priority-queue-typed
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1.53.6 • Public • Published

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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

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.

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npm i priority-queue-typed

Weekly Downloads

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Version

1.53.6

License

MIT

Unpacked Size

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