Cookiecutter Template for Python Data Science

A logical, reasonably standardized, but flexible project structure for doing and sharing data science work.

Quickstart

Requirements

- Python 2.7 or 3.5+

- Cookiecutter Python package(http://cookiecutter.readthedocs.org/en/latest/installation.html) >= 1.4.0: This can be installed with pip by or conda depending on how you manage your Python packages.

# Install cookiecutter and pipenv
pip install cookiecutter
pip install pipenv

# Use cookiecutter to create project from this template
cookiecutter https://github.com/skvorekn/python-cookiecutter
# OR clone the repo and create a project using:
cookiecutter python-cookiecutter/

# Enter project directory
cd <repo_name>

# Follow the instructions in the project README.md for further setup.

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Resulting features

• Testing with pytest
• Formatting with black
• Import sorting with isort
• Static typing with mypy
• Linting with flake8
• Git hooks that run all the above with pre-commit
• Continuous Integration with GitHub Actions

See {{ cookiecutter.repo_name }}/README.md for the resulting folder structure.

Contributing

1. Add changes/features.
2. Add tests associated with new features.
3. Edit documentation as necessary.
4. TODO: code formatting, etc.

Credits

Project based on the cookiecutter data science project template and the python best practices template.