python-packaging

To configure a Python package build system using pyproject.toml, you define build backend dependencies under the [build-system] table and specify project metadata in the [project] table. This modern standard replaces setup.py for declaring dependencies, tooling, and packaging requirements.

The recommended project layouts for distributing a Python package are the src layout and the flat layout. Using a src layout separates importable code from configuration files, preventing accidental imports during testing and ensuring clean package distribution.

You can publish a Python package to PyPI using GitHub Actions by creating an automated workflow that builds wheels and sdists, then uploads them using twine. This CI/CD integration ensures consistent testing and automated distribution upon repository commits or releases.

Choosing between setuptools, hatchling, flit, and poetry for Python packaging depends on your project complexity. Setuptools offers legacy stability, while hatchling, flit, and poetry provide modern PEP 517/518/621 compliant builds with varying dependency resolution and CLI features.

To add a command-line interface to a Python package, you define entry points in pyproject.toml that map to functions using Click or argparse. This registers executable console scripts when the package is installed, allowing users to run your tool from the terminal.

Yes, you can include C extensions and data files when building a Python wheel by configuring the build backend in pyproject.toml. The packaging process supports advanced features like namespace packages and data file inclusion for complex project requirements.