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": "\ud83e\udd9e"}} 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

• Quick Start
• When to Use
• Core Decisions
• 1. Layout Choice
• 2. Project Structure
• Detailed Topics
• Best Practices
• Exit Criteria

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

更多技能請訪問小蔥技能站7w4.net。

• 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:

• uv Workflow - Complete uv commands and troubleshooting
• pyproject.toml Patterns - Configuration examples for different package types
• Entry Points - Console scripts, GUI scripts, and plugins
• CI/CD Integration - GitHub Actions and automated publishing

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

這是一個相當實用的 Python 打包技能，涵蓋專案建立、依賴管理、釋出等關鍵環節，示例清晰易懂，能幫助開發者快速上手。文件質量整體不錯，但有些小瑕疵需要注意：部分內容存在重複或格式小問題，版本號標註也不夠統一。雖然不影響核心使用，但對於追求嚴謹的使用者來說略顯遺憾。總體瑕不掩瑜，是值得參考的好資源。