我有一个Python脚本，它把一个整数列表作为输入，我需要一次处理四个整数。不幸的是，我无法控制输入，否则我将它作为一个四元素元组列表传入。目前，我以这种方式迭代它:
for i in range(0, len(ints), 4):
# dummy op for example code
foo += ints[i] * ints[i + 1] + ints[i + 2] * ints[i + 3]
不过，它看起来很像“C-think”，这让我怀疑有一种更python的方式来处理这种情况。该列表在迭代后被丢弃，因此不需要保留。也许这样会更好?
while ints:
foo += ints[0] * ints[1] + ints[2] * ints[3]
ints[0:4] = []
不过，感觉还是不太对。: - /
相关问题:在Python中如何将列表分割成大小均匀的块?
当前回答
如果列表很大，执行效率最高的方法是使用生成器:
def get_chunk(iterable, chunk_size):
result = []
for item in iterable:
result.append(item)
if len(result) == chunk_size:
yield tuple(result)
result = []
if len(result) > 0:
yield tuple(result)
for x in get_chunk([1,2,3,4,5,6,7,8,9,10], 3):
print x
(1, 2, 3)
(4, 5, 6)
(7, 8, 9)
(10,)
其他回答
修改自Python的itertools文档中的Recipes部分:
from itertools import zip_longest
def grouper(iterable, n, fillvalue=None):
args = [iter(iterable)] * n
return zip_longest(*args, fillvalue=fillvalue)
例子
grouper('ABCDEFG', 3, 'x') # --> 'ABC' 'DEF' 'Gxx'
注意:在Python 2上使用izip_longest而不是zip_longest。
使用小的函数和东西真的不吸引我;我更喜欢使用切片:
data = [...]
chunk_size = 10000 # or whatever
chunks = [data[i:i+chunk_size] for i in xrange(0,len(data),chunk_size)]
for chunk in chunks:
...
如果列表很大，执行效率最高的方法是使用生成器:
def get_chunk(iterable, chunk_size):
result = []
for item in iterable:
result.append(item)
if len(result) == chunk_size:
yield tuple(result)
result = []
if len(result) > 0:
yield tuple(result)
for x in get_chunk([1,2,3,4,5,6,7,8,9,10], 3):
print x
(1, 2, 3)
(4, 5, 6)
(7, 8, 9)
(10,)
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
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.
