out", "question": "Announce that future is done running and run associated callbacks\n\n This will run any failure cleanups if the transfer failed if not\n they have not been run, allows the result() to be unblocked, and will\n run any done callbacks associated to the TransferFuture if they have\n not already been ran.", "scope": {"holder": "boto-s3transfer", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/boto/s3transfer/blob/2aead638c8385d8ae0b1756b2de17e8fad45fffa/s3transfer/copies.py#L271-L288", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:boto-s3transfer:CopyObjectTask._main-5cc23ea506@held-out", "question": ":param client: The client to use when calling PutObject\n :param copy_source: The CopySource parameter to use\n :param bucket: The name of the bucket to copy to\n :param key: The name of the key to copy to\n :param extra_args: A dictionary of any extra arguments that may be\n used in the upload.\n :param callbacks: List of callbacks to call after copy\n :param size: The size of the transfer. This value is passed into\n the callbacks", "scope": {"holder": "boto-s3transfer", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/boto/s3transfer/blob/2aead638c8385d8ae0b1756b2de17e8fad45fffa/s3transfer/tasks.py#L233-L278", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:boto-s3transfer:SubmissionTask._main-5f6b31eea6@held-out", "question": ":type transfer_future: s3transfer.futures.TransferFuture\n :param transfer_future: The transfer future associated with the\n transfer request that tasks are being submitted for\n\n :param kwargs: Any additional kwargs that you may want to pass\n to the _submit() method", "scope": {"holder": "boto-s3transfer", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/getgauge/gauge-python/blob/90f3547dcfd2d16d51f116cdd4e53527eeab1a57/getgauge/parser_parso.py#L87-L98", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:getgauge-gauge-python:ParsoPythonFile._find_step_node-5c998b5b60@held-out", "question": "Find the ast node which contains the text.", "scope": {"holder": "getgauge-gauge-python", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/CiscoDevNet/webexteamssdk/blob/6fc2cc3557e080ba4b2a380664cb2a0532ae45cd/webexteamssdk/utils.py#L59-L71", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:CiscoDevNet-webexteamssdk:to_unicode-5b5f4cdb31@held-out", "question": "Convert a string (bytes, str or unicode) to unicode.", "scope": {"holder": "CiscoDevNet-webexteamssdk", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/CiscoDevNet/webexteamssdk/blob/6fc2cc3557e080ba4b2a380664cb2a0532ae45cd/webexteamssdk/api/rooms.py#L76-L133", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:CiscoDevNet-webexteamssdk:RoomsAPI.list-f7b171d4e6@held-out", "question": "List rooms.\n\n By default, lists rooms to which the authenticated user belongs.\n\n This method supports Webex Teams's implementation of RFC5988 Web\n Linking to provide pagination support. It returns a generator\n container that incrementally yields all rooms returned by the\n query. The generator will automatically request additional 'pages' of\n responses from Webex as needed until all responses have been returned.\n The container makes the generator safe for reuse. A new API call will\n be made, using the same parameters that were specified when the\n generator was created, every time a new iterator is requested from the\n container.\n\n Args:\n teamId(basestring): Limit the rooms to those associated with a\n team, by ID.\n type(basestring): 'direct' returns all 1-to-1 rooms. `group`\n returns all group rooms. If not specified or values not\n matched, will return all room types.\n sortBy(basestring): Sort results by room ID (`id`), most recent\n activity (`lastactivity`), or most recently created\n (`created`).\n max(int): Limit the maximum number of items returned from the Webex\n Teams service per request.\n **request_parameters: Additional request parameters (provides\n support for parameters that may be added in the future).\n\n Returns:\n GeneratorContainer: A GeneratorContainer which, when iterated,\n yields the rooms returned by the Webex Teams query.\n\n Raises:\n TypeError: If the parameter types are incorrect.