python-packaging
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.
How do I install this agent skill?
npx skills add https://github.com/wshobson/agents --skill python-packagingIs this agent skill safe to install?
- Gen Agent Trust Hubpass
The skill is an educational guide for creating and distributing Python packages. It provides standard templates and follows security best practices, such as recommending API tokens for PyPI authentication and using GitHub Secrets for automated publishing.
- Socketpass
No alerts
- Snykpass
Risk: LOW · No issues
- Runlayerpass
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- ZeroLeakspass
Score: 93/100 · 2 sections analyzed
What does this agent skill do?
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.
How can the creator link this skill?
Add the canonical catalog link to the repository README so users can inspect current installs and available audits. The publishing guide covers the complete discovery path.
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