Promise not returning expected value

Promise not returning expected value - javascript

Ive been learning about promises and I have a question. I have a function named getNumber which return an array of number (for the sake of understanding). The I used that function to iterate over that array and make a http request for each value (with a setTimeout to make a delay between calls)
Then I want to used that information gathered in a then function, but it's giving me a 'undefined error'. obviously something is wrong here, but I cant see it. Do you guy know how can I fix this and what is wrong?
var getNumbers = () => {
return new Promise(function(resolve, reject) {
console.log("In function getNumbers");
var data = [1,2,3,4,5,6,7,8,9];
resolve(data);
});
};
getNumbers()
.then(numbersArray => {
//Supposed to return array of posts title
return numbersArray.map(number => {
console.log("Reading number" + number);
setTimeout(() => {
//make a http request
return getHtml("https://jsonplaceholder.typicode.com/posts/"+number)
.then(function(post) {
return post.title;
})
}, 10000);//make a request each ten seconds
});
})
.then(postTitlesArray => {
//Shows array of undefined
console.log(postTitlesArray)
});
function getHtml(webUrl) {
return fetch(webUrl)
.then(function(res) {
return res.json();
});
}

There are several conceptual things in the way of your approach doing what you want.
First, .map() is synchronous. That means it runs to completion and doesn't wait for any async operations to finish.
Second, setTimeout() is non-blocking. It just schedules a timer for some time in the future and then your .map() callback returns immediately, returning nothing.
So, your approach doesn't work at all.
From your comments, it appears that what you're trying to accomplish is to make a bunch of network calls in a loop, but put a delay between them so you don't get rate limited. There are a bunch of ways to do that.
There are two basic concepts you need to make that work:
Make your async operations be sequential so the next one doesn't get initiated until the prior one is done.
Put a delay that works with promises before starting the next one.
I'll first show an ES7 approach using async/await as it probably looks conceptually the simplest.
Using async/await to sequence asynchronous array access
function delay(t) {
return new Promise(resolve => {
setTimeout(resolve, t);
});
}
getNumbers().then(async function(numbersArray) {
//Supposed to return array of posts title
let results = [];
let delayT = 0; // first delay is zero
for (let number of numbersArray) {
console.log("Reading number" + number);
let r = await delay(delayT).then(() => {
delayT = 10 * 1000; // 10 seconds for subsequent delays
return getHtml("https://jsonplaceholder.typicode.com/posts/"+number).then(function(post) {
return post.title;
});
});
results.push(r);
}
return results;
});
Using .reduce() to sequence asynchronous array acess
If you wanted to do it without async/await, then you could use the .reduce() design pattern for sequencing async iteration of an array:
function delay(t) {
return new Promise(resolve => {
setTimeout(resolve, t);
});
}
getNumbers().then(numbersArray => {
//Supposed to return array of posts title
let results = [];
let delayT = 0; // first delay is zero
return numersArray.reduce((p, number) => {
return p.then(() => {
return delay(delayT).then(() => {
delayT = 10 * 1000; // 10 seconds for subsequent delays
return getHtml("https://jsonplaceholder.typicode.com/posts/"+number).then(function(post) {
results.push(post.title);
});
});
});
}, Promise.resolve()).then(() => {
// make array of results be the resolved value of the returned promise
return results;
});
});
Note that both of these algorithms are coded to not delay the first operation since presumably you don't need to, so it only delays between successive operations.
As coded, these are modeled after Promise.all() and they will reject if any of your getHtml() calls reject. If you want to return all results, even if some reject, then you can change:
return getHtml(...).then(...)
to
return getHtml(...).then(...).catch(err => null);
which will put null in the returned array for any result that failed, or if you want to log the error, you would use:
return getHtml(...).then(...).catch(err => {
console.log(err);
return null;
});
Generic Helper Function
And, since this is a somewhat generic problem, here's a generic helper function that lets you iterate an array calling an async operation on each item in the array and accumulating all the results into an array:
// Iterate through an array in sequence with optional delay between each async operation
// Returns a promise, resolved value is array of results
async iterateArrayAsync(array, fn, opts = {}) {
const options = Object.assign({
continueOnError: true,
delayBetweenAsyncOperations: 0,
errPlaceHolder: null
}, opts);
const results = [];
let delayT = 0; // no delay on first iteration
for (let item of array) {
results.push(await delay(delayT).then(() => {
return fn(item);
}).catch(err => {
console.log(err);
if (options.continueOnError) {
// keep going on errors, let options.errPlaceHolder be result for an error
return options.errPlaceHolder;
} else {
// abort processing on first error, will reject the promise
throw err;
}
}));
delayT = options.delayBetweenAsyncOperations; // set delay between requests
}
return results;
}
This accepts options that let you continueOnError, lets you set the delay between each async operation and lets you control the placeholder in the array of results for any failed operation (only used if continueOnError is set). All the options are optional.

I assume what you want to do is: 1) Get a list of numbers using getNumbers. 2) Iterate through each number from step one and form a url, with which an http request is made every ten seconds. 3) If a request is successfully sent, wait for its response. 4) Get post.title from response. 5) Wait until the iteration in step 2 ends, and return an array of all post.titles received from each call.
With the above assumptions in mind, I edit your code a bit and the following solution will work. See in jsfiddle.
I think the main problem with your code is that the map method doesn't return anything.
const getNumbers = () => {
return new Promise(function(resolve, reject) {
console.log("In function getNumbers");
var data = [1,2,3,4,5,6,7,8,9];
resolve(data);
});
};
const delay = (number, t) => {
return new Promise((resolve) => {
setTimeout(() => {
//make a http request
resolve(
getHtml("https://jsonplaceholder.typicode.com/posts/"+number)
.then(function(post) {
console.log('title', post.title)
return post.title;
})
)
}, t)
})
}
const getHtml = (webUrl) => {
return fetch(webUrl)
.then(function(res) {
return res.json();
});
}
getNumbers()
.then(numbersArray => {
//Supposed to return array of posts title
return Promise.all(numbersArray.map((number, i) => {
console.log("Reading number" + number);
return delay(number, 10000*(i+1));//make a request each ten seconds
}))
.then(postTitlesArray => {
console.log(postTitlesArray)
});
})

You can use Promise.all, assuming numbers are not in the thousands or else you can use batched Promise.all.
Then use throttlePeriod from here to make sure only 1 request is made every 10 seconds.
And then resolve failed requests with a special value so you don't loose all successes if one fails:
var getNumbers = () => {
return new Promise(function (resolve, reject) {
console.log("In function getNumbers");
var data = [1, 2, 3, 4, 5, 6, 7, 8, 9];
resolve(data);
});
};
function getHtml(webUrl) {
return fetch(webUrl)
.then(function (res) {
return res.json();
});
}
const Fail = function(reason){this.reason=reason;};
const isFail = x=>(x&&x.constructor)===Fail;
const notFail = x=>!isFail(x);
//maximum 1 per 10 seconds
//you can get throttle period from here:
//https://github.com/amsterdamharu/lib/blob/master/src/index.js
const max1Per10Seconds = lib.throttlePeriod(1,10000)(getHtml);
getNumbers()
.then(
numbersArray =>
Promise.all(//process all numbers
numbersArray
.map(//map number to url
number =>
`https://jsonplaceholder.typicode.com/posts/${number}`
)
//map url to promise
//max1Per10Seconds calls getHtml maximum 1 time per 10 seconds
// (will schedule the calls)
.map(max1Per10Seconds)
.map(//map promise to promise that does not reject
p=>//instead of rejecting promise, resolve with Fail value
//these Fail values can be filtered out of the result later.
//(see last then)
p.catch(err=>new Fail([err,number]))
)
)
).then(
//got the results, not all results may be successes
postTitlesArray => {
//is a comment really needed here?
const successes = postTitlesArray.filter(notFail);
const failed = postTitlesArray.filter(isFail);
}
);

Related

How can I add setTimeout() to promise of mapped async API fetch calls? [duplicate]

I have some code that is iterating over a list that was queried out of a database and making an HTTP request for each element in that list. That list can sometimes be a reasonably large number (in the thousands), and I would like to make sure I am not hitting a web server with thousands of concurrent HTTP requests.
An abbreviated version of this code currently looks something like this...
function getCounts() {
return users.map(user => {
return new Promise(resolve => {
remoteServer.getCount(user) // makes an HTTP request
.then(() => {
/* snip */
resolve();
});
});
});
}
Promise.all(getCounts()).then(() => { /* snip */});
This code is running on Node 4.3.2. To reiterate, can Promise.all be managed so that only a certain number of Promises are in progress at any given time?

P-Limit
I have compared promise concurrency limitation with a custom script, bluebird, es6-promise-pool, and p-limit. I believe that p-limit has the most simple, stripped down implementation for this need. See their documentation.
Requirements
To be compatible with async in example
ECMAScript 2017 (version 8)
Node version > 8.2.1
My Example
In this example, we need to run a function for every URL in the array (like, maybe an API request). Here this is called fetchData(). If we had an array of thousands of items to process, concurrency would definitely be useful to save on CPU and memory resources.
const pLimit = require('p-limit');
// Example Concurrency of 3 promise at once
const limit = pLimit(3);
let urls = [
"http://www.exampleone.com/",
"http://www.exampletwo.com/",
"http://www.examplethree.com/",
"http://www.examplefour.com/",
]
// Create an array of our promises using map (fetchData() returns a promise)
let promises = urls.map(url => {
// wrap the function we are calling in the limit function we defined above
return limit(() => fetchData(url));
});
(async () => {
// Only three promises are run at once (as defined above)
const result = await Promise.all(promises);
console.log(result);
})();
The console log result is an array of your resolved promises response data.

Using Array.prototype.splice
while (funcs.length) {
// 100 at a time
await Promise.all( funcs.splice(0, 100).map(f => f()) )
}

Note that Promise.all() doesn't trigger the promises to start their work, creating the promise itself does.
With that in mind, one solution would be to check whenever a promise is resolved whether a new promise should be started or whether you're already at the limit.
However, there is really no need to reinvent the wheel here. One library that you could use for this purpose is es6-promise-pool. From their examples:
var PromisePool = require('es6-promise-pool')
var promiseProducer = function () {
// Your code goes here.
// If there is work left to be done, return the next work item as a promise.
// Otherwise, return null to indicate that all promises have been created.
// Scroll down for an example.
}
// The number of promises to process simultaneously.
var concurrency = 3
// Create a pool.
var pool = new PromisePool(promiseProducer, concurrency)
// Start the pool.
var poolPromise = pool.start()
// Wait for the pool to settle.
poolPromise.then(function () {
console.log('All promises fulfilled')
}, function (error) {
console.log('Some promise rejected: ' + error.message)
})

If you know how iterators work and how they are consumed you would't need any extra library, since it can become very easy to build your own concurrency yourself. Let me demonstrate:
/* [Symbol.iterator]() is equivalent to .values()
const iterator = [1,2,3][Symbol.iterator]() */
const iterator = [1,2,3].values()
// loop over all items with for..of
for (const x of iterator) {
console.log('x:', x)
// notices how this loop continues the same iterator
// and consumes the rest of the iterator, making the
// outer loop not logging any more x's
for (const y of iterator) {
console.log('y:', y)
}
}
We can use the same iterator and share it across workers.
If you had used .entries() instead of .values() you would have gotten a iterator that yields [index, value] which i will demonstrate below with a concurrency of 2
const sleep = t => new Promise(rs => setTimeout(rs, t))
const iterator = Array.from('abcdefghij').entries()
// const results = [] || Array(someLength)
async function doWork (iterator, i) {
for (let [index, item] of iterator) {
await sleep(1000)
console.log(`Worker#${i}: ${index},${item}`)
// in case you need to store the results in order
// results[index] = item + item
// or if the order dose not mather
// results.push(item + item)
}
}
const workers = Array(2).fill(iterator).map(doWork)
// ^--- starts two workers sharing the same iterator
Promise.allSettled(workers).then(console.log.bind(null, 'done'))
The benefit of this is that you can have a generator function instead of having everything ready at once.
What's even more awesome is that you can do stream.Readable.from(iterator) in node (and eventually in whatwg streams as well). and with transferable ReadbleStream, this makes this potential very useful in the feature if you are working with web workers also for performances
Note: the different from this compared to example async-pool is that it spawns two workers, so if one worker throws an error for some reason at say index 5 it won't stop the other worker from doing the rest. So you go from doing 2 concurrency down to 1. (so it won't stop there) So my advise is that you catch all errors inside the doWork function

