{-# LANGUAGE BangPatterns #-} {-# LANGUAGE CPP #-} {-# LANGUAGE DeriveFoldable #-} {-# LANGUAGE DeriveTraversable #-} {-# LANGUAGE FlexibleInstances #-} {-# LANGUAGE GeneralizedNewtypeDeriving #-} {-# LANGUAGE MultiParamTypeClasses #-} {-# LANGUAGE UndecidableInstances #-} {-| The `ListT` type is like a list that lets you interleave effects between each element of the list. The type's definition is very short: > -- Every `ListT` begins with an outermost effect (the `m`) > newtype ListT m a = ListT { next :: m (Step m a) } > > > -- The return value of that effect is either > -- * Cons: a new list element followed by the rest of the list > -- * Nil : an empty list > data Step m a = Cons a (ListT m a) | Nil You most commonly use this type when you wish to generate each element of the list using `IO`. For example, you can read lines from standard input: > import List.Transformer > > import qualified System.IO > > stdin :: ListT IO String > stdin = ListT (do > eof <- System.IO.isEOF > if eof > then return Nil > else do > string <- getLine > return (Cons string stdin) ) You can also loop over a `ListT` to consume elements one-at-a-time. You \"pay as you go\" for effects, only running what you actually need: > stdout :: ListT IO String -> IO () > stdout strings = do > s <- next strings > case s of > Nil -> return () > Cons string strings' -> do > putStrLn string > stdout strings' Combining @stdin@ and @stdout@ forwards lines one-by-one from standard input to standard output: > main :: IO () > main = stdout stdin These lines stream in constant space, never retaining more than one line in memory: > $ runghc aboveExample.hs > Test > Test > 123 > 123 > ABC > ABC > > $ Sometimes we can simplify the code by taking advantage of the fact that the `Monad` instance for `ListT` behaves like a list comprehension: > stdout :: ListT IO String -> IO () > stdout strings = runListT (do > string <- strings > liftIO (putStrLn string) ) You can read the above code as saying: \"for each @string@ in @strings@, call `putStrLn` on @string@. You can even use list comprehension syntax if you enable the @MonadComprehensions@ language extension: > stdout strings = runListT [ r | str <- strings, r <- liftIO (putStrLn str) ] The most important operations that you should familiarize yourself with are: * `empty`, which gives you an empty `ListT` with 0 elements > empty :: ListT IO a * `pure` / `return`, which both convert a value into a one-element `ListT` > pure, return :: a -> ListT IO a * `liftIO`, which converts an `IO` action into a one-element `ListT` > liftIO :: IO a -> ListT IO a * (`<|>`), which concatenates two `ListT`s > (<|>) :: ListT IO a -> ListT IO a -> ListT IO a * (`>>=`), which powers @do@ notation and @MonadComprehensions@: > (>>=) :: ListT IO a -> (a -> ListT IO b) -> ListT IO b For example, suppose you want to build a `ListT` with three elements and no effects. You could just write: > pure 1 <|> pure 2 <|> pure 3 :: ListT IO Int ... although you would probably prefer to use `select` instead: > select :: [a] -> ListT IO a > > select [1, 2, 3] :: ListT IO Int To test your understanding, guess what this code does and then test your guess by running the code: > import List.Transformer > > strings :: ListT IO String > strings = do > _ <- select (repeat ()) > liftIO (putStrLn "Say something:") > liftIO getLine > > main :: IO () > main = runListT (do > string <- pure "Hello, there!" <|> strings > liftIO (putStrLn string) ) This library does not provide utilities like `mapM` because there are many possible minor variations on `mapM` that we could write, such as: > mapM :: Monad m => (a -> m b) -> [a] -> ListT m b > mapM f xs = do > x <- select xs > lift (f x) > > -- Alternatively, using MonadComprehensions: > mapM f xs = [ r | x <- select xs, r <- lift (f x) ] ... or: > mapM :: Monad m => (a -> m b) -> ListT m a -> ListT m b > mapM f xs = do > x <- xs > lift (f x) > > -- Alternatively, using MonadComprehensions: > mapM f xs = [ r | x <- xs, r <- lift (f x) ] ... or: > mapM :: Monad m => (a -> ListT m b) -> ListT m a -> ListT m b > mapM f xs = do > x <- xs > f x > > -- Alternatively, using MonadComprehensions: > mapM f xs = [ r | x <- xs, r <- f x ] > > -- Alternatively, using a pre-existing operator from "Control.Monad" > mapM = (=<<) Whichever one you prefer, all three variations still stream in constant space (unlike @"Control.Monad".