Creating Haskell datatype accepting type of non-* kind in one of its constructors - haskell

Hello. I am playing with Ivory library which relies heavily on modern features of Haskell. Among others, it defines the typeclasses IvoryType accepting all types and IvoryArea accepting types of special kind Area. The definitions look like this:
{-# LANGUAGE DataKinds #-}
{-# LANGUAGE KindSignatures #-}
{-# LANGUAGE ScopedTypeVariables #-}
{-# LANGUAGE ExistentialQuantification #-}
-- | Proxy datatype with a phantom arbitrary-kinded type
-- and a single constructor
data Proxy (a :: k) = Proxy
-- | The kind of memory-area types.
data Area k
= Struct Symbol
| Array Nat (Area k)
| CArray (Area k)
| Stored k
-- ^ This is lifting for a *-kinded type
class IvoryType t where
ivoryType :: Proxy t -> I.Type {- arguments are not important -}
-- | Guard the inhabitants of the Area type, as not all *s are Ivory *s.
class IvoryArea (a :: Area *) where
ivoryArea :: Proxy a -> I.Type {- arguments are not important -}
OK. Now let's try to express the fact that we are going to store values with ivoryType function defined. Obviously, they are the memebers of IvoryType class, so the answer is
data TypeStorage = TypeStorage (forall t . IvoryType t => t)
So far so good. Now we want to store values which have ivoryArea function defined. Let's use the IvoryArea class as a filter condition, like in the prevoius case:
data AreaStorage = AreaStorage (forall t . IvoryArea t => t)
Surprisingly, the compiler (ghc version 7.8.4) outputs an error
src/IvoryLL/Types.hs:59:45:
Expected a type, but ‘t’ has kind ‘Area *’
In the type ‘forall t. IvoryArea t => t’
In the definition of data constructor ‘AreaBase’
In the data declaration for ‘Area
Could you please explain, how to express the ownership of ivoryArea function in Haskell properly ?
Edit
Some links to the original declarations:
https://github.com/GaloisInc/ivory/blob/master/ivory/src/Ivory/Language/Type.hs
https://github.com/GaloisInc/ivory/blob/master/ivory/src/Ivory/Language/Area.hs

Now that we've established in the comments that you can't do what you want directly, which is create a special "subkind" of all types, we can use a bit more legwork to get what you want.
We just use a (closed) type family to interpret your Area * kind into something of kind * and then GADT, indexed by Area *, to hold such values. We can then wrap the whole shebang up in an existential to store arbitrary values of such a kind, if so desired.
Consider this cut down example:
data Area k
= Stored k
| List (Area k)
type family InterpIvoryArea a :: * where
InterpIvoryArea (Stored k) = k
InterpIvoryArea (List a) = [InterpIvoryArea a]
data AreaStorage a where
AreaStorage :: InterpIvoryArea a -> AreaStorage a
data AreaStorageExistential where
AreaStorageExistential :: AreaStorage a -> AreaStorageExistential
testValue :: AreaStorageExistential
testValue = AreaStorageExistential (AreaStorage [1,2,3] :: AreaStorage (List (Stored Int)))

Related

Is it possible to promote a value to type level?

