Typoclassopedia: Exercise solutions
Table of Contents 
I wanted to get proficient in Haskell so I decided to follow An [Essential] Haskell Reading List. There I stumbled upon Typoclassopedia, while the material is great, I couldn’t find solutions for the exercises to check against, so I decided I would write my own and hopefully the solutions would get fixed in case I have gone wrong by others. So if you think a solution is wrong, let me know in the comments!
In each section below, I left some reference material for the exercises and then the solutions.
Note: The post will be updated as I progress in Typoclassopedia myself
Functor
Instances
instance Functor [] where
fmap :: (a > b) > [a] > [b]
fmap _ [] = []
fmap g (x:xs) = g x : fmap g xs
 or we could just say fmap = map
instance Functor Maybe where
fmap :: (a > b) > Maybe a > Maybe b
fmap _ Nothing = Nothing
fmap g (Just a) = Just (g a)
((,) e) represents a container which holds an “annotation” of type e along with the actual value it holds. It might be clearer to write it as (e,), by analogy with an operator section like (1+), but that syntax is not allowed in types (although it is allowed in expressions with the TupleSections extension enabled). However, you can certainly think of it as (e,).
((>) e) (which can be thought of as (e >); see above), the type of functions which take a value of type e as a parameter, is a Functor. As a container, (e > a) represents a (possibly infinite) set of values of a, indexed by values of e. Alternatively, and more usefully, ((>) e) can be thought of as a context in which a value of type e is available to be consulted in a readonly fashion. This is also why ((>) e) is sometimes referred to as the reader monad; more on this later.
Exercises

Implement
Functor
instances forEither e
and((>) e)
.Solution:
instance Functor (Either e) where fmap _ (Left e) = Left e fmap g (Right a) = Right (g a) instance Functor ((>) e) where fmap g f = g . f

Implement
Functor
instances for((,) e)
and forPair
, defined as below. Explain their similarities and differences.Solution:
instance Functor ((,) e) where fmap g (a, b) = (a, g b) data Pair a = Pair a a instance Functor Pair where fmap g (Pair a b) = Pair (g a) (g b)
Their similarity is in the fact that they both represent types of two values. Their difference is that
((,) e)
(tuples of two) can have values of different types (kind of(,)
is* > *
) while both values ofPair
have the same typea
, soPair
has kind*
. 
Implement a
Functor
instance for the typeITree
, defined asdata ITree a = Leaf (Int > a)  Node [ITree a]
Solution:
instance Functor ITree where fmap g (Leaf f) = Leaf (g . f) fmap g (Node xs) = Node (fmap (fmap g) xs)
To test this instance, I defined a function to apply the tree to an
Int
:applyTree :: ITree a > Int > [a] applyTree (Leaf g) i = [g i] applyTree (Node []) _ = [] applyTree (Node (x:xs)) i = applyTree x i ++ applyTree (Node xs) i
This is not a standard tree traversing algorithm, I just wanted it to be simple for testing.
Now test the instance:
λ: let t = Node [Node [Leaf (+5), Leaf (+1)], Leaf (*2)] λ: applyTree t 1 [6,2,2] λ: applyTree (fmap id t) 1 [6,2,2] λ: applyTree (fmap (+10) t) 1 [16, 12, 12]

Give an example of a type of kind
* > *
which cannot be made an instance ofFunctor
(without usingundefined
).I don’t know the answer to this one yet!

Is this statement true or false?
The composition of two
Functor
s is also aFunctor
.If false, give a counterexample; if true, prove it by exhibiting some appropriate Haskell code.
Solution:
It’s true, and can be proved by the following function:
ffmap :: (Functor f, Functor j) => (a > b) > f (j a) > f (j b) ffmap g = fmap (fmap g)
You can test this on arbitrary compositions of
Functor
s:main = do let result :: Maybe (Either String Int) = ffmap (+ 2) (Just . Right $ 5) print result  (Just (Right 7))
Functor Laws
fmap id = id
fmap (g . h) = (fmap g) . (fmap h)
Exercises

