multiAI Summary Pending

python-packaging

Comprehensive guide to creating, structuring, and distributing Python packages using modern packaging tools, pyproject.toml, and publishing to PyPI.

28,273 stars

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/python-packaging/SKILL.md --create-dirs "https://raw.githubusercontent.com/sickn33/antigravity-awesome-skills/main/plugins/antigravity-awesome-skills-claude/skills/python-packaging/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/python-packaging/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How python-packaging Compares

Feature / Agentpython-packagingStandard Approach
Platform SupportmultiLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Comprehensive guide to creating, structuring, and distributing Python packages using modern packaging tools, pyproject.toml, and publishing to PyPI.

Which AI agents support this skill?

This skill is compatible with multi.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# Python Packaging

Comprehensive guide to creating, structuring, and distributing Python packages using modern packaging tools, pyproject.toml, and publishing to PyPI.

## Use this skill when

- Creating Python libraries for distribution
- Building command-line tools with entry points
- Publishing packages to PyPI or private repositories
- Setting up Python project structure
- Creating installable packages with dependencies
- Building wheels and source distributions
- Versioning and releasing Python packages
- Creating namespace packages
- Implementing package metadata and classifiers

## Do not use this skill when

- The task is unrelated to python packaging
- You need a different domain or tool outside this scope

## Instructions

- Clarify goals, constraints, and required inputs.
- Apply relevant best practices and validate outcomes.
- Provide actionable steps and verification.
- If detailed examples are required, open `resources/implementation-playbook.md`.

## Resources

- `resources/implementation-playbook.md` for detailed patterns and examples.