When we create a type class, we usually assume that its functions must obey some properties. Thus we have the Monoid and Monad laws for their respective type classes. But, what if there is some law, like associativity, that I want to specify that multiple classes either may or may not obey that law? Is there a way to do that in Haskell's type system? Is this sort of type classes for type classes idea even feasible in practice?
Here's a motivating example from algebra:
class Addition x where
add :: x -> x -> x
class Multiplication x where
mult :: x -> x -> x
instance Addition Int where
add = (+)
instance Multiplication Int where
add = (*)
Now, if I want to specify that addition over Int's is associative and commutative, I can create the classes and instances:
class (Addition x) => AssociativeAddition x where
class (Addition x) => CommutativeAddition x where
instance AssociativeAddition Int where
instance CommutativeAddition Int where
But this is cumbersome because I have to create all possible combinations for all classes. I can't just create Associative and Commutative classes, because what if addition is commutative, but multiplication is not (like in matrices)?
What I would like to be able to do is say something like:
class Associative x where
instance (Associative Addition, Commutative Addition) => Addition Int where
add = (+)
instance (Commutative Multiplication) => Multiplication Int where
mult = (*)
Can this be done?
(Haskell's abstract algebra packages, like algebra and constructive-algebra, do not currently do this, so I'm guessing not. But why not?)
You actually can do this with some recent GHC extensions:
{-# LANGUAGE ConstraintKinds, KindSignatures, MultiParamTypeClasses #-}
import GHC.Exts (Constraint)
class Addition (a :: *) where
plus :: a -> a -> a
instance Addition Integer where
plus = (+)
class (c a) => Commutative (a :: *) (c :: * -> Constraint) where
op :: a -> a -> a
instance Commutative Integer Addition where
op = plus
Related
With respect Listing 1, it is required that the type level axiom
(t a) = (t (getUI(t a)))
should derivable as a theorem for every specific type class instance.
Does the compilation of the test function prove the type level axiom holds for the particular types in the program? Does the compilation provide an example of Theorems for free!?
Listing 1
{-# LANGUAGE MultiParamTypeClasses #-}
data Continuant a = Continuant a deriving (Show,Eq)
class UI a where
instance UI Int where
class Category t a where
getUI :: (UI a) => (t a) -> a
instance Category Continuant Int where
getUI (Continuant a) = a
-- axiom (t a) = (t (getUI(t a))) holds for given types?
test :: Int -> Bool
test x = (Continuant x) == (Continuant (getUI (Continuant x)))
Additional Context
The code is based on a paper where it is stated:
For all implementations of getUI one may require that the axiom (t a)
= (t (getUI (t a))) holds. This must be proven to hold for every specific type class instance declaration. For finite types this can be
done by a program that enumerates all possibilities. For infinite
types this must be done manually via proofs by induction.
Listing 1 was my attempt at a proof. In the light of Solution 1, perhaps I mistakenly thought this required Theorems for free!
No, the fact that it's a class gives you far too much leeway for the type alone to guarantee that axiom. For example, the following alternate instance typechecks but violates your axiom:
instance Category Continuant Int where
getUI _ = 42
(Being completely explicit, our adversary could choose for example t=Continuant and a=6*9 to violate the axiom.) This abuses the fact that the class instantiator gets to choose the contained type. We can remove that ability by removing that argument to the class:
class Category t where
getUI :: UI a => t a -> a
Alas, even this is not enough. We can write
data Pair a = Pair a a
and then the free theorem tells us that for instance Category Pair, we must write one of the following two definitions:
getUI (Pair x y) = x
-- OR
getUI (Pair x y) = y
Whichever we choose, our adversary can choose a t which shows us that our axiom is wrong.
Our choice Adversary's choice
getUI (Pair x y) = x t y = Pair 42 y; a = 6*9
getUI (Pair x y) = y t x = Pair x 42; a = 6*9
Okay, this abuses the fact that the class instantiator gets to choose t. What if we removed that ability...?
class Category where
getUI :: UI a => t a -> a
This restricts the instantiator of Category quite a lot. Too much, in fact: getUI can't be implemented except as an infinite loop or the like.
I suspect it will be very difficult to encode the axiom you wish for as a type which can only be inhabited by things that satisfy it.
