0208. 实现 Trie (前缀树)

题目地址(208. 实现 Trie (前缀树))

https://leetcode-cn.com/problems/implement-trie-prefix-tree/

题目描述

实现一个 Trie (前缀树)，包含 insert, search, 和 startsWith 这三个操作。

示例:

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
说明:

你可以假设所有的输入都是由小写字母 a-z 构成的。
保证所有输入均为非空字符串。

前置知识

前缀树

公司

阿里
腾讯
百度
字节

思路

这是一道很直接的题目，上来就让你实现前缀树（字典树）。这算是基础数据结构中的知识了，不清楚什么是字典树的可以查阅相关资料。

我们看到题目给出的使用方法new Trie, insert,search和startWith.

为了区分search和startWith我们需要增加一个标示来区分当前节点是否是某个单词的结尾。因此节点的数据结构应该是:

function TrieNode(val) {
  this.val = val; // 当前的字母
  this.children = []; // 题目要求字典仅有a-z，那么其长度最大为26（26个字母）
  this.isWord = false;
}

每次 insert 我们其实都是从根节点出发，一个一个找到我们需要添加的节点，修改 children 的值.

我们应该修改哪一个 child 呢？我们需要一个函数来计算索引

function computeIndex(c) {
  return c.charCodeAt(0) - "a".charCodeAt(0);
}

其实不管 insert， search 和 startWith 的逻辑都是差不多的，都是从 root 出发，找到我们需要操作的 child，然后进行相应操作（添加，修改，返回）。

关键点解析

前缀树

代码

/*
 * @lc app=leetcode id=208 lang=javascript
 *
 * [208] Implement Trie (Prefix Tree)
 *
 * https://leetcode.com/problems/implement-trie-prefix-tree/description/
 *
 * algorithms
 * Medium (36.93%)
 * Total Accepted:    172K
 * Total Submissions: 455.5K
 * Testcase Example:  '["Trie","insert","search","search","startsWith","insert","search"]\n[[],["apple"],["apple"],["app"],["app"],["app"],["app"]]'
 *
 * Implement a trie with insert, search, and startsWith methods.
 *
 * Example:
 *
 *
 * Trie trie = new Trie();
 *
 * trie.insert("apple");
 * trie.search("apple");   // returns true
 * trie.search("app");     // returns false
 * trie.startsWith("app"); // returns true
 * trie.insert("app");
 * trie.search("app");     // returns true
 *
 *
 * Note:
 *
 *
 * You may assume that all inputs are consist of lowercase letters a-z.
 * All inputs are guaranteed to be non-empty strings.
 *
 *
 */
function TrieNode(val) {
  this.val = val;
  this.children = [];
  this.isWord = false;
}

function computeIndex(c) {
  return c.charCodeAt(0) - "a".charCodeAt(0);
}
/**
 * Initialize your data structure here.
 */
var Trie = function () {
  this.root = new TrieNode(null);
};

/**
 * Inserts a word into the trie.
 * @param {string} word
 * @return {void}
 */
Trie.prototype.insert = function (word) {
  let ws = this.root;
  for (let i = 0; i < word.length; i++) {
    const c = word[i];
    const current = computeIndex(c);
    if (!ws.children[current]) {
      ws.children[current] = new TrieNode(c);
    }
    ws = ws.children[current];
  }
  ws.isWord = true;
};

/**
 * Returns if the word is in the trie.
 * @param {string} word
 * @return {boolean}
 */
Trie.prototype.search = function (word) {
  let ws = this.root;
  for (let i = 0; i < word.length; i++) {
    const c = word[i];
    const current = computeIndex(c);
    if (!ws.children[current]) return false;
    ws = ws.children[current];
  }
  return ws.isWord;
};

/**
 * Returns if there is any word in the trie that starts with the given prefix.
 * @param {string} prefix
 * @return {boolean}
 */
Trie.prototype.startsWith = function (prefix) {
  let ws = this.root;
  for (let i = 0; i < prefix.length; i++) {
    const c = prefix[i];
    const current = computeIndex(c);
    if (!ws.children[current]) return false;
    ws = ws.children[current];
  }
  return true;
};

/**
 * Your Trie object will be instantiated and called as such:
 * var obj = new Trie()
 * obj.insert(word)
 * var param_2 = obj.search(word)
 * var param_3 = obj.startsWith(prefix)
 */

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/* * @lc app=leetcode id=208 lang=javascript * * [208] Implement Trie (Prefix Tree) * * https://leetcode.com/problems/implement-trie-prefix-tree/description/ * * algorithms * Medium (36.93%) * Total Accepted: 172K * Total Submissions: 455.5K * Testcase Example: '["Trie","insert","search","search","startsWith","insert","search"]\n[[],["apple"],["apple"],["app"],["app"],["app"],["app"]]' * * Implement a trie with insert, search, and startsWith methods. * * Example: * * * Trie trie = new Trie(); * * trie.insert("apple"); * trie.search("apple"); // returns true * trie.search("app"); // returns false * trie.startsWith("app"); // returns true * trie.insert("app"); * trie.search("app"); // returns true * * * Note: * * * You may assume that all inputs are consist of lowercase letters a-z. * All inputs are guaranteed to be non-empty strings. * * */ function TrieNode(val) { this.val = val; this.children = []; this.isWord = false; } function computeIndex(c) { return c.charCodeAt(0) - "a".charCodeAt(0); } /** * Initialize your data structure here. */ var Trie = function () { this.root = new TrieNode(null); }; /** * Inserts a word into the trie. * @param {string} word * @return {void} */ Trie.prototype.insert = function (word) { let ws = this.root; for (let i = 0; i < word.length; i++) { const c = word[i]; const current = computeIndex(c); if (!ws.children[current]) { ws.children[current] = new TrieNode(c); } ws = ws.children[current]; } ws.isWord = true; }; /** * Returns if the word is in the trie. * @param {string} word * @return {boolean} */ Trie.prototype.search = function (word) { let ws = this.root; for (let i = 0; i < word.length; i++) { const c = word[i]; const current = computeIndex(c); if (!ws.children[current]) return false; ws = ws.children[current]; } return ws.isWord; }; /** * Returns if there is any word in the trie that starts with the given prefix. * @param {string} prefix * @return {boolean} */ Trie.prototype.startsWith = function (prefix) { let ws = this.root; for (let i = 0; i < prefix.length; i++) { const c = prefix[i]; const current = computeIndex(c); if (!ws.children[current]) return false; ws = ws.children[current]; } return true; }; /** * Your Trie object will be instantiated and called as such: * var obj = new Trie() * obj.insert(word) * var param_2 = obj.search(word) * var param_3 = obj.startsWith(prefix) */