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	Folding Promises in JavaScript (codementor.io)
	60 points by anon335dtzbvc 3199 days ago

10 comments

adamjc 3198 days ago

>How can we make it better ? Let's start by removing the requirement for identity value to always be the promise.

I challenge the view that making the identity value being able to be something other than a Promise is 'making it better'. Pointless abstraction is one of my pet peeves in this industry. This looks like it has gone from a fairly straightforward, if kludgy, piece of code to something far more complex. Why not just:

  const listOfPromises = [...]

  const result = Promise.all(listOfPromises).then(results => {
    return results.reduce((acc, next) => acc + next)
  })


?

megawatthours 3198 days ago

Same reason given in the bluebird library documentation:

> Promise.reduce will start calling the reducer as soon as possible, this is why you might want to use it over Promise.all (which awaits for the entire array before you can call Array#reduce on it).

Whether this is ever necessary is another matter :)

codefined 3198 days ago

    let accumulator = 0
    for (let item of array) {
      const value = await item
      // your code here
    }

Is identical, doesn't use 'cool' reduce features but is much easier to read in my opinion.

todd3834 3198 days ago

Wouldn’t this code only execute 1 promise at a time? I thought Promise.all allowed promises to be resolved in parallel

theprotocol 3198 days ago

Indeed. You most likely should do `await Promise.all` and then do the reduction.

dvlsg 3198 days ago

If item is already a promise, and not a function returning a promise, they would be "executing" in parallel.

codefined 3198 days ago

Sorry, in the sense of being identical to the original code in the linked post (reduce), not the comment.

YCode 3198 days ago

I suppose this might be useful in situations where you are querying an API(s) with multiple requests and some will certainly return seconds before others.

This way you could have the same reducer handle the results and begin updating the UI as the results come in.

An example real-world app might be a price comparison tool or social media aggregator.

naasking 3198 days ago

> I suppose this might be useful in situations where you are querying an API(s) with multiple requests and some will certainly return seconds before others.

But it's still a serialized operation so the parallelism is still limited. What's really needed is a "parallel reduce" using something like C's select function that will reduce in an arbitrary order using any promises that are ready at any given step.

abritinthebay 3198 days ago

A nice use case for sure. Seems possible with some kind of iterator/generator wrapper rather than the mess in the OP however.

joeframbach 3198 days ago

The example isn't using Promise.reduce.

charliesome 3198 days ago

> Pointless abstraction is one of my pet peeves in this industry. This looks like it has gone from a fairly straightforward, if kludgy, piece of code to something far more complex. Why not just: [code]

Your example code works just fine for promises of course, but not all monads support a coalescing operation like Promise.all.

So even though this article only discusses folding over Promises, the core idea here can be generalised to any monad type (such as Promise, Result, Option, or anything else)

yorwba 3198 days ago

> not all monads support a coalescing operation like Promise.all.

Actually, they do. Haskell calls it sequence :: (Traversable t, Monad m) => t (m a) -> m (t a) [1]

It works by consuming the structure outside the monad and rebuilding it inside. A possible implementation specialized for lists is

  sequence [] = return []
  sequence (h:t) = do
    h' <- h
    t' <- sequence t
    return (h':t')

[1] http://hackage.haskell.org/package/base-4.10.0.0/docs/Prelud...

charliesome 3198 days ago

Sorry, I should've been more clear. You're right - you can absolutely build sequence out of the bind operation for any monad.

Promise.all is not just sequence though, there's some additional subtleties to it. In particular the fail-fast behaviour:

https://developer.mozilla.org/en-US/docs/Web/JavaScript/Refe...

That's the kind of fundamental coalescing operation that you cannot implement with bind on plain monads.

noelwelsh 3198 days ago

I don't think this is very well written. It doesn't start with any motivating problem, it introduces terms (functor) without defining them, and a lot of what is discussed doesn't apply to solving the problem.

fair24 3198 days ago

> Folding Promises in JavaScript

Or: How to make simple things complex and make a codebase a complete puzzle for those that come after you?

