Implement Trie (Prefix Tree)

Problem

https://leetcode.com/problems/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.

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 * 10:sup:`4` calls in total will be made to insert, search, and startsWith.

Pattern

Hash Table, String, Design, Trie

Approaches

Hash Map Children

Code

class TrieNode:

    def __init__(self, char, end_of_word=False):
        self.char = char
        self.end_of_word = end_of_word
        self.children = {}


class Trie:

    def __init__(self):
        self.root = TrieNode("<start_of_word>")

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

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

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

Test

>>> from implement_trie_prefix_tree__hash_map_children import Trie
>>> t = Trie()
>>> t.insert("apple")
>>> t.search("apple")
True
>>> t.search("app")
False
>>> t.startsWith("app")
True
>>> t.insert("app")
>>> t.search("app")
True

class implement_trie_prefix_tree__hash_map_children.TrieNode(char, end_of_word=False)

Bases: object

class implement_trie_prefix_tree__hash_map_children.Trie

Bases: object

insert(word: str) → None

search(word: str) → bool

startsWith(prefix: str) → bool