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Kotlin-based LeetCode algorithm problem solutions, regularly updated
208\. Implement Trie (Prefix Tree)
Medium
A [**trie**](https://en.wikipedia.org/wiki/Trie) (pronounced as "try") or **prefix tree** 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.
Implement the Trie class:
* `Trie()` Initializes the trie object.
* `void insert(String word)` Inserts the string `word` into the trie.
* `boolean search(String word)` Returns `true` if the string `word` is in the trie (i.e., was inserted before), and `false` otherwise.
* `boolean startsWith(String prefix)` Returns `true` if there is a previously inserted string `word` that has the prefix `prefix`, and `false` otherwise.
**Example 1:**
**Input** ["Trie", "insert", "search", "search", "startsWith", "insert", "search"] [[], ["apple"], ["apple"], ["app"], ["app"], ["app"], ["app"]]
**Output:** [null, null, true, false, true, null, true]
**Explanation:**
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
**Constraints:**
* `1 <= word.length, prefix.length <= 2000`
* `word` and `prefix` consist only of lowercase English letters.
* At most 3 * 104
calls **in total** will be made to `insert`, `search`, and `startsWith`.