Although it is not possible for a Functor instance to satisfy the first Functor law but not the second (excluding undefined), the reverse is possible. Give an example of a (bogus) Functor instance which satisfies the second law but not the first.
Solution:
This is easy, consider this instance:
instance Functor [] where fmap _ [] = [1] fmap g (x:xs) = g x: fmap g xs
Then, you can test the first and second laws:
λ: fmap id []  [1], breaks the first law λ: fmap ((+1) . (+2)) [1,2]  [4, 5], second law holds λ: fmap (+1) . fmap (+2) $ [1,2]  [4, 5]

Which laws are violated by the evil Functor instance for list shown above: both laws, or the first law alone? Give specific counterexamples.
 Evil Functor instance instance Functor [] where fmap :: (a > b) > [a] > [b] fmap _ [] = [] fmap g (x:xs) = g x : g x : fmap g xs
Solution:
The instance defined breaks the first law (
fmap id [1]  [1,1]
), but holds for the second law.
Category Theory
The Functor section links to Category Theory, so here I’m going to cover the exercises of that page, too.
Introduction to categories
Category laws:

The compositions of morphisms need to be associative:
$f \circ (g \circ h) = (f \circ g) \circ h$
 The category needs to be closed under the composition operator. So if $f : B \to C$ and $g: A \to B$, then there must be some $h: A \to C$ in the category such that $h = f \circ g$.
 Every object $A$ in a category must have an identity morphism, $id_A : A \to A$ that is an identity of composition with other morphisms. So for every morphism $g: A \to B$: $g \circ id_A = id_B \circ g = g$.
Exercises

As was mentioned, any partial order $(P, \leq)$ is a category with objects as the elements of P and a morphism between elements a and b iff $a \leq b$. Which of the above laws guarantees the transitivity of $\leq$?
Solution:
The second law, which states that the category needs to be closed under the composition operator guarantess that because we have a morphism $a \leq b$, and another morphism $b \leq c$, there must also be some other morphism such that $a \leq c$.

If we add another morphism to the above example, as illustrated below, it fails to be a category. Why? Hint: think about associativity of the composition operation.
Solution:
The first law does not hold:
$f \circ (g \circ h) = (f \circ g) \circ h$
To see that, we can evaluate each side to get an inequality:
$g \circ h = id_B$
$f \circ g = id_A$
$f \circ (g \circ h) = f \circ id_B = f$
$(f \circ g) \circ h = id_A \circ h = h$
$f \neq h$
Functors
Functor laws:

Given an identity morphism $id_A$ on an object $A$, $F(id_A)$ must be the identity morphism on $F(A)$, so: $F(id_A) = id_{F(A)}$

Functors must distribute over morphism composition: $F(f \circ g) = F(f) \circ F(g)$
Exercises

Check the functor laws for the diagram below.
Solution:
The first law is obvious as it’s directly written, the pale blue dotted arrows from $id_C$ to $F(id_C) = id_{F(C)}$ and $id_A$ and $id_B$ to $F(id_A) = F(id_B) = id_{F(A)} = id_{F(B)}$ show this.
The second law also holds, the only compositions in category $C$ are between $f$ and identities, and $g$ and identities, there is no composition between $f$ and $g$.
(Note: The second law always hold as long as the first one does, as was seen in Typoclassopedia)

Check the laws for the Maybe and List functors.
Solution:
instance Functor [] where fmap :: (a > b) > [a] > [b] fmap _ [] = [] fmap g (x:xs) = g x : fmap g xs  check the first law for each part: fmap id [] = [] fmap id (x:xs) = id x : fmap id xs = x : fmap id xs  the first law holds recursively  check the second law for each part: fmap (f . g) [] = [] fmap (f . g) (x:xs) = (f . g) x : fmap (f . g) xs = f (g x) : fmap (f . g) xs fmap f (fmap g (x:xs)) = fmap f (g x : fmap g xs) = f (g x) : fmap (f . g) xs
instance Functor Maybe where fmap :: (a > b) > Maybe a > Maybe b fmap _ Nothing = Nothing fmap g (Just a) = Just (g a)  check the first law for each part: fmap id Nothing = Nothing fmap id (Just a) = Just (id a) = Just a  check the second law for each part: fmap (f . g) Nothing = Nothing fmap (f . g) (Just x) = Just ((f . g) x) = Just (f (g x)) fmap f (fmap g (Just x)) = Just (f (g x)) = Just ((f . g) x)
Applicative
Laws

The identity law:
pure id <*> v = v

Homomorphism:
pure f <*> pure x = pure (f x)
Intuitively, applying a noneffectful function to a noneffectful argument in an effectful context is the same as just applying the function to the argument and then injecting the result into the context with pure.

