菜单
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.
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基于 SOC 职业分类
| name | improving-python-code-quality |
| description | 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. |
| Tool | Purpose | Command |
|---|---|---|
| ruff | Lint + format | ruff check src && ruff format src |
| mypy | Type check | mypy src |
Minimal config in pyproject.toml:
[tool.ruff]
line-length = 88
target-version = "py310"
[tool.ruff.lint]
select = ["E", "W", "F", "I", "B", "C4", "UP"]
For full configuration options, see RUFF_CONFIG.md.
[tool.mypy]
python_version = "3.10"
disallow_untyped_defs = true
warn_return_any = true
For strict settings and overrides, see MYPY_CONFIG.md.
# Basic
def process(items: list[str]) -> dict[str, int]: ...
# Optional
def fetch(url: str, timeout: int | None = None) -> bytes: ...
# Callable
def apply(func: Callable[[int], str], value: int) -> str: ...
# Generic
T = TypeVar("T")
def first(items: Sequence[T]) -> T | None: ...
For protocols and advanced patterns, see TYPE_PATTERNS.md.
# Bad: Mutable default
def process(items: list = []): # Bug!
...
# Good: None default
def process(items: list | None = None):
items = items or []
...
# Bad: Bare except
try:
...
except:
pass
# Good: Specific exception
try:
...
except ValueError as e:
logger.error(e)
# Iteration
for item in items: # Not: for i in range(len(items))
for i, item in enumerate(items): # When index needed
# Dictionary access
value = d.get(key, default) # Not: if key in d: value = d[key]
# Context managers
with open(path) as f: # Not: f = open(path); try: finally: f.close()
# Comprehensions (simple only)
squares = [x**2 for x in numbers]
src/my_library/
├── __init__.py # Public API exports
├── _internal.py # Private (underscore prefix)
├── exceptions.py # Custom exceptions
├── types.py # Type definitions
└── py.typed # Type hint marker
Code Quality:
- [ ] ruff check passes
- [ ] mypy passes (strict mode)
- [ ] Public API has type hints
- [ ] Public API has docstrings
- [ ] No mutable default arguments
- [ ] Specific exception handling
- [ ] py.typed marker present
This skill is based on the Code Quality section of the Guide to Developing High-Quality Python Libraries by Will McGinnis. See these posts for deeper coverage:
Prevents, detects, and remediates files that should never be committed — secrets (.env, API tokens, hardcoded credentials) and dev artifacts (build output, scratch databases, editor/OS files). Covers .gitignore (and why it does not untrack), git rm --cached, auditing tracked files, history scrubbing, and credential rotation. Use when a repo has committed secrets or junk, when setting up a new repo's ignore rules, or when reviewing what a repo actually tracks.
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.
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.
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.
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.
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.