探索的方法
1.生成器方法
next(i for i,v in enumerate(test_strings) if 'other' in v)
2。列表理解方法
[i for i,v in enumerate(test_strings) if 'other' in v]
3.使用带有生成器的索引(@HeapOverflow 建议)
test_strings.index(next(v for v in test_strings if 'other' in v))
4.带有生成器的正则表达式
re_pattern = re.compile('.*other.*')
next(test_strings.index(x) for x in test_strings if re_pattern.search(x))
结论
索引方法的时间最快(@HeapOverflow 在 cmets 中建议的方法)。
测试代码
Using Perfplot 使用 timeit
import random
import string
import re
import perfplot
def random_string(N):
return ''.join(random.choice(string.ascii_uppercase + string.digits) for _ in range(N))
def create_strings(length):
M = length // 2
random_strings = [random_string(5) for _ in range(length)]
front = ['...other...'] + random_strings
middle = random_strings[:M] + ['...other...'] + random_strings[M:]
end_ = random_strings + ['...other...']
return front, middle, end_
def search_list_comprehension(test_strings):
return [i for i,v in enumerate(test_strings) if 'other' in v][0]
def search_genearator(test_strings):
return next(i for i,v in enumerate(test_strings) if 'other' in v)
def search_index(test_strings):
return test_strings.index(next(v for v in test_strings if 'other' in v))
def search_regex(test_strings):
re_pattern = re.compile('.*other.*')
return next(test_strings.index(x) for x in test_strings if re_pattern.search(x))
# Each benchmark is run with the '..other...' placed in the front, middle and end of a random list of strings.
out = perfplot.bench(
setup=lambda n: create_strings(n), # create front, middle, end strings of length n
kernels=[
lambda a: [search_list_comprehension(x) for x in a],
lambda a: [search_genearator(x) for x in a],
lambda a: [search_index(x) for x in a],
lambda a: [search_regex(x) for x in a],
],
labels=["list_comp", "generator", "index", "regex"],
n_range=[2 ** k for k in range(15)],
xlabel="lenght list",
# More optional arguments with their default values:
# title=None,
# logx="auto", # set to True or False to force scaling
# logy="auto",
# equality_check=numpy.allclose, # set to None to disable "correctness" assertion
# automatic_order=True,
# colors=None,
# target_time_per_measurement=1.0,
# time_unit="s", # set to one of ("auto", "s", "ms", "us", or "ns") to force plot units
# relative_to=1, # plot the timings relative to one of the measurements
# flops=lambda n: 3*n, # FLOPS plots
)
out.show()
print(out)
结果
length list regex list_comp generator index
1.0 10199.0 3699.0 4199.0 3899.0
2.0 11399.0 3899.0 4300.0 4199.0
4.0 13099.0 4300.0 4599.0 4300.0
8.0 16300.0 5299.0 5099.0 4800.0
16.0 22399.0 7199.0 5999.0 5699.0
32.0 34900.0 10799.0 7799.0 7499.0
64.0 59300.0 18599.0 11799.0 11200.0
128.0 108599.0 33899.0 19299.0 18500.0
256.0 205899.0 64699.0 34699.0 33099.0
512.0 403000.0 138199.0 69099.0 62499.0
1024.0 798900.0 285600.0 142599.0 120900.0
2048.0 1599999.0 582999.0 288699.0 239299.0
4096.0 3191899.0 1179200.0 583599.0 478899.0
8192.0 6332699.0 2356400.0 1176399.0 953500.0
16384.0 12779600.0 4731100.0 2339099.0 1897100.0