priority-queue-typed

What

Brief

This is a standalone 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 priority-queue-typed --save

yarn

yarn add priority-queue-typed

methods

Priority Queue Min Priority Queue Max Priority Queue

snippet

TS

    import {PriorityQueue, MinPriorityQueue} from 'data-structure-typed';
    // /* or if you prefer */ import {PriorityQueue, MinPriorityQueue} from 'priority-queue-typed';

    const minPQ = new PriorityQueue<number>({nodes: [5, 2, 3, 4, 6, 1], comparator: (a, b) => a - b});
    minPQ.toArray()             //  [1, 2, 3, 4, 6, 5]
    minPQ.poll();
    minPQ.poll();
    minPQ.poll();
    minPQ.toArray()             //  [4, 5, 6]
    minPQ.peek()                //  4
    PriorityQueue.heapify({
        nodes: [3, 2, 1, 5, 6, 7, 8, 9, 10],
        comparator: (a, b) => a - b
    }).toArray()                //  [1, 2, 3, 5, 6, 7, 8, 9, 10]

    const priorityQueue = new MinPriorityQueue<number>();
    priorityQueue.add(5);
    priorityQueue.add(3);
    priorityQueue.add(7);
    priorityQueue.add(1);
    const sortedArray = priorityQueue.sort(); //  [1, 3, 5, 7]);

    const minPQ1 = new PriorityQueue<number>({nodes: [2, 5, 8, 3, 1, 6, 7, 4], comparator: (a, b) => a - b});
    const clonedPriorityQueue = minPQ1.clone();
    clonedPriorityQueue.getNodes()  //  minPQ1.getNodes()
    clonedPriorityQueue.sort()      //  [1, 2, 3, 4, 5, 6, 7, 8]
    minPQ1.DFS('in')                //  [4, 3, 2, 5, 1, 8, 6, 7]
    minPQ1.DFS('post')              //  [4, 3, 5, 2, 8, 7, 6, 1]
    minPQ1.DFS('pre')               //  [1, 2, 3, 4, 5, 6, 8, 7]

JS

    const {PriorityQueue, MinPriorityQueue} = require('data-structure-typed');
    // /* or if you prefer */ const {PriorityQueue, MinPriorityQueue} = require('priority-queue-typed');

    const minPQ = new PriorityQueue({nodes: [5, 2, 3, 4, 6, 1], comparator: (a, b) => a - b});
    minPQ.toArray()             //  [1, 2, 3, 4, 6, 5]
    minPQ.poll();
    minPQ.poll();
    minPQ.poll();
    minPQ.toArray()             //  [4, 5, 6]
    minPQ.peek()                //  4
    PriorityQueue.heapify({
        nodes: [3, 2, 1, 5, 6, 7, 8, 9, 10],
        comparator: (a, b) => a - b
    }).toArray()                //  [1, 2, 3, 5, 6, 7, 8, 9, 10]
    
    const priorityQueue = new MinPriorityQueue();
    priorityQueue.add(5);
    priorityQueue.add(3);
    priorityQueue.add(7);
    priorityQueue.add(1);
    const sortedArray = priorityQueue.sort(); //  [1, 3, 5, 7]);
    
    const minPQ1 = new PriorityQueue<number>({nodes: [2, 5, 8, 3, 1, 6, 7, 4], comparator: (a, b) => a - b});
    const clonedPriorityQueue = minPQ1.clone();
    clonedPriorityQueue.getNodes()  //  minPQ1.getNodes()
    clonedPriorityQueue.sort()      //  [1, 2, 3, 4, 5, 6, 7, 8]
    minPQ1.DFS('in')                //  [4, 3, 2, 5, 1, 8, 6, 7]
    minPQ1.DFS('post')              //  [4, 3, 5, 2, 8, 7, 6, 1]
    minPQ1.DFS('pre')               //  [1, 2, 3, 4, 5, 6, 8, 7]

API docs & Examples

API Docs

Live Examples

Examples Repository

Data Structures

Data Structure	Unit Test	Performance Test	API Docs
Priority Queue			PriorityQueue
Max Priority Queue			MaxPriorityQueue
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

max-priority-queue

test name	time taken (ms)	executions per sec	sample deviation
10,000 refill & poll	8.91	112.29	2.26e-4

priority-queue

test name	time taken (ms)	executions per sec	sample deviation
100,000 add & pop	103.59	9.65	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.