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python-packaging

Automate Python packaging from project layout to PyPI publishing.

Updated Feb 26, 2026
Search Tags:#python#build#packaging#pypi#distribution#package#pyproject
One-click install
npx skills add https://github.com/AndyAnh174/wellness --skill python-packaging-andyanh174
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: python-packaging
Source: https://github.com/AndyAnh174/wellness/tree/main/.agent/skills/python-packaging
Command: npx skills add https://github.com/AndyAnh174/wellness --skill python-packaging-andyanh174

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Packaging Python projects can be error-prone and inconsistently structured, making it hard to reliably build, distribute, and install libraries or CLI tools.

Core Features & Use Cases

  • Modern packaging standards adoption (PEP 517/518, PEP 621, PEP 660) and build backends (setuptools, hatchling, flit, poetry).
  • Clear project layout guidance (pyproject.toml, src layout) and metadata configuration for robust distributions.
  • Distribution to PyPI and TestPyPI with reproducible builds and versioning strategies.
  • Use cases include packaging libraries, creating CLI tools with entry points, or distributing code across teams.

Quick Start

Create a minimal package structure with pyproject.toml and a src/ layout, then configure your build system and publish to PyPI.

Frequently Asked Questions about python-packaging

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I package a Python project for PyPI using pyproject.toml?▼

Python packaging automates building and distributing libraries or CLI tools to PyPI. It guides you through configuring pyproject.toml, setting up a src layout, and publishing reproducible builds according to modern PEP 517/518/621 standards.

What is the best way to structure a Python package for distribution?▼

The best way to structure a Python package for distribution is using a src layout alongside a pyproject.toml file. This approach separates source code from configuration, ensuring clean builds and reliable metadata parsing across different build backends.

Does Python packaging support both setuptools and hatchling build backends?▼

Yes, Python packaging supports multiple build backends including setuptools, hatchling, flit, and poetry. You can configure your chosen backend in pyproject.toml to handle builds and metadata according to PEP 517/518 standards.

How do I create CLI tools with entry points in Python packaging?▼

To create CLI tools with entry points in Python packaging, define the console scripts in your pyproject.toml metadata. This configuration maps your command-line interface functions to executable scripts during installation, distributing them across teams.

Can I publish a Python package to TestPyPI before distributing to PyPI?▼

Yes, you can publish a Python package to TestPyPI before PyPI to validate your distribution workflow. This allows you to test installation and verify metadata without affecting the official PyPI registry, ensuring reproducible builds and versioning.

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