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GHC 9.10.3 · lts/ghc-9.10.x · 248f8f0 · 2026-10-05

Modulelist-transformer-1.1.1Haskell2010

List.Transformer

The ListT type is like a list that lets you interleave effects between each element of the list.

  • 3 types
  • 4 classes
  • 10 values

Introduction

0 declarations

The type's definition is very short:

newtype ListT m a = ListT { next :: m (Step m a) }

Every ListT begins with an outermost effect (the 'm', commonly IO). The return value of that effect is either:

data Step m a = Cons a (ListT m a) | Nil
  • Cons: a new list element followed by the rest of the list

  • Nil : an empty list

Example: stdin, stdout

You most commonly use the ListT 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<Enter>
Test
123<Enter>
123
ABC<Enter>
ABC
<Ctrl-D>
$

Core operations

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 :: a -> ListT IO a
liftIO :: IO a -> ListT IO a
(<|>) :: 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
select :: [a] -> ListT IO a

Monadic combination

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) ]

There are a few ways we could consider defining a ListT analogue to the mapM function from Prelude, but none are given in this library because they need require only (>>=) and some trivial lifting.

mapM                                :: (a -> IO b)       -> [a]        -> IO [b]
( \f xs -> xs        >>=        f ) :: (a -> ListT IO b) -> ListT IO a -> ListT IO b
( \f xs -> select xs >>= lift . f ) :: (a -> IO b)       -> [a]        -> ListT IO b
( \f xs -> xs        >>= lift . f ) :: (a -> IO b)       -> ListT IO a -> ListT IO b

A critical difference between mapM and ListT's monad is that ListT will stream in constant space, whereas mapM buffers the entire output list before returning a single element.

Exercise: Interaction

To test your understanding, guess what this code does and then test your guess by running the code:

import List.Transformer (ListT, runListT, liftIO, (<|>), select)
import Data.Foldable (asum)
import Data.List (repeat)

strings :: ListT IO String
strings = do
    select (repeat ())
    asum
        [ pure ""
        , pure "Say something:"
        , do
            x <- liftIO getLine
            return ("You said: " <|> x)
        ]

main :: IO ()
main = runListT (do
    string <- pure "Hello, there!" <|> strings
    liftIO (putStrLn string) )

ListT

1 declaration
newtypenewtype ListT (m :: Type -> Type) a
#

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

Constructors

Instances19MonadTrans, MFunctor, MonadError, MonadReader, MonadState, Monad, …

Consuming

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.

valuerunListT :: Monad m => ListT m a -> m ()
#

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 ()
valuefold :: Monad m => (x -> a -> x) -> x -> (x -> b) -> ListT m a -> m b
#

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
Example1 expression
fold (<>) "" id (select ["a", "b", "c", "d", "e"])"abcde"
valuefoldM :: Monad m => (x -> a -> m x) -> m x -> (x -> m b) -> ListT m a -> m b
#

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.

Constructing

empty is the empty list with no effects.

Use pure/return to construct a singleton list with no effects. Use liftIO to turn an effect into a singleton list whose sole element is the effect's result.

Suppose you want to build a ListT with three elements and no effects. You could write:

pure 1 <|> pure 2 <|> pure 3 :: ListT IO Int

... although you would probably prefer to use select instead:

select [1, 2, 3] :: ListT IO Int
valueselect :: (Foldable f, Alternative m) => f a -> m a
#

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
valueunfold :: Monad m => (b -> m (Maybe (a, b))) -> b -> ListT m a
#

unfold step seed generates a ListT from a step function and an initial seed.

Removing elements

valuetake :: Monad m => Int -> ListT m a -> ListT m a
#

take n xs takes n elements from the head of xs.

Example3 expressions
let list xs = do x <- select xs; liftIO (print (show x)); return xlet sum = fold (+) 0 idsum (take 2 (list [5,4,3,2,1]))"5""4"9
valuedrop :: Monad m => Int -> ListT m a -> ListT m a
#

drop n xs drops n elements from the head of xs, but still runs their effects.

Example3 expressions
let list xs = do x <- select xs; liftIO (print (show x)); return xlet sum = fold (+) 0 idsum (drop 2 (list [5,4,3,2,1]))"5""4""3""2""1"6
valuedropWhile :: Monad m => (a -> Bool) -> ListT m a -> ListT m a
#

dropWhile pred xs drops elements from the head of xs if they satisfy the predicate, but still runs their effects.