Instead of using promises for limiting http requests, use node's built-in http.Agent.maxSockets. This removes the requirement of using a library or writing your own pooling code, and has the added advantage more control over what you're limiting.
agent.maxSockets
By default set to Infinity. Determines how many concurrent sockets the agent can have open per origin. Origin is either a 'host:port' or 'host:port:localAddress' combination.
For example:
var http = require('http');
var agent = new http.Agent({maxSockets: 5}); // 5 concurrent connections per origin
var request = http.request({..., agent: agent}, ...);
If making multiple requests to the same origin, it might also benefit you to set keepAlive to true (see docs above for more info).

bluebird's Promise.map can take a concurrency option to control how many promises should be running in parallel. Sometimes it is easier than .all because you don't need to create the promise array.
const Promise = require('bluebird')
function getCounts() {
return Promise.map(users, user => {
return new Promise(resolve => {
remoteServer.getCount(user) // makes an HTTP request
.then(() => {
/* snip */
resolve();
});
});
}, {concurrency: 10}); // <---- at most 10 http requests at a time
}

As all others in this answer thread have pointed out, Promise.all() won't do the right thing if you need to limit concurrency. But ideally you shouldn't even want to wait until all of the Promises are done before processing them.
Instead, you want to process each result ASAP as soon as it becomes available, so you don't have to wait for the very last promise to finish before you start iterating over them.
So, here's a code sample that does just that, based partly on the answer by Endless and also on this answer by T.J. Crowder.
// example tasks that sleep and return a number
// in real life, you'd probably fetch URLs or something
const tasks = [];
for (let i = 0; i < 20; i++) {
tasks.push(async () => {
console.log(`start ${i}`);
await sleep(Math.random() * 1000);
console.log(`end ${i}`);
return i;
});
}
function sleep(ms) { return new Promise(r => setTimeout(r, ms)); }
(async () => {
for await (let value of runTasks(3, tasks.values())) {
console.log(`output ${value}`);
}
})();
async function* runTasks(maxConcurrency, taskIterator) {
// Each async iterator is a worker, polling for tasks from the shared taskIterator
// Sharing the iterator ensures that each worker gets unique tasks.
const asyncIterators = new Array(maxConcurrency);
for (let i = 0; i < maxConcurrency; i++) {
asyncIterators[i] = (async function* () {
for (const task of taskIterator) yield await task();
})();
}
yield* raceAsyncIterators(asyncIterators);
}
async function* raceAsyncIterators(asyncIterators) {
async function nextResultWithItsIterator(iterator) {
return { result: await iterator.next(), iterator: iterator };
}
/** #type Map<AsyncIterator<T>,
Promise<{result: IteratorResult<T>, iterator: AsyncIterator<T>}>> */
const promises = new Map(asyncIterators.map(iterator =>
[iterator, nextResultWithItsIterator(iterator)]));
while (promises.size) {
const { result, iterator } = await Promise.race(promises.values());
if (result.done) {
promises.delete(iterator);
} else {
promises.set(iterator, nextResultWithItsIterator(iterator));
yield result.value;
}
}
}
There's a lot of magic in here; let me explain.
This solution is built around async generator functions, which many JS developers may not be familiar with.
A generator function (aka function* function) returns a "generator," an iterator of results. Generator functions are allowed to use the yield keyword where you might have normally used a return keyword. The first time a caller calls next() on the generator (or uses a for...of loop), the function* function runs until it yields a value; that becomes the next() value of the iterator. But the subsequent time next() is called, the generator function resumes from the yield statement, right where it left off, even if it's in the middle of a loop. (You can also yield*, to yield all of the results of another generator function.)
An "async generator function" (async function*) is a generator function that returns an "async iterator," which is an iterator of promises. You can call for await...of on an async iterator. Async generator functions can use the await keyword, as you might do in any async function.
In the example, we call runTasks() with an array of task functions. runTasks() is an async generator function, so we can call it with a for await...of loop. Each time the loop runs, we'll process the result of the latest completed task.
runTasks() creates N async iterators, the workers. (Note that the workers are initially defined as async generator functions, but we immediately invoke each function, and store each resulting async iterator in the asyncIterators array.) The example calls runTasks with 3 concurrent workers, so no more than 3 tasks are launched at the same time. When any task completes, we immediately queue up the next task. (This is superior to "batching", where you do 3 tasks at once, await all three of them, and don't start the next batch of three until the entire previous batch has finished.)
runTasks() concludes by "racing" its async iterators with yield* raceAsyncIterators(). raceAsyncIterators() is like Promise.race() but it races N iterators of Promises instead of just N Promises; it returns an async iterator that yields the results of resolved Promises.
raceAsyncIterators() starts by defining a promises Map from each of the iterators to promises. Each promise is a promise for an iteration result along with the iterator that generated it.
With the promises map, we can Promise.race() the values of the map, giving us the winning iteration result and its iterator. If the iterator is completely done, we remove it from the map; otherwise we replace its Promise in the promises map with the iterator's next() Promise and yield result.value.
In conclusion, runTasks() is an async generator function that yields the results of racing N concurrent async iterators of tasks, so the end user can just for await (let value of runTasks(3, tasks.values())) to process each result as soon as it becomes available.

I suggest the library async-pool: https://github.com/rxaviers/async-pool
npm install tiny-async-pool
Description:
Run multiple promise-returning & async functions with limited concurrency using native ES6/ES7
asyncPool runs multiple promise-returning & async functions in a limited concurrency pool. It rejects immediately as soon as one of the promises rejects. It resolves when all the promises completes. It calls the iterator function as soon as possible (under concurrency limit).
Usage:
const timeout = i => new Promise(resolve => setTimeout(() => resolve(i), i));
await asyncPool(2, [1000, 5000, 3000, 2000], timeout);
// Call iterator (i = 1000)
// Call iterator (i = 5000)
// Pool limit of 2 reached, wait for the quicker one to complete...
// 1000 finishes
// Call iterator (i = 3000)
// Pool limit of 2 reached, wait for the quicker one to complete...
// 3000 finishes
// Call iterator (i = 2000)
// Itaration is complete, wait until running ones complete...
// 5000 finishes
// 2000 finishes
// Resolves, results are passed in given array order `[1000, 5000, 3000, 2000]`.

Here is my ES7 solution to a copy-paste friendly and feature complete Promise.all()/map() alternative, with a concurrency limit.
Similar to Promise.all() it maintains return order as well as a fallback for non promise return values.
I also included a comparison of the different implementation as it illustrates some aspects a few of the other solutions have missed.
Usage
const asyncFn = delay => new Promise(resolve => setTimeout(() => resolve(), delay));
const args = [30, 20, 15, 10];
await asyncPool(args, arg => asyncFn(arg), 4); // concurrency limit of 4
Implementation
async function asyncBatch(args, fn, limit = 8) {
// Copy arguments to avoid side effects
args = [...args];
const outs = [];
while (args.length) {
const batch = args.splice(0, limit);
const out = await Promise.all(batch.map(fn));
outs.push(...out);
}
return outs;
}
async function asyncPool(args, fn, limit = 8) {
return new Promise((resolve) => {
// Copy arguments to avoid side effect, reverse queue as
// pop is faster than shift
const argQueue = [...args].reverse();
let count = 0;
const outs = [];
const pollNext = () => {
if (argQueue.length === 0 && count === 0) {
resolve(outs);
} else {
while (count < limit && argQueue.length) {
const index = args.length - argQueue.length;
const arg = argQueue.pop();
count += 1;
const out = fn(arg);
const processOut = (out, index) => {
outs[index] = out;
count -= 1;
pollNext();
};
if (typeof out === 'object' && out.then) {
out.then(out => processOut(out, index));
} else {
processOut(out, index);
}
}
}
};
pollNext();
});
}
Comparison
// A simple async function that returns after the given delay
// and prints its value to allow us to determine the response order
const asyncFn = delay => new Promise(resolve => setTimeout(() => {
console.log(delay);
resolve(delay);
}, delay));
// List of arguments to the asyncFn function
const args = [30, 20, 15, 10];
// As a comparison of the different implementations, a low concurrency
// limit of 2 is used in order to highlight the performance differences.
// If a limit greater than or equal to args.length is used the results
// would be identical.
// Vanilla Promise.all/map combo
const out1 = await Promise.all(args.map(arg => asyncFn(arg)));
// prints: 10, 15, 20, 30
// total time: 30ms
// Pooled implementation
const out2 = await asyncPool(args, arg => asyncFn(arg), 2);
// prints: 20, 30, 15, 10
// total time: 40ms
// Batched implementation
const out3 = await asyncBatch(args, arg => asyncFn(arg), 2);
// prints: 20, 30, 20, 30
// total time: 45ms
console.log(out1, out2, out3); // prints: [30, 20, 15, 10] x 3
// Conclusion: Execution order and performance is different,
// but return order is still identical
Conclusion
asyncPool() should be the best solution as it allows new requests to start as soon as any previous one finishes.
asyncBatch() is included as a comparison as its implementation is simpler to understand, but it should be slower in performance as all requests in the same batch is required to finish in order to start the next batch.
In this contrived example, the non-limited vanilla Promise.all() is of course the fastest, while the others could perform more desirable in a real world congestion scenario.
Update
The async-pool library that others have already suggested is probably a better alternative to my implementation as it works almost identically and has a more concise implementation with a clever usage of Promise.race(): https://github.com/rxaviers/async-pool/blob/master/lib/es7.js
Hopefully my answer can still serve an educational value.

Semaphore is well known concurrency primitive that was designed to solve similar problems. It's very universal construct, implementations of Semaphore exist in many languages. This is how one would use Semaphore to solve this issue:
async function main() {
const s = new Semaphore(100);
const res = await Promise.all(
entities.map((users) =>
s.runExclusive(() => remoteServer.getCount(user))
)
);
return res;
}
I'm using implementation of Semaphore from async-mutex, it has decent documentation and TypeScript support.
If you want to dig deep into topics like this you can take a look at the book "The Little Book of Semaphores" which is freely available as PDF here

Unfortunately there is no way to do it with native Promise.all, so you have to be creative.
This is the quickest most concise way I could find without using any outside libraries.
It makes use of a newer javascript feature called an iterator. The iterator basically keeps track of what items have been processed and what haven't.
In order to use it in code, you create an array of async functions. Each async function asks the same iterator for the next item that needs to be processed. Each function processes its own item asynchronously, and when done asks the iterator for a new one. Once the iterator runs out of items, all the functions complete.
Thanks to #Endless for inspiration.
const items = [
'https://httpbin.org/bytes/2',
'https://httpbin.org/bytes/2',
'https://httpbin.org/bytes/2',
'https://httpbin.org/bytes/2',
'https://httpbin.org/bytes/2',
'https://httpbin.org/bytes/2',
'https://httpbin.org/bytes/2',
'https://httpbin.org/bytes/2'
]
// get a cursor that keeps track of what items have already been processed.
let cursor = items.entries();
// create 5 for loops that each run off the same cursor which keeps track of location
Array(5).fill().forEach(async () => {
for (let [index, url] of cursor){
console.log('getting url is ', index, url)
// run your async task instead of this next line
var text = await fetch(url).then(res => res.text())
console.log('text is', text.slice(0, 20))
}
})

Here goes basic example for streaming and 'p-limit'. It streams http read stream to mongo db.
const stream = require('stream');
const util = require('util');
const pLimit = require('p-limit');
const es = require('event-stream');
const streamToMongoDB = require('stream-to-mongo-db').streamToMongoDB;
const pipeline = util.promisify(stream.pipeline)
const outputDBConfig = {
dbURL: 'yr-db-url',
collection: 'some-collection'
};
const limit = pLimit(3);
async yrAsyncStreamingFunction(readStream) => {
const mongoWriteStream = streamToMongoDB(outputDBConfig);
const mapperStream = es.map((data, done) => {
let someDataPromise = limit(() => yr_async_call_to_somewhere())
someDataPromise.then(
function handleResolve(someData) {
data.someData = someData;
done(null, data);
},
function handleError(error) {
done(error)
}
);
})
await pipeline(
readStream,
JSONStream.parse('*'),
mapperStream,
mongoWriteStream
);
}

