@datastructures-js/priority-queue NPM

@datastructures-js/priority-queue

A heap-based implementation of priority queue in javascript with typescript support.

Install

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

API

PriorityQueue class allows using a compare function between values. MinPriorityQueue & MaxPriorityQueue can be used for primitive values and objects with known comparison prop.

require

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

import

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

constructor

PriorityQueue

constructor requires a compare function that works similar to javascript sort callback, returning a number bigger than 0, means swap elements.

TS

interface ICar {
  year: number;
  price: number;
}

const compareCars: ICompare<ICar> = (a: ICar, b: ICar) => {
  if (a.year > b.year) {
    return -1;
  }
  if (a.year < b.year) {
    // prioritize newest cars
    return 1;
  }
  // with lowest price
  return a.price < b.price ? -1 : 1;
};

const carsQueue = new PriorityQueue<ICar>(compareCars);

JS

const carsQueue = new PriorityQueue((a, b) => {
    if (a.year > b.year) {
      return -1;
    }
    if (a.year < b.year) {
      // prioratize newest cars
      return 1;
    }
    // with lowest price
    return a.price < b.price ? -1 : 1;
  }
);

MinPriorityQueue, MaxPriorityQueue

constructor requires a callback for object values to indicate which prop is used for comparison, and does not require any for primitive values like numbers or strings.

TS

const numbersQueue = new MinPriorityQueue<number>();

interface IBid {
  id: number;
  value: number;
}
const getBidValue: IGetCompareValue<IBid> = (bid) => bid.value;
const bidsQueue = new MaxPriorityQueue<IBid>(getBidValue);

JS

const numbersQueue = new MinPriorityQueue();
const bidsQueue = new MaxPriorityQueue((bid) => bid.value);

Legacy Compare Function (v5 compatibility)

For backward compatibility with v5, you can also pass a compare function in an options object:

// MinPriorityQueue with legacy compare
const minQueue = new MinPriorityQueue({ compare: (a, b) => a - b });

// MaxPriorityQueue with legacy compare
const maxQueue = new MaxPriorityQueue({ compare: (a, b) => a - b });

This format is supported for backward compatibility with v5 of the library.

fromArray

If the queue is being created from an existing array, and there is no desire to use an extra O(n) space, this static function can turn an array into a priority queue in O(n) runtime.

PriorityQueue

TS

const numbers = [3, -2, 5, 0, -1, -5, 4];

const pq = PriorityQueue.fromArray<number>(numbers, (a, b) => a - b);

console.log(numbers); // [-5, -1, -2, 3, 0, 5, 4]
pq.dequeue(); // -5
pq.dequeue(); // -2
pq.dequeue(); // -1
console.log(numbers); // [ 0, 3, 4, 5 ]

JS

const numbers = [3, -2, 5, 0, -1, -5, 4];

const pq = PriorityQueue.fromArray(numbers, (a, b) => a - b);

console.log(numbers); // [-5, -1, -2, 3, 0, 5, 4]
pq.dequeue(); // -5
pq.dequeue(); // -2
pq.dequeue(); // -1
console.log(numbers); // [ 0, 3, 4, 5 ]

MinPriorityQueue, MaxPriorityQueue

TS

const numbers = [3, -2, 5, 0, -1, -5, 4];

const mpq = MaxPriorityQueue.fromArray<number>(numbers);

console.log(numbers); // [-5, -1, -2, 3, 0, 5, 4]
mpq.dequeue(); // 5
mpq.dequeue(); // 4
mpq.dequeue(); // 3
console.log(numbers); // [ 0, -1, -5, -2 ]

JS

const numbers = [3, -2, 5, 0, -1, -5, 4];

const mpq = MaxPriorityQueue.fromArray(numbers);

console.log(numbers); // [-5, -1, -2, 3, 0, 5, 4]
mpq.dequeue(); // 5
mpq.dequeue(); // 4
mpq.dequeue(); // 3
console.log(numbers); // [ 0, -1, -5, -2 ]

enqueue (push)

adds a value based on its comparison with other values in the queue in O(log(n)) runtime.