Interchange:
u <*> pure y = pure ($ y) <*> u
Intuitively, this says that when evaluating the application of an effectful function to a pure argument, the order in which we evaluate the function and its argument doesn’t matter.

Composition:
u <*> (v <*> w) = pure (.) <*> u <*> v <*> w
This one is the trickiest law to gain intuition for. In some sense it is expressing a sort of associativity property of (
<*>
). The reader may wish to simply convince themselves that this law is typecorrect.
Exercises
(Tricky) One might imagine a variant of the interchange law that says something about applying a pure function to an effectful argument. Using the above laws, prove that
pure f <*> x = pure (flip ($)) <*> x <*> pure f
Solution:
pure (flip ($)) <*> x <*> pure f
= (pure (flip ($)) <*> x) <*> pure f  <*> is leftassociative
= pure ($ f) <*> (pure (flip ($)) <*> x)  interchange
= pure (.) <*> pure ($ f) <*> pure (flip ($)) <*> x  composition
= pure (($ f) . (flip ($))) <*> x  homomorphism
= pure ((flip ($) f) . (flip ($))) <*> x  identical
= pure f <*> x
Explanation of the last transformation:
flip ($)
has type a > (a > c) > c
, intuitively, it first takes an argument of type a
, then a function that accepts that argument, and in the end it calls the function with the first argument. So (flip ($) 5)
takes as argument a function which gets called with 5
as it’s argument. If we pass (+ 2)
to (flip ($) 5)
, we get (flip ($) 5) (+2)
which is equivalent to the expression (+2) $ 5
, evaluating to 7
.
flip ($) f
is equivalent to \x > x $ f
, that means, it takes as input a function and calls it with the function f
as argument.
The composition of these functions works like this: First flip ($)
takes x
as it’s first argument, and returns a function (flip ($) x)
, this function is awaiting a function as it’s last argument, which will be called with x
as it’s argument. Now this function (flip ($) x)
is passed to flip ($) f
, or to write it’s equivalent (\x > x $ f) (flip ($) x)
, this results in the expression (flip ($) x) f
, which is equivalent to f $ x
.
You can check the type of (flip ($) f) . (flip ($))
is something like this (depending on your function f
):
λ: let f = sqrt
λ: :t (flip ($) f) . (flip ($))
(flip ($) f) . (flip ($)) :: Floating c => c > c
Also see this question on Stack Overflow which includes alternative proofs.
Instances
Applicative instance of lists as a collection of values:
newtype ZipList a = ZipList { getZipList :: [a] }
instance Applicative ZipList where
pure :: a > ZipList a
pure = undefined  exercise
(<*>) :: ZipList (a > b) > ZipList a > ZipList b
(ZipList gs) <*> (ZipList xs) = ZipList (zipWith ($) gs xs)
Applicative instance of lists as a nondeterministic computation context:
instance Applicative [] where
pure :: a > [a]
pure x = [x]
(<*>) :: [a > b] > [a] > [b]
gs <*> xs = [ g x  g < gs, x < xs ]
Exercises

Implement an instance of
Applicative
forMaybe
.Solution:
instance Applicative (Maybe a) where pure :: a > Maybe a pure x = Just x (<*>) :: Maybe (a > b) > Maybe a > Maybe b _ <*> Nothing = Nothing Nothing <*> _ = Nothing (Just f) <*> (Just x) = Just (f x)

