7293664 report - OSSR Reports

Repository Information

Repository Name: IndexedConv/IndexedConv: v1.3.2
Record ID: 7293664
Repository URL: https://github.com/IndexedConv/IndexedConv
Tool Type: SoftwareSourceCode
Version: 1.3.2

Results

Indicator	generated by	evidence	Value	Run Status	Check passed
https://w3id.org/everse/i/indicators/codemeta_completeness	Codemeta Completeness Tool	Codemeta completeness = 32.4%, minimal threshold to consider this check to pass is set to 20.0%. Found ['codeRepository', 'programmingLanguage', 'applicationCategory', 'downloadUrl', 'softwareVersion', 'author', 'dateCreated', 'dateModified', 'datePublished', 'funder', 'keywords', 'license', 'version', 'isPartOf', 'description', 'identifier', 'name', 'identifier', 'name', 'maintainer', 'contIntegration', 'funding', 'issueTracker', 'readme'] keys in codemeta file.	0.32432432432432434	✅	✅
https://w3id.org/everse/i/indicators/codemeta_completeness	Codemeta Completeness Tool	Codemeta completeness = 32.4%, minimal threshold to consider this check to pass is set to 50.0%. Found ['codeRepository', 'programmingLanguage', 'applicationCategory', 'downloadUrl', 'softwareVersion', 'author', 'dateCreated', 'dateModified', 'datePublished', 'funder', 'keywords', 'license', 'version', 'isPartOf', 'description', 'identifier', 'name', 'identifier', 'name', 'maintainer', 'contIntegration', 'funding', 'issueTracker', 'readme'] keys in codemeta file.	0.32432432432432434	✅	❌
https://w3id.org/everse/i/indicators/doi_presence	SOMEF	Found DOI: https://doi.org/10.5281/zenodo.2542651 with confidence 100.0% from source https://raw.githubusercontent.com/IndexedConv/IndexedConv/master/codemeta.json	https://doi.org/10.5281/zenodo.2542651	⚠️	✅
https://w3id.org/everse/i/indicators/codemeta_discrepancy	SOMEF, Codemeta Completeness Tool	Comparison value: 0.6764705882352942, Threshold: 0.5, Status: True	0.6764705882352942	⚠️	✅

Results Output

https://w3id.org/everse/i/indicators/codemeta_completeness

Status: CompletedActionStatus
Value: 0.32
Evidence: Codemeta completeness = 32.4%, minimal threshold to consider this check to pass is set to 20.0%. Found ['codeRepository', 'programmingLanguage', 'applicationCategory', 'downloadUrl', 'softwareVersion', 'author', 'dateCreated', 'dateModified', 'datePublished', 'funder', 'keywords', 'license', 'version', 'isPartOf', 'description', 'identifier', 'name', 'identifier', 'name', 'maintainer', 'contIntegration', 'funding', 'issueTracker', 'readme'] keys in codemeta file.
Output:

{"pass": true, "value": 0.32432432432432434, "codemeta_dict": {"@context": "https://doi.org/10.5063/schema/codemeta-2.0", "@type": "SoftwareSourceCode", "license": "https://spdx.org/licenses/MIT", "codeRepository": "git+https://github.com/IndexedConv/IndexedConv.git", "contIntegration": "https://github.com/IndexedConv/IndexedConv/actions", "dateCreated": "2018-12-05", "datePublished": "2019-01-14", "dateModified": "2022-01-20", "downloadUrl": "https://zenodo.org/record/5884046/files/IndexedConv/IndexedConv-v1.3.1.zip", "issueTracker": "https://github.com/IndexedConv/IndexedConv/issues", "name": "IndexedConv", "version": "1.3.2", "softwareVersion": "1.3.2", "maintainer": {"@type": "Person", "givenName": "Mikael", "familyName": "Jacquemont", "@id": "https://orcid.org/0000-0002-4012-6930", "email": "jacquemont@lapp.in2p3.fr", "affiliation": {"@type": "Organization", "name": "Univ. Savoie Mont-Blanc, CNRS, LAPP"}}, "readme": "https://raw.githubusercontent.com/IndexedConv/IndexedConv/master/README.rst", "identifier": "10.5281/zenodo.2542651", "description": "The indexed operations allow the user to perform convolution and pooling on non-Euclidian grids of data given that the neighbors pixels of each pixel is known and provided.\n\nIt gives an alternative to masking or resampling the data in order to apply standard Euclidian convolution. This solution has been developed in order to apply convolutional neural networks to data from physics experiments that propose specific pixels arrangements.\n\nIt is used in the GammaLearn project for the Cherenkov Telescope Array.\n\nHere you will find the code for the indexed operations as well as applied examples. The current implementation has been done for pytorch.", "applicationCategory": "deep learning", "funding": "ESCAPE 824064, ASTERICS 653477", "isPartOf": "https://purl.org/gammalearn", "funder": {"@type": "Organization", "name": "European Union's Horizon 2020 research and innovation programme"}, "keywords": ["CTA"], "programmingLanguage": ["Python 3"], "author": [{"@type": "Person", "givenName": "Thomas", "familyName": "Vuillaume", "@id": "https://orcid.org/0000-0002-5686-2078", "email": "thomas.vuillaume@lapp.in2p3.fr", "affiliation": {"@type": "Organization", "name": "Univ. Savoie Mont-Blanc, CNRS, LAPP"}}, {"@type": "Person", "givenName": "Mikael", "familyName": "Jacquemont", "@id": "https://orcid.org/0000-0002-4012-6930", "email": "jacquemont@lapp.in2p3.fr", "affiliation": {"@type": "Organization", "name": "Univ. Savoie Mont-Blanc, CNRS, LAPP"}}, {"@type": "Person", "givenName": "Antiga", "familyName": "Luca", "affiliation": {"@type": "Organization", "name": "Orobix"}}]}, "threshold": 0.2}

https://w3id.org/everse/i/indicators/codemeta_completeness

Status: CompletedActionStatus
Value: 0.32