Androider 3198 days ago

I feel nothing has improved code readability like the recent mainstreaming of map/filter/fold/reduce and "const all the things". This type of code is so easy to follow, reason about and trivial to debug at every step, once you internalize the few primitive functions.

I don't think you need to necessarily memorize these transformation names, but writing these types of functions is all I seem to be doing these days, transforming one thing into another line for line.

jacobr 3198 days ago

I feel the code I wrote while on this bandwagon is the hardest to understand for others and for me myself today.

    pullAllBy(pluck(things, 'bar').map(compose(xor, lol, rofl)).reduce(differenceWith('id'))

Just write your transformations inline and go work on the next feature.

Androider 3198 days ago

The trick is to break that (on the dots) into three const assignments with descriptive names. Practically self-documenting, easily debuggable.

If you don't use the builtin transformations, you'll just end up re-implementing them, poorly. And adding to the cognitive overhead with new concepts. And I have to read your code with a fine-toothed comb to ensure it's really side-effect free. I don't advocate turning everything into a named function as in your example though, short one-off functions should all be inline IMO.

splintercell 3198 days ago

I feel like the functional code you wrote was written to intentionally obfuscate what is being done. For instance, composing a bunch of methods inline doesn't have any utility for it unless you define what compose(xor, lol, rofl) really means.

Ideally this is how it should be written for maximum readability.

  things
  |> pluck('bar')
  |> map(xor)
  |> map(lol)
  |> map(rofl)
  |> reduce(differenceWith('id')

The code is written equally well without using pipe operator but the proposal to introduce it is in works [1].

Here is it using lodash (not even lodash-fp), and this is going to do a single for loop when executing because this is lazy.

  _.chain(things)
   .pluck('bar')
   .map(_.xor)
   .map(_.lol)
   .map(_.rofl)
   .reduce(_.differenceWith('id'))
   .value();

It's no less readable than the code you'd write using using unfolded transformations.

1. https://github.com/tc39/proposal-pipeline-operator

gaastonsr 3198 days ago

I agree, but you shouldn't map 3 times when you can map once over the data.

   things
    |> pluck('bar')
    |> map(compose(rofl, lol, xor))
    |> reduce(differenceWith('id')

splintercell 3198 days ago

I made my case against the compose in the post.

Composing xor, rofl, lol isn't any better (esp in terms of readability) than it is individual maps.

What would be better is this:

  const makeHilarious = compose(rofl, lol, xor);
  
  things
    |> pluck('bar')
    |> map(makeHilarious)
    |> reduce(differenceWith('id')

disantlor 3198 days ago

the nice thing is that you can easily split that line up as much as makes sense, should you decide you need to access some intermediate form of the data. and you can use the variable names as a comment that explains what that chunk of transformations represents.

so someone reading over it can kind of skim down the left side and follow what's happening and scan to the right if they need to understand some part in detail

VMG 3198 days ago

If only you could still recognize it as a transformation when it is inline

jackcviers3 3198 days ago

These things map/reduce/compose/flatmap are universal - they're in java, python, c#, Ocaml, Haskell, lisp, ruby, javascript...

Complaining about learning them is like complaining about for loops. They just exist.

Just because some are more familiar with for loops than map doesn't mean that more universal, immutable, expression - based solutions are not widely familiar and easy to understand to programmers coming from other languages.

Readability is subjective.

brokenpromise 3198 days ago

I've been working with JavaScript since February and I want to give you a hug.

CapacitorSet 3198 days ago

I can't quite understand the difference between endomorphism ("input and output of the transformer must be from the same category") and homomorphism ("structure preserving transformation. We always stay in the same category"). Can someone help?

mmarx 3198 days ago

Homomorphisms are structure-preserving mappings between different types (called “category” in the post, in usual terminology, these would be »objects« in a »category«, though). Endomorphisms are special homomorphisms, mapping from a single type (»object«) to the same type (»object«).

