Free monad and type constraints - haskell

I am looking for practical strategies or tips for dealing with constraints in haskell, as illustrated by the case below.
I have a functor Choice and I want to transform an interpreter from Choice x functor to m x to an interpreter from Free Choice x to m x.
-- Choice : endofunctor
data Choice next = Choice next next deriving (Show)
instance Functor Choice where
fmap f (Choice a b) = Choice (f a) (f b)
-- I have a function from the functor to a monad m
inter1 :: Choice x -> IO x
inter1 (Choice a b) = do
x <- readLn :: IO Bool
return $ if x then a else b
-- universal property gives me a function from the free monad to m
go1 :: Free Choice x -> IO x
go1 = interpMonad inter1
where
type Free f a = FreeT f Identity a
data FreeF f r x = FreeF (f x) | Pure r deriving (Show)
newtype FreeT f m r = MkFreeT { runFreeT :: m (FreeF f r (FreeT f m r)) }
instance Show (m (FreeF f a (FreeT f m a))) => Show (FreeT f m a) where
showsPrec d (MkFreeT m) = showParen (d > 10) $
showString "FreeT " . showsPrec 11 m
instance (Functor f, Monad m) => Functor (FreeT f m) where
fmap (f::a -> b) (x::FreeT f m a) =
MkFreeT $ liftM f' (runFreeT x)
where f' :: FreeF f a (FreeT f m a) -> FreeF f b (FreeT f m b)
f' (FreeF (fx::f (FreeT f m a))) = FreeF $ fmap (fmap f) fx
f' (Pure r) = Pure $ f r
instance (Functor f, Monad m) => Applicative (FreeT f m) where
pure a = MkFreeT . return $ Pure a
(<*>) = ap
instance (Functor f, Monad m) => Monad (FreeT f m) where
return = MkFreeT . return . Pure
(MkFreeT m) >>= (f :: a -> FreeT f m b) = MkFreeT $ -- m (FreeF f b (FreeT f m b))
m >>= -- run the effect in the underlying monad !
\case FreeF fx -> return . FreeF . fmap (>>= f) $ fx -- continue to run effects
Pure r -> runFreeT (f r) -- apply the transformation
interpMonad :: (Functor f, Functor m, Monad m) =>
(forall x . f x -> m x) ->
forall x. Free f x -> m x
interpMonad interp (MkFreeT iFfxF) = (\case
Pure x -> return x
FreeF fxF -> let mmx = interp $ fmap (interpMonad interp) fxF
in join mmx) . runIdentity $ iFfxF
All is fine until I require Show x in my interpreter.
interp2 :: Show x => Choice x -> IO x
interp2 (Choice a b) = return a -- we follow left
go2 :: Show x => Free Choice x -> IO x
go2 = interpMonad interp2 -- FAILS
Then it can not find the show constraint to apply in interp2
I suspected the quantifiers were the problem, so I simplified to
lifting :: (forall x . x -> b) ->
(forall x. x -> b)
lifting = id
lifting2 :: (forall x . Show x => x -> b) ->
(forall x . Show x => x -> b)
lifting2 = id
somefunction :: Show x => x -> String
somefunction = lifting show -- FAILS
somefunction2 :: Show x => x -> String
somefunction2 = lifting2 show -- OK
This highlight the problem : Could not deduce (Show x1) arising from a use of ‘show’ from the context (Show x) we have two distinct type variable, and constraint do not flow from one to the other.
I could write some specialized function playing with the constraints as follows (does not work btw) but my question is what are the practical strategies for dealing with this ? (the equivalent of undefined, look at the type, go on...)
interpMonad2 :: (Functor f, Functor m, Monad m) =>
(forall x . ( Show (f x)) => f x -> m x) ->
forall x. ( Show (Free f x)) => Free f x -> m x
interpMonad2 interp (MkFreeT iFfxF) = (\case
Pure x -> return x
FreeF fxF -> let mmx = interp $ fmap (interpMonad interp) fxF
in join mmx) . runIdentity $ iFfxF
edit
based on the answer provided, here is the modification for the lifting function.
lifting :: forall b c. Proxy c
-> (forall x . c x => x -> b)
-> (forall x . c x => x -> b)
lifting _ = id
somefunction3 :: Show x => x -> String
somefunction3 = lifting (Proxy :: Proxy Show) show