\n ApiError: If the Webex Teams cloud returns an error.", "scope": {"holder": "CiscoDevNet-webexteamssdk", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/CiscoDevNet/webexteamssdk/blob/6fc2cc3557e080ba4b2a380664cb2a0532ae45cd/webexteamssdk/api/webhooks.py#L118-L162", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:CiscoDevNet-webexteamssdk:WebhooksAPI.create-10dc238ac8@held-out", "question": "Create a webhook.\n\n Args:\n name(basestring): A user-friendly name for this webhook.\n targetUrl(basestring): The URL that receives POST requests for\n each event.\n resource(basestring): The resource type for the webhook.\n event(basestring): The event type for the webhook.\n filter(basestring): The filter that defines the webhook scope.\n secret(basestring): The secret used to generate payload signature.\n **request_parameters: Additional request parameters (provides\n support for parameters that may be added in the future).\n\n Returns:\n Webhook: A Webhook object with the details of the created webhook.\n\n Raises:\n TypeError: If the parameter types are incorrect.\n ApiError: If the Webex Teams cloud returns an error.", "scope": {"holder": "CiscoDevNet-webexteamssdk", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/CiscoDevNet/webexteamssdk/blob/6fc2cc3557e080ba4b2a380664cb2a0532ae45cd/webexteamssdk/restsession.py#L155-L159", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:CiscoDevNet-webexteamssdk:RestSession.single_request_timeout-cfe0020497@held-out", "question": "The timeout (seconds) for a single HTTP REST API request.", "scope": {"holder": "CiscoDevNet-webexteamssdk", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/CiscoDevNet/webexteamssdk/blob/6fc2cc3557e080ba4b2a380664cb2a0532ae45cd/webexteamssdk/restsession.py#L174-L177", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:CiscoDevNet-webexteamssdk:RestSession.wait_on_rate_limit-644d22bcc5@held-out", "question": "Enable or disable automatic rate-limit handling.", "scope": {"holder": "CiscoDevNet-webexteamssdk", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/CiscoDevNet/webexteamssdk/blob/6fc2cc3557e080ba4b2a380664cb2a0532ae45cd/webexteamssdk/api/roles.py#L76-L100", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:CiscoDevNet-webexteamssdk:RolesAPI.list-bcbeabe894@held-out", "question": "List all roles.\n\n Args:\n **request_parameters: Additional request parameters (provides\n support for parameters that may be added in the future).\n\n Returns:\n GeneratorContainer: A GeneratorContainer which, when iterated,\n yields the roles returned by the Webex Teams query.\n\n Raises:\n TypeError: If the parameter types are incorrect.\n ApiError: If the Webex Teams cloud returns an error.", "scope": {"holder": "CiscoDevNet-webexteamssdk", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/CiscoDevNet/webexteamssdk/blob/6fc2cc3557e080ba4b2a380664cb2a0532ae45cd/examples/ngrokwebhook.py#L76-L92", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:CiscoDevNet-webexteamssdk:get_ngrok_public_url-f8e2ffc8da@held-out", "question": "Get the ngrok public HTTP URL from the local client API.", "scope": {"holder": "CiscoDevNet-webexteamssdk", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/ndokter/dsmr_parser/blob/c04b0a5add58ce70153eede1a87ca171876b61c7/dsmr_parser/__main__.py#L9-L65", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:ndokter-dsmr_parser:console-70d1d9d724@held-out", "question": "Output DSMR data to console.", "scope": {"holder": "ndokter-dsmr_parser", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/ndokter/dsmr_parser/blob/c04b0a5add58ce70153eede1a87ca171876b61c7/dsmr_parser/clients/serial_.py#L51-L78", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:ndokter-dsmr_parser:AsyncSerialReader.read-58e33d61bf@held-out", "question": "Read complete DSMR telegram's from the serial interface and parse it\n into CosemObject's and MbusObject's.\n\n Instead of being a generator, values are pushed to provided queue for\n asynchronous processing.