Trie即前缀树或字典树,利用字符串公共前缀降低搜索时间。速度为O(k),k为输入的字符串长度。
1.采用defaultdict创建trie
from collections import defaultdict
from functools import reduce
TrieNode = lambda: defaultdict(TrieNode)
class Trie:
def __init__(self):
self.trie = TrieNode()
def insert(self, word):
reduce(dict.__getitem__, word, self.trie)['end'] = True
def search(self, word):
return reduce(lambda d,k: d[k] if k in d else TrieNode(), word, self.trie).get('end', False)
def startsWith(self, word):
return bool(reduce(lambda d,k: d[k] if k in d else TrieNode(), word, self.trie).keys())
2.采用dictionary结构
#定义trie结构体
class TrieNode(object):
def __init__(self):
"""
Initialize your data structure here.
"""
self.data = {}
self.is_word = False
class Trie(object):
def __init__(self):
self.root = TrieNode()
def insert(self, word):
"""
Inserts a word into the trie.
:type word: str
:rtype: void
"""
node = self.root
for letter in word:
child = node.data.get(letter)
if not child:
node.data[letter] = TrieNode()
node = node.data[letter]
node.is_word = True
def search(self, word):
"""
Returns if the word is in the trie.
:type word: str
:rtype: bool
"""
node = self.root
for letter in word:
node = node.data.get(letter)
if not node:
return False
return node.is_word # 判断单词是否是完整的存在在trie树中
def starts_with(self, prefix):
"""
Returns if there is any word in the trie
that starts with the given prefix.
:type prefix: str
:rtype: bool
"""
node = self.root
for letter in prefix:
node = node.data.get(letter)
if not node:
return False
return True
def get_start(self, prefix):
"""
Returns words started with prefix
:param prefix:
:return: words (list)
"""
def _get_key(pre, pre_node):
words_list = []
if pre_node.is_word:
words_list.append(pre)
for x in pre_node.data.keys():
words_list.extend(_get_key(pre + str(x), pre_node.data.get(x)))
return words_list
words = []
if not self.starts_with(prefix):
return words
if self.search(prefix):
words.append(prefix)
return words
node = self.root
for letter in prefix:
node = node.data.get(letter)
return _get_key(prefix, node)