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  • Scalaz Kleisli question

    - by oxbow_lakes
    There is a trait called Kleisli in the scalaz library. Looking at the code: import scalaz._ import Scalaz._ type StringPair = (String, String) val f: Int => List[String] = (i: Int) => List((i |+| 1).toString, (i |+| 2).toString) val g: String => List[StringPair] = (s: String) => List("X" -> s, s -> "Y") val k = kleisli(f) >=> kleisli(g) //this gives me a function: Int => List[(String, String)] Calling the function k with the value of 2 gives: println( k(2) ) //Prints: List((X,3), (3,Y), (X,4), (4,Y)) My question is: how would I use Scalaz to combine f and g to get a function m such that the output of m(2) would be: val m = //??? some combination of f and g println( m(2) ) //Prints: List((X,3), (X,4), (3,Y), (4,Y)) Is this even possible?

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  • how to translate Haskell into Scalaz?

    - by TOB
    One of my high school students and I are going to try to do a port of Haskell's Parsec parser combinator library into Scala. (It has the advantage over Scala's built-in parsing library that you can pass state around fairly easily because all the parsers are monads.) The first hitch I've come across is trying to figure out how Functor works in scalaz. Can someone explain how to convert this Haskell code: data Reply s u a = Ok a !(State s u) ParseError | Error ParseError instance Functor (Reply s u) where fmap f (Ok x s e) = Ok (f x) s e fmap _ (Error e) = Error e -- XXX into Scala (using Scalaz, I assume). I got as far as sealed abstract class Reply[S, U, A] case class Ok[S, U, A](a: A, state: State[S, U], error: ParseError) extends Reply[S, U, A] case class Error[S, U, A](error: ParseError) extends Reply[S, U, A] and know that I should make Reply extend the scalaz.Functor trait, but I can't figure out how to do that. (Mostly I'm having trouble figuring out what the F[_] parameter does.) Any help appreciated! Thanks, Todd

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  • Good scalaz introduction

    - by Easy Angel
    Recently scalaz caught my eye. It looks very interesting, but I have not found any good introduction to the library. Seems that scalaz incorporates a lot of ideas from haskell and mathematics. Most articles that I found assume that you already feel comfortable with these concepts. What I'm looking for is gradual introduction to the library and underlying concepts - from simple and basic concepts to more advanced (which basesd in basics). I also looked to the examples, but it's hard for me to find the point where I should start to learn library. Can somebody recommend me some good scalaz introduction or tutorial (that covers basics and advanced concepts)? Or give me starting point in the answer. Thank you in advance!

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  • Scalaz: request for use case

    - by oxbow_lakes
    This question isn't meant as flame-bait! As it might be apparent, I've been looking at Scalaz recently. I'm trying to understand why I need some of the functionality that the library provides. Here's something: import scalaz._ import Scalaz._ type NEL[A] = NonEmptyList[A] val NEL = NonEmptyList I put some println statements in my functions to see what was going on (aside: what would I have done if I was trying to avoid side effects like that?). My functions are: val f: NEL[Int] => String = (l: NEL[Int]) => {println("f: " + l); l.toString |+| "X" } val g: NEL[String] => BigInt = (l: NEL[String]) => {println("g: " + l); BigInt(l.map(_.length).sum) } Then I combine them via a cokleisli and pass in a NEL[Int] val k = cokleisli(f) =>= cokleisli(g) println("RES: " + k( NEL(1, 2, 3) )) What does this print? f: NonEmptyList(1, 2, 3) f: NonEmptyList(2, 3) f: NonEmptyList(3) g: NonEmptyList(NonEmptyList(1, 2, 3)X, NonEmptyList(2, 3)X, NonEmptyList(3)X) RES: 57 The RES value is the character count of the (String) elements in the final NEL. Two things occur to me: How could I have known that my NEL was going to be reduced in this manner from the method signatures involved? (I wasn't expecting the result at all) What is the point of this? Can a reasonably simple and easy-to-follow use case be distilled for me? This question is a thinly-veiled plea for some lovely person like retronym to explain how this powerful library actually works.

