Agent skill
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.
Install this agent skill to your Project
npx add-skill https://github.com/wshobson/agents/tree/main/plugins/python-development/skills/python-packaging
SKILL.md
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/
Complete pyproject.toml Examples
Pattern 4: Full-Featured pyproject.toml
[build-system]
requires = ["setuptools>=61.0", "wheel"]
build-backend = "setuptools.build_meta"
[project]
name = "my-awesome-package"
version = "1.0.0"
description = "An awesome Python package"
readme = "README.md"
requires-python = ">=3.8"
license = {text = "MIT"}
authors = [
{name = "Your Name", email = "you@example.com"},
]
maintainers = [
{name = "Maintainer Name", email = "maintainer@example.com"},
]
keywords = ["example", "package", "awesome"]
classifiers = [
"Development Status :: 4 - Beta",
"Intended Audience :: Developers",
"License :: OSI Approved :: MIT License",
"Programming Language :: Python :: 3",
"Programming Language :: Python :: 3.8",
"Programming Language :: Python :: 3.9",
"Programming Language :: Python :: 3.10",
"Programming Language :: Python :: 3.11",
"Programming Language :: Python :: 3.12",
]
dependencies = [
"requests>=2.28.0,<3.0.0",
"click>=8.0.0",
"pydantic>=2.0.0",
]
[project.optional-dependencies]
dev = [
"pytest>=7.0.0",
"pytest-cov>=4.0.0",
"black>=23.0.0",
"ruff>=0.1.0",
"mypy>=1.0.0",
]
docs = [
"sphinx>=5.0.0",
"sphinx-rtd-theme>=1.0.0",
]
all = [
"my-awesome-package[dev,docs]",
]
[project.urls]
Homepage = "https://github.com/username/my-awesome-package"
Documentation = "https://my-awesome-package.readthedocs.io"
Repository = "https://github.com/username/my-awesome-package"
"Bug Tracker" = "https://github.com/username/my-awesome-package/issues"
Changelog = "https://github.com/username/my-awesome-package/blob/main/CHANGELOG.md"
[project.scripts]
my-cli = "my_package.cli:main"
awesome-tool = "my_package.tools:run"
[project.entry-points."my_package.plugins"]
plugin1 = "my_package.plugins:plugin1"
[tool.setuptools]
package-dir = {"" = "src"}
zip-safe = false
[tool.setuptools.packages.find]
where = ["src"]
include = ["my_package*"]
exclude = ["tests*"]
[tool.setuptools.package-data]
my_package = ["py.typed", "*.pyi", "data/*.json"]
# Black configuration
[tool.black]
line-length = 100
target-version = ["py38", "py39", "py310", "py311"]
include = '\.pyi?$'
# Ruff configuration
[tool.ruff]
line-length = 100
target-version = "py38"
[tool.ruff.lint]
select = ["E", "F", "I", "N", "W", "UP"]
# MyPy configuration
[tool.mypy]
python_version = "3.8"
warn_return_any = true
warn_unused_configs = true
disallow_untyped_defs = true
# Pytest configuration
[tool.pytest.ini_options]
testpaths = ["tests"]
python_files = ["test_*.py"]
addopts = "-v --cov=my_package --cov-report=term-missing"
# Coverage configuration
[tool.coverage.run]
source = ["src"]
omit = ["*/tests/*"]
[tool.coverage.report]
exclude_lines = [
"pragma: no cover",
"def __repr__",
"raise AssertionError",
"raise NotImplementedError",
]
Pattern 5: Dynamic Versioning
[build-system]
requires = ["setuptools>=61.0", "setuptools-scm>=8.0"]
build-backend = "setuptools.build_meta"
[project]
name = "my-package"
dynamic = ["version"]
description = "Package with dynamic version"
[tool.setuptools.dynamic]
version = {attr = "my_package.__version__"}
# Or use setuptools-scm for git-based versioning
[tool.setuptools_scm]
write_to = "src/my_package/_version.py"
In init.py:
# src/my_package/__init__.py
__version__ = "1.0.0"
# Or with setuptools-scm
from importlib.metadata import version
__version__ = version("my-package")
Command-Line Interface (CLI) Patterns
Pattern 6: CLI with Click
# src/my_package/cli.py
import click
@click.group()
@click.version_option()
def cli():
"""My awesome CLI tool."""
pass
@cli.command()
@click.argument("name")
@click.option("--greeting", default="Hello", help="Greeting to use")
def greet(name: str, greeting: str):
"""Greet someone."""
click.echo(f"{greeting}, {name}!")
