Haskell instances under type variable conditions - haskell

Starting with a concrete instance of my question, we all know (and love) the Monad type class:
class ... => Monad m where
return :: a -> m a
(>>=) :: m a -> (a -> m b) -> mb
...
Consider the following would-be instance, where we modify the standard list/"nondeterminism" instance using nub to retain only one copy of each "outcome":
type DistinctList a = DL { dL :: [a] }
instance Monad DistinctList where
return = DL . return
x >>= f = DL . nub $ (dL x) >>= (dL . f)
...Do you spot the error? The problem is that nub :: Eq a => [a] -> [a] and so x >>= f is only defined under the condition f :: Eq b => a -> DistinctList b, whereas the compiler demands f :: a -> DistinctList b. Is there some way I can proceed anyway?
Stepping back, suppose I have a would-be instance that is only defined under some condition on the parametric type's variable. I understand that this is generally not allowed because other code written with the type class cannot be guaranteed to supply parameter values that obey the condition. But are there circumstances where this still can be carried out? If so, how?

Here is an adaptation of the technique applied in set-monad to your case.
Note there is, as there must be, some "cheating". The structure includes extra value constructors to represent "return" and "bind". These act as suspended computations that need to be run. The Eq instance is there part of the run function, while the constructors that create the "suspension" are Eq free.
{-# LANGUAGE GADTs #-}
import qualified Data.List as L
import qualified Data.Functor as F
import qualified Control.Applicative as A
import Control.Monad
-- for reference, the bind operation to be implemented
-- bind operation requires Eq
dlbind :: Eq b => [a] -> (a -> [b]) -> [b]
dlbind xs f = L.nub $ xs >>= f
-- data structure comes with incorporated return and bind
-- `Prim xs` wraps a list into a DL
data DL a where
Prim :: [a] -> DL a
Return :: a -> DL a
Bind :: DL a -> (a -> DL b) -> DL b
-- converts a DL to a list
run :: Eq a => DL a -> [a]
run (Prim xs) = xs
run (Return x) = [x]
run (Bind (Prim xs) f) = L.nub $ concatMap (run . f) xs
run (Bind (Return x) f) = run (f x)
run (Bind (Bind ma f) g) = run (Bind ma (\a -> Bind (f a) g))
-- lifting of Eq and Show instance
-- Note: you probably should provide a different instance
-- one where eq doesn't depend on the position of the elements
-- otherwise you break functor laws (and everything else)
instance (Eq a) => Eq (DL a) where
dxs == dys = run dxs == run dys
-- this "cheats", i.e. it will convert to lists in order to show.
-- executing returns and binds in the process
instance (Show a, Eq a) => Show (DL a) where
show = show . run
-- uses the monad instance
instance F.Functor DL where
fmap = liftM
-- uses the monad instance
instance A.Applicative DL where
pure = return
(<*>) = ap
-- builds the DL using Return and Bind constructors
instance Monad DL where
return = Return
(>>=) = Bind
-- examples with bind for a "normal list" and a "distinct list"
list = [1,2,3,4] >>= (\x -> [x `mod` 2, x `mod` 3])
dlist = (Prim [1,2,3,4]) >>= (\x -> Prim [x `mod` 2, x `mod` 3])
And here is a dirty hack to make it more efficient, addressing the points raised below about evaluation of bind.
{-# LANGUAGE GADTs #-}
import qualified Data.List as L
import qualified Data.Set as S
import qualified Data.Functor as F
import qualified Control.Applicative as A
import Control.Monad
dlbind xs f = L.nub $ xs >>= f
data DL a where
Prim :: Eq a => [a] -> DL a
Return :: a -> DL a
Bind :: DL b -> (b -> DL a) -> DL a
-- Fail :: DL a -- could be add to clear failure chains
run :: Eq a => DL a -> [a]
run (Prim xs) = xs
run (Return x) = [x]
run b#(Bind _ _) =
case foldChain b of
(Bind (Prim xs) f) -> L.nub $ concatMap (run . f) xs
(Bind (Return a) f) -> run (f a)
(Bind (Bind ma f) g) -> run (Bind ma (\a -> Bind (f a) g))
-- fold a chain ((( ... >>= f) >>= g) >>= h
foldChain :: DL u -> DL u
foldChain (Bind b2 g) = stepChain $ Bind (foldChain b2) g
foldChain dxs = dxs
-- simplify (Prim _ >>= f) >>= g
-- if (f x = Prim _)
-- then reduce to (Prim _ >>= g)
-- else preserve (Prim _ >>= f) >>= g
stepChain :: DL u -> DL u
stepChain b#(Bind (Bind (Prim xs) f) g) =
let dys = map f xs
pms = [Prim ys | Prim ys <- dys]
ret = [Return ys | Return ys <- dys]
bnd = [Bind ys f | Bind ys f <- dys]
in case (pms, ret, bnd) of
-- ([],[],[]) -> Fail -- could clear failure
(dxs#(Prim ys:_),[],[]) -> let Prim xs = joinPrims dxs (Prim $ mkEmpty ys)
in Bind (Prim $ L.nub xs) g
_ -> b
stepChain dxs = dxs
-- empty list with type via proxy
mkEmpty :: proxy a -> [a]
mkEmpty proxy = []
-- concatenate Prims in on Prim
joinPrims [] dys = dys
joinPrims (Prim zs : dzs) dys = let Prim xs = joinPrims dzs dys in Prim (zs ++ xs)
instance (Ord a) => Eq (DL a) where
dxs == dys = run dxs == run dys
instance (Ord a) => Ord (DL a) where
compare dxs dys = compare (run dxs) (run dys)
instance (Show a, Eq a) => Show (DL a) where
show = show . run
instance F.Functor DL where
fmap = liftM
instance A.Applicative DL where
pure = return
(<*>) = ap
instance Monad DL where
return = Return
(>>=) = Bind
-- cheating here, Prim is needed for efficiency
return' x = Prim [x]
s = [1,2,3,4] >>= (\x -> [x `mod` 2, x `mod` 3])
t = (Prim [1,2,3,4]) >>= (\x -> Prim [x `mod` 2, x `mod` 3])
r' = ((Prim [1..1000]) >>= (\x -> return' 1)) >>= (\x -> Prim [1..1000])

