如何将任意长度的列表拆分为大小相等的块?
请参阅如果数据结果将直接用于循环,并且不需要存储,则如何以块形式遍历列表。
对于字符串输入的同一问题,请参见每n个字符拆分字符串?。相同的技术通常适用,但也有一些变化。
如何将任意长度的列表拆分为大小相等的块?
请参阅如果数据结果将直接用于循环,并且不需要存储,则如何以块形式遍历列表。
对于字符串输入的同一问题,请参见每n个字符拆分字符串?。相同的技术通常适用,但也有一些变化。
当前回答
任何可迭代的通用分块器,使用户可以选择如何在结尾处处理部分分块。
在Python 3上测试。
分块.py
from enum import Enum
class PartialChunkOptions(Enum):
INCLUDE = 0
EXCLUDE = 1
PAD = 2
ERROR = 3
class PartialChunkException(Exception):
pass
def chunker(iterable, n, on_partial=PartialChunkOptions.INCLUDE, pad=None):
"""
A chunker yielding n-element lists from an iterable, with various options
about what to do about a partial chunk at the end.
on_partial=PartialChunkOptions.INCLUDE (the default):
include the partial chunk as a short (<n) element list
on_partial=PartialChunkOptions.EXCLUDE
do not include the partial chunk
on_partial=PartialChunkOptions.PAD
pad to an n-element list
(also pass pad=<pad_value>, default None)
on_partial=PartialChunkOptions.ERROR
raise a RuntimeError if a partial chunk is encountered
"""
on_partial = PartialChunkOptions(on_partial)
iterator = iter(iterable)
while True:
vals = []
for i in range(n):
try:
vals.append(next(iterator))
except StopIteration:
if vals:
if on_partial == PartialChunkOptions.INCLUDE:
yield vals
elif on_partial == PartialChunkOptions.EXCLUDE:
pass
elif on_partial == PartialChunkOptions.PAD:
yield vals + [pad] * (n - len(vals))
elif on_partial == PartialChunkOptions.ERROR:
raise PartialChunkException
return
return
yield vals
测试.py
import chunker
chunk_size = 3
for it in (range(100, 107),
range(100, 109)):
print("\nITERABLE TO CHUNK: {}".format(it))
print("CHUNK SIZE: {}".format(chunk_size))
for option in chunker.PartialChunkOptions.__members__.values():
print("\noption {} used".format(option))
try:
for chunk in chunker.chunker(it, chunk_size, on_partial=option):
print(chunk)
except chunker.PartialChunkException:
print("PartialChunkException was raised")
print("")
test.py的输出
ITERABLE TO CHUNK: range(100, 107)
CHUNK SIZE: 3
option PartialChunkOptions.INCLUDE used
[100, 101, 102]
[103, 104, 105]
[106]
option PartialChunkOptions.EXCLUDE used
[100, 101, 102]
[103, 104, 105]
option PartialChunkOptions.PAD used
[100, 101, 102]
[103, 104, 105]
[106, None, None]
option PartialChunkOptions.ERROR used
[100, 101, 102]
[103, 104, 105]
PartialChunkException was raised
ITERABLE TO CHUNK: range(100, 109)
CHUNK SIZE: 3
option PartialChunkOptions.INCLUDE used
[100, 101, 102]
[103, 104, 105]
[106, 107, 108]
option PartialChunkOptions.EXCLUDE used
[100, 101, 102]
[103, 104, 105]
[106, 107, 108]
option PartialChunkOptions.PAD used
[100, 101, 102]
[103, 104, 105]
[106, 107, 108]
option PartialChunkOptions.ERROR used
[100, 101, 102]
[103, 104, 105]
[106, 107, 108]
其他回答
我创建了这两个漂亮的一行程序,它们既高效又懒惰,输入和输出都是可迭代的,而且它们不依赖于任何模块:
首先,一行是完全懒惰的,这意味着它返回迭代器生成迭代器(即,生成的每个块都是迭代器对块的元素进行迭代),如果块非常大或元素一个接一个地缓慢生成,并且在生成时应立即可用,则此版本适用于这种情况:
在线试用!
