有一个C ++比较,可以从列表列表中获取列表联合:The fastest way to find union of sets
还有其他一些与python相关的问题,但没有一个提出加入名单的最快方法:
从答案中,我发现至少有两种方法可以做到:
>>> from itertools import chain
>>> x = [[1,2,3], [3,4,5], [1,7,8]]
>>> list(set().union(*x))
[1, 2, 3, 4, 5, 7, 8]
>>> list(set(chain(*x)))
[1, 2, 3, 4, 5, 7, 8]
请注意,我之后将该集转换为列表,因为我需要修复列表的顺序以便进一步处理。
经过一些比较后,似乎list(set(chain(*x)))
更稳定,花费的时间更短:
from itertools import chain
import time
import random
# Dry run.
x = [[random.choice(range(10000))
for i in range(10)] for j in range(10)]
list(set().union(*x))
list(set(chain(*x)))
y_time = 0
z_time = 0
for _ in range(1000):
x = [[random.choice(range(10000))
for i in range(10)] for j in range(10)]
start = time.time()
y = list(set().union(*x))
y_time += time.time() - start
#print 'list(set().union(*x)):\t', y_time
start = time.time()
z = list(set(chain(*x)))
z_time += time.time() - start
#print 'list(set(chain(*x))):\t', z_time
assert sorted(y) == sorted(z)
#print
print y_time / 1000.
print z_time / 1000.
[OUT]:
1.39586925507e-05
1.09834671021e-05
取出铸造集的变量列表:
y_time = 0
z_time = 0
for _ in range(1000):
x = [[random.choice(range(10000))
for i in range(10)] for j in range(10)]
start = time.time()
y = set().union(*x)
y_time += time.time() - start
start = time.time()
z = set(chain(*x))
z_time += time.time() - start
assert sorted(y) == sorted(z)
print y_time / 1000.
print z_time / 1000.
[OUT]:
1.22241973877e-05
1.02684497833e-05
当我尝试打印中间计时(没有列表转换)时,这是完整输出:http://pastebin.com/raw/y3i6dXZ8
为什么list(set(chain(*x)))
花费的时间少于list(set().union(*x))
?
是否有其他方法可以实现相同的列表联合?使用numpy
或pandas
或sframe
或其他什么? 替代方案更快吗?
答案 0 :(得分:7)
最快的取决于func | x | time
unique_concatenate | many_uniques | 0.863
empty_set_union | many_uniques | 1.191
short_set_union_rest | many_uniques | 1.192
long_set_union_rest | many_uniques | 1.194
set_chain | many_uniques | 1.224
func | x | time
long_set_union_rest | many_duplicates | 0.958
short_set_union_rest | many_duplicates | 0.969
empty_set_union | many_duplicates | 0.971
set_chain | many_duplicates | 1.128
unique_concatenate | many_duplicates | 2.411
func | x | time
empty_set_union | many_small_lists | 1.023
long_set_union_rest | many_small_lists | 1.028
set_chain | many_small_lists | 1.032
short_set_union_rest | many_small_lists | 1.036
unique_concatenate | many_small_lists | 1.351
func | x | time
long_set_union_rest | few_large_lists | 0.791
empty_set_union | few_large_lists | 0.813
unique_concatenate | few_large_lists | 0.814
set_chain | few_large_lists | 0.829
short_set_union_rest | few_large_lists | 0.849
的性质 - 无论是长列表还是短列表,有多个子列表或少数子列表,子列表是长还是短,以及是否有很多重复或者很少重复。
以下是比较一些替代方案的一些时间结果。有很多可能性,这绝不是一个完整的分析,但也许这将为您提供一个研究您的用例的框架。
from __future__ import print_function
import random
import timeit
from itertools import chain
import numpy as np
def unique_concatenate(x):
return np.unique(np.concatenate(x))
def short_set_union_rest(x):
# This assumes x[0] is the shortest list in x
return list(set(x[0]).union(*x[1:]))
def long_set_union_rest(x):
# This assumes x[-1] is the longest list in x
return list(set(x[-1]).union(*x[1:]))
def empty_set_union(x):
return list(set().union(*x))
def set_chain(x):
return list(set(chain(*x)))
big_range = list(range(10**7))
small_range = list(range(10**5))
many_uniques = [[random.choice(big_range) for i in range(j)]
for j in range(10, 10000, 10)]
many_duplicates = [[random.choice(small_range) for i in range(j)]
for j in range(10, 10000, 10)]
many_small_lists = [[random.choice(big_range) for i in range(10)]
for j in range(10, 10000, 10)]
few_large_lists = [[random.choice(big_range) for i in range(1000)]
for j in range(10, 100, 10)]
if __name__=='__main__':
for x, n in [('many_uniques', 1), ('many_duplicates', 4),
('many_small_lists', 800), ('few_large_lists', 800)]:
timing = dict()
for func in [
'unique_concatenate', 'short_set_union_rest', 'long_set_union_rest',
'empty_set_union', 'set_chain']:
timing[func, x] = timeit.timeit(
'{}({})'.format(func, x), number=n,
setup='from __main__ import {}, {}'.format(func, x))
print('{:20} | {:20} | {}'.format('func', 'x', 'time'))
for key, t in sorted(timing.items(), key=lambda item: item[1]):
func, x = key
print('{:20} | {:20} | {:.3f}'.format(func, x, t))
print(end='\n')
请务必在您自己的计算机上运行timeit基准测试,因为结果可能会有所不同。
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