How to use Do notation with both Maybe and IO - haskell

I am trying to get a good grip on the do notation in Haskell.
I could use it with Maybe and then print the result. Like this:
maybeAdd :: Maybe Integer
maybeAdd = do one <- maybe1
two <- maybe2
three <- maybe3
return (one + two + three)
main :: IO ()
main = putStr (show $ fromMaybe 0 maybeAdd)
But instead of having a separate function I am trying to use the do notation with the Maybe inside the main function. But I am not having any luck. The various attempts I tried include:
main :: IO ()
main = do one <- maybe1
two <- maybe2
three <- maybe3
putStr (show $ fromMaybe 0 $ return (one + two + three))
main :: IO ()
main = do one <- maybe1
two <- maybe2
three <- maybe3
putStr (show $ fromMaybe 0 $ Just (one + two + three))
main :: IO ()
main = do one <- maybe1
two <- maybe2
three <- maybe3
putStr (show $ (one + two + three))
All of these leads to various types of compilation errors, which unfortunately I failed to decipher to get the correct way to do it.
How do I achieve the above? And perhaps maybe an explanation of why the approaches I tried were wrong also?

Each do block must work within a single monad. If you want to use multiple monads, you could use multiple do blocks. Trying to adapt your code:
main :: IO ()
main = do -- IO block
let x = do -- Maybe block
one <- maybe1
two <- maybe2
three <- maybe3
return (one + two + three)
putStr (show $ fromMaybe 0 x)
You could even use
main = do -- IO block
putStr $ show $ fromMaybe 0 $ do -- Maybe block
one <- maybe1
two <- maybe2
three <- maybe3
return (one + two + three)
-- other IO actions here
but it could be less readable in certain cases.

The MaybeT monad transformer would come handy in this particular case. MaybeT monad transformer is just a type defined something like;
newtype MaybeT m a = MaybeT {runMaybeT :: m (Maybe a)}
Actually transformers like MaybeT, StateT etc, are readily available in Control.Monad.Trans.Maybe, Control.Monad.Trans.State... For illustration purposes it' Monad instance could be something like shown below;
instance Monad m => Monad (MaybeT m) where
return = MaybeT . return . Just
x >>= f = MaybeT $ runMaybeT x >>= g
where
g Nothing = return Nothing
g (Just x) = runMaybeT $ f x
so as you will notice the monadic f function takes a value that resides in the Maybe monad which itself is in another monad (IO in our case). The f function does it's thing and wraps the result back into MaybeT m a.
Also there is a MonadTrans class where you can have some common functionalities those are used by the transformer types. One such is lift which is used to lift the value into a transformer according to that particular instance's definition. For MaybeT it should look like
instance MonadTrans MaybeT where
lift = MaybeT . (liftM Just)
Lets perform your task with monad transformers.
addInts :: MaybeT IO ()
addInts = do
lift $ putStrLn "Enter two integers.."
i <- lift getLine
guard $ test i
j <- lift getLine
guard $ test j
lift . print $ (read i :: Int) + (read j :: Int)
where
test = and . (map isDigit)
So when called like
λ> runMaybeT addInts
Enter two integers..
1453
1571
3024
Just ()
The catch is, since a monad transformer is also a member of Monad typeclass, one can nest them indefinitelly and still do things under a singe do notation.
Edit: answer gets downvoted but it is unclear to me why. If there is something wrong with the approach please care to elaborate me so that it helps people including me to learn something better.
Taking the opportunity of being on the edit session, i would like to add a better code since i think Char based testing might not be the best idea as it will not take negative Ints into account. So let's try using readMaybe from the Text.Read package while we are doing things with the Maybe type.
import Control.Monad.Trans.Maybe
import Control.Monad.Trans.Class (lift)
import Text.Read (readMaybe)
addInts :: MaybeT IO ()
addInts = do
lift $ putStrLn "Enter two integers.."
i <- lift getLine
MaybeT $ return (readMaybe i :: Maybe Int)
j <- lift getLine
MaybeT $ return (readMaybe j :: Maybe Int)
lift . print $ (read i :: Int) + (read j :: Int)
I guess now it works better...
λ> runMaybeT addInts
Enter two integers..
-400
500
100
Just ()
λ> runMaybeT addInts
Enter two integers..
Not an Integer
Nothing

