In the origami style of programming, higher-order recursion operators such as map, fold and unfold captures the structure of programs. These operators have two aspects: mapping and accumulating.
The Essence of the Iterator Pattern by Jeremy Gibbons and Bruno C. d. S. Oliveira show that applicative functors and the corresponding traverse
operator capture the essence of the ITERATOR pattern providing both mapping and accumulating. This explains why Haskell’s Applicative
and Traversable
work so well for many data types!
But in this post, instead of reiterating the paper, we are going to review one of the earlier approach which provides recursion operators in datatype-generic way. Surprisingly, what we need is only bifunctors.
This post is in literate Haskell, so let’s start with a list of GHC extensions and imports:
> {-# LANGUAGE DeriveFunctor #-}
> {-# LANGUAGE TemplateHaskell #-}
>
> import Data.Bifunctor
> import Data.Bifunctor.TH
Data.Bifunctor.TH
provides a TemplateHaskell
macro deriveBifunctor
, which automatically derives the Bifunctor
instance. This is possible because all sum-of-product data types induce bifunctors. Here’s our favorite list data type.
> data ListF a r = Nil | Cons a r deriving Functor
> deriveBifunctor ''ListF
Fix
is the fixed point of a Bifunctor
.
> newtype Fix s a = In { out :: s a (Fix s a) }
Then we define List
as a fixed point of ListF
.
> type List = Fix ListF
To map over an arbitrary data type defined by Fix
, we should be able to define a Functor
instance of Fix s
. It seems like a hard problem at first, but with enough patience and time it is actually possible to define fmap
in terms of bimap
as follows:
> instance Bifunctor s => Functor (Fix s) where
> fmap f = In . bimap f (fmap f) . out
This looks magical, but we can comprehend the definition by inspecting the types of its components.
- out :: Fix s a -> s a (Fix s a)
- In :: s a (Fix s a) -> Fix s a
- fmap :: (a -> b) -> Fix s a -> Fix s b
- bimap :: (a -> b) -> (c -> d) -> s a c -> s b d
The type of fmap f
is Fix s a -> Fix s b
, so the type of bimap f (fmap f)
is s a (Fix s a) -> s b (Fix s b)
. Now we can compose these:
- out :: Fix s a -> s a (Fix s a)
- bimap f (fmap f) :: s a -> s a (Fix s a) -> s b (Fix s b)
- In :: s b (Fix s b) -> Fix s b
Thus,
- In . bitmap f (fmap f) . out :: Fix s a -> Fix s b
fold
and unfold
can be defined similiarly:
> fold :: Bifunctor s => (s a b -> b) -> Fix s a -> b
> fold f = f . bimap id (fold f) . out
>
> unfold :: Bifunctor s => (b -> s a b) -> b -> Fix s a
> unfold f = In . bimap id (unfold f) . f
Here’s how we use fmap
on List
:
> nil :: List a
> nil = In Nil
>
> cons :: a -> List a -> List a
> cons x xs = In (Cons x xs)
>
> l :: List Int
> l = fmap (+1) (cons 3 (cons 4 nil))
Tada! These recursive operators are indeed datatype-generic because the defintion of fmap
, fold
and unfold
never use the specific data type we defined. They use only bimap
which is parameterized by the shape s
of the data. It means we can reuse these functions for other data types without reimplementing them for each type. For example, here’s a definition of Tree
:
> data TreeF a r = Leaf | Branch a r r deriving Functor
> deriveBifunctor ''TreeF
> type Tree = Fix TreeF
>
> leaf :: Tree a
> leaf = In Leaf
>
> branch :: a -> Tree a -> Tree a -> Tree a
> branch x l r= In (Branch x l r)
To map over a tree, we can just use the same fmap
function we defined above!
> t :: Tree Int
> t = fmap (+1) (branch 3 leaf (branch 4 leaf leaf))
This technique of using bifunctors to implement datatype-generic recursive functions is mostly superseded by Applicative
and Traversable
in Haskell, but I think it is still a good example which shows the real power of bifunctors!