Determine the correct definition of
pure
for theZipList
instance ofApplicative
—there is only one implementation that satisfies the law relatingpure
and(<*>)
.Solution:
newtype ZipList a = ZipList { getZipList :: [a] } instance Functor ZipList where fmap f (ZipList list) = ZipList { getZipList = fmap f list } instance Applicative ZipList where pure = ZipList . pure (ZipList gs) <*> (ZipList xs) = ZipList (zipWith ($) gs xs)
You can check the Applicative laws for this implementation.
Utility functions
Exercises

Implement a function
sequenceAL :: Applicative f => [f a] > f [a]
There is a generalized version of this,sequenceA
, which works for anyTraversable
(see the later section onTraversable
), but implementing this version specialized to lists is a good exercise.Solution:
createList = replicate 1 sequenceAL :: Applicative f => [f a] > f [a] sequenceAL = foldr (\x b > ((++) . createList <$> x) <*> b) (pure [])
Explanation:
First,
createList
is a simple function for creating a list of a single element, e.g.createList 2 == [2]
.Now let’s take
sequenceAL
apart, first, it does a fold over the list[f a]
, andb
is initialized topure []
, which results inf [a]
as required by the function’s output.Inside the function,
createList <$> x
appliescreateList
to the value insidef a
, resulting inf [a]
, and then(++)
is applied to the value again, so it becomesf ((++) [a])
, now we can apply the function(++) [a]
tob
by((++) . createList <$> x) <*> b
, which results inf ([a] ++ b)
.
Alternative formulation
Definition
class Functor f => Monoidal f where
unit :: f ()
(**) :: f a > f b > f (a,b)
Laws:

Left identity
unit ** v ≅ v

Right identity
u ** unit ≅ u

Associativity
u ** (v ** w) ≅ (u ** v) ** w

Neutrality
fmap (g *** h) (u ** v) = fmap g u ** fmap h v
Isomorphism
In the laws above, ≅
refers to isomorphism rather than equality. In particular we consider:
(x,()) ≅ x ≅ ((),x)
((x,y),z) ≅ (x,(y,z))
Exercises

Implement
pure
and<*>
in terms ofunit
and**
, and vice versa.unit :: f () unit = pure () (**) :: f a > f b > f (a, b) a ** b = fmap (,) a <*> b pure :: a > f a pure x = unit ** x (<*>) :: f (a > b) > f a > f b f <*> a = fmap (uncurry ($)) (f ** a) = fmap (\(f, a) > f a) (f ** a)

Are there any
Applicative
instances for which there are also functionsf () > ()
andf (a,b) > (f a, f b)
, satisfying some “reasonable” laws?The
Arrow
type class seems to satisfy these criteria.first unit = () (id *** f) (a, b) = (f a, f b)

(Tricky) Prove that given your implementations from the first exercise, the usual Applicative laws and the Monoidal laws stated above are equivalent.

Identity Law
pure id <*> v = fmap (uncurry ($)) ((unit ** id) ** v) = fmap (uncurry ($)) (id ** v) = fmap id v = v

Homomorphism
pure f <*> pure x = (unit ** f) <*> (unit ** x) = fmap (\(f, a) > f a) (unit ** f) (unit ** x) = fmap (\(f, a) > f a) (f ** x) = fmap f x = pure (f x)

Interchange
u <*> pure y = fmap (uncurry ($)) (u ** (unit ** y)) = fmap (uncurry ($)) (u ** y) = fmap (u $) y = fmap ($ y) u = pure ($ y) <*> u

Composition
u <*> (v <*> w) = fmap (uncurry ($)) (u ** (fmap (uncurry ($)) (v ** w))) = fmap (uncurry ($)) (u ** (fmap v w)) = fmap u (fmap v w) = fmap (u . v) w = pure (.) <*> u <*> v <*> w =

Monad
Definition
class Applicative m => Monad m where
return :: a > m a
(>>=) :: m a > (a > m b) > m b
(>>) :: m a > m b > m b
m >> n = m >>= \_ > n
fail :: String > m a
Instances
instance Monad Maybe where
return :: a > Maybe a
return = Just
(>>=) :: Maybe a > (a > Maybe b) > Maybe b
(Just x) >>= g = g x
Nothing >>= _ = Nothing
Exercises

