I've found two ways to promote an Integer to a Nat (or KnownNat, I don't get the distintion yet) at runtime, either using TypeLits and Proxy (Data.Proxy and GHC.TypeLits), or Singletons (Data.Singletons). In the code below you can see how each of the two approaches is used:
{-# LANGUAGE DataKinds #-}
{-# LANGUAGE ScopedTypeVariables #-}
{-# LANGUAGE NoImplicitPrelude #-}
module Main where
import Prelude hiding (replicate)
import Data.Proxy (Proxy(Proxy))
import Data.Monoid ((<>))
import Data.Singletons (SomeSing(..), toSing)
import GHC.TypeLits
import Data.Singletons.TypeLits
import Data.Vector.Sized (Vector, replicate)
main :: IO ()
main = playingWithTypes 8
playingWithTypes :: Integer -> IO ()
playingWithTypes nn = do
case someNatVal nn of
Just (SomeNat (proxy :: Proxy n)) -> do
-- let (num :: Integer) = natVal proxy
-- putStrLn $ "Some num: " <> show num
putStrLn $ "Some vector: " <> show (replicate 5 :: Vector n Int)
Nothing -> putStrLn "There's no number, the integer was not a natural number"
case (toSing nn :: SomeSing Nat) of
SomeSing (SNat :: Sing n) -> do
-- let (num :: Integer) = natVal (Proxy :: Proxy n)
-- putStrLn $ "Some num: " <> show num
putStrLn $ "Some vector: " <> show (replicate 5 :: Vector n Int)
The documentation for TypeLits indicates that it shouldn't be used by developers, but Singletons don't capture the case in which the given Integer is not a natural number (i.e., running playingWithTypes 8 runs without errors, but playingWithTypes (-2) fails when we try to create a Singleton from the non-natural number).
So, what is the "standard" way to promote an Integer to a Nat? Or what is the best approach to promote, using TypeLits and Proxy, or Singletons?
Nat (or KnownNat, I don't get the distintion yet)
Nat is the kind of type-level natural numbers. It has no term-level inhabitants. The idea is that GHC promotes any natural number into the type-level, and gives it kind Nat.
KnownNat is a constraint, on something of kind Nat, whose implementation witnesses how to convert the thing of kind Nat to a term-level Integer. GHC automagically creates instances of KnownNat for all type-level inhabitants of the kind Nat1.
That said, even if every n :: Nat (read type n of kind Nat) has a KnownNat instance on it1, you still need to write out the constraint.
I've found two ways to promote an Integer to a Nat
Have you really? At the end of the day, Nat in today's GHC is simply magical. singletons taps into that same magic. Under the hood, it uses someNatVal.
So, what is the "standard" way to promote an Integer to a Nat? Or what is the best approach to promote, using GHC.TypeLits and Proxy, or singletons?
There is no standard way. My take is: use singletons when you can afford its dependency footprint and GHC.TypeLits otherwise. The advantage of singletons is that the SingI type class makes it convenient to do induction based analysis while still also relying on GHC's special Nat type.
1 As pointed out in the comments, not every inhabitant of the Nat kind has a KnownNat instance. For example, Any Nat :: Nat where Any is the one from GHC.Exts. Only the inhabitants 0, 1, 2, ... have KnownNat instances.
Related
I am using data-reify and graphviz to transform an eDSL into a nice graphical representation, for introspection purposes.
As simple, contrived example, consider:
{-# LANGUAGE GADTs #-}
data Expr a where
Constant :: a -> Expr a
Map :: (other -> a) -> Expr a -> Expr a
Apply :: Expr (other -> a) -> Expr a -> Expr a
instance Functor Expr where
fmap fun val = Map fun val
instance Applicative Expr where
fun_expr <*> data_expr = Apply fun_expr data_expr
pure val = Constant val
-- And then some functions to optimize an Expr AST, evaluate Exprs, etc.
