mirror of
https://github.com/sweetwisdom/everything-claude-code-zh.git
synced 2026-03-22 14:40:14 +00:00
752 lines
17 KiB
Markdown
752 lines
17 KiB
Markdown
---
|
||
name: python-patterns
|
||
description: Pythonic idioms, PEP 8 standards, type hints, and best practices for building robust, efficient, and maintainable Python applications.
|
||
---
|
||
|
||
# Python 开发模式 (Python Development Patterns)
|
||
|
||
构建健壮、高效且可维护的应用程序的 Pythonic 惯用模式和最佳实践。
|
||
|
||
## 激活时机 (When to Activate)
|
||
|
||
- 编写新的 Python 代码时
|
||
- 进行 Python 代码审查（Review）时
|
||
- 重构现有的 Python 代码时
|
||
- 设计 Python 包（Package）或模块（Module）时
|
||
|
||
## 核心原则
|
||
|
||
### 1. 可读性至上 (Readability Counts)
|
||
|
||
Python 优先考虑可读性。代码应当直观且易于理解。
|
||
|
||
```python
|
||
# Good: 清晰且易读
|
||
def get_active_users(users: list[User]) -> list[User]:
|
||
"""仅从提供的列表中返回活跃用户。"""
|
||
return [user for user in users if user.is_active]
|
||
|
||
|
||
# Bad: 巧妙但令人困惑
|
||
def get_active_users(u):
|
||
return [x for x in u if x.a]
|
||
```
|
||
|
||
### 2. 显式优于隐式 (Explicit is Better Than Implicit)
|
||
|
||
避免“魔法”行为；清晰地表达代码的功能。
|
||
|
||
```python
|
||
# Good: 显式配置
|
||
import logging
|
||
|
||
logging.basicConfig(
|
||
level=logging.INFO,
|
||
format='%(asctime)s - %(name)s - %(levelname)s - %(message)s'
|
||
)
|
||
|
||
# Bad: 隐藏的副作用
|
||
import some_module
|
||
some_module.setup() # 这到底做了什么？
|
||
```
|
||
|
||
### 3. EAFP 模式 - 请求宽恕比请求许可更容易 (Easier to Ask Forgiveness Than Permission)
|
||
|
||
Python 倾向于使用异常处理而非预先检查条件。
|
||
|
||
```python
|
||
# Good: EAFP 风格
|
||
def get_value(dictionary: dict, key: str) -> Any:
|
||
try:
|
||
return dictionary[key]
|
||
except KeyError:
|
||
return default_value
|
||
|
||
# Bad: LBYL (Look Before You Leap，三思而后行) 风格
|
||
def get_value(dictionary: dict, key: str) -> Any:
|
||
if key in dictionary:
|
||
return dictionary[key]
|
||
else:
|
||
return default_value
|
||
```
|
||
|
||
## 类型提示 (Type Hints)
|
||
|
||
### 基础类型注解
|
||
|
||
```python
|
||
from typing import Optional, List, Dict, Any
|
||
|
||
def process_user(
|
||
user_id: str,
|
||
data: Dict[str, Any],
|
||
active: bool = True
|
||
) -> Optional[User]:
|
||
"""处理用户并返回更新后的 User 或 None。"""
|
||
if not active:
|
||
return None
|
||
return User(user_id, data)
|
||
```
|
||
|
||
### 现代类型提示 (Python 3.9+)
|
||
|
||
```python
|
||
# Python 3.9+ - 使用内置类型
|
||
def process_items(items: list[str]) -> dict[str, int]:
|
||
return {item: len(item) for item in items}
|
||
|
||
# Python 3.8 及更早版本 - 使用 typing 模块
|
||
from typing import List, Dict
|
||
|
||
def process_items(items: List[str]) -> Dict[str, int]:
|
||
return {item: len(item) for item in items}
|
||
```
|
||
|
||
### 类型别名 (Type Aliases) 和 TypeVar
|
||
|
||
```python
|
||
from typing import TypeVar, Union
|
||
|
||
# 复杂类型的类型别名
|
||
JSON = Union[dict[str, Any], list[Any], str, int, float, bool, None]
|
||
|
||
def parse_json(data: str) -> JSON:
|
||
return json.loads(data)
