Motivating the Foldable Type Class

Posted on September 16, 2016

Something I have never seen articulated is why the Foldable type class exists. It is lawless apart from the free theorems which leads to ad-hoc definitions of its methods. What use is the abstraction if not to enable us to reason more easily about our programs? This post aims to articulate some justification stemming from the universality of folds.

In brief, here is the argument.

  1. For inductive data types, the fold is unique defined as a consequence of initiality.
  2. The Foldable type class is a way to exploit this universality without having to define all of our data types as the fixed points of base functors.
  3. The uneasiness comes from this impedence mismatch between points 1 and 2.

To recall, the type class is meant to capture the intuitive notion of a fold. Folds are a way of consuming a data type by summarising values in a uniform manner before combining them together.

We now recall the basics of initial algebra semantics for polynomial data types.1 We can represent all data types as the fixed point of a polynomial functor. In Haskell we can represent the fixed point by the data type Mu.

data Mu f = Mu { out :: (f (Mu f)) }

-- Inital algebra
in :: f (Mu f) -> Mu f
in = Mu

We then specify data types by first defining a control functor \(F\) and then considering the initial \(F\)-algebra for the functor. The initial \(F\)-algebra is given by \((\mu F, in)\). The injection function \(in\) wraps up one level of the recursion. The projection function out strips off one layer of the recursion.2

We can define the type of lists by first specifying a control functor \(ListF = 1 + (A \times \_)\) and then defining lists in terms of this base functor and Mu.

data ListF a r = Nil | Cons a r

type ListM a = Mu (ListF a)

We call types which are definable in this manner inductive types.

We do not usually define data types in this style as programming directly with them is quite cumbersome as one must wrap and unwrap to access the recursive structure.

However, defining data in this manner has some useful properties. The one that we care about is that it is possible to define a generic fold operator for inductive types.

cata :: (f a -> a) -> Mu f -> a
cata f = f . fmap (cata f) . out

What’s more, due to initiality, cata f is the unique function of this type. We have no choice about how we define a fold operator after we have described how to interpret the control functor.

Fleshed out in some more detail, Given a functor \(F\), for any other algebra \((B, g : F B \to B)\) there exists a unique map \(h\) to this algebra from \((\mu F, in)\). Our definition of cata is precisely the way to construct this unique map.

Real-World Haskell

Languages such as Haskell allow users to define data types in a more ad-hoc fashion by specifying the recursive structure themselves rather than in terms of a base functor.

data List a = Nil | Cons a (List a)

It can be easily seen that Mu (ListF a) ~= List a and thus we can exploit the the uniqueness of the fold function and define a canonical fold function specialised to our newly defined data type.

foldr :: (a -> b -> b) -> b -> List a -> b

foldr is a specialisation of cata to lists. It is perhaps clearer to see the correspondence if we rewrite the function to explicitly take a list algebra as it’s first argument.

data ListAlg a b = ListAlg { z :: () -> b , cons :: (a, b) -> b }

foldr :: ListAlg a b -> List a -> b

Specifying a function ListF a b -> b is precisely the same as specifying ListAlg a b as it amounts to specifying functions \(1 \to b\) and \(a \times b \to b\).

So, for each data type we define we can specialise the cata operator in order to define a canonical fold operator. However, the issue now is that each one of our fold operators has a different type. It would be useful to still be able to provide a consistent interface so that we can still fold any inductive type. The answer to this problem is Foldable.

This highlights the essential tension with the Foldable type class. It exists in order to be able to continue to define a generic fold operation but without the cost of defining our data types in terms of fixed points and base functors.


The method foldr is the only method needed to define an instance of Foldable.3

class Foldable f where
  foldr :: (a -> b -> b) -> b -> t a -> b

It turns out that (a -> b -> b) and a single constant b are sufficient for specifying algebras for inductive types. Inductive types are built from polynomial base functors so we can describe an algebra by first matching on the summand and then iteratively applying the combining function to combine each recursive position. If there are no recursive positions, we instead use the zero value z.

Defining the instance for lists is straightforward:

instance Foldable [] where
  foldr _ z [] = z
  foldr f _ (x:xs) = f x (foldr f xs)

As another example, we consider writing an instance for binary trees which only contain values in the leaves. It is less obvious then how to implement foldr as the usual fold (foldTree below) has a different type signature.

data Tree a = Branch (Leaf a) (Leaf a) | Leaf a

foldTree :: (b -> b -> b) -> (a -> b) -> Tree a -> b

We can do so by cleverly instantiating the result type b when performing the recursive calls.

instance Foldable Tree where
  foldr :: (a -> b -> b) -> b -> Tree a -> b
  foldr f z t =
    case t of
      Leaf a -> f a z
      Branch l r -> foldr (\a c -> f a . c) id l
                   		(foldr f z r)

The first recursive call of foldr returns a function of type b -> b which tells us how to combine the next recursive occurence. In this case there are only two recursive positions but this process can be iterated to combine all the recursive holes.4

The definition for foldMap usually provides a more intuitive interface for defining instances but it is harder to motivate which is why we prefer foldr.

foldMapTree :: Monoid m => (a -> m) -> Tree a -> m
foldMapTree f (Leaf a) = f a
foldMapTree f (Branch l r) = foldMapTree f l <> foldMapTree f r

However, instances for inductive types defined in this uniform manner are less powerful than folds induced by an \(F\)-algebra. The problem comes from the fact that all the recursive holes much be combined in a uniform fashion.

The question I have, is it possible to define middle using the Foldable interface?

data Tree3F a r = Leaf a | Branch r r r

type Tree3 a = Mu (Tree3F a)

middleFold :: Tree3F a a -> a
middleFold (Leaf a) = a
middleFold (Branch _ m _) = m

middle :: Tree3 a -> a
middle = cata middleFold


The definition of Foldable is motivated by the well-understood theory of inductive data types. The pragmatics of Haskell lead us to the seemingly quite ad-hoc class definition which has generated much discussion in recent years. The goal of this post was to argue that the class is better founded than people think and to explain some of the reasons that it leads to some uncomfort.

My argument is not about deciding whether an ad-hoc definition is lawful, it is explaining the motivation for the class in a way which also explains the lawlessness. The class definition is a compromise because of the practicalities of Haskell. The only way in which we can know a definition is sensible or not is by inspecting whether the ad-hoc definition agrees with the canonical definition given by cata.

Appendix: Free Theorems of foldr

There are some free theorems for foldr which is natural in a and b.

foldr :: (a -> b -> b) -> b -> t a -> b

Naturality in b amounts to, for all functions g : b -> c.

g (foldr f z t) = foldr (\x y -> f x (g y)) (g z)

and naturality in a amounts to, for all functions f : c -> a.

foldr f z . fmap h = foldr (\x y -> f (h x) y) z

These are included for completeness.

  1. From now on when we say data type, we mean polynomial data type.

  2. Lambek’s lemma tells us that the two functions are each other’s inverse.

  3. Notice that we are only able to fold type constructors of kind * -> *, this is an arbritary choice, motivated by the fact that most containers which we wish to fold are polymorphic in one way. (For example, lists and trees).

  4. Note that I didn’t think of this definiton myself but arrived at it purely calculationally from the definition of foldMap and foldr.