Evidence: Codemeta completeness = 32.4%, minimal threshold to consider this check to pass is set to 50.0%. Found ['codeRepository', 'programmingLanguage', 'applicationCategory', 'downloadUrl', 'softwareVersion', 'author', 'dateCreated', 'dateModified', 'datePublished', 'funder', 'keywords', 'license', 'version', 'isPartOf', 'description', 'identifier', 'name', 'identifier', 'name', 'maintainer', 'contIntegration', 'funding', 'issueTracker', 'readme'] keys in codemeta file.
Output:

{"pass": false, "value": 0.32432432432432434, "codemeta_dict": {"@context": "https://doi.org/10.5063/schema/codemeta-2.0", "@type": "SoftwareSourceCode", "license": "https://spdx.org/licenses/MIT", "codeRepository": "git+https://github.com/IndexedConv/IndexedConv.git", "contIntegration": "https://github.com/IndexedConv/IndexedConv/actions", "dateCreated": "2018-12-05", "datePublished": "2019-01-14", "dateModified": "2022-01-20", "downloadUrl": "https://zenodo.org/record/5884046/files/IndexedConv/IndexedConv-v1.3.1.zip", "issueTracker": "https://github.com/IndexedConv/IndexedConv/issues", "name": "IndexedConv", "version": "1.3.2", "softwareVersion": "1.3.2", "maintainer": {"@type": "Person", "givenName": "Mikael", "familyName": "Jacquemont", "@id": "https://orcid.org/0000-0002-4012-6930", "email": "jacquemont@lapp.in2p3.fr", "affiliation": {"@type": "Organization", "name": "Univ. Savoie Mont-Blanc, CNRS, LAPP"}}, "readme": "https://raw.githubusercontent.com/IndexedConv/IndexedConv/master/README.rst", "identifier": "10.5281/zenodo.2542651", "description": "The indexed operations allow the user to perform convolution and pooling on non-Euclidian grids of data given that the neighbors pixels of each pixel is known and provided.\n\nIt gives an alternative to masking or resampling the data in order to apply standard Euclidian convolution. This solution has been developed in order to apply convolutional neural networks to data from physics experiments that propose specific pixels arrangements.\n\nIt is used in the GammaLearn project for the Cherenkov Telescope Array.\n\nHere you will find the code for the indexed operations as well as applied examples. The current implementation has been done for pytorch.", "applicationCategory": "deep learning", "funding": "ESCAPE 824064, ASTERICS 653477", "isPartOf": "https://purl.org/gammalearn", "funder": {"@type": "Organization", "name": "European Union's Horizon 2020 research and innovation programme"}, "keywords": ["CTA"], "programmingLanguage": ["Python 3"], "author": [{"@type": "Person", "givenName": "Thomas", "familyName": "Vuillaume", "@id": "https://orcid.org/0000-0002-5686-2078", "email": "thomas.vuillaume@lapp.in2p3.fr", "affiliation": {"@type": "Organization", "name": "Univ. Savoie Mont-Blanc, CNRS, LAPP"}}, {"@type": "Person", "givenName": "Mikael", "familyName": "Jacquemont", "@id": "https://orcid.org/0000-0002-4012-6930", "email": "jacquemont@lapp.in2p3.fr", "affiliation": {"@type": "Organization", "name": "Univ. Savoie Mont-Blanc, CNRS, LAPP"}}, {"@type": "Person", "givenName": "Antiga", "familyName": "Luca", "affiliation": {"@type": "Organization", "name": "Orobix"}}]}, "threshold": 0.5}

