这是我写的一个函数。它不是很有效，但很简单，您可以添加或删除任何您想要的标点符号：

def stripPunc(wordList):
    """Strips punctuation from list of words"""
    puncList = [".",";",":","!","?","/","\\",",","#","@","$","&",")","(","\""]
    for punc in puncList:
        for word in wordList:
            wordList=[word.replace(punc,'') for word in wordList]
    return wordList

>>> s = "string. With. Punctuation?"
>>> s = re.sub(r'[^\w\s]','',s)
>>> re.split(r'\s*', s)


['string', 'With', 'Punctuation']

显然，我无法对所选答案进行编辑，所以这里有一个适用于Python3的更新。在进行非平凡转换时，转换方法仍然是最有效的选择。

上面的@Brian为最初的繁重工作做出了贡献。感谢@ddejohn对原始测试的改进建议。

#!/usr/bin/env python3

"""Determination of most efficient way to remove punctuation in Python 3.

Results in Python 3.8.10 on my system using the default arguments:

set       : 51.897
regex     : 17.901
translate :  2.059
replace   : 13.209
"""

import argparse
import re
import string
import timeit

parser = argparse.ArgumentParser()
parser.add_argument("--filename", "-f", default=argparse.__file__)
parser.add_argument("--iterations", "-i", type=int, default=10000)
opts = parser.parse_args()
with open(opts.filename) as fp:
    s = fp.read()
exclude = set(string.punctuation)
table = str.maketrans("", "", string.punctuation)
regex = re.compile(f"[{re.escape(string.punctuation)}]")

def test_set(s):
    return "".join(ch for ch in s if ch not in exclude)

def test_regex(s):  # From Vinko's solution, with fix.
    return regex.sub("", s)

def test_translate(s):
    return s.translate(table)

def test_replace(s):  # From S.Lott's solution
    for c in string.punctuation:
        s = s.replace(c, "")
    return s

opts = dict(globals=globals(), number=opts.iterations)
solutions = "set", "regex", "translate", "replace"
for solution in solutions:
    elapsed = timeit.timeit(f"test_{solution}(s)", **opts)
    print(f"{solution:<10}: {elapsed:6.3f}")

我喜欢使用这样的函数：

def scrub(abc):
    while abc[-1] is in list(string.punctuation):
        abc=abc[:-1]
    while abc[0] is in list(string.punctuation):
        abc=abc[1:]
    return abc

为什么你们都不用这个？

 ''.join(filter(str.isalnum, s)) 

太慢了？

对于严肃的自然语言处理（NLP），您应该让像SpaCy这样的库通过标记化处理标点符号，然后您可以根据需要手动调整。

例如，您希望如何处理单词中的连字符？例外情况，如缩写？开始和结束引号？URL？在NLP中，将“let’s”这样的收缩分隔为“let”和“s”以进行进一步处理通常很有用。