So many good solutions. I started out with the elegant solution posted by #Endless and ended up with this little extension method that does not use any external libraries nor does it run in batches (although assumes you have features like async, etc):
Promise.allWithLimit = async (taskList, limit = 5) => {
const iterator = taskList.entries();
let results = new Array(taskList.length);
let workerThreads = new Array(limit).fill(0).map(() =>
new Promise(async (resolve, reject) => {
try {
let entry = iterator.next();
while (!entry.done) {
let [index, promise] = entry.value;
try {
results[index] = await promise;
entry = iterator.next();
}
catch (err) {
results[index] = err;
}
}
// No more work to do
resolve(true);
}
catch (err) {
// This worker is dead
reject(err);
}
}));
await Promise.all(workerThreads);
return results;
};
Promise.allWithLimit = async (taskList, limit = 5) => {
const iterator = taskList.entries();
let results = new Array(taskList.length);
let workerThreads = new Array(limit).fill(0).map(() =>
new Promise(async (resolve, reject) => {
try {
let entry = iterator.next();
while (!entry.done) {
let [index, promise] = entry.value;
try {
results[index] = await promise;
entry = iterator.next();
}
catch (err) {
results[index] = err;
}
}
// No more work to do
resolve(true);
}
catch (err) {
// This worker is dead
reject(err);
}
}));
await Promise.all(workerThreads);
return results;
};
const demoTasks = new Array(10).fill(0).map((v,i) => new Promise(resolve => {
let n = (i + 1) * 5;
setTimeout(() => {
console.log(`Did nothing for ${n} seconds`);
resolve(n);
}, n * 1000);
}));
var results = Promise.allWithLimit(demoTasks);

#tcooc's answer was quite cool. Didn't know about it and will leverage it in the future.
I also enjoyed #MatthewRideout's answer, but it uses an external library!!
Whenever possible, I give a shot at developing this kind of things on my own, rather than going for a library. You end up learning a lot of concepts which seemed daunting before.
class Pool{
constructor(maxAsync) {
this.maxAsync = maxAsync;
this.asyncOperationsQueue = [];
this.currentAsyncOperations = 0
}
runAnother() {
if (this.asyncOperationsQueue.length > 0 && this.currentAsyncOperations < this.maxAsync) {
this.currentAsyncOperations += 1;
this.asyncOperationsQueue.pop()()
.then(() => { this.currentAsyncOperations -= 1; this.runAnother() }, () => { this.currentAsyncOperations -= 1; this.runAnother() })
}
}
add(f){ // the argument f is a function of signature () => Promise
this.runAnother();
return new Promise((resolve, reject) => {
this.asyncOperationsQueue.push(
() => f().then(resolve).catch(reject)
)
})
}
}
//#######################################################
// TESTS
//#######################################################
function dbCall(id, timeout, fail) {
return new Promise((resolve, reject) => {
setTimeout(() => {
if (fail) {
reject(`Error for id ${id}`);
} else {
resolve(id);
}
}, timeout)
}
)
}
const dbQuery1 = () => dbCall(1, 5000, false);
const dbQuery2 = () => dbCall(2, 5000, false);
const dbQuery3 = () => dbCall(3, 5000, false);
const dbQuery4 = () => dbCall(4, 5000, true);
const dbQuery5 = () => dbCall(5, 5000, false);
const cappedPool = new Pool(2);
const dbQuery1Res = cappedPool.add(dbQuery1).catch(i => i).then(i => console.log(`Resolved: ${i}`))
const dbQuery2Res = cappedPool.add(dbQuery2).catch(i => i).then(i => console.log(`Resolved: ${i}`))
const dbQuery3Res = cappedPool.add(dbQuery3).catch(i => i).then(i => console.log(`Resolved: ${i}`))
const dbQuery4Res = cappedPool.add(dbQuery4).catch(i => i).then(i => console.log(`Resolved: ${i}`))
const dbQuery5Res = cappedPool.add(dbQuery5).catch(i => i).then(i => console.log(`Resolved: ${i}`))
This approach provides a nice API, similar to thread pools in scala/java.
After creating one instance of the pool with const cappedPool = new Pool(2), you provide promises to it with simply cappedPool.add(() => myPromise).
Obliviously we must ensure that the promise does not start immediately and that is why we must "provide it lazily" with the help of the function.
Most importantly, notice that the result of the method add is a Promise which will be completed/resolved with the value of your original promise! This makes for a very intuitive use.
const resultPromise = cappedPool.add( () => dbCall(...))
resultPromise
.then( actualResult => {
// Do something with the result form the DB
}
)

This solution uses an async generator to manage concurrent promises with vanilla javascript. The throttle generator takes 3 arguments:
An array of values to be be supplied as arguments to a promise genrating function. (e.g. An array of URLs.)
A function that return a promise. (e.g. Returns a promise for an HTTP request.)
An integer that represents the maximum concurrent promises allowed.
Promises are only instantiated as required in order to reduce memory consumption. Results can be iterated over using a for await...of statement.
The example below provides a function to check promise state, the throttle async generator, and a simple function that return a promise based on setTimeout. The async IIFE at the end defines the reservoir of timeout values, sets the async iterable returned by throttle, then iterates over the results as they resolve.
If you would like a more complete example for HTTP requests, let me know in the comments.
Please note that Node.js 16+ is required in order async generators.
const promiseState = function( promise ) {
const control = Symbol();
return Promise
.race([ promise, control ])
.then( value => ( value === control ) ? 'pending' : 'fulfilled' )
.catch( () => 'rejected' );
}
const throttle = async function* ( reservoir, promiseClass, highWaterMark ) {
let iterable = reservoir.splice( 0, highWaterMark ).map( item => promiseClass( item ) );
while ( iterable.length > 0 ) {
await Promise.any( iterable );
const pending = [];
const resolved = [];
for ( const currentValue of iterable ) {
if ( await promiseState( currentValue ) === 'pending' ) {
pending.push( currentValue );
} else {
resolved.push( currentValue );
}
}
console.log({ pending, resolved, reservoir });
iterable = [
...pending,
...reservoir.splice( 0, highWaterMark - pending.length ).map( value => promiseClass( value ) )
];
yield Promise.allSettled( resolved );
}
}
const getTimeout = delay => new Promise( ( resolve, reject ) => {
setTimeout(resolve, delay, delay);
} );
( async () => {
const test = [ 1100, 1200, 1300, 10000, 11000, 9000, 5000, 6000, 3000, 4000, 1000, 2000, 3500 ];
const throttledRequests = throttle( test, getTimeout, 4 );
for await ( const timeout of throttledRequests ) {
console.log( timeout );
}
} )();

The concurrent function below will return a Promise which resolves to an array of resolved promise values, while implementing a concurrency limit. No 3rd party library.
// waits 50 ms then resolves to the passed-in arg
const sleepAndResolve = s => new Promise(rs => setTimeout(()=>rs(s), 50))
// queue 100 promises
const funcs = []
for(let i=0; i<100; i++) funcs.push(()=>sleepAndResolve(i))
//run the promises with a max concurrency of 10
concurrent(10,funcs)
.then(console.log) // prints [0,1,2...,99]
.catch(()=>console.log("there was an error"))
/**
* Run concurrent promises with a maximum concurrency level
* #param concurrency The number of concurrently running promises
* #param funcs An array of functions that return promises
* #returns a promise that resolves to an array of the resolved values from the promises returned by funcs
*/
function concurrent(concurrency, funcs) {
return new Promise((resolve, reject) => {
let index = -1;
const p = [];
for (let i = 0; i < Math.max(1, Math.min(concurrency, funcs.length)); i++)
runPromise();
function runPromise() {
if (++index < funcs.length)
(p[p.length] = funcs[index]()).then(runPromise).catch(reject);
else if (index === funcs.length)
Promise.all(p).then(resolve).catch(reject);
}
});
}
Here's the Typescript version if you are interested
/**
* Run concurrent promises with a maximum concurrency level
* #param concurrency The number of concurrently running promises
* #param funcs An array of functions that return promises
* #returns a promise that resolves to an array of the resolved values from the promises returned by funcs
*/
function concurrent<V>(concurrency:number, funcs:(()=>Promise<V>)[]):Promise<V[]> {
return new Promise((resolve,reject)=>{
let index = -1;
const p:Promise<V>[] = []
for(let i=0; i<Math.max(1,Math.min(concurrency, funcs.length)); i++) runPromise()
function runPromise() {
if (++index < funcs.length) (p[p.length] = funcs[index]()).then(runPromise).catch(reject)
else if (index === funcs.length) Promise.all(p).then(resolve).catch(reject)
}
})
}

No external libraries. Just plain JS.
It can be resolved using recursion.
The idea is that initially we immediately execute the maximum allowed number of queries and each of these queries should recursively initiate a new query on its completion.
In this example I populate successful responses together with errors and I execute all queries but it's possible to slightly modify algorithm if you want to terminate batch execution on the first failure.
async function batchQuery(queries, limit) {
limit = Math.min(queries.length, limit);
return new Promise((resolve, reject) => {
const responsesOrErrors = new Array(queries.length);
let startedCount = 0;
let finishedCount = 0;
let hasErrors = false;
function recursiveQuery() {
let index = startedCount++;
doQuery(queries[index])
.then(res => {
responsesOrErrors[index] = res;
})
.catch(error => {
responsesOrErrors[index] = error;
hasErrors = true;
})
.finally(() => {
finishedCount++;
if (finishedCount === queries.length) {
hasErrors ? reject(responsesOrErrors) : resolve(responsesOrErrors);
} else if (startedCount < queries.length) {
recursiveQuery();
}
});
}
for (let i = 0; i < limit; i++) {
recursiveQuery();
}
});
}
async function doQuery(query) {
console.log(`${query} started`);
const delay = Math.floor(Math.random() * 1500);
return new Promise((resolve, reject) => {
setTimeout(() => {
if (delay <= 1000) {
console.log(`${query} finished successfully`);
resolve(`${query} success`);
} else {
console.log(`${query} finished with error`);
reject(`${query} error`);
}
}, delay);
});
}
const queries = new Array(10).fill('query').map((query, index) => `${query}_${index + 1}`);
batchQuery(queries, 3)
.then(responses => console.log('All successfull', responses))
.catch(responsesWithErrors => console.log('All with several failed', responsesWithErrors));

So I tried to make some examples shown work for my code, but since this was only for an import script and not production code, using the npm package batch-promises was surely the easiest path for me
NOTE: Requires runtime to support Promise or to be polyfilled.
Api
batchPromises(int: batchSize, array: Collection, i => Promise: Iteratee)
The Promise: Iteratee will be called after each batch.
Use:
batch-promises
Easily batch promises
NOTE: Requires runtime to support Promise or to be polyfilled.
Api
batchPromises(int: batchSize, array: Collection, i => Promise: Iteratee)
The Promise: Iteratee will be called after each batch.
Use:
import batchPromises from 'batch-promises';
batchPromises(2, [1,2,3,4,5], i => new Promise((resolve, reject) => {
// The iteratee will fire after each batch resulting in the following behaviour:
// # 100ms resolve items 1 and 2 (first batch of 2)
// # 200ms resolve items 3 and 4 (second batch of 2)
// # 300ms resolve remaining item 5 (last remaining batch)
setTimeout(() => {
resolve(i);
}, 100);
}))
.then(results => {
console.log(results); // [1,2,3,4,5]
});

Recursion is the answer if you don't want to use external libraries
downloadAll(someArrayWithData){
var self = this;
var tracker = function(next){
return self.someExpensiveRequest(someArrayWithData[next])
.then(function(){
next++;//This updates the next in the tracker function parameter
if(next < someArrayWithData.length){//Did I finish processing all my data?
return tracker(next);//Go to the next promise
}
});
}
return tracker(0);
}

expanding on the answer posted by #deceleratedcaviar, I created a 'batch' utility function that takes as argument: array of values, concurrency limit and processing function. Yes I realize that using Promise.all this way is more akin to batch processing vs true concurrency, but if the goal is to limit excessive number of HTTP calls at one time I go with this approach due to its simplicity and no need for external library.
async function batch(o) {
let arr = o.arr
let resp = []
while (arr.length) {
let subset = arr.splice(0, o.limit)
let results = await Promise.all(subset.map(o.process))
resp.push(results)
}
return [].concat.apply([], resp)
}
let arr = []
for (let i = 0; i < 250; i++) { arr.push(i) }
async function calc(val) { return val * 100 }
(async () => {
let resp = await batch({
arr: arr,
limit: 100,
process: calc
})
console.log(resp)
})();

