Python 那些坑与妙用

from functools import wraps

def log_time(func):
    @wraps(func)
    def wrapper(*args, **kwargs):
        start = time.time()
        result = func(*args, **kwargs)
        print(f'{func.__name__} took {time.time() - start:.3f}s')
        return result
    return wrapper

@log_time
def slow_function():
    time.sleep(1)

def retry(max_attempts=3):
    def decorator(func):
        @wraps(func)
        def wrapper(*args, **kwargs):
            for i in range(max_attempts):
                try:
                    return func(*args, **kwargs)
                except Exception as e:
                    if i == max_attempts - 1:
                        raise
                    print(f'重试第 {i+1} 次')
            return None
        return wrapper
    return decorator

@retry(max_attempts=5)
def unstable_api_call():
    ...

# 方式一：__enter__ / __exit__
class Timer:
    def __enter__(self):
        self.start = time.time()
        return self

    def __exit__(self, exc_type, exc_val, exc_tb):
        self.elapsed = time.time() - self.start
        print(f'耗时: {self.elapsed:.3f}s')

with Timer() as t:
    do_something()

# 方式二：contextmanager 装饰器
from contextlib import contextmanager

@contextmanager
def timer():
    start = time.time()
    yield
    print(f'耗时: {time.time() - start:.3f}s')

with timer():
    do_something()

from contextlib import suppress, ExitStack

# 忽略特定异常（比 try/except/pass 干净）
with suppress(FileNotFoundError):
    os.remove('temp.txt')

# 同时管理多个上下文
with ExitStack() as stack:
    files = [stack.enter_context(open(f)) for f in ['a.txt', 'b.txt']]
    # 所有文件会在退出 with 块时自动关闭

# 生成器函数
def read_large_file(file_path):
    with open(file_path) as f:
        for line in f:
            yield line.strip()

for line in read_large_file('data.csv'):
    process(line)  # 逐行处理，不会把整个文件读进内存

# yield from：委托给另一个生成器
def flatten(lists):
    for sub in lists:
        yield from sub

for item in flatten([[1, 2], [3, 4], [5]]):
    print(item)  # 1 2 3 4 5

# enumerate：同时拿下标和值
for i, v in enumerate(['a', 'b', 'c'], start=1):
    print(i, v)   # 1 a / 2 b / 3 c

# zip：合并多个可迭代对象
for name, age in zip(['Alice', 'Bob'], [30, 25]):
    print(f'{name}: {age}')

# itertools 链式迭代
from itertools import chain, groupby, product

list(chain([1,2], [3,4]))     # [1, 2, 3, 4]

from dataclasses import dataclass, field

@dataclass
class User:
    name: str
    age: int = 0
    tags: list[str] = field(default_factory=list)

# 自动生成 __init__、__repr__、__eq__ 等
u = User('Alice', 30)
print(u)        # User(name='Alice', age=30)
print(u == User('Alice', 30))  # True

from typing import Optional, List, Dict, Tuple

def greet(name: str) -> str:
    return f'Hello, {name}'

# 可选类型
def find_user(id: int) -> Optional[dict]:
    ...

# 3.10+ 写法更简洁
def process(items: list[str]) -> dict[str, int]:
    return {item: len(item) for item in items}

# Union 简化
# 旧：Union[int, str]  →  新：int | str
# 旧：Optional[str]    →  新：str | None

# requirements.txt
requests==2.31.0
flask>=2.3,<3.0

# ❌ 大坑
def add_item(item, lst=[]):
    lst.append(item)
    return lst

print(add_item(1))  # [1]
print(add_item(2))  # [1, 2]  ← 不是 [2]！

# ✅ 正确
def add_item(item, lst=None):
    if lst is None:
        lst = []
    lst.append(item)
    return lst

# ❌ 你以为输出什么？
funcs = []
for i in range(3):
    funcs.append(lambda: i)

for f in funcs:
    print(f())  # 2 2 2  ← 不是 0 1 2

# ✅ 正确：默认参数绑定当前值
funcs = []
for i in range(3):
    funcs.append(lambda i=i: i)

# else 在循环没有被 break 时执行
for n in range(2, 10):
    for x in range(2, n):
        if n % x == 0:
            break
    else:
        print(n, '是质数')

import copy

original = {'nested': {'a': 1}}
shallow = copy.copy(original)
deep = copy.deepcopy(original)

shallow['nested']['a'] = 99
print(original['nested']['a'])  # 99 ← 被改了

deep['nested']['a'] = 42
print(original['nested']['a'])  # 99 ← 没影响

# f-string 格式化（3.6+）
name = 'Alice'
age = 30
print(f'{name} is {age} years old')     # Alice is 30 years old
print(f'{name:>10}')                     # 右对齐：     Alice
print(f'{age:04d}')                      # 补零：0030

# 3.8+ 自调试表达式
print(f'{name=}, {age=}')                # name='Alice', age=30

# 3.12+ 支持引号复用
print(f'{name} is {age:,}')              # 30 → 30（数字千分位暂不支持）

from pathlib import Path

# 告别 os.path.join
data_dir = Path('data')
config = data_dir / 'config.json'

# 读文件（自动处理编码）
content = Path('data.txt').read_text(encoding='utf-8')

# 写文件
Path('output.txt').write_text('hello')

# 遍历目录
for py_file in Path('src').glob('**/*.py'):
    print(py_file)

# 确保目录存在
Path('output/logs').mkdir(parents=True, exist_ok=True)

import logging

logging.basicConfig(
    level=logging.INFO,
    format='%(asctime)s | %(levelname)-8s | %(name)s | %(message)s',
    datefmt='%Y-%m-%d %H:%M:%S',
)

logger = logging.getLogger(__name__)
logger.info('应用启动')
logger.error('出错了', exc_info=True)

# 按模块区分日志级别
logging.getLogger('httpx').setLevel(logging.WARNING)
logging.getLogger('urllib3').setLevel(logging.WARNING)