According to Wikipedia a catamorphism “denotes the unique homomorphism from an initial algebra into some other algebra”.

Uh huh. Sure.

I’ve got an admittedly very basic understanding of this concept, but I thought I’d share the small amount I have been able to learn and apply, as I’ve found it to be a useful tool for working with types.

Cat a what?

The word catamorphism comes from the Greek κατά, meaning “downwards”, and “morphism” which we tend to use to mean “transformation”. So it’s a transformation that takes something down, or reduces something.

What’s this mean in terms of functional programming? Remember from a while back, an endomorphism, or “inside transformation”, transforms a value of some type into a value of the same type? Well a catamorphism takes a value of a type with some structure, and reduces that to a value of another type.

Call me Option

To explore this idea, let’s define our own version of the Maybe type:

data Option a = Empty | Full a

A value of this type can either be Empty, or Full someValue. Now let’s say we want to convert an Option a to some type b. We need to get at the structure of our Option type, and work out how to convert each alternative to a b. We can do this using pattern matching:

option :: b -> (a -> b) -> Option a -> b
option valIfEmpty _ Empty = valIfEmpty
option _ f (Full a) = f a

The first argument to option is the default value of type b that will be returned when the option is Empty. The second argument is a function that will convert the value in a Full value to a b. The final argument is the option we are reducing.

We then have two patterns to match for Option a values. The first pattern is matched when the option is Empty, in which case the default value is returned. The second pattern is when we have a Full value, where we return the result of applying the function from the second argument f to that value. Here’s a quick example of it in action:

ghci> option "empty" show (Full 42)
ghci> option "empty" show Empty

So we’ve taken a type that has two possible components, and Empty and Full value, and created a function that transforms it into a type with a potentially reduced number of components. A downward transformation. A catamorphism. And we can now use this transformation to break apart our Option type without having to repeat that pattern matching everywhere.

Aside: Haskell has a built-in maybe function that works the same way for the Maybe type.

Catamorphisms and identity

Catamorphisms have an interesting property: if we use the type’s value constructors as arguments to the type’s catamorphism, we get the identity function for that type.

Our Option type has two value constructors. We can construct a value of type Option a using the Empty constructor, or using Full value. Let’s use these as arguments to the option function:

ghci> :t Empty
Empty :: Option a
ghci> :t Full
Full :: a -> Option a
ghci> :t option
option :: b -> (a -> b) -> Option a -> b

ghci> option Empty Full (Full 42)
Full 42
ghci> option Empty Full (Empty)
ghci> quickCheck $ \x -> id x == option Empty Full x
+++ OK, passed 100 tests.

Whatever value we pass to option Empty Full, we always get the same value back. This is a result of the option catamorphism deconstructing the Option type, so feeding in the constructors for that type reconstructs the type unchanged.

We can follow this pattern of matching value constructors to implement a catamorphism for any type:

data Foo = Bar Int | Zap String [Int] | Giraffe String
    deriving (Show, Eq)

-- Add an argument for each value constructor:
foo :: (Int -> b) -> (String -> [Int] -> b) -> (String -> b) -> Foo -> b
foo f _ _ (Bar x) = f x
foo _ f _ (Zap x y) = f x y
foo _ _ f (Giraffe x) = f x

{-  ghci> quickCheck $ \x -> id x == foo Bar Zap Giraffe x
    +++ OK, passed 100 tests.

The list catamorphism

To finish up, let’s look at a very well known catamorphism. In Haskell there are two ways to construct a list. The first is to use : (cons) to add an element to an existing list, x : list. The second is using the empty list constructor []. Now let’s have a look at this function:

foldr :: (a -> b -> b) -> b -> [a] -> b

The first two arguments to fold right match the value constructors for lists. The first takes a list item and a b used for accumulating the result of recursive calls, mirroring the calls used to construct the list. The second is the value used in the case of the empty list [].

ghci> quickCheck $ \x -> id x == foldr (:) [] x
+++ OK, passed 100 tests.

Which is why foldr is also know as the list catamorphism.

Parting thoughts

Catamorphisms, at least as I understand them, aren’t nearly as frightening as they sound. A catamorphism for a type is function for transforming it, deconstructing the type into its components and providing us the option to reduce the type to a simpler structure (reduced number of components). One result of this is that plugging in the type’s value constructors will reassemble the type, giving us an identity function for the type.

If you’ve read any of my posts on list folds you’ll probably have some appreciation for how useful catamorphisms can be. Whereas foldr lets us encapsulate list recursion, catamorphisms for other types like Maybe (or Option) let us deal with the constituent parts of a type, without having to repeat pattern matching on the type every time we wish to transform it.

Hope you found this interesting! As always, please ask away if you have any questions or if I’ve failed to explain something adequately.