One more solution with a custom promise library (CPromise):
using generators Live codesandbox demo
import { CPromise } from "c-promise2";
import cpFetch from "cp-fetch";
const promise = CPromise.all(
function* () {
const urls = [
"https://run.mocky.io/v3/7b038025-fc5f-4564-90eb-4373f0721822?mocky-delay=2s&x=1",
"https://run.mocky.io/v3/7b038025-fc5f-4564-90eb-4373f0721822?mocky-delay=2s&x=2",
"https://run.mocky.io/v3/7b038025-fc5f-4564-90eb-4373f0721822?mocky-delay=2s&x=3",
"https://run.mocky.io/v3/7b038025-fc5f-4564-90eb-4373f0721822?mocky-delay=2s&x=4",
"https://run.mocky.io/v3/7b038025-fc5f-4564-90eb-4373f0721822?mocky-delay=2s&x=5",
"https://run.mocky.io/v3/7b038025-fc5f-4564-90eb-4373f0721822?mocky-delay=2s&x=6",
"https://run.mocky.io/v3/7b038025-fc5f-4564-90eb-4373f0721822?mocky-delay=2s&x=7"
];
for (const url of urls) {
yield cpFetch(url); // add a promise to the pool
console.log(`Request [${url}] completed`);
}
},
{ concurrency: 2 }
).then(
(v) => console.log(`Done: `, v),
(e) => console.warn(`Failed: ${e}`)
);
// yeah, we able to cancel the task and abort pending network requests
// setTimeout(() => promise.cancel(), 4500);
using mapper Live codesandbox demo
import { CPromise } from "c-promise2";
import cpFetch from "cp-fetch";
const promise = CPromise.all(
[
"https://run.mocky.io/v3/7b038025-fc5f-4564-90eb-4373f0721822?mocky-delay=2s&x=1",
"https://run.mocky.io/v3/7b038025-fc5f-4564-90eb-4373f0721822?mocky-delay=2s&x=2",
"https://run.mocky.io/v3/7b038025-fc5f-4564-90eb-4373f0721822?mocky-delay=2s&x=3",
"https://run.mocky.io/v3/7b038025-fc5f-4564-90eb-4373f0721822?mocky-delay=2s&x=4",
"https://run.mocky.io/v3/7b038025-fc5f-4564-90eb-4373f0721822?mocky-delay=2s&x=5",
"https://run.mocky.io/v3/7b038025-fc5f-4564-90eb-4373f0721822?mocky-delay=2s&x=6",
"https://run.mocky.io/v3/7b038025-fc5f-4564-90eb-4373f0721822?mocky-delay=2s&x=7"
],
{
mapper: (url) => {
console.log(`Request [${url}]`);
return cpFetch(url);
},
concurrency: 2
}
).then(
(v) => console.log(`Done: `, v),
(e) => console.warn(`Failed: ${e}`)
);
// yeah, we able to cancel the task and abort pending network requests
//setTimeout(() => promise.cancel(), 4500);

Warning this has not been benchmarked for efficiency and does a lot of array copying/creation
If you want a more functional approach you could do something like:
import chunk from 'lodash.chunk';
const maxConcurrency = (max) => (dataArr, promiseFn) =>
chunk(dataArr, max).reduce(
async (agg, batch) => [
...(await agg),
...(await Promise.all(batch.map(promiseFn)))
],
[]
);
and then to you could use it like:
const randomFn = (data) =>
new Promise((res) => setTimeout(
() => res(data + 1),
Math.random() * 1000
));
const result = await maxConcurrency(5)(
[1, 2, 3, 4, 5, 6, 7, 8, 9, 10],
randomFn
);
console.log('result+++', result);

I had been using the bottleneck library, which I actually really liked, but in my case wasn't releasing memory and kept tanking long running jobs... Which isn't great for running the massive jobs that you likely want a throttling/concurrency library for in the first place.
I needed a simple, low-overhead, easy to maintain solution. I also wanted something that kept the pool topped up, rather than simply batching predefined chunks... In the case of a downloader, this will stop that nGB file from holding up your queue for minutes/hours at a time, even though the rest of the batch finished ages ago.
This is the Node.js v16+, no-dependency, async generator solution I've been using instead:
const promiseState = function( promise ) {
// A promise could never resolve to a unique symbol unless it was in this scope
const control = Symbol();
// This helps us determine the state of the promise... A little heavy, but it beats a third-party promise library. The control is the second element passed to Promise.race() since it will only resolve first if the promise being tested is pending.
return Promise
.race([ promise, control ])
.then( value => ( value === control ) ? 'pending' : 'fulfilled' )
.catch( () => 'rejected' );
}
const throttle = async function* ( reservoir, promiseFunction, highWaterMark ) {
let iterable = reservoir.splice( 0, highWaterMark ).map( item => promiseFunction( item ) );
while ( iterable.length > 0 ) {
// When a promise has resolved we have space to top it up to the high water mark...
await Promise.any( iterable );
const pending = [];
const resolved = [];
// This identifies the promise(s) that have resolved so that we can yield them
for ( const currentValue of iterable ) {
if ( await promiseState( currentValue ) === 'pending' ) {
pending.push( currentValue );
} else {
resolved.push( currentValue );
}
}
// Put the remaining promises back into iterable, and top it to the high water mark
iterable = [
...pending,
...reservoir.splice( 0, highWaterMark - pending.length ).map( value => promiseFunction( value ) )
];
yield Promise.allSettled( resolved );
}
}
// This is just an example of what would get passed as "promiseFunction"... This can be the function that returns your HTTP request promises
const getTimeout = delay => new Promise( (resolve, reject) => setTimeout(resolve, delay, delay) );
// This is just the async IIFE that bootstraps this example
( async () => {
const test = [ 1000, 2000, 3000, 4000, 5000, 6000, 1500, 2500, 3500, 4500, 5500, 6500 ];
for await ( const timeout of throttle( test, getTimeout, 4 ) ) {
console.log( timeout );
}
} )();

I have solution with creating chunks and using .reduce function to wait each chunks promise.alls to be finished. And also I add some delay if the promises have some call limits.
export function delay(ms: number) {
return new Promise<void>((resolve) => setTimeout(resolve, ms));
}
export const chunk = <T>(arr: T[], size: number): T[][] => [
...Array(Math.ceil(arr.length / size)),
].map((_, i) => arr.slice(size * i, size + size * i));
const myIdlist = []; // all items
const groupedIdList = chunk(myIdList, 20); // grouped by 20 items
await groupedIdList.reduce(async (prev, subIdList) => {
await prev;
// Make sure we wait for 500 ms after processing every page to prevent overloading the calls.
const data = await Promise.all(subIdList.map(myPromise));
await delay(500);
}, Promise.resolve());

Using tiny-async-pool ES9 for await...of API, you can do the following:
const asyncPool = require("tiny-async-pool");
const getCount = async (user) => ([user, remoteServer.getCount(user)]);
const concurrency = 2;
for await (const [user, count] of asyncPool(concurrency, users, getCount)) {
console.log(user, count);
}
The above asyncPool function returns an async iterator that yields as soon as a promise completes (under concurrency limit) and it rejects immediately as soon as one of the promises rejects.

It is possible to limit requests to server by using https://www.npmjs.com/package/job-pipe
Basically you create a pipe and tell it how many concurrent requests you want:
const pipe = createPipe({ throughput: 6, maxQueueSize: Infinity })
Then you take your function which performs call and force it through the pipe to create a limited amount of calls at the same time:
const makeCall = async () => {...}
const limitedMakeCall = pipe(makeCall)
Finally, you call this method as many times as you need as if it was unchanged and it will limit itself on how many parallel executions it can handle:
await limitedMakeCall()
await limitedMakeCall()
await limitedMakeCall()
await limitedMakeCall()
await limitedMakeCall()
....
await limitedMakeCall()
Profit.

I suggest not downloading packages and not writing hundreds of lines of code:
async function async_arr<T1, T2>(
arr: T1[],
func: (x: T1) => Promise<T2> | T2, //can be sync or async
limit = 5
) {
let results: T2[] = [];
let workers = [];
let current = Math.min(arr.length, limit);
async function process(i) {
if (i < arr.length) {
results[i] = await Promise.resolve(func(arr[i]));
await process(current++);
}
}
for (let i = 0; i < current; i++) {
workers.push(process(i));
}
await Promise.all(workers);
return results;
}

Here's my recipe, based on killdash9's answer.
It allows to choose the behaviour on exceptions (Promise.all vs Promise.allSettled).
// Given an array of async functions, runs them in parallel,
// with at most maxConcurrency simultaneous executions
// Except for that, behaves the same as Promise.all,
// unless allSettled is true, where it behaves as Promise.allSettled
function concurrentRun(maxConcurrency = 10, funcs = [], allSettled = false) {
if (funcs.length <= maxConcurrency) {
const ps = funcs.map(f => f());
return allSettled ? Promise.allSettled(ps) : Promise.all(ps);
}
return new Promise((resolve, reject) => {
let idx = -1;
const ps = new Array(funcs.length);
function nextPromise() {
idx += 1;
if (idx < funcs.length) {
(ps[idx] = funcs[idx]()).then(nextPromise).catch(allSettled ? nextPromise : reject);
} else if (idx === funcs.length) {
(allSettled ? Promise.allSettled(ps) : Promise.all(ps)).then(resolve).catch(reject);
}
}
for (let i = 0; i < maxConcurrency; i += 1) nextPromise();
});
}

I know there are a lot of answers already, but I ended up using a very simple, no library or sleep required, solution that uses only a few commands. Promise.all() simply lets you know when all the promises passed to it are finalized. So, you can check on the queue intermittently to see if it is ready for more work, if so, add more processes.
For example:
// init vars
const batchSize = 5
const calls = []
// loop through data and run processes
for (let [index, data] of [1,2,3].entries()) {
// pile on async processes
calls.push(doSomethingAsyncWithData(data))
// every 5th concurrent call, wait for them to finish before adding more
if (index % batchSize === 0) await Promise.all(calls)
}
// clean up for any data to process left over if smaller than batch size
const allFinishedProcs = await Promise.all(calls)

A good solution for controlling the maximum number of promises/requests is to split your list of requests into pages, and produce only requests for one page at a time.
The example below makes use of iter-ops library:
import {pipeAsync, map, page} from 'iter-ops';
const i = pipeAsync(
users, // make it asynchronous
page(10), // split into pages of 10 items in each
map(p => Promise.all(p.map(u => u.remoteServer.getCount(u)))), // map into requests
wait() // resolve each page in the pipeline
);
// below triggers processing page-by-page:
for await(const p of i) {
//=> p = resolved page of data
}
This way it won't try to create more requests/promises than the size of one page.

Javascript: Making sure one async function doesn't run until the other one is complete; working with promises

I'm working with fetching information from a github repository. I want to get the list of pull requests within that repo, get the list of commits associated with each pull request, then for each commit I want to get information such as the author of the commit, the number of files associated with each commit and the number of additions and deletions made to each file. I'm using axios and the github API to accomplish this. I know how to work with the API, but the promises and async functions are keeping me from accomplishing my task. I have the following code:
const axios = require('axios');
var mapOfInformationObjects = new Map();
var listOfCommits = [];
var listOfSHAs = [];
var gitApiPrefix = link I'll use to start fetching data;
var listOfPullRequestDataObjects = [];
var listOfPullRequestNumbers = [];
var mapOfPullNumberToCommits = new Map();
function getAllPullRequests(gitPullRequestApiLink) {
return new Promise((resolve, reject) => {
axios.get(gitPullRequestApiLink).then((response) =>{
listOfPullRequestDataObjects = response['data'];
var k;
for (k = 0; k < listOfPullRequestDataObjects.length; k++){
listOfPullRequestNumbers.push(listOfPullRequestDataObjects[k]['number']);
}
resolve(listOfPullRequestNumbers);
}).catch((error) => {
reject(error);
})
})
}
function getCommitsForEachPullRequestNumber(listOfPRNumbers) {
var j;
for (j = 0; j < listOfPRNumbers.length; j++) {
currPromise = new Promise((resolve, reject) => {
currentGitApiLink = gitApiPrefix + listOfPRNumbers[j] + "/commits";
axios.get(currentGitApiLink).then((response) => {
mapOfPullNumberToCommits.set(listOfPRNumbers[j], response['data']);
resolve("Done with Pull Request Number: " + listOfPRNumbers[j]);
}).catch((error) => {
reject(error);
})
})
}
}
function getListOfCommits(gitCommitApiLink){
return new Promise((resolve, reject) => {
axios.get(gitCommitApiLink).then((response) => {
resolve(response);
}).catch((error) => {
reject(error);
})
})
}
So far, I made some functions that I would like to call sequentially.
First I'd like to call getAllPullRequestNumbers(someLink)
Then I'd like to call getCommitsForEachPullRequestNumber(listofprnumbers)
Then getListOfCommits(anotherLink)
So it would look something like
getAllPullRequestNumbers(someLink)
getCommitsForEachPullRequestNumber(listofprnumbers)
getListOfCommits(anotherlink)
But two problems arise:
1) I'm not sure if this is how you would call the functions so that the first function in the sequence completes before the other.
2) Because I'm not familiar with Javascript, I'm not sure, especially with the getCommitsForEachPullRequestNumber function since you run a loop and call axios.get() on each iteration of the loop, if this is how you work with promises within the functions.
Would this be how you would go about accomplishing these two tasks? Any help is much appreciated. Thanks!

