这种方法可以很容易地移植到所有支持递归的编程语言中(没有itertools，没有yield，没有列表理解):

def combs(a):
    if len(a) == 0:
        return [[]]
    cs = []
    for c in combs(a[1:]):
        cs += [c, c+[a[0]]]
    return cs

>>> combs([1,2,3,4,5])
[[], [1], [2], [2, 1], [3], [3, 1], [3, 2], ..., [5, 4, 3, 2, 1]]

这一行代码给出了所有的组合(如果原始列表/set包含n个不同的元素，则在0到n个元素之间)，并使用本机方法itertools.combination:

Python 2

from itertools import combinations

input = ['a', 'b', 'c', 'd']

output = sum([map(list, combinations(input, i)) for i in range(len(input) + 1)], [])

Python 3

from itertools import combinations

input = ['a', 'b', 'c', 'd']

output = sum([list(map(list, combinations(input, i))) for i in range(len(input) + 1)], [])

输出将是:

[[],
 ['a'],
 ['b'],
 ['c'],
 ['d'],
 ['a', 'b'],
 ['a', 'c'],
 ['a', 'd'],
 ['b', 'c'],
 ['b', 'd'],
 ['c', 'd'],
 ['a', 'b', 'c'],
 ['a', 'b', 'd'],
 ['a', 'c', 'd'],
 ['b', 'c', 'd'],
 ['a', 'b', 'c', 'd']]

在网上试试吧:

http://ideone.com/COghfX

我喜欢这个问题，因为有很多方法来实现它。我决定为未来创造一个参考答案。

在生产中使用什么?

intertools的文档有一个独立的例子，为什么不在你的代码中使用它呢?一些人建议使用more_itertools。Powerset，但它具有完全相同的实现!如果我是你，我不会为一个小东西安装整个软件包。也许这是最好的方法:

import itertools

def powerset(iterable):
    "powerset([1,2,3]) --> () (1,) (2,) (3,) (1,2) (1,3) (2,3) (1,2,3)"
    s = list(iterable)
    return itertools.chain.from_iterable(combinations(s, r) for r in range(len(s)+1))

其他可能的方法

方法0:使用组合

import itertools

def subsets(nums):
    result = []
    for i in range(len(nums) + 1):
        result += itertools.combinations(nums, i)
    return result

方法1:简单的递归

def subsets(nums):
    result = []

    def powerset(alist, index, curr):
        if index == len(alist):
            result.append(curr)
            return

        powerset(alist, index + 1, curr + [alist[index]])
        powerset(alist, index + 1, curr)

    powerset(nums, 0, [])
    return result

方法2:回溯

def subsets(nums):
    result = []

    def backtrack(index, curr, k):
        if len(curr) == k:
            result.append(list(curr))
            return
        for i in range(index, len(nums)):
            curr.append(nums[i])
            backtrack(i + 1, curr, k)
            curr.pop()

    for k in range(len(nums) + 1):
        backtrack(0, [], k)
    return result

or

def subsets(nums):
    result = []

    def dfs(nums, index, path, result):
        result.append(path)
        for i in range(index, len(nums)):
            dfs(nums, i + 1, path + [nums[i]], result)

    dfs(nums, 0, [], result)
    return result

方法3:位掩码

def subsets(nums):
    res = []
    n = len(nums)
    for i in range(1 << n):
        aset = []
        for j in range(n):
            value = (1 << j) & i  # value = (i >> j) & 1
            if value:
                aset.append(nums[j])
        res.append(aset)
    return res

或者(不是位掩码，直觉上是2^n个子集)

def subsets(nums):
    subsets = []
    expected_subsets = 2 ** len(nums)

    def generate_subset(subset, nums):
        if len(subsets) >= expected_subsets:
            return
        if len(subsets) < expected_subsets:
            subsets.append(subset)
        for i in range(len(nums)):
            generate_subset(subset + [nums[i]], nums[i + 1:])

    generate_subset([], nums)
    return subsets

方法4:级联

def subsets(nums):
    result = [[]]
    for i in range(len(nums)):
        for j in range(len(result)):
            subset = list(result[j])
            subset.append(nums[i])
            result.append(subset)
    return result

下面是itertools.combination的两个实现

返回一个列表的函数

def combinations(lst, depth, start=0, items=[]):
    if depth <= 0:
        return [items]
    out = []
    for i in range(start, len(lst)):
        out += combinations(lst, depth - 1, i + 1, items + [lst[i]])
    return out

一个返回一个生成器

def combinations(lst, depth, start=0, prepend=[]):
    if depth <= 0:
        yield prepend
    else:
        for i in range(start, len(lst)):
            for c in combinations(lst, depth - 1, i + 1, prepend + [lst[i]]):
                yield c

请注意，建议为它们提供一个helper函数，因为prepend参数是静态的，不会随着每次调用而改变

print([c for c in combinations([1, 2, 3, 4], 3)])
# [[1, 2, 3], [1, 2, 4], [1, 3, 4], [2, 3, 4]]

# get a hold of prepend
prepend = [c for c in combinations([], -1)][0]
prepend.append(None)

print([c for c in combinations([1, 2, 3, 4], 3)])
# [[None, 1, 2, 3], [None, 1, 2, 4], [None, 1, 3, 4], [None, 2, 3, 4]]

这是一个很肤浅的例子，但小心为妙

你可以使用以下简单的代码在Python中生成列表的所有组合:

import itertools

a = [1,2,3,4]
for i in xrange(0,len(a)+1):
   print list(itertools.combinations(a,i))

结果将是:

[()]
[(1,), (2,), (3,), (4,)]
[(1, 2), (1, 3), (1, 4), (2, 3), (2, 4), (3, 4)]
[(1, 2, 3), (1, 2, 4), (1, 3, 4), (2, 3, 4)]
[(1, 2, 3, 4)]

这里是另一个解决方案(一行程序)，涉及到使用itertools.combination函数，但这里我们使用了双链表理解式(而不是for循环或sum):

def combs(x):
    return [c for i in range(len(x)+1) for c in combinations(x,i)]

演示:

>>> combs([1,2,3,4])
[(), 
 (1,), (2,), (3,), (4,), 
 (1, 2), (1, 3), (1, 4), (2, 3), (2, 4), (3, 4), 
 (1, 2, 3), (1, 2, 4), (1, 3, 4), (2, 3, 4), 
 (1, 2, 3, 4)]