下面是另一种使用字典的方法:

listA="The cat jumped over the house".split()
modify = {word:word for number,word in enumerate(listA)}
modify["cat"],modify["jumped"]="dog","walked"
print " ".join(modify[x] for x in listA)

sentence='its some sentence with a something text'

def replaceAll(f,Array1,Array2):
    if len(Array1)==len(Array2):
        for x in range(len(Array1)):
            return f.replace(Array1[x],Array2[x])

newSentence=replaceAll(sentence,['a','sentence','something'],['another','sentence','something something'])

print(newSentence)

我在学校作业中也做过类似的练习。这就是我的解

dictionary = {1: ['hate', 'love'],
              2: ['salad', 'burger'],
              3: ['vegetables', 'pizza']}

def normalize(text):
    for i in dictionary:
        text = text.replace(dictionary[i][0], dictionary[i][1])
    return text

自己查看测试字符串上的结果

string_to_change = 'I hate salad and vegetables'
print(normalize(string_to_change))

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。

这只是F.J和mini夸克的一个更简洁的概述，bgusach的伟大回答和最后但决定性的改进。所有你需要实现多个同步字符串替换是以下函数:

def multiple_replace(string, rep_dict):
    pattern = re.compile("|".join([re.escape(k) for k in sorted(rep_dict,key=len,reverse=True)]), flags=re.DOTALL)
    return pattern.sub(lambda x: rep_dict[x.group(0)], string)

用法:

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

如果您愿意，您可以从这个更简单的函数开始创建自己的专用替换函数。

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