Python代码质量之从规范到自动化检查全过程

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# 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()",

]

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importpytest

fromtypingimportList, Optional

classDataValidator:

"""数据验证器"""

@staticmethod

defvalidate_email(email:str)->bool:

"""验证邮箱格式"""

importre

pattern=r'^[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}$'

returnbool(re.match(pattern, email))

@staticmethod

defvalidate_positive(value:float)->bool:

"""验证正数"""

returnvalue >0

@staticmethod

defvalidate_in_range(value:float, min_val:float, max_val:float)->bool:

"""验证范围"""

returnmin_val <=value <=max_val

classTestDataValidator:

"""数据验证器测试"""

@pytest.mark.parametrize("email,expected", [

("test@example.com",True),

("user.name@domain.co.uk",True),

("invalid-email",False),

("@domain.com",False),

("user@",False),

("",False),

])

deftest_validate_email(self, email, expected):

assertDataValidator.validate_email(email)==expected

@pytest.mark.parametrize("value,expected", [

(1.0,True),

(0.0,False),

(-1.0,False),

(100.5,True),

])

deftest_validate_positive(self, value, expected):

assertDataValidator.validate_positive(value)==expected

deftest_validate_in_range(self):

assertDataValidator.validate_in_range(5,0,10)==True

assertDataValidator.validate_in_range(0,0,10)==True

assertDataValidator.validate_in_range(10,0,10)==True

assertDataValidator.validate_in_range(-1,0,10)==False

assertDataValidator.validate_in_range(11,0,10)==False

classTestEdgeCases:

"""边界情况测试"""

deftest_empty_string(self):

assertDataValidator.validate_email("")==False

deftest_unicode_email(self):

assertDataValidator.validate_email("用户@例子.广告")==False

deftest_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)

assertisinstance(result,bool)

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fromunittest.mockimportMock, patch, MagicMock

importpytest

classAPIClient:

"""API客户端"""

def__init__(self, base_url:str):

self.base_url=base_url

self.session=None

deffetch(self, endpoint:str)->dict:

"""获取数据"""

importrequests

response=requests.get(f"{self.base_url}/{endpoint}")

returnresponse.json()

classTestAPIClient:

"""API客户端测试"""

@patch('requests.get')

deftest_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")

assertresult["status"]=="success"

assertresult["data"]==[1,2,3]

mock_get.assert_called_once_with("https://api.example.com/users")

@patch('requests.get')

deftest_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")

deftest_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"inresult

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importpytest

importtime

classTestPerformance:

"""性能测试"""

deftest_sort_performance(self):

"""测试排序性能"""

importrandom

# 生成大量数据

data=[random.randint(0,10000)for_inrange(10000)]

start=time.perf_counter()

sorted_data=sorted(data)

elapsed=time.perf_counter()-start

# 应该在1秒内完成

assertelapsed <1.0, f"排序耗时 {elapsed:.2f}s，超过1秒"

# 验证排序正确性

assertsorted_data==sorted(data)

@pytest.mark.benchmark

deftest_list_comprehension_performance(self, benchmark):

"""基准测试列表推导式"""

result=benchmark(lambda: [i**2foriinrange(10000)])

assertlen(result)==10000

# conftest.py

defpytest_configure(config):

config.addinivalue_line("markers","benchmark: mark test as a benchmark")

@pytest.fixture

defsample_data():

"""示例数据fixture"""

return[iforiinrange(100)]

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# .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]

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# .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

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# 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.py45589%23,45,67

src/models.py781285%34,56,78

tests/test_validators.py600100%-

-----------------------------------------------------

TOTAL1831791%

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# 使用radon进行复杂度分析

fromradon.metricsimportmi_visit, h_visit

fromradon.complexityimportcc_visit

defanalyze_complexity(filepath:str):

"""代码复杂度分析"""

withopen(filepath,'r') as f:

source=f.read()

# 圈复杂度

complexity=cc_visit(source)

print("圈复杂度:")

foritemincomplexity:

ifitem.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

fromradon.metricsimporth_visit

halstead=h_visit(source)

print(f"难度: {halstead.difficulty:.1f}")

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-[ ] 代码符合PEP8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

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#!/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 --diffsrc/

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!"