python中的字符串替换性能

Question

我有一个约50,000个字符串（标题）的列表，以及从这些标题中删除的约150个字的列表（如果找到它们）。 到目前为止，我的代码如下。 最终输出应该是50,000个字符串的列表，其中删除了150个单词的所有实例。 我想知道这样做最有效（表现明智）的方式。 我的代码似乎在运行，虽然速度很慢..

excludes = GetExcludes()
titles = GetTitles()
titles_alpha = []
titles_excl = []
for k in range(len(titles)):
    #remove all non-alphanumeric characters 
    s = re.sub('[^0-9a-zA-Z]+', ' ',titles[k])

    #remove extra white space
    s = re.sub( '\s+', ' ', s).strip()

    #lowercase
    s = s.lower()

    titles_alpha.append(s)
    #remove any excluded words


    for i in range (len(excludes)):
        titles_excl.append(titles_alpha[k].replace(excludes[i],''))

print titles_excl

Answer 1

正则表达式的许多性能开销来自编译正则表达式。 您应该将正则表达式的编译移出循环。

这应该会给你一个相当大的改进：

pattern1 = re.compile('[^0-9a-zA-Z]+')
pattern2 = re.compile('\s+')
for k in range(len(titles)):
    #remove all non-alphanumeric characters 
    s = re.sub(pattern1,' ',titles[k])

    #remove extra white space
    s = re.sub(pattern2,' ', s).strip()

有一些测试wordlist.txt从这里 ：

import re
def noncompiled():
    with open("wordlist.txt",'r') as f:
        titles = f.readlines()
    titles = ["".join([title,nonalpha]) for title in titles for nonalpha in "!@#$%"]
    for k in range(len(titles)):
        #remove all non-alphanumeric characters 
        s = re.sub('[^0-9a-zA-Z]+', ' ',titles[k])

        #remove extra white space
        s = re.sub( '\s+', ' ', s).strip()

def compiled():
    with open("wordlist.txt",'r') as f:
        titles = f.readlines()
    titles = ["".join([title,nonalpha]) for title in titles for nonalpha in "!@#$%"]
    pattern1=re.compile('[^0-9a-zA-Z]+')
    pattern2 = re.compile( '\s+')
    for k in range(len(titles)):
        #remove all non-alphanumeric characters 
        s = pattern1.sub('',titles[k])

        #remove extra white space
        s = pattern2.sub('', s)



In [2]: %timeit noncompiled()
1 loops, best of 3: 292 ms per loop

In [3]: %timeit compiled()
10 loops, best of 3: 176 ms per loop

要从排除列表中删除“坏词”，您应该像@zsquare建议创建一个联合正则表达式，这很可能是您可以获得的最快速度。

def with_excludes():
    with open("wordlist.txt",'r') as f:
        titles = f.readlines()
    titles = ["".join([title,nonalpha]) for title in titles for nonalpha in "!@#$%"]
    pattern1=re.compile('[^0-9a-zA-Z]+')
    pattern2 = re.compile( '\s+')
    excludes = ["shit","poo","ass","love","boo","ch"]
    excludes_regex = re.compile('|'.join(excludes))
    for k in range(len(titles)):
        #remove all non-alphanumeric characters 
        s = pattern1.sub('',titles[k])

        #remove extra white space
        s = pattern2.sub('', s)
        #remove bad words
        s = pattern2.sub('', s)
In [2]: %timeit with_excludes()
1 loops, best of 3: 251 ms per loop

只需编译一个主正则表达式，您就可以进一步采用这种方法：

def master():
    with open("wordlist.txt",'r') as f:
        titles = f.readlines()
    titles = ["".join([title,nonalpha]) for title in titles for nonalpha in "!@#$%"]
    excludes = ["shit","poo","ass","love","boo","ch"]
    nonalpha='[^0-9a-zA-Z]+'
    whitespace='\s+'
    badwords = '|'.join(excludes)
    master_regex=re.compile('|'.join([nonalpha,whitespace,badwords]))

    for k in range(len(titles)):
        #remove all non-alphanumeric characters 
        s = master_regex.sub('',titles[k])
In [2]: %timeit master()
10 loops, best of 3: 148 ms per loop

通过避免python中的迭代，您可以获得更快的速度：

    result = [master_regex.sub('',item) for item in titles]


In [4]: %timeit list_comp()
10 loops, best of 3: 139 ms per loop

注意：数据生成步骤：

def baseline():
    with open("wordlist.txt",'r') as f:
        titles = f.readlines()
    titles = ["".join([title,nonalpha]) for title in titles for nonalpha in "!@#$%"]

In [2]: %timeit baseline()
10 loops, best of 3: 24.8 ms per loop

Answer 2

一种方法是动态创建被排除单词的正则表达式并在列表中替换它们。

就像是：

excludes_regex = re.compile('|'.join(excludes))
titles_excl = []
for title in titles:
    titles_excl.append(excludes_regex.sub('', title))