How does it help with CLI development?

It provides specific implementation patterns for registering entry points and creating user-friendly interfaces using Click or argparse.

Can I use this for private package repositories?

Absolutely. It includes patterns for publishing to private repositories such as JFrog Artifactory and AWS CodeArtifact.

What build backends does this skill support?

The skill provides guidance for various modern backends including setuptools, hatchling, flit, and poetry.

Does it follow the latest Python standards?

Yes, it implements current standards like PEP 517, 518, 621, and 660 for modern, robust packaging workflows.

Does it include CI/CD automation?

Yes, it contains ready-to-use GitHub Actions templates for automated building, checking, and publishing to PyPI.

Python Packaging & Distribution

Name: Python Packaging & Distribution
Author: ai-pilo

byai-pilo

Deployment & DevOps

Streamlines the creation of distributable Python packages using modern standards and best practices for PyPI publishing.

About

The Python Packaging skill provides comprehensive guidance for developers looking to transform Python code into professional, distributable libraries or CLI tools. It simplifies complex tasks such as configuring pyproject.toml files, implementing recommended source layouts, managing dependencies, and automating releases via GitHub Actions. By following modern PEP standards like PEP 517 and 621, this skill ensures your project is compatible, maintainable, and ready for distribution to PyPI or private repositories.

Key Features

Standardized pyproject.toml configuration for multiple build backends
Automated project scaffolding using recommended source layouts
0 GitHub stars
CLI tool implementation patterns using Click and argparse
Advanced patterns for namespace packages and dynamic versioning
CI/CD workflows for automated publishing to PyPI and TestPyPI

Use Cases

Setting up private package distributions for internal enterprise architectures
Creating and publishing standalone command-line utilities with entry points
Converting local scripts into a professional library for public distribution

About

Key Features

Standardized pyproject.toml configuration for multiple build backends
Automated project scaffolding using recommended source layouts
0 GitHub stars
CLI tool implementation patterns using Click and argparse
Advanced patterns for namespace packages and dynamic versioning
CI/CD workflows for automated publishing to PyPI and TestPyPI

Use Cases

Setting up private package distributions for internal enterprise architectures
Creating and publishing standalone command-line utilities with entry points
Converting local scripts into a professional library for public distribution