https://w3id.org/everse/i/indicators/codemeta_discrepancy

Status: PotentialActionStatus
Value: 0.68
Evidence: Comparison value: 0.6764705882352942, Threshold: 0.5, Status: True
Output:

{"pass": true, "value": 0.6764705882352942, "threshold": 0.5, "results": {"completeness_1": 0.32432432432432434, "codemeta_version_1": "codemeta-2.0", "codemeta_version_2": "codemeta-3.0", "completeness_2": 0.2972972972972973, "missing_keys_1": ["runtimePlatform", "targetProduct", "applicationSubCategory", "fileSize", "installUrl", "memoryRequirements", "operatingSystem", "permissions", "processorRequirements", "releaseNotes", "softwareHelp", "softwareRequirements", "storageRequirements", "supportingData", "citation", "contributor", "copyrightHolder", "copyrightYear", "editor", "encoding", "fileFormat", "producer", "provider", "publisher", "sponsor", "isAccessibleForFree", "hasPart", "position", "sameAs", "url", "relatedLink", "givenName", "familyName", "email", "affiliation", "address", "", "", "softwareSuggestions", "buildInstructions", "developmentStatus", "embargoDate", "referencePublication", "creator", "", "", "", "endDate", "roleName", "startDate"], "missing_keys_2": ["runtimePlatform", "targetProduct", "applicationCategory", "applicationSubCategory", "fileSize", "installUrl", "memoryRequirements", "operatingSystem", "permissions", "processorRequirements", "softwareHelp", "softwareRequirements", "storageRequirements", "supportingData", "citation", "contributor", "copyrightHolder", "copyrightYear", "editor", "encoding", "fileFormat", "funder", "producer", "provider", "publisher", "sponsor", "version", "isAccessibleForFree", "isPartOf", "hasPart", "position", "sameAs", "relatedLink", "givenName", "familyName", "email", "affiliation", "address", "", "", "softwareSuggestions", "maintainer", "developmentStatus", "embargoEndDate", "funding", "creator", "review", "reviewAspect", "reviewBody", "endDate", "roleName", "startDate"], "existing_keys_1": ["codeRepository", "programmingLanguage", "applicationCategory", "downloadUrl", "softwareVersion", "author", "dateCreated", "dateModified", "datePublished", "funder", "keywords", "license", "version", "isPartOf", "description", "identifier", "name", "identifier", "name", "maintainer", "contIntegration", "funding", "issueTracker", "readme"], "existing_keys_2": ["codeRepository", "programmingLanguage", "downloadUrl", "releaseNotes", "softwareVersion", "author", "dateCreated", "dateModified", "datePublished", "keywords", "license", "description", "identifier", "name", "url", "identifier", "name", "continuousIntegration", "buildInstructions", "issueTracker", "referencePublication", "readme"], "differences": {"codeRepository": {"value_in_1": "git+https://github.com/IndexedConv/IndexedConv.git", "value_in_2": "https://github.com/IndexedConv/IndexedConv"}, "programmingLanguage": {"value_in_1": ["Python 3"], "value_in_2": ["Python", "Python 3.8"]}, "applicationCategory": {"value_in_1": "deep learning", "value_in_2": null}, "downloadUrl": {"value_in_1": "https://zenodo.org/record/5884046/files/IndexedConv/IndexedConv-v1.3.1.zip", "value_in_2": "https://github.com/IndexedConv/IndexedConv/releases"}, "releaseNotes": {"value_in_1": null, "value_in_2": "## What's Changed\r\n* Update test badge by @vuillaut in https://github.com/IndexedConv/IndexedConv/pull/33\r\n* Create codemeta.json by @vuillaut in https://github.com/IndexedConv/IndexedConv/pull/34\r\n* Version 1.3.2 by @vuillaut in https://github.com/IndexedConv/IndexedConv/pull/35\r\n\r\n\r\n**Full Changelog**: https://github.com/IndexedConv/IndexedConv/compare/v1.3.1...v1.3.2"}, "softwareVersion": {"value_in_1": "1.3.2", "value_in_2": "v1.3.2"}, "author": {"value_in_1": [{"@type": "Person", "givenName": "Thomas", "familyName": "Vuillaume", "@id": "https://orcid.org/0000-0002-5686-2078", "email": "thomas.vuillaume@lapp.in2p3.fr", "affiliation": {"@type": "Organization", "name": "Univ. Savoie Mont-Blanc, CNRS, LAPP"}}, {"@type": "Person", "givenName": "Mikael", "familyName": "Jacquemont", "@id": "https://orcid.org/0000-0002-4012-6930", "email": "jacquemont@lapp.in2p3.fr", "affiliation": {"@type": "Organization", "name": "Univ. Savoie Mont-Blanc, CNRS, LAPP"}}, {"@type": "Person", "givenName": "Antiga", "familyName": "Luca", "affiliation": {"@type": "Organization", "name": "Orobix"}}], "value_in_2": [{"@type": "Organization", "@id": "https://github.com/IndexedConv"}, {"@type": "Person", "email": "thomas.vuillaume@lapp.in2p3.fr", "name": null}, {"@type": "Person", "email": "jacquemont@lapp.in2p3.fr", "name": null}, {"@type": "Person", "name": null}]}, "dateCreated": {"value_in_1": "2018-12-05", "value_in_2": "2018-09-26"}, "dateModified": {"value_in_1": "2022-01-20", "value_in_2": "2026-03-04"}, "funder": {"value_in_1": {"@type": "Organization", "name": "European