🎯

python-packaging

🎯Skill

Helps you turn your Python code into a package that others can install, and publish it to PyPI, the public site for sharing Python packages. It covers folder layout, the settings file, and building the files you upload.

wshobson/agents9,915 Installs27,673Last Updated Jan 19, 2026

Installation

$npx skills add wshobson/agents --skill python-packaging

Run it in a terminal; it asks which AI coding tools to install it for (Claude Code, Codex, Cursor and more).

Uses skills.sh Β· Node.js 22.20+

After installing

Ask for related work and the agent uses it on its own, or call it yourself.

Run it (Claude Code)/python-packaging
Install by hand

Copy the whole skill folder from GitHub to the place below. Copying only SKILL.md can leave out files the skill uses.

Open the skill folder β†’
  • This project .claude/skills/python-packaging/
  • All projects ~/.claude/skills/python-packaging/

These paths are for Claude Code. For other tools, the command above puts it in the right place.

What this skill does

Overview

This skill guides an AI coding tool in packaging Python code so it can be installed with one command. It centers on pyproject.toml, the single settings file modern Python projects use to describe a package. It also explains how to publish the result to PyPI, TestPyPI or a private company store.

Key Features

  • Set up a clean project folder, with the recommended src/ layout explained.
  • Write a minimal pyproject.toml with name, version and needed libraries.
  • Choose a build tool such as setuptools, hatchling, flit or poetry.
  • Turn your scripts into command-line tools people can run after installing.
  • Build install files and try them on TestPyPI before the real release.

Who is this for?

This is for Python developers who want to share a library or tool with others. It is also handy for teams that publish internal packages to a private repository.

Summarized by AI from this skill's SKILL.md. Suggest a better one

Create distributable Python packages with proper project structure, setup.py/pyproject.toml, and publishing to PyPI. Use when packaging Python libraries, creating CLI tools, or distributing Python code.

Python Packaging

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

When to Use This Skill

  • 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

Core Concepts

1. Package Structure

  • Source layout: src/package_name/ (recommended)
  • Flat layout: package_name/ (simpler but less flexible)
  • Package metadata: pyproject.toml, setup.py, or setup.cfg
  • Distribution formats: wheel (.whl) and source distribution (.tar.gz)

2. Modern Packaging Standards

  • PEP 517/518: Build system requirements
  • PEP 621: Metadata in pyproject.toml
  • PEP 660: Editable installs
  • pyproject.toml: Single source of configuration

3. Build Backends

  • setuptools: Traditional, widely used
  • hatchling: Modern, opinionated
  • flit: Lightweight, for pure Python
  • poetry: Dependency management + packaging

4. Distribution

  • PyPI: Python Package Index (public)
  • TestPyPI: Testing before production
  • Private repositories: JFrog, AWS CodeArtifact, etc.

Quick Start

Minimal Package Structure

my-package/
β”œβ”€β”€ pyproject.toml
β”œβ”€β”€ README.md
β”œβ”€β”€ LICENSE
β”œβ”€β”€ src/
β”‚   └── my_package/
β”‚       β”œβ”€β”€ __init__.py
β”‚       └── module.py
└── tests/
    └── test_module.py

Minimal pyproject.toml

[build-system]
requires = ["setuptools>=61.0"]
build-backend = "setuptools.build_meta"

[project]
name = "my-package"
version = "0.1.0"
description = "A short description"
authors = [{name = "Your Name", email = "you@example.com"}]
readme = "README.md"
requires-python = ">=3.8"
dependencies = [
    "requests>=2.28.0",
]

[project.optional-dependencies]
dev = [
    "pytest>=7.0",
    "black>=22.0",
]

Package Structure Patterns

Pattern 1: Source Layout (Recommended)

my-package/
β”œβ”€β”€ pyproject.toml
β”œβ”€β”€ README.md
β”œβ”€β”€ LICENSE
β”œβ”€β”€ .gitignore
β”œβ”€β”€ src/
β”‚   └── my_package/
β”‚       β”œβ”€β”€ __init__.py
β”‚       β”œβ”€β”€ core.py
β”‚       β”œβ”€β”€ utils.py
β”‚       └── py.typed          # For type hints
β”œβ”€β”€ tests/
β”‚   β”œβ”€β”€ __init__.py
β”‚   β”œβ”€β”€ test_core.py
β”‚   └── test_utils.py
└── docs/
    └── index.md

Advantages:

  • Prevents accidentally importing from source
  • Cleaner test imports
  • Better isolation

pyproject.toml for source layout:

[tool.setuptools.packages.find]
where = ["src"]

Pattern 2: Flat Layout

my-package/
β”œβ”€β”€ pyproject.toml
β”œβ”€β”€ README.md
β”œβ”€β”€ my_package/
β”‚   β”œβ”€β”€ __init__.py
β”‚   └── module.py
└── tests/
    └── test_module.py

Simpler but:

  • Can import package without installing
  • Less professional for libraries

Pattern 3: Multi-Package Project

project/
β”œβ”€β”€ pyproject.toml
β”œβ”€β”€ packages/
β”‚   β”œβ”€β”€ package-a/
β”‚   β”‚   └── src/
β”‚   β”‚       └── package_a/
β”‚   └── package-b/
β”‚       └── src/
β”‚           └── package_b/
└── tests/

Detailed patterns and worked examples

Detailed pattern documentation lives in references/details.md. Read that file when the navigation tier above is insufficient.

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