To make introspection nicer, I would like to print the values which are stored inside certain AST nodes of the DSL datatype.
However, in general any a might be stored in Constant, even those that do not implement Show. This is not necessarily a problem since we can constrain the instance of Expr like so:
instance Show a => Show (Expr a) where
...
This is not what I want however: I would still like to be able to print Expr even if a is not Show-able, by printing some placeholder value (such as just its type and a message that it is unprintable) instead.
So we want to do one thing if we have an a implementing Show, and another if a particular a does not.
Furthermore, the DSL also has the constructors Map and Apply which are even more problematic. The constructor is existential in other, and thus we cannot assume anything about other, a or (other -> a). Adding constraints to the type of other to the Map resp. Apply constructors would break the implementation of Functor resp. Applicative which forwards to them.
But here also I'd like to print for the functions:
a unique reference. This is always possible (even though it is not pretty as it requires unsafePerformIO) using System.Mem.StableName.
Its type, if possible (one technique is to use show (typeOf fun), but it requires that fun is Typeable).
Again we reach the issue where we want to do one thing if we have an f implementing Typeable and another if f does not.
How to do this?
Extra disclaimer: The goal here is not to create 'correct' Show instances for types that do not support it. There is no aspiration to be able to Read them later, or that print a != print b implies a != b.
The goal is to print any datastructure in a 'nice for human introspection' way.
The part I am stuck at, is that I want to use one implementation if extra constraints are holding for a resp. (other -> a), but a 'default' one if these do not exist.
Maybe type classes with FlexibleInstances, or maybe type families are needed here? I have not been able to figure it out (and maybe I am on the wrong track all together).
Not all problems have solutions. Not all constraint systems have a satisfying assignment.
So... relax the constraints. Store the data you need to make a sensible introspective function in your data structure, and use functions with type signatures like show, fmap, pure, and (<*>), but not exactly equal to them. If you need IO, use IO in your type signature. In short: free yourself from the expectation that your exceptional needs fit into the standard library.
To deal with things where you may either have an instance or not, store data saying whether you have an instance or not:
data InstanceOrNot c where
Instance :: c => InstanceOrNot c
Not :: InstanceOrNot c
(Perhaps a Constraint-kinded Either-alike, rather than Maybe-alike, would be more appropriate. I suspect as you start coding this you will discover what's needed.) Demand that clients that call notFmap and friends supply these as appropriate.
In the comments, I propose parameterizing your type by the constraints you demand, and giving a Functor instance for the no-constraints version. Here's a short example showing how that might look:
{-# LANGUAGE GADTs #-}
{-# LANGUAGE DataKinds #-}
{-# LANGUAGE TypeOperators #-}
{-# LANGUAGE TypeFamilies #-}
{-# LANGUAGE FlexibleInstances #-}
import Data.Kind
type family All cs a :: Constraint where
All '[] a = ()
All (c:cs) a = (c a, All cs a)
data Lol cs a where
Leaf :: a -> Lol cs a
Fmap :: All cs b => (a -> b) -> Lol cs a -> Lol cs b
instance Functor (Lol '[]) where
fmap f (Leaf a) = Leaf (f a)
fmap f (Fmap g garg) = Fmap (f . g) garg
Great timing! Well-typed recently released a library which allows you to recover runtime information. They specifically have an example of showing arbitrary values. It's on github at https://github.com/well-typed/recover-rtti.
It turns out that this is a problem which has been recognized by multiple people in the past, known as the 'Constrained Monad Problem'. There is an elegant solution, explained in detail in the paper The Constrained-Monad Problem by Neil Sculthorpe and Jan Bracker and George Giorgidze and Andy Gill.
A brief summary of the technique: Monads (and other typeclasses) have a 'normal form'. We can 'lift' primitives (which are constrained any way we wish) into this 'normal form' construction, itself an existential datatype, and then use any of the operations available for the typeclass we have lifted into. These operations themselves are not constrained, and thus we can use all of Haskell's normal typeclass functions.