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  • Scalaz: request for use case for Cokleisli composition

    - by oxbow_lakes
    This question isn't meant as flame-bait! As it might be apparent, I've been looking at Scalaz recently. I'm trying to understand why I need some of the functionality that the library provides. Here's something: import scalaz._ import Scalaz._ type NEL[A] = NonEmptyList[A] val NEL = NonEmptyList I put some println statements in my functions to see what was going on (aside: what would I have done if I was trying to avoid side effects like that?). My functions are: val f: NEL[Int] => String = (l: NEL[Int]) => {println("f: " + l); l.toString |+| "X" } val g: NEL[String] => BigInt = (l: NEL[String]) => {println("g: " + l); BigInt(l.map(_.length).sum) } Then I combine them via a cokleisli and pass in a NEL[Int] val k = cokleisli(f) =>= cokleisli(g) println("RES: " + k( NEL(1, 2, 3) )) What does this print? f: NonEmptyList(1, 2, 3) f: NonEmptyList(2, 3) f: NonEmptyList(3) g: NonEmptyList(NonEmptyList(1, 2, 3)X, NonEmptyList(2, 3)X, NonEmptyList(3)X) RES: 57 The RES value is the character count of the (String) elements in the final NEL. Two things occur to me: How could I have known that my NEL was going to be reduced in this manner from the method signatures involved? (I wasn't expecting the result at all) What is the point of this? Can a reasonably simple and easy-to-follow use case be distilled for me? This question is a thinly-veiled plea for some lovely person like retronym to explain how this powerful library actually works.

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  • Function syntax puzzler in scalaz

    - by oxbow_lakes
    Following watching Nick Partidge's presentation on deriving scalaz, I got to looking at this example, which is just awesome: import scalaz._ import Scalaz._ def even(x: Int) : Validation[NonEmptyList[String], Int] = if (x % 2 ==0) x.success else "not even: %d".format(x).wrapNel.fail println( even(3) <|*|> even(5) ) //prints: Failure(NonEmptyList(not even: 3, not even: 5)) I was trying to understand what the <|*|> method was doing, here is the source code: def <|*|>[B](b: M[B])(implicit t: Functor[M], a: Apply[M]): M[(A, B)] = <**>(b, (_: A, _: B)) OK, that is fairly confusing (!) - but it references the <**> method, which is declared thus: def <**>[B, C](b: M[B], z: (A, B) => C)(implicit t: Functor[M], a: Apply[M]): M[C] = a(t.fmap(value, z.curried), b) So I have a few questions: How come the method appears to take a monad of one type parameter (M[B]) but can get passed a Validation (which has two type paremeters)? How does the syntax (_: A, _: B) define the function (A, B) => C which the 2nd method expects? It doesn't even define an output via =>

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  • Implicit parameter in Scalaz

    - by Thomas Jung
    I try to find out why the call Ø in scalaz.ListW.<^> works def <^>[B: Zero](f: NonEmptyList[A] => B): B = value match { case Nil => Ø case h :: t => f(Scalaz.nel(h, t)) } My minimal theory is: trait X[T]{ def y : T } object X{ implicit object IntX extends X[Int]{ def y = 42 } implicit object StringX extends X[String]{ def y = "y" } } trait Xs{ def ys[T](implicit x : X[T]) = x.y } class A extends Xs{ def z[B](implicit x : X[B]) : B = ys //the call Ø } Which produces: import X._ scala> new A().z[Int] res0: Int = 42 scala> new A().z[String] res1: String = y Is this valid? Can I achieve the same result with fewer steps?

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  • Convert a List of Options to an Option of List using Scalaz

    - by Rafael de F. Ferreira
    The following function transforms a list of Option[T] into a list of Some[T], in the case where all members are Some's, or None, in the case where there is at least one None member. I guess the code is clearer that this explanation: def lo2ol[T](lo: List[Option[T]]): Option[List[T]] = { lo.foldRight[Option[List[T]]](Some(Nil)){(o, ol) => (o, ol) match { case (Some(x), Some(xs)) => Some(x :: xs); case _ => None : Option[List[T]]; }}} I remember seeing somewhere a similar example, but using Scalaz to simplify the code. How would it look like?

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  • Compilation issues using scalaz's MA methods on Set but not List

    - by oxbow_lakes
    The following compiles just fine using scala Beta1 and scalaz snapshot 5.0: val p1: Int => Boolean = (i : Int) => i > 4 val s: List[Int] = List(1, 2, 3) val b1 = s ? p1 And yet this does not: val s: Set[Int] = Set(1, 2, 3) val b1 = s ? p1 I get the following error: Found: Int = Boolean Required: Boolean = Boolean The signature of the ? method is: def ?(p: A => Boolean)(implicit r: FoldRight[M]): Boolean = any(p) And there should be an implicit SetFoldRight in scope. It is exactly the same for the methods: ?, ? and ?: - what is going on?

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  • How do I get the scalaz IDEA live templates working for the symbolic methods?

    - by oxbow_lakes
    Many of the methods in scalaz have symbolic equivalents, such as forever and 8 (of course, I have this the wrong way round, the symbolic methods really have ASCII equivalents). The project contains a live templates XML file for IDEA so these can be auto-completed, I believe by using the forever+TAB shortcut (in the above instance). I can't figure out how to import this live template into IDEA and actually use it, though. How can I do that?