I don't see your interpMonad function, so I will include one possible definition here:
interpMonad :: forall f m x . (Functor f, Monad m)
=> (forall y . f y -> m y) -> Free f x -> m x
interpMonad xx = go . runIdentity . runFreeT where
go (FreeF x) = xx x >>= go . runIdentity . runFreeT
go (Pure x) = return x
In order to also have a class constraint on the inner function, you simply add the constraint to the inner function. You also need the correct constraint on the type Free, and you need the extra Proxy to help the typechecker out a bit. Otherwise, the definition of the function is identical:
interpMonadC :: forall f m x c . (Functor f, Monad m, c (Free f x))
=> Proxy c
-> (forall y . c y => f y -> m y)
-> (Free f x -> m x)
interpMonadC _ xx = go . runIdentity . runFreeT where
go (FreeF x) = xx x >>= go . runIdentity . runFreeT
go (Pure x) = return x
And now quite simply:
>:t interpMonadC (Proxy :: Proxy Show) interp2
interpMonadC (Proxy :: Proxy Show) interp2
:: Show x => Free Choice x -> IO x

Related

Traversing with a Biapplicative

I was thinking about unzipping operations and realized that one way to express them is by traversing in a Biapplicative functor.
import Data.Biapplicative
class Traversable2 t where
traverse2 :: Biapplicative p
=> (a -> p b c) -> t a -> p (t b) (t c)
-- Note: sequence2 :: [(a,b)] -> ([a], [b])
sequence2 :: (Traversable2 t, Biapplicative p)
=> t (p b c) -> p (t b) (t c)
sequence2 = traverse2 id
instance Traversable2 [] where
traverse2 _ [] = bipure [] []
traverse2 f (x : xs) = bimap (:) (:) (f x) <<*>> traverse2 f xs
It smells to me as though every instance of Traversable can be transformed mechanically into an instance of Traversable2. But I haven't yet found a way to actually implement traverse2 using traverse, short of converting to and from lists or perhaps playing extremely dirty tricks with unsafeCoerce. Is there a nice way to do this?
Further evidence that anything Traversable is Traversable2:
class (Functor t, Foldable t) => Traversable2 t where
traverse2 :: Biapplicative p
=> (a -> p b c) -> t a -> p (t b) (t c)
default traverse2 ::
(Biapplicative p, Generic1 t, GTraversable2 (Rep1 t))
=> (a -> p b c) -> t a -> p (t b) (t c)
traverse2 f xs = bimap to1 to1 $ gtraverse2 f (from1 xs)
class GTraversable2 r where
gtraverse2 :: Biapplicative p
=> (a -> p b c) -> r a -> p (r b) (r c)
instance GTraversable2 V1 where
gtraverse2 _ x = bipure (case x of) (case x of)
instance GTraversable2 U1 where
gtraverse2 _ _ = bipure U1 U1
instance GTraversable2 t => GTraversable2 (M1 i c t) where
gtraverse2 f (M1 t) = bimap M1 M1 $ gtraverse2 f t
instance (GTraversable2 t, GTraversable2 u) => GTraversable2 (t :*: u) where
gtraverse2 f (t :*: u) = bimap (:*:) (:*:) (gtraverse2 f t) <<*>> gtraverse2 f u
instance (GTraversable2 t, GTraversable2 u) => GTraversable2 (t :+: u) where
gtraverse2 f (L1 t) = bimap L1 L1 (gtraverse2 f t)
gtraverse2 f (R1 t) = bimap R1 R1 (gtraverse2 f t)
instance GTraversable2 (K1 i c) where
gtraverse2 f (K1 x) = bipure (K1 x) (K1 x)
instance (Traversable2 f, GTraversable2 g) => GTraversable2 (f :.: g) where
gtraverse2 f (Comp1 x) = bimap Comp1 Comp1 $ traverse2 (gtraverse2 f) x
instance Traversable2 t => GTraversable2 (Rec1 t) where
gtraverse2 f (Rec1 xs) = bimap Rec1 Rec1 $ traverse2 f xs
instance GTraversable2 Par1 where
gtraverse2 f (Par1 p) = bimap Par1 Par1 (f p)
I think I might have something that fits your bill. (Edit: It doesn't, see comments.) You can define newtypes over p () c and p b () and make them Functor instances.
Implementation
Here's your class again with default definitions. I went the route of implementing sequence2 in terms of sequenceA because it seemed simpler.
class Functor t => Traversable2 t where
{-# MINIMAL traverse2 | sequence2 #-}
traverse2 :: Biapplicative p => (a -> p b c) -> t a -> p (t b) (t c)
traverse2 f = sequence2 . fmap f
sequence2 :: Biapplicative p => t (p b c) -> p (t b) (t c)
