将清单大致等份的最佳方法是什么?例如，如果列表有7个元素，并将其分为2部分，我们希望其中一部分有3个元素，而另一部分应该有4个元素。
我正在寻找类似even_split(L, n)的东西，它将L分解为n部分。
def chunks(L, n):
""" Yield successive n-sized chunks from L.
"""
for i in range(0, len(L), n):
yield L[i:i+n]
上面的代码给出了3个块，而不是3个块。我可以简单地转置(遍历这个，取每列的第一个元素，称之为第一部分，然后取第二个元素，把它放在第二部分，等等)，但这破坏了项目的顺序。
当前回答
只要你不想要像连续块这样愚蠢的东西:
>>> def chunkify(lst,n):
... return [lst[i::n] for i in xrange(n)]
...
>>> chunkify(range(13), 3)
[[0, 3, 6, 9, 12], [1, 4, 7, 10], [2, 5, 8, 11]]
其他回答
另一个简单可读的chunker的尝试。
def chunk(iterable, count): # returns a *generator* that divides `iterable` into `count` of contiguous chunks of similar size
assert count >= 1
return (iterable[int(_*len(iterable)/count+0.5):int((_+1)*len(iterable)/count+0.5)] for _ in range(count))
print("Chunk count: ", len(list( chunk(range(105),10))))
print("Chunks: ", list( chunk(range(105),10)))
print("Chunks: ", list(map(list,chunk(range(105),10))))
print("Chunk lengths:", list(map(len, chunk(range(105),10))))
print("Testing...")
for iterable_length in range(100):
for chunk_count in range(1,100):
chunks = list(chunk(range(iterable_length),chunk_count))
assert chunk_count == len(chunks)
assert iterable_length == sum(map(len,chunks))
assert all(map(lambda _:abs(len(_)-iterable_length/chunk_count)<=1,chunks))
print("Okay")
输出:
Chunk count: 10
Chunks: [range(0, 11), range(11, 21), range(21, 32), range(32, 42), range(42, 53), range(53, 63), range(63, 74), range(74, 84), range(84, 95), range(95, 105)]
Chunks: [[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10], [11, 12, 13, 14, 15, 16, 17, 18, 19, 20], [21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31], [32, 33, 34, 35, 36, 37, 38, 39, 40, 41], [42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52], [53, 54, 55, 56, 57, 58, 59, 60, 61, 62], [63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73], [74, 75, 76, 77, 78, 79, 80, 81, 82, 83], [84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94], [95, 96, 97, 98, 99, 100, 101, 102, 103, 104]]
Chunk lengths: [11, 10, 11, 10, 11, 10, 11, 10, 11, 10]
Testing...
Okay
你还可以用:
split=lambda x,n: x if not x else [x[:n]]+[split([] if not -(len(x)-n) else x[-(len(x)-n):],n)][0]
split([1,2,3,4,5,6,7,8,9],2)
[[1, 2], [3, 4], [5, 6], [7, 8], [9]]
def chunkify(target_list, chunk_size):
return [target_list[i:i+chunk_size] for i in range(0, len(target_list), chunk_size)]
>>> l = [5432, 432, 67, "fdas", True, True, False, (4324,131), 876, "ofsa", 8, 909, b'765']
>>> print(chunkify(l, 3))
>>> [[5432, 432, 67], ['fdas', True, True], [False, (4324, 131), 876], ['ofsa', 8, 909], [b'765']]
由于舍入错误，此代码被破坏。不要使用它!!
assert len(chunkIt([1,2,3], 10)) == 10 # fails
这里有一个可行的方法:
def chunkIt(seq, num):
avg = len(seq) / float(num)
out = []
last = 0.0
while last < len(seq):
out.append(seq[int(last):int(last + avg)])
last += avg
return out
测试:
>>> chunkIt(range(10), 3)
[[0, 1, 2], [3, 4, 5], [6, 7, 8, 9]]
>>> chunkIt(range(11), 3)
[[0, 1, 2], [3, 4, 5, 6], [7, 8, 9, 10]]
>>> chunkIt(range(12), 3)
[[0, 1, 2, 3], [4, 5, 6, 7], [8, 9, 10, 11]]
将代码更改为产生n个块，而不是n个块:
def chunks(l, n):
""" Yield n successive chunks from l.
"""
newn = int(len(l) / n)
for i in xrange(0, n-1):
yield l[i*newn:i*newn+newn]
yield l[n*newn-newn:]
l = range(56)
three_chunks = chunks (l, 3)
print three_chunks.next()
print three_chunks.next()
print three_chunks.next()
这使:
[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17]
[18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35]
[36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55]
这将把额外的元素分配给最后一组，这并不完美，但在你的“大致N相等部分”的规范范围内:-)我的意思是，56个元素作为(19,19,18)会更好，而这给出(18,18,20)。
你可以用下面的代码得到更均衡的输出:
#!/usr/bin/python
def chunks(l, n):
""" Yield n successive chunks from l.
"""
newn = int(1.0 * len(l) / n + 0.5)
for i in xrange(0, n-1):
yield l[i*newn:i*newn+newn]
yield l[n*newn-newn:]
l = range(56)
three_chunks = chunks (l, 3)
print three_chunks.next()
print three_chunks.next()
print three_chunks.next()
输出:
[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18]
[19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37]
[38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55]