Finally, to turn this back into the concrete type (which again has all the constraints we are interested in) we 'lower' it, which is an operation that takes for each of the typeclass' operations a function which it will apply at the appropriate time.
This way, constraints from the outside (which are part of the functions supplied to the lowering) and constraints from the inside (which are part of the primitives we lifted) are able to be matched, and finally we end up with one big happy constrained datatype for which we have been able to use any of the normal Functor/Monoid/Monad/etc. operations.
Interestingly, while the intermediate operations are not constrained, to my knowledge it is impossible to write something which 'breaks' them as this would break the categorical laws that the typeclass under consideration should adhere to.
This is available in the constrained-normal Hackage package to use in your own code.
The example I struggled with, could be implemented as follows:
{-# LANGUAGE GADTs #-}
{-# LANGUAGE DataKinds #-}
{-# LANGUAGE FlexibleInstances #-}
{-# LANGUAGE ScopedTypeVariables #-}
{-# LANGUAGE MultiParamTypeClasses #-}
{-# LANGUAGE FlexibleContexts #-}
{-# LANGUAGE StandaloneDeriving #-}
{-# LANGUAGE ConstraintKinds #-}
{-# LANGUAGE KindSignatures #-}
{-# LANGUAGE UndecidableInstances #-}
module Example where
import Data.Dynamic
import Data.Kind
import Data.Typeable
import Control.Monad.ConstrainedNormal
-- | Required to have a simple constraint which we can use as argument to `Expr` / `Expr'`.
-- | This is definitely the part of the example with the roughest edges: I have yet to figure out
-- | how to make Haskell happy with constraints
class (Show a, Typeable a) => Introspectable a where {}
instance (Show a, Typeable a) => Introspectable a where {}
data Expr' (c :: * -> Constraint) a where
C :: a -> Expr' c a
-- M :: (a -> b) -> Expr' a -> Expr' b --^ NOTE: This one is actually never used as ConstrainedNormal will use the 'free' implementation based on A + C.
A :: c a => Expr' c (a -> b) -> Expr' c a -> Expr' c b
instance Introspectable a => Show (Expr' Introspectable a) where
show e = case e of
C x -> "(C " ++ show x ++ ")"
-- M f x = "(M " ++ show val ++ ")"
A fx x -> "(A " ++ show (typeOf fx) ++ " " ++ show x ++ ")"
-- | In user-facing code you'd not want to expose the guts of this construction
-- So let's introduce a 'wrapper type' which is what a user would normally interact with.
type Expr c a = NAF c (Expr' c) a
liftExpr :: c a => Expr' c a -> Expr c a
liftExpr expr = liftNAF expr
lowerExpr :: c a => Expr c a -> Expr' c a
lowerExpr lifted_expr = lowerNAF C A lifted_expr
constant :: Introspectable a => a -> Expr c a
constant val = pure val -- liftExpr (C val)
You could now for instance write
ghci> val = constant 10 :: Expr Introspectable Int
(C 10)
ghci> (+2) <$> val
(C 12)
ghci> (+) <$> constant 10 <*> constant 32 :: Expr Introspectable Int
And by using Data.Constraint.Trivial (part of the trivial-constrained library, although it is also possible to write your own 'empty constrained') one could instead write e.g.
ghci> val = constant 10 :: Expr Unconstrained Int
which will work just as before, but now val cannot be printed.
The one thing I have not yet figured out, is how to properly work with subsets of constraints (i.e. if I have a function that only requires Show, make it work with something that is Introspectable). Currently everything has to work with the 'big' set of constraints.
Another minor drawback is of course that you'll have to annotate the constraint type (e.g. if you do not want constraints, write Unconstrained manually), as GHC will otherwise complain that c0 is not known.
We've reached the goal of having a type which can be optionally be constrained to be printable, with all machinery that does not need printing to work also on all instances of the family of types including those that are not printable, and the types can be used as Monoids, Functors, Applicatives, etc just as you like.
