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Description
tab: English
<p>A <a href="https://en.wikipedia.org/wiki/Trie" target="_blank"><strong>trie</strong></a> (pronounced as "try") or <strong>prefix tree</strong> is a tree data structure used to efficiently store and retrieve keys in a dataset of strings. There are various applications of this data structure, such as autocomplete and spellchecker.</p>
<p>Implement the Trie class:</p>
<ul>
<li><code>Trie()</code> Initializes the trie object.</li>
<li><code>void insert(String word)</code> Inserts the string <code>word</code> into the trie.</li>
<li><code>boolean search(String word)</code> Returns <code>true</code> if the string <code>word</code> is in the trie (i.e., was inserted before), and <code>false</code> otherwise.</li>
<li><code>boolean startsWith(String prefix)</code> Returns <code>true</code> if there is a previously inserted string <code>word</code> that has the prefix <code>prefix</code>, and <code>false</code> otherwise.</li>
</ul>
<p> </p>
<p><strong class="example">Example 1:</strong></p>
<pre>
<strong>Input</strong>
["Trie", "insert", "search", "search", "startsWith", "insert", "search"]
[[], ["apple"], ["apple"], ["app"], ["app"], ["app"], ["app"]]
<strong>Output</strong>
[null, null, true, false, true, null, true]
<strong>Explanation</strong>
Trie trie = new Trie();
trie.insert("apple");
trie.search("apple"); // return True
trie.search("app"); // return False
trie.startsWith("app"); // return True
trie.insert("app");
trie.search("app"); // return True
</pre>
<p> </p>
<p><strong>Constraints:</strong></p>
<ul>
<li><code>1 <= word.length, prefix.length <= 2000</code></li>
<li><code>word</code> and <code>prefix</code> consist only of lowercase English letters.</li>
<li>At most <code>3 * 10<sup>4</sup></code> calls <strong>in total</strong> will be made to <code>insert</code>, <code>search</code>, and <code>startsWith</code>.</li>
</ul>
---
[submissions](https://leetcode.com/problems/implement-trie-prefix-tree/submissions/) | [solutions](https://leetcode.com/problems/implement-trie-prefix-tree/solutions/)
tab: 中文
<p><strong><a href="https://baike.baidu.com/item/字典树/9825209?fr=aladdin" target="_blank">Trie</a></strong>（发音类似 "try"）或者说 <strong>前缀树</strong> 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。</p>
<p>请你实现 Trie 类：</p>
<ul>
<li><code>Trie()</code> 初始化前缀树对象。</li>
<li><code>void insert(String word)</code> 向前缀树中插入字符串 <code>word</code> 。</li>
<li><code>boolean search(String word)</code> 如果字符串 <code>word</code> 在前缀树中，返回 <code>true</code>（即，在检索之前已经插入）；否则，返回 <code>false</code> 。</li>
<li><code>boolean startsWith(String prefix)</code> 如果之前已经插入的字符串 <code>word</code> 的前缀之一为 <code>prefix</code> ，返回 <code>true</code> ；否则，返回 <code>false</code> 。</li>
</ul>
<p> </p>
<p><strong>示例：</strong></p>
<pre>
<strong>输入</strong>
["Trie", "insert", "search", "search", "startsWith", "insert", "search"]
[[], ["apple"], ["apple"], ["app"], ["app"], ["app"], ["app"]]
<strong>输出</strong>
[null, null, true, false, true, null, true]
<strong>解释</strong>
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
</pre>
<p> </p>
<p><strong>提示：</strong></p>
<ul>
<li><code>1 <= word.length, prefix.length <= 2000</code></li>
<li><code>word</code> 和 <code>prefix</code> 仅由小写英文字母组成</li>
<li><code>insert</code>、<code>search</code> 和 <code>startsWith</code> 调用次数 <strong>总计</strong> 不超过 <code>3 * 10<sup>4</sup></code> 次</li>
</ul>
---
[提交记录](https://leetcode.cn/problems/implement-trie-prefix-tree/submissions/) | [题解](https://leetcode.cn/problems/implement-trie-prefix-tree/solution/)
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