@datastructures-js/priority-queue

@datastructures-js/priority-queue

A performant priority queue implementation using a Heap data structure.

Table of Contents

• Install
• require
• import
• API
  • Construction
  • .enqueue(element[, priority])
  • .front()
  • .back()
  • .dequeue()
  • .isEmpty()
  • .size()
  • .toArray()
  • .clear()
• Build
• License

Install

npm install --save @datastructures-js/priority-queue

API

There are two types of PriorityQueue in this repo: MinPriorityQueue which uses a MinHeap and considers an element with smaller priority number as higher in priority. And MaxPriorityQueue which uses a MaxHeap and cosiders an element with bigger priority number as higher in priority.

require

const { MinPriorityQueue, MaxPriorityQueue } = require('@datastructures-js/priority-queue');

import

import { MinPriorityQueue, MaxPriorityQueue } from '@datastructures-js/priority-queue';

Construction

The constructor accepts a callback to get the numeric priority from the queued element. If not passed, the constructor adds a default priority callback that returns the value of the element itself.

// empty queue with default priority the element value itself.
const numbersQueue = new MinPriorityQueue();

// empty queue, will provide priority in .enqueue
const patientsQueue = new MinPriorityQueue();

// empty queue with priority returned from a prop of the queued object
const biddersQueue = new MaxPriorityQueue({ priority: (bid) => bid.value });

.enqueue(element[, priority])

adds an element with a numeric priority to the queue. Priority is not required here if a priority callback has been provided in the constructor. If passed here with a constructor callback, it will override the callback.

params	return	runtime
element: any priority: number	MinPriorityQueue | MaxPriorityQueue	O(log(n))

// MinPriorityQueue Example, where priority is the number element itself
const numbersQueue
  .enqueue(10)
  .enqueue(-7)
  .enqueue(2)
  .enqueue(-1)
  .enqueue(-17)
  .enqueue(33);

// MinPriorityQueue Example, where priority is the patient's turn
patientsQueue
  .enqueue('patient y', 1); // highest priority
  .enqueue('patient z', 3);
  .enqueue('patient w', 4); // lowest priority
  .enqueue('patient x', 2);

// MaxPriorityQueue Example, where priority is the bid's value.
biddersQueue
  .enqueue({ name: 'bidder y', value: 1000 }); // lowest priority
  .enqueue({ name: 'bidder w', value: 2500 });
  .enqueue({ name: 'bidder z', value: 3500 }); // highest priority
  .enqueue({ name: 'bidder x', value: 3000 });

.front()

returns the element with highest priority in the queue.

return	runtime
object	O(1)

console.log(numbersQueue.front()); // { priority: -17, element: -17 }

console.log(patientsQueue.front()); // { priority: 1, element: 'patient y' }

console.log(biddersQueue.front()); // { priority: 3500, element: { name: 'bidder z', value: 3500 } }

.back()

returns an element with a lowest priority in the queue.

return	runtime
object	O(1)

console.log(numbersQueue.back()); // { priority: 33, element: 33 }

patientsQueue.enqueue('patient m', 4); // lowest priority
patientsQueue.enqueue('patient c', 4); // lowest priority
console.log(patientsQueue.back()); // { priority: 4, element: 'patient c' }

biddersQueue.enqueue({ name: 'bidder m', value: 1000 }); // lowest priority
biddersQueue.enqueue({ name: 'bidder c', value: 1000 }); // lowest priority
console.log(biddersQueue.back()); // { priority: 1000, element: { name: 'bidder y', value: 1000 } }

.dequeue()

removes and returns the element with highest priority in the queue.

return	runtime
object	O(log(n))

console.log(numbersQueue.dequeue()); // { priority: -17, element: -17 }
console.log(numbersQueue.front()); // { priority: -7, element: -7 }

console.log(patientsQueue.dequeue()); // { priority: 1, element: 'patient y' }
console.log(patientsQueue.front()); // { priority: 2, element: 'patient x' }

console.log(biddersQueue.dequeue()); // { priority: 3500, element: { name: 'bidder z', value: 3500 } }
console.log(biddersQueue.front()); // { priority: 3000, element: { name: 'bidder x', value: 3000 } }

.isEmpty()

checks if the queue is empty.

return	runtime
boolean	O(1)

console.log(numbersQueue.isEmpty()); // false

console.log(patientsQueue.isEmpty()); // false

console.log(biddersQueue.isEmpty()); // false

.size()

returns the number of elements in the queue.

return	runtime
number	O(1)

console.log(numbersQueue.size()); // 5

console.log(patientsQueue.size()); // 5

console.log(biddersQueue.size()); // 5

.toArray()

returns a sorted array of elements by their priorities from highest to lowest.

return	runtime
array<object>	O(n*log(n))

console.log(numbersQueue.toArray());
/*
[
  { priority: -7, element: -7 },
  { priority: -1, element: -1 },
  { priority: 2, element: 2 },
  { priority: 10, element: 10 },
  { priority: 33, element: 33 }
]
*/

console.log(patientsQueue.toArray());
/*
[
  { priority: 2, element: 'patient x' },
  { priority: 3, element: 'patient z' },
  { priority: 4, element: 'patient c' },
  { priority: 4, element: 'patient w' },
  { priority: 4, element: 'patient m' }
]
*/

console.log(biddersQueue.toArray());
/*
[
  { priority: 3000, element: { name: 'bidder x', value: 3000 } },
  { priority: 2500, element: { name: 'bidder w', value: 2500 } },
  { priority: 1000, element: { name: 'bidder y', value: 1000 } },
  { priority: 1000, element: { name: 'bidder m', value: 1000 } },
  { priority: 1000, element: { name: 'bidder c', value: 1000 } }
]
*/

.clear()

clears all elements in the queue.

runtime
O(1)

numbersQueue.clear();
console.log(numbersQueue.size()); // 0
console.log(numbersQueue.front()); // null
console.log(numbersQueue.dequeue()); // null

patientsQueue.clear();
console.log(patientsQueue.size()); // 0
console.log(patientsQueue.front()); // null
console.log(patientsQueue.dequeue()); // null

biddersQueue.clear();
console.log(biddersQueue.size()); // 0
console.log(biddersQueue.front()); // null
console.log(biddersQueue.dequeue()); // null

Build

grunt build

License

The MIT License. Full License is here

Changelog

[5.0.1] - 2021-02-23

Fixed

• README