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。

我需要一个解决方案，其中字符串可以被替换为正则表达式， 例如，通过将多个空格字符替换为一个空格字符来帮助规范化长文本。根据其他人(包括MiniQuark和mmj)的一系列答案，我得出了以下结论:

def multiple_replace(string, reps, re_flags = 0):
    """ Transforms string, replacing keys from re_str_dict with values.
    reps: dictionary, or list of key-value pairs (to enforce ordering;
          earlier items have higher priority).
          Keys are used as regular expressions.
    re_flags: interpretation of regular expressions, such as re.DOTALL
    """
    if isinstance(reps, dict):
        reps = reps.items()
    pattern = re.compile("|".join("(?P<_%d>%s)" % (i, re_str[0])
                                  for i, re_str in enumerate(reps)),
                         re_flags)
    return pattern.sub(lambda x: reps[int(x.lastgroup[1:])][1], string)

它适用于其他答案中给出的例子，例如:

>>> multiple_replace("(condition1) and --condition2--",
...                  {"condition1": "", "condition2": "text"})
'() and --text--'

>>> multiple_replace('hello, world', {'hello' : 'goodbye', 'world' : 'earth'})
'goodbye, earth'

>>> multiple_replace("Do you like cafe? No, I prefer tea.",
...                  {'cafe': 'tea', 'tea': 'cafe', 'like': 'prefer'})
'Do you prefer tea? No, I prefer cafe.'

对我来说，最重要的是你也可以使用正则表达式，例如只替换整个单词，或规范化空白:

>>> s = "I don't want to change this name:\n  Philip II of Spain"
>>> re_str_dict = {r'\bI\b': 'You', r'[\n\t ]+': ' '}
>>> multiple_replace(s, re_str_dict)
"You don't want to change this name: Philip II of Spain"

如果你想使用字典键作为普通字符串， 你可以在调用multiple_replace之前转义这些，例如使用下面的函数:

def escape_keys(d):
    """ transform dictionary d by applying re.escape to the keys """
    return dict((re.escape(k), v) for k, v in d.items())

>>> multiple_replace(s, escape_keys(re_str_dict))
"I don't want to change this name:\n  Philip II of Spain"

下面的函数可以帮助在你的字典键中找到错误的正则表达式(因为来自multiple_replace的错误消息不是很明显):

def check_re_list(re_list):
    """ Checks if each regular expression in list is well-formed. """
    for i, e in enumerate(re_list):
        try:
            re.compile(e)
        except (TypeError, re.error):
            print("Invalid regular expression string "
                  "at position {}: '{}'".format(i, e))

>>> check_re_list(re_str_dict.keys())

请注意，它没有链接替换，而是同时执行它们。这使得它更有效率，而不会限制它能做什么。为了模仿链接的效果，你可能只需要添加更多的字符串替换对，并确保这些对的预期顺序:

>>> multiple_replace("button", {"but": "mut", "mutton": "lamb"})
'mutton'
>>> multiple_replace("button", [("button", "lamb"),
...                             ("but", "mut"), ("mutton", "lamb")])
'lamb'

这是我的0.02美元。它基于Andrew Clark的答案，只是更清楚一点，它还涵盖了当一个字符串被替换为另一个字符串的子字符串时的情况(更长的字符串胜出)

def multireplace(string, replacements):
    """
    Given a string and a replacement map, it returns the replaced string.

    :param str string: string to execute replacements on
    :param dict replacements: replacement dictionary {value to find: value to replace}
    :rtype: str

    """
    # Place longer ones first to keep shorter substrings from matching
    # where the longer ones should take place
    # For instance given the replacements {'ab': 'AB', 'abc': 'ABC'} against 
    # the string 'hey abc', it should produce 'hey ABC' and not 'hey ABc'
    substrs = sorted(replacements, key=len, reverse=True)

    # Create a big OR regex that matches any of the substrings to replace
    regexp = re.compile('|'.join(map(re.escape, substrs)))

    # For each match, look up the new string in the replacements
    return regexp.sub(lambda match: replacements[match.group(0)], string)

这就是这个要点，如果你有任何建议，请随意修改。

我的方法是首先将字符串标记化，然后决定每个标记是否包含它。

潜在地，如果我们可以假设一个hashmap/set的O(1)查找，可能会更好:

remove_words = {"we", "this"}
target_sent = "we should modify this string"
target_sent_words = target_sent.split()
filtered_sent = " ".join(list(filter(lambda word: word not in remove_words, target_sent_words)))

Filtered_sent现在是'应该修改字符串'

我觉得这个问题需要一个单行递归lambda函数的答案，只是因为。所以有:

>>> mrep = lambda s, d: s if not d else mrep(s.replace(*d.popitem()), d)

用法:

>>> mrep('abcabc', {'a': '1', 'c': '2'})
'1b21b2'

注:

这将消耗输入字典。 Python字典保留3.6起的键顺序;其他答案中的相应警告不再相关。为了向后兼容，可以使用基于元组的版本:

>>> mrep = lambda s, d: s if not d else mrep(s.replace(*d.pop()), d)
>>> mrep('abcabc', [('a', '1'), ('c', '2')])

注意:与python中的所有递归函数一样，太大的递归深度(即替换字典太大)将导致错误。请看这里。

为什么没有这样的解决方案呢?

s = "The quick brown fox jumps over the lazy dog"
for r in (("brown", "red"), ("lazy", "quick")):
    s = s.replace(*r)

#output will be:  The quick red fox jumps over the quick dog