If your type could be a Monad, then it would need to work in functions that are parameterized across all monads, or across all applicatives. But it can't, because people store all kinds of weird things in their monads. Most notably, functions are very often stored as the value in an applicative context. For example, consider:
pairs :: Applicative f => f a -> f b -> f (a, b)
pairs xs ys = (,) <$> xs <*> ys
Even though a and b are both Eq, in order to combine them into an (a, b) pair, we needed to first fmap a function into xs, briefly producing a value of type f (b -> (a, b)). If we let f be your DL monad, we see that this can't work, because this function type has no Eq instance.
Since pairs is guaranteed to work for all Applicatives, and it does not work for your type, we can be sure your type is not Applicative. And since all Monads are also Applicative, we can conclude that your type cannot possibly be made an instance of Monad: it would violate the laws.

Related

What would an idiomatic, monadic version of maximumBy look like?

How can I get a maximum element of an effectful container where computing attribute to compare against also triggers an effect?
There has to be more readable way of doing things like:
latest dir = Turtle.fold (z (ls dir)) Fold.maximum
z :: MonadIO m => m Turtle.FilePath -> m (UTCTime, Turtle.FilePath)
z mx = do
x <- mx
d <- datefile x
return (d, x)
I used overloaded version rather than non-overloaded maximumBy but the latter seems better suite for ad-hoc attribute selection.
How can I be more methodic in solving similar problems?
So I know nothing about Turtle; no idea whether this fits well with the rest of the Turtle ecosystem. But since you convinced me in the comments that maximumByM is worth writing by hand, here's how I would do it:
maximumOnM :: (Monad m, Ord b) => (a -> m b) -> [a] -> m a
maximumOnM cmp [x] = return x -- skip the effects if there's no need for comparison
maximumOnM cmp (x:xs) = cmp x >>= \b -> go x b xs where
go x b [] = return x
go x b (x':xs) = do
b' <- cmp x'
if b < b' then go x' b' xs else go x b xs
I generally prefer the *On versions of things -- which take a function that maps to an Orderable element -- to the *By versions -- which take a function that does the comparison directly. A maximumByM would be similar but have a type like Monad m => (a -> a -> m Ordering) -> [a] -> m a, but this would likely force you to redo effects for each a, and I'm guessing it's not what you want. I find *On more often matches with the thing I want to do and the performance characteristics I want.
Since you're already familiar with Fold, you might want to get to know FoldM, which is similar.
data FoldM m a b =
-- FoldM step initial extract
forall x . FoldM (x -> a -> m x) (m x) (x -> m b)
You can write:
maximumOnM ::
(Ord b, Monad m)
=> (a -> m b) -> FoldM m a (Maybe a)
maximumOnM f = FoldM combine (pure Nothing) (fmap snd)
where
combine Nothing a = do
f_a <- f a
pure (Just (f_a, a))
combine o#(Just (f_old, old)) new = do
f_new <- f new
if f_new > f_old
then pure $ Just (f_new, new)
else pure o
Now you can use Foldl.foldM to run the fold on a list (or other Foldable container). Like Fold, FoldM has an Applicative instance, so you can combine multiple effectful folds into one that interleaves the effects of each of them and combines their results.
It's possible to run effects on foldables using reducers package.
I'm not sure if it's correct, but it leverages existing combinators and instances (except for Bounded (Maybe a)).
import Data.Semigroup.Applicative (Ap(..))
import Data.Semigroup.Reducer (foldReduce)
import Data.Semigroup (Max(..))
import System.IO (withFile, hFileSize, IOMode(..))
-- | maxLength
--
-- >>> getMax $ maxLength ["abc","a","hello",""]
-- 5
maxLength :: [String] -> (Max Int)
maxLength = foldReduce . map (length)
-- | maxLengthIO
--
-- Note, this runs IO...
--
-- >>> (getAp $ maxLengthIO ["package.yaml", "src/Lib.hs"]) >>= return . getMax
-- Just 1212
--
-- >>> (getAp $ maxLengthIO []) >>= return . getMax
-- Nothing
maxLengthIO :: [String] -> Ap IO (Max (Maybe Integer))
maxLengthIO xs = foldReduce (map (fmap Just . f) xs) where
f :: String -> IO Integer
f s = withFile s ReadMode hFileSize
instance Ord a => Bounded (Maybe a) where
maxBound = Nothing
minBound = Nothing