Union's Horizon 2020 research and innovation programme"}, "value_in_2": null}, "keywords": {"value_in_1": ["CTA"], "value_in_2": "cnn, convolution, hexagonal, pytorch"}, "license": {"value_in_1": "https://spdx.org/licenses/MIT", "value_in_2": {"name": "MIT License", "url": "https://raw.githubusercontent.com/IndexedConv/IndexedConv/master/LICENSE", "identifier": "https://spdx.org/licenses/MIT", "spdx_id": "MIT"}}, "version": {"value_in_1": "1.3.2", "value_in_2": null}, "isPartOf": {"value_in_1": "https://purl.org/gammalearn", "value_in_2": null}, "description": {"value_in_1": "The indexed operations allow the user to perform convolution and pooling on non-Euclidian grids of data given that the neighbors pixels of each pixel is known and provided.\n\nIt gives an alternative to masking or resampling the data in order to apply standard Euclidian convolution. This solution has been developed in order to apply convolutional neural networks to data from physics experiments that propose specific pixels arrangements.\n\nIt is used in the GammaLearn project for the Cherenkov Telescope Array.\n\nHere you will find the code for the indexed operations as well as applied examples. The current implementation has been done for pytorch.", "value_in_2": ["The indexed operations allow the user to perform convolution and pooling on non-Euclidian grids of data given that the neighbors pixels of each pixel is known and provided.\n\nIt gives an alternative to masking or resampling the data in order to apply standard Euclidian convolution. This solution has been developed in order to apply convolutional neural networks to data from physics experiments that propose specific pixels arrangements.\n\nIt is used in the GammaLearn project for the Cherenkov Telescope Array.\n\nHere you will find the code for the indexed operations as well as applied examples. The current implementation has been done for pytorch."]}, "identifier": {"value_in_1": "10.5281/zenodo.2542651", "value_in_2": ["https://doi.org/10.5281/zenodo.2542651", "https://doi.org/10.5281/zenodo.7293664"]}, "url": {"value_in_1": null, "value_in_2": ["https://indexed-convolution.readthedocs.io"]}, "maintainer": {"value_in_1": {"@type": "Person", "givenName": "Mikael", "familyName": "Jacquemont", "@id": "https://orcid.org/0000-0002-4012-6930", "email": "jacquemont@lapp.in2p3.fr", "affiliation": {"@type": "Organization", "name": "Univ. Savoie Mont-Blanc, CNRS, LAPP"}}, "value_in_2": null}, "contIntegration": {"value_in_1": "https://github.com/IndexedConv/IndexedConv/actions", "value_in_2": null}, "buildInstructions": {"value_in_1": null, "value_in_2": ["https://raw.githubusercontent.com/IndexedConv/IndexedConv/master/README.rst", "https://indexed-convolution.readthedocs.io/en/latest/?badge=latest"]}, "funding": {"value_in_1": "ESCAPE 824064, ASTERICS 653477", "value_in_2": null}, "referencePublication": {"value_in_1": null, "value_in_2": [{"@type": "ScholarlyArticle", "identifier": "10.5220/0007364303620371", "name": "Indexed Operations for Non-rectangular Lattices Applied to Convolutional Neural Networks", "datePublished": "2019", "pagination": "362-371", "author": [{"@type": "Person", "familyName": "Mikael Jacquemont."}, {"@type": "Person", "familyName": "Luca Antiga."}, {"@type": "Person", "familyName": "Thomas Vuillaume."}, {"@type": "Person", "familyName": "Giorgia Silvestri."}, {"@type": "Person", "familyName": "Alexandre Benoit."}, {"@type": "Person", "familyName": "Patrick Lambert."}, {"@type": "Person", "familyName": "Gilles Maurin."}]}]}}, "equivalences": {"runtimePlatform": null, "targetProduct": null, "applicationSubCategory": null, "fileSize": null, "installUrl": null, "memoryRequirements": null, "operatingSystem": null, "permissions": null, "processorRequirements": null, "softwareHelp": null, "softwareRequirements": null, "storageRequirements": null, "supportingData": null, "citation": null, "contributor": null, "copyrightHolder": null, "copyrightYear": null, "datePublished": "2019-01-14", "editor": null, "encoding": null, "fileFormat": null, "producer": null, "provider": null, "publisher": null, "sponsor": null, "isAccessibleForFree": null, "hasPart": null, "position": null, "name": "IndexedConv", "sameAs": null, "relatedLink": null, "givenName": null, "familyName": null, "email": null, "affiliation": null, "address": null, "": null, "softwareSuggestions": null, "developmentStatus": null, "embargoDate": null, "issueTracker": "https://github.com/IndexedConv/IndexedConv/issues", "readme": "https://raw.githubusercontent.com/IndexedConv/IndexedConv/master/README.rst", "creator": null, "endDate": null, "roleName": null, "startDate": null}}}