\n\n :rtype: None", "scope": {"holder": "ndokter-dsmr_parser", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/ndokter/dsmr_parser/blob/c04b0a5add58ce70153eede1a87ca171876b61c7/dsmr_parser/clients/protocol.py#L98-L109", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:ndokter-dsmr_parser:DSMRProtocol.handle_telegram-b863994731@held-out", "question": "Send off parsed telegram to handling callback.", "scope": {"holder": "ndokter-dsmr_parser", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/ndokter/dsmr_parser/blob/c04b0a5add58ce70153eede1a87ca171876b61c7/dsmr_parser/parsers.py#L62-L92", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:ndokter-dsmr_parser:TelegramParser.validate_checksum-c804177ce5@held-out", "question": ":param str telegram:\n :raises ParseError:\n :raises InvalidChecksumError:", "scope": {"holder": "ndokter-dsmr_parser", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/ndokter/dsmr_parser/blob/c04b0a5add58ce70153eede1a87ca171876b61c7/dsmr_parser/clients/telegram_buffer.py#L29-L39", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:ndokter-dsmr_parser:TelegramBuffer._remove-a3d080b8e6@held-out", "question": "Remove telegram from buffer and incomplete data preceding it. This\n is easier than validating the data before adding it to the buffer.\n :param str telegram:\n :return:", "scope": {"holder": "ndokter-dsmr_parser", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/jupyter-widgets/jupyterlab-sidecar/blob/8889d09f1a0933e2cbee06d4874f720b075b29e8/setupbase.py#L295-L308", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:jupyter-widgets-jupyterlab-sidecar:recursive_mtime-e7e52267ff@held-out", "question": "Gets the newest/oldest mtime for all files in a directory.", "scope": {"holder": "jupyter-widgets-jupyterlab-sidecar", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/jupyter-widgets/jupyterlab-sidecar/blob/8889d09f1a0933e2cbee06d4874f720b075b29e8/setupbase.py#L454-L480", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:jupyter-widgets-jupyterlab-sidecar:_wrap_command-cdf51011f9@held-out", "question": "Wrap a setup command\n\n Parameters\n ----------\n cmds: list(str)\n The names of the other commands to run prior to the command.\n strict: boolean, optional\n Whether to raise errors when a pre-command fails.", "scope": {"holder": "jupyter-widgets-jupyterlab-sidecar", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/jupyter-widgets/jupyterlab-sidecar/blob/8889d09f1a0933e2cbee06d4874f720b075b29e8/setupbase.py#L583-L601", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:jupyter-widgets-jupyterlab-sidecar:_get_package_data-eaeca670c6@held-out", "question": "Expand file patterns to a list of `package_data` paths.\n\n Parameters\n -----------\n root: str\n The relative path to the package root from `HERE`.\n file_patterns: list or str, optional\n A list of glob patterns for the data file locations.\n The globs can be recursive if they include a `**`.\n They should be relative paths from the root or\n absolute paths. If not given, all files will be used.\n\n Note:\n Files in `node_modules` are ignored.", "scope": {"holder": "jupyter-widgets-jupyterlab-sidecar", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/jupyter-widgets/jupyterlab-sidecar/blob/8889d09f1a0933e2cbee06d4874f720b075b29e8/setupbase.py#L604-L613", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:jupyter-widgets-jupyterlab-sidecar:_compile_pattern-313dfad73a@held-out", "question": "Translate and compile a glob pattern to a regular expression matcher.", "scope": {"holder": "jupyter-widgets-jupyterlab-sidecar", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/memsql/memsql-python/blob/aac223a1b937d5b348b42af3c601a6c685ca633a/memsql/common/sql_step_queue/queue.py#L55-L63", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:memsql-memsql-python:SQLStepQueue.enqueue-410e503c84@held-out", "question": "Enqueue task with specified data.", "scope": {"holder": "memsql-memsql-python", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/memsql/memsql-python/blob/aac223a1b937d5b348b42af3c601a6c685ca633a/memsql/common/database.py#L95-L100", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:memsql-memsql-python:Connection.reconnect-78daf8d575@held-out", "question": "Closes the existing database connection and re-opens it.", "scope": {"holder": "memsql-memsql-python", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/memsql/memsql-python/blob/aac223a1b937d5b348b42af3c601a6c685ca633a/memsql/common/errorcodes.py#L838-L842", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:memsql-memsql-python:lookup_by_number-00bcbb206f@held-out", "question": "Used for development only", "scope": {"holder": "memsql-memsql-python", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/memsql/memsql-python/blob/aac223a1b937d5b348b42af3c601a6c685ca633a/memsql/common/connection_pool.py#L90-L92", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:memsql-memsql-python:ConnectionPool.size-8de06d3118@held-out", "question": "Returns the number of connections cached by the pool.", "scope": {"holder": "memsql-memsql-python", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/memsql/memsql-python/blob/aac223a1b937d5b348b42af3c601a6c685ca633a/memsql/common/connection_pool.py#L134-L147", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:memsql-memsql-python:_PoolConnectionFairy.