I think it is a beautiful approach, and want to commend Neil Sculthorpe et al. for their work on the paper and the constrained-normal library that makes this possible. It's very cool!
StackOverflow!
For reasons that would like to remain between me and God, I'm currently playing around with promoting runtime naturals to the type level. I've been following this approach with GHC.TypeLits, which has worked out fine so far.
However, in one instance, I have an additional constraint of 1 <= n, i.e. my promoted natural not to be just any natural, but at least 1. This is also from GHC.TypeLits And I am unsure if/how it is possible to extract and make that information known.
Here's a minimal non-working example:
{-# LANGUAGE DataKinds #-}
{-# LANGUAGE GADTs #-}
{-# LANGUAGE PolyKinds #-}
{-# LANGUAGE RankNTypes #-}
{-# LANGUAGE ScopedTypeVariables #-}
{-# LANGUAGE TypeOperators #-}
import Data.Maybe
import Data.Proxy
import GHC.TypeLits
import Numeric.Natural
data AnyNat (n :: Nat) where
AN :: AnyNat n
data AtLeast1Nat (n :: Nat) where
AL1N :: AtLeast1Nat n
promote0 :: Natural -> AnyNat n
promote0 k = case sn of
SomeNat (_ :: Proxy p) -> AN
where
sn = (fromJust . someNatVal . toInteger) k
promote1 :: (KnownNat n, 1 <= n) => Natural -> AtLeast1Nat n
promote1 k = case sn of
SomeNat (_ :: Proxy p) -> AL1N
where
sn = (fromJust . someNatVal . toInteger) k
main :: IO ()
main = do nat_in <- getLine
let nat = read nat_in :: Natural
let p0 = promote0 nat
let p1 = promote1 nat
putStrLn "Last statement must be an expression"
This produces this error (full error here, but this is the relevant part):
* Couldn't match type `1 <=? n0' with 'True
arising from a use of `promote1'
The type variable `n0' is ambiguous
Honestly, this isn't too surprising and I (think I) do understand why this happens. The Natural that we give in could be any of them, so why would we be able to derive that 1 <= n? That's why it works fine for promote0 and not promote1.
My question is hence, is there any way to also check (and propagate to type-level) this information so I can use it as intended, or am I using the wrong approach here?
You're using the wrong approach.
As discussed in the comments, promote0 (and similarly promote1) isn't doing what you're hoping. The problem is that the AN on the right-hand-side of the case has type AnyNat n for some n entirely unrelated to the term sn. You could have written:
promote0 k = case 2+2 of 4 -> AN
and gotten much the same effect. Note the critical difference between your code and the other Stack Overflow answer you link: in that answer, the type variable n in the case scrutinee is used to type something (via ScopedTypeVariables) in the case branch. You bind a type variable p in your scrutinee but then don't use it for anything.
If we consider your actual problem, suppose we want to write something like this:
import qualified Data.Vector.Sized as V
main = do
n <- readLn :: IO Int
let Just v = V.fromList (replicate n 1)
v2 = v V.++ v
print $ v2
This won't type check. It gives an error on V.fromList about the lack of a KnownNat constraint. The issue is that v has been assigned a type S.Vector k Int for some k :: Nat. But V.fromList performs a runtime check that the length of the input list (the run time value n) is equal to the type-level k. To do this, k must be converted to a runtime integer which requires KnownNat k.
The general solution, as you've guessed, is to construct a SomeNat that basically contains a KnownNat n => n that's unknown at compile time. However, you don't want to try to promote it to a known type-level Nat (i.e., you don't want promote0). You want to leave it as-is and case match on it at the point you need its type-level value. That type-level value will be available within the case but unavailable outside the case, so no types that depend on n can "escape" the case statement.
