learning Scalaz: day 18


Hey there. There's an updated html5 book version, if you want.

On day 17 we looked at IO monad as a way of abstracting side effects, and Iteratees as a way of handling streams. And the series ended.


I wanted to continue exploring a better way to compose applicative functions, and came up with a wrapper called AppFunc:

val f = AppFuncU { (x: Int) => x + 1 }
val g = AppFuncU { (x: Int) => List(x, 5) }
(f @&&& g) traverse List(1, 2, 3)

After sending this in as a pull request Lars Hupel (@larsr_h) suggested that I generalize the concept using typelevel module, so I expanded it to Func:

 * Represents a function `A => F[B]` where `[F: TC]`.
trait Func[F[_], TC[F[_]] <: Functor[F], A, B] {
  def runA(a: A): F[B]
  implicit def TC: KTypeClass[TC]
  implicit def F: TC[F]

Using this, AppFunc becomes Func with Applicative in the second type parameter. Lars still wants to expand it composition into general HList, but I am optimistic that this will be part of Scalaz 7 eventually.


What I want to explore today actually is the Free monad by reading Gabriel Gonzalez's Why free monads matter:

Let's try to come up with some sort of abstraction that represents the essence of a syntax tree. ... Our toy language will only have three commands:

output b -- prints a "b" to the console
bell     -- rings the computer's bell
done     -- end of execution

Here's Toy translated into Scala:

scala> :paste
// Entering paste mode (ctrl-D to finish)
sealed trait Toy[A]
case class Output[A, B](a: A, next: B) extends Toy[A]
case class Bell[A, B](next: B) extends Toy[A]
case class Done[A]() extends Toy[A]
// Exiting paste mode, now interpreting.
defined trait Toy
defined class Output
defined class Bell
defined class Done
scala> Output('A', Done())
res0: Output[Char,Done[Nothing]] = Output(A,Done())
scala> Bell(Output('A', Done()))
res1: Bell[Nothing,Output[Char,Done[Nothing]]] = Bell(Output(A,Done()))


but unfortunately this doesn't work because every time I want to add a command, it changes the type.

I don't know if this is a problem in Scala since they all extend Toy, but let's play along and define Fix:

scala> case class Fix[F[_]](f: F[Fix[F]])
defined class Fix
scala> Fix[({type λ[α] = Toy[Char]})#λ](Output('A', Fix[({type λ[α] = Toy[Char]})#λ](Done())))
res4: Fix[[α]Toy[Char]] = Fix(Output(A,Fix(Done())))
scala> Fix[({type λ[α] = Toy[Char]})#λ](Bell(Fix[({type λ[α] = Toy[Char]})#λ](Output('A', Fix[({type λ[α] = Toy[Char]})#λ](Done())))))
res11: Fix[[α]Toy[Char]] = Fix(Bell(Fix(Output(A,Fix(Done())))))

We are also going to try to implement FixE, which adds exception to this.

scala> :paste
// Entering paste mode (ctrl-D to finish)
sealed trait FixE[F[_], E]
case class Fix[F[_], E](f: F[FixE[F, E]]) extends FixE[F, E]
case class Throw[F[_], E](e: E) extends FixE[F, E] 
// Exiting paste mode, now interpreting.
defined trait FixE
defined class Fix
defined class Throw

Since catch is a reserverd word, I am going to rename this to catchy:

scala> import scalaz._
import scalaz._
scala> def catchy[F[_]: Functor, E1, E2](ex: => FixE[F, E1])(f: E1 => FixE[F, E2]): FixE[F, E2] = ex match {
         case Fix(x)   => Fix[F, E2](Functor[F].map(x) {catchy(_)(f)})
         case Throw(e) => f(e)
catchy: [F[_], E1, E2](ex: => FixE[F,E1])(f: E1 => FixE[F,E2])(implicit evidence$1: scalaz.Functor[F])FixE[F,E2]
scala> implicit def ToyFunctor[A1]: Functor[({type λ[α] = Toy[A1]})#λ] = new Functor[({type λ[α] = Toy[A1]})#λ] {
         def map[A, B](fa: Toy[A1])(f: A => B): Toy[A1] = fa match {
           case o: Output[A1, A] => Output(o.a, f(o.next))
           case b: Bell[A1, A]   => Bell(f(b.next))
           case Done()           => Done()
ToyFunctor: [A1]=> scalaz.Functor[[α]Toy[A1,α]]

