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1.0.6 • Public • Published


File Size MIT license JSR Score 100%

Tiny async queue with concurrency control. Like p-limit or fastq, but smaller and faster. See comparisons and benchmarks below.

Works with: browsers Deno Node.js Cloudflare Workers Bun


Create a queue with the newQueue function. Then add async functions - or promise returning functions - to your queue with the add method.

You can use queue.done() to wait for the queue to be empty.

import { newQueue } from '@henrygd/queue'

// create a new queue with a concurrency of 2
const queue = newQueue(2)

const pokemon = ['ditto', 'hitmonlee', 'pidgeot', 'poliwhirl', 'golem', 'charizard']

for (const name of pokemon) {
    queue.add(async () => {
        const res = await fetch(`https://pokeapi.co/api/v2/pokemon/${name}`)
        const json = await res.json()
        console.log(`${json.name}: ${json.height * 10}cm | ${json.weight / 10}kg`)

await queue.done()

The return value of queue.add is the same as the return value of the supplied function.

const response = await queue.add(() => fetch('https://pokeapi.co/api/v2/pokemon'))
console.log(response.ok, response.status, response.headers)

[!TIP] If you need support for Node's AsyncLocalStorage, import @henrygd/queue/async-storage instead.

Queue interface

/** Add an async function / promise wrapper to the queue */
queue.add<T>(promiseFunction: () => PromiseLike<T>): Promise<T>
/** Returns a promise that resolves when the queue is empty */
queue.done(): Promise<void>
/** Empties the queue (active promises are not cancelled) */
queue.clear(): void
/** Returns the number of promises currently running */
queue.active(): number
/** Returns the total number of promises in the queue */
queue.size(): number

Comparisons and benchmarks

Library Version Bundle size (B) Weekly downloads
@henrygd/queue 1.0.5 339 dozens :)
p-limit 5.0.0 1,763 118,953,973
async.queue 3.2.5 6,873 53,645,627
fastq 1.17.1 3,050 39,257,355
queue 7.0.0 2,840 4,259,101
promise-queue 2.2.5 2,200 1,092,431

Note on benchmarks

All libraries run the exact same test. Each operation measures how quickly the queue can resolve 1,000 async functions. The function just increments a counter and checks if it has reached 1,000.1

We check for completion inside the function so that promise-queue and p-limit are not penalized by having to use Promise.all (they don't provide a promise that resolves when the queue is empty).

Browser benchmark

This test was run in Chromium. Chrome and Edge are the same. Firefox and Safari are slower and closer, with @henrygd/queue just edging out promise-queue. I think both are hitting the upper limit of what those browsers will allow.

You can run or tweak for yourself here: https://jsbm.dev/c5W1T8CzAw232

@henrygd/queue - 13,665 Ops/s. fastq - 7,661 Ops/s. promise-queue - 7,650 Ops/s. async.queue - 4,060 Ops/s. p-limit - 1,067 Ops/s. queue - 721 Ops/s

Node.js benchmarks

p-limit is very slow because it uses AsyncResource.bind on every run, which is much faster in Bun than in Node or Deno.

Ryzen 5 4500U | 8GB RAM | Node 22.3.0

@henrygd/queue - 1.7x faster than fastq. 1.82x promise-queue. 3.45x async.queue. 18.55x queue. 73x p-limit.

Ryzen 7 6800H | 32GB RAM | Node 22.3.0

@henrygd/queue - 1.56x faster than fastq. 1.73x promise-queue. 3.31x async.queue. 5.68x queue. 77x p-limit.

Deno benchmarks

Ryzen 5 4500U | 8GB RAM | Deno 1.44.4

@henrygd/queue - 1.66x faster than fastq. 1.79x promise-queue. 3.3x async.queue. 6x queue. 24x p-limit.

Ryzen 7 6800H | 32GB RAM | Deno 1.44.4

@henrygd/queue - 1.6x faster than fastq. 1.71x promise-queue. 3.2x async.queue. 6.24x queue. 23x p-limit.

Bun benchmarks

Ryzen 5 4500U | 8GB RAM | Bun 1.1.16

@henrygd/queue - 1.32x faster than promise-queue. 1.58x fastq. 2.62x async.queue. 5.36x p-limit. 12.65x queue.

Ryzen 7 6800H | 32GB RAM | Bun 1.1.16

@henrygd/queue - 1.2x faster than promise-queue. 1.54x fastq. 2.76x async.queue. 5.45x p-limit. 5.83x queue.

Cloudflare Workers benchmark

Uses oha to make 1,000 requests to each worker. Each request creates a queue and resolves 5,000 functions.

This was run locally using Wrangler on a Ryzen 7 6800H laptop. Wrangler uses the same workerd runtime as workers deployed to Cloudflare, so the relative difference should be accurate. Here's the repository for this benchmark.

Library Requests/sec Total (sec) Average Slowest
@henrygd/queue 816.1074 1.2253 0.0602 0.0864
promise-queue 647.2809 1.5449 0.0759 0.1149
fastq 336.7031 3.0877 0.1459 0.2080
async.queue 198.9986 5.0252 0.2468 0.3544
queue 85.6483 11.6757 0.5732 0.7629
p-limit 77.7434 12.8628 0.6316 0.9585

Real world examples

henrygd/optimize - Uses @henrygd/queue to parallelize image optimization jobs.


MIT license

  1. In reality, you may not be running so many jobs at once, and your jobs will take much longer to resolve. So performance will depend more on the jobs themselves.

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