Doing this just for fun but I don't end up figuring this out.
Say I have a typeclass that unifies coordinate system on squares and hexagons:
{-# LANGUAGE DataKinds #-}
{-# LANGUAGE KindSignatures #-}
{-# LANGUAGE RankNTypes #-}
{-# LANGUAGE ScopedTypeVariables #-}
{-# LANGUAGE TypeApplications #-}
{-# LANGUAGE TypeFamilies #-}
import Data.Proxy
data Shape = Square | Hexagon
class CoordSystem (k :: Shape) where
type Coord k
-- all coordinates arranged in a 2D list
-- given a side length of the shape
allCoords :: forall p. p k -> Int -> [[Coord k]]
-- neighborhoods of a coordinate.
neighborsOf :: forall p. p k -> Int -> Coord k -> [Coord k]
-- omitting implementations
instance CoordSystem 'Square
instance CoordSystem 'Hexagon
Now suppose I want to use this interface with a s :: Shape that is only known at runtime. But to make use of this interface, at some point I'll need a function like this:
-- none of those two works:
-- promote :: CoordSystem k => Shape -> Proxy (k :: Shape) -- signature 1
-- promote :: Shape -> forall k. CoordSystem k => Proxy (k :: Shape)
promote s = case s of
Square -> Proxy #'Square
Hexagon -> Proxy #'Hexagon
However this does not work, if signature 1 is uncommented:
• Couldn't match type ‘k’ with ‘'Square’
‘k’ is a rigid type variable bound by
the type signature for:
promote :: forall (k :: Shape). CoordSystem k => Shape -> Proxy k
at SO.hs:28:1-55
Expected type: Proxy k
Actual type: Proxy 'Square
Understandably, none of 'Square, 'Hexagon, k :: Shape unifies with others, so I have no idea whether this is possible.
I also feel type erasure shouldn't be an issue here as alternatives of Shape can use to uniquely identify the instance - for such reason I feel singletons could be of use but I'm not familiar with that package to produce any working example either.
The usual way is to use either an existential type or its Church encoding. The encoded version is actually easier to understand at first, I think, and closer to what you already attempted. The problem with your forall k. CoordSystem k => {- ... thing mentioning k -} is that it promises to polymorph into whatever k the user likes (so long as the user likes CoordSystems!). To fix it, you can demand that the user polymorph into whatever k you like.
-- `a` must not mention `k`, since `k` is not
-- in scope in the final return type
promote :: forall a. Shape -> (forall k. CoordSystem k => Tagged k a) -> a
promote Square a = unTagged (a #Square)
promote Hexagon a = unTagged (a #Hexagon)
-- usage example
test = promote Hexagon (unproxy $ \p -> length (allCoords p 15))
Note that on the right hand side of the = sign, a has the type forall k. CoordSystem k => {- ... -} that says the user gets to choose k, but this time you're the user.
Another common option is to use an existential:
data SomeSystem where
-- Proxy to be able to name the wrapped type when matching on a SomeSystem;
-- in some future version of GHC we may be able to name it via pattern-matching
-- on a type application instead, which would be better
SomeSystem :: CoordSystem k => Proxy k -> SomeSystem
Then you would write something like
promote :: Shape -> SomeSystem
promote Square = SomeSystem (Proxy #Square)
promote Hexagon = SomeSystem (Proxy #Hexagon)
-- usage example
test = case promote Hexagon of SomeSystem p -> length (allCoords p 15)
and then the user would pattern match to extract the CoordSystem instance from it.
A final choice is singletons:
data ShapeS k where
SquareS :: ShapeS Square
HexagonS :: ShapeS Hexagon
Here we have made a direct connection between SquareS at the computation level and Square at the type level (resp. HexagonS and Hexagon). Then you can write:
-- N.B. not a rank-2 type, and in particular `a` is
-- now allowed to mention `k`
promote :: ShapeS k -> (CoordSystem k => a) -> a
promote SquareS a = a
promote HexagonS a = a
The singletons package offers tools for automatically deriving the singleton types that correspond to your ADTs.

How to 'show' unshowable types?

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!