Mapping while showing intermediate states

I need a function that does this:
>>> func (+1) [1,2,3]
[[2,2,3],[2,3,3],[2,3,4]]
My real case is more complex, but this example shows the gist of the problem. The main difference is that in reality using indexes would be infeasible. The List should be a Traversable or Foldable.
EDIT: This should be the signature of the function:
func :: Traversable t => (a -> a) -> t a -> [t a]
And closer to what I really want is the same signature to traverse but can't figure out the function I have to use, to get the desired result.
func :: (Traversable t, Applicative f) :: (a -> f a) -> t a -> f (t a)
It looks like #Benjamin Hodgson misread your question and thought you wanted f applied to a single element in each partial result. Because of this, you've ended up thinking his approach doesn't apply to your problem, but I think it does. Consider the following variation:
import Control.Monad.State
indexed :: (Traversable t) => t a -> (t (Int, a), Int)
indexed t = runState (traverse addIndex t) 0
where addIndex x = state (\k -> ((k, x), k+1))
scanMap :: (Traversable t) => (a -> a) -> t a -> [t a]
scanMap f t =
let (ti, n) = indexed (fmap (\x -> (x, f x)) t)
partial i = fmap (\(k, (x, y)) -> if k < i then y else x) ti
in map partial [1..n]
Here, indexed operates in the state monad to add an incrementing index to elements of a traversable object (and gets the length "for free", whatever that means):
> indexed ['a','b','c']
([(0,'a'),(1,'b'),(2,'c')],3)
and, again, as Ben pointed out, it could also be written using mapAccumL:
indexed = swap . mapAccumL (\k x -> (k+1, (k, x))) 0
Then, scanMap takes the traversable object, fmaps it to a similar structure of before/after pairs, uses indexed to index it, and applies a sequence of partial functions, where partial i selects "afters" for the first i elements and "befores" for the rest.
> scanMap (*2) [1,2,3]
[[2,2,3],[2,4,3],[2,4,6]]
As for generalizing this from lists to something else, I can't figure out exactly what you're trying to do with your second signature:
func :: (Traversable t, Applicative f) => (a -> f a) -> t a -> f (t a)
because if you specialize this to a list you get:
func' :: (Traversable t) => (a -> [a]) -> t a -> [t a]
and it's not at all clear what you'd want this to do here.
On lists, I'd use the following. Feel free to discard the first element, if not wanted.
> let mymap f [] = [[]] ; mymap f ys#(x:xs) = ys : map (f x:) (mymap f xs)
> mymap (+1) [1,2,3]
[[1,2,3],[2,2,3],[2,3,3],[2,3,4]]
This can also work on Foldable, of course, after one uses toList to convert the foldable to a list. One might still want a better implementation that would avoid that step, though, especially if we want to preserve the original foldable type, and not just obtain a list.
I just called it func, per your question, because I couldn't think of a better name.
import Control.Monad.State
func f t = [evalState (traverse update t) n | n <- [0..length t - 1]]
where update x = do
n <- get
let y = if n == 0 then f x else x
put (n-1)
return y
The idea is that update counts down from n, and when it reaches 0 we apply f. We keep n in the state monad so that traverse can plumb n through as you walk across the traversable.
ghci> func (+1) [1,1,1]
[[2,1,1],[1,2,1],[1,1,2]]
You could probably save a few keystrokes using mapAccumL, a HOF which captures the pattern of traversing in the state monad.
This sounds a little like a zipper without a focus; maybe something like this:
data Zippy a b = Zippy { accum :: [b] -> [b], rest :: [a] }
mapZippy :: (a -> b) -> [a] -> [Zippy a b]
mapZippy f = go id where
go a [] = []
go a (x:xs) = Zippy b xs : go b xs where
b = a . (f x :)
instance (Show a, Show b) => Show (Zippy a b) where
show (Zippy xs ys) = show (xs [], ys)
mapZippy succ [1,2,3]
-- [([2],[2,3]),([2,3],[3]),([2,3,4],[])]
(using difference lists here for efficiency's sake)
To convert to a fold looks a little like a paramorphism:
para :: (a -> [a] -> b -> b) -> b -> [a] -> b
para f b [] = b
para f b (x:xs) = f x xs (para f b xs)
mapZippy :: (a -> b) -> [a] -> [Zippy a b]
mapZippy f xs = para g (const []) xs id where
g e zs r d = Zippy nd zs : r nd where
nd = d . (f e:)
For arbitrary traversals, there's a cool time-travelling state transformer called Tardis that lets you pass state forwards and backwards:
mapZippy :: Traversable t => (a -> b) -> t a -> t (Zippy a b)
mapZippy f = flip evalTardis ([],id) . traverse g where
g x = do
modifyBackwards (x:)
modifyForwards (. (f x:))
Zippy <$> getPast <*> getFuture

Recursion scheme in Haskell for repeatedly breaking datatypes into "head" and "tail" and yielding a structure of results

In Haskell, I recently found the following function useful:
listCase :: (a -> [a] -> b) -> [a] -> [b]
listCase f [] = []
listCase f (x:xs) = f x xs : listCase f xs
I used it to generate sliding windows of size 3 from a list, like this:
*Main> listCase (\_ -> take 3) [1..5]
[[2,3,4],[3,4,5],[4,5],[5],[]]
Is there a more general recursion scheme which captures this pattern? More specifically, that allows you to generate a some structure of results by repeatedly breaking data into a "head" and "tail"?
What you are asking for is a comonad. This may sound scarier than monad, but is a simpler concept (YMMV).
Comonads are Functors with additional structure:
class Functor w => Comonad w where
extract :: w a -> a
duplicate :: w a -> w (w a)
extend :: (w a -> b) -> w a -> w b
(extendand duplicate can be defined in terms of each other)
and laws similar to the monad laws:
duplicate . extract = id
duplicate . fmap extract = id
duplicate . duplicate = fmap duplicate . duplicate
Specifically, the signature (a -> [a] -> b) takes non-empty Lists of type a. The usual type [a] is not an instance of a comonad, but the non-empty lists are:
data NE a = T a | a :. NE a deriving Functor
instance Comonad NE where
extract (T x) = x
extract (x :. _) = x
duplicate z#(T _) = T z
duplicate z#(_ :. xs) = z :. duplicate xs
The comonad laws allow only this instance for non-empty lists (actually a second one).
Your function then becomes
extend (take 3 . drop 1 . toList)
Where toList :: NE a -> [a] is obvious.
This is worse than the original, but extend can be written as =>> which is simpler if applied repeatedly.
For further information, you may start at What is the Comonad typeclass in Haskell?.
This looks like a special case of a (jargon here but it can help with googling) paramorphism, a generalisation of primitive recursion to all initial algebras.
Reimplementing ListCase
Let's have a look at how to reimplement your function using such a combinator. First we define the notion of paramorphism: a recursion principle where not only the result of the recursive call is available but also the entire substructure this call was performed on:
The type of paraList tells me that in the (:) case, I will have access to the head, the tail and the value of the recursive call on the tail and that I need to provide a value for the base case.
module ListCase where
paraList :: (a -> [a] -> b -> b) -- cons
-> b -- nil
-> [a] -> b -- resulting function on lists
paraList c n [] = n
paraList c n (x : xs) = c x xs $ paraList c n xs
We can now give an alternative definition of listCase:
listCase' :: (a -> [a] -> b) -> [a] -> [b]
listCase' c = paraList (\ x xs tl -> c x xs : tl) []
Considering the general case
In the general case, we are interested in building a definition of paramorphism for all data structures defined as the fixpoint of a (strictly positive) functor. We use the traditional fixpoint operator:
newtype Fix f = Fix { unFix :: f (Fix f) }
This builds an inductive structure layer by layer. The layers have an f shape which maybe better grasped by recalling the definition of List using this formalism. A layer is either Nothing (we're done!) or Just (head, tail):
newtype ListF a as = ListF { unListF :: Maybe (a, as) }
type List a = Fix (ListF a)
nil :: List a
nil = Fix $ ListF $ Nothing
cons :: a -> List a -> List a
cons = curry $ Fix . ListF .Just
Now that we have this general framework, we can define para generically for all Fix f where f is a functor:
para :: Functor f => (f (Fix f, b) -> b) -> Fix f -> b
para alg = alg . fmap (\ rec -> (rec, para alg rec)) . unFix
Of course, ListF a is a functor. Meaning we could use para to reimplement paraList and listCase.
instance Functor (ListF a) where fmap f = ListF . fmap (fmap f) . unListF
paraList' :: (a -> List a -> b -> b) -> b -> List a -> b
paraList' c n = para $ maybe n (\ (a, (as, b)) -> c a as b) . unListF
listCase'' :: (a -> List a -> b) -> List a -> List b
listCase'' c = paraList' (\ x xs tl -> cons (c x xs) tl) nil
You can implement a simple bijection toList, fromList to test it if you want. I could not be bothered to reimplement take so it's pretty ugly:
toList :: [a] -> List a
toList = foldr cons nil
fromList :: List a -> [a]
fromList = paraList' (\ x _ tl -> x : tl) []
*ListCase> fmap fromList . fromList . listCase'' (\ _ as -> toList $ take 3 $ fromList as). toList $ [1..5]
[[2,3,4],[3,4,5],[4,5],[5],[]]

Is it possible to fold <*> in haskell?