Here's the sample usage:

scala> case class IncompleteException()
defined class IncompleteException
scala> def subroutine = Fix[({type λ[α] = Toy[Char]})#λ, IncompleteException](Output('A', Throw[({type λ[α] = Toy[Char]})#λ, IncompleteException](IncompleteException())))
subroutine: Fix[[α]Toy[Char],IncompleteException]
scala> def program = catchy[({type λ[α] = Toy[Char]})#λ, IncompleteException, Nothing](subroutine) { _ =>
         Fix[({type λ[α] = Toy[Char]})#λ, Nothing](Bell(Fix[({type λ[α] = Toy[Char]})#λ, Nothing](Done())))
program: FixE[[α]Toy[Char],Nothing]

Free monads part 1


our FixE already exists, too, and it's called the Free monad:

data Free f r = Free (f (Free f r)) | Pure r

As the name suggests, it is automatically a monad (if f is a functor):

instance (Functor f) => Monad (Free f) where
    return = Pure
    (Free x) >>= f = Free (fmap (>>= f) x)
    (Pure r) >>= f = f r

The corresponding structure in Scalaz is called Free:

sealed abstract class Free[S[+_], +A](implicit S: Functor[S]) {
  final def map[B](f: A => B): Free[S, B] =
    flatMap(a => Return(f(a)))
  final def flatMap[B](f: A => Free[S, B]): Free[S, B] = this match {
    case Gosub(a, g) => Gosub(a, (x: Any) => Gosub(g(x), f))
    case a           => Gosub(a, f)
object Free extends FreeInstances {
  /** Return from the computation with the given value. */
  case class Return[S[+_]: Functor, +A](a: A) extends Free[S, A]
  /** Suspend the computation with the given suspension. */
  case class Suspend[S[+_]: Functor, +A](a: S[Free[S, A]]) extends Free[S, A]
  /** Call a subroutine and continue with the given function. */
  case class Gosub[S[+_]: Functor, A, +B](a: Free[S, A],
                                          f: A => Free[S, B]) extends Free[S, B]
trait FreeInstances {
  implicit def freeMonad[S[+_]:Functor]: Monad[({type f[x] = Free[S, x]})#f] =
    new Monad[({type f[x] = Free[S, x]})#f] {
      def point[A](a: => A) = Return(a)
      override def map[A, B](fa: Free[S, A])(f: A => B) = fa map f
      def bind[A, B](a: Free[S, A])(f: A => Free[S, B]) = a flatMap f

In Scalaz version, Free constructor is called Free.Suspend and Pure is called Free.Return. Let's implement liftF, and port Toy commands:

scala> def output[A](a: A): Free[({type λ[] = Toy[A]})#λ, Unit] =
         Free.Suspend[({type λ[] = Toy[A]})#λ, Unit](Output(a, Free.Return[({type λ[] = Toy[A]})#λ, Unit](())))
output: [A](a: A)scalaz.Free[[]Toy[A],Unit]
scala> def liftF[F[+_]: Functor, R](command: F[R]): Free[F, R] =
         Free.Suspend[F, R](Functor[F].map(command) {Free.Return[F, R](_)})
liftF: [F[+_], R](command: F[R])(implicit evidence$1: scalaz.Functor[F])scalaz.Free[F,R]
scala> def output[A](a: A) = liftF[({type λ[] = Toy[A]})#λ, Unit](Output(a, ()))
output: [A](a: A)scalaz.Free[[]Toy[A],Unit]
scala> def bell[A] = liftF[({type λ[] = Toy[A]})#λ, Unit](Bell(()))
bell: [A]=> scalaz.Free[[]Toy[A],Unit]
scala> def done[A] = liftF[({type λ[] = Toy[A]})#λ, Unit](Done())
done: [A]=> scalaz.Free[[]Toy[A],Unit]

