learning Scalaz: day 2


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

Yesterday we reviewed a few basic typeclasses from Scalaz like Equal by using Learn You a Haskell for Great Good as the guide. We also created our own CanTruthy typeclass.



And now, we're going to take a look at the Functor typeclass, which is basically for things that can be mapped over.

Like the book let's look how it's implemented:

trait Functor[F[_]]  { self =>
  /** Lift `f` into `F` and apply to `F[A]`. */
  def map[A, B](fa: F[A])(f: A => B): F[B]

Here are the injected operators it enables:

trait FunctorOps[F[_],A] extends Ops[F[A]] {
  implicit def F: Functor[F]
  import Leibniz.===
  final def map[B](f: A => B): F[B] = F.map(self)(f)

So this defines map method, which accepts a function A => B and returns F[B]. We are quite familiar with map method for collections:

scala> List(1, 2, 3) map {_ + 1}
res15: List[Int] = List(2, 3, 4)

Scalaz defines Functor instances for Tuples.

scala> (1, 2, 3) map {_ + 1}
res28: (Int, Int, Int) = (1,2,4)

Function as Functors

Scalaz also defines Functor instance for Function1.

scala> ((x: Int) => x + 1) map {_ * 7}
res30: Int => Int = <function1>
scala> res30(3)
res31: Int = 28

This is interesting. Basically map gives us a way to compose functions, except the order is in reverse from f compose g! No wonder Scalaz provides as an alias of map. Another way of looking at Function1 is that it's an infinite map from the domain to the range. Now let's skip the input and output stuff and go to Functors, Applicative Functors and Monoids.

How are functions functors?

What does the type fmap :: (a -> b) -> (r -> a) -> (r -> b) for this instance tell us? Well, we see that it takes a function from a to b and a function from r to a and returns a function from r to b. Does this remind you of anything? Yes! Function composition!

Oh man, LYAHFGG came to the same conclusion as I did about the function composition. But wait..

ghci> fmap (*3) (+100) 1
ghci> (*3) . (+100) $ 1  

In Haskell, the fmap seems to be working as the same order as f compose g. Let's check in Scala using the same numbers:

scala> (((_: Int) * 3) map {_ + 100}) (1)
res40: Int = 103

Something is not right. Let's compare the declaration of fmap and Scalaz's map operator:

fmap :: (a -> b) -> f a -> f b

and here's Scalaz:

final def map[B](f: A => B): F[B] = F.map(self)(f)

So the order is completely different. Since map here's an injected method of F[A], the data structure to be mapped over comes first, then the function comes next. Let's see List:

ghci> fmap (*3) [1, 2, 3]


scala> List(1, 2, 3) map {3*}
res41: List[Int] = List(3, 6, 9)

The order is reversed here too.

[We can think of fmap as] a function that takes a function and returns a new function that's just like the old one, only it takes a functor as a parameter and returns a functor as the result. It takes an a -> b function and returns a function f a -> f b. This is called lifting a function.

ghci> :t fmap (*2)  
fmap (*2) :: (Num a, Functor f) => f a -> f a  
ghci> :t fmap (replicate 3)  
fmap (replicate 3) :: (Functor f) => f a -> f [a]  

Are we going to miss out on this lifting goodness? There are several neat functions under Functor typeclass. One of them is called lift:

scala> Functor[List].lift {(_: Int) * 2}
res45: List[Int] => List[Int] = <function1>
scala> res45(List(3))
res47: List[Int] = List(6)

Functor also enables some operators that overrides the values in the data structure like >|, as, fpair, strengthL, strengthR, and void:

scala> List(1, 2, 3) >| "x"
res47: List[String] = List(x, x, x)
scala> List(1, 2, 3) as "x"
res48: List[String] = List(x, x, x)
scala> List(1, 2, 3).fpair
res49: List[(Int, Int)] = List((1,1), (2,2), (3,3))
scala> List(1, 2, 3).strengthL("x")
res50: List[(String, Int)] = List((x,1), (x,2), (x,3))
scala> List(1, 2, 3).strengthR("x")
res51: List[(Int, String)] = List((1,x), (2,x), (3,x))
scala> List(1, 2, 3).void
res52: List[Unit] = List((), (), ())



