What

Brief

This is a standalone Min Priority Queue 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

How

install

npm

npm i min-priority-queue-typed --save

yarn

yarn add min-priority-queue-typed

snippet

Shortest job first scheduling

 const jobs = new MinPriorityQueue<number>();

    jobs.add(8);  // 8 seconds
    jobs.add(2);  // 2 seconds
    jobs.add(5);  // 5 seconds
    jobs.add(1);  // 1 second

    // Shortest job first
    console.log(jobs.poll()); // 1;
    console.log(jobs.poll()); // 2;
    console.log(jobs.poll()); // 5;
    console.log(jobs.poll()); // 8;

Event-driven simulation with timestamps

 interface Event {
      time: number;
      action: string;
    }

    const timeline = new MinPriorityQueue<Event>([], {
      comparator: (a, b) => a.time - b.time
    });

    timeline.add({ time: 300, action: 'Timeout' });
    timeline.add({ time: 100, action: 'Request received' });
    timeline.add({ time: 200, action: 'Processing done' });
    timeline.add({ time: 150, action: 'Cache hit' });

    const order = [];
    while (timeline.size > 0) {
      order.push(timeline.poll()!.action);
    }
    console.log(order); // [
 //      'Request received',
 //      'Cache hit',
 //      'Processing done',
 //      'Timeout'
 //    ];

Huffman coding frequency selection

 // Character frequencies for Huffman tree building
    const freq = new MinPriorityQueue<[number, string]>([], {
      comparator: (a, b) => a[0] - b[0]
    });

    freq.add([5, 'a']);
    freq.add([9, 'b']);
    freq.add([12, 'c']);
    freq.add([2, 'd']);

    // Always pick two lowest frequencies
    const first = freq.poll()!;
    const second = freq.poll()!;
    console.log(first[1]); // 'd';  // freq 2
    console.log(second[1]); // 'a'; // freq 5

    // Combined node goes back
    freq.add([first[0] + second[0], first[1] + second[1]]);
    console.log(freq.peek()![0]); // 7;

API docs & Examples

API Docs

Live Examples

Examples Repository

Data Structures

Data Structure	Unit Test	Performance Test	API Docs
Min Priority Queue			MinPriorityQueue

Standard library data structure comparison

Data Structure Typed	C++ STL	java.util	Python collections
PriorityQueue<E>	priority_queue<T>	PriorityQueue<E>	-

Benchmark

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.