drivendataorg/cookiecutter-data-science
A logical, reasonably standardized, but flexible project structure for doing and sharing data science work.
Setting up a data science project can be complex, with many files and folders to organize. This tool helps data scientists quickly create a standardized, logical structure for new projects, providing a consistent layout for raw data, processed data, notebooks, models, and reports right from the start. It ensures all team members can easily understand and navigate the project's layout.
9,723 stars. Available on PyPI.
Use this if you are a data scientist starting a new project and want to ensure a consistent, well-organized file structure for your data, code, models, and reports.
Not ideal if you are a beginner looking for a simple, one-off script, or if you already have a deeply established and satisfactory project organization system.
Stars
9,723
Forks
2,628
Language
Python
License
MIT
Category
Last pushed
Mar 03, 2026
Commits (30d)
0
Dependencies
3
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/drivendataorg/cookiecutter-data-science"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Compare
Related frameworks
docker-science/cookiecutter-docker-science
Cookiecutter template for data scientists working with Docker containers
csinva/cookiecutter-ml-research
A logical, reasonably standardized, but flexible project structure for conducting ml research 🍪
mihail911/e2eml-cookiecutter
A generic template for building end-to-end machine learning projects
zenml-io/template-starter
A template for a starter project for ZenML
harrisonpim/biscuit-cutter
:cookie: A cookiecutter structure for reproducible data science projects, orchestrated with docker