So far, when we were mapping functions over functors, we usually mapped functions that take only one parameter. But what happens when we map a function like *, which takes two parameters, over a functor?

scala> List(1, 2, 3, 4) map {(_: Int) * (_:Int)}
<console>:14: error: type mismatch;
 found   : (Int, Int) => Int
 required: Int => ?
              List(1, 2, 3, 4) map {(_: Int) * (_:Int)}

Oops. We have to curry this:

scala> List(1, 2, 3, 4) map {(_: Int) * (_:Int)}.curried
res11: List[Int => Int] = List(<function1>, <function1>, <function1>, <function1>)
scala> res11 map {_(9)}
res12: List[Int] = List(9, 18, 27, 36)


Meet the Applicative typeclass. It lies in the Control.Applicative module and it defines two methods, pure and <*>.

Let's see the contract for Scalaz's Applicative:

trait Applicative[F[_]] extends Apply[F] with Pointed[F] { self =>

So Applicative extends two other typeclasses Pointed and Apply, but itself does not introduce new contract methods. Let's look at Pointed first.



pure should take a value of any type and return an applicative value with that value inside it. ... A better way of thinking about pure would be to say that it takes a value and puts it in some sort of default (or pure) context—a minimal context that still yields that value.

trait Pointed[F[_]] extends Functor[F] { self =>
  def point[A](a: => A): F[A]
  /** alias for `point` */
  def pure[A](a: => A): F[A] = point(a)

Scalaz likes the name point instead of pure, and it seems like it's basically a constructor that takes value A and returns F[A]. It doesn't introduce an operator, but it intoduces point method and its symbolic alias η to all data types.

scala> 1.point[List]
res14: List[Int] = List(1)
scala> 1.point[Option]
res15: Option[Int] = Some(1)
scala> 1.point[Option] map {_ + 2}
res16: Option[Int] = Some(3)
scala> 1.point[List] map {_ + 2}
res17: List[Int] = List(3)

I can't really express it in words yet, but there's something cool about the fact that constructor is abstracted out.



You can think of <*> as a sort of a beefed-up fmap. Whereas fmap takes a function and a functor and applies the function inside the functor value, <*> takes a functor that has a function in it and another functor and extracts that function from the first functor and then maps it over the second one.

trait Apply[F[_]] extends Functor[F] { self =>
  def ap[A,B](fa: => F[A])(f: => F[A => B]): F[B]

Using ap, Apply enables <*>, *>, and <* operator.

scala> 9.some <*> {(_: Int) + 3}.some
res20: Option[(Int, Int => Int)] = Some((9,<function1>))

I was hoping for Some(12) here. Scalaz 7.0.0-M3 creates a tuple in Some. I've asked the authors and it looks like it will be changed back to the same behavior as Haskell, Scalaz 6 and Scalaz 7.0.0-M2. Let's run it again using 7.0.0-M2:

scala>  9.some <*> {(_: Int) + 3}.some
res20: Option[Int] = Some(12)

This is much better.

*> and <* are variations that returns only the rhs or lhs.

scala> 1.some <* 2.some
res35: Option[Int] = Some(1)
scala> none <* 2.some
res36: Option[Nothing] = None
scala> 1.some *> 2.some
res38: Option[Int] = Some(2)
scala> none *> 2.some
res39: Option[Int] = None

Option as Apply

Thanks, but what happened to the <*> that can extract functions out of containers, and apply the extracted values to it? We can use <*> in 7.0.0-M2:

scala> 9.some <*> {(_: Int) + 3}.some
res57: Option[Int] = Some(12)
scala> 3.some <*> { 9.some <*> {(_: Int) + (_: Int)}.curried.some }
res58: Option[Int] = Some(12)

Applicative Style

Another thing I found in 7.0.0-M3 is a new notation that extracts values from containers and apply them to a single function:

scala> ^(3.some, 5.some) {_ + _}
res59: Option[Int] = Some(8)
scala> ^(3.some, none: Option[Int]) {_ + _}
res60: Option[Int] = None

This is actually useful because for one-function case, we no longer need to put it into the container. I am guessing that this is why Scalaz 7 does not introduce any operator from Applicative itself. Whatever the case, it seems like we no longer need Pointed or <$>.

