@datastructures-js/priority-queue
Advanced tools
A heap-based implementation of priority queue in javascript with typescript support.
@datastructures-js/priority-queue is an npm package that provides a robust implementation of a priority queue data structure. It allows you to manage a collection of elements where each element is associated with a priority, and elements are served based on their priority.
Creating a Priority Queue
This code demonstrates how to create a new instance of a MinPriorityQueue using the @datastructures-js/priority-queue package.
const { MinPriorityQueue } = require('@datastructures-js/priority-queue');
const pq = new MinPriorityQueue();Adding Elements
This code shows how to add elements to the priority queue with associated priorities.
pq.enqueue('task1', 1);
pq.enqueue('task2', 2);Removing Elements
This code demonstrates how to remove and return the element with the highest priority from the priority queue.
const highestPriorityElement = pq.dequeue();Peeking at the Highest Priority Element
This code shows how to peek at the element with the highest priority without removing it from the queue.
const highestPriorityElement = pq.front();Checking if the Queue is Empty
This code demonstrates how to check if the priority queue is empty.
const isEmpty = pq.isEmpty();js-priority-queue is another npm package that provides a priority queue implementation. It supports both min and max priority queues and allows for custom comparison functions. Compared to @datastructures-js/priority-queue, js-priority-queue offers more flexibility in terms of custom comparison but may have a steeper learning curve.
heap is an npm package that provides a binary heap implementation, which can be used to create priority queues. It supports both min-heaps and max-heaps. Compared to @datastructures-js/priority-queue, heap is more low-level and may require more manual handling of heap properties.
priorityqueuejs is a simple and efficient priority queue implementation in JavaScript. It supports custom comparators and is easy to use. Compared to @datastructures-js/priority-queue, priorityqueuejs is more lightweight but may lack some advanced features.
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);
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
[6.3.2] - 2025-01-05
FAQs
A heap-based implementation of priority queue in javascript with typescript support.
The npm package @datastructures-js/priority-queue receives a total of 15,026 weekly downloads. As such, @datastructures-js/priority-queue popularity was classified as popular.
We found that @datastructures-js/priority-queue demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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