chunk_iters = lambda it, n: ((e for i, g in enumerate(((f,), cit)) for j, e in zip(range((1, n - 1)[i]), g)) for cit in (iter(it),) for f in cit)
第二行返回生成列表的迭代器。一旦整个块的元素通过输入迭代器变得可用,或者到达最后一个块的最后一个元素,就会生成每个列表。如果输入元素快速生成或立即全部可用,则应使用此版本。应该使用其他明智的第一个更懒惰的一行代码版本。
在线试用!
chunk_lists = lambda it, n: (l for l in ([],) for i, g in enumerate((it, ((),))) for e in g for l in (l[:len(l) % n] + [e][:1 - i],) if (len(l) % n == 0) != i)
此外,我还提供了第一个chunk_iter的多行版本一行,它返回迭代器生成另一个迭代器(遍历每个chunk的元素):
在线试用!
def chunk_iters(it, n):
cit = iter(it)
def one_chunk(f):
yield f
for i, e in zip(range(n - 1), cit):
yield e
for f in cit:
yield one_chunk(f)
这里有一个使用itertools.groupby的想法:
def chunks(l, n):
c = itertools.count()
return (it for _, it in itertools.groupby(l, lambda x: next(c)//n))
这将返回一个生成器。如果需要列表列表,只需将最后一行替换为
return [list(it) for _, it in itertools.groupby(l, lambda x: next(c)//n)]
返回列表列表示例:
>>> chunks('abcdefghij', 4)
[['a', 'b', 'c', 'd'], ['e', 'f', 'g', 'h'], ['i', 'j']]
(因此,是的,这会受到“矮子问题”的影响,在特定情况下,这可能是问题,也可能不是问题。)
此时,我认为我们需要强制性的匿名递归函数。
Y = lambda f: (lambda x: x(x))(lambda y: f(lambda *args: y(y)(*args)))
chunks = Y(lambda f: lambda n: [n[0][:n[1]]] + f((n[0][n[1]:], n[1])) if len(n[0]) > 0 else [])
任何可迭代的通用分块器,使用户可以选择如何在结尾处处理部分分块。
在Python 3上测试。
分块.py
from enum import Enum
class PartialChunkOptions(Enum):
INCLUDE = 0
EXCLUDE = 1
PAD = 2
ERROR = 3
class PartialChunkException(Exception):
pass
def chunker(iterable, n, on_partial=PartialChunkOptions.INCLUDE, pad=None):
"""
A chunker yielding n-element lists from an iterable, with various options
about what to do about a partial chunk at the end.
on_partial=PartialChunkOptions.INCLUDE (the default):
include the partial chunk as a short (<n) element list
on_partial=PartialChunkOptions.EXCLUDE
do not include the partial chunk
on_partial=PartialChunkOptions.PAD
pad to an n-element list
(also pass pad=<pad_value>, default None)
on_partial=PartialChunkOptions.ERROR
raise a RuntimeError if a partial chunk is encountered
"""
on_partial = PartialChunkOptions(on_partial)
iterator = iter(iterable)
while True:
vals = []
for i in range(n):
try:
vals.append(next(iterator))
except StopIteration:
if vals:
if on_partial == PartialChunkOptions.INCLUDE:
yield vals
elif on_partial == PartialChunkOptions.EXCLUDE:
pass
elif on_partial == PartialChunkOptions.PAD:
yield vals + [pad] * (n - len(vals))
elif on_partial == PartialChunkOptions.ERROR:
raise PartialChunkException
return
return
yield vals
测试.py
import chunker
chunk_size = 3
for it in (range(100, 107),
range(100, 109)):
print("\nITERABLE TO CHUNK: {}".format(it))
print("CHUNK SIZE: {}".format(chunk_size))
for option in chunker.PartialChunkOptions.__members__.values():
print("\noption {} used".format(option))
try:
for chunk in chunker.chunker(it, chunk_size, on_partial=option):
print(chunk)
except chunker.PartialChunkException:
print("PartialChunkException was raised")
print("")
test.py的输出
ITERABLE TO CHUNK: range(100, 107)
CHUNK SIZE: 3
option PartialChunkOptions.INCLUDE used
[100, 101, 102]
[103, 104, 105]
[106]
option PartialChunkOptions.EXCLUDE used
[100, 101, 102]
[103, 104, 105]
option PartialChunkOptions.PAD used
[100, 101, 102]
[103, 104, 105]
[106, None, None]
option PartialChunkOptions.ERROR used
[100, 101, 102]
[103, 104, 105]
PartialChunkException was raised
ITERABLE TO CHUNK: range(100, 109)
CHUNK SIZE: 3
option PartialChunkOptions.INCLUDE used
[100, 101, 102]
[103, 104, 105]
[106, 107, 108]
option PartialChunkOptions.EXCLUDE used
[100, 101, 102]
[103, 104, 105]
[106, 107, 108]
option PartialChunkOptions.PAD used
[100, 101, 102]
[103, 104, 105]
[106, 107, 108]
option PartialChunkOptions.ERROR used
[100, 101, 102]
[103, 104, 105]
[106, 107, 108]
我很惊讶没有人想到使用iter的双参数形式:
from itertools import islice
def chunk(it, size):
it = iter(it)
return iter(lambda: tuple(islice(it, size)), ())
演示:
>>> list(chunk(range(14), 3))
[(0, 1, 2), (3, 4, 5), (6, 7, 8), (9, 10, 11), (12, 13)]
这适用于任何可迭代的对象,并延迟生成输出。它返回元组而不是迭代器,但我认为它还是有一定的优雅。它也不会垫;如果您需要填充,上面的一个简单变体就足够了:
from itertools import islice, chain, repeat
def chunk_pad(it, size, padval=None):
it = chain(iter(it), repeat(padval))
return iter(lambda: tuple(islice(it, size)), (padval,) * size)
演示:
>>> list(chunk_pad(range(14), 3))
[(0, 1, 2), (3, 4, 5), (6, 7, 8), (9, 10, 11), (12, 13, None)]
>>> list(chunk_pad(range(14), 3, 'a'))
[(0, 1, 2), (3, 4, 5), (6, 7, 8), (9, 10, 11), (12, 13, 'a')]
与基于izip_longest的解决方案一样,上面的解决方案也始终适用。据我所知,对于可选pad的函数,没有单行或双线itertools配方。通过结合以上两种方法,这一方法非常接近:
_no_padding = object()
def chunk(it, size, padval=_no_padding):
if padval == _no_padding:
it = iter(it)
sentinel = ()
else:
it = chain(iter(it), repeat(padval))
sentinel = (padval,) * size
return iter(lambda: tuple(islice(it, size)), sentinel)
演示:
>>> list(chunk(range(14), 3))
[(0, 1, 2), (3, 4, 5), (6, 7, 8), (9, 10, 11), (12, 13)]
>>> list(chunk(range(14), 3, None))
[(0, 1, 2), (3, 4, 5), (6, 7, 8), (9, 10, 11), (12, 13, None)]
>>> list(chunk(range(14), 3, 'a'))
[(0, 1, 2), (3, 4, 5), (6, 7, 8), (9, 10, 11), (12, 13, 'a')]
我相信这是提议的提供可选填充的最短的分块器。
正如Tomasz Gandor所观察到的,如果两个填充块遇到一长串填充值,它们会意外停止。以下是以合理方式解决该问题的最后一个变体:
_no_padding = object()
def chunk(it, size, padval=_no_padding):
it = iter(it)
chunker = iter(lambda: tuple(islice(it, size)), ())
if padval == _no_padding:
yield from chunker
else:
for ch in chunker:
yield ch if len(ch) == size else ch + (padval,) * (size - len(ch))
演示:
>>> list(chunk([1, 2, (), (), 5], 2))
[(1, 2), ((), ()), (5,)]
>>> list(chunk([1, 2, None, None, 5], 2, None))
[(1, 2), (None, None), (5, None)]