__potential_connection_failure-8d3fbe88f8@held-out", "question": "OperationalError's are emitted by the _mysql library for\n almost every error code emitted by MySQL. Because of this we\n verify that the error is actually a connection error before\n terminating the connection and firing off a PoolConnectionException", "scope": {"holder": "memsql-memsql-python", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/memsql/memsql-python/blob/aac223a1b937d5b348b42af3c601a6c685ca633a/memsql/common/sql_lock.py#L98-L108", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:memsql-memsql-python:SQLLock.release-436904593c@held-out", "question": "Release the lock.", "scope": {"holder": "memsql-memsql-python", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/memsql/memsql-python/blob/aac223a1b937d5b348b42af3c601a6c685ca633a/memsql/common/sql_utility.py#L41-L48", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:memsql-memsql-python:SQLUtility.ready-f7fac27330@held-out", "question": "Returns True if the tables have been setup, False otherwise", "scope": {"holder": "memsql-memsql-python", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/memsql/memsql-python/blob/aac223a1b937d5b348b42af3c601a6c685ca633a/memsql/common/sql_step_queue/task_handler.py#L129-L145", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:memsql-memsql-python:TaskHandler.stop_step-77b554fac7@held-out", "question": "Stop a step.", "scope": {"holder": "memsql-memsql-python", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Crypto-toolbox/btfxwss/blob/16827fa6aacb2c0e289aa852bf61a18df6905835/btfxwss/connection.py#L316-L324", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Crypto-toolbox-btfxwss:WebSocketConnection.pass_to_client-b11d2025f7@held-out", "question": "Passes data up to the client via a Queue().\n\n :param event:\n :param data:\n :param args:\n :return:", "scope": {"holder": "Crypto-toolbox-btfxwss", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Crypto-toolbox/btfxwss/blob/16827fa6aacb2c0e289aa852bf61a18df6905835/btfxwss/queue_processor.py#L205-L215", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Crypto-toolbox-btfxwss:QueueProcessor._handle_conf-9aa93b5e8d@held-out", "question": "Handles configuration messages.\n\n :param dtype:\n :param data:\n :param ts:\n :return:", "scope": {"holder": "Crypto-toolbox-btfxwss", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Crypto-toolbox/btfxwss/blob/16827fa6aacb2c0e289aa852bf61a18df6905835/btfxwss/client.py#L199-L207", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Crypto-toolbox-btfxwss:BtfxWss.unsubscribe_from_ticker-82ee1920a1@held-out", "question": "Unsubscribe to the passed pair's ticker channel.\n\n :param pair: str, Symbol pair to request data for\n :param kwargs:\n :return:", "scope": {"holder": "Crypto-toolbox-btfxwss", "scenario": "code-search", "session": null}, "split": "dev", "unanswerable": true}
{"answer": null, "answer_format": "code", "as_of": "2026-02-23T14:11:41+00:00", "gold": [], "modality": "code", "origin": {"construction": "held-out function", "dataset": "code-search-net/code_search_net", "item": "url:https://github.com/Crypto-toolbox/btfxwss/blob/16827fa6aacb2c0e289aa852bf61a18df6905835/btfxwss/client.py#L258-L266", "revision": "bd0cf261e357a3eb5c8fba490d23ec1a1cd59555"}, "query_id": "csn:Crypto-toolbox-btfxwss:BtfxWss.subscribe_to_trades-e15f274303@held-out", "question": "Subscribe to the passed pair's trades channel.\n\n :param pair: str, Symbol pair to request data for\n :param kwargs:\n :return:", "scope": {"holder": "Crypto-toolbox-btfxwss", "scenario": "code-search", "session": null}, "split": "test", "unanswerable": true}
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