A heap-based implementation of priority queue in javascript with typescript support.
npm install --save @datastructures-js/priority-queue
PriorityQueue class allows using a compare function between values. MinPriorityQueue & MaxPriorityQueue can be used for primitive values and objects with known comparison prop.
const {
PriorityQueue,
MinPriorityQueue,
MaxPriorityQueue,
} = require('@datastructures-js/priority-queue');
import {
PriorityQueue,
MinPriorityQueue,
MaxPriorityQueue,
ICompare,
IGetCompareValue,
} from '@datastructures-js/priority-queue';
constructor requires a compare function that works similar to javascript sort callback, returning a number bigger than 0, means swap elements.
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);
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;
}
);
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.
const numbersQueue = new MinPriorityQueue<number>();
interface IBid {
id: number;
value: number;
}
const getBidValue: IGetCompareValue<IBid> = (bid) => bid.value;
const bidsQueue = new MaxPriorityQueue<IBid>(getBidValue);
const numbersQueue = new MinPriorityQueue();
const bidsQueue = new MaxPriorityQueue((bid) => bid.value);
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.
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.
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 ]
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 ]
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 ]
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 ]
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));
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 }
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 }
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 }
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
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 }]
checks if the queue is empty.
console.log(carsQueue.isEmpty()); // false
console.log(numbersQueue.isEmpty()); // false
console.log(bidsQueue.isEmpty()); // false
returns the number of elements in the queue.
console.log(carsQueue.size()); // 3
console.log(numbersQueue.size()); // 3
console.log(bidsQueue.size()); // 3
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 }
]
*/
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
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
grunt build
The MIT License. Full License is here