sequence2 = traverse2 id
Now, the "right part" of the Biapplicative is
newtype R p c = R { runR :: p () c }
instance Bifunctor p => Functor (R p) where
fmap f (R x) = R $ bimap id f x
instance Biapplicative p => Applicative (R p) where
pure x = R (bipure () x)
R f <*> R x =
let f' = biliftA2 const (flip const) (bipure id ()) f
in R $ f' <<*>> x
mkR :: Biapplicative p => p b c -> R p c
mkR = R . biliftA2 const (flip const) (bipure () ())
sequenceR :: (Traversable t, Biapplicative p) => t (p b c) -> p () (t c)
sequenceR = runR . sequenceA . fmap mkR
with the "left part" much the same. The full code is in this gist.
Now we can make p (t b) () and p () (t c) and reassemble them into p (t b) (t c).
instance (Functor t, Traversable t) => Traversable2 t where
sequence2 x = biliftA2 const (flip const) (sequenceL x) (sequenceR x)
I needed to turn on FlexibleInstances and UndecidableInstances for that instance declaration. Also, somehow ghc wanted a Functor constaint.
Testing
I verified with your instance for [] that it gives the same results:
main :: IO ()
main = do
let xs = [(x, ord x - 97) | x <- ['a'..'g']]
print xs
print (sequence2 xs)
print (sequence2' xs)
traverse2' :: Biapplicative p => (a -> p b c) -> [a] -> p [b] [c]
traverse2' _ [] = bipure [] []
traverse2' f (x : xs) = bimap (:) (:) (f x) <<*>> traverse2 f xs
sequence2' :: Biapplicative p => [p b c] -> p [b] [c]
sequence2' = traverse2' id
outputs
[('a',0),('b',1),('c',2),('d',3),('e',4),('f',5),('g',6)]
("abcdefg",[0,1,2,3,4,5,6])
("abcdefg",[0,1,2,3,4,5,6])
This was a fun exercise!
The following seems to do the trick, exploiting “only” undefined. Possibly the traversable laws guarantee that this is ok, but I've not attempted to prove it.
{-# LANGUAGE GADTs, KindSignatures, TupleSections #-}
import Data.Biapplicative
import Data.Traversable
data Bimock :: (* -> * -> *) -> * -> * where
Bimock :: p a b -> Bimock p (a,b)
Bimfmap :: ((a,b) -> c) -> p a b -> Bimock p c
Bimpure :: a -> Bimock p a
Bimapp :: Bimock p ((a,b) -> c) -> p a b -> Bimock p c
instance Functor (Bimock p) where
fmap f (Bimock p) = Bimfmap f p
fmap f (Bimfmap g p) = Bimfmap (f . g) p
fmap f (Bimpure x) = Bimpure (f x)
fmap f (Bimapp gs xs) = Bimapp (fmap (f .) gs) xs
instance Biapplicative p => Applicative (Bimock p) where
pure = Bimpure
Bimpure f<*>xs = fmap f xs
fs<*>Bimpure x = fmap ($x) fs
fs<*>Bimock p = Bimapp fs p
Bimfmap g h<*>Bimfmap i xs = Bimfmap (\(~(a₁,a₂),~(b₁,b₂)) -> g (a₁,b₁) $ i (a₂, b₂))
$ bimap (,) (,) h<<*>>xs
Bimapp g h<*>xs = fmap uncurry g <*> ((,)<$>Bimock h<*>xs)
runBimock :: Biapplicative p => Bimock p (a,b) -> p a b
runBimock (Bimock p) = p
runBimock (Bimfmap f p) = bimap (fst . f . (,undefined)) (snd . f . (undefined,)) p
runBimock (Bimpure (a,b)) = bipure a b
runBimock (Bimapp (Bimpure f) xs) = runBimock . fmap f $ Bimock xs
runBimock (Bimapp (Bimfmap h g) xs)
= runBimock . fmap (\(~(a₂,a₁),~(b₂,b₁)) -> h (a₂,b₂) (a₁,b₁))
. Bimock $ bimap (,) (,) g<<*>>xs
runBimock (Bimapp (Bimapp h g) xs)
= runBimock . (fmap (\θ (~(a₂,a₁),~(b₂,b₁)) -> θ (a₂,b₂) (a₁,b₁)) h<*>)
. Bimock $ bimap (,) (,) g<<*>>xs
traverse2 :: (Biapplicative p, Traversable t) => (a -> p b c) -> t a -> p (t b) (t c)
traverse2 f s = runBimock . fmap (\bcs->(fmap fst bcs, fmap snd bcs)) $ traverse (Bimock . f) s
sequence2 :: (Traversable t, Biapplicative p)
=> t (p b c) -> p (t b) (t c)
sequence2 = traverse2 id
And even if this is safe, I wouldn't be surprised if it gives horrible performance, what with the irrefutable patterns and quadratic (or even exponential?) tuple-tree buildup.
A few observations short of a complete, original answer.
If you have a Biapplicative bifunctor, what you can do with it is apply it to something and separate it into a pair of bifunctors isomorphic to its two components.
data Helper w a b = Helper {
left :: w a (),
right :: w () b
}
runHelper :: forall p a b. Biapplicative p => Helper p a b -> p a b
