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Tips

Keep your dependencies up to date with Dependabot

The template ships with a pre-configured Dependabot setup in .github/dependabot.yml. Dependabot automatically opens pull requests to update outdated dependencies on a weekly schedule — it monitors both GitHub Actions versions and uv package dependencies.

To handle these PRs automatically, the template also includes a dependabot-reviewer workflow (.github/workflows/dependabot-reviewer.yml) that:

  • Auto-approves and merges patch and minor updates, as well as major updates of development-only dependencies
  • Flags major updates of production dependencies with a requires-manual-qa label for manual review

This means routine maintenance (e.g. bumping actions/checkout from v3 to v4) happens without any manual effort.

Required GitHub settings

Two settings must be enabled in your repository before the auto-merge workflow can function:

  1. Settings → General → Pull Requests → Allow auto-merge
    Enables the gh pr merge --auto command used by the workflow.

  2. Settings → Actions → General → Workflow permissions → Read and write permissions
    Allows the GITHUB_TOKEN to approve and merge PRs, and to update workflow files when Dependabot bumps GitHub Actions versions.

Keep your project up to date with cruft

If this template is updated in the future, you can pull in the latest changes to your already-generated project using cruft:

uvx cruft update

cruft tracks which version of the template your project was generated from and applies only the diff — similar to git merge for template updates. Run it periodically to stay current with improvements to the boilerplate.

Tip

If you created your project with cookiecutter instead of cruft, you can still link it retroactively: 

uvx cruft link https://github.com/markusritschel/cookiecutter-pyproject

A note on version controlling Jupyter notebooks

It is very ugly to keep Jupyter Notebooks under version control as they are in principle a very large JSON file, containing lots of metadata, output of your cells, etc. This circumstance makes it also quite hard to collaborate on them.

However, there's help: Jupytext syncs your Jupyter notebooks with another file for which you can choose a variety of formats (e.g. Markdown, R Markdown, normal Python, etc.). These "paired" files, which can either reside alongside your Jupyter notebooks or in a separate directory, can then be easily version-controlled. Jupytext can either be used from the command line (jupytext --sync notebooks/*ipynb) or as a Jupyter plugin.

For more information, visit https://jupytext.readthedocs.io/.