Example3 expressions
let list xs = do x <- select xs; liftIO (print (show x)); return xlet sum = fold (+) 0 idsum (dropWhile even (list [2,4,5,7,8]))"2""4""5""7""8"20
valuetakeWhile :: Monad m => (a -> Bool) -> ListT m a -> ListT m a
#

takeWhile pred xs takes elements from xs until the predicate pred fails

Example3 expressions
let list xs = do x <- select xs; liftIO (print (show x)); return xlet sum = fold (+) 0 idsum (takeWhile even (list [2,4,5,7,8]))"2""4""5"6

To filter elements from a list based on a predicate, use guard. For example, the following function is analogous to filter:

filter :: Monad m => (a -> m Bool) -> ListT m a -> ListT m a
filter pred as = do
    a <- as
    b <- lift (pred a)
    guard b
    return a

Concatenation

Use (<|>) to concatenate two lists.

(<|>) :: ListT IO a -> ListT IO a -> ListT IO a

Use asum to flatten a list of lists.

asum :: [ListT IO a] -> ListT IO a

Use join to flatten a ListT of ListTs.

join :: ListT IO (ListT IO a) -> ListT IO a

Pairwise combination

The (<>) operation joins every combination of an element from one list with an element from the other.

Example1 expression
runListT ( (select ["a", "b"] <> select ["1", "2", "3"]) >>= (liftIO . print) )"a1""a2""a3""b1""b2""b3"

This is the same combinatorial effect that (>>=) produces.

Example1 expression
runListT (do x <- select ["a", "b"]; y <- select ["1", "2", "3"]; liftIO (print (x <> y)))"a1""a2""a3""b1""b2""b3"
valuezip :: Monad m => ListT m a -> ListT m b -> ListT m (a, b)
#

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.

Example2 expressions
let list xs = do x <- select xs; liftIO (print (show x)); return xrunListT (zip (list [1,2,3,4,5]) (list [6,7,8]))"1""6""2""7""3""8""4"

Repetition

Unbounded repetition can be induced using select (repeat ()). For example, here are several functions analogous to cycle:

cycle1 :: Monad m => a -> ListT m a
cycle1 a = do
    select (Data.List.repeat ())
    return a
cycle2 :: Monad m => [a] -> ListT m a
cycle2 as = do
    select (Data.List.repeat ())
    select as
cycle3 :: Monad m => m a -> ListT m a
cycle3 m = do
    select (Data.List.repeat ())
    lift m
cycle4 :: Monad m => [m a] -> ListT m a
cycle4 ms = do
    select (Data.List.repeat ())
    m <- select ms
    lift m
cycle5 :: Monad m => ListT m a -> ListT m a
cycle5 x = do
    select (Data.List.repeat ())
    x
cycle6 :: Monad m => [ListT m a] -> ListT m a
cycle6 lists = do
    select (Data.List.repeat ())
    x <- select lists
    x

In a similar manner, we can use replicate as the initial selection to achieve bounded repetition:

replicate1 :: Monad m => Int -> a -> ListT m a
replicate1 n a = do
    select (Data.List.replicate n ())
    return a
replicate2 :: Monad m => Int -> [a] -> ListT m a
replicate2 n as = do
    select (Data.List.replicate n ())
    select as
replicate3 :: Monad m => Int -> m a -> ListT m a
replicate3 n m = do
    select (Data.List.replicate n ())
    lift m
replicate4 :: Monad m => Int -> [m a] -> ListT m a
replicate4 n ms = do
    select (Data.List.replicate n ())
    m <- select ms
    lift m
replicate5 :: Monad m => Int -> ListT m a -> ListT m a
replicate5 n x = do
    select (Data.List.replicate n ())
    x
replicate6 :: Monad m => Int -> [ListT m a] -> ListT m a
replicate6 n lists = do
    select (Data.List.replicate n ())
    x <- select lists
    x

Step

1 declaration
datadata Step (m :: Type -> Type) a
#

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'

Constructors

Instances4MFunctor, Functor, Foldable, Traversable

Alternative instances

1 declaration
newtypenewtype ZipListT (m :: Type -> Type) a
#

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.