|
||
|
||
# 泛型
|
||
T = TypeVar('T')
|
||
|
||
def first(items: list[T]) -> T | None:
|
||
"""返回第一项，如果列表为空则返回 None。"""
|
||
return items[0] if items else None
|
||
```
|
||
|
||
### 基于协议 (Protocol) 的鸭子类型 (Duck Typing)
|
||
|
||
```python
|
||
from typing import Protocol
|
||
|
||
class Renderable(Protocol):
|
||
def render(self) -> str:
|
||
"""将对象渲染为字符串。"""
|
||
|
||
def render_all(items: list[Renderable]) -> str:
|
||
"""渲染所有实现了 Renderable 协议的项目。"""
|
||
return "\n".join(item.render() for item in items)
|
||
```
|
||
|
||
## 异常处理模式 (Error Handling Patterns)
|
||
|
||
### 特定异常处理
|
||
|
||
```python
|
||
# Good: 捕获特定的异常
|
||
def load_config(path: str) -> Config:
|
||
try:
|
||
with open(path) as f:
|
||
return Config.from_json(f.read())
|
||
except FileNotFoundError as e:
|
||
raise ConfigError(f"Config file not found: {path}") from e
|
||
except json.JSONDecodeError as e:
|
||
raise ConfigError(f"Invalid JSON in config: {path}") from e
|
||
|
||
# Bad: 空异常捕获
|
||
def load_config(path: str) -> Config:
|
||
try:
|
||
with open(path) as f:
|
||
return Config.from_json(f.read())
|
||
except:
|
||
return None # 静默失败！
|
||
```
|
||
|
||
### 异常链 (Exception Chaining)
|
||
|
||
```python
|
||
def process_data(data: str) -> Result:
|
||
try:
|
||
parsed = json.loads(data)
|
||
except json.JSONDecodeError as e:
|
||
# 使用异常链以保留堆栈跟踪 (traceback)
|
||
raise ValueError(f"Failed to parse data: {data}") from e
|
||
```
|
||
|
||
### 自定义异常层次结构
|
||
|
||
```python
|
||
class AppError(Exception):
|
||
"""所有应用程序错误的基类。"""
|
||
pass
|
||
|
||
class ValidationError(AppError):
|
||
"""当输入验证失败时引发。"""
|
||
pass
|
||
|
||
class NotFoundError(AppError):
|
||
"""当请求的资源未找到时引发。"""
|
||
pass
|
||
|
||
# 使用示例
|
||
def get_user(user_id: str) -> User:
|
||
user = db.find_user(user_id)
|
||
if not user:
|
||
raise NotFoundError(f"User not found: {user_id}")
|
||
return user
|
||
```
|
||
|
||
## 上下文管理器 (Context Managers)
|
||
|
||
### 资源管理
|
||
|
||
```python
|
||
# Good: 使用上下文管理器
|
||
def process_file(path: str) -> str:
|
||
with open(path, 'r') as f:
|
||
return f.read()
|
||
|
||
# Bad: 手动资源管理
|
||
def process_file(path: str) -> str:
|
||
f = open(path, 'r')
|
||
try:
|
||
return f.read()
|
||
finally:
|
||
f.close()
|
||
```
|
||
|
||
### 自定义上下文管理器
|
||
|
||
```python
|
||
from contextlib import contextmanager
|
||
|
||
@contextmanager
|
||
def timer(name: str):
|
||
"""用于对代码块计时的上下文管理器。"""
|
||
start = time.perf_counter()
|
||
yield
|
||
elapsed = time.perf_counter() - start
|
||
print(f"{name} took {elapsed:.4f} seconds")
|
||
|
||
# 使用示例
|
||
with timer("data processing"):
|
||
process_large_dataset()
|
||
```
|
||
|
||
### 上下文管理器类
|
||
|
||
```python
|
||
class DatabaseTransaction:
|
||
def __init__(self, connection):
|
||
self.connection = connection
|
||
|
||
def __enter__(self):
|
||
self.connection.begin_transaction()
|
||
return self
|
||
|
||