runHelper x = biliftA2 const (flip const) (left x) (right x)
makeHelper :: (Biapplicative p)
=> p a b -> Helper p a b
makeHelper w = Helper (bimap id (const ()) w)
(bimap (const ()) id w)
type Separated w a b = (w a (), w () b)
It would be possible to combine the approaches of #nnnmmm and #leftroundabout by applying fmap (makeHelper . f) to the structure s, eliminating the need for undefined, but then you would need to make Helper or its replacement an instance of some typeclass with the useful operations that let you solve the problem.
If you have a Traversable structure, what you can do is sequenceA Applicative functors (in which case your solution will look like traverse2 f = fromHelper . sequenceA . fmap (makeHelper . f), where your Applicative instance builds a pair of t structures) or traverse it using a Functor (in which case your solution will look like traverse2 f = fromHelper . traverse (g . makeHelper . f) where ...). Either way, you need to define a Functor instance, since Applicative inherits from Functor. You might try to build your Functor from <<*>> and bipure id id, or bimap, or you might work on both separated variables in the same pass.
Unfortunately, to make the types work for the Functor instance, you have to paramaterize :: p b c to a type we would informally call :: w (b,c) where the one parameter is the Cartesian product of the two parameters of p. Haskell’s type system doesn’t seem to allow this without non-standard extensions, but #leftroundabout pulls this off ably with the Bimock class. using undefined to coerce both separated functors to have the same type.
For performance, what you want to do is make no more than one traversal, which produces an object isomorphic to p (t b) (t c) that you can then convert (similar to the Naturality law). You therefore want to implement traverse2 rather than sequence2 and define sequence2 as traverse2 id, to avoid traversing twice. If you separate variables and produce something isomorphic to (p (t b) (), p () (t c)), you can then recombine them as #mmmnnn does.
In practical use, I suspect you would want to impose some additional structure on the problem. Your question kept the components b and c of the Bifunctor completely free, but in practice they will usually be either covariant or contravariant functors that can be sequenced with biliftA2 or traversed together over a Bitraversable rather than Traversable t, or perhaps even have a Semigroup, Applicative or Monad instance.
A particularly efficient optimization would be if your p is isomorphic to a Monoid whose <> operation produces a data structure isomorphic to your t. (This works for lists and binary trees; Data.ByteString.Builder is an algebraic type that has this property.) In this case, the associativity of the operation lets you transform the structure into either a strict left fold or a lazy right fold.
This was an excellent question, and although I don’t have better code than #leftroundabout for the general case, I learned a lot from working on it.
One only mildly evil way to do this is using something like Magma from lens. This seems considerably simpler than leftaroundabout's solution, although it's not beautiful either.
data Mag a b t where
Pure :: t -> Mag a b t
Map :: (x -> t) -> Mag a b x -> Mag a b t
Ap :: Mag a b (t -> u) -> Mag a b t -> Mag a b u
One :: a -> Mag a b b
instance Functor (Mag a b) where
fmap = Map
instance Applicative (Mag a b) where
pure = Pure
(<*>) = Ap
traverse2 :: forall t a b c f. (Traversable t, Biapplicative f)
=> (a -> f b c) -> t a -> f (t b) (t c)
traverse2 f0 xs0 = go m m
where
m :: Mag a x (t x)
m = traverse One xs0
go :: forall x y. Mag a b x -> Mag a c y -> f x y
go (Pure t) (Pure u) = bipure t u
go (Map f x) (Map g y) = bimap f g (go x y)
go (Ap fs xs) (Ap gs ys) = go fs gs <<*>> go xs ys
go (One x) (One y) = f0 x
go _ _ = error "Impossible"

