# Adjunctions in the wild: foldl

I recently made a few connections that linked some different concepts in Haskell that I hadn’t realized before. They deal with one of my favorite “practical” libraries in Haskell, and also one of the more “profound” category theory-inspired abstractions in Haskell. In the process, it made the library a bit more useful to me, and also made the concept a bit more concrete and understandable to me.

This post mainly goes through my thought process in finding this out — it’s very much a “how I think through this” sort of thing — in the end, the goal is to show how much this example made me further appreciate the conceptual idea of adjunctions and how they can pop up in interesting places in practical libraries. Unlike most of my other posts, it’s not about necessarily about how practically useful an abstraction is, but rather what insight it gives us to understanding its instances.

The audience of this post is Haskellers with an understanding/appreciation of abstractions like Applicative, but be aware that the final section is separately considered as a fun aside for those familiar with some of Haskell’s more esoteric types. The code samples used here (along with exercise solutions) are available on github.

## foldl

The first concept is the great foldl library, which provides a nice “stream processor” type called Fold, where Fold r a is a stream processor that takes a stream of rs and produces an a:

import           Control.Foldl   (Fold(..))
import qualified Control.Foldl   as F

F.sum  :: Num a        => Fold a a
F.mean :: Fractional a => Fold a a
F.elem :: Eq a         => a -> Fold a Bool

F.fold F.sum  [1,2,3,4]
#   => 10
F.fold F.mean [1,2,3,4]
#   => 2.5
F.fold (F.elem 3) [1,2,3,4]
#   => True
F.fold (F.elem 5) [1,2,3,4]
#   => False

The most useful thing about the library is that it treats the folds as first-class objects, so you can create more complex folds by combining simpler folds (for example, with -XApplicativeDo)

-- source: https://github.com/mstksg/inCode/tree/master/code-samples/adjunctions/foldl.hs#L22-L29

variance :: Fractional a => Fold a a
variance = do
x  <- F.mean
x2 <- lmap (^2) F.mean     -- the mean of squared items
pure (x2 - x*x)

varianceTooBig :: (Fractional a, Ord a) => Fold a Bool
varianceTooBig = (> 3) <\$> variance

Most importantly, Fold r is an instance of both Functor and Applicative, so you can map over and combine the results of different folds.

To me, foldl is one of the shining examples of how well Haskell works for data and stream processing, and a library I often show to people when they ask what the big deal is about Haskell abstractions like Applicative, purity, and lists — this technique is often described as “beautiful folds”.

The second concept is the idea of adjoint functors (see also Bartosz Milewski’s introduction and nlab’s description, as well as Tai-Danae Bradley’s motivation), represented in Haskell by the adjunctions library and typeclass (Chris Penner has a nice article with an example of using the typeclass’s utility functions to simplify programs).

For some functors, we can think of a “conceptual inverse”. We can ask “I have a nice functor F. Conceptually, what functor represents the opposite idea/spirit of F?” The concept of an adjunction is one way to formalize what this means.

In Haskell1, with the Adjunctions typeclass (specifically, Functor functors), this manifests as this: if F -| U (F is left adjoint to U, and U is right adjoint to F), then all the ways of going “out of” F a to b are the same as all the ways of going “into” U b from a. Ways of going out can be encoded as ways of going in, and vice versa. They represent opposite ideas.

-- | The class saying you can always convert between:
--
-- * f a -> b (the ways to go out of f)
-- * a -> u b (the ways to go into g)
:: (f a -> b)       -- ^ the ways of going "out of" f
-> (a -> u b)       -- ^ the ways of going "into" u

:: (a -> u b)       -- ^ the ways of going "into" u
-> (f a -> b)       -- ^ the ways of going "out of" f

### Examples

For example, one of the more famous adjunctions in Haskell is the adjunction between (,) r and (->) r. “Tupling” represents some sort of “opposite” idea to “parameterizing”.

The ways to get “out” of a tuple is (r, a) -> b. The ways to go “into” a function is a -> (r -> b). Haskellers will recognize that these two types are the “same” (isomorphic) — any (a, b) -> c can be re-written as a -> (b -> c) (currying), and vice versa (uncurrying).

Another common pair is with same-typed either and tuple:

-- source: https://github.com/mstksg/inCode/tree/master/code-samples/adjunctions/foldl.hs#L31-L34

newtype SameEither a = SE (Either a a)

newtype SameTuple  a = ST (a, a)

People familiar with Either (sums) and (,) (products) in Haskell will recognize them as “opposite” ideas — one is “or”, and the other is “and” (depending on if you are talking about using them or making them).