When you a number of asynchronous operations (represented by promises) that you can run all together and you want to know when they are all done, you use Promise.all(). You collect an array of promises and pass it to Promise.all() and it will tell you when they have all completed or when one of them triggers an error. If all completed, Promise.all() will return a promise that resolves to an array of results (one for each asynchronous operation).
When you're iterating an array to do your set of asynchronous operations, it then works best to use .map() because that helps you create a parallel array of promises that you can feed to Promise.all(). Here's how you do that in getCommitsForEachPullRequestNumber():
function getCommitsForEachPullRequestNumber(listOfPRNumbers) {
let mapOfPullNumberToCommits = new Map();
return Promise.all(listOfPRNumbers.map(item => {
let currentGitApiLink = gitApiPrefix + item + "/commits";
return axios.get(currentGitApiLink).then(response => {
// put data into the map
mapOfPullNumberToCommits.set(item, response.data);
});
})).then(() => {
// make resolved value be the map we created, now that everything is done
return mapOfPullNumberToCommits;
});
}
// usage:
getCommitsForEachPullRequestNumber(list).then(results => {
console.log(results);
}).catch(err => {
console.log(err);
});
Then, in getListOfCommits(), since axios already returns a promise, there is no reason to wrap it in a manually created promise. That is, in fact, consider a promise anti-pattern. Instead, just return the promise that axios already returns. In fact, there's probably not even a reason to have this as a function since one can just use axios.get() directly to achieve the same result:
function getListOfCommits(gitCommitApiLink){
return axios.get(gitCommitApiLink);
}
Then, in getAllPullRequests() it appears you are just doing one axios.get() call and then processing the results. That can be done like this:
function getAllPullRequests(gitPullRequestApiLink) {
return axios.get(gitPullRequestApiLink).then(response => {
let listOfPullRequestDataObjects = response.data;
return listOfPullRequestDataObjects.map(item => {
return item.number;
});
});
}
Now, if you're trying to execute these three operations sequentially in this order:
getAllPullRequests(someLink)
getCommitsForEachPullRequestNumber(listofprnumbers)
getListOfCommits(anotherlink)
You can chain the promises from those three operations together to sequence them:
getAllPullRequests(someLink)
.then(getCommitsForEachPullRequestNumber)
.then(mapOfPullNumberToCommits => {
// not entirely sure what you want to do here, perhaps
// call getListOfCommits on each item in the map?
}).catch(err => {
console.log(err);
});
Or, if you put this code in an async function, then you can use async/awit:
async function getAllCommits(someLink) {
let pullRequests = await getAllPullRequests(someLink);
let mapOfPullNumberToCommits = await getCommitsForEachPullRequestNumber(pullRequests);
// then use getlistOfCommits() somehow to process mapOfPullNumberToCommits
return finalResults;
}
getAllCommits.then(finalResults => {
console.log(finalResults);
}).catch(err => {
console.log(err);
});

not as clean as jfriend00 solution,
but I played with your code and it finally worked
https://repl.it/#gui3/githubApiPromises
you get the list of commits in the variable listOfCommits
I don't understand the purpose of your last function, so I dropped it

Promise 2 resolves before the Promise 1

I am doing a search in the textfield and as I type, there is a call going to the backend after say 100ms.
For example, if we search "5041" and immediately search for "50" and again make it "5041", then there are 3 calls made to the backend.
1."5041" -> Promise 1
2."50" -> Promise 2
3."5041" -> Promise 3
However, promise 3 (web call takes 200ms) resolves before promise 2 (web call takes 500ms) which makes the screen reflect results for promise 2 ("50") when all I have in the textfield is "5041".
I need some way to let user type in the textfield without blocking the user along with the ability to show results for only the last call.
This is something that can be achieved using switchMap from rxjs in an angular app. However I need a way to achieve the same in vanilla JS.

First you can wrap your fetchData function into a something like fetchLatestSearchResults function which notes the time when network call was made and return the latest result from all the network calls(irrespective of what data was returned from server)
const generateLatestSearchFetch = function(fetchFunc){
let mostRecentResult = null;
let mostRecentResultFetchTime = Date.now();
return (...args) => {
const myFetchStartTime = Date.now();
return fetchFunc(...args)
.then(data => {
if (myFetchStartTime > mostRecentResultFetchTime) {
mostRecentResult = data;
mostRecentResultFetchTime = myFetchStartTime
}
return mostRecentResult;
});
}
};
Use Like:
fetchData = generateLatestSearchFetch(fetchData);
fetchData('10'); // resolves first and returns result for 10
fetchData('102'); // resolves third and returns result for 1024
fetchData('1024'); // resolves second and returns result for 1024
Last but not the least, use debounce more on this to optimize number of network calls made for every type event.

You need a "last" function:
// takes a function returning a promise and only reports the last resort
function last(fn) {
let p;
return function(...args) {
let current = fn(); // call the function
p = current; // mark it as the last call
return p.then(result => {
// ask am I still the last call?
if (p === current) return result;
else return new Promise(() => {}); // never resolve
});
}
}
let onlyLastSearch = last((name) => fetch('/api?name=' + name));
onlyLastSearch('a'); // will be ignored
onlyLastSearch('b'); // will be ignored
onlyLastSearch('c'); // only relevant result

You can use observer pattern for this.
const createWrapper = (fn) => {
let counter = 0;
let lastFetchId = 0;
const listeners = [];
return {
fetch: (str) => {
let id = ++counter;
fn(str).then((data) => {
if(id > lastFetchId) {
listeners.forEach(fn => {
fn(data);
});
lastFetchId = id;
}
});
},
listen: (fn) => {
listeners.push(fn);
return () => {
const index = listeners.indexOf(fn);
listeners.splice(index, 1);
};
}
}
}
const SearchWrapper = createWrapper(fetchData);
SearchWrapper.fetch('a');
SearchWrapper.fetch('b');
SearchWrapper.fetch('c');
SearchWrapper.listen((data) => {
console.log(data);
})

Programmatically Obtain All YouTube Videos Belonging to a User

Utilizing the YouTube Data API we can make a query to to obtain the first 50 (maximum amount of results obtainable with a single query) videos belonging to a user with the following request: https://www.googleapis.com/youtube/v3/search?key={access_key}&channelId={users_id}&part=id&order=date&maxResults=50&type=video
If there are more than 50 videos, then the resulting JSON will have a nextPageToken field, to obtain the next 50 videos we can append &pageToken={nextPageToken} to the above request, producing the next page of 50 videos. This is repeatable until the nextPageToken field is no longer present.
Here is a simple JavaScript function I wrote using the fetch API to obtain a single page of videos, specified by the nextPageToken parameter (or lack thereof).
function getUploadedVideosPage(nextPageToken) {
return new Promise((resolve, reject) => {
let apiUrl = 'https://www.googleapis.com/youtube/v3/search?key={access_key}&channelId={users_id}&part=id&order=date&maxResults=50&type=video';
if(nextPageToken)
apiUrl += '&pageToken=' + nextPageToken;
fetch(apiUrl)
.then((response) => {
response.json()
.then((data) => {
resolve(data);
});
});
});
}
Now we need a wrapper function that will iteratively call getUploadedVideosPage for as long as we have a nextPageToken. Here is my 'working' albeit dangerous (more on this later) implementation.
function getAllUploadedVideos() {
return new Promise((resolve, reject) => {
let dataJoined = [];
let chain = getUploadedVideosPage();
for(let i = 0; i < 20000; ++i) {
chain = chain
.then((data) => {
dataJoined.push(data);
if(data.nextPageToken !== undefined)
return getUploadedVideosPage(data.nextPageToken);
else
resolve(dataJoined);
});
}
});
}
The 'dangerous' aspect is the condition of the for loop, theoretically it should be infinite for(;;) since we have no predefined way of knowing exactly how many iterations to make, and the only way to terminate the loop should be with the resolve statement. Yet when I implement it this way it truly is infinite and never terminates.
Hence why I hard coded 20,000 iterations, and it seems to work but I don't trust the reliability of this solution. I was hopping somebody here can shed some light on how to go about implementing this iterative Promise chain that has no predefined terminating condition.

You can do this all with one function that calls itself if applicable.
You are also using an explicit promise construction anti-pattern wrapping fetch() in new Promise since fetch() already returns a promise
function getVideos(nextPageToken, results = []) {
let apiUrl = 'https://www.googleapis.com/youtube/v3/search?key={access_key}&channelId={users_id}&part=id&order=date&maxResults=50&type=video';
if (nextPageToken) {
apiUrl += '&pageToken=' + nextPageToken;
}
// return fetch() promise
return fetch(apiUrl)
.then(response => response.json())
.then(data => {
// merge new data into final results array
results = results.concat(data);
if (data.nextPageToken !== undefined) {
// return another request promise
return getVideos(data.nextPageToken, results);
} else {
// all done so return the final results
return results
}
});
}
// usage
getVideos().then(results=>{/*do something with all results*/})
.catch(err=>console.log('One of the requests failed'));

Get rid of the for loop altogether. Something like this:
function getAllUploadedVideos() {
return new Promise((resolve, reject) => {
let dataJoined = [];
function getNextPage(nextPageToken) {
return new Promise((resolve, reject) => {
getUploadedVideosPage(nextPageToken)
.then((data) => {
dataJoined.push(data);
if(data.nextPageToken !== undefined) {
resolve(data.nextPageToken);
}
else {
reject();
}
})
.catch((err) => {
// Just in case getUploadedVideosPage errors
reject(err);
});
});
}
getNextPage()
.then((nextPageToken) => {
getNextPage(nextPageToken);
})
.catch(() => {
// This will hit when there is no more pages to grab
resolve(dataJoined);
});
});
}

What is the best way to limit concurrency when using ES6's Promise.all()?

I have some code that is iterating over a list that was queried out of a database and making an HTTP request for each element in that list. That list can sometimes be a reasonably large number (in the thousands), and I would like to make sure I am not hitting a web server with thousands of concurrent HTTP requests.
An abbreviated version of this code currently looks something like this...
function getCounts() {
return users.map(user => {
return new Promise(resolve => {
remoteServer.getCount(user) // makes an HTTP request
.then(() => {
/* snip */
resolve();
});
});
});
}
Promise.all(getCounts()).then(() => { /* snip */});
This code is running on Node 4.3.2. To reiterate, can Promise.all be managed so that only a certain number of Promises are in progress at any given time?

P-Limit
I have compared promise concurrency limitation with a custom script, bluebird, es6-promise-pool, and p-limit. I believe that p-limit has the most simple, stripped down implementation for this need. See their documentation.
Requirements
To be compatible with async in example
ECMAScript 2017 (version 8)
Node version > 8.2.1
My Example
In this example, we need to run a function for every URL in the array (like, maybe an API request). Here this is called fetchData(). If we had an array of thousands of items to process, concurrency would definitely be useful to save on CPU and memory resources.
const pLimit = require('p-limit');
// Example Concurrency of 3 promise at once
const limit = pLimit(3);
let urls = [
"http://www.exampleone.com/",
"http://www.exampletwo.com/",
"http://www.examplethree.com/",
"http://www.examplefour.com/",
]
// Create an array of our promises using map (fetchData() returns a promise)
let promises = urls.map(url => {
// wrap the function we are calling in the limit function we defined above
return limit(() => fetchData(url));
});
(async () => {
// Only three promises are run at once (as defined above)
const result = await Promise.all(promises);
console.log(result);
})();
The console log result is an array of your resolved promises response data.

