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

在我的特殊情况下,我需要填充项目,以重复最后一个元素,直到它达到大小,所以我改变了这个答案,以适应我的需要。

大小为4的输入输出示例:

Input = [1,2,3,4,5,6,7,8]
Output= [[1,2,3,4], [5,6,7,8]]

Input = [[1,2,3,4,5,6,7]]
Output= [[1,2,3,4], [5,6,7,7]]

Input = [1,2,3,4,5]
Output= [[1,2,3,4], [5,5,5,5]]
def chunker(seq, size):
    res = []
    for el in seq:
        res.append(el)
        if len(res) == size:
            yield res
            res = []
    if res:
        res = res + (size - len(res)) * [res[-1]] 
        yield res

其他回答

在我的特殊情况下,我需要填充项目,以重复最后一个元素,直到它达到大小,所以我改变了这个答案,以适应我的需要。

大小为4的输入输出示例:

Input = [1,2,3,4,5,6,7,8]
Output= [[1,2,3,4], [5,6,7,8]]

Input = [[1,2,3,4,5,6,7]]
Output= [[1,2,3,4], [5,6,7,7]]

Input = [1,2,3,4,5]
Output= [[1,2,3,4], [5,5,5,5]]
def chunker(seq, size):
    res = []
    for el in seq:
        res.append(el)
        if len(res) == size:
            yield res
            res = []
    if res:
        res = res + (size - len(res)) * [res[-1]] 
        yield res

首先,我将它设计为将字符串拆分为子字符串以解析包含十六进制的字符串。 今天我把它变成复杂的,但仍然简单的生成器。

def chunker(iterable, size, reductor, condition):
    it = iter(iterable)
    def chunk_generator():
        return (next(it) for _ in range(size))
    chunk = reductor(chunk_generator())
    while condition(chunk):
        yield chunk
        chunk = reductor(chunk_generator())

参数:

明显的

Iterable是任何包含/生成/迭代输入数据的Iterable /迭代器/生成器, 当然,大小是你想要得到的块的大小,

更有趣的

reductor is a callable, which receives generator iterating over content of chunk. I'd expect it to return sequence or string, but I don't demand that. You can pass as this argument for example list, tuple, set, frozenset, or anything fancier. I'd pass this function, returning string (provided that iterable contains / generates / iterates over strings): def concatenate(iterable): return ''.join(iterable) Note that reductor can cause closing generator by raising exception. condition is a callable which receives anything what reductor returned. It decides to approve & yield it (by returning anything evaluating to True), or to decline it & finish generator's work (by returning anything other or raising exception). When number of elements in iterable is not divisible by size, when it gets exhausted, reductor will receive generator generating less elements than size. Let's call these elements lasts elements. I invited two functions to pass as this argument: lambda x:x - the lasts elements will be yielded. lambda x: len(x)==<size> - the lasts elements will be rejected. replace <size> using number equal to size

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.

另一种方法是使用双参数形式的iter:

from itertools import islice

def group(it, size):
    it = iter(it)
    return iter(lambda: tuple(islice(it, size)), ())

这可以很容易地适应使用填充(这类似于Markus Jarderot的答案):

from itertools import islice, chain, repeat

def group_pad(it, size, pad=None):
    it = chain(iter(it), repeat(pad))
    return iter(lambda: tuple(islice(it, size)), (pad,) * size)

这些甚至可以组合为可选的填充:

_no_pad = object()
def group(it, size, pad=_no_pad):
    if pad == _no_pad:
        it = iter(it)
        sentinel = ()
    else:
        it = chain(iter(it), repeat(pad))
        sentinel = (pad,) * size
    return iter(lambda: tuple(islice(it, size)), sentinel)

类似于其他提案,但不完全相同,我喜欢这样做,因为它简单易读:

it = iter([1, 2, 3, 4, 5, 6, 7, 8, 9])
for chunk in zip(it, it, it, it):
    print chunk

>>> (1, 2, 3, 4)
>>> (5, 6, 7, 8)

这样你就不会得到最后一部分。如果你想获取(9,None, None, None)作为最后一个块,只需使用itertools中的izip_longest。