Logs

Log File: docs/records/7293664/7293664_somef_log.txt

2026-03-05 09:12:11,601 somef_tool.py:140 INFO Running SOMEF on repository: https://github.com/IndexedConv/IndexedConv
2026-03-05 09:12:24,580 somef_utils.py:43 INFO SOftware Metadata Extraction Framework (SOMEF) Command Line Interface
CODEMETA PARSER - Processing file: /tmp/tmpejfmcx8_/IndexedConv_IndexedConv/IndexedConv-master/codemeta.json
CODEMETA PARSER - Source: https://raw.githubusercontent.com/IndexedConv/IndexedConv/master/codemeta.json
Saving json data to docs/records/7293664/7293664_somef.json
Success

2026-03-05 09:12:24,580 somef_utils.py:45 ERROR 05-Mar-26 09:12:18-DEBUG-Starting new HTTPS connection (1): github.com:443
05-Mar-26 09:12:18-DEBUG-https://github.com:443 "GET /api/v4/projects HTTP/1.1" 404 9
05-Mar-26 09:12:18-INFO-Loading Repository https://github.com/IndexedConv/IndexedConv Information....
05-Mar-26 09:12:18-DEBUG-Starting new HTTPS connection (1): api.github.com:443
05-Mar-26 09:12:18-DEBUG-https://api.github.com:443 "GET /repos/IndexedConv/IndexedConv HTTP/1.1" 200 1468
05-Mar-26 09:12:18-INFO-Remaining GitHub API requests: 9 ### Next rate limit reset at: 2026-03-05 09:55:33
05-Mar-26 09:12:18-DEBUG-Starting new HTTPS connection (1): api.github.com:443
05-Mar-26 09:12:18-DEBUG-https://api.github.com:443 "GET /repos/IndexedConv/IndexedConv/languages HTTP/1.1" 200 16
05-Mar-26 09:12:18-INFO-Remaining GitHub API requests: 18 ### Next rate limit reset at: 2026-03-05 09:55:33
05-Mar-26 09:12:18-DEBUG-Starting new HTTPS connection (1): api.github.com:443
05-Mar-26 09:12:18-DEBUG-https://api.github.com:443 "GET /repos/IndexedConv/IndexedConv/releases?per_page=100&page=1 HTTP/1.1" 200 None
05-Mar-26 09:12:18-INFO-Remaining GitHub API requests: 8 ### Next rate limit reset at: 2026-03-05 09:55:33
05-Mar-26 09:12:18-DEBUG-Starting new HTTPS connection (1): api.github.com:443
05-Mar-26 09:12:18-DEBUG-https://api.github.com:443 "GET /repos/IndexedConv/IndexedConv/releases?per_page=100&page=2 HTTP/1.1" 200 2
05-Mar-26 09:12:18-INFO-Remaining GitHub API requests: 17 ### Next rate limit reset at: 2026-03-05 09:55:33
05-Mar-26 09:12:18-INFO-Repository information successfully loaded.

05-Mar-26 09:12:18-INFO-Downloading https://github.com/IndexedConv/IndexedConv/archive/master.zip
05-Mar-26 09:12:18-DEBUG-Starting new HTTPS connection (1): github.com:443
05-Mar-26 09:12:18-DEBUG-https://github.com:443 "GET /IndexedConv/IndexedConv/archive/master.zip HTTP/1.1" 302 0
05-Mar-26 09:12:18-DEBUG-Starting new HTTPS connection (1): codeload.github.com:443
05-Mar-26 09:12:18-DEBUG-https://codeload.github.com:443 "GET /IndexedConv/IndexedConv/zip/refs/heads/master HTTP/1.1" 200 None
05-Mar-26 09:12:18-WARNING-No Content-Length header for https://github.com/IndexedConv/IndexedConv/archive/master.zip. Proceeding with download anyway (unable to estimate size).
05-Mar-26 09:12:18-DEBUG-Starting new HTTPS connection (1): github.com:443
05-Mar-26 09:12:19-DEBUG-https://github.com:443 "GET /IndexedConv/IndexedConv/archive/master.zip HTTP/1.1" 302 0
05-Mar-26 09:12:19-DEBUG-Starting new HTTPS connection (1): codeload.github.com:443
05-Mar-26 09:12:19-DEBUG-https://codeload.github.com:443 "GET /IndexedConv/IndexedConv/zip/refs/heads/master HTTP/1.1" 200 None
05-Mar-26 09:12:19-INFO-############### Processing package file: setup.py ############### 
05-Mar-26 09:12:19-INFO-Extracting information using headers
/builds/escape-ossr/rs_quality_checks/.venv/lib/python3.11/site-packages/somef/header_analysis.py:112: FutureWarning: A value is trying to be set on a copy of a DataFrame or Series through chained assignment using an inplace method.
The behavior will change in pandas 3.0. This inplace method will never work because the intermediate object on which we are setting values always behaves as a copy.