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  • Threading extra state through a parser in Scala

    - by Travis Brown
    I'll give you the tl;dr up front I'm trying to use the state monad transformer in Scalaz 7 to thread extra state through a parser, and I'm having trouble doing anything useful without writing a lot of t m a -> t m b versions of m a -> m b methods. An example parsing problem Suppose I have a string containing nested parentheses with digits inside them: val input = "((617)((0)(32)))" I also have a stream of fresh variable names (characters, in this case): val names = Stream('a' to 'z': _*) I want to pull a name off the top of the stream and assign it to each parenthetical expression as I parse it, and then map that name to a string representing the contents of the parentheses, with the nested parenthetical expressions (if any) replaced by their names. To make this more concrete, here's what I'd want the output to look like for the example input above: val target = Map( 'a' -> "617", 'b' -> "0", 'c' -> "32", 'd' -> "bc", 'e' -> "ad" ) There may be either a string of digits or arbitrarily many sub-expressions at a given level, but these two kinds of content won't be mixed in a single parenthetical expression. To keep things simple, we'll assume that the stream of names will never contain either duplicates or digits, and that it will always contain enough names for our input. Using parser combinators with a bit of mutable state The example above is a slightly simplified version of the parsing problem in this Stack Overflow question. I answered that question with a solution that looked roughly like this: import scala.util.parsing.combinator._ class ParenParser(names: Iterator[Char]) extends RegexParsers { def paren: Parser[List[(Char, String)]] = "(" ~> contents <~ ")" ^^ { case (s, m) => (names.next -> s) :: m } def contents: Parser[(String, List[(Char, String)])] = "\\d+".r ^^ (_ -> Nil) | rep1(paren) ^^ ( ps => ps.map(_.head._1).mkString -> ps.flatten ) def parse(s: String) = parseAll(paren, s).map(_.toMap) } It's not too bad, but I'd prefer to avoid the mutable state. What I want Haskell's Parsec library makes adding user state to a parser trivially easy: import Control.Applicative ((*>), (<$>), (<*)) import Data.Map (fromList) import Text.Parsec paren = do (s, m) <- char '(' *> contents <* char ')' h : t <- getState putState t return $ (h, s) : m where contents = flip (,) [] <$> many1 digit <|> (\ps -> (map (fst . head) ps, concat ps)) <$> many1 paren main = print $ runParser (fromList <$> paren) ['a'..'z'] "example" "((617)((0)(32)))" This is a fairly straightforward translation of my Scala parser above, but without mutable state. What I've tried I'm trying to get as close to the Parsec solution as I can using Scalaz's state monad transformer, so instead of Parser[A] I'm working with StateT[Parser, Stream[Char], A]. I have a "solution" that allows me to write the following: import scala.util.parsing.combinator._ import scalaz._, Scalaz._ object ParenParser extends ExtraStateParsers[Stream[Char]] with RegexParsers { protected implicit def monadInstance = parserMonad(this) def paren: ESP[List[(Char, String)]] = (lift("(" ) ~> contents <~ lift(")")).flatMap { case (s, m) => get.flatMap( names => put(names.tail).map(_ => (names.head -> s) :: m) ) } def contents: ESP[(String, List[(Char, String)])] = lift("\\d+".r ^^ (_ -> Nil)) | rep1(paren).map( ps => ps.map(_.head._1).mkString -> ps.flatten ) def parse(s: String, names: Stream[Char]) = parseAll(paren.eval(names), s).map(_.toMap) } This works, and it's not that much less concise than either the mutable state version or the Parsec version. But my ExtraStateParsers is ugly as sin—I don't want to try your patience more than I already have, so I won't include it here (although here's a link, if you really want it). I've had to write new versions of every Parser and Parsers method I use above for my ExtraStateParsers and ESP types (rep1, ~>, <~, and |, in case you're counting). If I had needed to use other combinators, I'd have had to write new state transformer-level versions of them as well. Is there a cleaner way to do this? I'd love to see an example of a Scalaz 7's state monad transformer being used to thread state through a parser, but Scala 6 or Haskell examples would also be useful.

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  • Functional equivalent of if (p(f(a), f(b)) a else b

    - by oxbow_lakes
    I'm guessing that there must be a better functional way of expressing the following: def foo(i: Any) : Int if (foo(a) < foo(b)) a else b So in this example f == foo and p == _ < _. There's bound to be some masterful cleverness in scalaz for this! I can see that using BooleanW I can write: p(f(a), f(b)).option(a).getOrElse(b) But I was sure that I would be able to write some code which only referred to a and b once. If this exists it must be on some combination of Function1W and something else but scalaz is a bit of a mystery to me! EDIT: I guess what I'm asking here is not "how do I write this?" but "What is the correct name and signature for such a function and does it have anything to do with FP stuff I do not yet understand like Kleisli, Comonad etc?"