Using Array.prototype.splice
while (funcs.length) {
// 100 at a time
await Promise.all( funcs.splice(0, 100).map(f => f()) )
}

Note that Promise.all() doesn't trigger the promises to start their work, creating the promise itself does.
With that in mind, one solution would be to check whenever a promise is resolved whether a new promise should be started or whether you're already at the limit.
However, there is really no need to reinvent the wheel here. One library that you could use for this purpose is es6-promise-pool. From their examples:
var PromisePool = require('es6-promise-pool')
var promiseProducer = function () {
// Your code goes here.
// If there is work left to be done, return the next work item as a promise.
// Otherwise, return null to indicate that all promises have been created.
// Scroll down for an example.
}
// The number of promises to process simultaneously.
var concurrency = 3
// Create a pool.
var pool = new PromisePool(promiseProducer, concurrency)
// Start the pool.
var poolPromise = pool.start()
// Wait for the pool to settle.
poolPromise.then(function () {
console.log('All promises fulfilled')
}, function (error) {
console.log('Some promise rejected: ' + error.message)
})

If you know how iterators work and how they are consumed you would't need any extra library, since it can become very easy to build your own concurrency yourself. Let me demonstrate:
/* [Symbol.iterator]() is equivalent to .values()
const iterator = [1,2,3][Symbol.iterator]() */
const iterator = [1,2,3].values()
// loop over all items with for..of
for (const x of iterator) {
console.log('x:', x)
// notices how this loop continues the same iterator
// and consumes the rest of the iterator, making the
// outer loop not logging any more x's
for (const y of iterator) {
console.log('y:', y)
}
}
We can use the same iterator and share it across workers.
If you had used .entries() instead of .values() you would have gotten a iterator that yields [index, value] which i will demonstrate below with a concurrency of 2
const sleep = t => new Promise(rs => setTimeout(rs, t))
const iterator = Array.from('abcdefghij').entries()
// const results = [] || Array(someLength)
async function doWork (iterator, i) {
for (let [index, item] of iterator) {
await sleep(1000)
console.log(`Worker#${i}: ${index},${item}`)
// in case you need to store the results in order
// results[index] = item + item
// or if the order dose not mather
// results.push(item + item)
}
}
const workers = Array(2).fill(iterator).map(doWork)
// ^--- starts two workers sharing the same iterator
Promise.allSettled(workers).then(console.log.bind(null, 'done'))
The benefit of this is that you can have a generator function instead of having everything ready at once.
What's even more awesome is that you can do stream.Readable.from(iterator) in node (and eventually in whatwg streams as well). and with transferable ReadbleStream, this makes this potential very useful in the feature if you are working with web workers also for performances
Note: the different from this compared to example async-pool is that it spawns two workers, so if one worker throws an error for some reason at say index 5 it won't stop the other worker from doing the rest. So you go from doing 2 concurrency down to 1. (so it won't stop there) So my advise is that you catch all errors inside the doWork function

Instead of using promises for limiting http requests, use node's built-in http.Agent.maxSockets. This removes the requirement of using a library or writing your own pooling code, and has the added advantage more control over what you're limiting.
agent.maxSockets
By default set to Infinity. Determines how many concurrent sockets the agent can have open per origin. Origin is either a 'host:port' or 'host:port:localAddress' combination.
For example:
var http = require('http');
var agent = new http.Agent({maxSockets: 5}); // 5 concurrent connections per origin
var request = http.request({..., agent: agent}, ...);
If making multiple requests to the same origin, it might also benefit you to set keepAlive to true (see docs above for more info).

bluebird's Promise.map can take a concurrency option to control how many promises should be running in parallel. Sometimes it is easier than .all because you don't need to create the promise array.
const Promise = require('bluebird')
function getCounts() {
return Promise.map(users, user => {
return new Promise(resolve => {
remoteServer.getCount(user) // makes an HTTP request
.then(() => {
/* snip */
resolve();
});
});
}, {concurrency: 10}); // <---- at most 10 http requests at a time
}

As all others in this answer thread have pointed out, Promise.all() won't do the right thing if you need to limit concurrency. But ideally you shouldn't even want to wait until all of the Promises are done before processing them.
Instead, you want to process each result ASAP as soon as it becomes available, so you don't have to wait for the very last promise to finish before you start iterating over them.
So, here's a code sample that does just that, based partly on the answer by Endless and also on this answer by T.J. Crowder.
// example tasks that sleep and return a number
// in real life, you'd probably fetch URLs or something
const tasks = [];
for (let i = 0; i < 20; i++) {
tasks.push(async () => {
console.log(`start ${i}`);
await sleep(Math.random() * 1000);
console.log(`end ${i}`);
return i;
});
}
function sleep(ms) { return new Promise(r => setTimeout(r, ms)); }
(async () => {
for await (let value of runTasks(3, tasks.values())) {
console.log(`output ${value}`);
}
})();
async function* runTasks(maxConcurrency, taskIterator) {
// Each async iterator is a worker, polling for tasks from the shared taskIterator
// Sharing the iterator ensures that each worker gets unique tasks.
const asyncIterators = new Array(maxConcurrency);
for (let i = 0; i < maxConcurrency; i++) {
asyncIterators[i] = (async function* () {
for (const task of taskIterator) yield await task();
})();
}
yield* raceAsyncIterators(asyncIterators);
}
async function* raceAsyncIterators(asyncIterators) {
async function nextResultWithItsIterator(iterator) {
return { result: await iterator.next(), iterator: iterator };
}
/** #type Map<AsyncIterator<T>,
Promise<{result: IteratorResult<T>, iterator: AsyncIterator<T>}>> */
const promises = new Map(asyncIterators.map(iterator =>
[iterator, nextResultWithItsIterator(iterator)]));
while (promises.size) {
const { result, iterator } = await Promise.race(promises.values());
if (result.done) {
promises.delete(iterator);
} else {
promises.set(iterator, nextResultWithItsIterator(iterator));
yield result.value;
}
}
}
There's a lot of magic in here; let me explain.
This solution is built around async generator functions, which many JS developers may not be familiar with.
A generator function (aka function* function) returns a "generator," an iterator of results. Generator functions are allowed to use the yield keyword where you might have normally used a return keyword. The first time a caller calls next() on the generator (or uses a for...of loop), the function* function runs until it yields a value; that becomes the next() value of the iterator. But the subsequent time next() is called, the generator function resumes from the yield statement, right where it left off, even if it's in the middle of a loop. (You can also yield*, to yield all of the results of another generator function.)
An "async generator function" (async function*) is a generator function that returns an "async iterator," which is an iterator of promises. You can call for await...of on an async iterator. Async generator functions can use the await keyword, as you might do in any async function.
In the example, we call runTasks() with an array of task functions. runTasks() is an async generator function, so we can call it with a for await...of loop. Each time the loop runs, we'll process the result of the latest completed task.
runTasks() creates N async iterators, the workers. (Note that the workers are initially defined as async generator functions, but we immediately invoke each function, and store each resulting async iterator in the asyncIterators array.) The example calls runTasks with 3 concurrent workers, so no more than 3 tasks are launched at the same time. When any task completes, we immediately queue up the next task. (This is superior to "batching", where you do 3 tasks at once, await all three of them, and don't start the next batch of three until the entire previous batch has finished.)
runTasks() concludes by "racing" its async iterators with yield* raceAsyncIterators(). raceAsyncIterators() is like Promise.race() but it races N iterators of Promises instead of just N Promises; it returns an async iterator that yields the results of resolved Promises.
raceAsyncIterators() starts by defining a promises Map from each of the iterators to promises. Each promise is a promise for an iteration result along with the iterator that generated it.
With the promises map, we can Promise.race() the values of the map, giving us the winning iteration result and its iterator. If the iterator is completely done, we remove it from the map; otherwise we replace its Promise in the promises map with the iterator's next() Promise and yield result.value.
In conclusion, runTasks() is an async generator function that yields the results of racing N concurrent async iterators of tasks, so the end user can just for await (let value of runTasks(3, tasks.values())) to process each result as soon as it becomes available.

I suggest the library async-pool: https://github.com/rxaviers/async-pool
npm install tiny-async-pool
Description:
Run multiple promise-returning & async functions with limited concurrency using native ES6/ES7
asyncPool runs multiple promise-returning & async functions in a limited concurrency pool. It rejects immediately as soon as one of the promises rejects. It resolves when all the promises completes. It calls the iterator function as soon as possible (under concurrency limit).
Usage:
const timeout = i => new Promise(resolve => setTimeout(() => resolve(i), i));
await asyncPool(2, [1000, 5000, 3000, 2000], timeout);
// Call iterator (i = 1000)
// Call iterator (i = 5000)
// Pool limit of 2 reached, wait for the quicker one to complete...
// 1000 finishes
// Call iterator (i = 3000)
// Pool limit of 2 reached, wait for the quicker one to complete...
// 3000 finishes
// Call iterator (i = 2000)
// Itaration is complete, wait until running ones complete...
// 5000 finishes
// 2000 finishes
// Resolves, results are passed in given array order `[1000, 5000, 3000, 2000]`.

Here is my ES7 solution to a copy-paste friendly and feature complete Promise.all()/map() alternative, with a concurrency limit.
Similar to Promise.all() it maintains return order as well as a fallback for non promise return values.
I also included a comparison of the different implementation as it illustrates some aspects a few of the other solutions have missed.
Usage
const asyncFn = delay => new Promise(resolve => setTimeout(() => resolve(), delay));
const args = [30, 20, 15, 10];
await asyncPool(args, arg => asyncFn(arg), 4); // concurrency limit of 4
Implementation
async function asyncBatch(args, fn, limit = 8) {
// Copy arguments to avoid side effects
args = [...args];
const outs = [];
while (args.length) {
const batch = args.splice(0, limit);
const out = await Promise.all(batch.map(fn));
outs.push(...out);
}
return outs;
}
async function asyncPool(args, fn, limit = 8) {
return new Promise((resolve) => {
// Copy arguments to avoid side effect, reverse queue as
// pop is faster than shift
const argQueue = [...args].reverse();
let count = 0;
const outs = [];
const pollNext = () => {
if (argQueue.length === 0 && count === 0) {
resolve(outs);
} else {
while (count < limit && argQueue.length) {
const index = args.length - argQueue.length;
const arg = argQueue.pop();
count += 1;
const out = fn(arg);
const processOut = (out, index) => {
outs[index] = out;
count -= 1;
pollNext();
};
if (typeof out === 'object' && out.then) {
out.then(out => processOut(out, index));
} else {
processOut(out, index);
}
}
}
};
pollNext();
});
}
Comparison
// A simple async function that returns after the given delay
// and prints its value to allow us to determine the response order
const asyncFn = delay => new Promise(resolve => setTimeout(() => {
console.log(delay);
resolve(delay);
}, delay));
// List of arguments to the asyncFn function
const args = [30, 20, 15, 10];
// As a comparison of the different implementations, a low concurrency
// limit of 2 is used in order to highlight the performance differences.
// If a limit greater than or equal to args.length is used the results
// would be identical.
// Vanilla Promise.all/map combo
const out1 = await Promise.all(args.map(arg => asyncFn(arg)));
// prints: 10, 15, 20, 30
// total time: 30ms
// Pooled implementation
const out2 = await asyncPool(args, arg => asyncFn(arg), 2);
// prints: 20, 30, 15, 10
// total time: 40ms
// Batched implementation
const out3 = await asyncBatch(args, arg => asyncFn(arg), 2);
// prints: 20, 30, 20, 30
// total time: 45ms
console.log(out1, out2, out3); // prints: [30, 20, 15, 10] x 3
// Conclusion: Execution order and performance is different,
// but return order is still identical
Conclusion
asyncPool() should be the best solution as it allows new requests to start as soon as any previous one finishes.
asyncBatch() is included as a comparison as its implementation is simpler to understand, but it should be slower in performance as all requests in the same batch is required to finish in order to start the next batch.
In this contrived example, the non-limited vanilla Promise.all() is of course the fastest, while the others could perform more desirable in a real world congestion scenario.
Update
The async-pool library that others have already suggested is probably a better alternative to my implementation as it works almost identically and has a more concise implementation with a clever usage of Promise.race(): https://github.com/rxaviers/async-pool/blob/master/lib/es7.js
Hopefully my answer can still serve an educational value.

