cookiecutter-python
Creating a new Python project can be a daunting task, especially when it comes to setting up all the necessary development and deployment tools. This is where my Cookiecutter Python template comes into play. This template simplifies the process of setting up a new Python project, allowing developers to focus on writing code rather than wrestling with configuration.
What is Cookiecutter?
Cookiecutter is a command-line utility that creates projects from project templates. With it, you can generate a new project structure with all the necessary files and directories based on a predefined template.
Key Features
- hatch for managing the project’s virtual environment and development tools
- ruff for code formatting and linting
- mypy for type checking
- hatch-pip-compile for dependency management + lockfiles
- pre-commit for managing git hooks
- GitHub Actions for CI/CD
- MkDocs and mkdocs-material for documentation
- GitHub Pages for hosting documentation
- semantic-release and gitmoji for automated releases
- Publishes to PyPI and Docker Hub
Getting Started
To use the template, you first need to install Cookiecutter. It’s recommended to use pipx
for the installation, but you can also use pip.
pipx install cookiecutter
Once Cookiecutter is installed, you can generate a new Python project using the following command:
cookiecutter gh:juftin/cookiecutter-python
After generating the project, navigate to the root directory of your new project, create a Git repository, and install pre-commit:
git init
pre-commit install
git add .
pre-commit run --all-files
git add .
git commit
Remember to commit your lockfiles, which are created at requirements.txt and in
the requirements directory. They will be created automatically when you run a
hatch command in the respective environment for the first time:
hatch run cov
hatch run lint:all
hatch run docs:serve
git add requirements.txt requirements/
git commit -m "🔐 add lockfiles"
Managing Secrets
This template uses GitHub Actions to deploy releases, documentation, and to publish artifacts
to PyPI and Docker Hub. You will need to create secrets in your GitHub repository to enable
these features. A .env file is provided in the project root for local development. To sync
your secrets to GitHub, run the following command with the GitHub CLI:
gh secret set --env-file .env
Developing Your Project
This project generates its own documentation for how to use the project’s tools. To view the documentation locally, run:
hatch run docs:serve
Once the server is running, you can view the documentation at localhost:8080/contributing or
see a preview at juftin.com/cookiecutter-python/contributing.
My Cookiecutter Python template is an excellent tool for Python developers. It simplifies the setup process, allowing developers to jump straight into coding. Whether you’re a seasoned developer or a beginner, this template is worth checking out.