The new ^(f1, f2) {...} style is not without the problem though. It doesn't seem to handle Applicatives that takes two type parameters like Function1, Writer, and Validation. There's another way called Applicative Builder, which apparently was the way it worked in Scalaz 6, got deprecated in M3, but will be vindicated again because of ^(f1, f2) {...}'s issues.

Here's how it looks:

scala> (3.some |@| 5.some) {_ + _}
res18: Option[Int] = Some(8)

We will use |@| style for now.

Lists as Apply


Lists (actually the list type constructor, []) are applicative functors. What a surprise!

Let's see if we can use <*> and |@|:

scala> List(1, 2, 3) <*> List((_: Int) * 0, (_: Int) + 100, (x: Int) => x * x)
res61: List[Int] = List(0, 0, 0, 101, 102, 103, 1, 4, 9)
scala> List(3, 4) <*> { List(1, 2) <*> List({(_: Int) + (_: Int)}.curried, {(_: Int) * (_: Int)}.curried) }
res62: List[Int] = List(4, 5, 5, 6, 3, 4, 6, 8)
scala> (List("ha", "heh", "hmm") |@| List("?", "!", ".")) {_ + _}
res63: List[String] = List(ha?, ha!, ha., heh?, heh!, heh., hmm?, hmm!, hmm.)

Zip Lists


However, [(+3),(*2)] <*> [1,2] could also work in such a way that the first function in the left list gets applied to the first value in the right one, the second function gets applied to the second value, and so on. That would result in a list with two values, namely [4,4]. You could look at it as [1 + 3, 2 * 2].

I did not find ZipList equivalent in Scalaz.

Useful functions for Applicatives


Control.Applicative defines a function that's called liftA2, which has a type of

liftA2 :: (Applicative f) => (a -> b -> c) -> f a -> f b -> f c .

There's Apply[F].lift2:

scala> Apply[Option].lift2((_: Int) :: (_: List[Int]))
res66: (Option[Int], Option[List[Int]]) => Option[List[Int]] = <function2>
scala> res66(3.some, List(4).some)
res67: Option[List[Int]] = Some(List(3, 4))


Let's try implementing a function that takes a list of applicatives and returns an applicative that has a list as its result value. We'll call it sequenceA.

sequenceA :: (Applicative f) => [f a] -> f [a]  
sequenceA [] = pure []  
sequenceA (x:xs) = (:) <$> x <*> sequenceA xs  

Let's try implementing this in Scalaz!

scala> def sequenceA[F[_]: Applicative, A](list: List[F[A]]): F[List[A]] = list match {
         case Nil     => (Nil: List[A]).point[F]
         case x :: xs => (x |@| sequenceA(xs)) {_ :: _} 
sequenceA: [F[_], A](list: List[F[A]])(implicit evidence$1: scalaz.Applicative[F])F[List[A]]

Let's test it:

scala> sequenceA(List(1.some, 2.some))
res82: Option[List[Int]] = Some(List(1, 2))
scala> sequenceA(List(3.some, none, 1.some))
res85: Option[List[Int]] = None
scala> sequenceA(List(List(1, 2, 3), List(4, 5, 6)))
res86: List[List[Int]] = List(List(1, 4), List(1, 5), List(1, 6), List(2, 4), List(2, 5), List(2, 6), List(3, 4), List(3, 5), List(3, 6))

We got the right answers. What's interesting here is that we did end up needing Pointed after all, and sequenceA is generic in typeclassy way.

For Function1 with Int fixed example, we have to unfortunately invoke a dark magic.

scala> type Function1Int[A] = ({type l[A]=Function1[Int, A]})#l[A]
defined type alias Function1Int
scala> sequenceA(List((_: Int) + 3, (_: Int) + 2, (_: Int) + 1): List[Function1Int[Int]])
res1: Int => List[Int] = <function1>
scala> res1(3)
res2: List[Int] = List(6, 5, 4)

It took us a while, but I am glad we got this far. We'll pick it up from here later.