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  • Different Scala Actor Implementations Overview

    - by Stefan K.
    I'm trying to find the 'right' actor implementation for my thesis. I realized there is a bunch of them and it's a bit confusing to pick one. Personally I'm especially interested in remote actors, but I guess a complete overview would be helpful to many others. This is a pretty general question, so feel free to answer just for the implementation you know about. I know about the following Scala Actor implementations (SAI). Please add the missing ones. Scala 2.7 (difference to) Scala 2.8 Akka (http://www.akkasource.org/) Lift (http://liftweb.net/) Scalaz (http://code.google.com/p/scalaz/) What are the target use-cases for these SAIs (lightweight vs. "heavy" enterprise framework)? do they support remote actors? What shortcomings do remote actors have in the SAIs? How is their performace? How active is there community? How easy are they to get started? How good is the documentation? How easy are they to extend? How stable are they? Which projects are using them? What are their shortcomings? What are their design principles? Are they thread based or event based (receive/ react) or both? Nested receiveS hotswapping the Actor’s message loop

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  • Can I transform this asynchronous java network API into a monadic representation (or something else

    - by AlecZorab
    I've been given a java api for connecting to and communicating over a proprietary bus using a callback based style. I'm currently implementing a proof-of-concept application in scala, and I'm trying to work out how I might produce a slightly more idiomatic scala interface. A typical (simplified) application might look something like this in Java: DataType type = new DataType(); BusConnector con = new BusConnector(); con.waitForData(type.getClass()).addListener(new IListener<DataType>() { public void onEvent(DataType t) { //some stuff happens in here, and then we need some more data con.waitForData(anotherType.getClass()).addListener(new IListener<anotherType>() { public void onEvent(anotherType t) { //we do more stuff in here, and so on } }); } }); //now we've got the behaviours set up we call con.start(); In scala I can obviously define an implicit conversion from (T = Unit) into an IListener, which certainly makes things a bit simpler to read: implicit def func2Ilistener[T](f: (T => Unit)) : IListener[T] = new IListener[T]{ def onEvent(t:T) = f } val con = new BusConnector con.waitForData(DataType.getClass).addListener( (d:DataType) => { //some stuff, then another wait for stuff con.waitForData(OtherType.getClass).addListener( (o:OtherType) => { //etc }) }) Looking at this reminded me of both scalaz promises and f# async workflows. My question is this: Can I convert this into either a for comprehension or something similarly idiomatic (I feel like this should map to actors reasonably well too) Ideally I'd like to see something like: for( d <- con.waitForData(DataType.getClass); val _ = doSomethingWith(d); o <- con.waitForData(OtherType.getClass) //etc )

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  • How to read Scala code with lots of implicits?

    - by Petr Pudlák
    Consider the following code fragment (adapted from http://stackoverflow.com/a/12265946/1333025): // Using scalaz 6 import scalaz._, Scalaz._ object Example extends App { case class Container(i: Int) def compute(s: String): State[Container, Int] = state { case Container(i) => (Container(i + 1), s.toInt + i) } val d = List("1", "2", "3") type ContainerState[X] = State[Container, X] println( d.traverse[ContainerState, Int](compute) ! Container(0) ) } I understand what it does on high level. But I wanted to trace what exactly happens during the call to d.traverse at the end. Clearly, List doesn't have traverse, so it must be implicitly converted to another type that does. Even though I spent a considerable amount of time trying to find out, I wasn't very successful. First I found that there is a method in scalaz.Traversable traverse[F[_], A, B] (f: (A) => F[B], t: T[A])(implicit arg0: Applicative[F]): F[T[B]] but clearly this is not it (although it's most likely that "my" traverse is implemented using this one). After a lot of searching, I grepped scalaz source codes and I found scalaz.MA's method traverse[F[_], B] (f: (A) => F[B])(implicit a: Applicative[F], t: Traverse[M]): F[M[B]] which seems to be very close. Still I'm missing to what List is converted in my example and if it uses MA.traverse or something else. The question is: What procedure should I follow to find out what exactly is called at d.traverse? Having even such a simple code that is so hard analyze seems to me like a big problem. Am I missing something very simple? How should I proceed when I want to understand such code that uses a lot of imported implicits? Is there some way to ask the compiler what implicits it used? Or is there something like Hoogle for Scala so that I can search for a method just by its name?

