A simple implementation of the Trie (Prefix Tree) data structure in JavaScript. This repository demonstrates how to create a trie class with essential methods and explains its functionality with practical examples.
A Trie, also known as a Prefix Tree, is a tree-like data structure used to store strings in a way that allows for efficient searching, insertion, and deletion of words, especially when dealing with large sets of strings. Each node represents a single character of a word, and words are stored along paths from the root to the leaves. It is particularly useful for tasks like autocomplete, spell checking, and IP routing.
- Insert: Add a word to the trie.
- Search: Check if a word exists in the trie.
- StartsWith: Check if there is any word in the trie that starts with a given prefix.
- Delete: Remove a word from the trie.
Here’s the JavaScript implementation of the trie:
class TrieNode {
constructor() {
this.children = {}; // Stores child nodes
this.isEndOfWord = false; // Marks if it's the end of a word
}
}
class Trie {
constructor() {
this.root = new TrieNode(); // Root of the trie
}
// Insert a word into the trie
insert(word) {
let currentNode = this.root;
for (let char of word) {
if (!currentNode.children[char]) {
currentNode.children[char] = new TrieNode();
}
currentNode = currentNode.children[char];
}
currentNode.isEndOfWord = true;
}
// Search for a word in the trie
search(word) {
let currentNode = this.root;
for (let char of word) {
if (!currentNode.children[char]) {
return false;
}
currentNode = currentNode.children[char];
}
return currentNode.isEndOfWord;
}
// Check if any word in the trie starts with the given prefix
startsWith(prefix) {
let currentNode = this.root;
for (let char of prefix) {
if (!currentNode.children[char]) {
return false;
}
currentNode = currentNode.children[char];
}
return true;
}
// Delete a word from the trie
delete(word) {
this.deleteHelper(this.root, word, 0);
}
// Helper function to delete a word
deleteHelper(node, word, index) {
if (index === word.length) {
if (!node.isEndOfWord) return false;
node.isEndOfWord = false;
return Object.keys(node.children).length === 0;
}
const char = word[index];
if (!node.children[char]) return false;
const shouldDeleteCurrentNode = this.deleteHelper(node.children[char], word, index + 1);
if (shouldDeleteCurrentNode) {
delete node.children[char];
return Object.keys(node.children).length === 0;
}
return false;
}
}// Initialize the trie
const trie = new Trie();
// Insert words into the trie
trie.insert("apple");
trie.insert("app");
// Search for words
console.log(trie.search("apple")); // Output: true
console.log(trie.search("app")); // Output: true
console.log(trie.search("appl")); // Output: false
// Check if any word starts with a given prefix
console.log(trie.startsWith("app")); // Output: true
console.log(trie.startsWith("appl")); // Output: true
console.log(trie.startsWith("banana")); // Output: false
// Delete a word from the trie
trie.delete("app");
console.log(trie.search("app")); // Output: false
console.log(trie.search("apple")); // Output: true- Autocomplete: Suggesting words based on a prefix.
- Spell Checking: Finding correct spelling suggestions.
- IP Routing: Efficient routing for network addresses.
- Dictionary Implementation: Storing a dictionary for fast word lookups.
Want to see a quick tutorial on how to build this? Check out this TikTok video:
- Clone the repository:
git clone /~https://github.com/fix2015/structure_trie cd structure_trie - Open the file
index.jsin your favorite code editor. - Run the file using Node.js:
node index.js
Contributions are welcome! If you have suggestions or want to add new features, feel free to create a pull request.
This project is licensed under the MIT License.
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