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python-packaging

说明现代 Python 打包全流程:uv 初始化与依赖管理、pyproject.toml 配置、源码与扁平布局选择、console script 等入口点、语义化版本管理、GitHub Actions 自动化发布,并给出最佳实践与退出标准;不覆盖包测试与性能优化。

athola
athola
热度 62.80
最近更新 2026-08-26 21:19:02
分类:开发依赖:代码执行 / 读写文件应用场景:DevOps / 模板 / 工作流

安装技能

复制下面的话术发给你的 Agent,它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill: npx secure-skills-cli add nm-parseltongue-python-packaging
Metadata
name
python-packaging
description
Python package creation and PyPI distribution via pyproject.toml and entry points
version
1.9.8
triggers
["python","packaging","pyproject.toml","uv","pip","pypi","distribution","publishing a package or setting up build configuration"]
metadata
{"openclaw":{"homepage":"https://github.com/athola/claude-night-market/tree/master/plugins/parseltongue","emoji":"🦞"}}
source
claude-night-market
source_plugin
parseltongue

Night Market Skill — ported from claude-night-market/parseltongue. For the full experience with agents, hooks, and commands, install the Claude Code plugin.

Table of Contents

Python Packaging

Modern Python packaging with pyproject.toml, uv, and best practices for distribution.

Quick Start

# Create new project with uv
uv init my-package
cd my-package

# Add dependencies
uv add requests click

# Build package
uv build

# Publish to PyPI
uv publish

Verification: Run the command with --help flag to verify availability.

When To Use

  • Creating distributable Python libraries
  • Building CLI tools
  • Publishing to PyPI
  • Setting up development environments
  • Managing project dependencies

When NOT To Use

  • Testing packages - use python-testing instead
  • Optimizing package performance - use python-performance
  • Testing packages - use python-testing instead
  • Optimizing package performance - use python-performance

Core Decisions

1. Layout Choice

# Source layout (recommended)
src/my_package/
    __init__.py
    module.py

# Flat layout (simple)
my_package/
    __init__.py
    module.py

Verification: Run the command with --help flag to verify availability.

Source layout benefits:

  • Clear separation of source and tests
  • Prevents accidental imports of uninstalled code
  • Better for packages with complex structure

2. Project Structure

Minimal Project:

**Verification:** Run `pytest -v` to verify tests pass.
my-project/
├── pyproject.toml
├── README.md
├── src/
│   └── my_package/
│       └── __init__.py
└── tests/
    └── test_init.py

Verification: Run pytest -v to verify tests pass.

Complete Project:

**Verification:** Run the command with `--help` flag to verify availability.
my-project/
├── pyproject.toml
├── README.md
├── LICENSE
├── .gitignore
├── src/
│   └── my_package/
│       ├── __init__.py
│       ├── cli.py
│       ├── core.py
│       └── utils.py
├── tests/
│   ├── conftest.py
│   └── test_core.py
└── docs/
    └── index.md

Verification: Run pytest -v to verify tests pass.

Detailed Topics

See modules for detailed information:

Best Practices

  1. Use source layout for anything beyond simple packages
  2. Pin direct dependencies with minimum versions
  3. Use optional dependency groups for dev/docs/test
  4. Include py.typed for type hint support
  5. Add detailed README with usage examples
  6. Use semantic versioning (MAJOR.MINOR.PATCH)
  7. Test on multiple Python versions before publishing

Exit Criteria

  • Modern pyproject.toml configuration
  • Clear dependency specification
  • Proper version management
  • Tests included and passing
  • Build process reproducible
  • Publishing pipeline automated