A Functor in Haskell is a type of kind f :: * -> * , which supports the operation fmap :: (a -> b) -> f a -> f b . Many "container" types are Functors, including the List type. But we’re not going to talk about "containers", per se. We’re going to explore a few of the simplest functors that we can squeeze out of the Haskell type system. Of course, I don’t know the actual name of some of these, so you’ll have to forgive me for giving them pet names instead.

Our end goal in exporing these functors is to reproduce the Conduit library by assembling pieces of it, one functor at a time. For this post, we’re just going to survey various functors, and ways to compose them. I’ll also touch lightly on how they play with the Free Monad Transformer, though serious discussion of such will be left to later posts.

> {-# LANGUAGE TypeOperators #-} > {-# OPTIONS_GHC -Wall #-} > > module Fun where

The Identity functor

> newtype Identity next = Identity next

The Identity functor trivially wraps a value. In order to implement fmap, it just applies the function directly to the value inside.

> instance Functor Identity where > fmap f ( Identity next ) = Identity ( f next )

When used with the Free Monad Transformer, the Identity monad trivially grants you the ability to represent "the thing that comes next". This will be convenient for us sometime around part 5 of this series.

The Empty functor

> data Empty next = Empty

The Empty functor contains no information. It admits the type variable, but is otherwise nothing but the trivial value, () .

> instance Functor Empty where > fmap _f Empty = Empty

When used with the Free Monad Transformer, the Empty functor allows you to short-circuit computation. The Free Monad Transformer works by stacking functors up, but as you can see, the Empty functor has no room for other functors to live inside of it.

The Const functor

> newtype Const a next = Const a

The Const functor is very similar to the Empty functor, except that it contains some actual value, which remains untouched by functor operations.

> instance Functor ( Const a ) where > fmap _f ( Const a ) = Const a

When used with the Free Monad Transformer, the Const functor allows you to terminate computation while providing some information. Joining this functor with the Identity functor will allow us to supply information without terminating computation (because the Identity functor gives a space for the "next" computation), which will be the heart of our yield functionality.

The (a ->) functor

> newtype Fun a next = Fun ( a -> next )

Functions, as you may know, are functors. In order to fmap onto a function, simply wait until the function has acquired input and produced an output, and then map onto the function’s output.

> instance Functor ( Fun a ) where > fmap f ( Fun g ) = Fun ( \ x -> f ( g x ) )

When used with the Free Monad Transformer, this allows us to represent inversion of control, or acquiring information from some outside source, in order to determine what to do next. This will be the heart of our await functionality.

Composing functors

> newtype ( f :.: g ) x = Composed ( f ( g x ) )

Functors can be composed, and the result is a functor.

> instance ( Functor f , Functor g ) => Functor ( f :.: g ) where > fmap f ( Composed x ) = Composed $ fmap ( fmap f ) x

I won’t be using this particular form of functor composition for future posts, but it was worth noting. Instead, let’s take a look at two other ways to combine functors:

Combining functors (tagged union)

> infixl 5 :|: > data ( f :|: g ) x = L ( f x ) | R ( g x )

If I have two functors f and g , then their tagged union is also a functor. We can just tag the f x values with L and the g x values with R so that whenever we come across some data, we know which of the two functors it actually was.

By case analysis, we can make a tagged union of functors also be a functor:

> instance ( Functor f , Functor g ) => Functor ( f :|: g ) where > fmap f ( L x ) = L ( fmap f x ) > fmap f ( R x ) = R ( fmap f x )

This will be very useful. While in normal code you would just use Haskell’s plain old tagged unions to define a data type:

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

we’re not going to do that, because it’s more fun to take advantage of functory goodness.

You could define a left-only or right-only functor for a tagged union if you wanted to.

Combining functors (product)

> infixl 7 :&: > data ( f :&: g ) x = f x :&: g x

If I have two functors f and g , then their product is also a functor: just perform the fmap on them both simultaneously.

> instance ( Functor f , Functor g ) => Functor ( f :&: g ) where > fmap f ( l :&: r ) = fmap f l :&: fmap f r

Similar to how in Haskell you can provide multiple pieces of data to a constructor, we can use :&: to bundle information together.

type Cons a = Const a :&: Identity type Nil = Empty type ListF a = Nil :|: Cons a type List a = FreeT ( ListF a )

Again, left-only or right-only Functor instances are possible, but unnecessary for my needs.

Next time

Next time, we’ll start by creating an implementation of Control.Pipe from the pipes package. Our Pipe type will be able to yield and await .

Exercise to the reader: try it yourself before you read the next post! Here’s a little bit to get you started.

{-# LANGUAGE TypeOperators #-} module Pipe where -- "cabal update && cabal install pipes" for this Free module import Control . Monad . Trans . Free import Fun newtype Then next = Then next -- Identity newtype Yield o next = Yield o -- Const newtype Await i next = Await ( i -> next ) -- Fun type PipeF i o = ( ??? :&: ??? ) :|: ??? type Pipe i o m r = ??? PipeF i o ??? yield :: o -> Pipe i o m () yield o = ??? await :: Pipe i o m i await = ???

To play with this code, download Fun.lhs.