下面是一个支持基本正则表达式替换的版本。主要的限制是表达式不能包含子组，并且可能存在一些边缘情况:

基于@bgusach和其他的代码

import re

class StringReplacer:

    def __init__(self, replacements, ignore_case=False):
        patterns = sorted(replacements, key=len, reverse=True)
        self.replacements = [replacements[k] for k in patterns]
        re_mode = re.IGNORECASE if ignore_case else 0
        self.pattern = re.compile('|'.join(("({})".format(p) for p in patterns)), re_mode)
        def tr(matcher):
            index = next((index for index,value in enumerate(matcher.groups()) if value), None)
            return self.replacements[index]
        self.tr = tr

    def __call__(self, string):
        return self.pattern.sub(self.tr, string)

测试

table = {
    "aaa"    : "[This is three a]",
    "b+"     : "[This is one or more b]",
    r"<\w+>" : "[This is a tag]"
}

replacer = StringReplacer(table, True)

sample1 = "whatever bb, aaa, <star> BBB <end>"

print(replacer(sample1))

# output: 
# whatever [This is one or more b], [This is three a], [This is a tag] [This is one or more b] [This is a tag]

诀窍是通过位置来识别匹配的组。它不是超级高效(O(n))，但它是有效的。

index = next((index for index,value in enumerate(matcher.groups()) if value), None)

替换是一次完成的。

这是我对这个问题的解决办法。我把它用在聊天机器人上，一次替换不同的单词。

def mass_replace(text, dct):
    new_string = ""
    old_string = text
    while len(old_string) > 0:
        s = ""
        sk = ""
        for k in dct.keys():
            if old_string.startswith(k):
                s = dct[k]
                sk = k
        if s:
            new_string+=s
            old_string = old_string[len(sk):]
        else:
            new_string+=old_string[0]
            old_string = old_string[1:]
    return new_string

print mass_replace("The dog hunts the cat", {"dog":"cat", "cat":"dog"})

这就成了猫捉狗

我把这句话建立在fj的精彩回答上:

import re

def multiple_replacer(*key_values):
    replace_dict = dict(key_values)
    replacement_function = lambda match: replace_dict[match.group(0)]
    pattern = re.compile("|".join([re.escape(k) for k, v in key_values]), re.M)
    return lambda string: pattern.sub(replacement_function, string)

def multiple_replace(string, *key_values):
    return multiple_replacer(*key_values)(string)

一针用法:

>>> replacements = (u"café", u"tea"), (u"tea", u"café"), (u"like", u"love")
>>> print multiple_replace(u"Do you like café? No, I prefer tea.", *replacements)
Do you love tea? No, I prefer café.

注意，由于替换只在一次传递中完成，“café”会变成“tea”，但不会变回“café”。

如果你需要做相同的替换多次，你可以很容易地创建一个替换函数:

>>> my_escaper = multiple_replacer(('"','\\"'), ('\t', '\\t'))
>>> many_many_strings = (u'This text will be escaped by "my_escaper"',
                       u'Does this work?\tYes it does',
                       u'And can we span\nmultiple lines?\t"Yes\twe\tcan!"')
>>> for line in many_many_strings:
...     print my_escaper(line)
... 
This text will be escaped by \"my_escaper\"
Does this work?\tYes it does
And can we span
multiple lines?\t\"Yes\twe\tcan!\"

改进:

将代码转换为函数 增加了多线支持 修正了逃跑的错误 容易创建一个函数，用于特定的多个替换

享受吧!: -)

这里有一个使用reduce的第一个解决方案的变体，如果你喜欢功能性的。：）

repls = {'hello' : 'goodbye', 'world' : 'earth'}
s = 'hello, world'
reduce(lambda a, kv: a.replace(*kv), repls.iteritems(), s)

马蒂诺的版本更好:

repls = ('hello', 'goodbye'), ('world', 'earth')
s = 'hello, world'
reduce(lambda a, kv: a.replace(*kv), repls, s)

您可以使用pandas库和replace函数，它既支持精确匹配，也支持正则表达式替换。例如:

df = pd.DataFrame({'text': ['Billy is going to visit Rome in November', 'I was born in 10/10/2010', 'I will be there at 20:00']})

to_replace=['Billy','Rome','January|February|March|April|May|June|July|August|September|October|November|December', '\d{2}:\d{2}', '\d{2}/\d{2}/\d{4}']
replace_with=['name','city','month','time', 'date']

print(df.text.replace(to_replace, replace_with, regex=True))

修改后的文本为:

0    name is going to visit city in month
1                      I was born in date
2                 I will be there at time

你可以在这里找到一个例子。请注意，文本上的替换是按照它们在列表中出现的顺序进行的

另一个例子: 输入列表

error_list = ['[br]', '[ex]', 'Something']
words = ['how', 'much[ex]', 'is[br]', 'the', 'fish[br]', 'noSomething', 'really']

期望的输出将是

words = ['how', 'much', 'is', 'the', 'fish', 'no', 'really']

代码:

[n[0][0] if len(n[0]) else n[1] for n in [[[w.replace(e,"") for e in error_list if e in w],w] for w in words]]