def __exit__(self, exc_type, exc_val, exc_tb):
|
||
if exc_type is None:
|
||
self.connection.commit()
|
||
else:
|
||
self.connection.rollback()
|
||
return False # 不要抑制异常
|
||
|
||
# 使用示例
|
||
with DatabaseTransaction(conn):
|
||
user = conn.create_user(user_data)
|
||
conn.create_profile(user.id, profile_data)
|
||
```
|
||
|
||
## 推导式 (Comprehensions) 与生成器 (Generators)
|
||
|
||
### 列表推导式 (List Comprehensions)
|
||
|
||
```python
|
||
# Good: 用于简单转换的列表推导式
|
||
names = [user.name for user in users if user.is_active]
|
||
|
||
# Bad: 手动循环
|
||
names = []
|
||
for user in users:
|
||
if user.is_active:
|
||
names.append(user.name)
|
||
|
||
# 复杂的推导式应当展开
|
||
# Bad: 太过复杂
|
||
result = [x * 2 for x in items if x > 0 if x % 2 == 0]
|
||
|
||
# Good: 使用生成器函数
|
||
def filter_and_transform(items: Iterable[int]) -> list[int]:
|
||
result = []
|
||
for x in items:
|
||
if x > 0 and x % 2 == 0:
|
||
result.append(x * 2)
|
||
return result
|
||
```
|
||
|
||
### 生成器表达式 (Generator Expressions)
|
||
|
||
```python
|
||
# Good: 用于延迟求值的生成器
|
||
total = sum(x * x for x in range(1_000_000))
|
||
|
||
# Bad: 创建了巨大的中间列表
|
||
total = sum([x * x for x in range(1_000_000)])
|
||
```
|
||
|
||
### 生成器函数 (Generator Functions)
|
||
|
||
```python
|
||
def read_large_file(path: str) -> Iterator[str]:
|
||
"""逐行读取大文件。"""
|
||
with open(path) as f:
|
||
for line in f:
|
||
yield line.strip()
|
||
|
||
# 使用示例
|
||
for line in read_large_file("huge.txt"):
|
||
process(line)
|
||
```
|
||
|
||
## 数据类 (Data Classes) 与命名元组 (Named Tuples)
|
||
|
||
### 数据类 (Data Classes)
|
||
|
||
```python
|
||
from dataclasses import dataclass, field
|
||
from datetime import datetime
|
||
|
||
@dataclass
|
||
class User:
|
||
"""具有自动生成 __init__、__repr__ 和 __eq__ 的用户实体。"""
|
||
id: str
|
||
name: str
|
||
email: str
|
||
created_at: datetime = field(default_factory=datetime.now)
|
||
is_active: bool = True
|
||
|
||
# 使用示例
|
||
user = User(
|
||
id="123",
|
||
name="Alice",
|
||
email="alice@example.com"
|
||
)
|
||
```
|
||
|
||
### 带验证的数据类
|
||
|
||
```python
|
||
@dataclass
|
||
class User:
|
||
email: str
|
||
age: int
|
||
|
||
def __post_init__(self):
|
||
# 验证电子邮件格式
|
||
if "@" not in self.email:
|
||
raise ValueError(f"Invalid email: {self.email}")
|
||
# 验证年龄范围
|
||
if self.age < 0 or self.age > 150:
|
||
raise ValueError(f"Invalid age: {self.age}")
|
||
```
|
||
|
||
### 命名元组 (Named Tuples)
|
||
|
||
```python
|
||
from typing import NamedTuple
|
||
|
||
class Point(NamedTuple):
|
||
"""不可变的二维点。"""
|
||
x: float
|
||
y: float
|
||
|
||
def distance(self, other: 'Point') -> float:
|
||
return ((self.x - other.x) ** 2 + (self.y - other.y) ** 2) ** 0.5
|
||
|
||
# 使用示例
|
||
p1 = Point(0, 0)
|
||
p2 = Point(3, 4)
|
||
print(p1.distance(p2)) # 5.0
|
||
```
|
||
|
||
## 装饰器 (Decorators)
|
||
|
||
### 函数装饰器
|
||
|
||
```python
|
||
import functools
|
||
import time
|
||
|
||
def timer(func: Callable) -> Callable:
|
||
"""用于对函数执行进行计时的装饰器。"""
|
||
@functools.wraps(func)
|
||
def wrapper(*args, **kwargs):
|
||
start = time.perf_counter()
|
||
result = func(*args, **kwargs)
|
||
elapsed = time.perf_counter() - start
|
||
print(f"{func.__name__} took {elapsed:.4f}s")
|
||
return result
|
||
return wrapper
|
||
|
||
@timer
|
||
def slow_function():
|
||
time.sleep(1)
|
||
|
||
# slow_function() 输出: slow_function took 1.0012s
|
||
```
|
||
|
||
### 参数化装饰器
|
||
|
||
```python
|
||
def repeat(times: int):
|
||
"""用于多次重复执行函数的装饰器。"""
|
||
def decorator(func: Callable) -> Callable:
|
||
@functools.wraps(func)
|
||
def wrapper(*args, **kwargs):
|
||
results = []
|
||
for _ in range(times):
|
||
results.append(func(*args, **kwargs))
|
||
return results
|
||
return wrapper
|
||
return decorator
|
||
|
||
@repeat(times=3)
|
||
def greet(name: str) -> str:
|
||
return f"Hello, {name}!"
|
||
|
||
# greet("Alice") 返回 ["Hello, Alice!", "Hello, Alice!", "Hello, Alice!"]
|
||
```
|
||
|
||
### 基于类的装饰器
|
||
|
||
```python
|
||
class CountCalls:
|
||
"""统计函数被调用次数的装饰器。"""
|
||
def __init__(self, func: Callable):
|
||
functools.update_wrapper(self, func)
|
||
self.func = func
|
||
self.count = 0
|
||
|
||
def __call__(self, *args, **kwargs):
|
||
self.count += 1
|
||
print(f"{self.func.__name__} has been called {self.count} times")
|
||
return self.func(*args, **kwargs)
|
||
|
||
@CountCalls
|
||
def process():
|
||
pass
|
||
|
||
# 每次调用 process() 都会打印调用计数
|
||
```
|
||
|
||
## 并发模式 (Concurrency Patterns)
|
||
|
||
### 线程 (Threading) 处理 I/O 密集型任务
|
||
|
||
```python
|
||
import concurrent.futures
|
||
import threading
|
||
|
||
def fetch_url(url: str) -> str:
|
||
"""获取 URL (I/O 密集型操作)。"""
|
||
import urllib.request
|
||
with urllib.request.urlopen(url) as response:
|
||
return response.read().decode()
|
||
|
||
def fetch_all_urls(urls: list[str]) -> dict[str, str]:
|
||
"""使用线程并发地获取多个 URL。"""
|
||
with concurrent.futures.ThreadPoolExecutor(max_workers=10) as executor:
|
||
future_to_url = {executor.submit(fetch_url, url): url for url in urls}
|
||
results = {}
|
||
for future in concurrent.futures.as_completed(future_to_url):
|
||
url = future_to_url[future]
|
||
try:
|
||
results[url] = future.result()
|
||
except Exception as e:
|
||
results[url] = f"Error: {e}"
|
||
return results
|
||
```
|
||
|
||
### 多进程 (Multiprocessing) 处理 CPU 密集型任务
|
||
|
||
```python
|
||
def process_data(data: list[int]) -> int:
|
||
"""CPU 密集型计算。"""
|
||
return sum(x ** 2 for x in data)
|
||
|
||
def process_all(datasets: list[list[int]]) -> list[int]:
|
||
"""使用多个进程处理多个数据集。"""
|
||
with concurrent.futures.ProcessPoolExecutor() as executor:
|
||
results = list(executor.map(process_data, datasets))
|
||
return results
|
||
```
|
||
|
||
### Async/Await 处理并发 I/O
|
||
|
||
```python
|
||
import asyncio
|
||
|
||
async def fetch_async(url: str) -> str:
|
||
"""异步获取 URL。"""
|
||
import aiohttp