Related

MonadRandom, State and monad transformers

I'm writing some code (around card-playing strategies) that uses State and recursion together. Perhaps this part doesn't need to actually (it already feels clumsy to me, even as a relative beginner), but there are other parts that probably do so my general question stands...
My initial naive implementation is entirely deterministic (the choice of bid is simply the first option provided by the function validBids):
bidOnRound :: (DealerRules d) => d -> NumCards -> State ([Player], PlayerBids) ()
bidOnRound dealerRules cardsThisRound = do
(players, bidsSoFar) <- get
unless (List.null players) $ do
let options = validBids dealerRules cardsThisRound bidsSoFar
let newBid = List.head $ Set.toList options
let p : ps = players
put (ps, bidsSoFar ++ [(p, newBid)])
bidOnRound dealerRules cardsThisRound
And I call it from:
playGame :: (DealerRules d, ScorerRules s) => d -> s -> StateT Results IO ()
...
let (_, bidResults) = execState (bidOnRound dealerRules cardsThisRound) (NonEmpty.toList players, [])
Now I'm aware that I need to bring randomness into this and several other parts of the code. Not wanting to litter IO everywhere, nor pass round random seeds manually all the time, I feel I should be using MonadRandom or something. A library I'm using uses it to good effect. Is this a wise choice?
Here's what I tried:
bidOnRound :: (DealerRules d, RandomGen g) => d -> NumCards -> RandT g (State ([Player], PlayerBids)) ()
bidOnRound dealerRules cardsThisRound = do
(players, bidsSoFar) <- get
unless (List.null players) $ do
let options = Set.toList $ validBids dealerRules cardsThisRound bidsSoFar
rnd <- getRandomR (0 :: Int, len options - 1)
let newBid = options List.!! rnd
let p : ps = players
put (ps, bidsSoFar ++ [(p, newBid)])
bidOnRound dealerRules cardsThisRound
but I'm uncomfortable already, plus can't work out how to call this, e.g. using evalRand in combination with execState etc. The more I read on MonadRandom, RandGen and mtl vs others, the less sure I am of what I'm doing...
How should I neatly combine Randomness and State and how do I call these properly?
Thanks!
EDIT: for reference, full current source on Github.
Well how about an example to help you out. Since you didn't post a full working code snippet I'll just replace a lot of your operations and show how the monads can be evaluated:
import Control.Monad.Trans.State
import Control.Monad.Random
import System.Random.TF
bidOnRound :: (RandomGen g) => Int -> RandT g (State ([Int], Int)) ()
bidOnRound i =
do rand <- getRandomR (10,20)
s <- lift $ get
lift $ put ([], i + rand + snd s)
main :: IO ()
main =
do g <- newTFGen
print $ flip execState ([],1000) $ evalRandT (bidOnRound 100) g
The thing to note here is you "unwrap" the outer monad first. So if you have RandT (StateT Reader ...) ... then you run RandT (ex via evalRandT or similar) then the state then the reader. Secondly, you must lift from the outer monad to use operations on the inner monad. This might seem clumsy and that is because it is horribly clumsy.
The best developers I know - those whose code I enjoy looking at and working with - extract monad operations and provide an API with all the primitives complete so I don't need to think about the structure of the monad while I'm thinking about the structure of the logic I'm writing.
In this case (it will be slightly contrived since I wrote the above without any application domain, rhyme or reason) you could write:
type MyMonad a = RandT TFGen (State ([Int],Int)) a
runMyMonad :: MyMonad () -> IO Int
runMyMonad f =
do g <- newTFGen
pure $ snd $ flip execState ([],1000) $ evalRandT f g
With the Monad defined as a simple alias and execution operation the basic functions are easier:
flipCoin :: MyMonad Int
flipCoin = getRandomR (10,20)
getBaseValue :: MyMonad Int
getBaseValue = snd <$> lift get
setBaseValue :: Int -> MyMonad ()
setBaseValue v = lift $ state $ \s -> ((),(fst s, v))
With that leg-work out of the way, which is usually a minor part of making a real application, the domain specific logic is easier to write and certainly easier to read:
bidOnRound2 :: Int -> MyMonad ()
bidOnRound2 i =
do rand <- flipCoin
old <- getBaseValue
setBaseValue (i + rand + old)
main2 :: IO ()
main2 = print =<< runMyMonad (bidOnRound2 100)