So, for example, you can write:
import qualified Data.Vector.Sized as V
import Data.Proxy
import GHC.TypeNats
main = do
n <- readLn :: IO Int
-- keep `sn` as the type-level representation of the runtime `n`
let sn = someNatVal (fromIntegral n)
-- scrutinize it when you need its value at type level
case sn of
-- bind the contained Nat to the type variable `n`
SomeNat (Proxy :: Proxy n) -> do
-- now it's available at the type level
let v = V.replicate #n 1 -- using type-level "n"
v2 = v V.++ v
print v2
but you can't write:
main :: IO ()
main = do
n <- readLn :: IO Int
let sn = someNatVal (fromIntegral n)
let v2 = case sn of
SomeNat (Proxy :: Proxy n) ->
let v = V.replicate #n 1
in v V.++ v
print v2
You'll get an error that a type variable is escaping its scope. (If you want to let sized vectors leak outside the case, you need to make use of V.SomeSized or something similar.)
As for the main part of your question about handling a 1 <= n constraint, dealing with inequalities for type-level naturals is a major headache. I think you'll need to post a minimal example of exactly how you want to use this constraint in the context of a sized vector imlementation, in order to get a decent answer.
In an attempt at learning how to work with dependent data types in haskell I encountered the following problem:
Suppose you have a function such as:
mean :: ((1 GHC.TypeLits.<=? n) ~ 'True, GHC.TypeLits.KnownNat n) => R n -> ℝ
defined in the hmatrix library, then how do you use this on a vector that has an existential type? E.g.:
{-# LANGUAGE DataKinds #-}
{-# LANGUAGE ScopedTypeVariables #-}
{-# LANGUAGE TypeOperators #-}
import Data.Proxy (Proxy (..))
import GHC.TypeLits
import Numeric.LinearAlgebra.Static
getUserInput =
let userInput = 3 -- pretend it's unknown at compile time
seed = 42
in existentialCrisis seed userInput
existentialCrisis seed userInput
| userInput <= 0 = 0
| otherwise =
case someNatVal userInput of
Nothing -> undefined -- let's ignore this case for now
Just (SomeNat (proxy :: Proxy n)) ->
let someVector = randomVector seed Gaussian :: R n
in mean someVector -- I know that 'n > 0' but the compiler doesn't
This gives the following error:
• Couldn't match type ‘1 <=? n’ with ‘'True’
arising from a use of ‘mean’
Makes sense indeed, but after some googling and fiddling around, I could not find out how to deal with this. How can I get hold of an n :: Nat, based on user input, such that it satisfies the 1 <= n constraint?. I believe it must be possible since the someNatVal function already succeeds in satisfying the KnownNat constraint based on the condition that the input is not negative.
It seems to me that this is a common thing when working with dependent types, and maybe the answer is obvious but I don't see it.
So my question:
How, in general, can I bring an existential type in scope satisfying the constraints required for some function?
My attempts:
To my surprise, even the following modification
let someVector = randomVector seed Gaussian :: R (n + 1)
gave a type error:
• Couldn't match type ‘1 <=? (n + 1)’ with ‘'True’
arising from a use of ‘mean’
Also, adding an extra instance to <=? to prove this equality does not work as <=? is closed.
I tried an approach combining GADTs with typeclasses as in this answer to a previous question of mine but could not make it work.
Thanks #danidiaz for pointing me in the right direction, the typelist-witnesses documentation provides a nearly direct answer to my question. Seems like I was using the wrong search terms when googling for a solution.