|
||
async with aiohttp.ClientSession() as session:
|
||
async with session.get(url) as response:
|
||
return await response.text()
|
||
|
||
async def fetch_all(urls: list[str]) -> dict[str, str]:
|
||
"""并发地获取多个 URL。"""
|
||
tasks = [fetch_async(url) for url in urls]
|
||
results = await asyncio.gather(*tasks, return_exceptions=True)
|
||
return dict(zip(urls, results))
|
||
```
|
||
|
||
## 包组织 (Package Organization)
|
||
|
||
### 标准项目布局
|
||
|
||
```
|
||
myproject/
|
||
├── src/
|
||
│ └── mypackage/
|
||
│ ├── __init__.py
|
||
│ ├── main.py
|
||
│ ├── api/
|
||
│ │ ├── __init__.py
|
||
│ │ └── routes.py
|
||
│ ├── models/
|
||
│ │ ├── __init__.py
|
||
│ │ └── user.py
|
||
│ └── utils/
|
||
│ ├── __init__.py
|
||
│ └── helpers.py
|
||
├── tests/
|
||
│ ├── __init__.py
|
||
│ ├── conftest.py
|
||
│ ├── test_api.py
|
||
│ └── test_models.py
|
||
├── pyproject.toml
|
||
├── README.md
|
||
└── .gitignore
|
||
```
|
||
|
||
### 导入规范
|
||
|
||
```python
|
||
# Good: 导入顺序 - 标准库、第三方库、本地库
|
||
import os
|
||
import sys
|
||
from pathlib import Path
|
||
|
||
import requests
|
||
from fastapi import FastAPI
|
||
|
||
from mypackage.models import User
|
||
from mypackage.utils import format_name
|
||
|
||
# Good: 使用 isort 自动进行导入排序
|
||
# pip install isort
|
||
```
|
||
|
||
### 用于包导出的 __init__.py
|
||
|
||
```python
|
||
# mypackage/__init__.py
|
||
"""mypackage - 一个 Python 包示例。"""
|
||
|
||
__version__ = "1.0.0"
|
||
|
||
# 在包级别导出主要的类/函数
|
||
from mypackage.models import User, Post
|
||
from mypackage.utils import format_name
|
||
|
||
__all__ = ["User", "Post", "format_name"]
|
||
```
|
||
|
||
## 内存与性能
|
||
|
||
### 使用 __slots__ 提高内存效率
|
||
|
||
```python
|
||
# Bad: 常规类使用 __dict__ (占用更多内存)
|
||
class Point:
|
||
def __init__(self, x: float, y: float):
|
||
self.x = x
|
||
self.y = y
|
||
|
||
# Good: __slots__ 减少内存使用
|
||
class Point:
|
||
__slots__ = ['x', 'y']
|
||
|
||
def __init__(self, x: float, y: float):
|
||
self.x = x
|
||
self.y = y
|
||
```
|
||
|
||
### 用于大数据的生成器
|
||
|
||
```python
|
||
# Bad: 在内存中返回完整列表
|
||
def read_lines(path: str) -> list[str]:
|
||
with open(path) as f:
|
||
return [line.strip() for line in f]
|
||
|
||
# Good: 一次产出一行
|
||
def read_lines(path: str) -> Iterator[str]:
|
||
with open(path) as f:
|
||
for line in f:
|
||
yield line.strip()
|
||
```
|
||
|
||
### 避免在循环中进行字符串拼接
|
||
|
||
```python
|
||
# Bad: 由于字符串不可变性，复杂度为 O(n²)
|
||
result = ""
|
||
for item in items:
|
||
result += str(item)
|
||
|
||
# Good: 使用 join，复杂度为 O(n)
|
||
result = "".join(str(item) for item in items)
|
||
|
||
# Good: 使用 StringIO 进行构建
|
||
from io import StringIO
|
||
|
||
buffer = StringIO()
|
||
for item in items:
|
||
buffer.write(str(item))
|
||
result = buffer.getvalue()
|
||
```
|
||
|
||
## Python 工具链集成
|
||
|
||
### 常用命令
|
||
|
||
```bash
|
||
# 代码格式化
|
||
black .
|
||
isort .
|
||
|
||
# 静态检查 (Linting)
|
||
ruff check .
