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 read-only fashion. This is also why ((->) e) is sometimes referred to as the reader monad; more on this later.

Exercises

  1. Implement Functor instances for Either 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
    
  2. Implement Functor instances for ((,) e) and for Pair, 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 of Pair have the same type a, so Pair has kind *.

  3. Implement a Functor instance for the type ITree, defined as

     data 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]
    
  4. Give an example of a type of kind * -> * which cannot be made an instance of Functor (without using undefined).

    I don’t know the answer to this one yet!

  5. Is this statement true or false?

    The composition of two Functors is also a Functor.

    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 Functors:

     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

  1. 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]
    
  2. 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:

  1. The compositions of morphisms need to be associative:

    $f \circ (g \circ h) = (f \circ g) \circ h$

  2. 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 $h = f \circ g$.
  3. 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

  1. 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 $a \leq c$.

  2. 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.

    not a category, an additional h: B -> A

    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:

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

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

Exercises

  1. Check the functor laws for the diagram below.

    functor diagram

    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)

  2. 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

  1. The identity law:

     pure id <*> v = v
    
  2. Homomorphism:

     pure f <*> pure x = pure (f x)
    

    Intuitively, applying a non-effectful function to a non-effectful 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.

  3. 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.

  4. 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 type-correct.

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 left-associative
  = 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 non-deterministic computation context:

instance Applicative [] where
  pure :: a -> [a]
  pure x = [x]
 
  (<*>) :: [a -> b] -> [a] -> [b]
  gs <*> xs = [ g x | g <- gs, x <- xs ]

Exercises

  1. Implement an instance of Applicative for Maybe.

    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)
    
  2. Determine the correct definition of pure for the ZipList instance of Applicative—there is only one implementation that satisfies the law relating pure 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

  1. Implement a function sequenceAL :: Applicative f => [f a] -> f [a] There is a generalized version of this, sequenceA, which works for any Traversable (see the later section on Traversable), 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], and b is initialized to pure [], which results in f [a] as required by the function’s output.

    Inside the function, createList <$> x applies createList to the value inside f a, resulting in f [a], and then (++) is applied to the value again, so it becomes f ((++) [a]), now we can apply the function (++) [a] to b by ((++) . createList <$> x) <*> b, which results in f ([a] ++ b).

Alternative formulation

Definition

class Functor f => Monoidal f where
  unit :: f ()
  (**) :: f a -> f b -> f (a,b)

Laws:

  1. Left identity

     unit ** v  v
    
  2. Right identity

     u ** unit  u
    
  3. Associativity

     u ** (v ** w)  (u ** v) ** w
    
  4. 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

  1. Implement pure and <*> in terms of unit 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)
    
  2. Are there any Applicative instances for which there are also functions f () -> () and f (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)
    
  3. (Tricky) Prove that given your implementations from the first exercise, the usual Applicative laws and the Monoidal laws stated above are equivalent.

    1. Identity Law

       pure id <*> v
         = fmap (uncurry ($)) ((unit ** id) ** v)
         = fmap (uncurry ($)) (id ** v)
         = fmap id v
         = v
      
    2. 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)
      
    3. Interchange

       u <*> pure y
         = fmap (uncurry ($)) (u ** (unit ** y))
         = fmap (uncurry ($)) (u ** y)
         = fmap (u $) y
         = fmap ($ y) u
         = pure ($ y) <*> u
      
    4. 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

  1. 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
    
  2. Implement a Monad instance for ((->) e).

    Solution:

     instance Monad ((->) e) where
       return x = const x
          
       g >>= f = f . g
    
  3. Implement Functor and Monad instance for Free f, defined as:

     data Free f a = Var a
                   | Node (f (Free f a))
    

    You may assume that f has a Functor 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

  1. Implement (>>=) in terms of fmap (or liftM) and join.

    Solution:

     a >>= f = join (fmap f a)
    
  2. Now implement join and fmap (liftM) in terms of (>>=) and return.

    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

  1. 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