{"id":37066031,"url":"https://github.com/anwielts/datasheet-for-dataset","last_synced_at":"2026-01-14T07:44:43.953Z","repository":{"id":296684459,"uuid":"990172584","full_name":"anwielts/datasheet-for-dataset","owner":"anwielts","description":"Automatically create standardized documentation for the dataset used in your ML project","archived":false,"fork":false,"pushed_at":"2025-11-21T16:19:26.000Z","size":543,"stargazers_count":2,"open_issues_count":12,"forks_count":0,"subscribers_count":0,"default_branch":"main","last_synced_at":"2026-01-08T12:25:15.457Z","etag":null,"topics":["artificial-intelligence","data-science","documentation","machine-learning","python"],"latest_commit_sha":null,"homepage":"https://datasheet-for-dataset.readthedocs.io/en/latest/","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/anwielts.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null,"notice":null,"maintainers":null,"copyright":null,"agents":null,"dco":null,"cla":null}},"created_at":"2025-05-25T16:43:23.000Z","updated_at":"2025-10-25T19:56:21.000Z","dependencies_parsed_at":"2025-06-01T18:47:19.906Z","dependency_job_id":"5f5f13e2-62a9-4079-9f25-5099a4ca15ec","html_url":"https://github.com/anwielts/datasheet-for-dataset","commit_stats":null,"previous_names":["anwielts/datasheet-for-dataset"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/anwielts/datasheet-for-dataset","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/anwielts%2Fdatasheet-for-dataset","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/anwielts%2Fdatasheet-for-dataset/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/anwielts%2Fdatasheet-for-dataset/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/anwielts%2Fdatasheet-for-dataset/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/anwielts","download_url":"https://codeload.github.com/anwielts/datasheet-for-dataset/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/anwielts%2Fdatasheet-for-dataset/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":28413486,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-01-14T05:26:33.345Z","status":"ssl_error","status_checked_at":"2026-01-14T05:21:57.251Z","response_time":107,"last_error":"SSL_connect returned=1 errno=0 peeraddr=140.82.121.5:443 state=error: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["artificial-intelligence","data-science","documentation","machine-learning","python"],"created_at":"2026-01-14T07:44:42.909Z","updated_at":"2026-01-14T07:44:43.933Z","avatar_url":"https://github.com/anwielts.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"[![Contributors][contributors-shield]][contributors-url]\n[![Issues][issues-shield]][issues-url]\n[![Unlicense License][license-shield]][license-url]\n[![Build and Publish](https://github.com/anwielts/datasheet-for-dataset/actions/workflows/build_and_publish.yml/badge.svg)](https://github.com/anwielts/datasheet-for-dataset/actions/workflows/build_and_publish.yml) [![Test and Lint](https://github.com/anwielts/datasheet-for-dataset/actions/workflows/test_and_lint.yml/badge.svg)](https://github.com/anwielts/datasheet-for-dataset/actions/workflows/test_and_lint.yml)\n# datasheet-for-dataset\n\nAutomatically create standardized documentation (\"datasheets\") for the datasets used in your ML projects.\n\nStatus: Early preview (v0.x). The public API is evolving and subject to change.\n\n## Features\n- Focused support for tabular datasets with pandas and polars backends\n- Automatic summary statistics and data quality diagnostics\n- Markdown templates that combine manual answers with automated insights\n- CLI and Python APIs for integrating datasheet generation into workflows\n\n## Installation\nPrerequisites: Python 3.10+\n\nInstall from PyPI:\n```\npip install datasheet-for-dataset\n```\n\n### Install a suitable backend\nTo use this library correctly, install a supported backend. Currently available backends are `polars` (default) and `pandas`.\n\nInstall for development (editable) with optional dev tools:\n```\n# clone the repository\ngit clone https://github.com/anwielts/datasheet-for-dataset.git\ncd datasheet-for-dataset\n\n# install the package (and dev extras: pytest, ruff)\nuv pip install -e \".