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60fps with Functional Programming in idle time

miketalbot profile image Mike Talbot ・3 min read

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js-coroutines has been able to process standard functions like parsing and stringifying JSON, or compressing data in idle time since it was launched - splitting up jobs over multiple frames so that everything stays smooth at 60fps - it now has the ability to build functional pipelines too:

const process =
            mapAsync.with((v) => ({...v, total: v.units * v.price})),

Here is a dummy routine that parses some JSON, works out a total value of items, stores it back in JSON, and compresses it.

We can then call this pipeline with our data:

   const compressedData = await process(inputJSON)

The pipe function creates an asynchronous process that, in conjunction with the standard js-coroutines, runs all of the jobs collaboratively on the main thread, ensuring that there is enough time for animations and interaction.

We can also just insert our own calculations that we'd like to split up:

      const process = pipe(
             function * (data) {
                let i = 0
                let output = []
                for(let item of data) {
                       total: item.units * item.price,
                       score: complexScore(item)
                    if((i++ % 100)==0) yield
                return output

Here we put a generator function into the pipeline and make sure we call yield now and again. This yield call will check that we have enough time to continue or will schedule the resumption of the function on the next idle.

New functions

Function Parameters Purpose
pipe ...function

each function can be an async function, a normal function or a generator

A function takes the current value of the pipeline and processes it. You can use the call() function to pass other parameters - for instance the mapping function of a mapAsync. All xxxAsync functions in js-coroutines have a .with() function you can use to shortcut importing call - it has the same effect.

Creates an async function to execute the pipeline
tap function(current){...} This function adds a function to the pipeline that receives the current value, but does not return it's result. You can use it to cause side effects like logging or saving. The pipeline pauses execution until the function is complete.
branch function(current){...} This function adds a function to the pipeline that receives the current value. You can use it to cause side effects like logging or saving. The pipeline DOES NOT pause execution, so a new continuation is formed from this point forwards.
repeat function,times Creates a function that executes the specified function a number of times
call function,...params This function enables calling another function that will take the current value of the pipeline but needs extra parameters. The parameters supplied will be appended to the current value of the pipeline.


Discussion (9)

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vldmrgnn profile image
Vlad • Edited

Great work! I am using the coroutines in the project I am working on. Even though most of the data manipulation is done Redux-Saga and/or Reselect, there are various situations in which the coroutines are highly useful.

Congrats on the home page too. Very helpful explanations and examples. And certainly the "pipe" is most welcome for the functional approach.
Still. I have not found a way to execute the smooth animation while fetching data from server. I make a heavy use of "useSWR" and the animation halts. It seems there is no room left for animation frame:). If you have any suggestion it would be great.
Anyway keep up the good work!

miketalbot profile image
Mike Talbot Author

Hey not used it, but looks useful :) Are you letting it parse JSON for you? If you are parsing JSON with it, I'd suggest using it to get plain text and then use parseAsync as this can be very slow - do feel free to create an issue on the GitHub and we can see what's possible.

vldmrgnn profile image
Vlad • Edited

Thanks. Actually I do some minor data manipulation on arrival (e.g. lodash/fp "keyBy" s.o) then dispatch to Redux Store. I'll check it deeper and if needed I will make an issue on GitHub as you suggested.
Thanks again!

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miketalbot profile image
Mike Talbot Author • Edited

Ok that keyBy might be an issue if the data is huge. You/I/we could do a version of keyBy that uses reduceAsync and that would split it up over frames. Fundamentally that would probably look like this:

function keyByAsync(items, predicate) {

    return reduceAsync(items, reducer, {})
    function reducer(acc, cur) {
        acc[predicate(cur)] = cur
        return acc

      await keyByAsync(yourArray, v=>v.somethingOrOther)

That's making a single lookup rather than a key to array - but it sounds like this is what you are after. It's a useful function, I may clean it and a few others like groupBy and add them. Basically anything that takes a while benefits from going through one of the async functions which yield every 8 times (by default) to see if there is still time.

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vldmrgnn profile image

Yes! It has to be this. The keyBy is really needed as the reducer was built that way for O1 access with selector and so on... I will try to put up something here to test but I am pretty sure that your keyByAsync would be much reliable than mine:) So I will stay tuned for update. Thanks a lot!

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miketalbot profile image
Mike Talbot Author

Totally makes sense to me. Ok I'll sort it over the next few days.

pavelloz profile image
Paweł Kowalski

Reminds me of streams, or RxJS - i dont know if there is any conceptual overlap, just my hunch :)

miketalbot profile image
Mike Talbot Author

I've never used RxJS, but I'm beginning to see some overlaps. I guess the main thing here is the use of generator functions to split a more "commonish" pattern up over multiple frames to maintain interactivity. I'm wondering about trying to get a hook into a more serious library that has additional features for functional programming but would benefit from collaborative multi-tasking.