A type constructor produces a type given a type. For example, the Maybe constructor
data Maybe a = Nothing | Just a
could be a given a concrete type, like Char, and give a concrete type, like Maybe Char. In terms of kinds, one has
GHCI> :k Maybe
Maybe :: * -> *
My question: Is it possible to define a type constructor that yields a concrete type given a Char, say? Put another way, is it possible to mix kinds and types in the type signature of a type constructor? Something like
GHCI> :k my_type
my_type :: Char -> * -> *
Can a Haskell type constructor have non-type parameters?
Let's unpack what you mean by type parameter. The word type has (at least) two potential meanings: do you mean type in the narrow sense of things of kind *, or in the broader sense of things at the type level? We can't (yet) use values in types, but modern GHC features a very rich kind language, allowing us to use a wide range of things other than concrete types as type parameters.
Higher-Kinded Types
Type constructors in Haskell have always admitted non-* parameters. For example, the encoding of the fixed point of a functor works in plain old Haskell 98:
newtype Fix f = Fix { unFix :: f (Fix f) }
ghci> :k Fix
Fix :: (* -> *) -> *
Fix is parameterised by a functor of kind * -> *, not a type of kind *.
Beyond * and ->
The DataKinds extension enriches GHC's kind system with user-declared kinds, so kinds may be built of pieces other than * and ->. It works by promoting all data declarations to the kind level. That is to say, a data declaration like
data Nat = Z | S Nat -- natural numbers
introduces a kind Nat and type constructors Z :: Nat and S :: Nat -> Nat, as well as the usual type and value constructors. This allows you to write datatypes parameterised by type-level data, such as the customary vector type, which is a linked list indexed by its length.
data Vec n a where
Nil :: Vec Z a
(:>) :: a -> Vec n a -> Vec (S n) a
ghci> :k Vec
Vec :: Nat -> * -> *
There's a related extension called ConstraintKinds, which frees constraints like Ord a from the yoke of the "fat arrow" =>, allowing them to roam across the landscape of the type system as nature intended. Kmett has used this power to build a category of constraints, with the newtype (:-) :: Constraint -> Constraint -> * denoting "entailment": a value of type c :- d is a proof that if c holds then d also holds. For example, we can prove that Ord a implies Eq [a] for all a:
ordToEqList :: Ord a :- Eq [a]
ordToEqList = Sub Dict
Life after forall
However, Haskell currently maintains a strict separation between the type level and the value level. Things at the type level are always erased before the program runs, (almost) always inferrable, invisible in expressions, and (dependently) quantified by forall. If your application requires something more flexible, such as dependent quantification over runtime data, then you have to manually simulate it using a singleton encoding.
For example, the specification of split says it chops a vector at a certain length according to its (runtime!) argument. The type of the output vector depends on the value of split's argument. We'd like to write this...
split :: (n :: Nat) -> Vec (n :+: m) a -> (Vec n a, Vec m a)
... where I'm using the type function (:+:) :: Nat -> Nat -> Nat, which stands for addition of type-level naturals, to ensure that the input vector is at least as long as n...
type family n :+: m where
Z :+: m = m
S n :+: m = S (n :+: m)
... but Haskell won't allow that declaration of split! There aren't any values of type Z or S n; only types of kind * contain values. We can't access n at runtime directly, but we can use a GADT which we can pattern-match on to learn what the type-level n is:
data Natty n where
Zy :: Natty Z
Sy :: Natty n -> Natty (S n)
ghci> :k Natty
Natty :: Nat -> *
Natty is called a singleton, because for a given (well-defined) n there is only one (well-defined) value of type Natty n. We can use Natty n as a run-time stand-in for n.
split :: Natty n -> Vec (n :+: m) a -> (Vec n a, Vec m a)
split Zy xs = (Nil, xs)
split (Sy n) (x :> xs) =
let (ys, zs) = split n xs
in (x :> ys, zs)
Anyway, the point is that values - runtime data - can't appear in types. It's pretty tedious to duplicate the definition of Nat in singleton form (and things get worse if you want the compiler to infer such values); dependently-typed languages like Agda, Idris, or a future Haskell escape the tyranny of strictly separating types from values and give us a range of expressive quantifiers. You're able to use an honest-to-goodness Nat as split's runtime argument and mention its value dependently in the return type.
#pigworker has written extensively about the unsuitability of Haskell's strict separation between types and values for modern dependently-typed programming. See, for example, the Hasochism paper, or his talk on the unexamined assumptions that have been drummed into us by four decades of Hindley-Milner-style programming.