Implementing `Applicative (Free f)`

For the Free Monad:
data Free f a = Var a
| Node (f (Free f a))
I implemented instance Functor (Free f):
instance Functor f => Functor (Free f) where
fmap g (Var x) = Var (g x)
fmap g (Node x) = Node $ fmap (\y -> fmap g y) x
Then I tried to implement instance Applicative (Free f):
instance Functor f => Applicative (Free f) where
pure x = Var x
My intuition is that var x is the right definition of pure.
However, regardless of whether that's correct, I'm not sure how to implement <*>.
In particular, is it necessary to support the following cases? Note that I ignored the make-up of the Var and Node with _.
(Var _) <*> (Var _)
(Var _) <*> (Node _)
(Node _) <*> (Var _)
(Node _) <*> (Node _)
Please give me a hint as to whether the above cases need to be matched.
Also, please provide me with an intuition as to what it means for both Free f a instances to exist on either side of <*>.
Will Ness gives a perfectly legitimate answer using ap. If you inline ap, you end up with this:
instance Functor f => Applicative (Free f) where
pure = A
A a <*> A b = A $ a b
A a <*> F mb = F $ fmap a <$> mb
F ma <*> b = F $ (<*> b) <$> ma
(Note: recent versions of the free package use this definition so as to be as explicit as possible.)
As chi showed, the first two cases can be combined:
A f <*> x = f <$> x
Defining Monad, and using ap for <*> (and return for pure, or course) works:
{-# LANGUAGE FlexibleContexts, UndecidableInstances #-}
import Control.Applicative -- <$>
import Control.Monad -- ap
data Free f a = A a | F (f (Free f a))
instance Functor f => Functor (Free f) where
fmap g (A a) = A (g a)
fmap g (F fv) = F ((g <$>) <$> fv)
instance Functor f => Monad (Free f) where
return = A
A a >>= k = k a
F fv >>= k = F ((k =<<) <$> fv)
-- ap mf mv = mf >>= \f-> mv >>= \v-> return f v
instance Functor f => Applicative (Free f) where
pure = return
fg <*> fv = ap fg fv
-- from http://stackoverflow.com/a/10875756/849891
instance (Show (f (Free f a)), Show a) => Show (Free f a) where
show (A x) = " A " ++ show x
show (F fv) = " F " ++ show fv
It is easy to handle the types, mentally, following the same pattern, as
($) :: (a -> b) -> a -> b
let g=g in (g $) :: a -> b
g :: (a -> b)
_____
Functor f => / \
fmap :: (a -> b) -> f a -> f b
let g=g in (g <$>) :: f a -> f b
g :: (a -> b)
___________________
Applicative f => / / \
(<*>) :: f (a -> b) -> f a -> f b
let h=h in (h <*>) :: f a -> f b
h :: f (a -> b)
_____________
Monad m => /.------. \
(=<<) :: (a -> m b) -> m a -> m b
let k=k in (k =<<) :: m a -> m b
k :: (a -> m b)
That's why I used (g <$>) and (k =<<), there.
As for building the intuition, see
#> let x = F [A 10, F [A 20, A 30]]
#> F[A (+1), A (+2)] <*> x
F [ F [ A 11, F [ A 21, A 31]], F [ A 12, F [ A 22, A 32]]]
#> A (+1) <*> F[x, x]
F [ F [ A 11, F [ A 21, A 31]], F [ A 11, F [ A 21, A 31]]]
#> (\a-> (+1) <$> F [A a, A (a+1)]) =<< x
F [ F [ A 11, A 12], F [ F [ A 21, A 22], F [ A 31, A 32]]]