`mapM`@, which buffers the entire output list before returning a single element). This library is designed to stream results in constant space and does not expose an obvious way to collect all the results into memory. As a rule of thumb if you think you need to collect all the results in memory try to instead see if you can consume the results as they are being generated (such as in all the above examples). If you can stream the data from start to finish then your code will use significantly less memory and your program will become more responsive. -} module List.Transformer ( -- * ListT ListT(..) , runListT , fold , foldM , select , take , drop , dropWhile , takeWhile , unfold , zip -- * Step , Step(..) -- * Alternative instances , ZipListT(..) -- * Re-exports , MonadTrans(..) , MonadIO(..) , Alternative(..) ) where #if MIN_VERSION_base(4,8,0) import Control.Applicative (Alternative(..), liftA2) #else import Control.Applicative (Applicative(..), Alternative(..), liftA2) import Data.Foldable (Foldable) import Data.Functor ((<$)) import Data.Monoid (Monoid(..)) import Data.Traversable (Traversable) #endif import Control.Monad (MonadPlus(..)) import Control.Monad.Error.Class (MonadError(..)) #if MIN_VERSION_base(4,9,0) && !(MIN_VERSION_base(4,13,0)) import Control.Monad.Fail (MonadFail(..)) #endif import Control.Monad.State.Class (MonadState(..)) import Control.Monad.Reader.Class (MonadReader(..)) import Control.Monad.Trans (MonadTrans(..), MonadIO(..)) import Data.Semigroup (Semigroup(..)) import Prelude hiding (drop, dropWhile, pred, take, takeWhile, zip) import qualified Data.Foldable -- $setup -- >>> :set -XNoMonomorphismRestriction {-| This is like a list except that you can interleave effects between each list element. For example: > stdin :: ListT IO String > stdin = ListT (do > eof <- System.IO.isEOF > if eof > then return Nil > else do > line <- getLine > return (Cons line stdin) ) The mnemonic is \"List Transformer\" because this type takes a base `Monad`, @\'m\'@, and returns a new transformed `Monad` that adds support for list comprehensions -} newtype ListT m a = ListT { next :: m (Step m a) } deriving (Foldable, Traversable) instance MonadTrans ListT where lift m = ListT (do x <- m return (Cons x empty) ) instance Monad m => Functor (ListT m) where fmap k (ListT m) = ListT (do s <- m return (fmap k s) ) instance Monad m => Applicative (ListT m) where pure x = ListT (return (Cons x empty)) ListT m <*> l = ListT (do s <- m case s of Nil -> return Nil Cons f l' -> next (fmap f l <|> (l' <*> l)) ) ListT m *> l = ListT (do s <- m case s of Nil -> return Nil Cons _ l' -> next (l <|> (l' *> l)) ) ListT m <* l = ListT (do s <- m case s of Nil -> return Nil Cons x l' -> next ((x <$ l) <|> (l' <* l)) ) instance Monad m => Monad (ListT m) where return = pure ListT m >>= k = ListT (do s <- m case s of Nil -> return Nil Cons x l' -> next (k x <|> (l' >>= k)) ) #if !(MIN_VERSION_base(4,13,0)) fail _ = mzero #endif instance Monad m => Alternative (ListT m) where empty = ListT (return Nil) ListT m <|> l = ListT (do s <- m case s of Nil -> next l Cons x l' -> return (Cons x (l' <|> l)) ) instance Monad m => MonadPlus (ListT m) where mzero = empty mplus = (<|>) #if MIN_VERSION_base(4,9,0) instance Monad m => MonadFail (ListT m) where fail _ = mzero #endif instance (Monad m, Data.Semigroup.Semigroup a) => Data.Semigroup.Semigroup (ListT m a) where (<>) = liftA2 (<>) instance (Monad m, Data.Semigroup.Semigroup a, Monoid a) => Monoid (ListT m a) where mempty = pure mempty #if !