const cars = [
  { year: 2013, price: 35000 },
  { year: 2010, price: 2000 },
  { year: 2013, price: 30000 },
  { year: 2017, price: 50000 },
  { year: 2013, price: 25000 },
  { year: 2015, price: 40000 },
  { year: 2022, price: 70000 }
];
cars.forEach((car) => carsQueue.enqueue(car));

const numbers = [3, -2, 5, 0, -1, -5, 4];
numbers.forEach((num) => numbersQueue.push(num)); // push is an alias for enqueue

const bids = [
  { id: 1, value: 1000 },
  { id: 2, value: 20000 },
  { id: 3, value: 1000 },
  { id: 4, value: 1500 },
  { id: 5, value: 12000 },
  { id: 6, value: 4000 },
  { id: 7, value: 8000 }
];
bids.forEach((bid) => bidsQueue.enqueue(bid));

front

peeks on the value with highest priority in the queue.

console.log(carsQueue.front()); // { year: 2022, price: 70000 }
console.log(numbersQueue.front()); // -5
console.log(bidsQueue.front()); // { id: 2, value: 20000 }

back

peeks on the value with a lowest priority in the queue.

console.log(carsQueue.back()); // { year: 2010, price: 2000 }
console.log(numbersQueue.back()); // 5
console.log(bidsQueue.back()); // { id: 1, value: 1000 }

dequeue (pop)

removes and returns the element with highest priority in the queue in O(log(n)) runtime.

console.log(carsQueue.dequeue()); // { year: 2022, price: 70000 }
console.log(carsQueue.dequeue()); // { year: 2017, price: 50000 }
console.log(carsQueue.dequeue()); // { year: 2015, price: 40000 }

console.log(numbersQueue.dequeue()); // -5
console.log(numbersQueue.dequeue()); // -2
console.log(numbersQueue.dequeue()); // -1

console.log(bidsQueue.pop()); // { id: 2, value: 20000 }
console.log(bidsQueue.pop()); // { id: 5, value: 12000 }
console.log(bidsQueue.pop()); // { id: 7, value: 8000 }

contains

checks if the queue contains an element that meet a criteria in O(n*log(n)) runtime.

carsQueue.contains((car) => car.price === 50000); // true
carsQueue.contains((car) => car.price === 200000); // false
numbersQueue.contains((n) => n === 4); // true
numbersQueue.contains((n) => n === 10); // false

remove

removes all elements that meet a criteria in O(n*log(n)) runtime and returns a list of the removed elements.

carsQueue.remove((car) => car.price === 35000); // [{ year: 2013, price: 35000 }]

numbersQueue.remove((n) => n === 4); // [4]

bidsQueue.remove((bid) => bid.id === 3); // [{ id: 3, value: 1000 }]

isEmpty

checks if the queue is empty.

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

size

returns the number of elements in the queue.

console.log(carsQueue.size()); // 3
console.log(numbersQueue.size()); // 3
console.log(bidsQueue.size()); // 3

toArray

returns a sorted array of elements by their priorities from highest to lowest in O(n*log(n)) runtime.

console.log(carsQueue.toArray());
/*
[
  { year: 2013, price: 25000 },
  { year: 2013, price: 30000 },
  { year: 2010, price: 2000 }
]
*/

console.log(numbersQueue.toArray()); // [ 0, 3, 5 ]

console.log(bidsQueue.toArray());
/*
[
  { id: 6, value: 4000 },
  { id: 4, value: 1500 },
  { id: 1, value: 1000 }
]
*/

Symbol.iterator

The queues implement a Symbol.iterator that makes them iterable on pop.

console.log([...carsQueue]);
/*
[
  { year: 2013, price: 25000 },
  { year: 2013, price: 30000 },
  { year: 2010, price: 2000 }
]
*/
console.log(carsQueue.size()); // 0

console.log([...numbersQueue]); // [ 0, 3, 5 ]
console.log(numbersQueue.size()); // 0

for (const bid of bidsQueue) {
  console.log(bid);
}
/*
{ id: 6, value: 4000 },
{ id: 4, value: 1500 },
{ id: 1, value: 1000 }
*/
console.log(bidsHeap.size()); // 0

clear

clears all elements in the queue.

carsQueue.clear();
console.log(carsQueue.size()); // 0
console.log(carsQueue.front()); // null
console.log(carsQueue.dequeue()); // null
console.log(carsQueue.isEmpty()); // true

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

bidsQueue.clear();
console.log(bidsQueue.size()); // 0
console.log(bidsQueue.front()); // null
console.log(bidsQueue.dequeue()); // null
console.log(bidsQueue.isEmpty()); // true