Let's try sequencing the commands:

scala> val subroutine = output('A')
subroutine: scalaz.Free[[]Toy[Char],Unit] = Suspend(Output(A,Return(())))
scala> val program = for {
         _ <- subroutine
         _ <- bell[Char]
         _ <- done[Char]
       } yield ()
program: scalaz.Free[[]Toy[Char],Unit] = Gosub(Suspend(Output(A,Return(()))),<function1>)

The showProgram doesn't quite work as is for this Free. See the definition of flatMap:

  final def flatMap[B](f: A => Free[S, B]): Free[S, B] = this match {
    case Gosub(a, g) => Gosub(a, (x: Any) => Gosub(g(x), f))
    case a           => Gosub(a, f)

Instead of recalculating a new Return or Suspend it's just creating Gosub structure. There's resume method that evaluates Gosub and returns \/, so using that we can implement showProgram as:

scala> def showProgram[A: Show, R: Show](p: Free[({type λ[] = Toy[A]})#λ, R]): String =
           case Output(a: A, next: Free[({type λ[] = Toy[A]})#λ, R]) =>
             "output " + Show[A].shows(a) + "\n" + showProgram(next)
           case Bell(next: Free[({type λ[] = Toy[A]})#λ, R]) =>
             "bell " + "\n" + showProgram(next)
           case d: Done[A] =>
         { r: R => "return " + Show[R].shows(r) + "\n" }) 
showProgram: [A, R](p: scalaz.Free[[]Toy[A],R])(implicit evidence$1: scalaz.Show[A], implicit evidence$2: scalaz.Show[R])String
scala> showProgram(program)
res101: String = 
"output A

Here's the pretty printer:

scala> def pretty[A: Show, R: Show](p: Free[({type λ[] = Toy[A]})#λ, R]) = print(showProgram(p))
pretty: [A, R](p: scalaz.Free[[]Toy[A],R])(implicit evidence$1: scalaz.Show[A], implicit evidence$2: scalaz.Show[R])Unit
scala> pretty(output('A'))
output A
return ()
scala> pretty(output('A') >>= { _ => done[Char]})
output A

Let's skip to part 2.

Free monads part 2


data Free f r = Free (f (Free f r)) | Pure r
data List a   = Cons  a (List a  )  | Nil

In other words, we can think of a free monad as just being a list of functors. The Free constructor behaves like a Cons, prepending a functor to the list, and the Pure constructor behaves like Nil, representing an empty list (i.e. no functors).

And here's part 3.

Free monads part 3


The free monad is the interpreter's best friend. Free monads "free the interpreter" as much as possible while still maintaining the bare minimum necessary to form a monad.

On the flip side, from the program writer's point of view, free monads do not give anything but being sequential. The interpreter needs to provide some run function to make it useful. The point, I think, is that given a data structure that satisfies Functor, Free provides minimal monads automatically.

Another way of looking at it is that Free monad provides a way of building a syntax tree given a container.

Stackless Scala with Free Monads

Now that we have general understanding of Free monads, let's watch Rúnar's presentation from Scala Days 2012: Stackless Scala With Free Monads. I recommend watching the talk before reading the paper, but it's easier to quote the paper version Stackless Scala With Free Monads.

Rúnar starts out with a code that uses State monad to zip a list with index. It blows the stack when the list is larger than the stack limit. Then he introduces tranpoline, which is a single loop that drives the entire program.

sealed trait Trampoline [+ A] {
  final def runT : A =
    this match {
      case More (k) => k().runT
      case Done (v) => v
case class More[+A](k: () => Trampoline[A])
  extends Trampoline[A]
case class Done [+A](result: A)
  extends Trampoline [A]

In the above code, Function0 k is used as a thunk for the next step.

