What is the recommended Python package structure?

The 'src' layout is generally recommended as it prevents accidental imports from the source directory and ensures tests run against the installed package.

How does this skill handle pyproject.toml?

It generates standardized pyproject.toml files following PEP 621, including build-system requirements, project metadata, and tool configurations for linting and testing.

Does it support creating CLI tools?

Absolutely. It includes templates for both Click and argparse, along with the necessary entry-point configurations in the packaging metadata.

Can I use this for private package repositories?

Yes, the skill provides patterns for configuring twine and environment variables to publish to private indices like JFrog, AWS CodeArtifact, or TestPyPI.

Is it compatible with modern build backends?

Yes, it supports multiple backends including setuptools, hatchling, flit, and poetry, allowing you to choose the backend that best fits your project needs.

Python Packaging & Distribution

Name: Python Packaging & Distribution
Author: Krosebrook

byKrosebrook

•

Developer Tools

Automates the creation of standardized, distributable Python packages using modern tools like pyproject.toml and PyPI integration.

This skill provides a comprehensive framework for structuring, configuring, and distributing Python libraries and CLI tools. It guides developers through modern packaging standards like PEP 621, helps implement professional 'src' layouts, and streamlines the process of publishing to PyPI or private repositories. Whether you are building a simple utility or a complex multi-package monorepo, it ensures your project metadata, dependencies, and build backends are correctly configured for maximum compatibility and maintainability.

Key Features

01Modern pyproject.toml configuration following PEP 621

02Command-line interface (CLI) boilerplate for Click and argparse

03Dynamic versioning and dependency management optimization

041 GitHub stars

05Professional project scaffolding for source and flat layouts

06Automated build and PyPI distribution workflow patterns

Use Cases

01Standardizing project structures within a monorepo ecosystem

02Building installable CLI tools with defined entry points

03Creating and publishing open-source libraries to PyPI

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add krosebrook/source-of-truth-monorepo python-packaging

For use in Claude.ai and ChatGPT

Download Skill