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
下面是我的go works on lists,iter和range…懒洋洋地:
def chunker(it,size):
rv = []
for i,el in enumerate(it,1) :
rv.append(el)
if i % size == 0 :
yield rv
rv = []
if rv : yield rv
几乎变成了一句俏皮话;(
In [95]: list(chunker(range(9),2) )
Out[95]: [[0, 1], [2, 3], [4, 5], [6, 7], [8]]
In [96]: list(chunker([1,2,3,4,5],2) )
Out[96]: [[1, 2], [3, 4], [5]]
In [97]: list(chunker(iter(range(9)),2) )
Out[97]: [[0, 1], [2, 3], [4, 5], [6, 7], [8]]
In [98]: list(chunker(range(9),25) )
Out[98]: [[0, 1, 2, 3, 4, 5, 6, 7, 8]]
In [99]: list(chunker(range(9),1) )
Out[99]: [[0], [1], [2], [3], [4], [5], [6], [7], [8]]
In [101]: %timeit list(chunker(range(101),2) )
11.3 µs ± 68.2 ns per loop (mean ± std. dev. of 7 runs, 100000 loops each)
其他回答
from itertools import izip_longest
def chunker(iterable, chunksize, filler):
return izip_longest(*[iter(iterable)]*chunksize, fillvalue=filler)
def chunker(seq, size):
return (seq[pos:pos + size] for pos in range(0, len(seq), size))
适用于任何序列:
text = "I am a very, very helpful text"
for group in chunker(text, 7):
print(repr(group),)
# 'I am a ' 'very, v' 'ery hel' 'pful te' 'xt'
print('|'.join(chunker(text, 10)))
# I am a ver|y, very he|lpful text
animals = ['cat', 'dog', 'rabbit', 'duck', 'bird', 'cow', 'gnu', 'fish']
for group in chunker(animals, 3):
print(group)
# ['cat', 'dog', 'rabbit']
# ['duck', 'bird', 'cow']
# ['gnu', 'fish']
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'
这里非常python化(也可以内联split_groups函数体)
import itertools
def split_groups(iter_in, group_size):
return ((x for _, x in item) for _, item in itertools.groupby(enumerate(iter_in), key=lambda x: x[0] // group_size))
for x, y, z, w in split_groups(range(16), 4):
foo += x * y + z * w
我喜欢这种方法。它感觉简单而不神奇，支持所有可迭代类型，并且不需要导入。
def chunk_iter(iterable, chunk_size):
it = iter(iterable)
while True:
chunk = tuple(next(it) for _ in range(chunk_size))
if not chunk:
break
yield chunk
