DFA profile reference: https://blog.csdn.net/chenssy/article/details/26961957
This article is the python version, full version, modified version of the above JAVA sensitive word filtering
First, let’s take a look at the final processing effect.
Example 1:
Input string
Processing result
Core code:
SensitiveFilter class
The frame is as follows
class SensitiveFilter:
#初始化
def __init__(self):
self.initSensitiveWordMap(self.sensitiveWordList)
...
#构建敏感词库
def initSensitiveWordMap(self,sensitiveWordList):
...
#检测文本中存在的敏感词
def checkSensitiveWord(self,txt,beginIndex=0):
...
#得到输入字符串中敏感词列表
def getSensitiveWord(self,txt):
...
#替换文本中的敏感词
def replaceSensitiveWord(self,txt,replaceChar='*'):
...
Let's look at each specific function
Part 1
init function initialization
def __init__(self):
# file把敏感词库加载到列表中
file = open(Dir_sensitive, 'r', encoding = 'ANSI')
file_lst = file.readlines()
self.sensitiveWordList = [i.split('\n')[0] for i in file_lst]
# print(sensitiveWordList[:10])
# file1把停用词加载到列表中
file1 = open(Dir_stopWord, 'r', encoding = 'ANSI')
file1_lst = file1.readlines()
self.stopWordList = [i.split('\n')[0] for i in file1_lst]
##得到sensitive字典
self.sensitiveWordMap = self.initSensitiveWordMap(self.sensitiveWordList)
Part 2
initSensitiveWordMap function to construct a sensitive word library
#构建敏感词库
def initSensitiveWordMap(self,sensitiveWordList):
sensitiveWordMap = {
}
# 读取每一行，每一个word都是一个敏感词
for word in sensitiveWordList:
nowMap=sensitiveWordMap
#遍历该敏感词的每一个特定字符
for i in range(len(word)):
keychar=word[i]
wordMap=nowMap.get(keychar)
if wordMap !=None:
#nowMap更新为下一层
nowMap=wordMap
else:
#不存在则构建一个map,isEnd设置为0，因为不是最后一个
newNextMap={
}
newNextMap["isEnd"]=0
nowMap[keychar]=newNextMap
nowMap=newNextMap
#到这个词末尾字符
if i==len(word)-1:
nowMap["isEnd"]=1
#print(sensitiveWordMap)
return sensitiveWordMap
Part 3
The checkSensitiveWord function detects the input text and returns the length of the sensitive word
def checkSensitiveWord(self,txt,beginIndex=0):
'''
:param txt: 输入待检测的文本
:param beginIndex:输入文本开始的下标
:return:返回敏感词字符的长度
'''
nowMap=self.sensitiveWordMap
sensitiveWordLen=0 #敏感词的长度
containChar_sensitiveWordLen=0 #包括特殊字符敏感词的长度
endFlag=False #结束标记位
for i in range(beginIndex,len(txt)):
char=txt[i]
if char in self.stopWordList:
containChar_sensitiveWordLen+=1
continue
nowMap=nowMap.get(char)
if nowMap != None:
sensitiveWordLen+=1
containChar_sensitiveWordLen+=1
#结束位置为True
if nowMap.get("isEnd")==1:
endFlag=True
else:
break
if endFlag==False:
containChar_sensitiveWordLen=0
#print(sensitiveWordLen)
return containChar_sensitiveWordLen
Part 4
getSensitiveWord function to get a list of sensitive words in the input text
def getSensitiveWord(self,txt):
cur_txt_sensitiveList=[]
#注意，并不是一个个char查找的，找到敏感词会i增强敏感词的长度
for i in range(len(txt)):
length=self.checkSensitiveWord(txt,i)
if length>0:
word=txt[i:i+length]
cur_txt_sensitiveList.append(word)
i=i+length-1
#出了循环还要+1 i+length是没有检测到的，
#下次直接从i+length开始
return cur_txt_sensitiveList
Part 5
replaceSensitiveWord function sensitive word replacement part
