Python代码质量之从规范到自动化检查全过程

# pyproject.toml
[tool.black]
line-length = 88
target-version = ['py39', 'py310', 'py311']
include = '\.pyi?$'
exclude = '''
/(
\.git
| \.venv
| build
| dist
)/
'''
[tool.isort]
profile = "black"
line_length = 88
known_first_party = ["src"]
skip = [".venv", "build", "dist"]
[tool.mypy]
python_version = "3.9"
warn_return_any = true
warn_unused_configs = true
disallow_untyped_defs = false
ignore_missing_imports = true
[tool.ruff]
line-length = 88
target-version = "py39"
[tool.ruff.lint]
select = ["E", "F", "W", "I", "N", "UP", "B", "C4"]
ignore = ["E501"]  # 行长度由black处理
[tool.coverage.run]
source = ["src"]
omit = ["*/tests/*", "*/test_*.py"]
[tool.coverage.report]
exclude_lines = [
"pragma: no cover",
"if __name__ == .__main__.:",
"raise AssertionError()",
]

import pytest
from typing import List, Optional
class DataValidator:
"""数据验证器"""
@staticmethod
def validate_email(email: str) -> bool:
"""验证邮箱格式"""
import re
pattern = r'^[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}$'
return bool(re.match(pattern, email))
@staticmethod
def validate_positive(value: float) -> bool:
"""验证正数"""
return value > 0
@staticmethod
def validate_in_range(value: float, min_val: float, max_val: float) -> bool:
"""验证范围"""
return min_val <= value <= max_val
class TestDataValidator:
"""数据验证器测试"""
@pytest.mark.parametrize("email,expected", [
("[email protected]", True),
("[email protected]", True),
("invalid-email", False),
("@domain.com", False),
("user@", False),
("", False),
])
def test_validate_email(self, email, expected):
assert DataValidator.validate_email(email) == expected
@pytest.mark.parametrize("value,expected", [
(1.0, True),
(0.0, False),
(-1.0, False),
(100.5, True),
])
def test_validate_positive(self, value, expected):
assert DataValidator.validate_positive(value) == expected
def test_validate_in_range(self):
assert DataValidator.validate_in_range(5, 0, 10) == True
assert DataValidator.validate_in_range(0, 0, 10) == True
assert DataValidator.validate_in_range(10, 0, 10) == True
assert DataValidator.validate_in_range(-1, 0, 10) == False
assert DataValidator.validate_in_range(11, 0, 10) == False
class TestEdgeCases:
"""边界情况测试"""
def test_empty_string(self):
assert DataValidator.validate_email("") == False
def test_unicode_email(self):
assert DataValidator.validate_email("用户@例子.广告") == False
def test_very_long_email(self):
long_email = "a" * 100 + "@example.com"
# 应该能处理但可能返回False（取决于具体实现）
result = DataValidator.validate_email(long_email)
assert isinstance(result, bool)

from unittest.mock import Mock, patch, MagicMock
import pytest
class APIClient:
"""API客户端"""
def __init__(self, base_url: str):
self.base_url = base_url
self.session = None
def fetch(self, endpoint: str) -> dict:
"""获取数据"""
import requests
response = requests.get(f"{self.base_url}/{endpoint}")
return response.json()
class TestAPIClient:
"""API客户端测试"""
@patch('requests.get')
def test_fetch_success(self, mock_get):
"""测试成功获取"""
mock_response = Mock()
mock_response.json.return_value = {"status": "success", "data": [1, 2, 3]}
mock_get.return_value = mock_response
client = APIClient("https://api.example.com")
result = client.fetch("users")
assert result["status"] == "success"
assert result["data"] == [1, 2, 3]
mock_get.assert_called_once_with("https://api.example.com/users")
@patch('requests.get')
def test_fetch_error(self, mock_get):
"""测试获取失败"""
mock_get.side_effect = ConnectionError("Network error")
client = APIClient("https://api.example.com")
with pytest.raises(ConnectionError):
client.fetch("users")
def test_with_fixture(self, mock_get):
"""使用fixture的测试"""
# fixture在conftest.py中定义
result = self.client.fetch("users")
assert "status" in result

