Blazing fast priority queue
npm install heapify
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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.
``js
import {MinQueue} from "heapify";
// const {MinQueue} = require("heapify"); // alternatively, require() also works
const queue = new MinQueue();
queue.push(1, 10);
queue.push(2, 5);
queue.pop(); // 2
queue.peek(); // 1
queue.clear();
queue.pop(); // undefined
`
It's the fastest publicly available JavaScript library implementation of a priority queue. Here's a benchmark comparing Heapify to other popular libraries:
| Operation | Closure | FlatQueue | TinyQueue | Heapify |
|----------------------|---------|-----------|-----------|---------|
| build | 201 | n/a | n/a | 18 |
| push | 222 | 66 | 75 | 24 |
| pop | 496 | 137 | 917 | 110 |
| push/pop batch | 279 | 83 | 280 | 89 |
| push/pop interleaved | 315 | 50 | 265 | 34 |
| push/pop random | 186 | 50 | 257 | 48 |
See the benchmark section for more details.
Heapify's design strives for reliability, with strong test coverage and focus on code readability. It should be easy to understand what the library is doing. The library is also very lean, with no dependencies and a small and concise source code.
- Features
- How to install
- How to import
- API
- constructor
- capacity
- clear()
- peek()
- peekPriority()
- pop()
- push(key, priority)
- size
- Benchmark
- Contributing
Supported queue operations:
- push: O(log n)
- pop: O(log n) in the general case, O(1) if not preceded by a pop
- peek: O(1) in the general case, O(log n) if preceded by a pop
- peekPriority: O(1) in the general case, O(log n) if preceded by a pop
- creation with pre-existing list of priorities: O(n)
Other features:
- runs on browser and Node.js with ES5 and ES6 support
- tiny code base (under 200 LoC)
- no runtime dependencies
- supports several types of priorities and keys
`sh`
npm i heapify
Or if you're a yarn person:
`sh`
yarn add heapify
You can import it in your Node.js project using TypeScript:
`js`
import {MinQueue} from "heapify";
Or directly via native ES6 module support, using the mjs ES6 module bundle:
`js`
import {MinQueue} from "heapify/heapify.mjs";
Or just require() it in your good old CommonJS project:
`js`
const {MinQueue} = require("heapify");
Heapify can be included via regular script tags, where Heapify will be exposed globally:
`html`
The example above uses unpkg, but you can of course reference a local copy installed either manually or via npm/yarn.
For projects using native ES6 modules, make sure to import the mjs ES6 module bundle instead:
`js`
import {MinQueue} from "https://unpkg.com/heapify/heapify.mjs"
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:
`js`
const queue1 = new MinQueue(32);
const queue2 = new MinQueue(16, [], [], Uint16Array, Uint32Array);
A read-only property that returns the maximum capacity of the queue. Example:
`js`
const queue = new MinQueue(32);
queue.capacity; // 32
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:
`js`
const queue = new MinQueue();
queue.push(1, 10);
console.info(queue.size); // 1
queue.clear();
console.info(queue.size); // 0
Gets the key with the smallest priority, but does not remove it from the queue.
Example:
`js`
const queue = new MinQueue();
queue.push(1, 10);
queue.peek(); // 1
Gets the _priority_ of the key with the smallest priority, but does not remove the item from the queue.
Example:
`js`
const queue = new MinQueue();
queue.push(1, 10);
queue.peekPriority(); // 10
Removes the smallest priority item from the queue, returning its key. Returns undefined if the queue is empty.
Note that Heapify's heap implementation is not stable. If multiple keys have the same priority, there are no guarantees about the order in which they will be popped.
Example:
`js`
const queue = new MinQueue();
queue.push(1, 10);
queue.pop(); // 1
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:
`js`
const queue = new MinQueue();
queue.push(1, 10);
queue.size; // 1
queue.peek(); // 1
queue.peekPriority(); // 10
A read-only property that returns the current size of the queue.
Example:
`js`
const queue = new MinQueue();
queue.size; // 0
queue.push(1, 10);
queue.size; // 1
queue.pop();
queue.size; // 0
Here's a table comparing Heapify with other implementations (times are in milliseconds):
`
Closure FastPQ FlatQueue TinyQueue Heapify
build 201 15 - - 18
push 222 47 66 75 24
pop 496 143 137 917 110
push/pop batch 279 128 83 280 89
push/pop interleaved 315 65 50 265 34
push/pop random 186 45 50 257 48
Host machine: Node.js 13.8.0, 2.6 GHz 6-Core Intel Core i7, 32 GB 2400 MHz DDR4 RAM.
Operations:
- build - build queue from scratch by providing a collection of keys and priorities, all at once;
- push - insert a single element into the queue;
- pop - remove a single element from the queue;
- push/pop batch - performs batches of 1k pushes followed by 1k pops;
- push/pop interleaved - starting with a partially filled queue, this test inserts a random element and then immediately removes the lowest priority value from the queue;
- push/pop random - starting with a partially filled queue, this test runs either a push or a pop at random.
Each test performs 1 million operations and is repeated 5 times. The median value is used as the result.
Tested libraries:
- Google Closure library - a hugely popular library, but is the worst implementation with respect to performance;
- Fast Priority Queue - runs comparably fast, but doesn't support inserting keys as well, so its implementation significantly limits what the user is able to achieve with it;
- FlatQueue and TinyQueue - two very nice queue implementations by Vladimir Agafonkin. They don't support the build method and that's why they're missing this benchmark. FlatQueue performs considerably well for an implementation that is not based on typed arrays.
You are welcome to contribute, but please take the time to read and follow these guidelines.