[size-image]: https://img.shields.io/github/size/henrygd/queue/dist/index.min.js?style=flat
[license-image]: https://img.shields.io/github/license/henrygd/queue?style=flat&color=%2349ac0c
[license-url]: /LICENSE

@henrygd/queue

[![File Size][size-image]](https://github.com/henrygd/queue/blob/main/dist/index.min.js) [![MIT license][license-image]][license-url] 

Tiny async queue with concurrency control. Like p-limit or fastq, but smaller and faster. Optional time-based rate limiting also available. See comparisons and benchmarks below.

Works with:

Usage

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.

``ts
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)
})
}

console.log('running')
await queue.done()
console.log('done')
`

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

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

queue.all is like Promise.all with concurrency control:

`ts
import { newQueue } from "@henrygd/queue";

const queue = newQueue(2);

const tasks = ["ditto", "hitmonlee", "pidgeot", "poliwhirl"].map(
(name) => async () => {
const res = await fetch(https://pokeapi.co/api/v2/pokemon/${name});
return await res.json();
}
);

// Process all tasks concurrently (limited by queue concurrency) and wait for all to complete
const results = await queue.all(tasks);
console.log(results); // [{ name: 'ditto', ... }, { name: 'hitmonlee', ... }, ...]
`

You can also mix existing promises and function wrappers.

`ts
const existingPromise = fetch("https://pokeapi.co/api/v2/pokemon/ditto").then(
(r) => r.json()
);
const results = await queue.all([
existingPromise,
() =>
fetch("https://pokeapi.co/api/v2/pokemon/pidgeot").then((r) => r.json()),
]);
`

Note that only the wrapper functions are queued, since existing promises start running as soon as you create them.

Time-based rate limiting

If you need to limit not just concurrency (how many tasks run simultaneously) but also rate (how many tasks can start within a time window), use @henrygd/queue/rl.

This is useful when working with APIs that have rate limits.

`ts
import { newQueue } from '@henrygd/queue/rl'

// max 10 concurrent requests, but only 3 can start per second
const queue = newQueue(10, 3, 1000)

const start = Date.now()

for (let i = 1; i <= 10; i++) {
queue.add(async () => console.log(Task ${i} started at ${Date.now() - start}ms))
}

await queue.done()
`

The signature is: newQueue(concurrency, rate?, interval?).

- concurrency - Maximum number of tasks running simultaneously
- rate - Maximum number of tasks that can start within the interval (optional)
- interval - Time window in milliseconds for rate limiting (optional)

If you omit rate and interval, it works exactly like the main package (just concurrency limiting).

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

Queue interface

`ts
/* Add an async function / promise wrapper to the queue /
queue.add(promiseFunction: () => PromiseLike): Promise
/* Adds promises (or wrappers) to the queue and resolves like Promise.all /
queue.all(promiseFunctions: Array | (() => PromiseLike)>): Promise
/* Returns a promise that resolves when the queue is empty /
queue.done(): Promise
/* Empties the queue - pending promises are rejected, active promises continue /
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 | 1.2.0 | 472 | hundreds :) |
| @henrygd/queue/rl | 1.2.0 | 685 | - |
| 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 |

$3

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.[^benchmark]

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/TKyOdie0sbpOh

!@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

> Note: p-limit 6.1.0 now places between async.queue and queue in Node and Deno.

Ryzen 5 4500U | 8GB RAM | Node 22.3.0

!@henrygd/queue - 1.9x faster than fastq. 2.03x promise-queue. 3.86x async.queue. 20x queue. 86x p-limit.

Ryzen 7 6800H | 32GB RAM | Node 22.3.0

!@henrygd/queue - 1.9x faster than fastq. 2.01x promise-queue. 3.98x async.queue. 6.86x queue. 88x p-limit.

Deno benchmarks

> Note: p-limit 6.1.0 now places between async.queue and queue in Node and Deno.

Ryzen 5 4500U | 8GB RAM | Deno 1.44.4

!@henrygd/queue - 1.9x faster than fastq. 2.01x promise-queue. 4.7x async.queue. 7x queue. 28x p-limit.

Ryzen 7 6800H | 32GB RAM | Deno 1.44.4

!@henrygd/queue - 1.82x faster than fastq. 1.91x promise-queue. 3.47x async.queue. 7x queue. 26x p-limit.

Bun benchmarks

Ryzen 5 4500U | 8GB RAM | Bun 1.1.17

!@henrygd/queue - 1.25x faster than promise-queue. 1.66x fastq. 2.73x async.queue. 5.44x p-limit. 12x queue.

Ryzen 7 6800H | 32GB RAM | Bun 1.1.17

!@henrygd/queue - 1.17x faster than promise-queue. 1.51x fastq. 2.53x async.queue. 5.25x p-limit. 5.39x 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 |

Related

@henrygd/semaphore` - Fastest javascript inline semaphores and mutexes using async / await.

License

MIT license

[^benchmark]: In real applications, 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.