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  • Type classes or implicit parameters? What do you prefer and why? [closed]

    - by Petr Pudlák
    I was playing a bit with Scalaz and I realized that Haskell's type classes are very similar to Scala's implicit parameters. While Haskell passes the methods defined by a type class using hidden dictionaries, Scala allows a similar thing using implicit parameters. For example, in Haskell, one could write: incInside :: (Functor f) => f Int -> f Int incInside = fmap (+ 1) and the same function using Scalaz: import scalaz._; import Scalaz._; def incInside[F[_]](x: F[Int])(implicit fn: Functor[F]): F[Int] = fn.fmap(x, (_:Int) + 1); I wonder: If you could choose (i.e. your favorite language would offer both), what would you pick - implicits or type classes? And what are your pros/cons?

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  • First impressions of Scala

    - by Scott Weinstein
    I have an idea that it may be possible to predict build success/failure based on commit data. Why Scala? It’s a JVM language, has lots of powerful type features, and it has a linear algebra library which I’ll need later. Project definition and build Neither maven or the scala build tool (sbt) are completely satisfactory. This maven **archetype** (what .Net folks would call a VS project template) mvn archetype:generate `-DarchetypeGroupId=org.scala-tools.archetypes `-DarchetypeArtifactId=scala-archetype-simple `-DremoteRepositories=http://scala-tools.org/repo-releases `-DgroupId=org.SW -DartifactId=BuildBreakPredictor gets you started right away with “hello world” code, unit tests demonstrating a number of different testing approaches, and even a ready made `.gitignore` file - nice! But the Scala version is behind at v2.8, and more seriously, compiling and testing was painfully slow. So much that a rapid edit – test – edit cycle was not practical. So Lab49 colleague Steve Levine tells me that I can either adjust my pom to use fsc – the fast scala compiler, or use sbt. Sbt has some nice features It’s fast – it uses fsc by default It has a continuous mode, so  `> ~test` will compile and run your unit test each time you save a file It’s can consume (and produce) Maven 2 dependencies the build definition file can be much shorter than the equivalent pom (about 1/5 the size, as repos and dependencies can be declared on a single line) And some real limitations Limited support for 3rd party integration – for instance out of the box, TeamCity doesn’t speak sbt, nor does IntelliJ IDEA Steeper learning curve for build steps outside the default Side note: If a language has a fast compiler, why keep the slow compiler around? Even worse, why make it the default? I choose sbt, for the faster development speed it offers. Syntax Scala APIs really like to use punctuation – sometimes this works well, as in the following map1 |+| map2 The `|+|` defines a merge operator which does addition on the `values` of the maps. It’s less useful here: http(baseUrl / url >- parseJson[BuildStatus] sure you can probably guess what `>-` does from the context, but how about `>~` or `>+`? Language features I’m still learning, so not much to say just yet. However case classes are quite usefull, implicits scare me, and type constructors have lots of power. Community A number of projects, such as https://github.com/scalala and https://github.com/scalaz/scalaz are split between github and google code – github for the src, and google code for the docs. Not sure I understand the motivation here.

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  • Scala libraries and frameworks

    - by folone
    Each technology is powerful with libraries and frameworks, written for it. I understand, that Scala is able to use libraries and frameworks, written for Java. But there are already some frameworks, written for Scala in Scala. Like, for example: Lift Framework ScalaTest Scalaz Do you know any more great libraries and frameworks for Scala, written in Scala?

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  • Closures and universal quantification

    - by Apocalisp
    I've been trying to work out how to implement Church-encoded data types in Scala. It seems that it requires rank-n types since you would need a first-class const function of type forAll a. a -> (forAll b. b -> b). However, I was able to encode pairs thusly: import scalaz._ trait Compose[F[_],G[_]] { type Apply = F[G[A]] } trait Closure[F[_],G[_]] { def apply[B](f: F[B]): G[B] } def pair[A,B](a: A, b: B) = new Closure[Compose[PartialApply1Of2[Function1,A]#Apply, PartialApply1Of2[Function1,B]#Apply]#Apply, Identity] { def apply[C](f: A => B => C) = f(a)(b) } For lists, I was able to get encode cons: def cons[A](x: A) = { type T[B] = B => (A => B => B) => B new Closure[T,T] { def apply[B](xs: T[B]) = (b: B) => (f: A => B => B) => f(x)(xs(b)(f)) } } However, the empty list is more problematic and I've not been able to get the Scala compiler to unify the types. Can you define nil, so that, given the definition above, the following compiles? cons(1)(cons(2)(cons(3)(nil)))

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