For example, when doing 'df[col].method(value, inplace=True)', try using 'df.method({col: value}, inplace=True)' or df[col] = df[col].method(value) instead, to perform the operation inplace on the original object.


  df['Content'].replace('', np.nan, inplace=True)
05-Mar-26 09:12:19-INFO-Labeling headers.
/builds/escape-ossr/rs_quality_checks/.venv/lib/python3.11/site-packages/somef/header_analysis.py:224: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0!
You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy.
A typical example is when you are setting values in a column of a DataFrame, like:

df["col"][row_indexer] = value

Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`.

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy

  data['Group'].iloc[0] = ['unknown']
/builds/escape-ossr/rs_quality_checks/.venv/lib/python3.11/site-packages/somef/header_analysis.py:230: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0!
You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy.
A typical example is when you are setting values in a column of a DataFrame, like:

df["col"][row_indexer] = value

Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`.

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy

  data['Group'].iloc[0] = np.NaN
05-Mar-26 09:12:20-INFO-Header information extracted.
05-Mar-26 09:12:20-INFO-Splitting text into valid excerpts for classification
05-Mar-26 09:12:20-INFO-Extraction of bibtex citation from readme completed. 

05-Mar-26 09:12:20-INFO-Text Successfully split.
05-Mar-26 09:12:20-INFO-Classifying excerpts for the category description
05-Mar-26 09:12:20-INFO-Checking thresholds for classified excerpts.
05-Mar-26 09:12:20-INFO-All excerpts below the threshold have been removed.
05-Mar-26 09:12:20-DEBUG-Starting new HTTPS connection (1): zenodo.org:443
05-Mar-26 09:12:21-DEBUG-https://zenodo.org:443 "GET /badge/latestdoi/150430897 HTTP/1.1" 302 263
05-Mar-26 09:12:21-DEBUG-Starting new HTTPS connection (1): doi.org:443
05-Mar-26 09:12:21-DEBUG-https://doi.org:443 "GET /10.5281/zenodo.7293664 HTTP/1.1" 302 None
05-Mar-26 09:12:21-DEBUG-https://zenodo.org:443 "GET /record/7293664 HTTP/1.1" 301 219
05-Mar-26 09:12:23-DEBUG-https://zenodo.org:443 "GET /records/7293664 HTTP/1.1" 200 None
05-Mar-26 09:12:23-DEBUG-Starting new HTTPS connection (1): github.com:443
05-Mar-26 09:12:23-DEBUG-https://github.com:443 "GET /IndexedConv/IndexedConv/wiki HTTP/1.1" 302 0
05-Mar-26 09:12:23-DEBUG-Starting new HTTPS connection (1): anaconda.org:443
05-Mar-26 09:12:23-DEBUG-https://anaconda.org:443 "GET /gammalearn/indexedconv HTTP/1.1" 200 None
05-Mar-26 09:12:23-DEBUG-Starting new HTTPS connection (1): anaconda.org:443
05-Mar-26 09:12:23-DEBUG-https://anaconda.org:443 "GET /gammalearn/indexedconv HTTP/1.1" 200 None
05-Mar-26 09:12:23-INFO-Completed extracting regular expressions

Log File: docs/records/7293664/7293664_codemeta_completeness_tool_log.txt

2026-03-05 09:12:24,582 codemeta_completeness_tool.py:72 INFO [codemeta completeness tool] Running Codemeta Completeness Tool on record ID: 7293664

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