|
||
pylint mypackage/
|
||
|
||
# 类型检查
|
||
mypy .
|
||
|
||
# 测试
|
||
pytest --cov=mypackage --cov-report=html
|
||
|
||
# 安全扫描
|
||
bandit -r .
|
||
|
||
# 依赖管理
|
||
pip-audit
|
||
safety check
|
||
```
|
||
|
||
### pyproject.toml 配置
|
||
|
||
```toml
|
||
[project]
|
||
name = "mypackage"
|
||
version = "1.0.0"
|
||
requires-python = ">=3.9"
|
||
dependencies = [
|
||
"requests>=2.31.0",
|
||
"pydantic>=2.0.0",
|
||
]
|
||
|
||
[project.optional-dependencies]
|
||
dev = [
|
||
"pytest>=7.4.0",
|
||
"pytest-cov>=4.1.0",
|
||
"black>=23.0.0",
|
||
"ruff>=0.1.0",
|
||
"mypy>=1.5.0",
|
||
]
|
||
|
||
[tool.black]
|
||
line-length = 88
|
||
target-version = ['py39']
|
||
|
||
[tool.ruff]
|
||
line-length = 88
|
||
select = ["E", "F", "I", "N", "W"]
|
||
|
||
[tool.mypy]
|
||
python_version = "3.9"
|
||
warn_return_any = true
|
||
warn_unused_configs = true
|
||
disallow_untyped_defs = true
|
||
|
||
[tool.pytest.ini_options]
|
||
testpaths = ["tests"]
|
||
addopts = "--cov=mypackage --cov-report=term-missing"
|
||
```
|
||
|
||
## 快速参考：Python 惯用法 (Python Idioms)
|
||
|
||
| 惯用法 | 描述 |
|
||
|-------|-------------|
|
||
| EAFP | 请求宽恕比请求许可更容易 (Easier to Ask Forgiveness than Permission) |
|
||
| 上下文管理器 (Context managers) | 使用 `with` 进行资源管理 |
|
||
| 列表推导式 (List comprehensions) | 用于简单转换 |
|
||
| 生成器 (Generators) | 用于延迟求值和大型数据集 |
|
||
| 类型提示 (Type hints) | 为函数签名添加注解 |
|
||
| 数据类 (Dataclasses) | 用于带有自动生成方法的各种数据容器 |
|
||
| `__slots__` | 用于内存优化 |
|
||
| f-strings | 用于字符串格式化 (Python 3.6+) |
|
||
| `pathlib.Path` | 用于路径操作 (Python 3.4+) |
|
||
| `enumerate` | 在循环中获取索引-元素对 |
|
||
|
||
## 应避免的反模式 (Anti-Patterns)
|
||
|
||
```python
|
||
# Bad: 可变默认参数
|
||
def append_to(item, items=[]):
|
||
items.append(item)
|
||
return items
|
||
|
||
# Good: 使用 None 并创建新列表
|
||
def append_to(item, items=None):
|
||
if items is None:
|
||
items = []
|
||
items.append(item)
|
||
return items
|
||
|
||
# Bad: 使用 type() 检查类型
|
||
if type(obj) == list:
|
||
process(obj)
|
||
|
||
# Good: 使用 isinstance
|
||
if isinstance(obj, list):
|
||
process(obj)
|
||
|
||
# Bad: 使用 == 与 None 比较
|
||
if value == None:
|
||
process()
|
||
|
||
# Good: 使用 is
|
||
if value is None:
|
||
process()
|
||
|
||
# Bad: from module import *
|
||
from os.path import *
|
||
|
||
# Good: 显式导入
|
||
from os.path import join, exists
|
||
|
||
# Bad: 空异常捕获
|
||
try:
|
||
risky_operation()
|
||
except:
|
||
pass
|
||
|
||
# Good: 特定异常
|
||
try:
|
||
risky_operation()
|
||
except SpecificError as e:
|
||
logger.error(f"Operation failed: {e}")
|
||
```
|
||
|
||
__记住__：Python 代码应当是易读的、显式的，并遵循最小惊讶原则。如有疑问，请优先考虑清晰度而非巧妙性。
|
||
|
||
```
|