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)]

如果有人正在寻找一个反向列表，就像我一样:

stuff = [1, 2, 3, 4]

def reverse(bla, y):
    for subset in itertools.combinations(bla, len(bla)-y):
        print list(subset)
    if y != len(bla):
        y += 1
        reverse(bla, y)

reverse(stuff, 1)

来自itertools的组合

import itertools
col_names = ["aa","bb", "cc", "dd"]
all_combinations = itertools.chain(*[itertools.combinations(col_names,i+1) for i,_ in enumerate(col_names)])
print(list(all_combinations))

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

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]]

我想我应该为那些寻求答案的人添加这个函数，而不需要导入itertools或任何其他额外的库。

def powerSet(items):
    """
    Power set generator: get all possible combinations of a list’s elements

    Input:
        items is a list
    Output:
        returns 2**n combination lists one at a time using a generator 

    Reference: edx.org 6.00.2x Lecture 2 - Decision Trees and dynamic programming
    """

    N = len(items)
    # enumerate the 2**N possible combinations
    for i in range(2**N):
        combo = []
        for j in range(N):
            # test bit jth of integer i
            if (i >> j) % 2 == 1:
                combo.append(items[j])
        yield combo

简单Yield Generator用法:

for i in powerSet([1,2,3,4]):
    print (i, ", ",  end="")

以上用法示例的输出:

[], [1], [2], [1, 2], [3], [1, 3], [2, 3], [1, 2, 3], [4]. [1, 4], [2, 4], [1, 2, 4], [3, 4], [1, 3, 4], [2, 3, 4], [1, 2, 3, 4],