We can formalize this idea of opposites using adjunctions: Going “out of” Either a a into b can be encoded as going “into” (b, b) from a, and vice versa: Either a a -> b can be encoded as a -> (b, b), which can be encoded as Either a a -> b — the two types are isomorphic. This is because to go out of Either a a, you have to handle the situation of getting a Left and the situation of getting a Right. To go into (b, b), you have to able to ask what goes in the first field, and what goes in the right field. Both Either a a -> b and a -> (b, b) have to answer the same questions. (A fun exercise would be to write the functions to convert between the two — one solution is here)

### Big Picture

Aside from being an interesting curiosity (formalizing the idea of “opposite idea” is pretty neat), hunting for adjunctions can be useful in figuring out “why” a functor is useful, what you can do with it, and also what functors are intimately connected with it. There’s also the helper functions in the Data.Functor.Adjunction module that implement some nice helper functions on your types if an adjoint happens to exist — you can do some neat things by going “back and forth” between adjoint functors.

So, from the build-up, you’ve probably guessed what we’re going to do next: find a functor that is adjoint to Fold r. What’s the “conceptual opposite” of Fold r? Let’s go adjunction hunting!

Important note — the rest of this section is not a set of hard rules, but rather an intuitive process of heuristics to search for candidates that would be adjoint to a given functor of interest. There are no hard and fast rules, and the adjoint might not always exist (it usually doesn’t). But when it does, it can be a pleasant surprise.

### Patterns to look for

Now, on to the hunting. Let’s say we have functor Q and we want to identify any adjoints. We want to spot functions that use both Q a and a with some other value, in opposite positions.

(Of course, this is only the case if we are using a functor that comes from a library. If we are writing our own functor from scratch, and want to hunt for adjunctions there, we have to instead think of ways to use Q a and a)

One common pattern is functions for “converting between” the going-in and going-out functions. In Data.Functor.Adjunctions, these are called leftAdjunct and rightAdjunct:

leftAdjunct  :: Adjunction f u => (f a -> b) -> (a -> u b)
rightAdjunct :: Adjunction f u => (a -> u b) -> (f a -> b)

This pair is significant because it is the adjunctions “in practice”: Sure, an (r, a) -> b is useful, but “using” the adjunction means that you can convert between (r, a) -> b and a -> r -> b

Another common pattern that you can spot are “indexing” and “tabulating” functions, in the case that you have a right-adjoint:

indexAdjunction    :: Adjunction f u => u b -> f () -> b
tabulateAdjunction :: Adjunction f u => (f () -> b) -> u b

indexAdjunction means: if it’s possible to “extract” from u b to b using only an f () as extra information, then u might be right-adjoint to f.

tabulateAdjunction means: if it’s possible to “generate” a u b based on a function that “builds” a b from f (), then u might right-adjoint to f.

This pair is equivalent in power — you can implement rightAdjunct in terms of indexAdjunction and leftAdjunct in terms of tabulateAdjunction and vice versa. This comes from the fact that all Adjunctions in Haskell Functors arise from some idea of “indexability”. We’ll go into more detail later, but this is the general intuition.

### Adjoints to Fold

Now, let’s look out for examples of these functions for Fold! In the case of Fold, there is actually only one function I can find that directly takes a Fold r a and returns an a:

fold :: Fold r b -> [r] -> b

(the type has been simplified and re-labeled, for illustration’s sake)

You “give” a Fold r b and “get” an b (and so they have opposite polarities/positions). This sort of function would make Fold r a right adjoint, since the naked type b (the final parameter of Fold r b) is the final result, not the input.

Of our common patterns, this one looks a looooot like indexAdjunction.2

fold            :: Fold r b -> [r]  -> b
indexAdjunction :: Fold r b -> f () -> b

This means that Fold r b is right-adjoint to some functor f where f () = [r]. A good first guess (just a hunch?) would be to just have f a = ([r], a):

-- source: https://github.com/mstksg/inCode/tree/master/code-samples/adjunctions/foldl.hs#L73-L74

data EnvList r a = EnvList [r] a
deriving (Functor, Show, Eq, Ord)

EnvList r3 adds a list of rs to a type. It is now also our suspect for a potential left-adjoint to Fold r: a “conceptual opposite”.

-- source: https://github.com/mstksg/inCode/tree/master/code-samples/adjunctions/foldl.hs#L76-L77

indexFold :: Fold r b -> EnvList r () -> b
indexFold fld (EnvList rs _) = F.fold fld rs

To seal the deal, let’s find its pair, tabulateAdjunction. That means we are looking for:

tabulateFold :: (EnvList r () -> b) -> Fold r b

Or, to simplify the type by expanding the definition of EnvList r ():

tabulateFold :: ([r] -> b) -> Fold r b

This tells us that, given any list processor [r] -> b, we can write a fold Fold r b representing that list processor. Scanning things more, we can see that this actually looks a lot like foldMap from the library:

import qualified Control.Foldl as F

F.foldMap
:: Monoid w
=> (r -> w)
-> (w -> b)
-> Fold r b

-- or

F.foldMap (\r -> [r])
:: ([r] -> b)
-> Fold r b

So:

-- source: https://github.com/mstksg/inCode/tree/master/code-samples/adjunctions/foldl.hs#L79-L80

tabulateFold :: (EnvList r () -> b) -> Fold r b
tabulateFold f = F.foldMap (:[]) (\rs -> f (EnvList rs ()))

The fact the have both of these gives us a pretty strong footing to claim that EnvList r is the left-adjoint of Fold r. Proof by hunch, for now.

Note that if we had missed fold during our adjunction hunt, we might have also lucked out by noticing F.foldMap (:[]) fitting the criteria for a candidate for tabulateAdjunction, instead.

## Opposite Concepts

We’ve identified a likely candidate for a left-adjoint to Fold r! But … does any of this make any sense? Does this make sense as a left-adjoint, conceptually … and did we gain anything?

Let’s think about this from the beginning: What is the conceptual opposite of “something that folds a list”?

Well, what other thing is more naturally an opposite than “a list to be folded”!

• EnvList r: A list of r
• Fold r: Consumes a list of r

Or, in terms of the result of the functor application:

• EnvList r a
• An a
• … tupled with a list of r
• Fold r a
• An a
• … parameterized by consumption of a list of r

It seems to “flip” the idea of “list vs. list consumer”, and also the idea of “tupled vs. parameterizing” (which was our first example of an adjunction earlier, as well).

In addition, lists seem to be at the heart of how to create and consume a Fold r.

fold can be thought of as the fundamental way to consuming a Fold r. This makes the adjunction with EnvList r make sense: what good is the ability to fold … if there is nothing to fold? EnvList r (a list of [r]) is intimately related to Fold r: they are the yin and yang, peanut butter and jelly, night and day. Their fates are intertwined from their very inception. You cannot have one without the other.

In addition, F.foldMap is arguably a fundamental (although maybe inefficient) way to specify a Fold r. A Fold r is, fundamentally, a list processor — which is what EnvList r a -> b literally is (an [r] -> b). Fold r and EnvList rdyads in the force. (Or, well…literally monads, since all adjunctions give rise to monads, as we will see later.)

The fact that EnvList r and Fold r form an adjunction together formalizes the fact that they are conceptually “opposite” concepts, and also that they are bound together by destiny in a close and fundamental way.

A Note on Representable

Note that in this case, a lot of what we are concluding simply stems from the fact that we can “index” a Fold r a using an [r]. This actually is more fundamentally associated with the concept of a Representable Functor.

-- source: https://github.com/mstksg/inCode/tree/master/code-samples/adjunctions/foldl.hs#L87-L90

instance Representable (Fold r) where
type Rep (Fold r) = [r]
tabulate = F.foldMap (:[])
index    = F.fold

As it turns out, in Haskell, a functor being representable is equivalent to it having a left adjoint. So thinking of Fold r as a representable functor and thinking of it as a right adjoint are equivalent ideas. This article chooses to analyze it from the adjunctions perspective because we get to imagine the adjoint Functor, which can sometimes reveal some extra insight over just looking at some index value.