import pytest
import time
class TestPerformance:
"""性能测试"""
def test_sort_performance(self):
"""测试排序性能"""
import random
# 生成大量数据
data = [random.randint(0, 10000) for _ in range(10000)]
start = time.perf_counter()
sorted_data = sorted(data)
elapsed = time.perf_counter() - start
# 应该在1秒内完成
assert elapsed < 1.0, f"排序耗时 {elapsed:.2f}s，超过1秒"
# 验证排序正确性
assert sorted_data == sorted(data)
@pytest.mark.benchmark
def test_list_comprehension_performance(self, benchmark):
"""基准测试列表推导式"""
result = benchmark(lambda: [i**2 for i in range(10000)])
assert len(result) == 10000
# conftest.py
def pytest_configure(config):
config.addinivalue_line("markers", "benchmark: mark test as a benchmark")
@pytest.fixture
def sample_data():
"""示例数据fixture"""
return [i for i in range(100)]

# .pre-commit-config.yaml
repos:
- repo: https://github.com/pre-commit/pre-commit-hooks
rev: v4.4.0
hooks:
- id: trailing-whitespace
- id: end-of-file-fixer
- id: check-yaml
- id: check-added-large-files
- id: check-merge-conflict
- repo: https://github.com/psf/black
rev: 23.3.0
hooks:
- id: black
language_version: python3.10
- repo: https://github.com/pycqa/isort
rev: 5.12.0
hooks:
- id: isort
args: ["--profile", "black"]
- repo: https://github.com/astral-sh/ruff-pre-commit
rev: v0.0.261
hooks:
- id: ruff
args: ["--fix"]
- repo: https://github.com/pre-commit/mirrors-mypy
rev: v1.3.0
hooks:
- id: mypy
additional_dependencies: [types-all]

# .github/workflows/ci.yml
name: CI
on:
push:
branches: [main, develop]
pull_request:
branches: [main]
jobs:
test:
runs-on: ubuntu-latest
strategy:
matrix:
python-version: ['3.9', '3.10', '3.11']
steps:
- uses: actions/checkout@v3
- name: Set up Python ${{ matrix.python-version }}
uses: actions/setup-python@v4
with:
python-version: ${{ matrix.python-version }}
- name: Install dependencies
run: |
python -m pip install --upgrade pip
pip install -e ".[dev]"
- name: Lint with ruff
run: ruff check src/
- name: Format check with black
run: black --check src/
- name: Type check with mypy
run: mypy src/
- name: Test with pytest
run: |
coverage run -m pytest tests/
coverage report --fail-under=80
- name: Upload coverage
uses: codecov/codecov-action@v3
with:
files: ./coverage.xml

# 运行测试并生成覆盖率报告
$ coverage run -m pytest tests/
$ coverage report -m
Name                 Stmts   Miss  Cover   Missing
-----------------------------------------------------
src/validators.py       45      5    89%    23,45,67
src/models.py           78     12    85%    34,56,78
tests/test_validators.py  60      0   100%    -
-----------------------------------------------------
TOTAL                 183     17    91%

# 使用radon进行复杂度分析
from radon.metrics import mi_visit, h_visit
from radon.complexity import cc_visit
def analyze_complexity(filepath: str):
"""代码复杂度分析"""
with open(filepath, 'r') as f:
source = f.read()
# 圈复杂度
complexity = cc_visit(source)
print("圈复杂度:")
for item in complexity:
if item.classname:
name = f"{item.classname}.{item.name}"
else:
name = item.name
print(f"  {name}: {item.complexity}")
# 维护性指数
mi = mi_visit(source, multi=True)
print(f"\n维护性指数: {mi:.1f}")
# Halstead指标
from radon.metrics import h_visit
halstead = h_visit(source)
print(f"难度: {halstead.difficulty:.1f}")

- [ ] 代码符合PEP 8规范
- [ ] 函数和类有docstring
- [ ] 类型注解完整
- [ ] 单元测试覆盖关键逻辑
- [ ] 没有硬编码的魔法数字
- [ ] 错误处理适当
- [ ] 没有安全漏洞
- [ ] 性能符合要求

#!/bin/bash
# pre-commit-check.sh
set -e
echo "运行代码检查..."
# 格式化
black --check src/
echo "✓ 格式化检查通过"
# 检查import
isort --check-only --diff src/
echo "✓ import检查通过"
# Lint
ruff check src/
echo "✓ Lint检查通过"
# 类型检查
mypy src/
echo "✓ 类型检查通过"
# 测试
pytest tests/ -v
echo "✓ 测试通过"
echo "所有检查通过!"