I want to realize something like
fun1 f a_ziplist
for example
getZipList $ (\x y z -> x*y+z) <$> ZipList [4,7] <*> ZipList [6,9] <*> ZipList [5,10]
f = (\x y z -> x*y+z)
ziplist = [[4,7],[6,9],[5,10]]
To do this, I want to recursively apply <*> like
foldx (h:w) = h <*> foldx w
foldx (w:[]) = w
but it seems impossible to make <*> recursive.
Let's play with the types in ghci, to see where they carry us.
λ import Control.Applicative
The type of (<*>)
λ :t (<*>)
(<*>) :: Applicative f => f (a -> b) -> f a -> f b
The type of foldr:
λ :t Prelude.foldr
Prelude.foldr :: (a -> b -> b) -> b -> [a] -> b
Perhaps we could use (<*>) as the function that is passed as the first parameter of foldr. What would be the type?
λ :t Prelude.foldr (<*>)
Prelude.foldr (<*>) :: Applicative f => f a -> [f (a -> a)] -> f a
So it seems that it takes an initial value in an applicative context, and a list of functions in an applicative context, and returns another applicative.
For example, using ZipList as the applicative:
λ getZipList $ Prelude.foldr (<*>) (ZipList [2,3]) [ ZipList [succ,pred], ZipList [(*2)] ]
The result is:
[5]
I'm not sure if this is what the question intended, but it seems like a natural way to fold using (<*>).
If the ziplist argument has to be a plain list, it looks impossible. This is because fold f [a1,...,an] must be well typed for every n, hence f must be a function type taking at least n arguments for every n, hence infinitely many.
However, if you use a GADT list type, in which values expose their length as a type-level natural you can achieve something similar to what you want.
{-# LANGUAGE DataKinds, KindSignatures, TypeFamilies, GADTs #-}
import Control.Applicative
-- | Type-level naturals
data Nat = Z | S Nat
-- | Type family for n-ary functions
type family Fn (n :: Nat) a b
type instance Fn Z a b = b
type instance Fn (S n) a b = a -> Fn n a b
-- | Lists exposing their length in their type
data List a (n :: Nat) where
Nil :: List a Z
Cons :: a -> List a n -> List a (S n)
-- | General <*> applied to a list of arguments of the right length
class Apply (n :: Nat) where
foldF :: Applicative f => f (Fn n a b) -> List (f a) n -> f b
instance Apply Z where
foldF f0 Nil = f0
instance Apply n => Apply (S n) where
foldF fn (Cons x xs) = foldF (fn <*> x) xs
test :: [(Integer,Integer,Integer)]
test = foldF (pure (,,)) (Cons [10,11] (Cons [20,21] (Cons [30,31] Nil)))
-- Result: [(10,20,30),(10,20,31),(10,21,30),(10,21,31)
-- ,(11,20,30),(11,20,31),(11,21,30),(11,21,31)]
In general folding (<*>) is tricky because of types, as others have mentioned. But for your specific example, where your ziplist elements are all of the same type, you can use a different method and make your calculation work with a small change to f to make it take a list argument instead of single elements:
import Data.Traversable
import Control.Applicative
f = (\[x,y,z] -> x*y+z)
ziplist = [[4,7],[6,9],[5,10]]
fun1 f l = getZipList $ f <$> traverse ZipList l
It's even possible to achieve this with just Data.List and Prelude functions:
fun1 f = map f . transpose