## The Helper Functions

Let’s take a look at some of the useful helper functions that an instance of Adjunction gives us for Fold r, to see how their existence can better help us understand Fold. For all of these, I’m going to write them first as EnvList r a, and then also as ([r], a), to help make things clearer.

unit :: a -> Fold r (EnvList r a)
unit :: a -> Fold r ([r], a)

counit :: EnvList r (Fold r a) -> a
counit :: [r] -> Fold r a -> a

leftAdjunct :: (EnvList r a -> b) -> (a -> Fold r b)
leftAdjunct :: ([r] -> a -> b   ) -> (a -> Fold r b)

rightAdjunct :: (a -> Fold r b) -> (EnvList r a -> b)
rightAdjunct :: (a -> Fold r b) -> ([r] -> a -> b   )

tabulateAdjunction :: (EnvList r () -> b) -> Fold r b
tabulateAdjunction :: ([r] -> b)          -> Fold r b

indexAdjunction :: Fold r b -> EnvList r a -> b
indexAdjunction :: Fold r b -> [r]         -> b

zipR :: Fold r a -> Fold r b -> Fold r (a, b)
1. unit :: a -> Fold r ([r], a), when we specialize a ~ (), becomes:

unit :: Fold r [r]

This means that unit for Fold r folds a list [r] into “itself”, while also tagging on a value

F.fold (unit True) [1,2,3]
#   => EnvList [1,2,3] True
2. counit :: [r] -> Fold r a -> a is essentially just F.fold when we expand it. Neat!

3. leftAdjunct :: ([r] -> a -> b) -> (a -> Fold r b) … if we write it as leftAdjunct :: a -> (a -> [r] -> b) -> Fold r b, and feed the a into the first function, we get:

leftAdjunct' :: ([r] -> b) -> Fold r b

which is just tabulateAdjunction, or F.foldMap (:[])! It encodes our list processor [r] -> b into a Fold r b.

4. rightAdjunct :: (a -> Fold r b) -> ([r] -> a -> b) – if we again rewrite as rightAdjunct :: a -> (a -> Fold r b) -> [r] -> b, and again feed the a into the first function, becomes:

rightAdjunct' :: Fold r b -> [r] -> b

which happens to just be fold, or counit!

5. tabulateAdjunction and indexAdjunction we went over earlier, seeing them as F.foldMap (:[]) and fold

6. zipR :: Fold r a -> Fold r b -> Fold r (a, b) takes two Fold rs and combines them into a single fold. This is exactly the “combining fold” behavior that makes Folds so useful! The implementation of zipR is less efficient than the implementation of <*>/liftA2 for Fold r, but knowing that zipR exists means that we know Fold rs can be combined.

Seeing how these functions all fit together, we can write a full instance of Adjunction. We can choose to provide unit and counit, or leftAdjunct and rightAdjunct4; the unit/counit definitions are the easiest to conceptualize, for me, but the other pair isn’t much tricker to write.

-- source: https://github.com/mstksg/inCode/tree/master/code-samples/adjunctions/foldl.hs#L92-L97

instance Adjunction (EnvList r) (Fold r) where
unit x = F.foldMap (:[]) (EnvList x)
counit (EnvList rs fld) = F.fold fld rs

leftAdjunct f x = F.foldMap (:[]) (\rs -> f (EnvList rs x))
rightAdjunct f (EnvList rs x) = F.fold (f x) rs

Another interesting thing we might want to look at is the monad and comonad that our adjunction defines. All adjunctions define a monad, so what does our new knowledge of the Fold r adjunction give us?

If we have F -| U, then U . F is a monad. In this case, we have FoldEnv:

-- source: https://github.com/mstksg/inCode/tree/master/code-samples/adjunctions/foldl.hs#L99-L100

newtype FoldEnv r a = FE { getFE :: Fold r (EnvList r a) }
deriving Functor

-- or
type FoldEnv r = Fold r ([r], a)

As it turns out, this is essentially equivalent to the famous State Monad! More specifically, it’s the Representable State Monad.

type FoldEnv r = State [r]

-- or, more literally, from Control.Monad.Representable.State
type FoldEnv r = State (Fold r)

So the induced monad from the adjunction we just found is essentially the same as the State monad over a list — except with some potentially different performance characteristics.

In the end, finding this adjunction gives us a neat way to represent stateful computations on lists, which is arguably an extension of what Fold was really meant for in the first place.