[dev]\"\n```\n\n## Quickstart\n\n### CLI workflow\nGenerate a template, fill in the manual sections, and compile the final markdown datasheet:\n\n```bash\n# create an empty questionnaire\ndfd template --output docs/datasheet_template.md\n\n# after answering the questions in docs/datasheet_template.md, combine it with a dataset\ndfd build \\\n  --data data/customers.csv \\\n  --template docs/datasheet_template.md \\\n  --output docs/datasheet.md \\\n  --name \"Customer Churn\" \\\n  --backend auto\n```\n\n### Python workflow\nUse the programmatic API to analyse a dataframe or to build a datasheet directly from a dataset file:\n\n```python\nimport pandas as pd\n\nfrom dfd import Datasheet\n\n# Load your data\ndf = pd.read_csv(\"data/your_data.csv)\n\n# Access automated statistics in-memory\nsheet = Datasheet(data=df)\nfor stat in sheet.analyse():\n    print(stat.column_name, stat.mean_val)\n\n# Generate a template and export a full datasheet\nDatasheet.generate_template(\"docs/datasheet_template.md\")\ncompiled = Datasheet.from_path(\n    \"data/customers.csv\",\n    backend=\"auto\",\n    dataset_name=\"Customer Churn\",\n)\ncompiled.to_markdown(\n    output_path=\"docs/auto_datasheet.md\",\n    template_path=None,\n    version=\"1.0\",\n)\n```\n\n## Development\nAfter setting up the project for development (see Installation), you can use the following commands:\n\n### Install uv with:\n```bash\npip install uv\n```\n### Lock dependencies / sync project\n```bash\nuv lock\nuv sync\nuv sync --extra dev\n```\n\n### Building the package\n```bash\nuv build\n```\n\n### Running Tests\n```bash\n# Run tests using hatch\nuv run pytest\n```\n\n### Code Quality with Ruff\n```bash\n# Check for linting issues\nuv run ruff check .\n\n# Auto-fix linting issues where possible\nuv run ruff check . --fix\n\n# Format code (optional)\nuv run ruff format .\n```\n\n## Links\n- Homepage: https://github.com/anwielts/datasheet-for-dataset\n- Issue tracker: https://github.com/anwielts/datasheet-for-dataset/issues\n- Documentation: https://github.com/anwielts/datasheet-for-dataset/wiki\n\n## Contributing\nContributions are welcome! To contribute:\n1. Fork the repository and create a new branch from main.\n2. Set up the project locally (see Installation \u003e development).\n3. Ensure code quality and tests pass:\n   - Lint/format: `ruff check .` (and optionally `ruff format` if you use Ruff formatting)\n   - Tests: `pytest`\n4. Open a pull request with a clear description of the change and any relevant context.\n\nTips:\n- Keep PRs focused and small where possible.\n- Add or update tests when you introduce behavior changes.\n- Follow the existing code style and project conventions.\n\n## License\nThis project is licensed under the MIT License. See the LICENSE file for details.\n\n## Links\n- Homepage: https://github.com/anwielts/datasheet-for-dataset\n- Issue tracker: https://github.com/anwielts/datasheet-for-dataset/issues\n\n## Contact\n- Maintainers: \n  - anwielts — 52626848+anwielts@users.noreply.github.com\n  - Flippchen — 91947480+flippchen@users.noreply.github.com\n\nFor questions, ideas, or issues, please open a GitHub issue; for sensitive security concerns, consider contacting the maintainers by email.\n\n\n[contributors-shield]: https://img.shields.io/github/contributors/anwielts/datasheet-for-dataset.svg?style=for-the-badge\n[contributors-url]: https://github.com/anwielts/datasheet-for-dataset/graphs/contributors\n[issues-shield]: https://img.shields.io/github/issues/anwielts/datasheet-for-dataset.svg?style=for-the-badge\n[issues-url]: https://github.com/anwielts/datasheet-for-dataset/issues\n[license-shield]: https://img.shields.io/github/license/anwielts/datasheet-for-dataset.svg?style=for-the-badge\n[license-url]: https://github.com/anwielts/datasheet-for-dataset/blob/main/LICENSE\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fanwielts%2Fdatasheet-for-dataset","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fanwielts%2Fdatasheet-for-dataset","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fanwielts%2Fdatasheet-for-dataset/lists"}