50. 实现 Trie (前缀树).md

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，例如自动补完和拼写检查。

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

class TrieNode():
    def __init__(self, val=None):
        self.val = val
        self.isEnd = False
        self.children = {}

class Trie:
    def __init__(self):
        self.root = TrieNode()

    def insert(self, word: str) -> None:
        cur_node = self.root
        for c in word:
            if c not in cur_node.children:
                cur_node.children[c] = TrieNode(c)
            cur_node = cur_node.children[c]
        cur_node.isEnd = True

    def search(self, word: str) -> bool:
        cur_node = self.root
        for c in word:
            if c not in cur_node.children:
                return False
            cur_node = cur_node.children[c]
        return cur_node.isEnd

    def startsWith(self, prefix: str) -> bool:
        cur_node = self.root
        for c in prefix:
            if c not in cur_node.children:
                return False
            cur_node = cur_node.children[c]
        return True