To do this, I want to recursively apply <*> like
foldx (h:w) = h <*> foldx w
foldx (w:[]) = w
but it seems impossible to make <*> recursive.
I think you're getting confused over left- vs. right-associativity. danidiaz reformulates this in terms of foldr (<*>), which is quite useful for this analysis. The documentation gives a useful definition of foldr in terms of expansion:
foldr f z [x1, x2, ..., xn] == x1 `f` (x2 `f` ... (xn `f` z) ...)
So applying that to your case:
foldr (<*>) z [x1, x2, ..., xn] == x1 <*> (x2 <*> ... (xn <*> z) ...)
Note the parens. <*> is left-associative, so the foldr expansion is different from:
x1 <*> x2 <*> ... <*> xn <*> z == ((... (x1 <*> x2) <*> ...) <*> xn) <*> z
Let's think also a bit more about what foldr (<*>) means. Another way of thinking of this is to rewrite it just slightly:
flip (foldr (<*>)) :: Applicative f :: [f (a -> a)] -> f a -> f a
Types of the form (a -> a) are often called endomorphisms, and they form a monoid, with composition as the operation and id as the identity. There's a newtype wrapper in Data.Monoid for these:
newtype Endo a = Endo { appEndo :: a -> a }
instance Monoid (Endo a) where
mempty = id
mappend = (.)
This gives us yet another way to think of foldr (<*>), by formulating it in terms of Endo:
toEndo :: Applicative f => f (a -> a) -> Endo (f a)
toEndo ff = Endo (ff <*>)
And then what foldr (<*>) does, basically, is reduce this monoid:
foldrStar :: Applicative f => [f (a -> a)] -> Endo (f a)
foldrStar fs = mconcat $ map toMonoid fs
what you have is equivalent to zipWith3 (\x y z -> x*y+z) [4,7] [6,9] [5,10].
it's impossible to foldl the <*> (and you do need foldl as <*> associates to the left) because foldl :: (a -> b -> a) -> a -> [b] -> a i.e. it's the same a in a -> b -> a, but when you apply your ternary function on first list of numbers, you get a list of binary functions, and then unary functions at the next step, and only finally, numbers (all different types, then):
>> let xs = map ZipList [[4,7],[6,9],[5,10]]
>> getZipList $ pure (\x y z -> x*y+z) <*> (xs!!0) <*> (xs!!1) <*> (xs!!2)
[29,73]
>> foldl (<*>) (pure (\x y z -> x*y+z)) xs
<interactive>:1:6:
Occurs check: cannot construct the infinite type: b = a -> b
Expected type: f (a -> b)
Inferred type: f b
In the first argument of `foldl', namely `(<*>)'
In the expression: foldl (<*>) (pure (\ x y z -> x * y + z)) xs
>> :t foldl
foldl :: ( a -> b -> a ) -> a -> [b] -> a
>> :t (<*>)
(<*>) :: (Applicative f) => f (a -> b) -> f a -> f b -- f (a -> b) = f b
The answer by chi addresses this, but the arity is fixed (for a particular code). In effect, what that answer really does is defining (a restricted version of) zipWithN (well, here, when used with the ZipList applicative - obviously, it works with any applicative in general) for any N (but just for the a -> a -> a -> ... -> a type of functions), whereas e.g.
zipWith7 :: (a -> b -> c -> d -> e -> f -> g -> h) ->
[a] -> [b] -> [c] -> [d] -> [e] -> [f] -> [g] -> [h]
(in other words, zipWith3 (,,) [10,11] ([20,21]::[Integer]) ([30,31]::[Int]) works).