Semaphore is well known concurrency primitive that was designed to solve similar problems. It's very universal construct, implementations of Semaphore exist in many languages. This is how one would use Semaphore to solve this issue:
async function main() {
const s = new Semaphore(100);
const res = await Promise.all(
entities.map((users) =>
s.runExclusive(() => remoteServer.getCount(user))
)
);
return res;
}
I'm using implementation of Semaphore from async-mutex, it has decent documentation and TypeScript support.
If you want to dig deep into topics like this you can take a look at the book "The Little Book of Semaphores" which is freely available as PDF here

Unfortunately there is no way to do it with native Promise.all, so you have to be creative.
This is the quickest most concise way I could find without using any outside libraries.
It makes use of a newer javascript feature called an iterator. The iterator basically keeps track of what items have been processed and what haven't.
In order to use it in code, you create an array of async functions. Each async function asks the same iterator for the next item that needs to be processed. Each function processes its own item asynchronously, and when done asks the iterator for a new one. Once the iterator runs out of items, all the functions complete.
Thanks to #Endless for inspiration.
const items = [
'https://httpbin.org/bytes/2',
'https://httpbin.org/bytes/2',
'https://httpbin.org/bytes/2',
'https://httpbin.org/bytes/2',
'https://httpbin.org/bytes/2',
'https://httpbin.org/bytes/2',
'https://httpbin.org/bytes/2',
'https://httpbin.org/bytes/2'
]
// get a cursor that keeps track of what items have already been processed.
let cursor = items.entries();
// create 5 for loops that each run off the same cursor which keeps track of location
Array(5).fill().forEach(async () => {
for (let [index, url] of cursor){
console.log('getting url is ', index, url)
// run your async task instead of this next line
var text = await fetch(url).then(res => res.text())
console.log('text is', text.slice(0, 20))
}
})

Here goes basic example for streaming and 'p-limit'. It streams http read stream to mongo db.
const stream = require('stream');
const util = require('util');
const pLimit = require('p-limit');
const es = require('event-stream');
const streamToMongoDB = require('stream-to-mongo-db').streamToMongoDB;
const pipeline = util.promisify(stream.pipeline)
const outputDBConfig = {
dbURL: 'yr-db-url',
collection: 'some-collection'
};
const limit = pLimit(3);
async yrAsyncStreamingFunction(readStream) => {
const mongoWriteStream = streamToMongoDB(outputDBConfig);
const mapperStream = es.map((data, done) => {
let someDataPromise = limit(() => yr_async_call_to_somewhere())
someDataPromise.then(
function handleResolve(someData) {
data.someData = someData;
done(null, data);
},
function handleError(error) {
done(error)
}
);
})
await pipeline(
readStream,
JSONStream.parse('*'),
mapperStream,
mongoWriteStream
);
}

So many good solutions. I started out with the elegant solution posted by #Endless and ended up with this little extension method that does not use any external libraries nor does it run in batches (although assumes you have features like async, etc):
Promise.allWithLimit = async (taskList, limit = 5) => {
const iterator = taskList.entries();
let results = new Array(taskList.length);
let workerThreads = new Array(limit).fill(0).map(() =>
new Promise(async (resolve, reject) => {
try {
let entry = iterator.next();
while (!entry.done) {
let [index, promise] = entry.value;
try {
results[index] = await promise;
entry = iterator.next();
}
catch (err) {
results[index] = err;
}
}
// No more work to do
resolve(true);
}
catch (err) {
// This worker is dead
reject(err);
}
}));
await Promise.all(workerThreads);
return results;
};
Promise.allWithLimit = async (taskList, limit = 5) => {
const iterator = taskList.entries();
let results = new Array(taskList.length);
let workerThreads = new Array(limit).fill(0).map(() =>
new Promise(async (resolve, reject) => {
try {
let entry = iterator.next();
while (!entry.done) {
let [index, promise] = entry.value;
try {
results[index] = await promise;
entry = iterator.next();
}
catch (err) {
results[index] = err;
}
}
// No more work to do
resolve(true);
}
catch (err) {
// This worker is dead
reject(err);
}
}));
await Promise.all(workerThreads);
return results;
};
const demoTasks = new Array(10).fill(0).map((v,i) => new Promise(resolve => {
let n = (i + 1) * 5;
setTimeout(() => {
console.log(`Did nothing for ${n} seconds`);
resolve(n);
}, n * 1000);
}));
var results = Promise.allWithLimit(demoTasks);

#tcooc's answer was quite cool. Didn't know about it and will leverage it in the future.
I also enjoyed #MatthewRideout's answer, but it uses an external library!!
Whenever possible, I give a shot at developing this kind of things on my own, rather than going for a library. You end up learning a lot of concepts which seemed daunting before.
class Pool{
constructor(maxAsync) {
this.maxAsync = maxAsync;
this.asyncOperationsQueue = [];
this.currentAsyncOperations = 0
}
runAnother() {
if (this.asyncOperationsQueue.length > 0 && this.currentAsyncOperations < this.maxAsync) {
this.currentAsyncOperations += 1;
this.asyncOperationsQueue.pop()()
.then(() => { this.currentAsyncOperations -= 1; this.runAnother() }, () => { this.currentAsyncOperations -= 1; this.runAnother() })
}
}
add(f){ // the argument f is a function of signature () => Promise
this.runAnother();
return new Promise((resolve, reject) => {
this.asyncOperationsQueue.push(
() => f().then(resolve).catch(reject)
)
})
}
}
//#######################################################
// TESTS
//#######################################################
function dbCall(id, timeout, fail) {
return new Promise((resolve, reject) => {
setTimeout(() => {
if (fail) {
reject(`Error for id ${id}`);
} else {
resolve(id);
}
}, timeout)
}
)
}
const dbQuery1 = () => dbCall(1, 5000, false);
const dbQuery2 = () => dbCall(2, 5000, false);
const dbQuery3 = () => dbCall(3, 5000, false);
const dbQuery4 = () => dbCall(4, 5000, true);
const dbQuery5 = () => dbCall(5, 5000, false);
const cappedPool = new Pool(2);
const dbQuery1Res = cappedPool.add(dbQuery1).catch(i => i).then(i => console.log(`Resolved: ${i}`))
const dbQuery2Res = cappedPool.add(dbQuery2).catch(i => i).then(i => console.log(`Resolved: ${i}`))
const dbQuery3Res = cappedPool.add(dbQuery3).catch(i => i).then(i => console.log(`Resolved: ${i}`))
const dbQuery4Res = cappedPool.add(dbQuery4).catch(i => i).then(i => console.log(`Resolved: ${i}`))
const dbQuery5Res = cappedPool.add(dbQuery5).catch(i => i).then(i => console.log(`Resolved: ${i}`))
This approach provides a nice API, similar to thread pools in scala/java.
After creating one instance of the pool with const cappedPool = new Pool(2), you provide promises to it with simply cappedPool.add(() => myPromise).
Obliviously we must ensure that the promise does not start immediately and that is why we must "provide it lazily" with the help of the function.
Most importantly, notice that the result of the method add is a Promise which will be completed/resolved with the value of your original promise! This makes for a very intuitive use.
const resultPromise = cappedPool.add( () => dbCall(...))
resultPromise
.then( actualResult => {
// Do something with the result form the DB
}
)

This solution uses an async generator to manage concurrent promises with vanilla javascript. The throttle generator takes 3 arguments:
An array of values to be be supplied as arguments to a promise genrating function. (e.g. An array of URLs.)
A function that return a promise. (e.g. Returns a promise for an HTTP request.)
An integer that represents the maximum concurrent promises allowed.
Promises are only instantiated as required in order to reduce memory consumption. Results can be iterated over using a for await...of statement.
The example below provides a function to check promise state, the throttle async generator, and a simple function that return a promise based on setTimeout. The async IIFE at the end defines the reservoir of timeout values, sets the async iterable returned by throttle, then iterates over the results as they resolve.
If you would like a more complete example for HTTP requests, let me know in the comments.
Please note that Node.js 16+ is required in order async generators.
const promiseState = function( promise ) {
const control = Symbol();
return Promise
.race([ promise, control ])
.then( value => ( value === control ) ? 'pending' : 'fulfilled' )
.catch( () => 'rejected' );
}
const throttle = async function* ( reservoir, promiseClass, highWaterMark ) {
let iterable = reservoir.splice( 0, highWaterMark ).map( item => promiseClass( item ) );
while ( iterable.length > 0 ) {
await Promise.any( iterable );
const pending = [];
const resolved = [];
for ( const currentValue of iterable ) {
if ( await promiseState( currentValue ) === 'pending' ) {
pending.push( currentValue );
} else {
resolved.push( currentValue );
}
}
console.log({ pending, resolved, reservoir });
iterable = [
...pending,
...reservoir.splice( 0, highWaterMark - pending.length ).map( value => promiseClass( value ) )
];
yield Promise.allSettled( resolved );
}
}
const getTimeout = delay => new Promise( ( resolve, reject ) => {
setTimeout(resolve, delay, delay);
} );
( async () => {
const test = [ 1100, 1200, 1300, 10000, 11000, 9000, 5000, 6000, 3000, 4000, 1000, 2000, 3500 ];
const throttledRequests = throttle( test, getTimeout, 4 );
for await ( const timeout of throttledRequests ) {
console.log( timeout );
}
} )();

The concurrent function below will return a Promise which resolves to an array of resolved promise values, while implementing a concurrency limit. No 3rd party library.
// waits 50 ms then resolves to the passed-in arg
const sleepAndResolve = s => new Promise(rs => setTimeout(()=>rs(s), 50))
// queue 100 promises
const funcs = []
for(let i=0; i<100; i++) funcs.push(()=>sleepAndResolve(i))
//run the promises with a max concurrency of 10
concurrent(10,funcs)
.then(console.log) // prints [0,1,2...,99]
.catch(()=>console.log("there was an error"))
/**
* Run concurrent promises with a maximum concurrency level
* #param concurrency The number of concurrently running promises
* #param funcs An array of functions that return promises
* #returns a promise that resolves to an array of the resolved values from the promises returned by funcs
*/
function concurrent(concurrency, funcs) {
return new Promise((resolve, reject) => {
let index = -1;
const p = [];
for (let i = 0; i < Math.max(1, Math.min(concurrency, funcs.length)); i++)
runPromise();
function runPromise() {
if (++index < funcs.length)
(p[p.length] = funcs[index]()).then(runPromise).catch(reject);
else if (index === funcs.length)
Promise.all(p).then(resolve).catch(reject);
}
});
}
Here's the Typescript version if you are interested
/**
* Run concurrent promises with a maximum concurrency level
* #param concurrency The number of concurrently running promises
* #param funcs An array of functions that return promises
* #returns a promise that resolves to an array of the resolved values from the promises returned by funcs
*/
function concurrent<V>(concurrency:number, funcs:(()=>Promise<V>)[]):Promise<V[]> {
return new Promise((resolve,reject)=>{
let index = -1;
const p:Promise<V>[] = []
for(let i=0; i<Math.max(1,Math.min(concurrency, funcs.length)); i++) runPromise()
function runPromise() {
if (++index < funcs.length) (p[p.length] = funcs[index]()).then(runPromise).catch(reject)
else if (index === funcs.length) Promise.all(p).then(resolve).catch(reject)
}
})
}

No external libraries. Just plain JS.
It can be resolved using recursion.
The idea is that initially we immediately execute the maximum allowed number of queries and each of these queries should recursively initiate a new query on its completion.
In this example I populate successful responses together with errors and I execute all queries but it's possible to slightly modify algorithm if you want to terminate batch execution on the first failure.
async function batchQuery(queries, limit) {
limit = Math.min(queries.length, limit);
return new Promise((resolve, reject) => {
const responsesOrErrors = new Array(queries.length);
let startedCount = 0;
let finishedCount = 0;
let hasErrors = false;
function recursiveQuery() {
let index = startedCount++;
doQuery(queries[index])
.then(res => {
responsesOrErrors[index] = res;
})
.catch(error => {
responsesOrErrors[index] = error;
hasErrors = true;
})
.finally(() => {
finishedCount++;
if (finishedCount === queries.length) {
hasErrors ? reject(responsesOrErrors) : resolve(responsesOrErrors);
} else if (startedCount < queries.length) {
recursiveQuery();
}
});
}
for (let i = 0; i < limit; i++) {
recursiveQuery();
}
});
}
async function doQuery(query) {
console.log(`${query} started`);
const delay = Math.floor(Math.random() * 1500);
return new Promise((resolve, reject) => {
setTimeout(() => {
if (delay <= 1000) {
console.log(`${query} finished successfully`);
resolve(`${query} success`);
} else {
console.log(`${query} finished with error`);
reject(`${query} error`);
}
}, delay);
});
}
const queries = new Array(10).fill('query').map((query, index) => `${query}_${index + 1}`);
batchQuery(queries, 3)
.then(responses => console.log('All successfull', responses))
.catch(responsesWithErrors => console.log('All with several failed', responsesWithErrors));

