什么是更快的操作，re.match/search 或 str.find？

Question

对于一次性字符串搜索，简单地使用 str.find/rfind 是否比使用 re.match/search 更快？

也就是说，对于给定的字符串 s，我应该使用：

if s.find('lookforme') > -1:
    do something

或

if re.match('lookforme',s):
    do something else

?

Answer 1

使用这个：

if 'lookforme' in s:
    do something

需要先编译正则表达式，这会增加一些开销。无论如何，Python 的普通字符串搜索非常有效。

如果你经常搜索同一个词或者当你做一些更复杂的事情时，那么正则表达式会变得更有用。

Answer 2

问题：使用timeit 最好回答哪个更快。

from timeit import timeit
import re

def find(string, text):
    if string.find(text) > -1:
        pass

def re_find(string, text):
    if re.match(text, string):
        pass

def best_find(string, text):
    if text in string:
       pass

print timeit("find(string, text)", "from __main__ import find; string='lookforme'; text='look'")  
print timeit("re_find(string, text)", "from __main__ import re_find; string='lookforme'; text='look'")  
print timeit("best_find(string, text)", "from __main__ import best_find; string='lookforme'; text='look'")  

输出是：

0.441393852234
2.12302494049
0.251421928406

因此，您不仅应该使用in 运算符，因为它更易于阅读，而且还更快。

Answer 3

如果您一遍又一遍地搜索相同的东西，re.compile 会大大加快正则表达式的速度。但是我通过在比赛前使用“in”来剔除不良案例，从而获得了巨大的加速。轶事，我知道。 〜本

Answer 4

我也遇到了同样的问题。我使用 Jupyter 的 %timeit 来检查：

import re
sent = "a sentence for measuring a find function"
sent_list = sent.split()
print("x in sentence")
%timeit "function" in sent
print("x in token list")
%timeit "function" in sent_list

print("regex search")
%timeit bool(re.match(".*function.*", sent))
print("compiled regex search")
regex = re.compile(".*function.*")
%timeit bool(regex.match(sent))

句子中的 x 每个循环 61.3 ns ± 3 ns（平均值 ± 标准偏差，7 次运行，每次 10000000 次循环）

令牌列表中的 x 93.3 ns ± 1.26 ns 每个循环（平均值 ± 标准偏差。7 次运行，每次 10000000 次循环）

正则表达式搜索 772 ns ± 8.42 ns 每个循环（平均值 ± 标准差。7 次运行，每次 1000000 次循环）

编译的正则表达式搜索每个循环 420 ns ± 7.68 ns（平均值 ± 标准偏差。7 次运行，每次 1000000 次循环）

编译速度很快，但简单的 in 更好。

Answer 5

只是为了完成关于正则表达式编译时间的投票最多的回答问题，这里有一个带有预编译模式的版本：

from timeit import timeit
import re

def find(string, text):
    if string.find(text) > -1:
        pass

def re_find(string, text_re):
    if text_re.match(string):
        pass

def best_find(string, text):
    if text in string:
       pass

print timeit("find(string, text)", "from __main__ import find; string='lookforme'; text='look'")  
print timeit("re_find(string, text_re)", "from __main__ import re_find; string='lookforme'; import re; text_re=re.compile('look')")  
print timeit("best_find(string, text)", "from __main__ import best_find; string='lookforme'; text='look'")

还有我的号码：

0.189274072647
0.239935874939
0.0820939540863

预编译模式提高了数字，但in 仍然更快。

Answer 6

也许有人仍然感兴趣。 给定的答案看起来不错，但只看一个很短的字符串。 事实上，如果您使用长字符串并且您正在寻找的模式大致位于末尾，那么性能会发生变化，有利于正则表达式！