Chaining values with catamorphisms

Suppose I have definitions as follows (where cata is the catamorphism):
type Algebra f a = f a -> a
newtype Fix f = Fx (f (Fix f))
unFix :: Fix f -> f (Fix f)
unFix (Fx x) = x
cata :: Functor f => (f a -> a) -> Fix f -> a
cata alg = alg . fmap (cata alg) . unFix
I was wondering if there would be some way to modify the definition of cata so that I could chain some object such as an int through it such that I could generate unique handles for things within the alg function, i.e. "a0", "a1", "a2", ..., etc.
Edit: To make this more clear, I'd like to be able to have some function cata' such that when I have something similar to the following definitions
data IntF a
= Const Int
| Add a a
instance Functor IntF where
fmap eval (Const i) = Const i
fmap eval (x `Add` y) = eval x `Add` eval y
alg :: Int -> Algebra IntF String
alg n (Const i) = "a" ++ show n
alg n (s1 `Add` s2) = s1 ++ " && " ++ s2
eval = cata' alg
addExpr = Fx $ (Fx $ Const 5) `Add` (Fx $ Const 4)
run = eval addExpr
then run evaluates to "a0 && a1" or something similar, i.e. the two constants don't get labeled the same thing.
Just sequence them as monads.
newtype Ctr a = Ctr { runCtr :: Int -> (a, Int) } -- is State Int
instance Functor Ctr
instance Applicative Ctr
instance Monad Ctr
type MAlgebra m f a = f (m a) -> m a
fresh :: Ctr Int
fresh = Ctr (\i -> (i, i+1))
data IntF a
= Val
| Add a a
malg :: IntF (Ctr String) -> Ctr String
malg Val = (\x -> "a" ++ show x) <$> fresh
malg (Add x y) = (\a b -> a ++ " && " ++ b) <$> x <*> y
go = cata malg
As I understand, you want something like
cata' :: Functor f => (Int -> f a -> a) -> Fix f -> a
so that you can operate both on f a and it's index.
If that's true, here's a possible solution.
Associated Int
First we define a new type which will represent Int-labelled functor:
{-# LANGUAGE DeriveFunctor #-}
data IntLabel f a = IntLabel Int (f a) deriving (Functor)
-- This acts pretty much like `zip`.
labelFix :: Functor f => [Int] -> Fix f -> Fix (IntLabel f)
labelFix (x:xs) (Fx f) = Fx . IntLabel x $ fmap (labelFix xs) f
Now we can define cata' using cata and labelFix:
cata' :: Functor f => (Int -> f a -> a) -> Fix f -> a
cata' alg = cata alg' . labelFix [1..]
where
alg' (IntLabel n f) = alg n f
NOTE: unique Ints are assigned to each layer, not each functor. E.g. for Fix [] each sublist of the outermost list will be labelled with 2.
Threading effects
A different approach to the problem would be to use cata to produce monadic value:
cata :: Functor f => (f (m a) -> m a) -> Fix f -> m a
This is just a specialized version of cata. With it we can define (almost) cat' as
cata'' :: Traversable f => (Int -> f a -> a) -> Fix f -> a
cata'' alg = flip evalState [1..] . cata alg'
where
alg' f = alg <$> newLabel <*> sequenceA f
newLabel :: State [a] a
newLabel = state (\(x:xs) -> (x, xs))
Note that Traversable instance now is needed in order to switch f (m a) to m (f a).
However, you might want to use just a bit more specialized cata:
cata :: (Functor f, MonadReader Int m) => (f (m a) -> m a) -> Fix f -> m a

