与语言 X 闭包相比，Python 中的闭包有哪些限制？

我看到人们在使用 Python 时遇到的唯一困难是，当他们试图将变量重赋等非功能性功能与闭包混合在一起时，当这不起作用时会感到惊讶：

def outer ():
    x = 1
    def inner ():
        print x
        x = 2
    return inner
outer () ()

通常，只要指出一个函数有自己的局部变量就足以阻止这种愚蠢。

目前，最重要的限制是不能赋值给外域变量。换言之，闭包是只读的：

>>> def outer(x): 
...     def inner_reads():
...         # Will return outer's 'x'.
...         return x
...     def inner_writes(y):
...         # Will assign to a local 'x', not the outer 'x'
...         x = y
...     def inner_error(y):
...         # Will produce an error: 'x' is local because of the assignment,
...         # but we use it before it is assigned to.
...         tmp = x
...         x = y
...         return tmp
...     return inner_reads, inner_writes, inner_error
... 
>>> inner_reads, inner_writes, inner_error = outer(5)
>>> inner_reads()
5
>>> inner_writes(10)
>>> inner_reads()
5
>>> inner_error(10)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "<stdin>", line 11, in inner_error
UnboundLocalError: local variable 'x' referenced before assignment

除非另有声明，否则在本地作用域（函数）中分配给的名称始终是本地名称。虽然有“全局”声明来声明一个变量全局，即使它被赋值给，但对于封闭的变量还没有这样的声明。在 Python 3.0 中，有（将有）“非本地”声明可以做到这一点。

同时，您可以使用可变容器类型来解决此限制：

>>> def outer(x):
...     x = [x]
...     def inner_reads():
...         # Will return outer's x's first (and only) element.
...         return x[0]
...     def inner_writes(y):
...         # Will look up outer's x, then mutate it.      
...         x[0] = y
...     def inner_error(y):
...         # Will now work, because 'x' is not assigned to, just referenced.
...         tmp = x[0]
...         x[0] = y
...         return tmp
...     return inner_reads, inner_writes, inner_error
... 
>>> inner_reads, inner_writes, inner_error = outer(5)
>>> inner_reads()
5
>>> inner_writes(10)
>>> inner_reads()
10
>>> inner_error(15)
10
>>> inner_reads()
15

@John米利金

def outer():
    x = 1 # local to `outer()`

    def inner():
        x = 2     # local to `inner()`
        print(x)
        x = 3
        return x

    def inner2():
        nonlocal x
        print(x)  # local to `outer()`
        x = 4     # change `x`, it is not local to `inner2()`
        return x

    x = 5         # local to `outer()`
    return (inner, inner2)

for inner in outer():
    print(inner()) 

# -> 2 3 5 4

在 Python 3 中通过非本地语句修复：

该语句使列出的标识符引用最近封闭范围（不包括全局变量）中先前绑定的变量。这很重要，因为绑定的默认行为是首先搜索本地命名空间。该语句允许封装的代码重新绑定全局（模块）范围之外的局部范围之外的变量。nonlocal

_{注释 @Kevin Little 的答案以包含代码示例}

nonlocal在 python3.0 上不能完全解决这个问题：

x = 0 # global x
def outer():
    x = 1 # local to `outer`
    def inner():
        global x
        x = 2 # change global
        print(x) 
        x = 3 # change global
        return x
    def inner2():
##        nonlocal x # can't use `nonlocal` here
        print(x)     # prints global
##        x = 4      # can't change `x` here
        return x
    x = 5
    return (inner, inner2)

for inner in outer():
    print(inner())
# -> 2 3 3 3

另一方面：

x = 0
def outer():
    x = 1 # local to `outer`
    def inner():
##        global x
        x = 2
        print(x) # local to `inner` 
        x = 3 
        return x
    def inner2():
        nonlocal x
        print(x)
        x = 4  # local to `outer`
        return x
    x = 5
    return (inner, inner2)

for inner in outer():
    print(inner())
# -> 2 3 5 4

它适用于 python3.1-3.3

在 3.0 之前，更好的解决方法是将变量作为默认参数包含在随附的函数定义中：

def f()
    x = 5
    def g(y, z, x=x):
        x = x + 1

与 Javascript 闭包相比，Python 闭包的一个局限性（或“限制”）是它不能用于有效的数据隐藏

Java脚本

var mksecretmaker = function(){
    var secrets = [];
    var mksecret = function() {
        secrets.push(Math.random())
    }
    return mksecret
}
var secretmaker = mksecretmaker();
secretmaker(); secretmaker()
// privately generated secret number list
// is practically inaccessible

蟒

import random
def mksecretmaker():
    secrets = []
    def mksecret():
        secrets.append(random.random())
    return mksecret

secretmaker = mksecretmaker()
secretmaker(); secretmaker()
# "secrets" are easily accessible,
# it's difficult to hide something in Python:
secretmaker.__closure__[0].cell_contents # -> e.g. [0.680752847190161, 0.9068475951742101]