To extend its usage for State monad, he then reifies flatMap into a data structure called FlatMap:

case class FlatMap [A,+B](
  sub: Trampoline [A],
  k: A => Trampoline[B]) extends Trampoline[B]

Next, it is revealed that Trampoline is a free monad of Function0. Here's how it's defined in Scalaz 7:

  type Trampoline[+A] = Free[Function0, A]

Free monads

In addition, Rúnar introduces several data structures that can form useful free monad:

type Pair[+A] = (A, A)
type BinTree[+A] = Free[Pair, A]
type Tree[+A] = Free[List, A]
type FreeMonoid[+A] = Free[({type λ[] = (A,α)})#λ, Unit]
type Trivial[+A] = Unit
type Option[+A] = Free[Trivial, A]

There's also iteratees implementation based on free monads. Finally, he summarizes free monads in nice bullet points:

  • A model for any recursive data type with data at the leaves.
  • A free monad is an expression tree with variables at the leaves and flatMap is variable substitution.


Using Trampoline any program can be transformed into a stackless one. Let's try implementing even and odd from the talk using Scalaz 7's Trampoline. Free object extends FreeFunction which defines a few useful functions for tramplining:

trait FreeFunctions {
  /** Collapse a trampoline to a single step. */
  def reset[A](r: Trampoline[A]): Trampoline[A] = { val a = r.run; return_(a) }
  /** Suspend the given computation in a single step. */
  def return_[S[+_], A](value: => A)(implicit S: Pointed[S]): Free[S, A] =
    Suspend[S, A](S.point(Return[S, A](value)))
  def suspend[S[+_], A](value: => Free[S, A])(implicit S: Pointed[S]): Free[S, A] =
    Suspend[S, A](S.point(value))
  /** A trampoline step that doesn't do anything. */
  def pause: Trampoline[Unit] =

We can call import Free._ to use these.

scala> import Free._
import Free._
scala> :paste
// Entering paste mode (ctrl-D to finish)
def even[A](ns: List[A]): Trampoline[Boolean] =
  ns match {
    case Nil => return_(true)
    case x :: xs => suspend(odd(xs))
def odd[A](ns: List[A]): Trampoline[Boolean] =
  ns match {
    case Nil => return_(false)
    case x :: xs => suspend(even(xs))
// Exiting paste mode, now interpreting.
even: [A](ns: List[A])scalaz.Free.Trampoline[Boolean]
odd: [A](ns: List[A])scalaz.Free.Trampoline[Boolean]
scala> even(List(1, 2, 3)).run
res118: Boolean = false
scala> even(0 |-> 3000).run
res119: Boolean = false

This was surprisingly simple.

List using Free

Let's try defining "List" using Free.

scala> type FreeMonoid[A] = Free[({type λ[] = (A,α)})#λ, Unit]
defined type alias FreeMonoid
scala> def cons[A](a: A): FreeMonoid[A] = Free.Suspend[({type λ[] = (A,α)})#λ, Unit]((a, Free.Return[({type λ[] = (A,α)})#λ, Unit](())))
cons: [A](a: A)FreeMonoid[A]
scala> cons(1)
res0: FreeMonoid[Int] = Suspend((1,Return(())))
scala> cons(1) >>= {_ => cons(2)}
res1: scalaz.Free[[](Int, α),Unit] = Gosub(Suspend((1,Return(()))),<function1>)

As a way of interpretting the result, let's try converting this to a standard List:

scala> def toList[A](list: FreeMonoid[A]): List[A] =
           { case (x: A, xs: FreeMonoid[A]) => x :: toList(xs) },
           { _ => Nil })
scala> toList(res1)
res4: List[Int] = List(1, 2)

That's it for today.