So here is a self contained compileable solution:
{-# LANGUAGE DataKinds #-}
{-# LANGUAGE ScopedTypeVariables #-}
{-# LANGUAGE TypeOperators #-}
{-# LANGUAGE TypeFamilies #-}
import Data.Proxy (Proxy (..))
import Data.Type.Equality ((:~:)(Refl))
import GHC.TypeLits
import GHC.TypeLits.Compare
import Numeric.LinearAlgebra.Static
existentialCrisis :: Int -> Int -> IO (Double)
existentialCrisis seed userInput =
case someNatVal (fromIntegral userInput) of
Nothing -> print "someNatVal failed" >> return 0
Just (SomeNat (proxy :: Proxy n)) ->
case isLE (Proxy :: Proxy 1) proxy of
Nothing -> print "isLE failed" >> return 0
Just Refl ->
let someVector = randomVector seed Gaussian :: R n
in do
print userInput
-- I know that 'n > 0' and so does the compiler
return (mean someVector)
And it works with input only known at runtime:
λ: :l ExistentialCrisis.hs
λ: existentialCrisis 41 1
(0.2596687587224799 :: R 1)
0.2596687587224799
*Main
λ: existentialCrisis 41 0
"isLE failed"
0.0
*Main
λ: existentialCrisis 41 (-1)
"someNatVal failed"
0.0
It seems like typelist-witnesses does a lot unsafeCoerceing under the hood. But the interface is type-safe so it doesn't really matter that much for practical use cases.
EDIT:
If this question was of interest to you, might also find this post interesting: https://stackoverflow.com/a/41615278/2496293
Let us say I want to make a ADT as follows in Haskell:
data Properties = Property String [String]
deriving (Show,Eq)
I want to know if it is possible to give the second list a bounded and enumerated property? Basically the first element of the list will be the minBound and the last element will be the maxBound. I am trying,
data Properties a = Property String [a]
deriving (Show, Eq)
instance Bounded (Properties a) where
minBound a = head a
maxBound a = (head . reverse) a
But not having much luck.
Well no, you can't do quite what you're asking, but maybe you'll find inspiration in this other neat trick.
{-# language ScopedTypeVariables, FlexibleContexts, UndecidableInstances #-}
import Data.Reflection -- from the reflection package
import qualified Data.List.NonEmpty as NE
import Data.List.NonEmpty (NonEmpty (..))
import Data.Proxy
-- Just the plain string part
newtype Pstring p = P String deriving Eq
-- Those properties you're interested in. It will
-- only be possible to produce bounds if there's at
-- least one property, so NonEmpty makes more sense
-- than [].
type Props = NonEmpty String
-- This is just to make a Show instance that does
-- what you seem to want easier to write. It's not really
-- necessary.
data Properties = Property String [String] deriving Show
Now we get to the key part, where we use reflection to produce class instances that can depend on run-time values. Roughly speaking, you can think of
Reifies x t => ...
as being a class-level version of
\(x :: t) -> ...
Because it operates at the class level, you can use it to parametrize instances. Since Reifies x t binds a type variable x, rather than a term variable, you need to use reflect to actually get the value back. If you happen to have a value on hand whose type ends in p, then you can just apply reflect to that value. Otherwise, you can always magic up a Proxy :: Proxy p to do the job.
-- If some Props are "in the air" tied to the type p,
-- then we can show them along with the string.
instance Reifies p Props => Show (Pstring p) where
showsPrec k p#(P str) =
showsPrec k $ Property str (NE.toList $ reflect p)
-- If some Props are "in the air" tied to the type p,
-- then we can give Pstring p a Bounded instance.
instance Reifies p Props => Bounded (Pstring p) where
minBound = P $ NE.head (reflect (Proxy :: Proxy p))
maxBound = P $ NE.last (reflect (Proxy :: Proxy p))
Now we need to have a way to actually bind types that can be passed to the type-level lambdas. This is done using the reify function. So let's throw some Props into the air and then let the butterfly nets get them back.
main :: IO ()
main = reify ("Hi" :| ["how", "are", "you"]) $
\(_ :: Proxy p) -> do
print (minBound :: Pstring p)
print (maxBound :: Pstring p)
./dfeuer#squirrel:~/src> ./WeirdBounded
Property "Hi" ["Hi","how","are","you"]
Property "you" ["Hi","how","are","you"]
You can think of reify x $ \(p :: Proxy p) -> ... as binding a type p to the value x; you can then pass the type p where you like by constraining things to have types involving p.