It is indeed very unfortunate that the article conflates terminology.

lsjroberts 3198 days ago

I believe homomorphism is a subset of endomorphism.

So a function that turns an array into another array of different length would be endomorphic (since it maintains the same type), but not homomorphic since it has a different structure (a different set of keys).

catnaroek 3198 days ago

The other way around. A homomorphism is a structure-preserving map between two arbitrary objects, whereas an endomorphism is a homomorphism where the source and target objects coincide.

tel 3198 days ago

Endomorphism has less implied structure. Lots of dumb things are endomorphisms. Homomorphism implies "structure preservation" which can make it more specific.

catnaroek 3198 days ago

I'm surprised to read this coming from you.

dllthomas 3198 days ago

It seems "endomorphism" is used both ways (in, presumably, different contexts).

https://ncatlab.org/nlab/show/endomorphism

I think "endomorphism is a homomorphism ..." is more common, but notably is not the usage in Haskell (https://hackage.haskell.org/package/base/docs/Data-Monoid.ht...)

catnaroek 3198 days ago

Of course, Haskell's `Endo` is a type constructor for `Hask`-endomorphisms, but more interesting categories exist. Tell me with a straight face ring and field endomorphisms aren't interesting.

molf 3198 days ago

With async/await this can become:

    const reduceP = async (fn, identity, listP) => {
      const values = await Promise.all(listP)
      return values.reduce(fn, identity)
    }

The whole thing feels like a synthetic and overcomplicated example, though. In practice I'm sure I'd just write:

    let total = 0
    while (listP.length > 0) {
      total += await listP.pop()
    }

megawatthours 3198 days ago

That code does the same thing as https://news.ycombinator.com/item?id=15302465 but not the same thing as the code in the article.

egeozcan 3198 days ago

I don't know much about these concepts but isn't `const objToArray = ({ a }) => [a];` losing data, that being the key of the value in the object? I'm asking because it says that "Isomorphism is a pair of transformations between two categories with no data loss".

In any case, this is very helpful, thanks for writing/sharing.

paavohtl 3198 days ago

It's a pair of transformations between [A] and { a: A }, not between arbitrary arrays and objects.

As long as you know what the transformation is, you can convert between them without data loss.

navaati 3198 days ago

EDIT: see paavohtl's comment: I hadn't payed attention to the types, dumb me.

You're right, because for a pair of functions f and g, you have an isomorphism if:

  f(g(x)) == x

  g(f(x)) == x

for every x. However, here of course

  (([a]) => {a})( (({ a }) => [a])({ key: 'data'}) )

is equal to

  { a: 'data' }

The OP doesn't quite master what he's talking about…

wereHamster 3198 days ago

The pair of functions form an isomorphism. You have these two laws:

    forall x. objToArray(arrayToObj(x)) == x
    forall x. arrayToObj(objToArray(x)) == x

idbehold 3198 days ago

Yeah, that was my though as well. It seems like what you need is something like:

   const objToArray = Object.entries
   const arrayToObj = (a) => a.reduce((a, [k, v]) => ((a[k]=v), a), {})
   arrayToObj(objToArray({ foo: 'bar' })) // { foo: 'bar' }

fortythirteen 3198 days ago

"Programs must be written for people to read, and only incidentally for machines to execute." - Harold Abelson

porlune 3198 days ago

The author mentions the library Bluebird, which I think is a fantastic library. The 'mapSeries' method it offers is also very useful when iterating over an array of values that need to be 'promisified' and mapped in the given order. You can even set 'concurrency' as an option, which puts a limit on the concurrent promises that can run (great for reducing API load).

chajath 3198 days ago

I've written a javascript library to deal with folding and mapping recurring promises (i.e. promises that resolve to a value part of which contains clue to the "next" promise)

https://github.com/google/chained-promise

minitech 3198 days ago

With async (it’s just monads!):

  listOfPromises.reduce(
    async (m, n) => await m + await n,
    0,
  )