(MIN_VERSION_base(4,11,0)) mappend = (<>) #endif instance MonadIO m => MonadIO (ListT m) where liftIO m = lift (liftIO m) instance MonadError e m => MonadError e (ListT m) where throwError e = ListT (throwError e) catchError (ListT m) k = ListT (catchError m (next . k)) instance MonadReader i m => MonadReader i (ListT m) where ask = lift ask local k (ListT m) = ListT (do s <- local k m case s of Nil -> return Nil Cons x l -> return (Cons x (local k l)) ) reader k = lift (reader k) instance MonadState s m => MonadState s (ListT m) where get = lift get put x = lift (put x) state k = lift (state k) instance (Monad m, Num a) => Num (ListT m a) where fromInteger n = pure (fromInteger n) negate = fmap negate abs = fmap abs signum = fmap signum (+) = liftA2 (+) (*) = liftA2 (*) (-) = liftA2 (-) instance (Monad m, Fractional a) => Fractional (ListT m a) where fromRational n = pure (fromRational n) recip = fmap recip (/) = liftA2 (/) instance (Monad m, Floating a) => Floating (ListT m a) where pi = pure pi exp = fmap exp sqrt = fmap sqrt log = fmap log sin = fmap sin tan = fmap tan cos = fmap cos asin = fmap asin atan = fmap atan acos = fmap acos sinh = fmap sinh tanh = fmap tanh cosh = fmap cosh asinh = fmap asinh atanh = fmap atanh acosh = fmap acosh (**) = liftA2 (**) logBase = liftA2 logBase {-| Use this to drain a `ListT`, running it to completion and discarding all values. For example: > stdout :: ListT IO String -> IO () > stdout l = runListT (do > str <- l > liftIO (putStrLn str) ) The most common specialized type for `runListT` will be: > runListT :: ListT IO a -> IO () -} runListT :: Monad m => ListT m a -> m () runListT (ListT m) = do s <- m case s of Nil -> return () Cons _ l' -> runListT l' {-| Use this to fold a `ListT` into a single value. This is designed to be used with the @foldl@ library: > import Control.Foldl (purely) > import List.Transformer (fold) > > purely fold :: Monad m => Fold a b -> ListT m a -> m b ... but you can also use the `fold` function directly: > fold (+) 0 id :: Num a => ListT m a -> m a -} fold :: Monad m => (x -> a -> x) -> x -> (x -> b) -> ListT m a -> m b fold step begin done l = go begin l where go !x (ListT m) = do s <- m case s of Cons a l' -> go (step x a) l' Nil -> return (done x) {-| Use this to fold a `ListT` into a single value. This is designed to be used with the @foldl@ library: > import Control.Foldl (impurely) > import List.Transformer (fold) > > impurely fold :: Monad m => FoldM m a b -> ListT m a -> m b ... but you can also use the `foldM` function directly. -} foldM :: Monad m => (x -> a -> m x) -> m x -> (x -> m b) -> ListT m a -> m b foldM step begin done l0 = do x0 <- begin go x0 l0 where go !x (ListT m) = do s <- m case s of Cons a l' -> do x' <- step x a go x' l' Nil -> done x {-| Convert any collection that implements `Foldable` to another collection that implements `Alternative` For this library, the most common specialized type for `select` will be: > select :: [a] -> ListT IO a -} select :: (Foldable f, Alternative m) => f a -> m a select = Data.Foldable.foldr cons empty where cons x xs = pure x <|> xs -- | @take n xs@ takes @n@ elements from the head of @xs@. -- -- >>> let list xs = do x <- select xs; liftIO (print (show x)); return x -- >>> let sum = fold (+) 0 id -- >>> sum (take 2 (list [5,4,3,2,1])) -- "5" -- "4" -- 9 take :: Monad m => Int -> ListT m a -> ListT m a take n l | n <= 0 = empty | otherwise = ListT (do s <- next l case s of Cons a l' -> return (Cons a (take (n-1) l')) Nil -> return Nil) -- | @drop n xs@ drops @n@ elements from the head of @xs@, but still runs their -- effects. -- -- >>> let list xs = do x <- select xs; liftIO (print (show x)); return x -- >>> let sum = fold (+) 0 id -- >>> sum (drop 2 (list [5,4,3,2,1])) -- "5" -- "4" -- "3" -- "2" -- "1" -- 6 drop :: Monad m => Int -> ListT m a -> ListT m a drop n l | n <= 0 = l | otherwise = ListT (do s <- next l case s of Cons _ l' -> next (drop (n-1) l') Nil -> return Nil) -- | @dropWhile pred xs@ drops elements from the head of @xs@ if they -- satisfy the predicate, but still runs their effects. -- -- >>> let list xs = do x <- select xs; liftIO (print (show x)); return x -- >>> let sum = fold (+) 0 id -- >>> sum (dropWhile even (list [2,4,5,7,8])) -- "2" -- "4" -- "5" -- "7" -- "8" -- 20 dropWhile :: Monad m => (a -> Bool) -> ListT m a -> ListT m a dropWhile pred l = ListT (do n <- next l case n of Cons x l' | pred x -> next (dropWhile pred l') | otherwise -> return (Cons x l') Nil -> return Nil ) -- | @takeWhile pred xs@ takes elements from @xs@ until the predicate @pred@ fails -- -- >>> let list xs = do x <- select xs; liftIO (print (show x)); return x -- >>> let sum = fold (+) 0 id -- >>> sum (takeWhile even (list [2,4,5,7,8])) -- "2" -- "4" -- "5" -- 6 takeWhile :: Monad m => (a -> Bool) -> ListT m a -> ListT m a takeWhile pred l = ListT (do n <- next l case n of Cons x l' | pred x -> return (Cons x (takeWhile pred l')) _ -> return Nil ) -- | @unfold step seed@ generates a 'ListT' from a @step@ function and an -- initial @seed@. unfold :: Monad m => (b -> m (Maybe (a, b))) -> b -> ListT m a unfold step = loop where loop seed = ListT (do mx <- step seed case mx of Just (x, seed') -> return (Cons x (loop seed')) Nothing -> return Nil) -- | @zip xs ys@ zips two 'ListT' together, running the effects of each before -- possibly recursing. Notice in the example below, @4@ is output even though -- it has no corresponding element in the second list. -- -- >>> let list xs = do x <- select xs; liftIO (print (show x)); return x -- >>> runListT (zip (list [1,2,3,4,5]) (list [6,7,8])) -- "1" -- "6" -- "2" -- "7" -- "3" -- "8" -- "4" zip :: Monad m => ListT m a -> ListT m b -> ListT m (a, b) zip xs ys = ListT (do sx <- next xs sy <- next ys case (sx, sy) of (Cons x xs', Cons y ys') -> return (Cons (x, y) (zip xs' ys')) _ -> return Nil) {-| Pattern match on this type when you loop explicitly over a `ListT` using `next`. For example: > stdout :: ListT IO String -> IO () > stdout l = do > s <- next l > case s of > Nil -> return () > Cons x l' -> do > putStrLn x > stdout l' -} data Step m a = Cons a (ListT m a) | Nil deriving (Foldable, Traversable) instance Monad m => Functor (Step m) where fmap _ Nil = Nil fmap k (Cons x l) = Cons (k x) (fmap k l) -- | Similar to 'ZipList' in /base/: a newtype wrapper over 'ListT' that -- overrides its normal 'Applicative' instance (combine every combination) -- with one that "zips" outputs together one at a time. -- -- >>> let xs = do x <- select [1,2,3,4]; liftIO (print x) -- >>> let ys = do y <- select [5,6]; liftIO (print y) -- >>> runListT (xs *> ys) -- 1 -- 5 -- 6 -- 2 -- 5 -- 6 -- 3 -- 5 -- 6 -- 4 -- 5 -- 6 -- >>> runListT (getZipListT (ZipListT xs *> ZipListT ys)) -- 1 -- 5 -- 2 -- 6 -- 3 -- -- Note that the final "3" is printed even though it isn't paired with -- anything. -- -- While this can be used to do zipping, it is usually more convenient to -- just use 'zip'. This is more useful if you are working with a function -- that expects "an Applicative instance", written to be polymorphic over -- all Applicatives. newtype ZipListT m a = ZipListT { getZipListT :: ListT m a } deriving (Functor, Alternative, Foldable, Traversable, MonadTrans, Floating, Fractional, Num, Semigroup, Monoid) instance Monad m => Applicative (ZipListT m) where pure x = ZipListT go where go = ListT (pure (Cons x go)) ZipListT fs <*> ZipListT xs = ZipListT (fmap (uncurry ($)) (zip fs xs))