If we have F -| U, then F . U is a comonad. In this case, we have EnvFold:

-- source: https://github.com/mstksg/inCode/tree/master/code-samples/adjunctions/foldl.hs#L111-L112

newtype EnvFold r a = EF { getEF :: EnvList r (Fold r a) }
deriving Functor

-- or
type EnvFold r = ([r], Fold r a)

This one is exactly the Representable Store comonad. It’s essentially the normal Store comonad:

type EnvFold r = Store [r]

-- or, more literally, from Control.Comonad.Representable.Store
type EnvFold r = Store (Fold r)

This comonad “stores” an [r] as well as a way to produce an a from an [r]. All of the utility of this induced comonad basically is the same as the utility of Store, except with potentially different performance profiles.

In the end, finding this adjunction gives us a neat way to define a comonadic contextual projection on lists, which I would say is also an extension of the original purpose of Fold.

## Conclusion

In the end, in a “practical” sense, we got some nice helper functions, as well as a new way to extend the conceptual idea of Fold using the induced monad and comonad.

Admittedly, the selection of helper functions that Adjunction gives us pales in comparison to abstractions like Monoid, Applicative, Traversable, Monad, etc., which makes Adjunction (in my opinion) nowhere as practical when compared to them. A lot of these helper functions (like the induced state monad and store comonad) actually also just exist if we only talk about Representable.

However, to me (and, as how I’ve seen other people use it), Adjunction is most useful as a conceptual tool in Haskell. The idea of “opposites” or “duals” show up a lot in Haskell, starting from the most basic level – sums and products, products and functions. From day 1, Haskellers are introduced to natural pairs and opposites in concepts. The idea of opposites and how they interact with each other is always on the mind of a Haskeller, and close to their heart.

So, what makes Adjunction so useful to me is that it actually is able to formalize what we mean by “opposite concepts”. The process of identifying a functor’s “opposite concept” (if it exists) will only help is better understand the functor we’re thinking about, in terms of how it works and how it is used.

Hopefully this blog post helps you appreciate both Fold in a new way, and also the fundamental “idea” of adjunctions in Haskell.

## The Algebraic Way

In this section we’re going to get a bit mathy and look at the definition of Fold, to see if we can algebraically find an adjunction of Fold, instead of just trying to hunt for API functions like before. In practice you don’t often have to make algebraic deductions like this, but it’s at least nice to know that something like this possible from a purely algebraic and logical sense. You never need all this fancy math to be able to write Haskell … but many feel like it can make things a lot more fun! :)

Be warned that this method does require some familiarity (or at least awareness) of certain types that appear often in the more … esoteric corners of Haskelldom :)

The game plan here is to start with the definition of Fold, and then rearrange it using algebraic substitutions until it matches something that already has an Adjunction instance in the adjunctions library.

First, the actual definition of Fold in the foldl library itself is:

data Fold r a = forall x. Fold (x -> r -> x) x (x -> a)

Maybe not the friendliest definition at first! But something in this looks a little familiar, maybe. Let’s do some re-arranging:

data Fold r a = forall x. Fold (x -> r -> x) x (x -> a)
= forall x. Fold x (x -> r -> x) (x -> a)
= forall x. Fold x (x -> (r -> x, a))

Ah, this looks a lot like the constructor Nu for some f:

data Nu f = forall x. Nu (x -> f x) x

Nu is one of the three main famous fixed-point type combinators in Haskell. The other two are Mu and Fix:

data    Nu  f = forall x. Nu (x -> f x) x
newtype Fix f = Fix (f (Fix f))
newtype Mu  f = Mu (forall x. (f x -> x) -> x)

In Haskell these are all equivalent5, but they have very different performance profiles for certain operations. Nu is easy to “build up”, and Mu is easy to “tear down” – and they exist sort of opposite to each other. Fix exists in opposite to … itself. Sorry, Fix.

Anyway, looking at Fold r a:

data Fold r a = forall x. Fold x (x -> (r -> x, a))
data Nu   f   = forall x. Nu   x (x -> f x)

it seems like we can pick an F such that Nu (F r a) = Fold r a. Let’s try…

newtype (f :.: g) x = Comp (f (g x))

type Fold r a = Nu (((,) a) :.: ((->) r))

From here, some might recognize the fixed point of (,) a :.: f as Cofree, from Control.Comonad.Cofree — one of the more commonly used fixed points.

type Cofree f a = Nu ((,) a :.: f     )

type Fold r a   = Nu ((,) a :.: (->) r)
type Fold r     = Cofree ((->) r)

It looks like Fold r is just Cofree ((->) r) 6 … and now we’ve hit the jackpot! That’s because Cofree f has an instance of Adjunction!

instance Adjunction f u => Adjunction (Free f) (Cofree u)

This means that Cofree u is right-adjoint to Free f, if f is right-adjoint to u. Well, our u here is (->) r, which was actually our very first example of a right-adjoint functor — it’s right-adjoint to (,). So, Fold r is apparently a right-adjoint, like we guessed previously! More specifically, it looks like like Fold r is right-adjoint to Free ((,) r).