Memoizing and repeating IO monads

EDITED 2015-11-29: see bottom
I'm trying to write an application that has a do-last-action-again button. The command in question can ask for input, and my thought for how to accomplish this was to just rerun the resulting monad with memoized IO.
There are lots of posts on SO with similar questions, but none of the solutions seem to work here.
I lifted the memoIO code from this SO answer, and changed the implementation to run over MonadIO.
-- Memoize an IO function
memoIO :: MonadIO m => m a -> m (m a)
memoIO action = do
ref <- liftIO $ newMVar Nothing
return $ do
x <- maybe action return =<< liftIO (takeMVar ref)
liftIO . putMVar ref $ Just x
return x
I've got a small repro of my app's approach, the only real difference being my app has a big transformer stack instead of just running in IO:
-- Global variable to contain the action we want to repeat
actionToRepeat :: IORef (IO String)
actionToRepeat = unsafePerformIO . newIORef $ return ""
-- Run an action and store it as the action to repeat
repeatable :: IO String -> IO String
repeatable action = do
writeIORef actionToRepeat action
action
-- Run the last action stored by repeatable
doRepeat :: IO String
doRepeat = do
x <- readIORef actionToRepeat
x
The idea being I can store an action with memoized IO in an IORef (via repeatable) when I record what was last done, and then do it again it out with doRepeat.
I test this via:
-- IO function to memoize
getName :: IO String
getName = do
putStr "name> "
getLine
main :: IO ()
main = do
repeatable $ do
memoized <- memoIO getName
name <- memoized
putStr "hello "
putStrLn name
return name
doRepeat
return ()
with expected output:
name> isovector
hello isovector
hello isovector
but actual output:
name> isovector
hello isovector
name> wasnt memoized
hello wasnt memoized
I'm not entirely sure what the issue is, or even how to go about debugging this. Gun to my head, I'd assume lazy evaluation is biting me somewhere, but I can't figure out where.
Thanks in advance!
EDIT 2015-11-29: My intended use case for this is to implement the repeat last change operator in a vim-clone. Each action can perform an arbitrary number of arbitrary IO calls, and I would like it to be able to specify which ones should be memoized (reading a file, probably not. asking the user for input, yes).
the problem is in main you are creating a new memo each time you call the action
you need to move memoized <- memoIO getName up above the action
main :: IO ()
main = do
memoized <- memoIO getName --moved above repeatable $ do
repeatable $ do
--it was here
name <- memoized
putStr "hello "
putStrLn name
return name
doRepeat
return ()
edit: is this acceptable
import Data.IORef
import System.IO.Unsafe
{-# NOINLINE actionToRepeat #-}
actionToRepeat :: IORef (IO String)
actionToRepeat = unsafePerformIO . newIORef $ return ""
type Repeatable a = IO (IO a)
-- Run an action and store the Repeatable part of the action
repeatable :: Repeatable String -> IO String
repeatable action = do
repeatAction <- action
writeIORef actionToRepeat repeatAction
repeatAction
-- Run the last action stored by repeatable
doRepeat :: IO String
doRepeat = do
x <- readIORef actionToRepeat
x
-- everything before (return $ do) is run just once
hello :: Repeatable String
hello = do
putStr "name> "
name <- getLine
return $ do
putStr "hello "
putStrLn name
return name
main :: IO ()
main = do
repeatable hello
doRepeat
return ()
I came up with a solution. It requires wrapping the original monad in a new transformer which records the results of IO and injects them the next time the underlying monad is run.
Posting it here so my answer is complete.
{-# LANGUAGE FlexibleContexts #-}
{-# LANGUAGE GeneralizedNewtypeDeriving #-}
{-# LANGUAGE LambdaCase #-}
import Control.Applicative (Applicative(..))
import Data.Dynamic
import Data.Maybe (fromJust)
import Control.Monad.RWS
-- | A monad transformer adding the ability to record the results
-- of IO actions and later replay them.
newtype ReplayT m a =
ReplayT { runReplayT :: RWST () [Dynamic] [Dynamic] m a }
deriving ( Functor
, Applicative
, Monad
, MonadIO
, MonadState [Dynamic]
, MonadWriter [Dynamic]
, MonadTrans
)
-- | Removes the first element from a list State and returns it.
dequeue :: MonadState [r] m
=> m (Maybe r)
dequeue = do
get >>= \case
[] -> return Nothing
(x:xs) -> do
put xs
return $ Just x
-- | Marks an IO action to be memoized after its first invocation.
sample :: ( MonadIO m
, Typeable r)
=> IO r
-> ReplayT m r
sample action = do
a <- dequeue >>= \case
Just x -> return . fromJust $ fromDynamic x
Nothing -> liftIO action
tell [toDyn a]
return a
-- | Runs an action and records all of its sampled IO. Returns a
-- action which when invoked will use the recorded IO.
record :: Monad m
=> ReplayT m a
-> m (m a)
record action = do
(a, w) <- evalRWST (runReplayT action) () []
return $ do
evalRWST (runReplayT action) () w
return a

