Python Packaging

SkillDev tools

python-packaging is a skill that guides an AI agent through creating, structuring, and distributing Python packages. It covers modern packaging tools, pyproject.toml configuration, and publishing to PyPI. Use it when you want your agent to handle packaging work without leaving the conversation.

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Then ask your AI: use the Python Packaging skill

Details

Instructions available. Your AI can read the instructions. Execution depends on the setup they require.

Have a Python project or an idea for a package that needs packaging.

Python PackagingStart free

What your AI can do with it

  • Create a new Python package with a standard directory layout
  • Write and edit pyproject.toml for modern packaging tools
  • Structure modules, packages, and entry points correctly
  • Prepare a package for distribution
  • Publish a package to PyPI

Getting started

  1. Have a Python project or an idea for a package that needs packaging.
  2. Add the python-packaging skill to your agent's available skills.
  3. Ask the agent to create or update the package structure and pyproject.toml.
  4. Review the generated files and run the build or publish steps the agent suggests.

What this skill tells your AI

The instructions your AI receives, as published by sickn33/agentic-awesome-skills in skills/python-packaging/SKILL.md and read by ahel’s review.

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.

Signals

GitHub stars
47k
Forks
7k
Last commit
Sep 2026

ahel review

  • K1binfo
    installs-packages (in references/advanced-patterns.md)
  • K1binfo
    installs-packages (in references/details.md)

Automated review, not a security audit. Ruleset v1+k2.

Questions

What kind of tool is python-packaging?
It is a skill for an AI agent. It provides guidance and actions for creating, structuring, and distributing Python packages using modern tools and pyproject.toml.
Does it help publish to PyPI?
Yes. The skill covers publishing to PyPI as part of distributing Python packages.
Does it use pyproject.toml?
Yes. pyproject.toml is part of the modern packaging approach the skill supports.
Can it create a package from scratch?
Yes. It can create a new Python package with a standard structure and the necessary configuration files.
Does it replace manual packaging work?
It guides and performs packaging tasks through the agent, but you still review and run the final build or publish steps.
Advanced
Item type
skill
Key
python-packaging
Source
github.com/sickn33/agentic-awesome-skills