[Python知识库]小黑模块代码分析:Tire Tree

示意图:

import collections

# Tire结点
class TireNode(object):
    def __init__(self):
        self.children = collections.defaultdict(TireNode)
        self.is_word = False
        
# Tire Tree
class Tire(object):
    def __init__(self):
        self.root = TireNode()
        
    def insert(self,word):
        current = self.root
        for char in word:
            # defaultdict的索引操作:
            # 1.key在defaultdict时:return current.children[key]
            # 2.key不在defaultdict时,分为两步:
            # (1) current.children[key] = TireNode()
            # (2) return current.children[key]
            current = current.children[char]
        #标记位变为True,表明从根节点到这里是一个词
        current.is_word = True
    
    def search(self,word):
        current = self.root
        for char in word:
            current = current.children.get(char)
            # 词典里没有该前缀的词语
            if not current:
                return False
        # 判断是否是一个合法词语
        return current.is_word
    
    def startsWith(self,word):
        current = self.root
        for char in word:
            current = current.children.get(char)
            # 词典里没有该前缀的词语
            if not current:
                return False
        return True
    
    # 匹配过程:
    # 南京长江大桥
    # 南京长江大
    # ...
    # 南
    def enumerateMatch(self,sentence,space = '_'):
        current = self.root
        sentence = list(sentence)
        matched = []
        # 依次从后向前匹配
        while len(sentence) - 1:
            if self.search(sentence):
                matched.append('_'.join(sentence))
            del sentence[-1]
        return matched    
        
            
t = Tire()
gazetteer = ['南京', '南京市', '市长', '长江', '长江大桥', '大桥']
for gaz in gazetteer:
    t.insert(gaz)
# 测试insert与search:
matchs = ['南京', '南京市', '市长', '长江', '长江大桥', '大桥','江大桥','小黑']
print('###测试insert与search:\n')
for match in matchs:
    print(match,':',t.search(match))

words = ['南', '京', '市', '长', '江', '大', '桥']
print('###测试enumerateMatch:\n')
print(t.enumerateMatch(words))

print('###应用Tire Tree,找到每一个char的对应的word:\n')
words = ['南', '京', '市', '长', '江', '大', '桥']
matched = []
for _ in range(len(words)):
    matched.append([])

for index in range(len(words)):
    current_word = words[index:]
    print(index,''.join(current_word),end = ':')
    result = t.enumerateMatch(current_word)
    for res in result:
        matched[index + len(res.split('_')) - 1].append(res)
    print(' ',result)
print('matched:',matched)

输出:

###测试insert与search:

南京 : True
南京市 : True
市长 : True
长江 : True
长江大桥 : True
大桥 : True
江大桥 : False
小黑 : False
###测试enumerateMatch:

[‘南_京_市’, ‘南_京’]
###应用Tire Tree,找到每一个char的对应的word:

0 南京市长江大桥: [‘南_京_市’, ‘南_京’]
1 京市长江大桥: []
2 市长江大桥: [‘市_长’]
3 长江大桥: [‘长_江_大_桥’, ‘长_江’]
4 江大桥: []
5 大桥: [‘大_桥’]
6 桥: []
matched: [[], [‘南_京’], [‘南_京_市’], [‘市_长’], [‘长_江’], [], [‘长_江_大_桥’, ‘大_桥’]]