Simplest non-trivial monad transformer example for "dummies", IO+Maybe

Could someone give a super simple (few lines) monad transformer example, which is non-trivial (i.e. not using the Identity monad - that I understand).
For example, how would someone create a monad that does IO and can handle failure (Maybe)?
What would be the simplest example that would demonstrate this?
I have skimmed through a few monad transformer tutorials and they all seem to use State Monad or Parsers or something complicated (for a newbee). I would like to see something simpler than that. I think IO+Maybe would be simple, but I don't really know how to do that myself.
How could I use an IO+Maybe monad stack?
What would be on top? What would be on bottom? Why?
In what kind of use case would one want to use the IO+Maybe monad or the Maybe+IO monad? Would that make sense to create such a composite monad at all? If yes, when, and why?
This is available here as a .lhs file.
The MaybeT transformer will allow us to break out of a monad computation much like throwing an exception.
I'll first quickly go over some preliminaries. Skip down to Adding Maybe powers to IO for a worked example.
First some imports:
import Control.Monad
import Control.Monad.Trans
import Control.Monad.Trans.Maybe
Rules of thumb:
In a monad stack IO is always on the bottom.
Other IO-like monads will also, as a rule, always appear on the bottom, e.g. the state transformer monad ST.
MaybeT m is a new monad type which adds the power of the Maybe monad to the monad m - e.g. MaybeT IO.
We'll get into what that power is later. For now, get used to thinking of MaybeT IO as the maybe+IO monad stack.
Just like IO Int is a monad expression returning an Int, MaybeT IO Int is a MaybeT IO expression returning an Int.
Getting used to reading compound type signatures is half the battle to understanding monad transformers.
Every expression in a do block must be from the same monad.
I.e. this works because each statement is in the IO-monad:
greet :: IO () -- type:
greet = do putStr "What is your name? " -- IO ()
n <- getLine -- IO String
putStrLn $ "Hello, " ++ n -- IO ()
This will not work because putStr is not in the MaybeT IO monad:
mgreet :: MaybeT IO ()
mgreet = do putStr "What is your name? " -- IO monad - need MaybeT IO here
...
Fortunately there is a way to fix this.
To transform an IO expression into a MaybeT IO expression use liftIO.
liftIO is polymorphic, but in our case it has the type:
liftIO :: IO a -> MaybeT IO a
mgreet :: MaybeT IO () -- types:
mgreet = do liftIO $ putStr "What is your name? " -- MaybeT IO ()
n <- liftIO getLine -- MaybeT IO String
liftIO $ putStrLn $ "Hello, " ++ n -- MaybeT IO ()
Now all of the statement in mgreet are from the MaybeT IO monad.
Every monad transformer has a "run" function.
The run function "runs" the top-most layer of a monad stack returning
a value from the inside layer.
For MaybeT IO, the run function is:
runMaybeT :: MaybeT IO a -> IO (Maybe a)
Example:
ghci> :t runMaybeT mgreet
mgreet :: IO (Maybe ())
ghci> runMaybeT mgreet
What is your name? user5402
Hello, user5402
Just ()
Also try running:
runMaybeT (forever mgreet)
You'll need to use Ctrl-C to break out of the loop.
So far mgreet doesn't do anything more than what we could do in IO.
Now we'll work on an example which demonstrates the power of mixing
the Maybe monad with IO.
Adding Maybe powers to IO
We'll start with a program which asks some questions:
askfor :: String -> IO String
askfor prompt = do
putStr $ "What is your " ++ prompt ++ "? "
getLine
survey :: IO (String,String)
survey = do n <- askfor "name"
c <- askfor "favorite color"
return (n,c)
Now suppose we want to give the user the ability to end the survey
early by typing END in response to a question. We might handle it
this way:
askfor1 :: String -> IO (Maybe String)
askfor1 prompt = do
putStr $ "What is your " ++ prompt ++ " (type END to quit)? "
r <- getLine
if r == "END"
then return Nothing
else return (Just r)
survey1 :: IO (Maybe (String, String))
survey1 = do
ma <- askfor1 "name"
case ma of
Nothing -> return Nothing
Just n -> do mc <- askfor1 "favorite color"
case mc of
Nothing -> return Nothing
Just c -> return (Just (n,c))
The problem is that survey1 has the familiar staircasing issue which
doesn't scale if we add more questions.
We can use the MaybeT monad transformer to help us here.
askfor2 :: String -> MaybeT IO String
askfor2 prompt = do
liftIO $ putStr $ "What is your " ++ prompt ++ " (type END to quit)? "
r <- liftIO getLine
if r == "END"
then MaybeT (return Nothing) -- has type: MaybeT IO String
else MaybeT (return (Just r)) -- has type: MaybeT IO String
Note how all of the statemens in askfor2 have the same monad type.
We've used a new function:
MaybeT :: IO (Maybe a) -> MaybeT IO a
Here is how the types work out:
Nothing :: Maybe String
return Nothing :: IO (Maybe String)
MaybeT (return Nothing) :: MaybeT IO String
Just "foo" :: Maybe String
return (Just "foo") :: IO (Maybe String)
MaybeT (return (Just "foo")) :: MaybeT IO String
Here return is from the IO-monad.
Now we can write our survey function like this:
survey2 :: IO (Maybe (String,String))
survey2 =
runMaybeT $ do a <- askfor2 "name"
b <- askfor2 "favorite color"
return (a,b)
Try running survey2 and ending the questions early by typing END as a response to either question.
Short-cuts
I know I'll get comments from people if I don't mention the following short-cuts.
The expression:
MaybeT (return (Just r)) -- return is from the IO monad
may also be written simply as:
return r -- return is from the MaybeT IO monad
Also, another way of writing MaybeT (return Nothing) is:
mzero
Furthermore, two consecutive liftIO statements may always combined into a single liftIO, e.g.:
do liftIO $ statement1
liftIO $ statement2
is the same as:
liftIO $ do statement1
statement2
With these changes our askfor2 function may be written:
askfor2 prompt = do
r <- liftIO $ do
putStr $ "What is your " ++ prompt ++ " (type END to quit)?"
getLine
if r == "END"
then mzero -- break out of the monad
else return r -- continue, returning r
In a sense, mzero becomes a way of breaking out of the monad - like throwing an exception.
Another example
Consider this simple password asking loop:
loop1 = do putStr "Password:"
p <- getLine
if p == "SECRET"
then return ()
else loop1
This is a (tail) recursive function and works just fine.
In a conventional language we might write this as a infinite while loop with a break statement:
def loop():
while True:
p = raw_prompt("Password: ")
if p == "SECRET":
break
With MaybeT we can write the loop in the same manner as the Python code:
loop2 :: IO (Maybe ())
loop2 = runMaybeT $
forever $
do liftIO $ putStr "Password: "
p <- liftIO $ getLine
if p == "SECRET"
then mzero -- break out of the loop
else return ()
The last return () continues execution, and since we are in a forever loop, control passes back to the top of the do block. Note that the only value that loop2 can return is Nothing which corresponds to breaking out of the loop.
Depending on the situation you might find it easier to write loop2 rather than the recursive loop1.
Suppose you have to work with IO values that "may fail" in some sense, like foo :: IO (Maybe a), func1 :: a -> IO (Maybe b) and func2 :: b -> IO (Maybe c).
Manually checking for the presence of errors in a chain of binds quickly produces the dreaded "staircase of doom":
do
ma <- foo
case ma of
Nothing -> return Nothing
Just a -> do
mb <- func1 a
case mb of
Nothing -> return Nothing
Just b -> func2 b
How to "automate" this in some way? Perhaps we could devise a newtype around IO (Maybe a) with a bind function that automatically checks if the first argument is a Nothing inside IO, saving us the trouble of checking it ourselves. Something like
newtype MaybeOverIO a = MaybeOverIO { runMaybeOverIO :: IO (Maybe a) }
With the bind function:
betterBind :: MaybeOverIO a -> (a -> MaybeOverIO b) -> MaybeOverIO b
betterBind mia mf = MaybeOverIO $ do
ma <- runMaybeOverIO mia
case ma of
Nothing -> return Nothing
Just a -> runMaybeOverIO (mf a)
This works! And, looking at it more closely, we realize that we aren't using any particular functions exclusive to the IO monad. Generalizing the newtype a little, we could make this work for any underlying monad!
newtype MaybeOverM m a = MaybeOverM { runMaybeOverM :: m (Maybe a) }
And this is, in essence, how the MaybeT transformer works. I have left out a few details, like how to implement return for the transformer, and how to "lift" IO values into MaybeOverM IO values.
Notice that MaybeOverIO has kind * -> * while MaybeOverM has kind (* -> *) -> * -> * (because its first "type argument" is a monad type constructor, that itself requires a "type argument").
Sure, the MaybeT monad transformer is:
newtype MaybeT m a = MaybeT {unMaybeT :: m (Maybe a)}
We can implement its monad instance as so:
instance (Monad m) => Monad (MaybeT m) where
return a = MaybeT (return (Just a))
(MaybeT mmv) >>= f = MaybeT $ do
mv <- mmv
case mv of
Nothing -> return Nothing
Just a -> unMaybeT (f a)
This will allow us to perform IO with the option of failing gracefully in certain circumstances.
For instance, imagine we had a function like this:
getDatabaseResult :: String -> IO (Maybe String)
We can manipulate the monads independently with the result of that function, but if we compose it as so:
MaybeT . getDatabaseResult :: String -> MaybeT IO String
We can forget about that extra monadic layer, and just treat it as a normal monad.

