with open('one.txt','r')as myFile:

    str1=myFile.read()

    print(str1)


    punctuation = ['(', ')', '?', ':', ';', ',', '.', '!', '/', '"', "'"] 

for i in punctuation:

        str1 = str1.replace(i," ") 
        myList=[]
        myList.extend(str1.split(" "))
print (str1) 
for i in myList:

    print(i,end='\n')
    print ("____________")

我通常用这样的词：

>>> s = "string. With. Punctuation?" # Sample string
>>> import string
>>> for c in string.punctuation:
...     s= s.replace(c,"")
...
>>> s
'string With Punctuation'

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

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}")

不一定更简单，但如果你更熟悉re家族的话，就另辟蹊径。

import re, string
s = "string. With. Punctuation?" # Sample string 
out = re.sub('[%s]' % re.escape(string.punctuation), '', s)

作为更新，我重写了Python 3中的@Brian示例，并对其进行了更改，以将正则表达式编译步骤移到函数内部。我在这里的想法是对使功能工作所需的每一步进行计时。也许您使用的是分布式计算，无法在工作人员之间共享regex对象，需要在每个工作人员处执行re.compile步骤。此外，我还很好奇地对Python 3的maketrans的两种不同实现进行计时

table = str.maketrans({key: None for key in string.punctuation})

vs

table = str.maketrans('', '', string.punctuation)

另外，我添加了另一种使用集合的方法，在这里我利用交集函数来减少迭代次数。

这是完整的代码：

import re, string, timeit

s = "string. With. Punctuation"


def test_set(s):
    exclude = set(string.punctuation)
    return ''.join(ch for ch in s if ch not in exclude)


def test_set2(s):
    _punctuation = set(string.punctuation)
    for punct in set(s).intersection(_punctuation):
        s = s.replace(punct, ' ')
    return ' '.join(s.split())


def test_re(s):  # From Vinko's solution, with fix.
    regex = re.compile('[%s]' % re.escape(string.punctuation))
    return regex.sub('', s)


def test_trans(s):
    table = str.maketrans({key: None for key in string.punctuation})
    return s.translate(table)


def test_trans2(s):
    table = str.maketrans('', '', string.punctuation)
    return(s.translate(table))


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


print("sets      :",timeit.Timer('f(s)', 'from __main__ import s,test_set as f').timeit(1000000))
print("sets2      :",timeit.Timer('f(s)', 'from __main__ import s,test_set2 as f').timeit(1000000))
print("regex     :",timeit.Timer('f(s)', 'from __main__ import s,test_re as f').timeit(1000000))
print("translate :",timeit.Timer('f(s)', 'from __main__ import s,test_trans as f').timeit(1000000))
print("translate2 :",timeit.Timer('f(s)', 'from __main__ import s,test_trans2 as f').timeit(1000000))
print("replace   :",timeit.Timer('f(s)', 'from __main__ import s,test_repl as f').timeit(1000000))

这是我的结果：

sets      : 3.1830138750374317
sets2      : 2.189873124472797
regex     : 7.142953420989215
translate : 4.243278483860195
translate2 : 2.427158243022859
replace   : 4.579746678471565