下面是一个“标准递归答案”，类似于其他类似的答案https://stackoverflow.com/a/23743696/711085。(实际上，我们不必担心耗尽堆栈空间，因为我们没有办法处理所有N!排列)。

它依次访问每个元素，要么取它，要么离开它(从这个算法中我们可以直接看到2^N的基数)。

def combs(xs, i=0):
    if i==len(xs):
        yield ()
        return
    for c in combs(xs,i+1):
        yield c
        yield c+(xs[i],)

演示:

>>> list( combs(range(5)) )
[(), (0,), (1,), (1, 0), (2,), (2, 0), (2, 1), (2, 1, 0), (3,), (3, 0), (3, 1), (3, 1, 0), (3, 2), (3, 2, 0), (3, 2, 1), (3, 2, 1, 0), (4,), (4, 0), (4, 1), (4, 1, 0), (4, 2), (4, 2, 0), (4, 2, 1), (4, 2, 1, 0), (4, 3), (4, 3, 0), (4, 3, 1), (4, 3, 1, 0), (4, 3, 2), (4, 3, 2, 0), (4, 3, 2, 1), (4, 3, 2, 1, 0)]

>>> list(sorted( combs(range(5)), key=len))
[(), 
 (0,), (1,), (2,), (3,), (4,), 
 (1, 0), (2, 0), (2, 1), (3, 0), (3, 1), (3, 2), (4, 0), (4, 1), (4, 2), (4, 3), 
 (2, 1, 0), (3, 1, 0), (3, 2, 0), (3, 2, 1), (4, 1, 0), (4, 2, 0), (4, 2, 1), (4, 3, 0), (4, 3, 1), (4, 3, 2), 
 (3, 2, 1, 0), (4, 2, 1, 0), (4, 3, 1, 0), (4, 3, 2, 0), (4, 3, 2, 1), 
 (4, 3, 2, 1, 0)]

>>> len(set(combs(range(5))))
32

3个功能:

列出n个元素的所有组合 列出n个元素的所有组合，其中顺序不明确 所有的排列

import sys

def permutations(a):
    return combinations(a, len(a))

def combinations(a, n):
    if n == 1:
        for x in a:
            yield [x]
    else:
        for i in range(len(a)):
            for x in combinations(a[:i] + a[i+1:], n-1):
                yield [a[i]] + x

def combinationsNoOrder(a, n):
    if n == 1:
        for x in a:
            yield [x]
    else:
        for i in range(len(a)):
            for x in combinationsNoOrder(a[:i], n-1):
                yield [a[i]] + x
    
if __name__ == "__main__":
    for s in combinations(list(map(int, sys.argv[2:])), int(sys.argv[1])):
        print(s)

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)]

我同意Dan H的观点，Ben确实要求所有的组合。itertools.combination()不会给出所有的组合。

另一个问题是，如果输入iterable很大，返回一个生成器而不是列表中的所有内容可能会更好:

iterable = range(10)
for s in xrange(len(iterable)+1):
  for comb in itertools.combinations(iterable, s):
    yield comb

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