import re

def find(string, text):
    if string.find(text) > -1:
        pass

def re_find(string, text):
    if re.match(text, string):
        pass

def best_find(string, text):
    if text in string:
       pass

very_long_string = 'sasgda;dlaskjgasdlj sadlf;jsaf lkjvasdfa dsadkfldsfhsa svnsa;df adsfkj;ljkasdf asdf;lkjafd sasgda;dlaskjgasdlj sadlf;jsaf lkjvasdfa dsadkfldsfhsa svnsa;df adsfkj;ljkasdf asdf;lkjafd sasgda;dlaskjgasdlj sadlf;jsaf lkjvasdfa dsadkfldsfhsa svnsa;df adsfkj;ljkasdf asdf;lkjafd sasgda;dlaskjgasdlj sadlf;jsaf lkjvasdfa dsadkfldsfhsa svnsa;df adsfkj;ljkasdf asdf;lkjafd sasgda;dlaskjgasdlj sadlf;jsaf lkjvasdfa dsadkfldsfhsa svnsa;df adsfkj;ljkasdf asdf;lkjafd sasgda;dlaskjgasdlj sadlf;jsaf lkjvasdfa dsadkfldsfhsa svnsa;df adsfkj;ljkasdf asdf;lkjafd sasgda;dlaskjgasdlj sadlf;jsaf lkjvasdfa dsadkfldsfhsa svnsa;df adsfkj;ljkasdf asdf;lkjafd sasgda;dlaskjgasdlj sadlf;jsaf lkjvasdfa dsadkfldsfhsa svnsa;df adsfkj;ljkasdf asdf;lkjafd sasgda;dlaskjgasdlj sadlf;jsaf lkjvasdfa dsadkfldsfhsa svnsa;df adsfkj;ljkasdf asdf;lkjafd sasgda;dlaskjgasdlj sadlf;jsaf lkjvasdfa dsadkfldsfhsa svnsa;df adsfkj;ljkasdf asdf;lkjafd sasgda;dlaskjgasdlj sadlf;jsaf lkjvasdfa dsadkfldsfhsa svnsa;df adsfkj;ljkasdf asdf;lkjafd sasgda;dlaskjgasdlj sadlf;jsaf lkjvasdfa dsadkfldsfhsa svnsa;df adsfkj;ljkasdf asdf;lkjafd sasgda;dlaskjgasdlj sadlf;jsaf lkjvasdfa dsadkfldsfhsa svnsa;df adsfkj;ljkasdf asdf;lkjafd sasgda;dlaskjgasdlj sadlf;jsaf lkjvasdfa dsadkfldsfhsa svnsa;df adsfkj;ljkasdf asdf;lkjafd sasgda;dlaskjgasdlj sadlf;jsaf lkjvasdfa dsadkfldsfhsa svnsa;df adsfkj;ljkasdf asdf;lkjafd sasgda;dlaskjgasdlj sadlf;jsaf lkjvasdfa dsadkfldsfhsa svnsa;df adsfkj;ljkasdf asdf;lkjafd sasgda;dlaskjgasdlj sadlf;jsaf lkjvasdfa dsadkfldsfhsa svnsa;df adsfkj;ljkasdf asdf;lkjafd sasgda;dlaskjgasdlj sadlf;jsaf lkjvasdfa dsadkfldsfhsa svnsa;df adsfkj;ljkasdf asdf;lkjafd sasgda;dlaskjgasdlj sadlf;jsaf lkjvasdfa dsadkfldsfhsa svnsa;df adsfkj;ljkasdf asdf;lkjafd sasgda;dlaskjgasdlj sadlf;jsaf lkjvasdfa dsadkfldsfhsa svnsa;df adsfkj;ljkasdf asdf;lkjafd sasgda;dlaskjgasdlj sadlf;jsaf lkjvasdfa dsadkfldsfhsa svnsa;df adsfkj;ljkasdf asdf;lkjafd sasgda;dlaskjgasdlj sadlf;jsaf lkjvasdfa dsadkfldsfhsa svnsa;df adsfkj;ljkasdf asdf;lkjafd sasgda;dlaskjgasdlj sadlf;jsaf lkjvasdfa dsadkfldsfhsa svnsa;df adsfkj;ljkasdf asdf;lkjafd sasgda;dlaskjgasdlj sadlf;jsaf lkjvasdfa dsadkfldsfhsa svnsa;df adsfkj;ljkasdf asdf;lkjafd sasgda;dlaskjgasdlj sadlf;jsaf lkjvasdfa dsadkfldsfhsa svnsa;df adsfkj;ljkasdf asdf;lkjafd sasgda;dlaskjgasdlj sadlf;jsaf lkjvasdfa dsadkfldsfhsa svnsa;df adsfkj;ljkasdf asdf;lkjafd sasgda;dlaskjgasdlj sadlf;jsaf lkjvasdfa dsadkfldsfhsa svnsa;df adsfkj;ljkasdf asdf;lkjafd sasgda;dlaskjgasdlj sadlf;jsaf lkjvasdfa dsadkfldsfhsa svnsa;df adsfkj;ljkasdf asdf;lkjafd sasgda;dlaskjgasdlj sadlf;jsaf lkjvasdfa dsadkfldsfhsa svnsa;df adsfkj;ljkasdf asdf;lkjafd sasgda;dlaskjgasdlj sadlf;jsaf lkjvasdfa dsadkfldsfhsa svnsa;df adsfkj;ljkasdf asdf;lkjafd sasgda;dlaskjgasdlj sadlf;jsaf lkjvasdfa dsadkfldsfhsa svnsa;df adsfkj;ljkasdf asdf;lkjafd sasgda;dlaskjgasdlj sadlf;jsaf lkjvasdfa dsadkfldsfhsa svnsa;df adsfkj;ljkasdf asdf;lkjafd