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Python Project Template

Tests Code Style

Python packaging can be confusing because there are a lot of different opinions and loose standards.

This is a template for a Python project following all the current best practices. Since there is not just one way to do those things in Python this is also kind of opinionated but I tried to reduce this to a minimum.

This template is configured for Python versions 3.6 and above and should work on Linux, macOS and Windows.

Getting Started

To use this template for your project, do the following:

  1. Update the [tool.poetry] section of the pyproject.toml with your and you package’s information.
  2. If you want to use another license, change COPYING file and license section in pyproject.toml. You may consider changing the filename of COPYING if you do not want to use GPL according to the licence’s guidelines.
  3. Rename src/sample_package to src/$YOURPROJECT.
  4. Update docs/index.rst to match your package.
  5. Enable GitHub Pages to make your documentation available.

Poetry Quickstart

Poetry is used to build the package. After installing Poetry, you can install this package with:

poetry install

Poetry handles all the dependencies and virtual environments for you. To run your code from and in your virtual environment prepend poetry run to your command. This applies to all the non-Make commands in this README.

By default, Poetry creates the virtual environments in it’s own directory. Since a lot of other tools expect your virtual environments in the project directory itself as .venv. To do that, add the following lines in poetry.toml:

[virtualenvs]
in-project = true
path = ".venv"

You can add dependencies with poetry [-D] add $DEPENDENCY_NAME, where -D specifies development dependencies, e.g. libraries you need to build and develop the code that don’t need to be shipped for end users. I advise you to take a look at the Poetry documentation

Makefile

This repository also provides a Makefile for convenience. It contains the following rules:

  • install (default): Install the package with poetry
  • test: This is probably the most useful rule for developing. It checks the linter and runs the tests with the current Python version. This will also run in the CI.
  • linters: Run the linters. You can disable certain errors in pyproject.toml and the Makefile itself. This will also run in the CI.
  • codeformat: Format all source and test files with Black.
  • distribution: Build the source distribution and wheel packages.
  • docs: Build the documentation with Sphinx
  • docs-spelling: Run a spell checker on the documentation. You can add your own dictionary in docs/spelling_wordlist.txt.
  • clean: Removes all the local build files. Note that this does not include anything in the virtual environment to prevent conflicts with your Poetry workflow.

I recommend using the make rules instead of running all the commands manually since it's easy to forget something.

To adjust the Makefile to your project you have to change the MODULE_NAME. If your source folder names differ from this template, this has to be changed in SOURCE_FOLERS accordingly.

GitHub Actions Workflows

CI should work out of the box with the provided configurations in .github/workflow. The following workflows are provided

Code Formatting

The linter.yml workflow checks the source code with Black, flake8, pylint and pydocstyle.

To format your contributions so that they will pass, run

make codeformat

Tests

The test.yml workflow will run the tests on the latest Ubuntu, macOS, and Windows with Python 3.6, 3.7, and 3.8.

Continuous Deployment

When you push commits tagged with tags that match "v*.*.*", the source distribution and the wheel package get uploaded to the releases page on GitHub. This is configured in the release.yml workflow.