最通用的方法是使用unicodedata表的“类别”，它对每个字符进行分类。例如，下面的代码只过滤基于类别的可打印字符:

import unicodedata
# strip of crap characters (based on the Unicode database
# categorization:
# http://www.sql-und-xml.de/unicode-database/#kategorien

PRINTABLE = set(('Lu', 'Ll', 'Nd', 'Zs'))

def filter_non_printable(s):
    result = []
    ws_last = False
    for c in s:
        c = unicodedata.category(c) in PRINTABLE and c or u'#'
        result.append(c)
    return u''.join(result).replace(u'#', u' ')

查看上面给出的所有相关类别的URL。当然你也可以过滤 按标点符号分类。

function regexFuntion(st) {
  const regx = /[^\w\s]/gi; // allow : [a-zA-Z0-9, space]
  st = st.replace(regx, ''); // remove all data without [a-zA-Z0-9, space]
  st = st.replace(/\s\s+/g, ' '); // remove multiple space

  return st;
}

console.log(regexFuntion('$Hello; # -world--78asdf+-===asdflkj******lkjasdfj67;'));
// Output: Hello world78asdfasdflkjlkjasdfj67

这将删除除空格外的所有非字母数字字符。

string = "Special $#! characters   spaces 888323"
''.join(e for e in string if (e.isalnum() or e.isspace()))

特殊字符空格888323

下面是一个正则表达式，用于匹配不是字母或数字的字符串:

[^A-Za-z0-9]+

下面是执行正则表达式替换的Python命令:

re.sub('[^A-Za-z0-9]+', '', mystring)

import re
my_string = """Strings are amongst the most popular data types in Python. We can create the strings by enclosing characters in quotes. Python treats single quotes the 

和双引号一样。”＂＂

# if we need to count the word python that ends with or without ',' or '.' at end

count = 0
for i in text:
    if i.endswith("."):
        text[count] = re.sub("^([a-z]+)(.)?$", r"\1", i)
    count += 1
print("The count of Python : ", text.count("python"))

最通用的方法是使用unicodedata表的“类别”，它对每个字符进行分类。例如，下面的代码只过滤基于类别的可打印字符:

import unicodedata
# strip of crap characters (based on the Unicode database
# categorization:
# http://www.sql-und-xml.de/unicode-database/#kategorien

PRINTABLE = set(('Lu', 'Ll', 'Nd', 'Zs'))

def filter_non_printable(s):
    result = []
    ws_last = False
    for c in s:
        c = unicodedata.category(c) in PRINTABLE and c or u'#'
        result.append(c)
    return u''.join(result).replace(u'#', u' ')

查看上面给出的所有相关类别的URL。当然你也可以过滤 按标点符号分类。