sasgda;dlaskjgasdlj sadlf;jsaf lkjvasdfa dsadkfldsfhsa svnsa;df adsfkj;ljkasdf asdf;lkjafd sasgda;dlaskjgasdlj sadlf;jsaf lkjvasdfa dsadkfldsfhsa svnsa;df adsfkj;ljkasdf asdf;lkjafd sasgda;dlaskjgasdlj sadlf;jsaf lkjvasdfa dsadkfldsfhsa svnsa;df adsfkj;ljkasdf asdf;lkjafd sasgda;dlaskjgasdlj sadlf;jsaf lkjvasdfa dsadkfldsfhsa svnsa;df adsfkj;ljkasdf asdf;lkjafd sasgda;dlaskjgasdlj sadlf;jsaf lkjvasdfa dsadkfldsfhsa svnsa;df adsfkj;ljkasdf asdf;lkjafd sasgda;dlaskjgasdlj sadlf;jsaf lkjvasdfa dsadkfldsfhsa svnsa;df adsfkj;ljkasdf asdf;lkjafd sasgda;dlaskjgasdlj sadlf;jsaf lkjvasdfa dsadkfldsfhsa svnsa;df adsfkj;ljkasdf asdf;lkjafd sasgda;dlaskjgasdlj sadlf;jsaf lkjvasdfa dsadkfldsfhsa svnsa;df adsfkj;ljkasdf asdf;lkjafd sasgda;dlaskjgasdlj sadlf;jsaf lkjvasdfa dsadkfldsfhsa svnsa;df adsfkj;ljkasdf asdf;lkjafd sasgda;dlaskjgasdlj sadlf;jsaf lkjvasdfa dsadkfldsfhsa svnsa;df adsfkj;ljkasdf asdf;lkjafd sasgda;dlaskjgasdlj sadlf;jsaf lkjvasdfa dsadkfldsfhsa svnsa;df adsfkj;ljkasdf asdf;lkjafd sasgda;dlaskjgasdlj sadlf;jsaf lkjvasdfa dsadkfldsfhsa svnsa;df adsfkj;ljkasdf asdf;lkjafd sasgda;dlaskjgasdlj sadlf;jsaf lkjvasdfa dsadkfldsfhsa svnsa;df adsfkj;ljkasdf asdf;lkjafd sasgda;dlaskjgasdlj sadlf;jsaf lkjvasdfa dsadkfldsfhsa svnsa;df adsfkj;ljkasdf asdf;lkjafd sasgda;dlaskjgasdlj sadlf;jsaf lkjvasdfa dsadkfldsfhsa svnsa;df adsfkj;ljkasdf asdf;lkjafd sasgda;dlaskjgasdlj sadlf;jsaf lkjvasdfa dsadkfldsfhsa svnsa;df adsfkj;ljkasdf asdf;lkjafd sasgda;dlaskjgasdlj sadlf;jsaf lkjvasdfa dsadkfldsfhsa svnsa;df adsfkj;ljkasdf asdf;lkjafd sasgda;dlaskjgasdlj sadlf;jsaf lkjvasdfa dsadkfldsfhsa svnsa;df adsfkj;ljkasdf asdf;lkjafd sasgda;dlaskjgasdlj sadlf;jsaf lkjvasdfa dsadkfldsfhsa svnsa;df adsfkj;ljkasdf asdf;lkjafd sasgda;dlaskjgasdlj sadlf;jsaf lkjvasdfa dsadkfldsfhsa svnsa;df adsfkj;ljkasdf asdf;lkjafd sasgda;dlaskjgasdlj sadlf;jsaf lkjvasdfa dsadkfldsfhsa svnsa;df adsfkj;ljkasdf asdf;lkjafd sasgda;dlaskjgasdlj sadlf;jsaf lkjvasdfa dsadkfldsfhsa svnsa;df adsfkj;ljkasdf asdf;lkjafd sasgda;dlaskjgasdlj sadlf;jsaf lkjvasdfa dsadkfldsfhsa svnsa;df adsfkj;ljkasdf asdf;lkjafd sasgda;dlaskjgasdlj sadlf;jsaf lkjvasdfa dsadkfldsfhsa svnsa;df adsfkj;ljkasdf asdf;lkjafd sasgda;dlaskjgasdlj sadlf;jsaf lkjvasdfa dsadkfldsfhsa svnsa;df adsfkj;ljkasdf asdf;lkjafd sasgda;dlaskjgasdlj sadlf;jsaf lkjvasdfa dsadkfldsfhsa svnsa;df adsfkj;ljkasdf asdf;lkjafd sasgda;dlaskjgasdlj sadlf;jsaf lkjvasdfa dsadkfldsfhsa svnsa;df adsfkj;ljkasdf asdf;lkjafd sasgda;dlaskjgasdlj sadlf;jsaf lkjvasdfa dsadkfldsfhsa svnsa;df adsfkj;ljkasdf asdf;lkjafd sasgda;dlaskjgasdlj sadlf;jsaf lkjvasdfa dsadkfldsfhsa svnsa;df adsfkj;ljkasdf asdf;lkjafd sasgda;dlaskjgasdlj sadlf;jsaf lkjvasdfa dsadkfldsfhsa svnsa;df adsfkj;ljkasdf asdf;lkjafd sasgda;dlaskjgasdlj sadlf;jsaf lkjvasdfa dsadkfldsfhsa svnsa;df adsfkj;ljkasdf asdf;lkjafd sasgda;dlaskjgasdlj sadlf;jsaf lkjvasdfa dsadkfldsfhsa svnsa;df adsfkj;ljkasdf asdf;lkjafd sasgda;dlaskjgasdlj sadlf;jsaf lkjvasdfa dsadkfldsfhsa svnsa;df adsfkj;ljkasdf asdf;lkjafd sasgda;dlaskjgasdlj sadlf;jsaf lkjvasdfa dsadkfldsfhsa svnsa;df adsfkj;ljkasdf asdf;lkjafd sasgda;dlaskjgasdlj sadlf;jsaf lkjvasdfa