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教你如何实现Python 过滤敏感词

一个简单的实现

主要是通过循环和replace的方式进行敏感词的替换

class NaiveFilter():
'''Filter Messages from keywords
very simple filter implementation
>>> f = NaiveFilter()
>>> f.parse("filepath")
>>> f.filter("hello sexy baby")
hello **** baby
'''
def __init__(self):
self.keywords = set([])
def parse(self, path):
for keyword in open(path):
self.keywords.add(keyword.strip().decode('utf-8').lower())
def filter(self, message, repl="*"):
message = str(message).lower()
for kw in self.keywords:
message = message.replace(kw, repl)
return message
使用BSF(宽度优先搜索)进行实现

对于搜索查找进行了优化,对于英语单词,直接进行了按词索引字典查找。对于其他语言模式,我们采用逐字符查找匹配的一种模式。

BFS:宽度优先搜索方式

class BSFilter:
'''Filter Messages from keywords
Use Back Sorted Mapping to reduce replacement times
>>> f = BSFilter()
>>> f.add("sexy")
>>> f.filter("hello sexy baby")
hello **** baby
'''
def __init__(self):
self.keywords = []
self.kwsets = set([])
self.bsdict = defaultdict(set)
self.pat_en = re.compile(r'^[0-9a-zA-Z]+$')  # english phrase or not
def add(self, keyword):
if not isinstance(keyword, str):
keyword = keyword.decode('utf-8')
keyword = keyword.lower()
if keyword not in self.kwsets:
self.keywords.append(keyword)
self.kwsets.add(keyword)
index = len(self.keywords) - 1
for word in keyword.split():
if self.pat_en.search(word):
self.bsdict[word].add(index)
else:
for char in word:
self.bsdict[char].add(index)
def parse(self, path):
with open(path, "r") as f:
for keyword in f:
self.add(keyword.strip())
def filter(self, message, repl="*"):
if not isinstance(message, str):
message = message.decode('utf-8')
message = message.lower()
for word in message.split():
if self.pat_en.search(word):
for index in self.bsdict[word]:
message = message.replace(self.keywords[index], repl)
else:
for char in word:
for index in self.bsdict[char]:
message = message.replace(self.keywords[index], repl)
return message
使用DFA(Deterministic Finite Automaton)进行实现

DFA即Deterministic Finite Automaton,也就是确定有穷自动机。

使用了嵌套的字典来实现。

 class DFAFilter():
'''Filter Messages from keywords
Use DFA to keep algorithm perform constantly
>>> f = DFAFilter()
>>> f.add("sexy")
>>> f.filter("hello sexy baby")
hello **** baby
'''
def __init__(self):
self.keyword_chains = {}
self.delimit = '\x00'
def add(self, keyword):
if not isinstance(keyword, str):
keyword = keyword.decode('utf-8')
keyword = keyword.lower()
chars = keyword.strip()
if not chars:
return
level = self.keyword_chains
for i in range(len(chars)):
if chars[i] in level:
level = level[chars[i]]
else:
if not isinstance(level, dict):
break
for j in range(i, len(chars)):
level[chars[j]] = {}
last_level, last_char = level, chars[j]
level = level[chars[j]]
last_level[last_char] = {self.delimit: 0}
break
if i == len(chars) - 1:
level[self.delimit] = 0
def parse(self, path):
with open(path,encoding='UTF-8') as f:
for keyword in f:
self.add(keyword.strip())
def filter(self, message, repl="*"):
if not isinstance(message, str):
message = message.decode('utf-8')
message = message.lower()
ret = []
start = 0
while start

到此这篇关于Python 敏感词过滤的实现示例的文章就介绍到这了。

炫意HTML5 » 教你如何实现Python 过滤敏感词

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