Monad vs Applicative in the case of Reader resp. ((->) a)

In Haskell, what does the monad instance of functions give over just applicative? Looking at their implementations, they seem almost identical:
(<*>) f g x = f x (g x)
(>>=) f g x = g (f x) x
Is there anything you can do with >>= that you can't do with just <*>?
They are equivalent in power for the function instance: flip f <*> g == g >>= f. This is not true for most types that are instances of Monad though.
It's a little more clear if we compare <*> and =<< (which is flip (>>=)) specialized to the ((->) r) instance:
(<*>) :: Applicative f => f (a -> b) -> f a -> f b
-- Specialized to ((->) r):
(<*>) :: (r -> a -> b) -> (r -> a) -> r -> b
(=<<) :: Monad m => (a -> m b) -> m a -> m b
-- Specialized to ((->) r):
(=<<) :: (a -> r -> b) -> (r -> a) -> r -> b

Why can't I generalize this from Monad to Applicative?

I generalized hoistFree from the free package to hoistFreeM, similarly to how one can generalize fmap to Data.Traversable.mapM.
import Control.Monad
import Control.Monad.Free
import Data.Traversable as T
hoistFreeM :: (Traversable g, Monad m) =>
(forall a. f a -> m (g a)) -> Free f b -> m (Free g b)
hoistFreeM f = go
where go (Pure x) = return $ Pure x
go (Free xs) = liftM Free $ T.mapM go =<< f xs
However, I don't think there is a way to further generalize it to work with any Applicative, similarly to how one can generalize Data.Traversable.mapM to Data.Traversable.traverse. Am I correct? If so, why?
You can't lift an Applicative through a Free Monad because the Monad structure demands choice (via (>>=) or join) and the Applicative can't provide that. But, perhaps unsurprisingly, you can lift an Applicative through a Free Applicative
-- also from the `free` package
data Ap f a where
Pure :: a -> Ap f a
Ap :: f a -> Ap f (a -> b) -> Ap f b
hoistAp :: (forall a. f a -> g a) -> Ap f b -> Ap g b
hoistAp _ (Pure a) = Pure a
hoistAp f (Ap x y) = Ap (f x) (hoistAp f y)
hoistApA :: Applicative v => (forall a. f a -> v (g a)) -> Ap f b -> v (Ap g b)
hoistApA _ (Pure a) = pure (Pure a)
hoistApA f (Ap x y) = Ap <$> f x <*> hoistApA f y
-- just what you'd expect, really
To be more explicit, let's try generalizing hoistFreeM to hoistFreeA. It's easy enough to begin
hoistFreeA :: (Traversable f, Applicative v) =>
(forall a. f a -> v (g a)) -> Free f b -> v (Free g b)
hoistFreeA _ (Pure a) = pure (Pure a)
And we can try to continue by analogy from hoistFreeM here. mapM becomes traverse and we can get as far as
hoistFreeA f (Free xs) = ?f $ traverse (hoistFreeA f) xs
where I've been using ?f as a makeshift type hole to try to figure out how to move forward. We can complete this definition if we can make
?f :: v (f (Free g b)) -> v (Free g b)
In other words, we need to transform that f layer into a g layer while living underneath our v layer. It's easy enough to get underneath v since v is a Functor, but the only way we have to transform f a to g a is our argument function forall a . f a -> v (g a).
We can try applying that f anyway along with a Free wrapper in order to fold up our g layer.
hoistFreeA f (Free xs) = ?f . fmap (fmap Free . f) $ traverse (hoistFreeA f) xs
But now we have to solve
?f :: v (v (Free g b)) -> v (Free g b)
which is just join, so we're stuck. This is fundamentally where we're always going to get stuck. Free Monads model Monads and thus in order to wrap over them we need to somehow join or bind.

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