This is a standalone Trie data structure from the data-structure-typed collection. If you wish to access more data
structures or advanced features, you can transition to directly installing the
complete data-structure-typed package
Autocomplete: Prefix validation and checking
const autocomplete = new Trie<string>(['gmail.com', 'gmail.co.nz', 'gmail.co.jp', 'yahoo.com', 'outlook.com']);
// Get all completions for a prefix
const gmailCompletions = autocomplete.getWords('gmail');
console.log(gmailCompletions); // ['gmail.com', 'gmail.co.nz', 'gmail.co.jp']
File System Path Operations
const fileSystem = new Trie<string>([
'/home/user/documents/file1.txt',
'/home/user/documents/file2.txt',
'/home/user/pictures/photo.jpg',
'/home/user/pictures/vacation/',
'/home/user/downloads'
]);
// Find common directory prefix
console.log(fileSystem.getLongestCommonPrefix()); // '/home/user/'
// List all files in a directory
const documentsFiles = fileSystem.getWords('/home/user/documents/');
console.log(documentsFiles); // ['/home/user/documents/file1.txt', '/home/user/documents/file2.txt']
Autocomplete: Basic word suggestions
// Create a trie for autocomplete
const autocomplete = new Trie<string>([
'function',
'functional',
'functions',
'class',
'classes',
'classical',
'closure',
'const',
'constructor'
]);
// Test autocomplete with different prefixes
console.log(autocomplete.getWords('fun')); // ['functional', 'functions', 'function']
console.log(autocomplete.getWords('cla')); // ['classes', 'classical', 'class']
console.log(autocomplete.getWords('con')); // ['constructor', 'const']
// Test with non-matching prefix
console.log(autocomplete.getWords('xyz')); // []
Dictionary: Case-insensitive word lookup
// Create a case-insensitive dictionary
const dictionary = new Trie<string>([], { caseSensitive: false });
// Add words with mixed casing
dictionary.add('Hello');
dictionary.add('WORLD');
dictionary.add('JavaScript');
// Test lookups with different casings
console.log(dictionary.has('hello')); // true
console.log(dictionary.has('HELLO')); // true
console.log(dictionary.has('Hello')); // true
console.log(dictionary.has('javascript')); // true
console.log(dictionary.has('JAVASCRIPT')); // true
// Add IP address prefixes and their corresponding routes
const routes = {
'192.168.1': 'LAN_SUBNET_1',
'192.168.2': 'LAN_SUBNET_2',
'10.0.0': 'PRIVATE_NETWORK_1',
'10.0.1': 'PRIVATE_NETWORK_2'
};
const ipRoutingTable = new Trie<string>(Object.keys(routes));
// Check IP address prefix matching
console.log(ipRoutingTable.hasPrefix('192.168.1')); // true
console.log(ipRoutingTable.hasPrefix('192.168.2')); // true
// Validate IP address belongs to subnet
const ip = '192.168.1.100';
const subnet = ip.split('.').slice(0, 3).join('.');
console.log(ipRoutingTable.hasPrefix(subnet)); // true
API Docs
Live Examples
Examples Repository
Data Structure |
Unit Test |
Performance Test |
API Docs |
Trie |
|
|
Trie |
Standard library data structure comparison
Data Structure Typed |
C++ STL |
java.util |
Python collections |
Trie |
- |
- |
- |
trie
test name |
time taken (ms) |
executions per sec |
sample deviation |
100,000 push |
45.97 |
21.76 |
0.00 |
100,000 getWords |
66.20 |
15.11 |
0.00 |
Built-in classic algorithms
Algorithm |
Function Description |
Iteration Type |
Software Engineering Design Standards
Principle |
Description |
Practicality |
Follows ES6 and ESNext standards, offering unified and considerate optional parameters, and simplifies method names. |
Extensibility |
Adheres to OOP (Object-Oriented Programming) principles, allowing inheritance for all data structures. |
Modularization |
Includes data structure modularization and independent NPM packages. |
Efficiency |
All methods provide time and space complexity, comparable to native JS performance. |
Maintainability |
Follows open-source community development standards, complete documentation, continuous integration, and adheres to TDD (Test-Driven Development) patterns. |
Testability |
Automated and customized unit testing, performance testing, and integration testing. |
Portability |
Plans for porting to Java, Python, and C++, currently achieved to 80%. |
Reusability |
Fully decoupled, minimized side effects, and adheres to OOP. |
Security |
Carefully designed security for member variables and methods. Read-write separation. Data structure software does not need to consider other security aspects. |
Scalability |
Data structure software does not involve load issues. |