| test name | time taken (ms) | executions per sec | sample deviation |
|---|---|---|---|
| 10,000 refill & poll | 8.91 | 112.29 | 2.26e-4 |
Priority Queue
npm install priority-queue-typed!NPM
!GitHub top language
!npm
!eslint
!npm bundle size
!npm bundle size
!npm
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
``bash`
npm i priority-queue-typed --save
`bash`
yarn add priority-queue-typed
#### TS
`typescript
import {PriorityQueue, MinPriorityQueue} from 'data-structure-typed';
// / or if you prefer / import {PriorityQueue, MinPriorityQueue} from 'priority-queue-typed';
const minPQ = new PriorityQueue
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
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
`javascript
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
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]
``
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[//]: # (No deletion!!! End of Example Replace Section)
| Data Structure | Unit Test | Performance Test | API Docs |
|---|---|---|---|
| Priority Queue | PriorityQueue | ||
| Max Priority Queue | MaxPriorityQueue | ||
| Min Priority Queue | MinPriorityQueue |
| Data Structure Typed | C++ STL | java.util | Python collections |
|---|---|---|---|
| PriorityQueue<E> | priority_queue<T> | PriorityQueue<E> | - |
[//]: # (No deletion!!! Start of Replace Section)
| test name | time taken (ms) | executions per sec | sample deviation |
|---|---|---|---|
| 10,000 refill & poll | 8.91 | 112.29 | 2.26e-4 |
| test name | time taken (ms) | executions per sec | sample deviation |
|---|---|---|---|
| 100,000 add & pop | 103.59 | 9.65 | 0.00 |
[//]: # (No deletion!!! End of Replace Section)
| Algorithm | Function Description | Iteration Type |
|---|
| 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. |