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
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']]
其他回答
这是另一种变体，它将“剩余”元素均匀地分布在所有块中，一次一个，直到一个都不剩。在这个实现中，较大的块出现在流程的开头。
def chunks(l, k):
""" Yield k successive chunks from l."""
if k < 1:
yield []
raise StopIteration
n = len(l)
avg = n/k
remainders = n % k
start, end = 0, avg
while start < n:
if remainders > 0:
end = end + 1
remainders = remainders - 1
yield l[start:end]
start, end = end, end+avg
例如，从14个元素的列表中生成4个块:
>>> list(chunks(range(14), 4))
[[0, 1, 2, 3], [4, 5, 6, 7], [8, 9, 10], [11, 12, 13]]
>>> map(len, list(chunks(range(14), 4)))
[4, 4, 3, 3]
在这种情况下，我自己编写了代码:
def chunk_ports(port_start, port_end, portions):
if port_end < port_start:
return None
total = port_end - port_start + 1
fractions = int(math.floor(float(total) / portions))
results = []
# No enough to chuck.
if fractions < 1:
return None
# Reverse, so any additional items would be in the first range.
_e = port_end
for i in range(portions, 0, -1):
print "i", i
if i == 1:
_s = port_start
else:
_s = _e - fractions + 1
results.append((_s, _e))
_e = _s - 1
results.reverse()
return results
Divide_ports(1,10,9)将返回
[(1, 2), (3, 3), (4, 4), (5, 5), (6, 6), (7, 7), (8, 8), (9, 9), (10, 10)]
这里有一个生成器，可以处理任何正(整数)数量的块。如果块的数量大于输入列表的长度，一些块将为空。该算法在短块和长块之间交替，而不是将它们分开。
我还包含了一些用于测试ragged_chunks函数的代码。
''' Split a list into "ragged" chunks
The size of each chunk is either the floor or ceiling of len(seq) / chunks
chunks can be > len(seq), in which case there will be empty chunks
Written by PM 2Ring 2017.03.30
'''
def ragged_chunks(seq, chunks):
size = len(seq)
start = 0
for i in range(1, chunks + 1):
stop = i * size // chunks
yield seq[start:stop]
start = stop
# test
def test_ragged_chunks(maxsize):
for size in range(0, maxsize):
seq = list(range(size))
for chunks in range(1, size + 1):
minwidth = size // chunks
#ceiling division
maxwidth = -(-size // chunks)
a = list(ragged_chunks(seq, chunks))
sizes = [len(u) for u in a]
deltas = all(minwidth <= u <= maxwidth for u in sizes)
assert all((sum(a, []) == seq, sum(sizes) == size, deltas))
return True
if test_ragged_chunks(100):
print('ok')
我们可以通过将乘法导出到range调用中来稍微提高效率，但我认为以前的版本更易于阅读(和dry)。
def ragged_chunks(seq, chunks):
size = len(seq)
start = 0
for i in range(size, size * chunks + 1, size):
stop = i // chunks
yield seq[start:stop]
start = stop
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]]
1>
import numpy as np
data # your array
total_length = len(data)
separate = 10
sub_array_size = total_length // separate
safe_separate = sub_array_size * separate
splited_lists = np.split(np.array(data[:safe_separate]), separate)
splited_lists[separate - 1] = np.concatenate(splited_lists[separate - 1],
np.array(data[safe_separate:total_length]))
splited_lists # your output
2>
splited_lists = np.array_split(np.array(data), separate)
