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This piece of code will leak memory and eventually crash your Node.js process or browser:

// Tested on Node.js 7.10, Firefox 57 and Chrome 61
// Usage of `setImmediate` is to prove that we have
// async boundaries, can be removed for browsers
// not supporting it.

function signal(i) {
  return new Promise(cb => setImmediate(() => cb(i)))

function loop(n) {
  return signal(n).then(i => {
    if (i % 1000 == 0) console.log(i)
    return loop(n + 1)


→ Load Sample for Browser

It takes a while to fill GBs of heap, plus Node is less conservative, the GC eventually freezing the process trying to recover memory, so give it a few seconds.

This is equivalent with this async function:

async function loop(n) {
  const i = await signal(n)
  if (i % 1000 == 0) console.log(i)

  // Recursive call
  return loop(n + 1)

Of course, if this loop would be synchronous, not using Promise or async / await, then the process would blow up with a stack overflow error because at the moment of writing JavaScript does not do tail calls optimizations (until everybody implements ECMAScript 6 fully at least).

But before you jump to conclusions, this has nothing to do with JavaScript’s lack of TCO support. This is because in our recursive function it’s not JavaScript’s call stack that’s managing that loop, but rather the Promise implementation. That recursive call is asynchronous and so it does not abuse the call stack by definition.

Unfortunately, just like a regular function using the call stack for those recursive calls, the Promise implementation is abusing the heap memory, not chaining then calls correctly. And that sample should not leak, the Promise implementation should be able to do the equivalent of TCO and in such a case eliminate frames in the then chain being created.

The Spec is The Problem #

We’re talking of the Promise/A+ specification. Relevant links to known issues on GitHub, explaining why:

  1. Node.js issue, now closed: node/#6673
  2. Promise/A+ spec issue, open since 2014: promises-spec/#179

As you’ll see, there are some reasonable arguments for why the Promise implementation is allowed to leak memory. But I can’t agree.

The Non-leaky Solution #

The solution, if you insist on using JavaScript’s Promise, is to work with non-recursive functions:

async function loop(n) {
  let i = 0

  while (true) {
    i = await signal(i + 1)
    if (i % 1000 == 0) console.log(i)

But at this point any semblance of functional programming, if you ever had any, goes out the window, see below.

Common Objections #

Gathering feedback from people, here are the common objections:

1. This is Normal #

No, if you judge this implementation, relative to other Promise / Future implementations in the industry, which are setting expectations.

Here are the implementations that I know about that DO NOT leak memory:

  1. Bluebird, probably the most popular non-standard Promise implementation for JavaScript
  2. Scala’s standard Future, in the wild since 2013; the fix for the leaky flatMap chains was added by Rich Dougherty in this PR, inspired by Twitter’s Future implementation
  3. Twitter’s Future, which is used in all of Twitter’s backend infrastructure, being integrated in Finagle
  4., a Java Future implementation providing a TailRec builder meant precissely for this use-case
  5. My very own Funfix Future and Monix CancelableFuture

Interestingly, complaints for Scala’s Future happened due to usage of Play’s Iteratees, with which people have been modeling stream processing.

2. But It Does Unlimited Chaining of Promises #

Yes, that’s why it’s leaking memory.

No, the implementation should not chain promises like that and an alternative implementation is possible and well known, as evidenced by the implementations mentioned that don’t leak.

The fault lies with the standard Promise implementation, not with the shown sample, being a legitimate use-case.

3. That Sample Does Not Use the Return Value #

The sample is kept simple for didactic purposes, however:

  1. you can easily imagine a loop that processes a very long stream of data, aggregating information along the way, returning a result later
  2. the script does do error handling and without that inner return, the .catch(console.error) would have no effect

4. That’s the Equivalent of a Stack Overflow #

Yes, I’ve mentioned this above, but just to set your mind at rest on this point, proper Tail-Calls Optimizations are coming for normal call sites, being part of ECMAScript, see:

You can’t rely on it yet, but you can rest assured that in the future if that sample would be synchronous, it would not trigger a stack overflow.

Therefore, given that asynchronous calls are by definition processes / events happening independently of the current call stack / run loop, this behavior is actually surprising, since one of the reasons to go async is to escape the limitations of the call stack.

5. You Don’t Understand How Promises Work #

I’ve been told that I don’t understand promises. So I apologize for the appeal to authority that I’m about to make.