Dependent Kinds
Finally, for what it's worth, with TypeInType modern GHC unifies types and kinds, allowing us to talk about kind variables using the same tools that we use to talk about type variables. In a previous post about session types I made use of TypeInType to define a kind for tagged type-level sequences of types:
infixr 5 :!, :?
data Session = Type :! Session -- Type is a synonym for *
| Type :? Session
| E
I'd recommend #Benjamin Hodgson's answer and the references he gives to see how to make this sort of thing useful. But, to answer your question more directly, using several extensions (DataKinds, KindSignatures, and GADTs), you can define types that are parameterized on (certain) concrete types.
For example, here's one parameterized on the concrete Bool datatype:
{-# LANGUAGE DataKinds, KindSignatures, GADTs #-}
{-# LANGUAGE FlexibleInstances #-}
module FlaggedType where
-- The single quotes below are optional. They serve to notify
-- GHC that we are using the type-level constructors lifted from
-- data constructors rather than types of the same name (and are
-- only necessary where there's some kind of ambiguity otherwise).
data Flagged :: Bool -> * -> * where
Truish :: a -> Flagged 'True a
Falsish :: a -> Flagged 'False a
-- separate instances, just as if they were different types
-- (which they are)
instance (Show a) => Show (Flagged 'False a) where
show (Falsish x) = show x
instance (Show a) => Show (Flagged 'True a) where
show (Truish x) = show x ++ "*"
-- these lists have types as indicated
x = [Truish 1, Truish 2, Truish 3] -- :: Flagged 'True Integer
y = [Falsish "a", Falsish "b", Falsish "c"] -- :: Flagged 'False String
-- this won't typecheck: it's just like [1,2,"abc"]
z = [Truish 1, Truish 2, Falsish 3] -- won't typecheck
Note that this isn't much different from defining two completely separate types:
data FlaggedTrue a = Truish a
data FlaggedFalse a = Falsish a
In fact, I'm hard pressed to think of any advantage Flagged has over defining two separate types, except if you have a bar bet with someone that you can write useful Haskell code without type classes. For example, you can write:
getInt :: Flagged a Int -> Int
getInt (Truish z) = z -- same polymorphic function...
getInt (Falsish z) = z -- ...defined on two separate types
Maybe someone else can think of some other advantages.
Anyway, I believe that parameterizing types with concrete values really only becomes useful when the concrete type is sufficient "rich" that you can use it to leverage the type checker, as in Benjamin's examples.
As #user2407038 noted, most interesting primitive types, like Ints, Chars, Strings and so on can't be used this way. Interestingly enough, though, you can use literal positive integers and strings as type parameters, but they are treated as Nats and Symbols (as defined in GHC.TypeLits) respectively.
So something like this is possible:
import GHC.TypeLits
data Tagged :: Symbol -> Nat -> * -> * where
One :: a -> Tagged "one" 1 a
Two :: a -> Tagged "two" 2 a
Three :: a -> Tagged "three" 3 a
Look at using Generalized Algebraic Data Types (GADTS), which enable you to define concrete outputs based on input type, e.g.
data CustomMaybe a where
MaybeChar :: Maybe a -> CustomMaybe Char
MaybeString :: Maybe a > CustomMaybe String
MaybeBool :: Maybe a -> CustomMaybe Bool
exampleFunction :: CustomMaybe a -> a
exampleFunction (MaybeChar maybe) = 'e'
exampleFunction (MaybeString maybe) = True //Compile error
main = do
print $ exampleFunction (MaybeChar $ Just 10)
To a similar effect, RankNTypes can allow the implementation of similar behaviour:
exampleFunctionOne :: a -> a
exampleFunctionOne el = el
type PolyType = forall a. a -> a
exampleFuntionTwo :: PolyType -> Int
exampleFunctionTwo func = func 20
exampleFunctionTwo func = func "Hello" --Compiler error, PolyType being forced to return 'Int'
main = do
print $ exampleFunctionTwo exampleFunctionOne
The PolyType definition allows you to insert the polymorphic function within exampleFunctionTwo and force its output to be 'Int'.
No. Haskell doesn't have dependent types (yet). See https://typesandkinds.wordpress.com/2016/07/24/dependent-types-in-haskell-progress-report/ for some discussion of when it may.
In the meantime, you can get behavior like this in Agda, Idris, and Cayenne.
I'm covering polymorphism and I'm trying to see the practical uses of such a feature.
My basic understanding of Rank 2 is:
type MyType = ∀ a. a -> a
subFunction :: a -> a
subFunction el = el
mainFunction :: MyType -> Int
mainFunction func = func 3
I understand that this is allowing the user to use a polymorphic function (subFunction) inside mainFunction and strictly specify it's output (Int). This seems very similar to GADT's:
data Example a where
ExampleInt :: Int -> Example Int
ExampleBool :: Bool -> Example Bool
1) Given the above, is my understanding of Rank 2 polymorphism correct?
