designing-python-apis
Designs intuitive Python library APIs following principles of simplicity, consistency, and discoverability. Handles API evolution, deprecation, breaking changes, and error handling. Use when designing new library APIs, reviewing existing APIs for improvements, or managing API versioning and deprecations.
building-python-clis
Builds command-line interfaces for Python libraries using Click or Typer. Includes command groups, argument handling, progress bars, shell completion, and CLI testing with CliRunner. Use when adding CLI functionality to a library or building standalone command-line tools.
improving-python-code-quality
Improves Python library code quality through ruff linting, mypy type checking, Pythonic idioms, and refactoring. Use when reviewing code for quality issues, adding type hints, configuring static analysis tools, or refactoring Python library code.
building-python-communities
Builds and manages open source Python library communities including CONTRIBUTING.md, CODE_OF_CONDUCT.md, issue/PR templates, contributor recognition, and GitHub automation. Use when setting up community infrastructure, improving contributor experience, or managing project governance.
documenting-python-libraries
Creates comprehensive Python library documentation including Google-style docstrings, Sphinx setup, API references, tutorials, and ReadTheDocs configuration. Use when writing docstrings, setting up Sphinx documentation, or creating user guides for Python libraries.
reviewing-python-libraries
Comprehensively reviews Python libraries for quality across project structure, packaging, code quality, testing, security, documentation, API design, and CI/CD. Provides actionable feedback and improvement recommendations. Use when evaluating library health, preparing for major releases, or auditing dependencies.
packaging-python-libraries
Packages and distributes Python libraries using modern pyproject.toml, build backends (setuptools, hatchling), PyPI publishing with trusted publishing, and wheel building. Use when packaging libraries for distribution, publishing to PyPI, or troubleshooting packaging issues.
optimizing-python-performance
Optimizes Python library performance through profiling (cProfile, PyInstrument), memory analysis (memray, tracemalloc), benchmarking (pytest-benchmark), and optimization strategies. Use when analyzing performance bottlenecks, finding memory leaks, or setting up performance regression testing.
setting-up-python-libraries
Sets up professional Python library projects with modern tooling (pyproject.toml, uv, ruff, pytest, pre-commit, GitHub Actions). Use when creating new Python libraries, modernizing existing projects to pyproject.toml, configuring linting/testing/CI, or setting up Makefiles and pre-commit hooks.
managing-python-releases
Manages Python library releases including semantic versioning, changelog maintenance (Keep a Changelog format), release automation with GitHub Actions, and deprecation workflows. Use when planning releases, writing changelogs, automating release pipelines, or communicating breaking changes.
auditing-python-security
Audits Python libraries for security vulnerabilities using Bandit, pip-audit, Semgrep, and detect-secrets. Identifies SQL injection, command injection, hardcoded credentials, weak cryptography, and insecure deserialization. Use when reviewing library security, setting up security scanning in CI, or implementing secure coding patterns.
testing-python-libraries
Designs and implements pytest test suites for Python libraries with fixtures, parametrization, mocking, Hypothesis property-based testing, and CI configuration. Use when creating tests, improving coverage, setting up testing infrastructure, or implementing property-based testing.