heap-typed

What

Brief

This is a standalone Heap 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 heap-typed --save

yarn

yarn add heap-typed

methods

Min Heap Max Heap

snippet

TS

    import {MinHeap, MaxHeap} from 'data-structure-typed';
    // /* or if you prefer */ import {MinHeap, MaxHeap} from 'heap-typed';

    const minNumHeap = new MinHeap<number>();
    minNumHeap.add(1).add(6).add(2).add(0).add(5).add(9);
    minNumHeap.has(1)        //  true
    minNumHeap.has(2)        //  true
    minNumHeap.poll()        //  0
    minNumHeap.poll()        //  1
    minNumHeap.peek()        //  2
    minNumHeap.has(1);       // false
    minNumHeap.has(2);       // true
    const arrFromHeap = minNumHeap.toArray();
    arrFromHeap.length       //  4
    arrFromHeap[0]           //  2
    arrFromHeap[1]           //  5
    arrFromHeap[2]           //  9
    arrFromHeap[3]           //  6
    minNumHeap.sort()        //  [2, 5, 6, 9]
    
    
    const maxHeap = new MaxHeap<{ keyA: string }>();
    const myObj1 = {keyA: 'a1'}, myObj6 = {keyA: 'a6'}, myObj5 = {keyA: 'a5'}, myObj2 = {keyA: 'a2'},
        myObj0 = {keyA: 'a0'}, myObj9 = {keyA: 'a9'};
    maxHeap.add(1, myObj1);
    maxHeap.has(myObj1)  // true
    maxHeap.has(myObj9)  // false
    maxHeap.add(6, myObj6);
    maxHeap.has(myObj6)  // true
    maxHeap.add(5, myObj5);
    maxHeap.has(myObj5)  // true
    maxHeap.add(2, myObj2);
    maxHeap.has(myObj2)  // true
    maxHeap.has(myObj6)  // true
    maxHeap.add(0, myObj0);
    maxHeap.has(myObj0)  // true
    maxHeap.has(myObj9)  // false
    maxHeap.add(9, myObj9);
    maxHeap.has(myObj9)  // true
    
    const peek9 = maxHeap.peek(true);
    peek9 && peek9.val && peek9.val.keyA  // 'a9'
    
    const heapToArr = maxHeap.toArray(true);
    heapToArr.map(item => item?.val?.keyA)  // ['a9', 'a2', 'a6', 'a1', 'a0', 'a5']
    
    const values = ['a9', 'a6', 'a5', 'a2', 'a1', 'a0'];
    let i = 0;
    while (maxHeap.size > 0) {
        const polled = maxHeap.poll(true);
        polled && polled.val && polled.val.keyA  // values[i]
        i++;
    }

JS

    const {MinHeap, MaxHeap} = require('data-structure-typed');
    // /* or if you prefer */ const {MinHeap, MaxHeap} = require('heap-typed');

    const minNumHeap = new MinHeap();
    minNumHeap.add(1).add(6).add(2).add(0).add(5).add(9);
    minNumHeap.has(1)        //  true
    minNumHeap.has(2)        //  true
    minNumHeap.poll()        //  0
    minNumHeap.poll()        //  1
    minNumHeap.peek()        //  2
    minNumHeap.has(1);       // false
    minNumHeap.has(2);       // true
    const arrFromHeap = minNumHeap.toArray();
    arrFromHeap.length       //  4
    arrFromHeap[0]           //  2
    arrFromHeap[1]           //  5
    arrFromHeap[2]           //  9
    arrFromHeap[3]           //  6
    minNumHeap.sort()        //  [2, 5, 6, 9]
    
    
    const maxHeap = new MaxHeap();
    const myObj1 = {keyA: 'a1'}, myObj6 = {keyA: 'a6'}, myObj5 = {keyA: 'a5'}, myObj2 = {keyA: 'a2'},
        myObj0 = {keyA: 'a0'}, myObj9 = {keyA: 'a9'};
    maxHeap.add(1, myObj1);
    maxHeap.has(myObj1)  // true
    maxHeap.has(myObj9)  // false
    maxHeap.add(6, myObj6);
    maxHeap.has(myObj6)  // true
    maxHeap.add(5, myObj5);
    maxHeap.has(myObj5)  // true
    maxHeap.add(2, myObj2);
    maxHeap.has(myObj2)  // true
    maxHeap.has(myObj6)  // true
    maxHeap.add(0, myObj0);
    maxHeap.has(myObj0)  // true
    maxHeap.has(myObj9)  // false
    maxHeap.add(9, myObj9);
    maxHeap.has(myObj9)  // true
    
    const peek9 = maxHeap.peek(true);
    peek9 && peek9.val && peek9.val.keyA  // 'a9'
    
    const heapToArr = maxHeap.toArray(true);
    heapToArr.map(item => item?.val?.keyA)  // ['a9', 'a2', 'a6', 'a1', 'a0', 'a5']
    
    const values = ['a9', 'a6', 'a5', 'a2', 'a1', 'a0'];
    let i = 0;
    while (maxHeap.size > 0) {
        const polled = maxHeap.poll(true);
        polled && polled.val && polled.val.keyA  // values[i]
        i++;
    }

API docs & Examples

API Docs

Live Examples

Examples Repository

Data Structures

Data Structure	Unit Test	Performance Test	API Docs
Heap			Heap

Standard library data structure comparison

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

Benchmark

heap

test name	time taken (ms)	executions per sec	sample deviation
10,000 add & pop	5.80	172.35	8.78e-5
10,000 fib add & pop	357.92	2.79	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.