Type members are [almost] type parameters

This is the first of a series of articles on “Type Parameters and Type Members”.

Type members like Member

class Blah {
  type Member

and parameters like Param

class Blah2[Param]

have more similarities than differences. The choice of which to use for a given situation is usually a matter of convenience. In brief, a rule of thumb: a type parameter is usually more convenient and harder to screw up, but if you intend to use it existentially in most cases, changing it to a member is probably better.

Here, and in later posts, we will discuss what on earth that means, among other things. In this series of articles on Type Parameters and Type Members, I want to tackle a variety of Scala types that look very different, but are really talking about the same thing, or almost.

Two lists, all alike

To illustrate, let’s see two versions of the functional list. Typically, it isn’t used existentially, so the usual choice of parameter over member fits our rule of thumb above. It’s instructive anyway, so let’s see it.

sealed abstract class PList[T]
final case class PNil[T]() extends PList[T]
final case class PCons[T](head: T, tail: PList[T]) extends PList[T]

sealed abstract class MList {self =>
  type T
  def uncons: Option[MCons {type T = self.T}]
sealed abstract class MNil extends MList {
  def uncons = None
sealed abstract class MCons extends MList {self =>
  val head: T
  val tail: MList {type T = self.T}
  def uncons = Some(self: MCons {type T = self.T})

We’re not quite done; we’re missing a way to make MNils and MConses, which PNil and PCons have already provided for themselves, by virtue of being case classes. But it’s already pretty clear that a type parameter is a more straightforward way to define this particular data type.

The instance creation takes just a bit more scaffolding for our examples:

def MNil[T0](): MNil {type T = T0} =
  new MNil {
    type T = T0

def MCons[T0](hd: T0, tl: MList {type T = T0})
  : MCons {type T = T0} =
  new MCons {
    type T = T0
    val head = hd
    val tail = tl

Why all the {type T = ...}?

After all, isn’t the virtue of type members that we don’t have to pass the type around everywhere?

Let’s see what happens when we attempt to apply that theory. Suppose we remove only one of the refinements above, as these {...} rainclouds at the type level are called. Let’s remove the one in val tail, so class MCons looks like this:

sealed abstract class MCons extends MList {self =>
  val head: T
  val tail: MList

Now let us put a couple members into the list, and add them together.

scala> val nums = MCons(2, MCons(3, MNil())): MCons{type T = Int}
nums: tmtp.MCons{type T = Int} = tmtp.MList$$anon$2@3c649f69

scala> nums.head
res1: nums.T = 2

scala> res1 + res1
res2: Int = 4

res3: Option[nums.tail.T] = Some(3)

scala> - res2)
<console>:21: error: value - is not a member of nums.tail.T - res2)

When we took the refinement off of tail, we eliminated any evidence about what its type T might be. We only know that it must be some type. That’s what existential means.

In terms of type parameters, MList is like PList[_], and MList {type T = Int} is like PList[Int]. For the former, we say that the member, or parameter, is existential.

When is existential OK?

Despite the limitation implied by the error above, there are useful functions that can be written on the existential version. Here’s one of the simplest:

def mlength(xs: MList): Int =
  xs.uncons match {
    case None => 0
    case Some(c) => 1 + mlength(c.tail)

For the type parameter equivalent, the parameter on the argument is usually carried out or lifted to the function, like so:

def plengthT[T](xs: PList[T]): Int =
  xs match {
    case PNil() => 0
    case PCons(_, t) => 1 + plengthT(t)

By the conversion rules above, though, we should be able to write an existential equivalent of mlength for PList, and indeed we can:

def plengthE(xs: PList[_]): Int =
  xs match {
    case PNil() => 0
    case PCons(_, t) => 1 + plengthE(t)

There’s another simple rule we can follow when determining whether we can rewrite in an existential manner.

  1. When a type parameter appears only in one argument, and
  2. appears nowhere in the result type,

we should always, ideally, be able to write the function in an existential manner. (We will discuss why it’s only “ideally” in the next article.)

You can demonstrate this to yourself by having the parameterized variant (e.g. plengthT) call the existential variant (e.g. plengthE), and, voilà, it compiles, so it must be right.

This hints at what is usually, though not always, an advantage for type parameters: you have to ask for an existential, rather than silently getting one just because you forgot a refinement. We will discuss what happens when you forget one in a later post.

Equivalence as a learning tool

Scala is large enough that very few understand all of it. Moreover, there are many aspects of it that are poorly understood in general.

So why focus on how different features are similar? When we understand one area of Scala well, but another one poorly, we can form sensible ideas about the latter by drawing analogies with the former. This is how we solve problems with computers in general: we create an informal model in our heads, which we translate to a mathematical statement that a program can interpret, and it gives back a result that we can translate back to our informal model.

My guess is that type parameters are much better understood than type members, but that existentials via type members are better understood than existentials introduced by _ or forSome, though I’d wager that neither form of existential is particularly well understood.

By knowing about equivalences and being able to discover more, you have a powerful tool for understanding unfamiliar aspects of Scala: just translate the problem back to what you know and think about what it means there, because the conclusion will still hold when you translate it forward. (Category theorists, eat your hearts out.)

In this vein, we will next generalize the above rule about existential methods, discovering a simple tool for determining whether two method types in general are equivalent, whereby things you know about one easily carry over to the other. We will also explore methods that cannot be written in the existential style, at least under Scala’s restrictions.

That all happens in the next part, “When are two methods alike?”.

This article was tested with Scala 2.11.7.


Unless otherwise noted, all content is licensed under a Creative Commons Attribution 3.0 Unported License.

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