mikolalysenko / heapify

The fastest JavaScript priority queue out there. Zero dependencies.

🚑 🚴 🚌 🚕 🚗 🚚 🚛

A very fast JavaScript priority queue, implemented using a binary heap, which in turn is implemented using two underlying parallel typed arrays. No dependencies whatsoever; just plain, vanilla JS.

It's the fastest publicly available JavaScript library implementation of a priority queue. Here's an average benchmark comparing Heapify with TinyQueue and FlatQueue, running for 1 million elements:

              build     push       pop     push+pop
TinyQueue     110ms    110ms     624ms        205ms
FlatQueue      85ms     85ms     157ms        112ms
Heapify        32ms     41ms     150ms        112ms 

Host machine: 2.4 GHz Dual-Core Intel Core i7, 16 GB RAM.

Note: the build operation doesn't actually exist in TinyQueue and FlatQueue, so it has to be replaced with a manual push operation. That's why build times for those two cases are the same as for push.

Supported operations:

• push: O(log n)
• pop: O(log n)
• peek: O(1)
• creation with pre-existing list of priorities: O(n)

Features:

• runs on browser and Node.js with support to ES6 modules
• tiny code base (under 100 LoC)
• no dependencies
• supports several types of priorities and keys

Upcoming features:

• standalone heap structures
• max heaps
• unique items
• accessing arbitrary items
• changing the priority of arbitrary items
• objects as keys (with performance hit)
• dynamic size

How to install

npm i heapify

Or if you're a yarn person:

yarn add heapify

If you're on a browser, there's also the option of using a CDN:

import Heapify from "https://unpkg.com/heapify";

And to import a specific version:

import Heapify from "https://unpkg.com/heapify@0.2.1";

How to use

import Heapify from "heapify";

const queue = new Heapify();
queue.push(1, 10);
queue.push(2, 5);
queue.pop();  // 2
queue.peek();  // 1
queue.clear();
queue.pop();  // undefined

Running tests

npm run test

For benchmark tests:

npm run bench

API

new Heapify(capacity = 64, keys = [], priorities = [], KeysBackingArrayType = Uint32Array, PrioritiesBackingArrayType = Uint32Array)

Creates a new priority queue. Parameters are:

• capacity: the size of the underlying typed arrays backing the heap;
• keys: an optional array of pre-existing keys. Provide [] to skip this field;
• priorities: an optional array of pre-existing priorities. Must match number of keys above. Provide [] to skip this field;
• KeysBackingArrayType: the array type to be used for keys;
• PrioritiesBackingArrayType: the array type to be used for priorities.

Example:

const queue1 = new Heapify(32);
const queue2 = new Heapify(16, [], [], Uint64Array, Uint32Array);

clear()

Effectively empties the queue. The heap capacity is not changed, nor its elements get erased in any way; it's just the variable that tracks the length that gets cleared to zero, so it's a very cheap operation.

Example:

const queue = new Heapify();
queue.push(1, 10);
console.info(queue.length);  // 1
queue.clear();
console.info(queue.length);  // 0

peek()

Gets the key with the smallest priority, but does not remove it from the queue.

Example:

const queue = new Heapify();
queue.push(1, 10);
queue.peek();  // 1

peekPriority()

Gets the priority of the key with the smallest priority, but does not remove the item from the queue.

Example:

const queue = new Heapify();
queue.push(1, 10);
queue.peekPriority();  // 10

pop()

Removes the smallest priority item from the queue, returning its key.

Example:

const queue = new Heapify();
queue.push(1, 10);
queue.pop();  // 1

push(key, priority)

Adds a new item to the queue with a given key and priority. Will throw an error if the queue is already at its capacity.

Example:

const queue = new Heapify();
queue.push(1, 10);
queue.length;  // 1
queue.peek();  // 1
queue.peekPriority();  // 10

toString()

Returns a string with an array representation of all priorities in the queue. For instance, given the following priority heap:

    10
  30  20
40

The returned string will be [10 30 20 40]. See tests for more examples.