Abstraction for monadic recursion with "unless"

I'm trying to work out if it's possible to write an abstraction for the following situation. Suppose I have a type a with function a -> m Bool e.g. MVar Bool and readMVar. To abstract this concept out I create a newtype wrapper for the type and its function:
newtype MPredicate m a = MPredicate (a,a -> m Bool)
I can define a fairly simple operation like so:
doUnless :: (Monad m) => Predicate m a -> m () -> m ()
doUnless (MPredicate (a,mg)) g = mg a >>= \b -> unless b g
main = do
b <- newMVar False
let mpred = MPredicate (b,readMVar)
doUnless mpred (print "foo")
In this case doUnless would print "foo". Aside: I'm not sure whether a type class might be more appropriate to use instead of a newtype.
Now take the code below, which outputs an incrementing number then waits a second and repeats. It does this until it receives a "turn off" instruction via the MVar.
foobar :: MVar Bool -> IO ()
foobar mvb = foobar' 0
where
foobar' :: Int -> IO ()
foobar' x = readMVar mvb >>= \b -> unless b $ do
let x' = x + 1
print x'
threadDelay 1000000
foobar' x'
goTillEnter :: MVar Bool -> IO ()
goTillEnter mv = do
_ <- getLine
_ <- takeMVar mv
putMVar mv True
main = do
mvb <- newMVar False
forkIO $ foobar mvb
goTillEnter mvb
Is it possible to refactor foobar so that it uses MPredicate and doUnless?
Ignoring the actual implementation of foobar' I can think of a simplistic way of doing something similar:
cycleUnless :: x -> (x -> x) -> MPredicate m a -> m ()
cycleUnless x g mp = let g' x' = doUnless mp (g' $ g x')
in g' $ g x
Aside: I feel like fix could be used to make the above neater, though I still have trouble working out how to use it
But cycleUnless won't work on foobar because the type of foobar' is actually Int -> IO () (from the use of print x').
I'd also like to take this abstraction further, so that it can work threading around a Monad. With stateful Monads it becomes even harder. E.g.
-- EDIT: Updated the below to show an example of how the code is used
{- ^^ some parent function which has the MVar ^^ -}
cycleST :: (forall s. ST s (STArray s Int Int)) -> IO ()
cycleST sta = readMVar mvb >>= \b -> unless b $ do
n <- readMVar someMVar
i <- readMVar someOtherMVar
let sta' = do
arr <- sta
x <- readArray arr n
writeArray arr n (x + i)
return arr
y = runSTArray sta'
print y
cycleST sta'
I have something similar to the above working with RankNTypes. Now there's the additional problem of trying to thread through the existential s, which is not likely to type check if threaded around through an abstraction the likes of cycleUnless.
Additionally, this is simplified to make the question easier to answer. I also use a set of semaphores built from MVar [MVar ()] similar to the skip channel example in the MVar module. If I can solve the above problem I plan to generalize the semaphores as well.
Ultimately this isn't some blocking problem. I have 3 components of the application operating in a cycle off the same MVar Bool but doing fairly different asynchronous tasks. In each one I have written a custom function that performs the appropriate cycle.
I'm trying to learn the "don't write large programs" approach. What I'd like to do is refactor chunks of code into their own mini libraries so that I'm not building a large program but assembling lots of small ones. But so far this particular abstraction is escaping me.
Any thoughts on how I might go about this are very much appreciated!
You want to cleanly combine a stateful action having side effects, a delay, and an independent stopping condition.
The iterative monad transformer from the free package can be useful in these cases.
This monad transformer lets you describe a (possibly nonending) computation as a series of discrete steps. And what's better, it let's you interleave "stepped" computations using mplus. The combined computation stops when any of the individual computations stops.
Some preliminary imports:
import Data.Bool
import Control.Monad
import Control.Monad.Trans
import Control.Monad.Trans.Iter (delay,untilJust,IterT,retract,cutoff)
