逐字符拆分列表元素

在一行中的功能：

reduce(lambda a, x: a + x, map(lambda x: list(x), ['1', '22', '333']))

我解释一下 -reduce它以一个函数作为输入，该函数组合了按函数拆分列表的结果map。Map接受一个函数和一个初始数组作为输入，这个函数在数组的每个元素上执行。同样可以用下面的代码来表达：

>>> result_list = []
>>> for x in ['1', '22', '333']:
...     for y in list(x):
...         result_list.append(y)
... 
>>> print(result_list)
['1', '2', '2', '3', '3', '3']

建议选项的速度比较：

join在一行结果中使用和关联的变体已经完成了所有工作。这并不奇怪 - 这里的所有操作都很快。适用于任何iterable对象：

$python3 -m timeit "list(''.join(['1', '22', '333']))"
1000000 loops, best of 3: 0.318 usec per loop

使用@jfs 答案中的列表生成器的变体非常快：

$python3 -m timeit "[char for s in ['1', '22', '333'] for char in s]"
1000000 loops, best of 3: 0.452 usec per loop

use 选项sum在速度上排名第三，但在我看来它失去了直观性：

$python3 -m timeit "sum([list(i) for i in ['1', '22', '333']], [])"
1000000 loops, best of 3: 0.984 usec per loop

选项开map-reduce是最慢的。我为什么要用它？因为我喜欢调用链。剩下的就是味道了。然而，即使是 Guido 也讨厌reduce（并functools在python3中呈现）

$python3 -m timeit "from functools import reduce; reduce(lambda a, x: a + x, map(lambda x: list(x), ['1', '22', '333']))"
100000 loops, best of 3: 2.16 usec per loop

选项 ccollections涵盖了传递的对象可以是不可迭代的（例如，一个数字）的所有情况，但这样做的代价是执行时间很长：

$python3 -m timeit "import collections

def it(obj):
    if isinstance(obj, collections.Iterable):
        for ob in obj:
            if isinstance(ob, collections.Iterable) and len(ob) > 1:
                yield from it(ob)
            else: yield ob
    else:
        yield obj

list(it(['1', 2, [2, 44, '123', ('qwe')], 2]))"
100000 loops, best of 3: 14.6 usec per loop

由于他们开始在这里收集不同的方式，我将提供：

list(''.join(['1', '22', '333']))

（现在有人必须比较所有选项的性能:)

你可以这样做：

l = ['1', '22', '333']
s = sum([list(i) for i in l], [])
print(s)
['1', '2', '2', '3', '3', '3']

要从字符串列表中获取字符列表，可以在列表生成器中使用嵌套循环：

strings = ['1', '22', '333']
chars = [char for s in strings for char in s]
# chars -> ['1', '2', '2', '3', '3', '3']

类似问题：Flattening a shallow list in Python。

根据@Alex Martelli 的说法，此选项可能比使用sum(),reduce()的解决方案更快。列表理解解决方案也比reduce().

import collections

def it(obj):
    if isinstance(obj, collections.Iterable):
        for ob in obj:
            if isinstance(ob, collections.Iterable) and len(ob) > 1:
                yield from it(ob)
            else: yield ob
    else:
        yield obj

a = list(it(['1', 2, [2, 44, '123', ('qwe')], 2]))
print(a)
['1', 2, 2, 44, '1', '2', '3', 'q', 'w', 'e', 2]

抓住：

a = ['1', '22', '333']
a = [x for x in ''.join(a)]

import time
from functools import wraps, reduce

def tefn(fn, args, kwargs):
    t = time.time()
    tuple(fn(*args, **kwargs))
    return t - time.time()

def efn(fn, args, kwargs):
    t = time.time()
    fn(*args, **kwargs)
    return t - time.time()

def runTime(tp=0, count=25):
    def dec(fn):
        @wraps(fn)
        def wrap(*args, **kwargs):
            print(fn)
            res = tefn if tp else efn
            return sum(res(fn, args, kwargs) for _ in range(count)) / count
        return wrap
    return dec


@runTime()
def fnTuple(): return tuple(char for s in list_ for char in s)
@runTime(tp=1)
def fnIter(): return iter(char for s in list_ for char in s)
@runTime()
def fnList(): return list(char for s in list_ for char in s)
@runTime(tp=1)
def fnYield():
    for a in list_: yield from a
@runTime(tp=1)
def fnJoin(): return ''.join(list_)
@runTime()
def fnSumm(): return sum([list(i) for i in list_], [])
@runTime()
def fnReduce(): return reduce(lambda a, x: a + x, map(lambda x: list(x), list_))
@runTime()
def fnNew(): return ['1' * 999, '22' * 999, '333' * 999] * 99

if __name__ == '__main__':
    list_ = ['1' * 999, '22' * 999, '333' * 999] * 99
    g = globals()
    result = list((fn.__name__, fn()) for fn in (g[f] for f in g if f.startswith('fn')))
    result.sort(key=lambda r: r[1], reverse=True)
    for e, r in enumerate(result):
        print(e, r)

出去：

<function fnReduce at 0x02938FA8>
<function fnNew at 0x0293B078>
<function fnList at 0x02938D68>
<function fnTuple at 0x028F7348>
<function fnYield at 0x02938DF8>
<function fnIter at 0x02938CD8>
<function fnJoin at 0x02938E88>
<function fnSumm at 0x02938F18>
0 ('fnNew', 0.0)
1 ('fnJoin', -0.018803834915161133)
2 ('fnYield', -0.04936907768249512)
3 ('fnTuple', -0.061401805877685546)
4 ('fnList', -0.06224835395812988)
5 ('fnIter', -0.07298644065856934)
6 ('fnSumm', -0.8121062469482422)
7 ('fnReduce', -0.8314747619628906)

或者

import pandas as pd
a = ['1', 2, [2, 44, '123', ('qwe')], 2]

df = pd.DataFrame(a, columns=['a'])
a = list(''.join(map(str, df.explode('a')['a'])))