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https://github.com/davidnguyen11/p-queue-ts
Priority Queue in Typescript & Javascript
https://github.com/davidnguyen11/p-queue-ts
algorithm array-heap binary-heap binary-trees data-structures javascript nodejs priority-queue typescript
Last synced: about 2 months ago
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Priority Queue in Typescript & Javascript
- Host: GitHub
- URL: https://github.com/davidnguyen11/p-queue-ts
- Owner: davidnguyen11
- License: mit
- Created: 2020-04-14T02:41:23.000Z (over 4 years ago)
- Default Branch: master
- Last Pushed: 2023-05-13T12:52:04.000Z (over 1 year ago)
- Last Synced: 2024-10-13T15:09:55.033Z (2 months ago)
- Topics: algorithm, array-heap, binary-heap, binary-trees, data-structures, javascript, nodejs, priority-queue, typescript
- Language: TypeScript
- Homepage:
- Size: 460 KB
- Stars: 15
- Watchers: 1
- Forks: 3
- Open Issues: 12
-
Metadata Files:
- Readme: README.md
- Funding: .github/FUNDING.yml
- License: LICENSE
Awesome Lists containing this project
README
# Priority Queue
A priority queue is a collection in which items can be added at any time, but the only item that can be removed is the one with the highest priority.
For more information, please check [wiki](https://en.wikipedia.org/wiki/Priority_queue).
[](https://codecov.io/gh/davidnguyen179/p-queue-ts) [](https://travis-ci.org/davidnguyen179/p-queue-ts) [](https://github.com/davidnguyen179/p-queue-ts/pulls) [](https://github.com/davidnguyen179/p-queue-ts/blob/master/LICENSE)
## Motivation
During practising some challenges in `leetcode`. I found this [problem](https://leetcode.com/problems/last-stone-weight/) requires `priority queue`. So I decided to research some documentations online and try to implement by myself this lib. The result beats 97% in `leetcode`.
## Installation
_npm_
```bash
npm i p-queue-ts
```
_yarn_
```bash
yarn add p-queue-ts
```
## Usage
The `priority queue` lib uses max heap as a default way to build a queue.
```ts
import { PriorityQueue } from 'p-queue-ts';
```
or
```ts
const { PriorityQueue } = require('p-queue-ts');
```
**Max priority queue**
_with array of numbers_
```ts
const p = new PriorityQueue();
p.push(2);
p.push(7);
p.push(4);
p.push(1);
p.push(8);
p.push(1);
// The queue: [8, 7, 4, 1, 2, 1]
```
_with array of objects_
```ts
const p = new PriorityQueue(function (a, b) {
return a.value < b.value;
});
p.push({ text: 'a', value: 2 });
p.push({ text: 'b', value: 7 });
p.push({ text: 'c', value: 4 });
p.push({ text: 'd', value: 1 });
p.push({ text: 'e', value: 8 });
p.push({ text: 'f', value: 1 });
/** The queue
[
{ text: 'e', value: 8 },
{ text: 'b', value: 7 },
{ text: 'c', value: 4 },
{ text: 'd', value: 1 },
{ text: 'a', value: 2 },
{ text: 'f', value: 1 },
]
*/
```
If you want to support min `priority queue`. The lib allows providing the customized `comparator`.
**Min priority queue**
_with array of numbers_
```ts
const p = new PriorityQueue(function (a, b) {
return a > b;
});
p.push(2);
p.push(7);
p.push(4);
p.push(1);
p.push(8);
p.push(1);
// The queue: [1, 2, 1, 7, 8, 4]
```
_with array of objects_
```ts
const p = new PriorityQueue(function (a, b) {
return a.value > b.value;
});
p.push({ text: 'a', value: 2 });
p.push({ text: 'b', value: 7 });
p.push({ text: 'c', value: 4 });
p.push({ text: 'd', value: 1 });
p.push({ text: 'e', value: 8 });
p.push({ text: 'f', value: 1 });
/** The queue
[
{ text: 'd', value: 1 },
{ text: 'a', value: 2 },
{ text: 'f', value: 1 },
{ text: 'b', value: 7 },
{ text: 'e', value: 8 },
{ text: 'c', value: 4 }
]
*/
```
## API
### push(value: T)
Add elements to queue
```ts
const p = new PriorityQueue();
p.push(1); // adding "1" to queue
p.push(2); // adding "2" to queue
p.push(3); // adding "3" to queue
// The queue: [3, 1, 2]
```
### pop()
Extract the largest or smallest element from the queue
```ts
const p = new PriorityQueue();
p.push(1); // adding "1" to queue
p.push(2); // adding "2" to queue
p.push(3); // adding "3" to queue
const elmenet = p.pop(); // Output: 3
```
The queue looks like this `[2, 1]`
### top()
Peek the element (get the largest or smallest element without removing it from queue)
```ts
const p = new PriorityQueue();
p.push(1); // adding "1" to queue
p.push(2); // adding "2" to queue
p.push(3); // adding "3" to queue
const elmenet = p.pop(); // Output: 3
// The queue is remained the same
```
### size()
Get the size of the queue
```ts
const p = new PriorityQueue();
p.push(1); // adding "1" to queue
p.push(2); // adding "2" to queue
p.push(3); // adding "3" to queue
p.push(4); // adding "4" to queue
const length = p.size(); // Output: 4
```
### empty()
Check whether the queue is empty or not.
- true: if the queue is empty
- false: if the queue has data
### toArray()
Extract queue to array
```ts
const p = new PriorityQueue();
p.push(1); // adding "1" to queue
p.push(2); // adding "2" to queue
p.push(3); // adding "3" to queue
const array = p.toArray(); // Output: [3, 1, 2]
```
### clear()
Removes all of the elements from this priority queue.
### contains(value: T, comparator?: (item: T) => boolean)
Returns true if this queue contains the specified element.
- true: if the element exists in queue
- false: if the element does not exist in queue
_with array of numbers_
```ts
const p = new PriorityQueue();
p.push(2);
p.push(7);
p.push(4);
p.push(1);
p.push(8);
p.push(1);
p.contains(8); // true
p.contains(100); // false
```
_with array of objects_
```ts
const p = new PriorityQueue(function (a, b) {
return a.value > b.value;
});
p.push({ text: 'a', value: 2 });
p.push({ text: 'b', value: 7 });
p.push({ text: 'c', value: 4 });
p.push({ text: 'd', value: 1 });
p.push({ text: 'e', value: 8 });
p.push({ text: 'f', value: 1 });
function callback(item: any) {
return item.value === element.value;
}
p.contains(8, callback); // true
p.contains(100, callback); // false
```
## Running time
You can check the performance of the package here: [https://jsperf.com/p-queue-ts](https://jsperf.com/p-queue-ts)
| Operation | Binary heap |
| --------- | ----------- |
| push | O(lg n) |
| top | O(1) |
| pop | O(lg n) |