如何替换字符串的多个子字符串?

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是一个字典——每个定义都是一个字符串，将替换与术语匹配的字符串。

请注意: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."

Possible output #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."

如果你的text字符串太大或字典中有很多对，则无效。

下面是一个简短的例子，应该做的技巧与正则表达式:

import re


rep = {"condition1": "", "condition2": "text"} # define desired replacements here


# use these three lines to do the replacement
rep = dict((re.escape(k), v) for k, v in rep.iteritems())
#Python 3 renamed dict.iteritems to dict.items so use rep.items() for latest versions
pattern = re.compile("|".join(rep.keys()))
text = pattern.sub(lambda m: rep[re.escape(m.group(0))], text)

例如:

>>> pattern.sub(lambda m: rep[re.escape(m.group(0))], "(condition1) and --condition2--")
'() and --text--'

你真的不应该这样做，但我觉得这太酷了:

>>> replacements = {'cond1':'text1', 'cond2':'text2'}
>>> cmd = 'answer = s'
>>> for k,v in replacements.iteritems():
>>>     cmd += ".replace(%s, %s)" %(k,v)
>>> exec(cmd)

现在，answer是所有替换的结果

同样，这是非常黑客，不是你应该经常使用的东西。但我很高兴知道如果你需要的话，你可以这样做。

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。

我想建议使用字符串模板。只需将要替换的字符串放在字典中，一切就都设置好了!docs.python.org的例子

>>> from string import Template
>>> s = Template('$who likes $what')
>>> s.substitute(who='tim', what='kung pao')
'tim likes kung pao'
>>> d = dict(who='tim')
>>> Template('Give $who $100').substitute(d)
Traceback (most recent call last):
[...]
ValueError: Invalid placeholder in string: line 1, col 10
>>> Template('$who likes $what').substitute(d)
Traceback (most recent call last):
[...]
KeyError: 'what'
>>> Template('$who likes $what').safe_substitute(d)
'tim likes $what'

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)

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。实现多个同时的字符串替换所需要的是以下函数:

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。

或者简单说一下:

for line in to_read:
read_buffer = line
stripped_buffer1 = read_buffer.replace("term1", " ")
stripped_buffer2 = stripped_buffer1.replace("term2", " ")
write_to_file = to_write.write(stripped_buffer2)

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)

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。在其他人(包括MiniQuark和mmj)的一系列答案的基础上，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，例如使用这个函数:

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'

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()

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"})

这将成为The cat hunts the dog

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]]

在我的情况下，我需要一个简单的唯一键替换名称，所以我想到了这个:

a = 'This is a test string.'
b = {'i': 'I', 's': 'S'}
for x,y in b.items():
a = a.replace(x, y)
>>> a
'ThIS IS a teSt StrIng.'

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)

它在这个这个要点中，如果你有任何建议，请随意修改它。

我不知道速度如何，但这是我日常的快速解决方法:

reduce(lambda a, b: a.replace(*b)
, [('o','W'), ('t','X')] #iterable of pairs: (oldval, newval)
, 'tomato' #The string from which to replace values
)

．.． 但我喜欢上面的#1正则表达式答案。注意:如果一个新值是另一个值的子字符串，那么该操作是不可交换的。

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

从Python 3.8开始，并引入赋值表达式 (:=操作符)，我们可以在一个列表推导式中应用替换:

# text = "The quick brown fox jumps over the lazy dog"
# replacements = [("brown", "red"), ("lazy", "quick")]
[text := text.replace(a, b) for a, b in replacements]
# text = 'The quick red fox jumps over the quick dog'

你可以使用pandas库和replace函数，它们既支持精确匹配，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

你可以找到一个例子在这里。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

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。参见e.g. 在这里。

我也在这个问题上苦苦挣扎。由于有很多替换，正则表达式的速度比循环string.replace慢四倍(在我的实验条件下)。

你绝对应该尝试使用Flashtext库(这里是博客文章， Github在这里)。对我来说对于每个文档，它都比快了两个数量级，从1.8秒到0.015秒(正则表达式耗时7.7秒)稍微多一点。

在上面的链接中很容易找到使用示例，但这是一个工作示例:

    from flashtext import KeywordProcessor
self.processor = KeywordProcessor(case_sensitive=False)
for k, v in self.my_dict.items():
self.processor.add_keyword(k, v)
new_string = self.processor.replace_keywords(string)

注意，Flashtext在一次传递中进行替换(以避免A——> b和B——> c将'a'转换为'c')。Flashtext也会查找整个单词(所以'is'不会匹配'th是')。如果你的目标是几个单词(将“This is”替换为“Hello”)，这种方法也很有效。

对于只替换一个字符，使用translate和str.maketrans是我最喜欢的方法。

dr > result_string = your_string.translate(str.maketrans(dict_mapping)) . tl

演示

my_string = 'This is a test string.'
dict_mapping = {'i': 's', 's': 'S'}
result_good = my_string.translate(str.maketrans(dict_mapping))
result_bad = my_string
for x, y in dict_mapping.items():
result_bad = result_bad.replace(x, y)
print(result_good)  # ThsS sS a teSt Strsng.
print(result_bad)   # ThSS SS a teSt StrSng.

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'should modify string'

我今天也面临类似的问题，我不得不多次使用.replace()方法，但这对我来说感觉不太好。所以我做了这样的事情:

REPLACEMENTS = {'<': '&lt;', '>': '&gt;', '&': '&amp;'}


event_title = ''.join([REPLACEMENTS.get(c,c) for c in event['summary']])

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(< em > O (n) < / em >)，但它工作。

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

替换是一次完成的。

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))