import Control.Concurrent
Your foobar function could be understood as a "sum" of three things:
A computation that does nothing but reading from the MVar at each step, and finishes when the Mvar is True.
untilTrue :: (MonadIO m) => MVar Bool -> IterT m ()
untilTrue = untilJust . liftM guard . liftIO . readMVar
An infinite computation that takes a delay at each step.
delays :: (MonadIO m) => Int -> IterT m a
delays = forever . delay . liftIO . threadDelay
An infinite computation that prints an increasing series of numbers.
foobar' :: (MonadIO m) => Int -> IterT m a
foobar' x = do
let x' = x + 1
liftIO (print x')
delay (foobar' x')
With this in place, we can write foobar as:
foobar :: (MonadIO m) => MVar Bool -> m ()
foobar v = retract (delays 1000000 `mplus` untilTrue v `mplus` foobar' 0)
The neat thing about this is that you can change or remove the "stopping condition" and the delay very easily.
Some clarifications:
The delay function is not a delay in IO, it just tells the iterative monad transformer to "put the argument in a separate step".
retract brings you back from the iterative monad transformer to the base monad. It's like saying "I don't care about the steps, just run the computation". You can combine retract with cutoff if you want to limit the maximum number of iterations.
untilJustconverts a value m (Maybe a) of the base monad into a IterT m a by retrying in each step until a Just is returned. Of course, this risks non-termination!
MPredicate is rather superfluous here; m Bool can be used instead. The monad-loops package contains plenty of control structures with m Bool conditions. whileM_ in particular is applicable here, although we need to include a State monad for the Int that we're threading around:
import Control.Monad.State
import Control.Monad.Loops
import Control.Applicative
foobar :: MVar Bool -> IO ()
foobar mvb = (`evalStateT` (0 :: Int)) $
whileM_ (not <$> lift (readMVar mvb)) $ do
modify (+1)
lift . print =<< get
lift $ threadDelay 1000000
Alternatively, we can use a monadic version of unless. For some reason monad-loops doesn't export such a function, so let's write it:
unlessM :: Monad m => m Bool -> m () -> m ()
unlessM mb action = do
b <- mb
unless b action
It's somewhat more convenient and more modular in a monadic setting, since we can always go from a pure Bool to m Bool, but not vice versa.
foobar :: MVar Bool -> IO ()
foobar mvb = go 0
where
go :: Int -> IO ()
go x = unlessM (readMVar mvb) $ do
let x' = x + 1
print x'
threadDelay 1000000
go x'
You mentioned fix; sometimes people indeed use it for ad-hoc monadic loops, for example:
printUntil0 :: IO ()
printUntil0 =
putStrLn "hello"
fix $ \loop -> do
n <- fmap read getLine :: IO Int
print n
when (n /= 0) loop
putStrLn "bye"
With some juggling it's possible to use fix with multi-argument functions. In the case of foobar:
foobar :: MVar Bool -> IO ()
foobar mvb = ($(0 :: Int)) $ fix $ \loop x -> do
unlessM (readMVar mvb) $ do
let x' = x + 1
print x'
threadDelay 1000000
loop x'
I'm not sure what's your MPredicate is doing.
First, instead of newtyping a tuple, it's probably better to use a normal algebric data type
data MPredicate a m = MPredicate a (a -> m Bool)
Second, the way you use it, MPredicate is equivalent to m Bool.
Haskell is lazzy, therefore there is no need to pass, a function and it's argument (even though
it's usefull with strict languages). Just pass the result, and the function will be called when needed.
I mean, instead of passing (x, f) around, just pass f x
Of course, if you are not trying to delay the evaluation and really need at some point, the argument or the function as well as the result, a tuple is fine.
Anyway, in the case your MPredicate is only there to delay the function evaluation, MPredicat reduces to m Bool and doUnless to unless.
Your first example is strictly equivalent :
main = do
b <- newMVar False
unless (readMVar b) (print "foo")
Now, if you want to loop a monad until a condition is reach (or equivalent) you should have a look at the monad-loop package. What you are looking it at is probably untilM_ or equivalent.

