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
为什么不使用列表理解
l = [1 , 2, 3, 4, 5, 6, 7, 8, 9, 10, 11]
n = 4
filler = 0
fills = len(l) % n
chunks = ((l + [filler] * fills)[x * n:x * n + n] for x in range(int((len(l) + n - 1)/n)))
print(chunks)
[[1, 2, 3, 4], [5, 6, 7, 8], [9, 10, 11, 0]]
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)
制作itertools很容易。Groupby工作为您获得一个iterables的iterable，而不创建任何临时列表:
groupby(iterable, (lambda x,y: (lambda z: x.next()/y))(count(),100))
不要被嵌套lambda吓跑，外部lambda只运行一次，将count()生成器和常数100放入内部lambda的作用域。
我用它来发送行块到mysql。
for k,v in groupby(bigdata, (lambda x,y: (lambda z: x.next()/y))(count(),100))):
cursor.executemany(sql, v)
你可以使用函数库中的partition或chunks函数:
from funcy import partition
for a, b, c, d in partition(4, ints):
foo += a * b * c * d
这些函数还有迭代器版本ipartition和ichunks，在这种情况下更有效。
您还可以查看它们的实现。
这个答案拆分了一个字符串列表，f.ex。达到符合pep8线长的要求:
def split(what, target_length=79):
'''splits list of strings into sublists, each
having string length at most 79'''
out = [[]]
while what:
if len("', '".join(out[-1])) + len(what[0]) < target_length:
out[-1].append(what.pop(0))
else:
if not out[-1]: # string longer than target_length
out[-1] = [what.pop(0)]
out.append([])
return out
使用
>>> split(['deferred_income', 'long_term_incentive', 'restricted_stock_deferred', 'shared_receipt_with_poi', 'loan_advances', 'from_messages', 'other', 'director_fees', 'bonus', 'total_stock_value', 'from_poi_to_this_person', 'from_this_person_to_poi', 'restricted_stock', 'salary', 'total_payments', 'exercised_stock_options'], 75)
[['deferred_income', 'long_term_incentive', 'restricted_stock_deferred'], ['shared_receipt_with_poi', 'loan_advances', 'from_messages', 'other'], ['director_fees', 'bonus', 'total_stock_value', 'from_poi_to_this_person'], ['from_this_person_to_poi', 'restricted_stock', 'salary', 'total_payments'], ['exercised_stock_options']]