def replaceSensitiveWord(self,txt,replaceChar='*'):
Lst=self.getSensitiveWord(txt)
#print(Lst)
for word in Lst:
replaceStr=len(word)*replaceChar
txt=txt.replace(word,replaceStr)
return txt
Sensitive words and stop words can be customized. The
format is as follows
Complete code
#!/usr/bin/env python
#-*- coding:utf-8 -*-
# author:zbt
# datetime:2020-03-16 11:53
# software: PyCharm
Dir_sensitive='C:\\Users\\zbt\\Desktop\\X实习\\敏感词【ing】\\敏感词.txt'
Dir_stopWord='C:\\Users\\zbt\\Desktop\\X实习\\敏感词【ing】\\停用词.txt'
class SensitiveFilter:
def __init__(self):
# file把敏感词库加载到列表中
file = open(Dir_sensitive, 'r', encoding = 'ANSI')
file_lst = file.readlines()
self.sensitiveWordList = [i.split('\n')[0] for i in file_lst]
# print(sensitiveWordList[:10])
# >>['1234', '12345', '123456', '甲基麻黄碱', '来曲唑', '依西美坦', '阿那曲唑', '螺内酯', '沙美特罗', '丙磺舒']
# file1把停用词加载到列表中
file1 = open(Dir_stopWord, 'r', encoding = 'ANSI')
file1_lst = file1.readlines()
self.stopWordList = [i.split('\n')[0] for i in file1_lst]
##得到sensitive字典
self.sensitiveWordMap = self.initSensitiveWordMap(self.sensitiveWordList)
#构建敏感词库
def initSensitiveWordMap(self,sensitiveWordList):
sensitiveWordMap = {
}
# 读取每一行，每一个word都是一个敏感词
for word in sensitiveWordList:
nowMap=sensitiveWordMap
#遍历该敏感词的每一个特定字符
for i in range(len(word)):
keychar=word[i]
wordMap=nowMap.get(keychar)
if wordMap !=None:
#nowMap更新为下一层
nowMap=wordMap
else:
#不存在则构建一个map,isEnd设置为0，因为不是最后一个
newNextMap={
}
newNextMap["isEnd"]=0
nowMap[keychar]=newNextMap
nowMap=newNextMap
#到这个词末尾字符
if i==len(word)-1:
nowMap["isEnd"]=1
#print(sensitiveWordMap)
return sensitiveWordMap
def checkSensitiveWord(self,txt,beginIndex=0):
'''
:param txt: 输入待检测的文本
:param beginIndex:输入文本开始的下标
:return:返回敏感词字符的长度
'''
nowMap=self.sensitiveWordMap
sensitiveWordLen=0 #敏感词的长度
containChar_sensitiveWordLen=0 #包括特殊字符敏感词的长度
endFlag=False #结束标记位
for i in range(beginIndex,len(txt)):
char=txt[i]
if char in self.stopWordList:
containChar_sensitiveWordLen+=1
continue
nowMap=nowMap.get(char)
if nowMap != None:
sensitiveWordLen+=1
containChar_sensitiveWordLen+=1
#结束位置为True
if nowMap.get("isEnd")==1:
endFlag=True
else:
break
if endFlag==False:
containChar_sensitiveWordLen=0
#print(sensitiveWordLen)
return containChar_sensitiveWordLen
def getSensitiveWord(self,txt):
cur_txt_sensitiveList=[]
#注意，并不是一个个char查找的，找到敏感词会i增强敏感词的长度
for i in range(len(txt)):
length=self.checkSensitiveWord(txt,i)
if length>0:
word=txt[i:i+length]
cur_txt_sensitiveList.append(word)
i=i+length-1 #出了循环还要+1 i+length是没有检测到的，下次直接从i+length开始
return cur_txt_sensitiveList
def replaceSensitiveWord(self,txt,replaceChar='*'):
Lst=self.getSensitiveWord(txt)
#print(Lst)
for word in Lst:
replaceStr=len(word)*replaceChar
txt=txt.replace(word,replaceStr)
return txt
if __name__ == "__main__":
str="blablablabla"
Filter=SensitiveFilter()
replaceStr=Filter.replaceSensitiveWord(str)
print(replaceStr)
Finally, sensitive words and stop words are included for free
https://pan.baidu.com/s/1AftA45Zdz2_AtVJEuI5jHA
password
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