# Reflecting strictness in Haskell types

In GHC, from the operational point of view, the type Int does not indicate a bit pattern somewhere in memory that represents an integer. What it indicates is either an integer bit pattern or a “thunk” (a delayed computation) which can be “forced” (run). When and if the computation terminates the thunk will be overwritten with the integer bit pattern that it produced.

Thus the GHC type system provides less fine-grained information than we might naively expect, especially if we are used to the strict point of view. Often the ability to invisibly interchange thunks and values is a blessing. In fact it is one of Haskell’s great blessings. However, it is well known that it can also be a curse. Here’s an example:

foldl :: (a -> b -> a) -> a -> [b] -> a
foldl _ z [] = z
foldl f z (b:bs) = foldl f (f z b) bs

The application of f to z and b does not result in an evaluated a. Instead it results in a thunk representing the function call. If the input list is of length n we make n recursive calls and build up a thunk whose size is proportional to n. This leaks space.

The way to avoid a space leak is to explicitly force the a we have created with a call to seq before each recursive call.

foldl' :: (a -> b -> a) -> a -> [b] -> a
foldl' _ z [] = z
foldl' f z (b:bs) = a seq foldl f a bs
where a = f z b

This way the a remains completely evaluated at each stage.

This is a reasonable solution, but as Haskellers we are used to our types specifying very fine-grained information about the operation of our program. We want our types to specify when IO actions can occur, so why not ask for our types to specify when evaluation of thunks takes place?

Unfortunately this isn’t straightforward to come by. For example, we might try

data Strict a = Strict !a

foldl :: (a -> b -> a) -> Strict a -> [b] -> a
foldl _ (Strict z) [] = z
foldl f (Strict z) (b:bs) = foldl f (Strict (f z b)) bs

But this is no good. After all, a Strict a doesn’t represent a strict a but rather a thunk returning a strict a! So we build up a chain of thunks nonetheless. In fact there is no difference in terms of laziness between a and our attempted Strict a. Both of them are just thunks that can be forced to return an a.

However, there is a trick that allows us to represent strictness in types. The trick is to indicate strictness in the argument to a function rather than its return type. I learned this from a post of Stefan Holdermans to the Haskell-Cafe mailing list.

{-# LANGUAGE TypeOperators #-}

data a :-> b = Strict (a -> b)
-- Strict constructor will be hidden

-- Specifying the precedence of :-> merely for neater syntax
infixr 0 :->

strictly :: (a -> b) -> a :-> b
strictly f = Strict (\a -> a seq f a)

(!) :: (a :-> b) -> a -> b
Strict f ! a = f a

Then we can write a recursive foldl which is guaranteed to be space leak free because it has the right type.

foldl' :: (a -> b -> a) -> a :-> [b] -> a
foldl' f = strictly (\z xs -> case xs of
[]   -> z
y:ys -> foldl' f !(f z y) $ys) The value whose type is on the left hand side of a :-> is guaranteed to be evaluated strictly, i.e. forced before the result can start to be consumed. ## Polymorphic strictness What do we do if we want to define functions which are polymorphic over strictness type? For example the standard definition of const doesn’t touch its b argument when its return value is evaluated. const :: a -> b -> a const a b = a On the other hand we can define another version which does const' :: a -> b -> a const' a b = b seq a How do we implement both of these with one definition? Well, we can introduce a class to capture the general concept with instances for (->) and (:->). (The need for the notation arrow instead of something symbolic is a syntactic annoyance. I’m not sure how to get round it.) class FunctionLike arrow where (?) :: (a arrow b) -> a -> b functionLike :: (a -> b) -> (a arrow b) instance FunctionLike (->) where (?) = id functionLike = id instance FunctionLike (:->) where (?) = (!) functionLike = strictly Then we can define polymorphic const as constPolymorphic :: FunctionLike arrow => a -> b arrow a constPolymorphic a = functionLike (\_ -> a) and use it to directly derive the two specialisations that we want. const :: a -> b -> a const = constPolymorphic const' :: a -> b :-> a const' = constPolymorphic If we were so inclined we could use FunctionLike to define the leaky and leak free versions of foldl at the same time! foldlPolymorphic :: FunctionLike arrow => (a -> b -> a) -> a arrow ([b] -> a) foldlPolymorphic f = functionLike (\z xs -> case xs of [] -> z y:ys -> foldl' f ?(f z y)) The operator ? should be interpreted as function application which is polymorphic over strictness. ## Strictness in data types Even more amazingly, gelisam on Haskell Reddit showed me how to make data types that are strictness polymorphic! The key observation is that the only difference between the usual, lazy data Foo a = Foo a and the strict data Foo a = Foo !a is that the function which constructs Foos is lazy in its argument for the former, and strict in its argument for the latter. If we want to be polymorphic over strict and lazy lists, for example, we can define data List (arrow :: * -> * -> *) a = Nil | Cons a (List arrow a) -- The List constructor will have to be hidden, although pattern -- matching on it would be OK. arrow is a phantom type which we -- use as a strictness indicator. -- We expose this polymorphic cons instead cons :: FunctionLike arrow => a arrow (List arrow a arrow List arrow a) cons = functionLike (\x -> functionLike (\y -> Cons x y)) (Again I apologise for the syntax. Hopefully someone knowledgeable can tell me what to do about that.) A List (->) a is a lazy list of a, and a List (:->) a is a strict list of a. We can define data values in a way that is polymorphic over strictness type, for example enumerating all integers in a range. range :: FunctionLike arrow => Int -> Int -> List arrow Int range a b = if a > b then Nil else cons ?a ?(range (a+1) b) (Recall that the operator ? should be interpreted as function application which is polymorphic over strictness.) Then count 1 1000000 :: List (->) Int is a lazy list where the one million elements are computed as required. count 1 1000000 :: List (:->) Int is a strict list where all one million elements are computed at once. ## Wadler’s “strictness monad” Wadler talks about a “strictness monad” in section 3.2 on page 9 of Comprehending Monads but I don’t think it solves the problem I want it to solve. For example, consider foldl :: (a -> b -> a) -> Str a -> [b] -> Str a foldl _ z [] = z foldl f z (b:bs) = foldl f (f <$> z <*> pure b) bs

This still builds up a chain of thunks in the same way that our original Strict attempt did. All the Str monad seems to achieve is enforcing an ordering of evaluations with respect to each other. Perhaps there’s a way of getting the desired behaviour with a cleverer usage of Str, but I don’t see it.

## Conclusion

Strictness in Haskell is generally hidden away and not reflected by types, but there does seem to be a way of representing strictness in the type system!