distributions/claude/skills/python-packaging-patterns/SKILL.md
Structure Python projects for distribution with pyproject.toml, src layouts, dependency management, and publishing workflows. Covers packaging tools (hatch, setuptools, flit, poetry), versioning strategies, and editable installs. Triggers on Python project setup, packaging configuration, or dependency management requests.
npx skillsauth add a-organvm/a-i--skills python-packaging-patternsInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
Structure Python projects for reliable distribution and dependency management.
src Layout (Recommended)my-project/
├── pyproject.toml
├── src/
│ └── my_package/
│ ├── __init__.py
│ ├── core.py
│ └── cli.py
├── tests/
│ ├── conftest.py
│ └── test_core.py
└── README.md
Why src layout: Prevents accidental imports from the working directory. Forces installation before testing, catching packaging errors early.
my-project/
├── pyproject.toml
├── my_package/
│ ├── __init__.py
│ └── core.py
└── tests/
Acceptable for internal tools and single-organ repos where distribution is not a concern.
[build-system]
requires = ["hatchling"]
build-backend = "hatchling.build"
[project]
name = "my-package"
version = "0.1.0"
description = "A concise description"
requires-python = ">=3.11"
license = "MIT"
dependencies = [
"httpx>=0.27",
]
[project.optional-dependencies]
dev = [
"pytest>=8.0",
"ruff>=0.5",
"mypy>=1.10",
]
| Backend | When to Use | |---------|-------------| | hatchling | Default choice. Fast, minimal config, good monorepo support | | setuptools | Legacy projects, C extensions, complex build needs | | flit | Pure Python, minimal config, simple projects | | poetry-core | When using Poetry for dependency management |
Organize optional dependencies by use case:
[project.optional-dependencies]
dev = ["pytest>=8.0", "ruff>=0.5", "mypy>=1.10"]
docs = ["sphinx>=7.0", "myst-parser"]
dashboard = ["fastapi>=0.110", "uvicorn"]
metrics = ["prometheus-client"]
Install specific groups: pip install -e ".[dev,dashboard]"
[project.scripts]
my-cli = "my_package.cli:main"
[project.entry-points."my_app.plugins"]
csv = "my_package.plugins.csv:CsvPlugin"
json = "my_package.plugins.json:JsonPlugin"
# In pyproject.toml
[project]
dynamic = ["version"]
[tool.hatch.version]
path = "src/my_package/__init__.py"
# In __init__.py
__version__ = "0.1.0"
For infrastructure packages where semantic versioning adds little value:
__version__ = "2026.03.1" # YYYY.MM.patch
| Context | Strategy | Tool |
|---------|----------|------|
| Library | Loose bounds (>=1.0,<2.0) | pyproject.toml |
| Application | Exact pins | pip-compile / uv lock |
| CI | Lockfile | uv.lock / requirements.txt |
# Using uv (recommended)
uv pip compile pyproject.toml -o requirements.txt
uv pip compile pyproject.toml --extra dev -o requirements-dev.txt
# Using pip-tools
pip-compile pyproject.toml -o requirements.txt
# Standard editable install
pip install -e .
# With dev dependencies
pip install -e ".[dev]"
# In a fresh venv
python -m venv .venv && source .venv/bin/activate
pip install -e ".[dev]"
[tool.ruff]
line-length = 100
target-version = "py311"
[tool.ruff.lint]
select = ["E", "F", "I", "N", "W", "UP"]
[tool.pytest.ini_options]
testpaths = ["tests"]
asyncio_mode = "auto"
pythonpath = ["."]
[tool.mypy]
strict = true
python_version = "3.11"
# Build
python -m build
# Upload (use trusted publishing when possible)
python -m twine upload dist/*
- uses: pypa/gh-action-pypi-publish@release/v1
with:
password: ${{ secrets.PYPI_API_TOKEN }}
For multi-repo packages sharing a namespace:
# Repo A
src/organvm/engine/__init__.py
# Repo B
src/organvm/dashboard/__init__.py
Use implicit namespace packages (no __init__.py at namespace level).
dependencies = [
"tomli>=2.0; python_version < '3.11'",
"typing-extensions>=4.0; python_version < '3.12'",
]
[tool.hatch.build.targets.wheel]
packages = ["src/my_package"]
[tool.hatch.build.targets.wheel.force-include]
"assets" = "my_package/assets"
development
Create algorithmic and generative art using mathematical patterns, noise functions, particle systems, and procedural generation. Covers flow fields, L-systems, fractals, and creative coding foundations. Triggers on generative art, algorithmic art, creative coding, procedural generation, or mathematical visualization requests.
development
Audits web applications and architectures for compliance with GDPR, CCPA, and other privacy regulations, focusing on consent, data minimization, and user rights.
development
Optimize Google Cloud Platform resource allocation and manage cloud credits efficiently. Use when planning GCP deployments, analyzing cloud spend, maximizing value from expiring credits, right-sizing instances, or designing cost-effective architectures. Triggers on GCP cost optimization, credit management, resource allocation planning, or cloud budget concerns.
testing
Designs engaging gameplay loops, economies, and progression systems, balancing challenge and reward for interactive experiences.