Error check within do block in Haskell

i have the following set of actions:
action1 :: IO Bool
action2 :: IO Bool
action3 :: IO Bool
some actions are just composition of another actions
complexAction = do
action1
action2
action3
What i need is the construction that checks result of each action and returns False in a case of false. I can do it manually but i know for sure that haskell does have tools to get rid of that kind of boilerplate.
The simplest way is
complexAction = fmap and (sequence [action1, action2, action3])
But you could also write your own combinator to stop after the first action:
(>>/) :: Monad m => m Bool -> m Bool -> m Bool
a >>/ b = do
yes <- a
if yes then b else return False
You'd want to declare the fixity to make it associative
infixl 1 >>/
Then you can do
complexAction = action1 >>/ action2 >>/ action3
I'd suggest you to use MaybeT monad transformer instead. Using it has many advantages over just returning IO Bool:
Your actions can have different types and return values (not just true/false). If you don't need any results, just use MaybeT IO ().
Later ones can depend on results of preceding ones.
Since MaybeT produces monads that are instances of MonadPlus, you can use all monad plus operations. Namely mzero for a failed action and x mplus y, which will run y iff x fails.
A slight disadvantage is that you have to lift all IO actions to MaybeT IO. This can be solved by writing your actions as MonadIO m => ... -> m a instead of ... -> IO a.
For example:
import Control.Monad
import Control.Monad.IO.Class
import Control.Monad.Trans
import Control.Monad.Trans.Maybe
-- Lift print and putStrLn
print' :: (MonadIO m, Show a) => a -> m ()
print' = liftIO . print
putStrLn' :: (MonadIO m) => String -> m ()
putStrLn' = liftIO . putStrLn
-- Add something to an argument
plus1, plus3 :: Int -> MaybeT IO Int
plus1 n = print' "+1" >> return (n + 1)
plus3 n = print' "+3" >> return (n + 3)
-- Ignore an argument and fail
justFail :: Int -> MaybeT IO a
justFail _ = mzero
-- This action just succeeds with () or fails.
complexAction :: MaybeT IO ()
complexAction = do
i <- plus1 0
justFail i -- or comment this line out <----------------<
j <- plus3 i
print' j
-- You could use this to convert your actions to MaybeT IO:
boolIOToMaybeT :: IO Bool -> MaybeT IO ()
boolIOToMaybeT x = do
r <- lift x
if r then return () else mzero
-- Or you could have even more general version that works with other
-- transformers as well:
boolIOToMaybeT' :: (MonadIO m, MonadPlus m) => IO Bool -> m ()
boolIOToMaybeT' x = do
r <- liftIO x
if r then return () else mzero
main :: IO ()
main = runMaybeT complexAction >>= print'
As Petr says, for anything but a narrow and contained case, you're almost certainly better off wiring your code for proper error handling from the outset. I know I've often regretted not doing this, condemning myself to some very tedious refactoring.
If I may, I'd like to recommend Gabriel Gonzalez's errors package, which imposes a little more coherence on Haskell's various error-handling mechanisms than has been traditional. It allows you to plumb Eithers through your code, and Either is a good type for capturing errors. (By contrast, Maybe will lose information on the error side.) Once you've installed the package, you can write things like this:
module Errors where
import Control.Error
import Data.Traversable (traverse)
data OK = OK Int deriving (Show)
action1, action2, action3 :: IO (Either String OK)
action1 = putStrLn "Running action 1" >> return (Right $ OK 1)
action2 = putStrLn "Running action 2" >> return (Right $ OK 2)
action3 = putStrLn "Running action 3" >> return (Left "Oops on 3")
runStoppingAtFirstError :: [IO (Either String OK)] -> IO (Either String [OK])
runStoppingAtFirstError = runEitherT . traverse EitherT
...with output like
*Errors> runStoppingAtFirstError [action1, action2]
Running action 1
Running action 2
Right [OK 1,OK 2]
*Errors> runStoppingAtFirstError [action1, action3, action2]
Running action 1
Running action 3
Left "Oops on 3"
(But note that the computation here stops at the first error and doesn't soldier on until the bitter end -- which might not be what you had wanted. The errors package is certainly wide-ranging enough that many other variations are possible.)

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