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。

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

你可以做一个漂亮的循环函数。

def replace_all(text, dic):
    for i, j in dic.iteritems():
        text = text.replace(i, j)
    return text

其中text是完整的字符串，dic是字典-每个定义都是一个字符串，将替换与术语匹配的字符串。

注意:在Python 3中，iteritems()已被items()取代

注意:Python字典没有迭代的可靠顺序。此解决方案仅在以下情况下解决您的问题:

替换的顺序无关紧要 替换者可以改变之前替换者的结果

更新:上述与插入顺序相关的语句不适用于大于或等于3.6的Python版本，因为标准字典已更改为使用插入顺序进行迭代。

例如:

d = { "cat": "dog", "dog": "pig"}
my_sentence = "This is my cat and this is my dog."
replace_all(my_sentence, d)
print(my_sentence)

可能输出#1:

"This is my pig and this is my pig."

可能的输出#2

"This is my dog and this is my pig."

一个可能的解决方法是使用OrderedDict。

from collections import OrderedDict
def replace_all(text, dic):
    for i, j in dic.items():
        text = text.replace(i, j)
    return text
od = OrderedDict([("cat", "dog"), ("dog", "pig")])
my_sentence = "This is my cat and this is my dog."
replace_all(my_sentence, od)
print(my_sentence)

输出:

"This is my pig and this is my pig."

注意事项#2:如果你的文本字符串太大或字典中有很多对，效率就会很低。

注意:测试你的案例，见注释。

这里有一个例子，它在长弦上更有效，有许多小的替换。

source = "Here is foo, it does moo!"

replacements = {
    'is': 'was', # replace 'is' with 'was'
    'does': 'did',
    '!': '?'
}

def replace(source, replacements):
    finder = re.compile("|".join(re.escape(k) for k in replacements.keys())) # matches every string we want replaced
    result = []
    pos = 0
    while True:
        match = finder.search(source, pos)
        if match:
            # cut off the part up until match
            result.append(source[pos : match.start()])
            # cut off the matched part and replace it in place
            result.append(replacements[source[match.start() : match.end()]])
            pos = match.end()
        else:
            # the rest after the last match
            result.append(source[pos:])
            break
    return "".join(result)

print replace(source, replacements)

关键是要避免长字符串的多次连接。我们将源字符串切成片段，在我们形成列表时替换一些片段，然后将整个字符串连接回字符串。

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'

从安德鲁的宝贵答案开始，我开发了一个脚本，从一个文件加载字典，并详细说明所有文件上打开的文件夹做替换。脚本从一个外部文件加载映射，您可以在该文件中设置分隔符。我是一个初学者，但我发现这个脚本在多个文件中做多个替换时非常有用。它在几秒钟内加载了一个包含1000多个条目的字典。这并不优雅，但对我来说很管用

import glob
import re

mapfile = input("Enter map file name with extension eg. codifica.txt: ")
sep = input("Enter map file column separator eg. |: ")
mask = input("Enter search mask with extension eg. 2010*txt for all files to be processed: ")
suff = input("Enter suffix with extension eg. _NEW.txt for newly generated files: ")

rep = {} # creation of empy dictionary

with open(mapfile) as temprep: # loading of definitions in the dictionary using input file, separator is prompted
    for line in temprep:
        (key, val) = line.strip('\n').split(sep)
        rep[key] = val

for filename in glob.iglob(mask): # recursion on all the files with the mask prompted

    with open (filename, "r") as textfile: # load each file in the variable text
        text = textfile.read()

        # start replacement
        #rep = dict((re.escape(k), v) for k, v in rep.items()) commented to enable the use in the mapping of re reserved characters
        pattern = re.compile("|".join(rep.keys()))
        text = pattern.sub(lambda m: rep[m.group(0)], text)

        #write of te output files with the prompted suffice
        target = open(filename[:-4]+"_NEW.txt", "w")
        target.write(text)
        target.close()