The key to functional programming is abstraction, and composability of abstractions. Monads, Arrows, Lenses, these are all abstractions which have proven themselves useful, mostly because they are composable. You’ve asked for a “prescriptive” answer, but I’m going to say no. Perhaps you’re not convinced that functional programming matters? I’m sure plenty of people on StackOverflow … Read more
I cannot answer it all, but i try on some parts: Is there some reason that the “most asynchronous” behavior—i.e., don’t consume the collection before returning, and don’t wait for each future to complete before moving on to the next—isn’t represented here? If you have dependent calculations and a limited number of threads, you can … Read more
In Practice No, it can not be done, at least not in a meaningful way. Consider this Haskell code action :: Int -> IO String action n = print n >> getLine This takes n first, prints it (IO performed here), then reads a line from the user. Assume we had an hypothetical transform :: … Read more
sequence is used to gather together applicative effects. More concretely, it lets you “flip” F[G[A]] to G[F[A]], provided G is Applicative and F is Traversable. So we can use it to “pull together” a bunch of Applicative effects (note all Monads are Applicative): List(Future.successful(1), Future.successful(2)).sequence : Future[List[Int]] // = Future.successful(List(1, 2)) List(4.set(“abc”), 5.set(“def”)).sequence : Writer[String, … Read more
A scalaz-stream solution: import scalaz.std.vector._ import scalaz.syntax.traverse._ import scalaz.std.string._ val action = linesR(“example.txt”).map(_.trim). splitOn(“”).flatMap(_.traverseU { s => s.split(” “) match { case Array(form, pos) => emit(form -> pos) case _ => fail(new Exception(s”Invalid input $s”)) }}) We can demonstrate that it works: scala> action.collect.attempt.run.foreach(_.foreach(println)) Vector((no,UH), (,,,), (it,PRP), (was,VBD), (n’t,RB), (monday,NNP), (.,.)) Vector((the,DT), (equity,NN), (market,NN), (was,VBD), … Read more
1) After rewriting your code as follows: case class Monoid[A](m0: A) // We only care about the zero here implicit def s[T] : Monoid[Set[T]] = Monoid(Set.empty[T]) implicit def l[T] : Monoid[List[T]] = Monoid(List.empty[T]) def mzero[A]()(implicit m: Monoid[A]) : A = m.m0 val zero = mzero[List[Int]]() val zero2: List[Int] = mzero() then becomes clearly why that … Read more
Type Constructors as Type Parameters M is a type parameter to one of Scalaz’s main pimps, MA, that represents the Type Constructor (aka Higher Kinded Type) of the pimped value. This type constructor is used to look up the appropriate instances of Functor and Apply, which are implicit requirements to the method <**>. trait MA[M[_], … Read more
This is the most comprehensive comparison I have seen so far: http://doc.akka.io/docs/misc/Comparison_between_4_actor_frameworks.pdf via http://klangism.tumblr.com/post/2497057136/all-actors-in-scala-compared
Edit: I missed that the title of your question asked for Either[Seq[A],Seq[B]], but I did read “I’d like to obtain the first error message or a concatenation of all error messages”, and this would give you the former: def sequence[A, B](s: Seq[Either[A, B]]): Either[A, Seq[B]] = s.foldRight(Right(Nil): Either[A, List[B]]) { (e, acc) => for (xs … Read more
I would like to keep this from getting too political*, but cats is for all intents and purposes scalaz. It has not reached full parity as of yet, but keep in mind it was only created a few months ago. The goal is for it to be a more pragmatic approach and more democratic when … Read more