LeetCode - 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 * 104 calls in total will be made to insert, search, and startsWith.

 

My Solution:

class Trie:

    def __init__(self):
        self.words = set()


    def insert(self, word: str) -> None:
        self.words.add(word)


    def search(self, word: str) -> bool:
        return word in self.words


    def startsWith(self, prefix: str) -> bool:
        for word in self.words:
            if word.startswith(prefix):
                return True
        
        return False



# 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)

 

 

ChatGPT's Solution:

class TrieNode:
    def __init__(self):
        # Each node stores a dictionary of children and a boolean for end of word.
        self.children = {}
        self.is_end_of_word = False


class Trie:

    def __init__(self):
        # Initialize the trie with a root node.
        self.root = TrieNode()


    def insert(self, word: str) -> None:
        # Insert a word into the trie.
        node = self.root
        for char in word:
            if char not in node.children:
                node.children[char] = TrieNode()
            node = node.children[char]
        node.is_end_of_word = True


    def search(self, word: str) -> bool:
        # Return true if the word is in the trie, otherwise false.
        node = self.root
        for char in word:
            if char not in node.children:
                return False
            node = node.children[char]
        return node.is_end_of_word


    def startsWith(self, prefix: str) -> bool:
        # Return true if there is a word in the trie that starts with the given prefix.
        node = self.root
        for char in prefix:
            if char not in node.children:
                return False
            node = node.children[char]
        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:

1. TrieNode class:

   • It has a dictionary children to store the next characters of the word.

   • is_end_of_word is a boolean flag to indicate whether the current node marks the end of a word.

2. Trie class:

   • insert(word): This method inserts a word into the trie. It traverses the trie, adding new nodes if necessary.

   • search(word): This method checks if the word exists in the trie by traversing through the nodes.

   • startsWith(prefix): This method checks if any word in the trie starts with the given prefix.

Example Usage:

trie = Trie()
trie.insert("apple")
print(trie.search("apple"))  # Returns True
print(trie.search("app"))    # Returns False
print(trie.startsWith("app"))  # Returns True
trie.insert("app")
print(trie.search("app"))    # Returns True