If you're just doing a couple of things, all this machinery is way more than necessary. Where it gets nice is when you're performing lots of operations with values that have phantom types carrying extra information. In many cases, you can avoid most of the explicit applications of reflect and the explicit proxy handling, because type inference just takes care of it all for you. For a good example of this technique in action, see the hyperloglog package. Configuration information for the HyperLogLog data structure is carried in a type parameter; this guarantees, at compile time, that only similarly configured structures are merged with each other.
I am working with Data.Typeable and in particular I want to be able to generate correct types of a particular kind (say *). The problem that I'm running into is that TypeRep allows us to do the following (working with the version in GHC 7.8):
let maybeType = typeRep (Proxy :: Proxy Maybe)
let maybeCon = fst (splitTyConApp maybeType)
let badType = mkTyConApp maybeCon [maybeType]
Here badType is in a sense the representation of the type Maybe Maybe, which is not a valid type of any Kind:
> :k Maybe (Maybe)
<interactive>:1:8:
Expecting one more argument to ‘Maybe’
The first argument of ‘Maybe’ should have kind ‘*’,
but ‘Maybe’ has kind ‘* -> *’
In a type in a GHCi command: Maybe (Maybe)
I'm not looking for enforcing this at type level, but I would like to be able to write a program that is smart enough to avoid constructing such types at runtime. I can do this with data-level terms with TypeRep. Ideally, I would have something like
data KindRep = Star | KFun KindRep KindRep
and have a function kindOf with kindOf Int = Star (probably really kindOf (Proxy :: Proxy Int) = Star) and kindOf Maybe = KFun Star Star, so that I could "kind-check" my TypeRep value.
I think I can do this manually with a polykinded typeclass like Typeable, but I'd prefer to not have to write my own instances for everything. I'd also prefer to not revert to GHC 7.6 and use the fact that there are separate type classes for Typeable types of different kinds. I am open to methods that get this information from GHC.
We can get the kind of a type, but we need to throw a whole host of language extensions at GHC to do so, including the (in this case) exceeding questionable UndecidableInstances and AllowAmbiguousTypes.
{-# LANGUAGE KindSignatures #-}
{-# LANGUAGE FlexibleInstances #-}
{-# LANGUAGE PolyKinds #-}
{-# LANGUAGE ScopedTypeVariables #-}
{-# LANGUAGE UndecidableInstances #-}
{-# LANGUAGE AllowAmbiguousTypes #-}
import Data.Proxy
Using your definition for a KindRep
data KindRep = Star | KFun KindRep KindRep
we define the class of Kindable things whose kind can be determined
class Kindable x where
kindOf :: p x -> KindRep
The first instance for this is easy, everything of kind * is Kindable:
instance Kindable (a :: *) where
kindOf _ = Star
Getting the kind of higher-kinded types is hard. We will try to say that if we can find the kind of its argument and the kind of the result of applying it to an argument, we can figure out its kind. Unfortunately, since it doesn't have an argument, we don't know what type its argument will be; this is why we need AllowAmbiguousTypes.
instance (Kindable a, Kindable (f a)) => Kindable f where
kindOf _ = KFun (kindOf (Proxy :: Proxy a)) (kindOf (Proxy :: Proxy (f a)))
Combined, these definitions allow us to write things like
kindOf (Proxy :: Proxy Int) = Star
kindOf (Proxy :: Proxy Maybe) = KFun Star Star
kindOf (Proxy :: Proxy (,)) = KFun Star (KFun Star Star)
kindOf (Proxy :: Proxy StateT) = KFun Star (KFun (KFun Star Star) (KFun Star Star))
Just don't try to determine the kind of a polykinded type like Proxy
kindOf (Proxy :: Proxy Proxy)
which fortunately results in a compiler error in only a finite amount of time.