dsadkfldsfhsa svnsa;df adsfkj;ljkasdf asdf;lkjafd sasgda;dlaskjgasdlj sadlf;jsaf lkjvasdfa dsadkfldsfhsa svnsa;df adsfkj;ljkasdf asdf;lkjafd sasgda;dlaskjgasdlj sadlf;jsaf lkjvasdfa dsadkfldsfhsa svnsa;df adsfkj;ljkasdf asdf;lkjafd sasgda;dlaskjgasdlj sadlf;jsaf lkjvasdfa dsadkfldsfhsa svnsa;df adsfkj;ljkasdf asdf;lkjafd sasgda;dlaskjgasdlj sadlf;jsaf lkjvasdfa dsadkfldsfhsa svnsa;df adsfkj;ljkasdf asdf;lkjafd sasgda;dlaskjgasdlj sadlf;jsaf lkjvasdfa dsadkfldsfhsa svnsa;df adsfkj;ljkasdf asdf;lkjafd sasgda;dlaskjgasdlj sadlf;jsaf lkjvasdfa dsadkfldsfhsa svnsa;df adsfkj;ljkasdf asdf;lkjafd sasgda;dlaskjgasdlj sadlf;jsaf lkjvasdfa dsadkfldsfhsa svnsa;df adsfkj;ljkasdf asdf;lkjafd sasgda;dlaskjgasdlj sadlf;jsaf lkjvasdfa dsadkfldsfhsa svnsa;df adsfkj;ljkasdf asdf;lkjafd sasgda;dlaskjgasdlj sadlf;jsaf lkjvasdfa dsadkfldsfhsa svnsa;df adsfkj;ljkasdf asdf;lkjafd sasgda;dlaskjgasdlj sadlf;jsaf lkjvasdfa dsadkfldsfhsa svnsa;df adsfkj;ljkasdf asdf;lkjafd sasgda;dlaskjgasdlj sadlf;jsaf lkjvasdfa dsadkfldsfhsa svnsa;df adsfkj;ljkasdf asdf;lkjafd sasgda;dlaskjgasdlj sadlf;jsaf lkjvasdfa dsadkfldsfhsa svnsa;df adsfkj;ljkasdf asdf;lkjafd sasgda;dlaskjgasdlj sadlf;jsaf lkjvasdfa dsadkfldsfhsa svnsa;df adsfkj;ljkasdf asdf;lkjafd sasgda;dlaskjgasdlj sadlf;jsaf lkjvasdfa dsadkfldsfhsa svnsa;df adsfkj;ljkasdf asdf;lkjafd sasgda;dlaskjgasdlj sadlf;jsaf lkjvasdfa dsadkfldsfhsa svnsa;df adsfkj;ljkasdf asdf;lkjafd sasgda;dlaskjgasdlj sadlf;jsaf lkjvasdfa dsadkfldsfhsa svnsa;df adsfkj;ljkasdf asdf;lkjafd sasgda;dlaskjgasdlj sadlf;jsaf lkjvasdfa dsadkfldsfhsa svnsa;df adsfkj;ljkasdf asdf;lkjafd sasgda;dlaskjgasdlj sadlf;jsaf lkjvasdfa dsadkfldsfhsa svnsa;df adsfkj;ljkasdf asdf;lkjafd sasgda;dlaskjgasdlj sadlf;jsaf lkjvasdfa dsadkfldsfhsa svnsa;df adsfkj;ljkasdf asdf;lkjafd sasgda;dlaskjgasdlj sadlf;jsaf lkjvasdfa dsadkfldsfhsa svnsa;df adsfkj;ljkasdf asdf;lkjafd sasgda;dlaskjgasdlj sadlf;jsaf lkjvasdfa dsadkfldsfhsa svnsa;df adsfkj;ljkasdf asdf;lkjafd sasgda;dlaskjgasdlj sadlf;jsaf lkjvasdfa dsadkfldsfhsa svnsa;df adsfkj;ljkasdf asdf;lkjafd sasgda;dlaskjgasdlj sadlf;jsaf lkjvasdfa dsadkfldsfhsa svnsa;df adsfkj;ljkasdf asdf;lkjafd sasgda;dlaskjgasdlj sadlf;jsaf lkjvasdfa dsadkfldsfhsa svnsa;df adsfkj;ljkasdf asdf;lkjafd sasgda;dlaskjgasdlj sadlf;jsaf lkjvasdfa dsadkfldsfhsa svnsa;df adsfkj;ljkasdf asdf;lkjafd sasgda;dlaskjgasdlj sadlf;jsaf lkjvasdfa dsadkfldsfhsa svnsa;df adsfkj;ljkasdf asdf;lkjafd sasgda;dlaskjgasdlj sadlf;jsaf lkjvasdfa dsadkfldsfhsa svnsa;df adsfkj;ljkasdf asdf;lkjafd sasgda;dlaskjgasdlj sadlf;jsaf lkjvasdfa dsadkfldsfhsa svnsa;df adsfkj;ljkasdf asdf;lkjafd'
pattern = 'look'
print('pattern at the end of string')
print('find:', end=' ')
%timeit find(very_long_string + pattern, pattern)
print('regex:', end=' ')
%timeit re_find(very_long_string + pattern, pattern)
print('in:', end=' ')
%timeit best_find(very_long_string + pattern, pattern)
print('pattern in front of string')
print('find:', end=' ')
%timeit find(pattern + very_long_string, pattern)
print('regex:', end=' ')
%timeit re_find(pattern + very_long_string, pattern)
print('in:', end=' ')
%timeit best_find(pattern + very_long_string, pattern)