Implement a
Monad
instance for the list constructor,[]
. Follow the types!Solution:
instance Monad [] where return a = [a] [] >> _ = [] (x:xs) >>= f = f x : xs >>= f

Implement a
Monad
instance for((>) e)
.Solution:
instance Monad ((>) e) where return x = const x g >>= f = f . g

Implement
Functor
andMonad
instance forFree f
, defined as:data Free f a = Var a  Node (f (Free f a))
You may assume that
f
has aFunctor
instance. This is known as the free monad built from the functor f.Solution:
instance Functor (Free f) where fmap f (Var a) = Var (f a) fmap f (Node x) = Node (f x) instance Monad (Free f) where return x = Var x (Var x) >>= f = Var (f x) (Node x) >>= f = Node (fmap f x)
Intuition
Exercises

Implement
(>>=)
in terms offmap
(orliftM
) andjoin
.Solution:
a >>= f = join (fmap f a)

Now implement
join
andfmap
(liftM
) in terms of(>>=)
andreturn
.Solution:
fmap f a = a >>= (return . f) join m = m >>= id
Laws
Standard:
return a >>= k = k a
m >>= return = m
m >>= (\x > k x >>= h) = (m >>= k) >>= h
In terms of >=>
:
return >=> g = g
g >=> return = g
(g >=> h) >=> k = g >=> (h >=> k)
Exercises

Given the definition
g >=> h = \x > g x >>= h
, prove the equivalence of the above laws and the standard monad laws.Solution:
return >=> g = \x > return x >>= g = \x > g x = g g >=> return = \x > g x >>= return = \x > g x = g g >=> (h >=> k) = \y > g y >>= (\x > h x >>= k) = \y > (g y >>= h) >>= k = \y > (\x > g x >>= h) y >>= k = (\x > g x >>= h) >=> k = (g >=> h) >=> k
Monad Transformers
Definition and laws
class MonadTrans t where
lift :: Monad m => m a > t m a
Exercises

What is the kind of
t
in the declaration ofMonadTrans
?Solution:
t
is of the kind(* > *) > * > *
, as we see in(t m) a
,t
accepts aMonad
first, which is of type* > *
, and then another argument of kind*
.
Composing Monads
Exercises

Implement
join :: M (N (M (N a))) > M (N a)
givendistrib :: N (M a) > M (N a)
and assumingM
andN
are instances ofMonad
.join :: M (N (M (N a))) > M (N a) join m = distrib ((distrib m) >>= join) >>= join  one by one let m :: M (N (M (N a))) a = distrib m :: N (M (M (N a))) b = a >>= join :: N (M (N a)) c = distrib b :: M (N (N a)) in c >>= join :: M (N a)
MonadFix
Examples and intuition
maybeFix :: (a > Maybe a) > Maybe a
maybeFix f = ma
where ma = f (fromJust ma)
Exercises

Implement a MonadFix instance for [].
Solution:
listFix :: (a > [a]) > [a] listFix f = la where la = f (head la)
Foldable
Definition
class Foldable t where
fold :: Monoid m => t m > m
foldMap :: Monoid m => (a > m) > t a > m
foldr :: (a > b > b) > b > t a > b
foldr' :: (a > b > b) > b > t a > b
foldl :: (b > a > b) > b > t a > b
foldl' :: (b > a > b) > b > t a > b
foldr1 :: (a > a > a) > t a > a
foldl1 :: (a > a > a) > t a > a
toList :: t a > [a]
null :: t a > Bool
length :: t a > Int
elem :: Eq a => a > t a > Bool
maximum :: Ord a => t a > a
minimum :: Ord a => t a > a
sum :: Num a => t a > a
product :: Num a => t a > a
Instances and examples
Exercises

Implement
fold
in terms offoldMap
.Solution:
fold = foldMap id

What would you need in order to implement
foldMap
in terms offold
?Solution:
A
map
function should exist for the instance, so we can apply the function(a > m)
to the container first.foldMap f = fold . map f