Example4 expressions
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)156256356456runListT (getZipListT (ZipListT xs *> ZipListT ys))15263

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.

Constructors

Instances10Functor, Applicative, Foldable, Traversable, Alternative, Floating, …

Re-exports

4 declarations
classclass (forall (m :: Type -> Type). Monad m => Monad (t m)) => MonadTrans (t :: (Type -> Type) -> Type -> Type) where
#

The class of monad transformers. For any monad m, the result t m should also be a monad, and lift should be a monad transformation from m to t m, i.e. it should satisfy the following laws:

Since 0.6.0.0 and for GHC 8.6 and later, the requirement that t m be a Monad is enforced by the implication constraint forall m. Monad m => Monad (t m) enabled by the QuantifiedConstraints extension.

Ambiguity error with GHC 9.0 to 9.2.2

These versions of GHC have a bug (https://gitlab.haskell.org/ghc/ghc/-/issues/20582) which causes constraints like

(MonadTrans t, forall m. Monad m => Monad (t m)) => ...

to be reported as ambiguous. For transformers 0.6 and later, this can be fixed by removing the second constraint, which is implied by the first.

Methods

  • lift :: Monad m => m a -> t m a

    Lift a computation from the argument monad to the constructed monad.

Instances17MonadTrans, …
classclass Monad m => MonadIO (m :: Type -> Type) where
#

Monads in which IO computations may be embedded. Any monad built by applying a sequence of monad transformers to the IO monad will be an instance of this class.

Instances should satisfy the following laws, which state that liftIO is a transformer of monads:

Methods

  • liftIO :: IO a -> m a

    Lift a computation from the IO monad. This allows us to run IO computations in any monadic stack, so long as it supports these kinds of operations (i.e. IO is the base monad for the stack).

    Example
    import Control.Monad.Trans.State -- from the "transformers" library
    
    printState :: Show s => StateT s IO ()
    printState = do
      state <- get
      liftIO $ print state

    Had we omitted liftIO, we would have ended up with this error:

    • Couldn't match type ‘IO’ with ‘StateT s IO’
     Expected type: StateT s IO ()
       Actual type: IO ()

    The important part here is the mismatch between StateT s IO () and IO ().

    Luckily, we know of a function that takes an IO a and returns an (m a): liftIO, enabling us to run the program and see the expected results:

    > evalStateT printState "hello"
    "hello"
    
    > evalStateT printState 3
    3
    
Instances18MonadIO, …
classclass Applicative f => Alternative (f :: Type -> Type) where
#

A monoid on applicative functors.

If defined, some and many should be the least solutions of the equations:

Examples
Example1 expression
Nothing <|> Just 42Just 42
Example1 expression
[1, 2] <|> [3, 4][1,2,3,4]
Example1 expression
empty <|> print (2^15)32768

Methods

  • empty :: f a

    The identity of <|>

    empty <|> a     == a
    a     <|> empty == a
  • (<|>) :: f a -> f a -> f ainfixl 3

    An associative binary operation

  • some :: f a -> f [a]

    One or more.

    Examples
    Example1 expression
    some (putStr "la")lalalalalalalalala... * goes on forever *
    Example1 expression
    some Nothingnothing
    Example1 expression
    take 5 <$> some (Just 1)* hangs forever *

    Note that this function can be used with Parsers based on Applicatives. In that case some parser will attempt to parse parser one or more times until it fails.

  • many :: f a -> f [a]

    Zero or more.

    Examples
    Example1 expression
    many (putStr "la")lalalalalalalalala... * goes on forever *
    Example1 expression
    many NothingJust []
    Example1 expression
    take 5 <$> many (Just 1)* hangs forever *

    Note that this function can be used with Parsers based on Applicatives. In that case many parser will attempt to parse parser zero or more times until it fails.

Instances43Alternative, …
classclass MFunctor (t :: (Type -> Type) -> k -> Type) where
#

A functor in the category of monads, using hoist as the analog of fmap:

hoist (f . g) = hoist f . hoist g

hoist id = id

Methods

  • hoist :: Monad m => (forall a. m a -> n a) -> t m b -> t n b

    Lift a monad morphism from m to n into a monad morphism from (t m) to (t n)

    The first argument to hoist must be a monad morphism, even though the type system does not enforce this

Instances18MFunctor, …