# Type Classes¶

Distinct from the traditional interfaces from so-called OOP, there is a solution to make abstractions on types(including higher kinded types, the same below) and separate assigning features to types from the type definitions.

One of the goal of abstractions is to make better reuse of codes, which could be acheived through polymorphisms.

Another goal of abstractions is to make programs safer, which could be acheived through static checking.

To meet these expectations, the Type Class then came into being.

A well-known example of polymorphisms with type classes is Functor, the polymorphic function map could be applied on Array, List, Maybe/Option, etc.

val map : forall {f, a, b, Functor f} -> (a -> b) -> f a -> f b
val lst : List<int>
val arr : Array<int>
val m   : Maybe<int>
let f x = x + 1
let _ = map f lst
let _ = map f arr
let _ = map f m


In above codes, List, Array, Maybe are all Functor s.

The Functor is not a type or type constructor. In my point of view, a type class $$A$$ could be taken as a set of attributes $$\{A_1, A_2, \cdots \}$$ that could be used to describe types, and if we say type $$a$$ is an instance of type class $$A$$, it’s the same to say that $$a$$ has a set of attributes $$\{A_1, A_2, \cdots \}$$. These attributes can be leveraged for so-called instance resolution, which specializes the implementation/instance of a polymorphic function on its callsite.

Given a custom implementation of Functor and its instance for List,

type List = [] # avoid confusing stuffs for newbies.

class Functor f where
map :: (a -> b) -> f a -> f b

instance Functor (List)
map :: (a -> b) -> List f -> List b
map f = \case
[]   -> []
x:xs -> f x : map f xs


Let’s see how to perform instance resolution on the callsites of map .

map (+1) [1, 2, 3]

1. map :: Functor f => (a -> b) -> f a -> f b
2. [1, 2, 3] :: Num a => List a
3. (+)       :: Num a => a -> a -> a
4. 1         :: Num a => a

5. for (3), (4),
(+1)     :: Num a => a -> a

6. for (1), (2)
f = List,
now look up the instance (Functor List),
find out the corresponding map function.

map :: (a -> b) -> f a -> f b,
where f = List, a = Num a => a

7. for (6), (5),

a -> b ~ Num a => a -> a
b :: Num a => a
(+1) :: Num a => a -> a

p.s: ~ means unify

8. as a result,

map (+1) [1, 2, 3] :: Num a => List a


If we make the instance Functor A, then we can use the polymorphic map function on type A.

Something deserved to be note here is, although the traditional interfaces from OOP can provide polymorphisms, it’s much weaker when it comes to static checking. Type classes reach polymorphisms without casting objects, while if you want to use methods of some OOP interface, an unnecessary cast is always required.

For type classes could be leveraged to implement full-featured interfaces and the real(not the emulated) type classes can be faster than interfaces(type classes avoid some redundant runtime costs), we can safely make the conclusion that type classes are superior to OOP interfaces.

## About Separation of Type Definitions and Data Manipulations¶

OOP interfaces strongly couple the definitions with the valid interoperations for a type(for you have to point out which interfaces to be inherited), while type classes provide the freedom upon this aspect.

For instance, a show method is aimed at representing the objects of some type that implements type class Show with strings.

data S = S
instance Show S where
show S = "oh, it's a S, the unique S!"


In traditional OOP, we have to define toString/ToString/__str__ methods exactly when defining the types, while languages with type classes, like Rust and Haskell, would allow you to define it somewhere more proper. Something that is super advanced is, you can make show method qualified in current workload, and allow other implementations of show outside the qualified scope.

This extremely enhanced the extensibility and enabled thorough uncoupling without any mental burden.

1. F# doesn’t support statically resolved type parameters with type extensions, as a consequence, although it’s feasible for F# to implement ad-hoc polymorphisms, but in terms of some built-in datatypes and primitive types like int, List, Array, etc., it’s definitely impossible. A wrapper is always required, and severe performance issues could be caused.
2. Let’s focus on the show again. The common method sprintf is already defined and works with some existed protocols which should been ensured when definining the your data types. The way to organize your codes is then fixed, of course the way to sprintf a datatype is then fixed, too.
[<StructuredFormatDisplay("{str}")>] // This must be given here to make custom format method.