2) What are the general situations where Rank 2 polymorphism can be used, as opposed to GADT's, for example?
If you pass a polymorphic function as and argument to a Rank2-polymorphic function, you're essentially passing not just one function but a whole family of functions – for all possible types that fulfill the constraints.
Typically, those forall quantifiers come with a class constraint. For example, I might wish to do number arithmetic with two different types simultaneously (for comparing precision or whatever).
data FloatCompare = FloatCompare {
singlePrecision :: Float
, doublePrecision :: Double
}
Now I might want to modify those numbers through some maths operation. Something like
modifyFloat :: (Num -> Num) -> FloatCompare -> FloatCompare
But Num is not a type, only a type class. I could of course pass a function that would modify any particular number type, but I couldn't use that to modify both a Float and a Double value, at least not without some ugly (and possibly lossy) converting back and forth.
Solution: Rank-2 polymorphism!
modifyFloat :: (∀ n . Num n => n -> n) -> FloatCompare -> FloatCompare
mofidyFloat f (FloatCompare single double)
= FloatCompare (f single) (f double)
The best single example of how this is useful in practice are probably lenses. A lens is a “smart accessor function” to a field in some larger data structure. It allows you to access fields, update them, gather results... while at the same time composing in a very simple way. How it works: Rank2-polymorphism; every lens is polymorphic, with the different instantiations corresponding to the “getter” / “setter” aspects, respectively.
The go-to example of an application of rank-2 types is runST as Benjamin Hodgson mentioned in the comments. This is a rather good example and there are a variety of examples using the same trick. For example, branding to maintain abstract data type invariants across multiple types, avoiding confusion of differentials in ad, a region-based version of ST.
But I'd actually like to talk about how Haskell programmers are implicitly using rank-2 types all the time. Every type class whose methods have universally quantified types desugars to a dictionary with a field with a rank-2 type. In practice, this is virtually always a higher-kinded type class* like Functor or Monad. I'll use a simplified version of Alternative as an example. The class declaration is:
class Alternative f where
empty :: f a
(<|>) :: f a -> f a -> f a
The dictionary representing this class would be:
data AlternativeDict f = AlternativeDict {
empty :: forall a. f a,
(<|>) :: forall a. f a -> f a -> f a }
Sometimes such an encoding is nice as it allows one to use different "instances" for the same type, perhaps only locally. For example, Maybe has two obvious instances of Alternative depending on whether Just a <|> Just b is Just a or Just b. Languages without type classes, such as Scala, do indeed use this encoding.
To connect to leftaroundabout's reference to lenses, you can view the hierarchy there as a hierarchy of type classes and the lens combinators as simply tools for explicitly building the relevant type class dictionaries. Of course, the reason it isn't actually a hierarchy of type classes is that we usually will have multiple "instances" for the same type. E.g. _head and _head . _tail are both "instances" of Traversal' s a.
* A higher-kinded type class doesn't necessarily lead to this, and it can happen for a type class of kind *. For example:
-- Higher-kinded but doesn't require universal quantification.
class Sum c where
sum :: c Int -> Int
-- Not higher-kinded but does require universal quantification.
class Length l where
length :: [a] -> l
If you are using modules in Haskell, you are already using Rank-2 types. Theoretically speaking, modules are records with rank-2 type properties.
For example, the Foo module below in Haskell ...
module Foo(id) where
id :: forall a. a -> a
id x = x
import qualified Foo
main = do
putStrLn (Foo.id "hello")
return ()
... can actually be thought as a record as follows:
type FooType = FooType {
id :: forall a. a -> a
}
Foo :: FooType
Foo = Foo {
id = \x -> x
}
P/S (unrelated this question): from a language design perspective, if you are going to support module system, then you might as well support higher-rank types (i.e. allow arbitrary quantification of type variables on any level) to reduce duplication of efforts (i.e. type checking a module should be almost the same as type checking a record with higher rank types).
How is a function defined for different types in Haskell?