At least, we’ve reached our goal! We found an adjunction for Fold r in a purely algebraic way, and deduced it to be right-adjunct to Free ((,) r).

At this point we have our answer, so we can stop here. But it’s possible to go a little further, to find a true “perfect companion” for Fold r. Its perfect match and conceptual opposite, as the adjunction mythos claims.

We know that Free f is, itself, a fixed-point – it’s the fixed point of Sum (Const a) f (from Data.Functor.Sum). So Free ((,) r) a is the fixed-point of Sum (Const a) ((,) r). Since we are looking at conceptual opposites, maybe let’s try using the Mu fixed-point operator, to be opposite of the Nu that Fold r is. This also makes sense because this is something we’re going to “tear down” with a Fold, and Mu is good at being torn down.

newtype Mu f = Mu (forall x. (f x -> x) -> x)

type EL r a = Mu (Sum (Const a) ((,) r))

newtype EL r a = EL {
runEL :: forall x. (Either a (r, x) -> x) -> x
}

-- or, with some shuffling around, recognizing that Either a b -> c is
-- equivalent to (a -> c, b -> c)
newtype EL r a = EL {
runEL :: forall x. (a -> x) -> (x -> r -> x) -> x
}

The new EL is actually isomorphic to the EnvList one we wrote earlier (as long as the list is finite), meaning that one can encode the other, and they have identical structure. Writing functions to convert between the two can be fun; here is one solution, and there’s a bonus solution if you can write it using only the new instance for Adjunction (EL r) (Fold r) and F.foldMap, since it can be shown that all adjuncts are unique up to isomorphism.

And…this looks pretty neat, I think. In the end we discover that these two types are adjoints to each other:7

data Fold r a = forall x. Fold            (x -> a)    (x -> r -> x)    x
data EL   r a =           EL   (forall x. (a -> x) -> (x -> r -> x) -> x)

They look superficially syntactically similar and I don’t really know what to make of that … but a lot of “opposites” seem to be paired here. The existential x in Fold becomes a Rank2 universal in EList, and the x -> a in Fold becomes an a -> x in EList. Neat neat.

Adjunctions: take an idea and just make everything opposite.

One nice thing about this representation is that writing the fundamental operation of Fold (that is, fold) becomes really clean:8

-- source: https://github.com/mstksg/inCode/tree/master/code-samples/adjunctions/foldl-algebraic.hs#L51-L52

foldEL :: Fold r b -> EL r a -> b
foldEL (Fold step init extr) el = extr (runEL el (const init) step)

And this is, maybe, the real treasure all along.

## Special Thanks

I am very humbled to be supported by an amazing community, who make it possible for me to devote time to researching and writing these posts. Very special thanks to my supporter at the “Amazing” level on patreon, Josh Vera! :)

1. Note that the intuition we are going to be going into is specifically for adjunctions between Functor functors — functors that the Functor typeclass models (aka, endofunctors in Hask). For a more general view of adjunctions in general, see the links above.↩︎

2. As it so happens, fold is actually exactly index for Representable (Fold r), from Data.Functor.Rep. Here we are utilizing the fact that a representable Functor gives rise to a left-adjoint for free — the two ideas are equivalent in Haskell. We go into this in more detail in an upcoming aside.↩︎

3. The name here is inspired by the Env comonadEnvList r is Env [r].↩︎

4. We should also be able to define it using tabulateAdjunction and indexAdjunction … but this isn’t allowed for some reason?↩︎

5. They are only equivalent in Haskell because of laziness — in strict languages, they are different.↩︎

6. Some might recognize Cofree ((->) r) as a common way of implementing a Moore machine in Haskell. In fact, our derivation here is basically a backwards version of the process described here by Edward Kmett.↩︎

7. The instance is written out here.↩︎

8. Implementing a tabulate equivalent (solution here) reveals that this refactoring is only really useful for index (to “consume” a Fold) … using tabulate or leftAdjunct to “produce” a Fold reveals how inefficient this is.↩︎