I actually think that return type polymorphism is one of the best features of type classes. After having used it for a while, it is sometimes hard for me to go back to OOP style modeling where I don't have it.
Consider the encoding of algebra. In Haskell we have a type class Monoid
(ignoring mconcat
)
class Monoid a where
mempty :: a
mappend :: a -> a -> a
How could we encode this as an interface in an OO language? The short answer is we can't. That's because the type of mempty
is (Monoid a) => a
aka, return type polymorphism. Having the ability to model algebra is incredibly useful IMO.*
You start your post with the complaint about "Referential Transparency." This raises an important point: Haskell is a value oriented language. So expressions like read 3
don't have to be understood as things that compute values, they can also be understood as values. What this means is that the real issue is not return type polymorphism: it is values with polymorphic type ([]
and Nothing
). If the language should have these, then it really has to have polymorphic return types for consistency.
Should we be able to say []
is of type forall a. [a]
? I think so. These features are very useful, and they make the language much simpler.
If Haskell had subtype polymorphism []
could be a subtype for all [a]
. The problem is, that I don't know of a way of encoding that without having the type of the empty list be polymorphic. Consider how it would be done in Scala (it is shorter than doing it in the canonical statically typed OOP language, Java)
abstract class List[A]
case class Nil[A] extends List[A]
case class Cons[A](h: A. t: List[A]) extends List[A]
Even here, Nil()
is an object of type Nil[A]
**
Another advantage of return type polymorphism is that it makes the Curry-Howard embedding much simpler.
Consider the following logical theorems:
t1 = forall P. forall Q. P -> P or Q
t2 = forall P. forall Q. P -> Q or P
We can trivially capture these as theorems in Haskell:
data Either a b = Left a | Right b
t1 :: a -> Either a b
t1 = Left
t2 :: a -> Either b a
t2 = Right
To sum up: I like return type polymorphism, and only think it breaks referential transparency if you have a limited notion of values (although this is less compelling in the ad hoc type class case). On the other hand, I do find your points about MR and type defaulting compelling.
*. In the comments ysdx points out this isn't strictly true: we could re-implement type classes by modeling the algebra as another type. Like the java:
abstract class Monoid<M>{
abstract M empty();
abstract M append(M m1, M m2);
}
You then have to pass objects of this type around with you. Scala has a notion of implicit parameters which avoids some, but in my experience not all, of the overhead of explicitly managing these things. Putting your utility methods (factory methods, binary methods, etc) on a separate F-bounded type turns out to be an incredibly nice way of managing things in an OO language that has support for generics. That said, I'm not sure I would have groked this pattern if I didn't have experience modeling things with typeclasses, and I'm not sure other people will.
It also has limitations, out of the box there is no way to get an object that implements the typeclass for an arbitrary type. You have to either pass the values explicitly, use something like Scala's implicits, or use some form of dependency injection technology. Life gets ugly. On the other hand, it is nice that you can have multiple implementations for the same type. Something can be a Monoid in multiple ways. Also, carrying around these structures separately has IMO a more mathematically modern, constructive, feel to it. So, although I still generally prefer the Haskell way of doing this, I probably overstated my case.
Typeclasses with return type polymorphism makes this kind of thing easy to handle. That doesn't meen it is the best way to do it.
**. Jörg W Mittag points out this isn't really the canonical way of doing this in Scala. Instead, we would follow the standard library with something more like:
abstract class List[+A] ...
case class Cons[A](head: A, tail: List[A]) extends List[A] ...
case object Nil extends List[Nothing] ...
This takes advantage of Scala's support for bottom types, as well as covariant type paramaters. So, Nil
is of type Nil
not Nil[A]
. At this point we are pretty far from Haskell, but it is interesting to note how Haskell represents the bottom type
undefined :: forall a. a
That is, it isn't the subtype of all types, it is polymorphically(sp) a member of all types.
Yet more return type polymorphism.
Haskell doesn't quite have full dependent types, although it can get very close with extensions like DataKinds
and TypeFamilies
. The issue at the moment, as far as I know, is that value-level Haskell has explicit bottoms but type-level Haskell does not.
This doesn't stop you from parametrizing types over other types, including the DataKind
-lifting of values. As of GHC 7.6, and with DataKinds
enabled, you can use type-level naturals and strings, as well as type-level tuples, type-level lists, and the type-level liftings of any (non-higher-kinded, non-generalized, non-constrained) algebraic data types, which is similar to (but much more general than) C++'s ability to use integers in templates.
Best Answer
Probably your confusion comes from the fact that you are used to eager evaluation, whereas Haskell uses lazy evaluation.
For example, if you were to use the definition
to evaluate the expression
repeat' 10
eagerly, then you would getand this would loop forever.
With lazy evaluation it is different. If you have the expression
repeat' 10
in a certain context, this is not evaluated until the result ofrepeat' 10
is required.As soon as you take values from the list, the above steps are executed, but only as many of them get executed as requested.
So, in Haskell applying your function to some value does not create an infinite data structure that is completely loaded in memory at some point in time: this is impossible because there is only a finite amount of memory and a computation that terminates can only take a finite amount of time. It rather creates a program from which you can pull any finite number of elements, i.e. any finite prefix of the infinite list.
Note that the finite prefix is not represented as a plain list
but as a term like
So, suppose you want to compute with a finite list, e.g.
take 2 [1, 2, 3]
:Now, the same but with your infinite list: