Basic Type Level Programming in Haskell

Dependently typed programming is becoming all the rage these days. Advocates are talking about all the neat stuff you can do by putting more and more information into the type system. It’s true! Type level programming gives you interesting new tools for designing software. You can guarantee safety properties, and in some cases, even gain performance optimizations through the use of these types.

I’m not going to try and sell you on these benefits – presumably you’ve read about something like the dependently typed neural networks, or about Idris’s encoding of network protocols in the type system. If you’re not convinced, then this isn’t the right article for you. If you are interested, and have some familiarity with Haskell, Elm, F#, or another ML-family language, then this article will be right up your alley.

The Basic Types

So let’s talk about some basic types. I’m going to stick with the real basic types here: no primitives, just stuff we can define in one line in Haskell.

data Unit = MkUnit data Bool = True | False

This code block defines two new types: Unit and Bool . The Unit type has one constructor, called MkUnit . Since there’s only one constructor for this type, and it takes no parameters, there is only one value of this type. We call it Unit because there’s only one value.

Bool is a type that has two constructors: True and False . These don’t take any parameters either, so they’re kind of like constants.

What does it mean to be a type? A type is a way of classifying things. Things – that’s a vague word. What do I mean by ‘things’?

Well, for these simple types above, we’ve already seen all their possible values – we can say that True and False are members of the type Bool . Furthermore, 1 , 'a' , and Unit are not members of the type Bool .

These types are kind of boring. Let’s look at another type:

data IntAndChar = MkIntAndChar Int Char

This introduces a type IntAndChar with a single constructor that takes two arguments: one of which is an Int and the other is a Char . Values of this type look like:

theFirstOne = MkIntAndChar 3 'a' theSecond = MkIntAndChar ( - 3 ) 'b'

MkIntAndChar looks a lot like a function. In fact, if we ask GHCi about it’s type, we get this back:

λ > : t MkIntAndChar MkIntAndChar :: Int -> Char -> IntAndChar

MkIntAndChar is a function accepting an Int and a Char and finally yielding a value of type IntAndChar .

So we can construct values, and values have types. Can we construct types? And if so, what do they have?

The Higher Kinds

Let’s hold onto our intuition about functions and values. A function with the type foo :: Int -> IntAndChar is saying:

Give me a value with the type Int , and I will give you a value with the type IntAndChar .

Now, let’s lift that intuition into the type level. A value constructor accepts a value and yields a value. So a type constructor accepts a type and yields a type. Haskell’s type variables allow us to express this.

Let’s consider everyone’s favorite sum type:

data Maybe a = Just a | Nothing

Here, we declare a type Maybe , with two data constructors: Just , which accepts a value of type a , and Nothing , which does not accept any values at all. Let’s ask GHCi about the type of Just and Nothing !

λ > : t Just Just :: a -> Maybe a λ > : t Nothing Nothing :: Maybe a

So Just has that function type – and it looks like, whatever type of value we give it, it becomes a Maybe of that type. Nothing , however, can conjure up whatever type it wants, without needing a value at all. Let’s play with that a bit:

λ > let nothingA = Nothing :: Maybe a λ > let nothingInt = Nothing :: Maybe Int λ > let nothingChar = Nothing :: Maybe Char λ > nothingInt == nothingChar \< interactive \>: 27 : 15 : error : • Couldn't match type ‘ Char ’ with ‘ Int ’ Expected type : Maybe Int Actual type : Maybe Char • In the second argument of ‘ ( == ) ’ , namely ‘ nothingChar ’ In the expression : nothingInt == nothingChar In an equation for ‘ it ’ : it = nothingInt == nothingChar λ > nothingA == nothingInt True λ > nothingA == nothingChar True

Woah – we get a type error when trying to compare nothingInt with nothingChar . That makes sense – (==) only works on values that have the same type. But then, wait, why does nothingA not complain when compared with nothingInt and nothingChar ?

The reason is that nothingA :: Maybe a really means:

I am a value of Maybe a , for any and all types a that you might provide to me.

So I’m seeing that we’re passing types to Maybe , in much the same way that we pass values to MkIntAndChar . Let’s ask GHCi about the type of Maybe !

λ > : type Maybe \< interactive \>: 1 : 1 : error : • Data constructor not in scope : Maybe • Perhaps you meant variable ‘ maybe ’ ( imported from Prelude )

Well, it turns out that types don’t have types (kind of, sort of). Types have kinds. We can ask GHCi about the kind of types with the :kind command:

λ > : kind Maybe Maybe :: * -> *

What is * doing there? Well, * is the kind of types which have values. Check this out:

λ > : kind Maybe Maybe :: * -> *

So Maybe has the kind * -> * , which means:

Give me a type that has values, and I will give you a type that has values.

Maybe you’ve heard about higher kinded polymorphism before. Let’s write a data type that demonstrates that this means:

data HigherKinded f a = Bare a | Wrapped ( f a )

Haskell’s kind inference is awfully kind on the fingers – since we use f applied to a , Haskell just knows that f must have the kind * -> * . If we ask GHCi about the kind of HigherKinded , we get back:

λ > : kind HigherKinded HigherKinded :: ( * -> * ) -> * -> *

So HigherKinded is a type that accepts a type of kind * -> * , and a type of kind * , and returns a type of kind * . In plain, verbose English, this reads as:

Give me two types: the first of which is a function that does not have values itself, but when given a type that does have values, it can have values. The second being a type that has values. Finally, I will return to you a type that can have ordinary values.

Dynamically Kinded Programming

* reminds me of regular expressions – “match anything.” Indeed, * matches any type that has values, or even types that are only inhabited by the infinite loop:

λ > data Void λ > : kind Void Void :: *

We don’t provide any ways to construct a void value, yet it still has kind * .

In the same way that you can productively program at the value level with dynamic types, you can productively program at the type level with dynamic kinds. And * is basically that!

Let’s encode our first type level numbers. We’ll start with the Peano natural numbers, where numbers are inductively defined as either Zero or the Successor of some natural number.

data Zero data Succ a type One = Succ Zero type Two = Succ One type Three = Succ Two type Four = Succ ( Succ ( Succ ( Succ Zero )))

But this is pretty unsatisfying. After all, there’s nothing that stops us from saying Succ Bool , which doesn’t make any sense. I’m pretty sold on the benefits of types for clarifying thinking and preventing errors, so abandoning the safety of types when I program my types just seems silly. In order to get that safety back, we need to introduce more kinds than merely * . For this, we have to level up our GHC.

Data Kinds

{-# LANGUAGE DataKinds #-}

The DataKinds extension allows us to promote data constructors into type constructors, which also promotes their type constructors into kind constructors. To promote something up a level, we prefix the name with an apostrophe, or tick: ' .

Now, let’s define our kind safe type level numbers:

data Nat = Zero | Succ Nat

In plain Haskell, this definition introduces a new type Nat with two value constructors, Zero and Succ (which takes a value of type Nat ). With the DataKinds extension, this also defines some extra new tidbits. We get a new kind Nat , which exists in a separate namespace. And we get two new types: a type constant 'Zero , which has the kind Nat , and a type constructor 'Succ , which accepts a type of kind Nat . Let’s ask GHCi about our new buddies:

λ > : kind 'Zero 'Zero :: Nat λ > : kind 'Succ 'Succ :: Nat -> Nat

You might think: that looks familiar! And it should. After all, the types look very much the same!

λ > : type Zero Zero :: Nat λ > : type Succ Succ :: Nat -> Nat

Where it can be ambiguous, the ' is used to disambiguate. Otherwise, Haskell can infer which you mean.

It’s important to note that there are no values of type 'Zero . The only kind that can have types that can have values is * .

We’ve gained the ability to construct some pretty basic types and kinds. In order to actually use them, though, we need a bit more power.

GADTs

{-# LANGUAGE GADTs #-}

You may be wondering, “What does GADT stand for?” Richard Eisenberg will tell you that they’re Generalized Algebraic Data Types, but that the terminology isn’t helpful, so just think of them as Gadts.

GADTs are a tool we can use to provide extra type information by matching on constructors. They use a slightly different syntax than normal Haskell data types. Let’s check out some simpler types that we’ll write with this syntax:

data Maybe a where Just :: a -> Maybe a Nothing :: Maybe a

The GADT syntax lists the constructors line-by-line, and instead of providing the fields of the constructor, we provide the type signature of the constructor. This is an interesting change – I just wrote out a -> Maybe a . That suggests, to me, that I can make these whatever type I want.

data IntBool a where Int :: Int -> IntBool Int Bool :: Bool -> IntBool Bool

This declaration creates a new type IntBool , which has the kind * -> * . It has two constructors: Int , which has the type Int -> IntBool Int , and Bool , which has the type Bool -> IntBool Bool .

Since the constructors carry information about the resulting type, we get bonus information about the type when we pattern match on the constructors! Check this signature out:

extractIntBool :: IntBool a -> a extractIntBool ( Int _ ) = 0 extractIntBool ( Bool b ) = b

Something really interesting is happening here! When we match on Int , we know that IntBool a ~ IntBool Int . That ~ tilde is a symbol for type equality, and introduces a constraint that GHC needs to solve to type check the code. For this branch, we know that a ~ Int , so we can return an Int value.

We now have enough power in our toolbox to implement everyone’s favorite example of dependent types: length indexed vectors!

Vectors

Length indexed vectors allow us to put the length of a list into the type system, which allows us to statically forbid out-of-bounds errors. We have a way to promote numbers into the type level using DataKinds , and we have a way to provide bonus type information using GADTs . Let’s combine these two powers for this task.

I’ll split this definition up into multiple blocks, so I can walk through it easily.

data Vector ( n :: Nat ) a where

We’re defining a type Vector with kind Nat -> * -> * . The first type parameter is the length index. The second type parameter is the type of values contained in the vector. Note that, in order to compile something with a kind signature, we need…

{-# LANGUAGE KindSignatures #-}

Thinking about types often requires us to think in a logical manner. We often need to consider things inductively when constructing them, and recursively when destructing them. What is the base case for a vector? It’s the empty vector, with a length of Zero .

VNil :: Vector 'Zero a

A value constructed by VNil can have any type a , but the length is always constrained to be 'Zero .

The inductive case is adding another value to a vector. One more value means one more length.

VCons :: a -> Vector n a -> Vector ( 'Succ n ) a

The VCons constructor takes two values: one of type a , and another of type Vector n a . We don’t know how long the Vector provided is – it can be any n such that n is a Nat ural number. We do know that the resulting vector is the Succ essor of that n umber, though.

So here’s the fully annotated and explicit definition:

data Vector ( n :: Nat ) ( a :: * ) where VNil :: Vector 'Zero a VCons :: a -> Vector n a -> Vector ( 'Succ n ) a

Fortunately, Haskell can infer these things for us! Whether you use the above explicit definition or the below implicit definition is a matter of taste, aesthetics, style, and documentation.

data Vector n a where VNil :: Vector Zero a VCons :: a -> Vector n a -> Vector ( Succ n ) a

Let’s now write a Show instance for these length indexed vectors. It’s pretty painless:

instance Show a => Show ( Vector n a ) where show VNil = "VNil" show ( VCons a as ) = "VCons " ++ show a ++ " (" ++ show as ++ ")"

That n type parameter is totally arbitrary, so we don’t have to worry about it too much.

The Vector API

As a nice exercise, let’s write append :: Vector n a -> Vector m a -> Vector ??? a . But wait, what is ??? going to be? It needs to represent the addition of these two natural numbers. Addition is a function. And we don’t have type functions, right? Well, we do, but we have to upgrade our GHC again.

{-# LANGUAGE TypeFamilies #-}

For some reason, functions that operate on types are called type families. There are two ways to write a type family: open, where anyone can add new cases, and closed, where all the cases are defined at once. We’ll mostly be dealing with closed type families here.

So let’s figure out how to add two Nat ural numbers, at the type level. For starters, let’s figure out how to add at at the value level first.

add :: Nat -> Nat -> Nat

This is the standard Haskell function definitions we all know and love. We can pattern match on values, write where clauses with helpers, etc.

We’re working with an inductive definition of numbers, so we’ll need to use recursion get our answer. We need a base case, and then the inductive case. So lets start basic: if we add 0 to any number, then the answer is that number.

add Zero n = n

The inductive case asks:

If we add the successor of a number ( Succ n ) to another number ( m ), what is the answer?

Well, we know we want to get to Zero , so we want to somehow shrink our problem a bit. We’ll have to shift that Succ from the left term to the right term. Then we can recurse on the addition.

add ( Succ n ) m = add n ( Succ m )

If you imagine a natural number as a stack of plates, we can visualize the addition of two natural numbers as taking one plate off the top of the first stack, and putting it on top of the second. Eventually, we’ll use all of the plates – this leaves us with Zero plates, and our final single stack of plates is the answer.

add :: Nat -> Nat -> Nat add Zero n = n add ( Succ n ) m = add n ( Succ m )

Alright, let’s promote this to the type level.

Type Families

The first line of a type family definition is the signature:

type family Add n m where

This introduces a new type function Add which accepts two parameters. We can now define the individual cases. We can pattern match on type constructors, just like we can pattern match on value constructors. So we’ll write the Zero case:

Add 'Zero n = n

Next, we recurse on the inductive case:

Add ( 'Succ n ) m = Add n ( 'Succ m )

Ahh, except now GHC is going to give us an error.

• The type family application ‘Add n ('Succ m)’ is no smaller than the instance head (Use UndecidableInstances to permit this) • In the equations for closed type family ‘Add’ In the type family declaration for ‘Add’

GHC is extremely scared of undecidability, and won’t do anything that it can’t easily figure out on it’s own. UndecidableInstances is an extension which allows you to say:

Look, GHC, it’s okay. I know you can’t figure this out. I promise this makes sense and will eventually terminate.

So now we get to add:

{-# LANGUAGE UndecidableInstances #-}

to our file. The type family definition compiles fine now. How can we test it out?

Where we used :kind to inspect the kind of types, we can use :kind! to evaluate these types as far as GHC can. This snippet illustrates the difference:

λ > : kind Add ( Succ ( Succ Zero )) ( Succ Zero ) Add ( Succ ( Succ Zero )) ( Succ Zero ) :: Nat λ > : kind ! Add ( Succ ( Succ Zero )) ( Succ Zero ) Add ( Succ ( Succ Zero )) ( Succ Zero ) :: Nat = 'Succ ( 'Succ ( 'Succ 'Zero ))

The first line just tells us that the result of Add ing two Nat ural numbers is itself a Nat ural number. The second line shows the actual result of evaluating the type level function. Cool! So now we can finally finish writing append .

append :: Vector n a -> Vector m a -> Vector ( Add n m ) a

Let’s start with some bad attempts, to see what the types buy us:

append VNil rest = VNil

This fails with a type error – cool!

• Could not deduce: m ~ 'Zero from the context: n ~ 'Zero bound by a pattern with constructor: VNil :: forall a. Vector 'Zero a, in an equation for ‘append’ at /home/matt/Projects/dep-types.hs:31:8-11 ‘m’ is a rigid type variable bound by the type signature for: append :: forall (n :: Nat) a (m :: Nat). Vector n a -> Vector m a -> Vector (Add n m) a at /home/matt/Projects/dep-types.hs:30:11 Expected type: Vector (Add n m) a Actual type: Vector 'Zero a • In the expression: VNil In an equation for ‘append’: append VNil rest = VNil • Relevant bindings include rest :: Vector m a (bound at /home/matt/Projects/dep-types.hs:31:13) append :: Vector n a -> Vector m a -> Vector (Add n m) a (bound at /home/matt/Projects/dep-types.hs:31:1)

The error is kinda big and scary at first. Let’s dig into it a bit.

GHC is telling us that it can’t infer that m (which is the length of the second parameter vector) is equal to Zero . It knows that n (the length of the first parameter) is Zero because we’ve pattern matched on VNil . So, what values can we return? Let’s replace the definition we have thus far with undefined , reload in GHCi, and inspect some types:

λ> :t append VNil append VNil :: Vector m a -> Vector m a

We need to construct a value Vector m a , and we have been given a value Vector m a . BUT – we don’t know what m is! So we have no way to spoof this or fake it. We have to return our input. So our first case is simply:

append VNil xs = xs

Like with addition of natural numbers, we’ll need to have the inductive case. Since we have the base case on our first parameter, we’ll want to try shrinking our first parameter in the recursive call.

So let’s try another bad implementation:

append ( VCons a rest ) xs = append rest ( VCons a xs )

This doesn’t really do what we want, which we can verify in the REPL:

λ > append ( VCons 1 ( VCons 3 VNil )) ( VCons 2 VNil ) VCons 3 ( VCons 1 ( VCons 2 ( VNil )))

The answer should be VCons 1 (VCons 3 (VCons 2 VNil)) . However, our Vector type only encodes the length of the vector in the type. The sequence is not considered. Anything that isn’t lifted into the type system doesn’t get any correctness guarantees.

So let’s fix the implementation:

append ( VCons a rest ) xs = VCons a ( append rest xs )

And let’s reload in GHCi to test it out!

λ> :reload [1 of 1] Compiling DepTypes ( /home/matt/Projects/dep-types.hs, interpreted ) /home/matt/Projects/dep-types.hs:32:28: error: • Could not deduce: Add n1 ('Succ m) ~ 'Succ (Add n1 m) from the context: n ~ 'Succ n1 bound by a pattern with constructor: VCons :: forall a (n :: Nat). a -> Vector n a -> Vector ('Succ n) a, in an equation for ‘append’ at /home/matt/Projects/dep-types.hs:32:9-20 Expected type: Vector (Add n m) a Actual type: Vector ('Succ (Add n1 m)) a • In the expression: VCons a (append rest xs) In an equation for ‘append’: append (VCons a rest) xs = VCons a (append rest xs) • Relevant bindings include xs :: Vector m a (bound at /home/matt/Projects/dep-types.hs:32:23) rest :: Vector n1 a (bound at /home/matt/Projects/dep-types.hs:32:17) append :: Vector n a -> Vector m a -> Vector (Add n m) a (bound at /home/matt/Projects/dep-types.hs:31:1) Failed, modules loaded: none.

Oh no! A type error! GHC can’t figure out that Add n (Succ m) is the same as Succ (Add n m) . We can kinda see what went wrong if we lay the Vector , Add and append definitions next to each other:

data Vector n a where VNil :: Vector Zero a VCons :: a -> Vector n a -> Vector ( Succ n ) a type family Add x y where Add 'Zero n = n Add ( 'Succ n ) m = Add n ( 'Succ m ) append :: Vector n a -> Vector m a -> Vector ( Add n m ) a append VNil xs = xs append ( VCons a rest ) xs = VCons a ( append rest xs )

In Vector ’s inductive case, we are building up a bunch of Succ s. In Add ’s recursive case, we’re tearing down the left hand side, such that the exterior is another Add . And in append s recursive case, we’re building up the right hand side. Let’s trace how this error happens, and supply some type annotations as well:

append ( VCons a rest ) xs =

Here, we know that VCons a rest has the type Vector (Succ n) a , and xs has the type Vector m a . We need to produce a result of type Vector (Add (Succ n) m) a in order for the type to line up right. We use VCons a (append rest xs) . VCons has a length value that is the Succ essor of the result of append rest xs , which should have the value Add n m , so the length there is Succ (Add n m) . Unfortunately, our result type needs to be Add (Succ n) m .

We know these values are equivalent. Unfortuantely, GHC cannot prove this, so it throws up it’s hands. Two definitions, which are provably equivalent, are structurally different, and this causes the types and proofs to fail. This is a HUGE gotcha in type level programming – the implementation details matter, a lot, and they leak, hard. We can fix this by using a slightly different definition of Add :

type family Add x y where Add 'Zero n = n Add ( 'Succ n ) m = 'Succ ( Add n m )

This definition has a similar structure of recursion – we pull the Succ s out, which allows us to match the way that VCons adds Succ on top.

This new definition compiles and works fine.

This Sucks

Agreed, which is why I’ll defer the interested reader to this much better tutorial on length indexed vectors in Haskell. Instead, let’s look at some other more interesting and practical examples of type level programming.

Heterogeneous Lists

Heterogeneous lists are kind of like tuples, but they’re defined inductively. We keep a type level list of the contents of the heterogeneous list, which let us operate safely on them.

To use ordinary Haskell lists at the type level, we need another extension:

{-# LANGUAGE TypeOperators #-}

which allows us to use operators at the type level.

Here’s the data type definition:

data HList xs where HNil :: HList '[ ] ( ::: ) :: a -> HList as -> HList ( a ': as ) infixr 6 :::

The HNil constructor has an empty list of values, which makes sense, because it doesn’t have any values! The ::: construction operator takes a value of type a , an HList that already has a list of types as that it contains, and returns an HList where the first element in the type level list is a followed by as .

Let’s see what a value for this looks like:

λ > : t 'a' ::: 1 ::: "hello" ::: HNil 'a' ::: 1 ::: "hello" ::: HNil :: HList '[ C har , Int , String ]

So now we know that we have a Char , Int , and String contained in this HList , and their respective indexes. What if we want to Show that?

λ > 'a' ::: 1 ::: "hello" ::: HNil \< interactive \>: 13 : 1 : No instance for ( Show ( HList '[ C har , Int , String ])) arising from a use of ‘ print ’ In the first argument of ‘ print ’ , namely ‘ it ’ In a stmt of an interactive GHCi command : print it

Hmm. We’ll need to write a Show instance for HList . How should we approach this? Let’s try something dumb first. We’ll ignore all the contents!

instance Show ( HList xs ) where show HNil = "HNil" show ( x ::: rest ) = "_ ::: " ++ show rest

Ahah! this compiles, and it even works!

λ > 'a' ::: 1 ::: "hello" ::: HNil _ ::: _ ::: _ ::: HNil

Unfortunately, it’s not very useful. Can we do better? We can!

Inductive Type Class Instances

First, we’ll define the base case – showing an empty HList!

instance Show ( HList '[ ] ) where show HNil = "HNil"

This causes a compile error, requiring that we enable yet another language extension:

{-# LANGUAGE FlexibleInstances #-}

If you’re doing this in another file than the type family above, you’ll also get an error about FlexibleContexts . It turns out that enabling UndecidableInstances implies FlexibleContexts for some reason. So let’s throw that one on too, for good measure:

{-# LANGUAGE FlexibleContexts #-}

This compiles, and we can finally show HNil and it works out. Now, we must recurse!

The principle of induction states that:

We must be able to do something for the base case. If we can do something for a random case, then we can do it for a case that is one step larger. By 1 and 2, you can do it for all cases.

We’ve covered that base case. We’ll assume that we can handle the smaller cases, and demonstrate how to handle a slightly large case:

instance ( Show ( HList as ), Show a ) => Show ( HList ( a ': as )) where show ( a ::: rest ) = show a ++ " ::: " ++ show rest

This instance basically says:

Given that I know how to Show an HList of as , and I know how to Show an a : I can Show an HList with an a and a bunch of as .

λ > 'a' ::: 1 ::: "hello" ::: HNil 'a' ::: 1 ::: "hello" ::: HNil

Further Exercises

Write an aeson instance for HList . It’ll be similar to the Show instance, but require a bit more stuff.

Extensible Records

There are a few variants on extensible records in Haskell. Here’s a tiny implementation that requires yet more extensions:

{-# LANGUAGE PolyKinds #-} {-# LANGUAGE TypeApplications #-} import GHC.TypeLits ( KnownSymbol , symbolVal ) import Data.Proxy

This generalizes definitions for type variables, which allows for non-value type variables to have kind polymorphism. Type applications allow us to explicitly pass types as arguments using an @ symbol.

First, we must define the type of our fields, and then our record:

newtype s >> a = Named a data HRec xs where HEmpty :: HRec '[ ] HCons :: ( s >> a ) -> HRec xs -> HRec ( s >> a ': xs )

The s parameter is going to be a type with the kind Symbol . Symbol is defined in GHC.TypeLits , so we need that import to do the fun stuff.

We’ll construct a value using the TypeApplications syntax, so a record will look like:

λ > HCons ( Named @ "foo" 'a' ) ( HCons ( Named @ "bar" ( 3 :: Int )) HEmpty ) \< interactive \>: 10 : 1 : error : • No instance for ( Show ( HRec '[ " foo " >> Char, " bar " >> Int])) arising from a use of ‘print’ • In a stmt of an interactive GHCi command: print it

So, this type checks fine! Cool. But it does not Show, so we need to define a Show instance.

Those string record fields only exist at the type level – but we can use the KnownSymbol class to bring them back down to the value level using symbolVal .

Here’s our base case:

instance Show ( HRec '[ ] ) where show _ = "HEmpty"

And, when we recurse, we need a tiny bit more information. Let’s start with the instance head first, so we know what variables we need:

instance Show ( HRec ( s >> a ': xs )) where

OK, so we have a s type, which has the kind Symbol , an a :: * , and xs . So now we pattern match on that bad boy:

instance Show ( HRec ( s >> a ': xs )) where show ( HCons ( Named a ) rest ) =

OK, so we need to show the a value. Easy. Which means we need a Show a constraint tacked onto our instance:

instance ( Show a ) => Show ( HRec ( s >> a ': xs )) where show ( HCons ( Named a ) rest ) = let val = show a

Next up, we need the key as a string. Which means we need to use symbolVal , which takes a proxy s and returns the String associated with the s provided that s is a KnownSymbol .

instance ( Show a , KnownSymbol s ) => Show ( HRec ( s >> a ': xs )) where show ( HCons ( Named a ) rest ) = let val = show a key = symbolVal ( Proxy :: Proxy s )

At this point, you’re probably going to get an error like No instance for 'KnownSymbol s0' . This is because Haskell’s type variables have a very limited scope by default. When you write:

topLevelFunction :: a -> ( a -> b ) -> b topLevelFunction a = go where go :: ( a -> b ) -> b go f = f a

Haskell interprets each type signature as it’s own scope for the type variables. This means that the a and b variables in the go helper function are different type variables, and a more precise way to write it would be:

topLevelFunction :: a0 -> ( a0 -> b0 ) -> b0 topLevelFunction a = go where go :: ( a1 -> b1 ) -> b1 go f = f a

If we want for type variables to have a scope similar to other variables, we need another extension:

{-# LANGUAGE ScopedTypeVariables #-}

Finally, we need to show the rest of the stuff!

instance ( Show a , KnownSymbol s , Show ( HRec xs )) => Show ( HRec ( s >> a ': xs )) where show ( HCons ( Named a ) rest ) = let val = show a key = symbolVal ( Proxy :: Proxy s ) more = show rest in "(" ++ key ++ ": " ++ val ++ ") " ++ more

This gives us a rather satisfying Show instance, now:

λ > HCons ( Named @ "foo" 'a' ) ( HCons ( Named @ "bar" ( 3 :: Int )) HEmpty ) ( foo : 'a' ) ( bar : 3 ) HEmpty

Exercise:

Write an Aeson ToJSON instance for this HRec type which converts into a JSON object.

Bonus points: Write an Aeson FromJSON instance for the HRec type.

Like what you read?

If you enjoyed this post, you should check out the book Thinking with Types by Sandy Maguire. It is an extensive manual on practical type-level programming in Haskell.