{"id":13856719,"url":"https://github.com/iterative/cookiecutter-data-science","last_synced_at":"2025-07-13T19:32:28.651Z","repository":{"id":47488970,"uuid":"169507650","full_name":"iterative/cookiecutter-data-science","owner":"iterative","description":"A logical, reasonably standardized, but flexible project structure for doing and sharing data science work.","archived":false,"fork":true,"pushed_at":"2023-09-01T11:24:37.000Z","size":635,"stargazers_count":26,"open_issues_count":1,"forks_count":8,"subscribers_count":5,"default_branch":"master","last_synced_at":"2024-08-06T03:02:15.769Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":"http://drivendata.github.io/cookiecutter-data-science/","language":"Python","has_issues":false,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":"drivendataorg/cookiecutter-data-science","license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/iterative.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}},"created_at":"2019-02-07T02:17:49.000Z","updated_at":"2024-05-22T17:30:49.000Z","dependencies_parsed_at":null,"dependency_job_id":null,"html_url":"https://github.com/iterative/cookiecutter-data-science","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/iterative%2Fcookiecutter-data-science","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/iterative%2Fcookiecutter-data-science/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/iterative%2Fcookiecutter-data-science/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/iterative%2Fcookiecutter-data-science/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/iterative","download_url":"https://codeload.github.com/iterative/cookiecutter-data-science/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":225912234,"owners_count":17544129,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","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":[],"created_at":"2024-08-05T03:01:10.513Z","updated_at":"2024-11-22T14:30:38.070Z","avatar_url":"https://github.com/iterative.png","language":"Python","funding_links":[],"categories":["Python"],"sub_categories":[],"readme":"# Cookiecutter Data Science\n\n_A logical, reasonably standardized, but flexible project structure for doing and sharing data science work._\n\n\n#### [Project homepage](http://drivendata.github.io/cookiecutter-data-science/)\n\n\n### Requirements to use the cookiecutter template:\n-----------\n - Python 2.7 or 3.5+\n - [Cookiecutter Python package](http://cookiecutter.readthedocs.org/en/latest/installation.html) \u003e= 1.4.0: This can be installed with pip by or conda depending on how you manage your Python packages:\n\n``` bash\n$ pip install cookiecutter\n```\n\nor\n\n``` bash\n$ conda config --add channels conda-forge\n$ conda install cookiecutter\n```\n\n\n### To start a new project, run:\n------------\n\n    cookiecutter -c v1 https://github.com/drivendata/cookiecutter-data-science\n\n\n[![asciicast](https://asciinema.org/a/244658.svg)](https://asciinema.org/a/244658)\n\n### New version of Cookiecutter Data Science\n------------\nCookiecutter data science is moving to v2 soon, which will entail using\nthe command `ccds ...` rather than `cookiecutter ...`. The cookiecutter command\nwill continue to work, and this version of the template will still be available.\nTo use the legacy template, you will need to explicitly use `-c v1` to select it.\nPlease update any scripts/automation you have to append the `-c v1` option (as above),\nwhich is available now.\n\n\n### The resulting directory structure\n------------\n\nThe directory structure of your new project looks like this: \n\n```\n├── LICENSE\n├── Makefile           \u003c- Makefile with commands like `make data` or `make train`\n├── README.md          \u003c- The top-level README for developers using this project.\n├── data\n│   ├── external       \u003c- Data from third party sources.\n│   ├── interim        \u003c- Intermediate data that has been transformed.\n│   ├── processed      \u003c- The final, canonical data sets for modeling.\n│   └── raw            \u003c- The original, immutable data dump.\n├── data.dvc           \u003c- A data version control file (optional); see dvc.org for details\n│\n├── docs               \u003c- A default Sphinx project; see sphinx-doc.org for details\n│\n├── models             \u003c- Trained and serialized models, model predictions, or model summaries\n│\n├── notebooks          \u003c- Jupyter notebooks. Naming convention is a number (for ordering),\n│                         the creator's initials, and a short `-` delimited description, e.g.\n│                         `1.0-jqp-initial-data-exploration`.\n│\n├── references         \u003c- Data dictionaries, manuals, and all other explanatory materials.\n│\n├── reports            \u003c- Generated analysis as HTML, PDF, LaTeX, etc.\n│   └── figures        \u003c- Generated graphics and figures to be used in reporting\n│\n├── requirements.txt   \u003c- The requirements file for reproducing the analysis environment, e.g.\n│                         generated with `pip freeze \u003e requirements.txt`\n│\n├── setup.py           \u003c- makes project pip installable (pip install -e .) so src can be imported\n├── src                \u003c- Source code for use in this project.\n│   ├── __init__.py    \u003c- Makes src a Python module\n│   │\n│   ├── data           \u003c- Scripts to download or generate data\n│   │   └── make_dataset.py\n│   │\n│   ├── features       \u003c- Scripts to turn raw data into features for modeling\n│   │   └── build_features.py\n│   │\n│   ├── models         \u003c- Scripts to train models and then use trained models to make\n│   │   │                 predictions\n│   │   ├── predict_model.py\n│   │   └── train_model.py\n│   │\n│   └── visualization  \u003c- Scripts to create exploratory and results oriented visualizations\n│       └── visualize.py\n│\n└── tox.ini            \u003c- tox file with settings for running tox; see tox.readthedocs.io\n```\n\n## Contributing\n\nWe welcome contributions! [See the docs for guidelines](https://drivendata.github.io/cookiecutter-data-science/#contributing).\n\n### Installing development requirements\n------------\n\n    pip install -r requirements.txt\n\n### Running the tests\n------------\n\n    py.test tests\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fiterative%2Fcookiecutter-data-science","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fiterative%2Fcookiecutter-data-science","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fiterative%2Fcookiecutter-data-science/lists"}