Python 可变默认参数 & 闭包延迟绑定的实现

def add_item(item, items=[]):
    items.append(item)
    return items

print(add_item(1))          # [1]
print(add_item(2))          # [1, 2]  👈 预期是 [2]！
print(add_item(3))          # [1, 2, 3]

def test(items=[]):
    print(id(items))  # 每次调用都打印相同的内存地址

test()  # 4395790912
test()  # 4395790912
test()  # 4395790912

# ✅ 用 None 做哨兵，函数内部创建新对象
def add_item(item, items=None):
    if items is None:
        items = []
    items.append(item)
    return items

print(add_item(1))   # [1]
print(add_item(2))   # [2]  ✅ 符合预期

# 不只是 list，任何可变对象都一样
def bad(d={}):
    d["count"] = d.get("count", 0) + 1
    return d

print(bad())  # {'count': 1}
print(bad())  # {'count': 2}  ❌

# 甚至连 Datetime 和 lambda 也不例外
import datetime

def log_time(t=datetime.datetime.now()):
    print(t)

log_time()  # 每次打印相同的时刻 ❌

def create_multipliers():
    return [lambda x: i * x for i in range(5)]

multipliers = create_multipliers()
for m in multipliers:
    print(m(2))  # 输出：8 8 8 8 8  👈 预期：0 2 4 6 8

# 等价写法，更容易看穿
funcs = []
for i in range(5):
    funcs.append(lambda x: i * x)

i = 4  # 循环结束后的 i

for f in funcs:
    print(f(2))  # 全部 8

def create_multipliers():
    return [lambda x, i=i: i * x for i in range(5)]
    #          ^^^^  默认参数在循环每次迭代时求值，i 的值被固定

from functools import partial

def multiply(x, i):
    return i * x

def create_multipliers():
    return [partial(multiply, i) for i in range(5)]

def create_multipliers():
    def make_multiplier(i):
        return lambda x: i * x
    return [make_multiplier(i) for i in range(5)]

def create_actions():
    actions = []
    for i in range(3):
        def action(item, cache=[]):  # 默认参数绑定 + 可变对象
            cache.append(item)
            return f"i={i}, cache={cache}"  # i 是延迟绑定的
        actions.append(action)
    return actions

actions = create_actions()
print(actions[0]("a"))  # i=2, cache=['a']  ❌ i 预期 0
print(actions[1]("b"))  # i=2, cache=['a', 'b']  ❌ 双重坑
print(actions[2]("c"))  # i=2, cache=['a', 'b', 'c']

def create_actions():
    actions = []
    for i in range(3):
        def action(item, cache=None):
            if cache is None:
                cache = []
            cache.append(item)
            return f"i={i}, cache={cache}"
        actions.append(action)
    return actions

def create_actions():
    actions = []
    for i in range(3):
        def action(item, cache=None, i=i):  # 同时解决两个坑
            if cache is None:
                cache = []
            cache.append(item)
            return f"i={i}, cache={cache}"
        actions.append(action)
    return actions

# ❌ 不要这样写
def process(data=[]):           # 可变默认参数
    ...

# ✅ 改成这样
def process(data=None):
    data = data or []           # 或严格判断：if data is None: data = []


# ❌ 不要在循环中直接创建闭包
funcs = [lambda: i for i in range(5)]

# ✅ 绑定当前值
funcs = [lambda i=i: i for i in range(5)]