Implement
foldMap
in terms offoldr
.Solution:
foldMap f = foldr (\a b > mappend (f a) b) mempty

Implement
foldr
in terms offoldMap
(hint: use theEndo
monoid).Solution:
foldr f b c = foldMap (Endo . f) c `appEndo` b

What is the type of
foldMap . foldMap
? OrfoldMap . foldMap . foldMap
, etc.? What do they do?Solution:
Each composition makes
foldMap
operate on a deeper level, so:foldMap :: Monoid m => (a > m) > t a > m foldMap . foldMap :: Monoid m => (a > m) > t (t a) > m foldMap . foldMap . foldMap :: Monoid m => (a > m) > t (t (t a)) > m foldMap id [1,2,3] :: Sum Int  6 (foldMap . foldMap) id [[1,2,3]] :: Sum Int  6 (foldMap . foldMap . foldMap) id [[[1,2,3]]] :: Sum Int  6
Derived folds
Exercises

Implement
toList :: Foldable f => f a > [a]
in terms of eitherfoldr
orfoldMap
.Solution:
toList = foldMap (replicate 1)

Show how one could implement the generic version of
foldr
in terms oftoList
, assuming we had only the listspecificfoldr :: (a > b > b) > b > [a] > b
.Solution:
foldr f b c = foldr f b (toList c)

Pick some of the following functions to implement:
concat
,concatMap
,and
,or
,any
,all
,sum
,product
,maximum(By)
,minimum(By)
,elem
,notElem
, andfind
. Figure out how they generalize toFoldable
and come up with elegant implementations usingfold
orfoldMap
along with appropriateMonoid
instances.Solution:
concat :: Foldable t => t [a] > [a] concat = foldMap id concatMap :: Foldable t => (a > [b]) > t a > [b] concatMap f = foldMap (foldMap (replicate 1 . f)) and :: Foldable t => t Bool > Bool and = getAll . foldMap All or :: Foldable t => t Bool > Bool or = getAny . foldMap Any any :: Foldable t => (a > Bool) > t a > Bool any f = getAny . foldMap (Any . f) all :: Foldable t => (a > Bool) t a > Bool all f = getAll . foldMap (All . f) sum :: (Num a, Foldable t) => t a > a sum = getSum . foldMap Sum product :: (Num a, Foldable t) => t a > a product = getProduct . foldMap Product  I think there are more elegant implementations for maximumBy, leave a comment  if you have a suggestion maximumBy :: Foldable t => (a > a > Ordering) > t a > a maximumBy f c = head $ foldMap (\a > [a  cmp a]) c where cmp a = all (/= LT) (map (f a) lst) lst = toList c elem :: (Eq a, Foldable t) => a > t a > Bool elem x c = any (==x) c find :: Foldable t => (a > Bool) > t a > Maybe a find f c = listToMaybe $ foldMap (\a > [a  f a]) c
Utility functions

sequenceA_ :: (Applicative f, Foldable t) => t (f a) > f ()
takes a container full of computations and runs them in sequence, discarding the results (that is, they are used only for their effects). Since the results are discarded, the container only needs to be Foldable. (Compare withsequenceA :: (Applicative f, Traversable t) => t (f a) > f (t a)
, which requires a stronger Traversable constraint in order to be able to reconstruct a container of results having the same shape as the original container.) 
traverse_ :: (Applicative f, Foldable t) => (a > f b) > t a > f ()
applies the given function to each element in a foldable container and sequences the effects (but discards the results).
Exercises

Implement
traverse_
in terms ofsequenceA_
and vice versa. One of these will need an extra constraint. What is it?Solution:
sequenceA_ :: (Applicative f, Foldable t) => t (f a) > f () sequenceA_ = traverse_ id traverse_ :: (Applicative f, Foldable t, Functor t) => (a > f b) > t a > f () traverse_ f c = sequenceA_ (fmap f c)
The additional constraint for implementing
traverse_
in terms ofsequenceA_
is the requirement of theFoldable
instancet
to be aFunctor
as well.
Traversable
Intuition
traverse :: Applicative f => (a > f b) > t a > f (t b)
sequenceA :: Applicative f => t (f a) > f (t a)
Exercises