Subset algebraic data type, or type-level set, in Haskell

Suppose you have a large number of types and a large number of functions that each return "subsets" of these types.
Let's use a small example to make the situation more explicit. Here's a simple algebraic data type:
data T = A | B | C
and there are two functions f, g that return a T
f :: T
g :: T
For the situation at hand, assume it is important that f can only return a A or B and g can only return a B or C.
I would like to encode this in the type system. Here are a few reasons/circumstances why this might be desirable:
Let the functions f and g have a more informative signature than just ::T
Enforce that implementations of f and g do not accidentally return a forbidden type that users of the implementation then accidentally use
Allow code reuse, e.g. when helper functions are involved that only operate on subsets of type T
Avoid boilerplate code (see below)
Make refactoring (much!) easier
One way to do this is to split up the algebraic datatype and wrap the individual types as needed:
data A = A
data B = B
data C = C
data Retf = RetfA A | RetfB B
data Retg = RetgB B | RetgC C
f :: Retf
g :: Retg
This works, and is easy to understand, but carries a lot of boilerplate for frequent unwrapping of the return types Retf and Retg.
I don't see polymorphism being of any help, here.
So, probably, this is a case for dependent types. It's not really a type-level list, rather a type-level set, but I've never seen a type-level set.
The goal, in the end, is to encode the domain knowledge via the types, so that compile-time checks are available, without having excessive boilerplate. (The boilerplate gets really annoying when there are lots of types and lots of functions.)
Define an auxiliary sum type (to be used as a data kind) where each branch corresponds to a version of your main type:
{-# LANGUAGE FlexibleInstances #-}
{-# LANGUAGE StandaloneKindSignatures #-}
{-# LANGUAGE StandaloneDeriving #-}
{-# LANGUAGE DataKinds #-}
import Data.Kind
import Data.Void
import GHC.TypeLits
data Version = AllEnabled | SomeDisabled
Then define a type family that maps the version and the constructor name (given as a type-level Symbol) to the type () if that branch is allowed, and to the empty type Void if it's disallowed.
type Enabled :: Version -> Symbol -> Type
type family Enabled v ctor where
Enabled SomeDisabled "C" = Void
Enabled _ _ = ()
Then define your type as follows:
type T :: Version -> Type
data T v = A !(Enabled v "A")
| B !(Enabled v "B")
| C !(Enabled v "C")
(The strictness annotations are there to help the exhaustivity checker.)
Typeclass instances can be derived, but separately for each version:
deriving instance Show (T AllEnabled)
deriving instance Eq (T AllEnabled)
deriving instance Show (T SomeDisabled)
deriving instance Eq (T SomeDisabled)
Here's an example of use:
noC :: T SomeDisabled
noC = A ()
main :: IO ()
main = print $ case noC of
A _ -> "A"
B _ -> "B"
-- this doesn't give a warning with -Wincomplete-patterns
This solution makes pattern-matching and construction more cumbersome, because those () are always there.
A variation is to have one type family per branch (as in Trees that Grow) instead of a two-parameter type family.
I tried to achieve something like this in the past, but without much success -- I was not too satisfied with my solution.
Still, one can use GADTs to encode this constraint:
data TagA = IsA | NotA
data TagC = IsC | NotC
data T (ta :: TagA) (tc :: TagC) where
A :: T 'IsA 'NotC
B :: T 'NotA 'NotC
C :: T 'NotA 'IsC
-- existential wrappers
data TnotC where TnotC :: T ta 'NotC -> TnotC
data TnotA where TnotA :: T 'NotA tc -> TnotA
f :: TnotC
g :: TnotA
This however gets boring fast, because of the wrapping/unwrapping of the exponentials. Consumer functions are more convenient since we can write
giveMeNotAnA :: T 'NotA tc -> Int
to require anything but an A. Producer functions instead need to use existentials.
In a type with many constructors, it also gets inconvenient since we have to use a GADT with many tags/parameters. Maybe this can be streamlined with some clever typeclass machinery.
Giving each individual value its own type scales extremely badly, and is quite unnecessarily fine-grained.
What you probably want is just restrict the types by some property on their values. In e.g. Coq, that would be a subset type:
Inductive T: Type :=
| A
| B
| C.
Definition Retf: Type := { x: T | x<>C }.
Definition Retg: Type := { x: T | x<>A }.
Well, Haskell has no way of expressing such value constraints, but that doesn't stop you from creating types that conceptually fulfill them. Just use newtypes:
newtype Retf = Retf { getRetf :: T }
mkRetf :: T -> Maybe Retf
mkRetf C = Nothing
mkRetf x = Retf x
newtype Retg = Retg { getRetg :: T }
mkRetg :: ...
Then in the implementation of f, you match for the final result of mkRetf and raise an error if it's Nothing. That way, an implementation mistake that makes it give a C will unfortunately not give a compilation error, but at least a runtime error from within the function that's actually at fault, rather than somewhere further down the line.
An alternative that might be ideal for you is Liquid Haskell, which does support subset types. I can't say too much about it, but it's supposedly pretty good (and will in new GHC versions have direct support).

Is this use of GADTs fully equivalent to existential types?

