python-packaging
Enables your agent to create distributable packages of Python code. Useful for sharing Python libraries or tools created with others.
What it does
This tool helps organize and prepare your Python code to be shared with others. It creates a 'package' that can be easily installed and used in other projects, or even published for anyone to use.
When to use it
- ✓When you create Python code you want others to use.
- ✓When developing command-line tools.
- ✓To publish your code on PyPI (the Python package store).
Example of what to ask your AI
“How do I create a Python package to share my code?”
Want more? Open the sections below.
How to use
The easiest way: copy the message below and paste it into Claude, ChatGPT, Cursor or any AI. It reads the skill and follows the instructions.
Skill link
Ready-to-paste message
How it works
The tool organizes your code into a standard structure, defines project information in a file called `pyproject.toml`, and uses specific tools to create the distributable package.
Installation
Easiest way: copy the skill link and paste it into Claude, ChatGPT or Cursor asking it to follow the instructions.
In the terminal (Claude Code, Codex, Cursor), in your project folder:
npx skills add wshobson/agents --skill python-packagingOr download just the file:
curl -L https://raw.githubusercontent.com/wshobson/agents/main/plugins/python-development/skills/python-packaging/SKILL.md -o SKILL.mdTechnical content (original SKILL.md)
Original text by the author, straight from GitHub.
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/
├── pyproject.toml
├── README.md
├── LICENSE
├── src/
│ └── my_package/
│ ├── __init__.py
│ └── 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/
├── pyproject.toml
├── README.md
├── LICENSE
├── .gitignore
├── src/
│ └── my_package/
│ ├── __init__.py
│ ├── core.py
│ ├── utils.py
│ └── py.typed # For type hints
├── tests/
│ ├── __init__.py
│ ├── test_core.py
│ └── 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/
├── pyproject.toml
├── README.md
├── my_package/
│ ├── __init__.py
│ └── module.py
└── tests/
└── test_module.py
Simpler but:
- Can import package without installing
- Less professional for libraries
Pattern 3: Multi-Package Project
project/
├── pyproject.toml
├── packages/
│ ├── package-a/
│ │ └── src/
│ │ └── package_a/
│ └── package-b/
│ └── src/
│ └── 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.
FAQ
What is PyPI?
PyPI stands for Python Package Index. It's a large repository where developers publish and find Python packages.
What's the difference between `src/` and a 'flat' layout?
The `src/` layout is recommended because it separates the main code from other project files, avoiding confusion. The 'flat' layout is simpler but can be less organized for larger projects.
What is `pyproject.toml`?
It's a modern configuration file that centralizes your Python project's information, such as name, version, dependencies, and how the package should be built.
Details
Original description by the author
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.
repo: wshobson/agents
Popularity
- GitHub stars
- 41k
- Ranking position
- #4930
- License
- MIT
- Updated
- 10/15/2026
Comments
- …
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