208. Implement Trie (Prefix Tree)

A 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

Example 1:

• Input: ``
• Output: ``
• Explanation: 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 * 10^4 calls in total will be made to insert, search, and startsWith.

Approach

Solution

class TrieNode:
    def __init__(self):
        self.children = {}
        self.endOfWord = False


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

    def insert(self, word: str) -> None:
        cur = self.root

        for c in word:
            if c not in cur.children:
                cur.children[c] = TrieNode()
            cur = cur.children[c]
        cur.endOfWord = True

    def search(self, word: str) -> bool:
        cur = self.root

        for c in word:
            if c not in cur.children:
                return False
            cur = cur.children[c]

        return cur.endOfWord

    def startsWith(self, prefix: str) -> bool:
        cur = self.root

        for c in prefix:
            if c not in cur.children:
                return False
            cur = cur.children[c]

        return True


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

Explanation