![npm](https://img.shields.io/npm/v/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
![](https://github.com/zrwusa/assets/blob/master/images/data-structure-typed/methods-8bit/max-heap.png?raw=true)
snippet
TS
import {MinHeap, MaxHeap} from 'data-structure-typed';
const minNumHeap = new MinHeap<number>([1, 6, 2, 0, 5]);
minNumHeap.add(9);
minNumHeap.has(1)
minNumHeap.has(2)
minNumHeap.poll()
minNumHeap.poll()
minNumHeap.peek()
minNumHeap.has(1);
minNumHeap.has(2);
const arrFromHeap = minNumHeap.toArray();
arrFromHeap.length
arrFromHeap[0]
arrFromHeap[1]
arrFromHeap[2]
arrFromHeap[3]
minNumHeap.sort()
const maxHeap = new MaxHeap<{ keyA: string }>([], {comparator: (a, b) => b.keyA - a.keyA});
const obj1 = {keyA: 'a1'}, obj6 = {keyA: 'a6'}, obj5 = {keyA: 'a5'}, obj2 = {keyA: 'a2'},
obj0 = {keyA: 'a0'}, obj9 = {keyA: 'a9'};
maxHeap.add(obj1);
maxHeap.has(obj1)
maxHeap.has(obj9)
maxHeap.add(obj6);
maxHeap.has(obj6)
maxHeap.add(obj5);
maxHeap.add(obj2);
maxHeap.add(obj0);
maxHeap.add(obj9);
maxHeap.has(obj9)
const peek9 = maxHeap.peek();
console.log(peek9.keyA)
const heapToArr = maxHeap.toArray();
console.log(heapToArr.map(ele => ele?.keyA));
const values = ['a9', 'a6', 'a5', 'a2', 'a1', 'a0'];
let i = 0;
while (maxHeap.size > 0) {
const polled = maxHeap.poll();
console.log(polled.keyA)
i++;
}
JS
const {MinHeap, MaxHeap} = require('data-structure-typed');
const minNumHeap = new MinHeap([1, 6, 2, 0, 5]);
minNumHeap.add(9);
minNumHeap.has(1)
minNumHeap.has(2)
minNumHeap.poll()
minNumHeap.poll()
minNumHeap.peek()
minNumHeap.has(1);
minNumHeap.has(2);
const arrFromHeap = minNumHeap.toArray();
arrFromHeap.length
arrFromHeap[0]
arrFromHeap[1]
arrFromHeap[2]
arrFromHeap[3]
minNumHeap.sort()
const maxHeap = new MaxHeap([], {comparator: (a, b) => b.keyA - a.keyA});
const obj1 = {keyA: 'a1'}, obj6 = {keyA: 'a6'}, obj5 = {keyA: 'a5'}, obj2 = {keyA: 'a2'},
obj0 = {keyA: 'a0'}, obj9 = {keyA: 'a9'};
maxHeap.add(obj1);
maxHeap.has(obj1)
maxHeap.has(obj9)
maxHeap.add(obj6);
maxHeap.has(obj6)
maxHeap.add(obj5);
maxHeap.add(obj2);
maxHeap.add(obj0);
maxHeap.add(obj9);
maxHeap.has(obj9)
const peek9 = maxHeap.peek();
console.log(peek9.keyA)
const heapToArr = maxHeap.toArray();
console.log(heapToArr.map(ele => ele?.keyA));
const values = ['a9', 'a6', 'a5', 'a2', 'a1', 'a0'];
let i = 0;
while (maxHeap.size > 0) {
const polled = maxHeap.poll();
console.log(polled.keyA)
i++;
}
API docs & Examples
API Docs
Live Examples
Examples Repository
Data Structures
Data Structure | Unit Test | Performance Test | API Docs |
---|
Heap | ![](https://raw.githubusercontent.com/zrwusa/assets/master/images/data-structure-typed/assets/tick.svg) | ![](https://raw.githubusercontent.com/zrwusa/assets/master/images/data-structure-typed/assets/tick.svg) | 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. |