Filter an infinite list of monadic values

Perhaps this is obvious, but I can't seem to figure out how to best filter an infinite list of IO values. Here is a simplified example:
infinitelist :: [IO Int]
predicate :: (a -> Bool)
-- how to implement this?
mysteryFilter :: (a -> Bool) -> [IO a] -> IO [a]
-- or perhaps even this?
mysteryFilter' :: (a -> Bool) -> [IO a] -> [IO a]
Perhaps I have to use sequence in some way, but I want the evaluation to be lazy. Any suggestions? The essence is that for each IO Int in the output we might have to check several IO Int values in the input.
Thank you!
Not doable without using unsafeInterleaveIO or something like it. You can't write a filter with the second type signature, since if you could you could say
unsafePerformIOBool :: IO Bool -> Bool
unsafePerformIOBool m = case mysteryFilter' id [m] of
[] -> False
(_:_) -> True
Similarly, the first type signature isn't going to work--any recursive call will give you back something of type IO [a], but then to build a list out of this you will need to perform this action before returning a result (since : is not in IO you need to use >>=). By induction you will have to perform all the actions in the list (which takes forever when the list is infinitely long) before you can return a result.
unsafeInterleaveIO resolves this, but is unsafe.
mysteryFilter f [] = return []
mysteryFilter f (x:xs) = do ys <- unsafeInterleaveIO $ mysteryFilter f xs
y <- x
if f y then return (y:ys) else return ys
the problem is that this breaks the sequence that the monad is supposed to provide. You no longer have guarantees about when your monadic actions happen (they might never happen, they might happen multiple times, etc).
Lists just do not play nice with IO. This is why we have the plethora of streaming types (Iteratees, Conduits, Pipes, etc).
The simplest such type is probably
data MList m a = Nil | Cons a (m (MList m a))
note that we observe that
[a] == MList Id a
since
toMList :: [a] -> MList Id a
toMList [] = Nil
toMList (x:xs) = Cons x $ return $ toMList xs
fromMList :: MList Id a -> [a]
fromMList Nil = []
fromMList (Cons x xs) = x:(fromMList . runId $ xs)
also, MList is a functor
instance Functor m => Functor (MList m) where
fmap f Nil = Nil
fmap f (Cons x xs) = Cons (f x) (fmap (fmap f) xs)
and it is a functor in the category of Functor's and Natural transformations.
trans :: Functor m => (forall x. m x -> n x) -> MList m a -> MList n a
trans f Nil = Nil
trans f (Cons x xs) = Cons x (f (fmap trans f xs))
with this it is easy to write what you want
mysteryFilter :: (a -> Bool) -> MList IO (IO a) -> IO (MList IO a)
mysteryFilter f Nil = return Nil
mysteryFilter f (Cons x xs)
= do y <- x
let ys = liftM (mysteryFilter f) xs
if f y then Cons y ys else ys
or various other similar functions.

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