Given
func :: Integral a => a -> a
func x = x
func' :: (RealFrac a , Integral b) => a -> b
func' x = truncate x
How could they be combined into one function with the signature
func :: (SomeClassForBoth a, Integral b) => a -> b
With a typeclass.
class TowardsZero a where towardsZero :: Integral b => a -> b
instance TowardsZero Int where towardsZero = fromIntegral
instance TowardsZero Double where towardsZero = truncate
-- and so on
Possibly a class with an associated type family constraint is closer to what you wrote (though perhaps not closer to what you had in mind):
{-# LANGUAGE TypeFamilies #-}
import GHC.Exts
class TowardsZero a where
type RetCon a b :: Constraint
towardsZero :: RetCon a b => a -> b
instance TowardsZero Int where
type RetCon Int b = Int ~ b
towardsZero = id
instance TowardsZero Double where
type RetCon Double b = Integral b
towardsZero = truncate
-- and so on
This is known as ad hoc polymorphism, where you execute different code depending on the type. The way this is done in Haskell is using typeclasses. The most direct way is to define a new class
class Truncable a where
trunc :: Integral b => a -> b
And then you can define several concrete instances.
instance Truncable Integer where trunc = fromInteger
instance Truncable Double where trunc = truncate
This is unsatisfying because it requires an instance for each concrete type, when there are really only two families of identical-looking instances. Unfortunately, this is one of the cases where it is hard to reduce boilerplate, for technical reasons (being able to define "instance families" like this interferes with the open-world assumption of typeclasses, among other difficulties with type inference). As a hint of the complexity, note that your definition assumes that there is no type that is both RealFrac and Integral, but this is not guaranteed -- which implementation should we pick in this case?
There is another issue with this typeclass solution, which is that the Integral version doesn't have the type
trunc :: Integral a => a -> a
as you specified, but rather
trunc :: (Integral a, Integral b) => a -> b
Semantically this is not a problem, as I don't believe it is possible to end up with some polymorphic code where you don't know whether the type you are working with is Integral, but you do need to know that when it is, the result type is the same as the incoming type. That is, I claim that whenever you would need the former rather than the latter signature, you already know enough to replace trunc by id in your source. (It's a gut feeling though, and I would love to be proven wrong, seems like a fun puzzle)
There may be performance implications, however, since you might unnecessarily call fromIntegral to convert a type to itself, and I think the way around this is to use {-# RULES #-} definitions, which is a dark scary bag of complexity that I've never really dug into, so I don't know how hard or easy this is.
I don't recommend this, but you can hack at it with a GADT:
data T a where
T1 :: a -> T a
T2 :: RealFrac a => a -> T b
func :: Integral a => T a -> a
func (T1 x) = x
func (T2 x) = truncate x
The T type says, "Either you already know the type of the value I'm wrapping up, or it's some unknown instance of RealFrac". The T2 constructor existentially quantifies a and packs up a RealFrac dictionary, which we use in the second clause of func to convert from (unknown) a to b. Then, in func, I'm applying an Integral constraint to the a which may or may not be inside the T.
I have played around with TypeFamilies, FunctionalDependencies, and MultiParamTypeClasses. And it seems to me as though TypeFamilies doesn't add any concrete functionality over the other two. (But not vice versa). But I know type families are pretty well liked so I feel like I am missing something:
"open" relation between types, such as a conversion function, which does not seem possible with TypeFamilies. Done with MultiParamTypeClasses:
class Convert a b where
convert :: a -> b
instance Convert Foo Bar where
convert = foo2Bar
instance Convert Foo Baz where
convert = foo2Baz
instance Convert Bar Baz where
convert = bar2Baz
Surjective relation between types, such as a sort of type safe pseudo-duck typing mechanism, that would normally be done with a standard type family. Done with MultiParamTypeClasses and FunctionalDependencies:
class HasLength a b | a -> b where
getLength :: a -> b
instance HasLength [a] Int where
getLength = length
instance HasLength (Set a) Int where
getLength = S.size
instance HasLength Event DateDiff where
getLength = dateDiff (start event) (end event)
Bijective relation between types, such as for an unboxed container, which could be done through TypeFamilies with a data family, although then you have to declare a new data type for every contained type, such as with a newtype. Either that or with an injective type family, which I think is not available prior to GHC 8. Done with MultiParamTypeClasses and FunctionalDependencies:
class Unboxed a b | a -> b, b -> a where
toList :: a -> [b]
fromList :: [b] -> a
instance Unboxed FooVector Foo where
toList = fooVector2List
fromList = list2FooVector
instance Unboxed BarVector Bar where
toList = barVector2List
fromList = list2BarVector
And lastly a surjective relations between two types and a third type, such as python2 or java style division function, which can be done with TypeFamilies by also using MultiParamTypeClasses. Done with MultiParamTypeClasses and FunctionalDependencies:
class Divide a b c | a b -> c where
divide :: a -> b -> c
instance Divide Int Int Int where
divide = div
instance Divide Int Double Double where
divide = (/) . fromIntegral
instance Divide Double Int Double where
divide = (. fromIntegral) . (/)
instance Divide Double Double Double where
divide = (/)
One other thing I should also add is that it seems like FunctionalDependencies and MultiParamTypeClasses are also quite a bit more concise (for the examples above anyway) as you only have to write the type once, and you don't have to come up with a dummy type name which you then have to type for every instance like you do with TypeFamilies:
instance FooBar LongTypeName LongerTypeName where
FooBarResult LongTypeName LongerTypeName = LongestTypeName
fooBar = someFunction
vs:
instance FooBar LongTypeName LongerTypeName LongestTypeName where
fooBar = someFunction
So unless I am convinced otherwise it really seems like I should just not bother with TypeFamilies and use solely FunctionalDependencies and MultiParamTypeClasses. Because as far as I can tell it will make my code more concise, more consistent (one less extension to care about), and will also give me more flexibility such as with open type relationships or bijective relations (potentially the latter is solver by GHC 8).
