还有另一个答案，它的优点是:

1)容易理解 2)适用于任何可迭代对象，而不仅仅是序列(上面的一些答案会阻塞文件句柄) 3)不立即将数据块加载到内存 4)不会在内存中生成对同一迭代器的块长的引用列表 5)在列表的末尾没有填充填充值

话虽如此，我还没有计算它的时间，所以它可能比一些更聪明的方法慢，而且考虑到用例，一些优势可能是无关紧要的。

def chunkiter(iterable, size):
  def inneriter(first, iterator, size):
    yield first
    for _ in xrange(size - 1): 
      yield iterator.next()
  it = iter(iterable)
  while True:
    yield inneriter(it.next(), it, size)

In [2]: i = chunkiter('abcdefgh', 3)
In [3]: for ii in i:                                                
          for c in ii:
            print c,
          print ''
        ...:     
        a b c 
        d e f 
        g h 

Update: A couple of drawbacks due to the fact the inner and outer loops are pulling values from the same iterator: 1) continue doesn't work as expected in the outer loop - it just continues on to the next item rather than skipping a chunk. However, this doesn't seem like a problem as there's nothing to test in the outer loop. 2) break doesn't work as expected in the inner loop - control will wind up in the inner loop again with the next item in the iterator. To skip whole chunks, either wrap the inner iterator (ii above) in a tuple, e.g. for c in tuple(ii), or set a flag and exhaust the iterator.

似乎没有一个漂亮的方法来做到这一点。下面是一个有很多方法的页面，包括:

def split_seq(seq, size):
    newseq = []
    splitsize = 1.0/size*len(seq)
    for i in range(size):
        newseq.append(seq[int(round(i*splitsize)):int(round((i+1)*splitsize))])
    return newseq

在你的第二种方法中，我将通过这样做进入下一组4人:

ints = ints[4:]

然而，我还没有做过任何绩效评估，所以我不知道哪种方法更有效。

话虽如此，我通常会选择第一种方法。这并不漂亮，但这通常是与外部世界接触的结果。

关于J.F. Sebastian给出的解决方案:

def chunker(iterable, chunksize):
    return zip(*[iter(iterable)]*chunksize)

它很聪明，但有一个缺点——总是返回元组。如何获得字符串代替? 当然，你可以写“.join(chunker(…))”，但无论如何都要构造临时元组。

你可以通过编写自己的zip来摆脱临时元组，就像这样:

class IteratorExhausted(Exception):
    pass

def translate_StopIteration(iterable, to=IteratorExhausted):
    for i in iterable:
        yield i
    raise to # StopIteration would get ignored because this is generator,
             # but custom exception can leave the generator.

def custom_zip(*iterables, reductor=tuple):
    iterators = tuple(map(translate_StopIteration, iterables))
    while True:
        try:
            yield reductor(next(i) for i in iterators)
        except IteratorExhausted: # when any of iterators get exhausted.
            break

Then

def chunker(data, size, reductor=tuple):
    return custom_zip(*[iter(data)]*size, reductor=reductor)

使用示例:

>>> for i in chunker('12345', 2):
...     print(repr(i))
...
('1', '2')
('3', '4')
>>> for i in chunker('12345', 2, ''.join):
...     print(repr(i))
...
'12'
'34'

more-itertools包有一个分块方法，它可以做到这一点:

import more_itertools
for s in more_itertools.chunked(range(9), 4):
    print(s)

打印

[0, 1, 2, 3]
[4, 5, 6, 7]
[8]

Chunked返回列表中的项。如果你更喜欢迭代对象，可以使用ichunked。

我从来不想填充我的块，所以这个要求是必要的。我发现在任何可迭代对象上工作的能力也是必需的。鉴于此，我决定扩展公认的答案，https://stackoverflow.com/a/434411/1074659。

如果由于需要比较和筛选填充值而不需要填充，则这种方法的性能会受到轻微的影响。然而，对于大块大小，这个实用程序是非常高性能的。

#!/usr/bin/env python3
from itertools import zip_longest


_UNDEFINED = object()


def chunker(iterable, chunksize, fillvalue=_UNDEFINED):
    """
    Collect data into chunks and optionally pad it.

    Performance worsens as `chunksize` approaches 1.

    Inspired by:
        https://docs.python.org/3/library/itertools.html#itertools-recipes

    """
    args = [iter(iterable)] * chunksize
    chunks = zip_longest(*args, fillvalue=fillvalue)
    yield from (
        filter(lambda val: val is not _UNDEFINED, chunk)
        if chunk[-1] is _UNDEFINED
        else chunk
        for chunk in chunks
    ) if fillvalue is _UNDEFINED else chunks