给出输出：

pattern at the end of string
find: 3.41 µs ± 74.2 ns per loop (mean ± std. dev. of 7 runs, 100000 loops each)
regex: 1.93 µs ± 23.8 ns per loop (mean ± std. dev. of 7 runs, 1000000 loops each)
in: 3.32 µs ± 74.6 ns per loop (mean ± std. dev. of 7 runs, 100000 loops each)
pattern in front of string
find: 748 ns ± 15.6 ns per loop (mean ± std. dev. of 7 runs, 1000000 loops each)
regex: 2.03 µs ± 21.1 ns per loop (mean ± std. dev. of 7 runs, 100000 loops each)
in: 589 ns ± 6.75 ns per loop (mean ± std. dev. of 7 runs, 1000000 loops each)

总结：find 和 in 取决于字符串长度和模式在字符串中的位置，而 regex 在某种程度上与字符串长度无关，并且对于结尾有模式的非常长的字符串更快。

Answer 7

除了上述答案之外，re.search() 和 re.match() 采用相同的运行时间。

if(re.search(rf"\b{re.escape(some_keyword)}\b",some_sentence))

采用与

相同的运行时间

if(re.search(rf"\b{re.escape(some_keyword)}\b",some_sentence))

如果您的正则表达式必须需要一些单词匹配，那么减少与“if”“in”搜索的正则表达式比较是一个更好的选择。例如，下面的比上面的两个要快，并且给出相同的结果：

if(some_keyword.lower() in some_sentence.lower()):
  if(re.search(rf"\b{re.escape(some_keyword)}\b",some_sentence)):