M208.实现Trie(前缀树)
OOP,字典树,https://leetcode.cn/problems/implement-trie-prefix-tree/
Trie(发音类似 "try")或者说 前缀树 是一种树形数据结构,用于高效地存储和检索字符串数据集中的键。这一数据结构有相当多的应用情景,例如自动补全和拼写检查。
请你实现 Trie 类:
Trie()初始化前缀树对象。void insert(String word)向前缀树中插入字符串word。boolean search(String word)如果字符串word在前缀树中,返回true(即,在检索之前已经插入);否则,返回false。boolean startsWith(String prefix)如果之前已经插入的字符串word的前缀之一为prefix,返回true;否则,返回false。
示例:
输入
["Trie", "insert", "search", "search", "startsWith", "insert", "search"]
[[], ["apple"], ["apple"], ["app"], ["app"], ["app"], ["app"]]
输出
[null, null, true, false, true, null, true]
解释
Trie trie = new Trie();
trie.insert("apple");
trie.search("apple"); // 返回 True
trie.search("app"); // 返回 False
trie.startsWith("app"); // 返回 True
trie.insert("app");
trie.search("app"); // 返回 True提示:
1 <= word.length, prefix.length <= 2000word和prefix仅由小写英文字母组成insert、search和startsWith调用次数 总计 不超过3 * 10^4次
python
class Trie:
def __init__(self):
"""
Initialize your data structure here.
"""
self.root = {}
self.end_of_word = "#"
def insert(self, word: str) -> None:
"""
Inserts a word into the trie.
"""
node = self.root
for char in word:
node = node.setdefault(char, {}) #returns the value of the item with the specified key.
# If the key does not exist, insert the key, with the specified value
node[self.end_of_word] = self.end_of_word
def search(self, word: str) -> bool:
"""
Returns if the word is in the trie.
"""
node = self.root
for char in word:
if char not in node:
return False
node = node[char]
return self.end_of_word in node
def startsWith(self, prefix: str) -> bool:
"""
Returns if there is any word in the trie that starts with the given prefix.
"""
node = self.root
for char in prefix:
if char not in node:
return False
node = node[char]
return True
if __name__ == "__main__":
trie = Trie()
trie.insert("apple")
print(trie.search("apple")) # return True
print(trie.search("app")) # return False
print(trie.startsWith("app")) # return True
trie.insert("app")
print(trie.search("app")) # return True