Data types for dealing with asynchrony have been a hobby of mine since 2012 and I’ve been authoring several projects in which I implemented Promise-like data types:

  • Monix, which implements Task, one of the best ports of Haskell’s IO, along with a complementary CancelableFuture and what I think is the best back-pressured Rx Observable implementations in existence
  • Funfix, a JavaScript library for FP, delivering a Future and an IO implementation, see below
  • have contributed to cats-effect, a more conservative IO port

Bonus — see my presentation from Scala Days!

My work, good or bad, has followed a certain pattern, which is why I do understand promises, I do understand at least two solutions to this, hence this article.

6. No Use-cases, This is a Niche #

Functional programming might be a niche, however more and more projects, including at big companies such as Facebook, are now using an actual FP style.

You cannot describe any functional programming algorithm involving loops without tail recursions. If folds are used, then folds are described with tail recursions as well. That’s because:

  1. any loop can be described with a tail recursion
  2. you can’t have immutability of the state you’re evolving without it

An example of a use-case is the processing of really long / infinite streams of events, for which it’s really natural to describe algorithms using tail recursions and for which you can’t really work with imperative, mutation-based loops.

Imagine reading chunks of data from a file and describing them with a data structure like this:

interface List<A>

class Next<A> implements List<A> {
    public readonly head: A,
    public readonly next: () => Promise<List<A>>
  ) {}

class Halt implements List<A> {
  constructor(public readonly error?: any) {}

Sample is using TypeScript (could be Flow) for making it clear what the types are. You can work with plain JavaScript of course.

This structure is really cheap and effective, being a lazy, asynchronous, referentially transparent stream. And in fact it’s really similar to JavaScript implementations of async iterators, so yes, you are going to work with something like this in the future, even if you don’t like it ;-)

And describing transformation functions like this one is really fun too:

function map<A, B>(list: List<A>, f: (a: A) => B): List<B> {
  if (list instanceof Next) {
    try {
      const cons = list as Next<A>
      return new Next(f(cons.head), () => => map(xs, f)))
    } catch (e) {
      return new Halt(e)
  } else {
    return list

Alas, with the Promise implementation leaking, this doesn’t work ;-)

Alternatives #

Fluture #

Project Page:

This is the most popular Promise alternative that I know of.

It isn’t a direct replacement however because it has lazy behavior, being meant for suspending side effects. This is more like an IO data type. Which is cool, you should use something like it, but it’s also apples vs oranges.

I don’t have enough experience with it, making this recommendation solely based on its popularity and I double checked that it indeed preserves stack safety.

Funfix #

I’ve been building a new project, Funfix, a JavaScript library for functional programming (capital FP), supporting TypeScript and Flow types out of the box.

Funfix exposes Future<A>, an eager Promise alternative that’s safe, cancellable and filled with goodies, along with IO<A>, a lazy, lawful, cancellable data type for handling all kinds of side effects, inspired by Haskell, the two being complementary.

This piece of code powered by Future does not leak:

import { Future } from "funfix"

function loop(n) {
  return Future.of(() => n).flatMap(i => {
    if (i % 1000 == 0) console.log(i)
    return loop(n + 1)


And neither does this one, powered by IO:

import { IO } from "funfix"

function loop(n) {
  return IO.of(() => n).flatMap(i => {
    if (i % 1000 == 0) console.log(i)
    return loop(n + 1)


This IO is a port of Monix’s Task, being a better IO than Haskell’s IO due to its cancellable nature ;-)

In this PR I’ve also fixed the memory leak for Future, doing the same tricks that Scala’s Future is doing. Now released in v6.2.0.

And note that this is harder to do for Funfix’s Future due to also having to deal with chains of Cancelable references, which can also leak.

Author’s Rant — in response to this article I’ve been called a scumbag for “shameless self promotion”.

I’m building stuff that I share with the world and I like talking about it on my personal blog. I’m not going to apologize for it.

Final Words #

That the current JavaScript Promise implementation has this leak is a big problem, because tail-recursive calls are the cornerstone of functional programming.

Yes, it’s true that Promise is not a useful monadic type for doing FP, since it does not suspend side effects (which is why you should use IO), but that’s beside the point, plus for the FP purists out there, you can always suspend it in a thunk, assuming that it doesn’t leak in then chains.

This is also why I fear standardization by committee in general. Along with the totally awkward then signature that can’t be safely described with TypeScript’s or Flow’s types, this is another example of how standard solutions can be harmful, because by being pushed as a standard, it makes it hard for alternatives to exist, since most people are just going to use the standard implementation, especially in JavaScript’s ecosystem where people are afraid to take on dependencies.

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