Existentially quantified data constructors like
data Foo = forall a. MkFoo a (a -> Bool)
| Nil
can be easily translated to GADTs:
data Foo where
MkFoo :: a -> (a -> Bool) -> Foo
Nil :: Foo
Are there any differences between them: code which compiles with one but not another, or gives different results?
They are nearly equivalent, albeit not completely so, depending on which extensions you turn on.
First of all, note that you don't need to enable the GADTs extension to use the data .. where syntax for existential types. It suffices to enable the following lesser extensions.
{-# LANGUAGE GADTSyntax #-}
{-# LANGUAGE ExistentialQuantification #-}
With these extensions, you can compile
data U where
U :: a -> (a -> String) -> U
foo :: U -> String
foo (U x f) = f x
g x = let h y = const y x
in (h True, h 'a')
The above code also compiles if we replace the extensions and the type definition with
{-# LANGUAGE ExistentialQuantification #-}
data U = forall a . U a (a -> String)
The above code, however, does not compile with the GADTs extension turned on! This is because GADTs also turns on the MonoLocalBinds extension, which prevents the above definition of g to compile. This is because the latter extension prevents h to receive a polymorphic type.
From the documentation:
Notice that GADT-style syntax generalises existential types (Existentially quantified data constructors). For example, these two declarations are equivalent:
data Foo = forall a. MkFoo a (a -> Bool)
data Foo' where { MKFoo :: a -> (a->Bool) -> Foo' }
(emphasis on the word equivalent)
The latter isn't actually a GADT - it's an existentially quantified data type declared with GADT syntax. As such, it is identical to the former.
The reason it's not a GADT is that there is no type variable that gets refined based on the choice of constructor. That's the key new functionality added by GADTs. If you have a GADT like this:
data Foo a where
StringFoo :: String -> Foo String
IntFoo :: Int -> Foo Int
Then pattern-matching on each constructor reveals additional information that can be used inside the matching clause. For instance:
deconstructFoo :: Foo a -> a
deconstructFoo (StringFoo s) = "Hello! " ++ s ++ " is a String!"
deconstructFoo (IntFoo i) = i * 3 + 1
Notice that something very interesting is happening there, from the point of view of the type system. deconstructFoo promises it will work for any choice of a, as long as it's passed a value of type Foo a. But then the first equation returns a String, and the second equation returns an Int.
This is what you cannot do with a regular data type, and the new thing GADTs provide. In the first equation, the pattern match adds the constraint (a ~ String) to its context. In the second equation, the pattern match adds (a ~ Int).
If you haven't created a type where pattern-matching can cause type refinement, you don't have a GADT. You just have a type declared with GADT syntax. Which is fine - in a lot of ways, it's a better syntax than the basic data type syntax. It's just more verbose for the easiest cases.

Convert from type `T a` to `T b` without boilerplate

So, I have an AST data type with a large number of cases, which is parameterized by an "annotation" type
data Expr a = Plus a Int Int
| ...
| Times a Int Int
I have annotation types S and T, and some function f :: S -> T. I want to take an Expr S and convert it to an Expr T using my conversion f on each S which occurs within an Expr value.
Is there a way to do this using SYB or generics and avoid having to pattern match on every case? It seems like the type of thing that this is suited for. I just am not familiar enough with SYB to know the specific way to do it.
It sounds like you want a Functor instance. This can be automatically derived by GHC using the DeriveFunctor extension.
Based on your follow-up question, it seems that a generics library is more appropriate to your situation than Functor. I'd recommend just using the function given on SYB's wiki page:
{-# LANGUAGE DeriveDataTypeable, ScopedTypeVariables, FlexibleContexts #-}
import Data.Generics
import Unsafe.Coerce
newtype C a = C a deriving (Data,Typeable)
fmapData :: forall t a b. (Typeable a, Data (t (C a)), Data (t a)) =>
(a -> b) -> t a -> t b
fmapData f input = uc . everywhere (mkT $ \(x::C a) -> uc (f (uc x)))
$ (uc input :: t (C a))
where uc = unsafeCoerce
The reason for the extra C type is to avoid a problematic corner case where there are occurrences of fields at the same type as a (more details on the wiki). The caller of fmapData doesn't need to ever see it.
This function does have a few extra requirements compared to the real fmap: there must be instances of Typeable for a, and Data for t a. In your case t a is Expr a, which means that you'll need to add a deriving Data to the definition of Expr, as well as have a Data instance in scope for whatever a you're using.

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