from there, I suggest to work backwards
i.e start from the result, and see what you need to get there
e.g the last step is from
F[List[(DataSpec, DataSetRef]] to F[List[DataSetRef]]
that's
map(_.map(_._2))
now, how do you get to
F[List[(DataSpec, DataSetRef]]
and so on
for example, you might get to
map(...).sequence.flatMap(_.flatten)
map(...).sequence is traverse
traverse(...).flatMap(_.flatten) is flatTraverse
and there you go
it takes some time to learn but after a while you'll do it all in your head instantaneously :)
Instead of papering over the final type
exactly
what I've noticed is that people stare at the solution, concentrating as much as they can, waiting for illumination
because when you can't decompose the problem, that's all you can do
but in pure FP, often, you can decompose the problem
so one of the most things to learn (and teach) is how to do that
what you can do is delete my code
and try deriving it again from scratch
Hi there. Could someone explain me, please, what is the difference between
Task.map2 and Task.parMap2. The documentation states that the former is sequential, although the latter is parallel. But it seems, that the implementation of these two are the same except a subtle difference: Task.parMap2 just calls Task.mapBoth directly, although Task.map2 calls non-static (but final anyway) Task.zipMap first, which, in turn, calls that Task.mapBoth. So, in my understanding, they both should behave in the same way. What does make one of them sequential and the other one parallel?
Hi @/all, I am creating a GH repo that explains how to organize a scalabridge workshop (so that many people can do so in different parts of the world). Scalabridge is a workshop that teaches underrepresented students the basics of programming in Scala using Creative Scala tutorial. It is a great way to grow the community. I am organizing a list of mentors (based on location) who are interested in helping out, so that a new organizer has mentors to reach out to when organizing a workshop. If you're interested in helping out as a scalabridge mentor, please create a PR and put your info in this file: https://github.com/xingyif/scalabridge/blob/master/organize-a-workshop/invite-mentors.md#interested--mentors
Thanks
Thanks
@satorg It seems like that was a bug. If you check upstream, it has been corrected to execute sequentially https://github.com/monix/monix/blob/master/monix-eval/shared/src/main/scala/monix/eval/Task.scala#L3093
won’t be available in 2.x series though probably
@satorg @RaasAhsan If any of you are interested in patching the 2.x series, do a PR for this branch: https://github.com/monix/monix/tree/series/2.x — and I'll publish a patch release afterwards.
Hi, I'm trying to setup an app that will consume a Kafka stream and produce to a Kafka stream with some processing in the middle which is currently built using
Tasks. What's the recommended way to set this up? I'm currently trying to use monix-kafka's KafkaConsumerObservable and in the process of building out an Observer which I believe means eventually I need convert the ConsumerRecord into my data type and kick off my processing within onNext(). Does that mean I need to run the Task within onNext()? Is consumeWith a better option? And would that mean I need to handle polling?
@yanana did you get anywhere with this https://gitter.im/monix/monix?at=58eb038008c00c092a65d6b7 , please ?
Tasks that are not yet attached to execution contexts should be serializable out of the box, no?
Guess you should try it and see if it breaks or not 🙂 serialization in Java is unfortunately a dark art of sorts. I avoid it as much as possible, but guessing with Spark it is inevitable.
Is there a way to create an
Observable that waits for input? I imagine if you're streaming an Observable from a file and there's a delay on disk IO, it will patiently wait before getting the next bits and processing them. Is there a way to get the same behaviour waiting for input from my program?
So anything subscribed to the observable will do nothing until an element is fed to it
@jdrphillips might be helpful: https://github.com/monix/monix.io/blob/038de49219af7db7beeeea53e8c6c3963304b7ef/_tut/docs/3x/reactive/observable.md#subjects
I'd recommend using
Task versions whenever possible, there are also for traverse, parTraverse and normal sequence + unordered variants