Here's an example of where TypeFamilies really shines compared to MultiParamClasses with FunctionalDependencies. In fact, I challenge you to come up with an equivalent MultiParamClasses solution, even one that uses FlexibleInstances, OverlappingInstance, etc.
Consider the problem of type level substitution (I ran across a specific variant of this in Quipper in QData.hs). Essentially what you want to do is recursively substitute one type for another. For example, I want to be able to
substitute Int for Bool in Either [Int] String and get Either [Bool] String,
substitute [Int] for Bool in Either [Int] String and get Either Bool String,
substitute [Int] for [Bool] in Either [Int] String and get Either [Bool] String.
All in all, I want the usual notion of type level substitution. With a closed type family, I can do this for any types (albeit I need an extra line for each higher-kinded type constructor - I stopped at * -> * -> * -> * -> *).
{-# LANGUAGE TypeFamilies #-}
-- Subsitute type `x` for type `y` in type `a`
type family Substitute x y a where
Substitute x y x = y
Substitute x y (k a b c d) = k (Substitute x y a) (Substitute x y b) (Substitute x y c) (Substitute x y d)
Substitute x y (k a b c) = k (Substitute x y a) (Substitute x y b) (Substitute x y c)
Substitute x y (k a b) = k (Substitute x y a) (Substitute x y b)
Substitute x y (k a) = k (Substitute x y a)
Substitute x y a = a
And trying at ghci I get the desired output:
> :t undefined :: Substitute Int Bool (Either [Int] String)
undefined :: Either [Bool] [Char]
> :t undefined :: Substitute [Int] Bool (Either [Int] String)
undefined :: Either Bool [Char]
> :t undefined :: Substitute [Int] [Bool] (Either [Int] String)
undefined :: Either [Bool] [Char]
With that said, maybe you should be asking yourself why am I using MultiParamClasses and not TypeFamilies. Of the examples you gave above, all except Convert translate to type families (albeit you will need an extra line per instance for the type declaration).
Then again, for Convert, I am not convinced it is a good idea to define such a thing. The natural extension to Convert would be instances such as
instance (Convert a b, Convert b c) => Convert a c where
convert = convert . convert
instance Convert a a where
convert = id
which are as unresolvable for GHC as they are elegant to write...
To be clear, I am not saying there are no uses of MultiParamClasses, just that when possible you should be using TypeFamilies - they let you think about type-level functions instead of just relations.
This old HaskellWiki page does an OK job of comparing the two.
EDIT
Some more contrasting and history I stumbled upon from augustss blog
Type families grew out of the need to have type classes with
associated types. The latter is not strictly necessary since it can be
emulated with multi-parameter type classes, but it gives a much nicer
notation in many cases. The same is true for type families; they can
also be emulated by multi-parameter type classes. But MPTC gives a
very logic programming style of doing type computation; whereas type
families (which are just type functions that can pattern match on the
arguments) is like functional programming.
Using closed type families
adds some extra strength that cannot be achieved by type classes. To
get the same power from type classes we would need to add closed type
classes. Which would be quite useful; this is what instance chains
gives you.
Functional dependencies only affect the process of constraint solving, while type families introduced the notion of non-syntactic type equality, represented in GHC's intermediate form by coercions. This means type families interact better with GADTs. See this question for the canonical example of how functional dependencies fail here.