There are at least two natural ways to turn a tree of lists into a list of trees. What are they, and why?
Note: I’m not really sure whether my solution is natural, I think the question is rather ambiguous in the sense that it’s not clear whether the trees in the final list of trees can have lists as their values, i.e.
Tree [Int] > [Tree [Int]]
is valid or onlyTree [Int] > [Tree Int]
is, but let me know if you think otherwise.Solution:
One way is to put each
Node
,Leaf
orEmpty
in a list inorder, this way the structure of the tree can be recovered from the list, here is a quick sketch ([]
is an arbitrary list):let tree = Node (Node (Leaf []) Empty) [] (Leaf []) let list = [Node Empty [] Empty, Node Empty [] Empty, Leaf [], Empty, Leaf []]

Give a natural way to turn a list of trees into a tree of lists.
Solution:
To recover the original tree from the list of trees, whenever we encounter a
Node
in the list, we catch the next three values as left, value, and right nodes of the original node. 
What is the type of
traverse . traverse
? What does it do?Solution:
(traverse . traverse) :: Applicative f => (a > f b) > t (t2 a) > f (t (t2 b))
It traverses on a deeper level, retaining the structure of the first level.

Implement
traverse
in terms ofsequenceA
, and vice versa.Solution:
sequenceA = traverse id traverseA f c = sequenceA (fmap f c)
Instances and examples
Exercises

Implement
fmap
andfoldMap
using only theTraversable
methods. (Note that theTraversable
module provides these implementations asfmapDefault
andfoldMapDefault
.)Solution:
newtype Id a = Id { getId :: a } instance Functor Id where fmap f (Id x) = Id (f x) instance Applicative Id where pure x = Id x (Id f) <*> (Id x) = Id (f x) fmapDefault :: Traversable t => (a > b) > t a > t b fmapDefault f = getId . traverse (Id . f) foldMapDefault :: (Monoid m, Traversable t) => (a > m) > t a > m foldMapDefault f = getConst . traverse (Const . f)
See the Const Functor’s definition for intuition.

Implement
Traversable
instances for[]
,Maybe
,((,) a)
, andEither a
.Solution:
instance Traversable [] where traverse :: Applicative f => (a > f b) > [a] > f [b] traverse _ [] = pure [] traverse f (x:xs) = (:) <$> f x <*> Main.traverse f xs instance Traversable Maybe where traverse :: Applicative f => (a > f b) > Maybe a > f (Maybe b) traverse _ Nothing = pure Nothing traverse f (Just x) = Just <$> f x instance Traversable ((,) c) where traverse :: Applicative f => (a > f b) > (c, a) > f (c, b) traverse f (c, a) = (,) c <$> f a instance Traversable (Either c) where traverse :: Applicative f => (a > f b) > Either c a > f (Either c b) traverse _ (Left c) = pure (Left c) traverse f (Right a) = Right <$> f a

Explain why
Set
isFoldable
but notTraversable
.Solution:
First, in terms of laws,
Set
is not aFunctor
, thus it cannot be made into aTraversable
instance, sinceTraversable
instances requireFunctor
superclasses.Second, on an intuitive level: In
Foldable
, the goal is not to keep the shape/structure of the original container, we are trying to reduce the container into some value, and the shape of the final result doesn’t matter, but inTraversable
, we ought to keep the structure of the final result, but we can’t guarantee this while usingSet
s, because we can define some transformationf :: Set a > Set a
which reduces the length of theSet
.See Foldable vs. Traversable and Sets, Functors and Eq confusion. and Foldable and Traversable for more details.

Show that
Traversable
functors compose: that is, implement an instance forTraversable (Compose f g)
givenTraversable
instances forf
andg
.Solution:
instance (Traversable f, Traversable g) => Traversable (Compose f g) where traverse :: (Applicative f) => (a > f b) > Compose g h a > f (Compose g h b) traverse f (Compose t) = Compose <$> traverse (traverse f) t