So I tried to make some examples shown work for my code, but since this was only for an import script and not production code, using the npm package batch-promises was surely the easiest path for me
NOTE: Requires runtime to support Promise or to be polyfilled.
Api
batchPromises(int: batchSize, array: Collection, i => Promise: Iteratee)
The Promise: Iteratee will be called after each batch.
Use:
batch-promises
Easily batch promises
NOTE: Requires runtime to support Promise or to be polyfilled.
Api
batchPromises(int: batchSize, array: Collection, i => Promise: Iteratee)
The Promise: Iteratee will be called after each batch.
Use:
import batchPromises from 'batch-promises';
batchPromises(2, [1,2,3,4,5], i => new Promise((resolve, reject) => {
// The iteratee will fire after each batch resulting in the following behaviour:
// # 100ms resolve items 1 and 2 (first batch of 2)
// # 200ms resolve items 3 and 4 (second batch of 2)
// # 300ms resolve remaining item 5 (last remaining batch)
setTimeout(() => {
resolve(i);
}, 100);
}))
.then(results => {
console.log(results); // [1,2,3,4,5]
});

Recursion is the answer if you don't want to use external libraries
downloadAll(someArrayWithData){
var self = this;
var tracker = function(next){
return self.someExpensiveRequest(someArrayWithData[next])
.then(function(){
next++;//This updates the next in the tracker function parameter
if(next < someArrayWithData.length){//Did I finish processing all my data?
return tracker(next);//Go to the next promise
}
});
}
return tracker(0);
}

expanding on the answer posted by #deceleratedcaviar, I created a 'batch' utility function that takes as argument: array of values, concurrency limit and processing function. Yes I realize that using Promise.all this way is more akin to batch processing vs true concurrency, but if the goal is to limit excessive number of HTTP calls at one time I go with this approach due to its simplicity and no need for external library.
async function batch(o) {
let arr = o.arr
let resp = []
while (arr.length) {
let subset = arr.splice(0, o.limit)
let results = await Promise.all(subset.map(o.process))
resp.push(results)
}
return [].concat.apply([], resp)
}
let arr = []
for (let i = 0; i < 250; i++) { arr.push(i) }
async function calc(val) { return val * 100 }
(async () => {
let resp = await batch({
arr: arr,
limit: 100,
process: calc
})
console.log(resp)
})();

One more solution with a custom promise library (CPromise):
using generators Live codesandbox demo
import { CPromise } from "c-promise2";
import cpFetch from "cp-fetch";
const promise = CPromise.all(
function* () {
const urls = [
"https://run.mocky.io/v3/7b038025-fc5f-4564-90eb-4373f0721822?mocky-delay=2s&x=1",
"https://run.mocky.io/v3/7b038025-fc5f-4564-90eb-4373f0721822?mocky-delay=2s&x=2",
"https://run.mocky.io/v3/7b038025-fc5f-4564-90eb-4373f0721822?mocky-delay=2s&x=3",
"https://run.mocky.io/v3/7b038025-fc5f-4564-90eb-4373f0721822?mocky-delay=2s&x=4",
"https://run.mocky.io/v3/7b038025-fc5f-4564-90eb-4373f0721822?mocky-delay=2s&x=5",
"https://run.mocky.io/v3/7b038025-fc5f-4564-90eb-4373f0721822?mocky-delay=2s&x=6",
"https://run.mocky.io/v3/7b038025-fc5f-4564-90eb-4373f0721822?mocky-delay=2s&x=7"
];
for (const url of urls) {
yield cpFetch(url); // add a promise to the pool
console.log(`Request [${url}] completed`);
}
},
{ concurrency: 2 }
).then(
(v) => console.log(`Done: `, v),
(e) => console.warn(`Failed: ${e}`)
);
// yeah, we able to cancel the task and abort pending network requests
// setTimeout(() => promise.cancel(), 4500);
using mapper Live codesandbox demo
import { CPromise } from "c-promise2";
import cpFetch from "cp-fetch";
const promise = CPromise.all(
[
"https://run.mocky.io/v3/7b038025-fc5f-4564-90eb-4373f0721822?mocky-delay=2s&x=1",
"https://run.mocky.io/v3/7b038025-fc5f-4564-90eb-4373f0721822?mocky-delay=2s&x=2",
"https://run.mocky.io/v3/7b038025-fc5f-4564-90eb-4373f0721822?mocky-delay=2s&x=3",
"https://run.mocky.io/v3/7b038025-fc5f-4564-90eb-4373f0721822?mocky-delay=2s&x=4",
"https://run.mocky.io/v3/7b038025-fc5f-4564-90eb-4373f0721822?mocky-delay=2s&x=5",
"https://run.mocky.io/v3/7b038025-fc5f-4564-90eb-4373f0721822?mocky-delay=2s&x=6",
"https://run.mocky.io/v3/7b038025-fc5f-4564-90eb-4373f0721822?mocky-delay=2s&x=7"
],
{
mapper: (url) => {
console.log(`Request [${url}]`);
return cpFetch(url);
},
concurrency: 2
}
).then(
(v) => console.log(`Done: `, v),
(e) => console.warn(`Failed: ${e}`)
);
// yeah, we able to cancel the task and abort pending network requests
//setTimeout(() => promise.cancel(), 4500);

Warning this has not been benchmarked for efficiency and does a lot of array copying/creation
If you want a more functional approach you could do something like:
import chunk from 'lodash.chunk';
const maxConcurrency = (max) => (dataArr, promiseFn) =>
chunk(dataArr, max).reduce(
async (agg, batch) => [
...(await agg),
...(await Promise.all(batch.map(promiseFn)))
],
[]
);
and then to you could use it like:
const randomFn = (data) =>
new Promise((res) => setTimeout(
() => res(data + 1),
Math.random() * 1000
));
const result = await maxConcurrency(5)(
[1, 2, 3, 4, 5, 6, 7, 8, 9, 10],
randomFn
);
console.log('result+++', result);

I had been using the bottleneck library, which I actually really liked, but in my case wasn't releasing memory and kept tanking long running jobs... Which isn't great for running the massive jobs that you likely want a throttling/concurrency library for in the first place.
I needed a simple, low-overhead, easy to maintain solution. I also wanted something that kept the pool topped up, rather than simply batching predefined chunks... In the case of a downloader, this will stop that nGB file from holding up your queue for minutes/hours at a time, even though the rest of the batch finished ages ago.
This is the Node.js v16+, no-dependency, async generator solution I've been using instead:
const promiseState = function( promise ) {
// A promise could never resolve to a unique symbol unless it was in this scope
const control = Symbol();
// This helps us determine the state of the promise... A little heavy, but it beats a third-party promise library. The control is the second element passed to Promise.race() since it will only resolve first if the promise being tested is pending.
return Promise
.race([ promise, control ])
.then( value => ( value === control ) ? 'pending' : 'fulfilled' )
.catch( () => 'rejected' );
}
const throttle = async function* ( reservoir, promiseFunction, highWaterMark ) {
let iterable = reservoir.splice( 0, highWaterMark ).map( item => promiseFunction( item ) );
while ( iterable.length > 0 ) {
// When a promise has resolved we have space to top it up to the high water mark...
await Promise.any( iterable );
const pending = [];
const resolved = [];
// This identifies the promise(s) that have resolved so that we can yield them
for ( const currentValue of iterable ) {
if ( await promiseState( currentValue ) === 'pending' ) {
pending.push( currentValue );
} else {
resolved.push( currentValue );
}
}
// Put the remaining promises back into iterable, and top it to the high water mark
iterable = [
...pending,
...reservoir.splice( 0, highWaterMark - pending.length ).map( value => promiseFunction( value ) )
];
yield Promise.allSettled( resolved );
}
}
// This is just an example of what would get passed as "promiseFunction"... This can be the function that returns your HTTP request promises
const getTimeout = delay => new Promise( (resolve, reject) => setTimeout(resolve, delay, delay) );
// This is just the async IIFE that bootstraps this example
( async () => {
const test = [ 1000, 2000, 3000, 4000, 5000, 6000, 1500, 2500, 3500, 4500, 5500, 6500 ];
for await ( const timeout of throttle( test, getTimeout, 4 ) ) {
console.log( timeout );
}
} )();

I have solution with creating chunks and using .reduce function to wait each chunks promise.alls to be finished. And also I add some delay if the promises have some call limits.
export function delay(ms: number) {
return new Promise<void>((resolve) => setTimeout(resolve, ms));
}
export const chunk = <T>(arr: T[], size: number): T[][] => [
...Array(Math.ceil(arr.length / size)),
].map((_, i) => arr.slice(size * i, size + size * i));
const myIdlist = []; // all items
const groupedIdList = chunk(myIdList, 20); // grouped by 20 items
await groupedIdList.reduce(async (prev, subIdList) => {
await prev;
// Make sure we wait for 500 ms after processing every page to prevent overloading the calls.
const data = await Promise.all(subIdList.map(myPromise));
await delay(500);
}, Promise.resolve());

Using tiny-async-pool ES9 for await...of API, you can do the following:
const asyncPool = require("tiny-async-pool");
const getCount = async (user) => ([user, remoteServer.getCount(user)]);
const concurrency = 2;
for await (const [user, count] of asyncPool(concurrency, users, getCount)) {
console.log(user, count);
}
The above asyncPool function returns an async iterator that yields as soon as a promise completes (under concurrency limit) and it rejects immediately as soon as one of the promises rejects.

It is possible to limit requests to server by using https://www.npmjs.com/package/job-pipe
Basically you create a pipe and tell it how many concurrent requests you want:
const pipe = createPipe({ throughput: 6, maxQueueSize: Infinity })
Then you take your function which performs call and force it through the pipe to create a limited amount of calls at the same time:
const makeCall = async () => {...}
const limitedMakeCall = pipe(makeCall)
Finally, you call this method as many times as you need as if it was unchanged and it will limit itself on how many parallel executions it can handle:
await limitedMakeCall()
await limitedMakeCall()
await limitedMakeCall()
await limitedMakeCall()
await limitedMakeCall()
....
await limitedMakeCall()
Profit.

I suggest not downloading packages and not writing hundreds of lines of code:
async function async_arr<T1, T2>(
arr: T1[],
func: (x: T1) => Promise<T2> | T2, //can be sync or async
limit = 5
) {
let results: T2[] = [];
let workers = [];
let current = Math.min(arr.length, limit);
async function process(i) {
if (i < arr.length) {
results[i] = await Promise.resolve(func(arr[i]));
await process(current++);
}
}
for (let i = 0; i < current; i++) {
workers.push(process(i));
}
await Promise.all(workers);
return results;
}

Here's my recipe, based on killdash9's answer.
It allows to choose the behaviour on exceptions (Promise.all vs Promise.allSettled).
// Given an array of async functions, runs them in parallel,
// with at most maxConcurrency simultaneous executions
// Except for that, behaves the same as Promise.all,
// unless allSettled is true, where it behaves as Promise.allSettled
function concurrentRun(maxConcurrency = 10, funcs = [], allSettled = false) {
if (funcs.length <= maxConcurrency) {
const ps = funcs.map(f => f());
return allSettled ? Promise.allSettled(ps) : Promise.all(ps);
}
return new Promise((resolve, reject) => {
let idx = -1;
const ps = new Array(funcs.length);
function nextPromise() {
idx += 1;
if (idx < funcs.length) {
(ps[idx] = funcs[idx]()).then(nextPromise).catch(allSettled ? nextPromise : reject);
} else if (idx === funcs.length) {
(allSettled ? Promise.allSettled(ps) : Promise.all(ps)).then(resolve).catch(reject);
}
}
for (let i = 0; i < maxConcurrency; i += 1) nextPromise();
});
}

I know there are a lot of answers already, but I ended up using a very simple, no library or sleep required, solution that uses only a few commands. Promise.all() simply lets you know when all the promises passed to it are finalized. So, you can check on the queue intermittently to see if it is ready for more work, if so, add more processes.
For example:
// init vars
const batchSize = 5
const calls = []
// loop through data and run processes
for (let [index, data] of [1,2,3].entries()) {
// pile on async processes
calls.push(doSomethingAsyncWithData(data))
// every 5th concurrent call, wait for them to finish before adding more
if (index % batchSize === 0) await Promise.all(calls)
}
// clean up for any data to process left over if smaller than batch size
const allFinishedProcs = await Promise.all(calls)

A good solution for controlling the maximum number of promises/requests is to split your list of requests into pages, and produce only requests for one page at a time.
The example below makes use of iter-ops library:
import {pipeAsync, map, page} from 'iter-ops';
const i = pipeAsync(
users, // make it asynchronous
page(10), // split into pages of 10 items in each
map(p => Promise.all(p.map(u => u.remoteServer.getCount(u)))), // map into requests
wait() // resolve each page in the pipeline
);
// below triggers processing page-by-page:
for await(const p of i) {
//=> p = resolved page of data
}
This way it won't try to create more requests/promises than the size of one page.

Develop Reference

JavaScript is the programming language of the Web.

Promise not returning expected value - javascript

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