@cli.command()
@click.option("--count", default=1, help="Number of times to repeat")
def repeat(count: int):
"""Repeat a message."""
for i in range(count):
click.echo(f"Message {i + 1}")
def main():
"""Entry point for CLI."""
cli()
if __name__ == "__main__":
main()
Register in pyproject.toml:
[project.scripts]
my-tool = "my_package.cli:main"
Usage:
pip install -e .
my-tool greet World
my-tool greet Alice --greeting="Hi"
my-tool repeat --count=3
Pattern 7: CLI with argparse
# src/my_package/cli.py
import argparse
import sys
def main():
"""Main CLI entry point."""
parser = argparse.ArgumentParser(
description="My awesome tool",
prog="my-tool"
)
parser.add_argument(
"--version",
action="version",
version="%(prog)s 1.0.0"
)
subparsers = parser.add_subparsers(dest="command", help="Commands")
# Add subcommand
process_parser = subparsers.add_parser("process", help="Process data")
process_parser.add_argument("input_file", help="Input file path")
process_parser.add_argument(
"--output", "-o",
default="output.txt",
help="Output file path"
)
args = parser.parse_args()
if args.command == "process":
process_data(args.input_file, args.output)
else:
parser.print_help()
sys.exit(1)
def process_data(input_file: str, output_file: str):
"""Process data from input to output."""
print(f"Processing {input_file} -> {output_file}")
if __name__ == "__main__":
main()
Building and Publishing
Pattern 8: Build Package Locally
# Install build tools
pip install build twine
# Build distribution
python -m build
# This creates:
# dist/
# my-package-1.0.0.tar.gz (source distribution)
# my_package-1.0.0-py3-none-any.whl (wheel)
# Check the distribution
twine check dist/*
Pattern 9: Publishing to PyPI
# Install publishing tools
pip install twine
# Test on TestPyPI first
twine upload --repository testpypi dist/*
# Install from TestPyPI to test
pip install --index-url https://test.pypi.org/simple/ my-package
# If all good, publish to PyPI
twine upload dist/*
Using API tokens (recommended):
# Create ~/.pypirc
[distutils]
index-servers =
pypi
testpypi
[pypi]
username = __token__
password = pypi-...your-token...
[testpypi]
username = __token__
password = pypi-...your-test-token...
Pattern 10: Automated Publishing with GitHub Actions
# .github/workflows/publish.yml
name: Publish to PyPI
on:
release:
types: [created]
jobs:
publish:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v3
- name: Set up Python
uses: actions/setup-python@v4
with:
python-version: "3.11"
- name: Install dependencies
run: |
pip install build twine
- name: Build package
run: python -m build
- name: Check package
run: twine check dist/*
- name: Publish to PyPI
env:
TWINE_USERNAME: __token__
TWINE_PASSWORD: ${{ secrets.PYPI_API_TOKEN }}
run: twine upload dist/*
For advanced patterns including data files, namespace packages, C extensions, version management, testing installation, documentation templates, and distribution workflows, see references/advanced-patterns.md
Recommended Agent Skills
Expand your agent's capabilities with these related and highly-rated skills.
protocol-reverse-engineering
Master network protocol reverse engineering including packet analysis, protocol dissection, and custom protocol documentation. Use when analyzing network traffic, understanding proprietary protocols, or debugging network communication.
binary-analysis-patterns
Master binary analysis patterns including disassembly, decompilation, control flow analysis, and code pattern recognition. Use when analyzing executables, understanding compiled code, or performing static analysis on binaries.
anti-reversing-techniques
Understand anti-reversing, obfuscation, and protection techniques encountered during software analysis. Use this skill when analyzing malware evasion techniques, when implementing anti-debugging protections for CTF challenges, when reverse engineering packed binaries, or when building security research tools that need to detect virtualized environments.
memory-forensics
Master memory forensics techniques including memory acquisition, process analysis, and artifact extraction using Volatility and related tools. Use when analyzing memory dumps, investigating incidents, or performing malware analysis from RAM captures.
nx-workspace-patterns
Configure and optimize Nx monorepo workspaces. Use when setting up Nx, configuring project boundaries, optimizing build caching, or implementing affected commands.
auth-implementation-patterns
Master authentication and authorization patterns including JWT, OAuth2, session management, and RBAC to build secure, scalable access control systems. Use when implementing auth systems, securing APIs, or debugging security issues.
Didn't find tool you were looking for?