I am trying to come up with a modular program design and I, once again, kindly request your help.
As a follow-up to these following posts Monad Transformers vs passing Parameters and Large Scale Design in Haskell, I am trying to build two independent modules that use Monad Transformers but expose Monad-agnostic functions, then combine a Monad-agnostic function from each of these modules into a new Monad-agnostic function.
I have been unable to run the combining function e.g. how do I call mainProgram using runReaderT in the example below ?.
The subsidiary question is: is there a better way to achieve the same modular design goal ?
The example has two mock modules (but compiles), one that performs logging and one that reads an user input and manipulates it. The combining function reads the user input, logs it and prints it.
{-# LANGUAGE FlexibleContexts #-}
module Stackoverflow2 where
import Control.Monad.Reader
----
---- From Log Module - Writes the passed message in the log
----
data LogConfig = LC { logFile :: FilePath }
doLog :: (MonadIO m, MonadReader LogConfig m) => String -> m ()
doLog _ = undefined
----
---- From UserProcessing Module - Reads the user Input and changes it to the configured case
----
data MessageCase = LowerCase | UpperCase deriving (Show, Read)
getUserInput :: (MonadReader MessageCase m, MonadIO m) => m String
getUserInput = undefined
----
---- Main program that combines the two
----
mainProgram :: (MonadReader MessageCase m, MonadReader LogConfig m, MonadIO m) => m ()
mainProgram = do input <- getUserInput
doLog input
liftIO $ putStrLn $ "Entry logged: " ++ input
There is a way to write a fully modular version of the program. The way you need to approach the problem is to bundle up your reader configuration into one data structure, and then define type classes that describe the partial interface that specific functions need towards that data structure. For example:
class LogConfiguration c where
logFile :: c -> FilePath
doLog :: (MonadIO m, LogConfiguration c, MonadReader c m) => String -> m ()
doLog = do
file <- asks logFile
-- ...
class MessageCaseConfiguration c where
isLowerCase :: c -> Bool
getUserInput :: (MonadIO m, MessageCaseConfiguration c, MonadReader c m) => m String
getUserInput = do
lc <- asks isLowerCase
-- ...
data LogConfig = LC { logConfigFile :: FilePath }
data MessageCase = LowerCase | UpperCase
data Configuration = Configuration { logging :: LogConfig, casing :: MessageCase }
instance LogConfiguration Configuration where
logFile = logConfigFile . logging
instance MessageCaseConfiguration Configuration where
isLowerCase c = case casing c of
LowerCase -> True
UpperCase -> False
mainProgram :: (MonadIO m, MessageCaseConfiguration c, LogConfiguration c, MonadReader c m) => m ()
mainProgram = do
input <- getUserInput
doLog input
liftIO . putStrLn $ "Entry logged: " ++ input
Now you can call mainProgram with a Configuration in a ReaderT monad and it'll work as you would expect.
Your mainProgram signature is problematic, because the MonadReader typeclass contains the functional dependency MonadReader r m | m -> r. This essentially means that a single concrete type cannot have a MonadReader instance for multiple different types. So when you say that the type m has both instances MonadReader MessageCase and MonadReader LogConfig it goes against the dependency declaration.
The easiest solution is to change mainProgram to have a non-generic type:
mainProgram :: ReaderT MessageCase (ReaderT LogConfig IO) ()
mainProgram = do input <- getUserInput
lift $ doLog input
liftIO $ putStrLn $ "Entry logged: " ++ input
This also requires the explicit lift for doLog.
Now you can run the mainProgram by running each ReaderT separately, like this:
main :: IO ()
main = do
let messageCase = undefined :: MessageCase
logConfig = undefined :: LogConfig
runReaderT (runReaderT mainProgram messageCase) logConfig
If you want to have a generic function that uses two different MonadReader instances, you need to make it explicit in the signature that one reader is a monad transformer on top of the other reader.
mainProgram :: (MonadTrans mt, MonadReader MessageCase (mt m), MonadReader LogConfig m, MonadIO (mt m), MonadIO m) => mt m ()
mainProgram = do input <- getUserInput
lift $ doLog input
liftIO $ putStrLn $ "Entry logged: " ++ input
However, this has the unfortunate effect that the function is no longer fully generic, because the order in which the two readers appear in the monad stack is locked. Maybe there is a cleaner way to achieve this, but I wasn't able to figure one out from the top of my head without sacrificing (even more) genericity.
Related
I will preface this by saying that I am a novice Haskell programmer (tinkered with it sporadically over the years) but I have a fair few years on the counter when it comes to OOO and imperative programming. I am currently learning how to use monads & combining them via the use of monad transformers (assuming I've got the correct term).
While I am able to assemble/chain things together, I am finding it hard to build an intuition for what the best way and style is & how best to assemble/write those interactions.
Specifically, I am curious to know what the best practice (or at least your practice) is for using lift/liftIO and any flavour in between & if there is way (and benefit) to hide them as I am finding them rather 'noisy'.
Below is an example snippet which I have put together to illustrate what I mean :
consumeRenderStageGL' :: RenderStage -> StateT RenderStageContext IO ()
consumeRenderStageGL' r = do
pushDebugGroupGL (name r)
liftIO $ consumePrologueGL ( prologue r )
liftIO $ consumeEpilogueGL ( epilogue r )
consumeStreamGL ( stream r )
liftIO $ popDebugGroupGL
Some of the functions it calls make use of the state monad :
pushDebugGroupGL :: String -> StateT RenderStageContext IO ()
pushDebugGroupGL tag = do
currentDebugMessageID <- gets debugMessageID
liftIO $ GL.pushDebugGroup GL.DebugSourceApplication (GL.DebugMessageID currentDebugMessageID) tag
modify (\fc -> fc { debugMessageID = (currentDebugMessageID + 1) })
consumeStreamGL :: Stream -> StateT RenderStageContext IO ()
consumeStreamGL s = do
mapM_ consumeTokenGL s
logGLErrors
While most don't and just live in IO (meaning they have to be lifted):
consumePrologueGL :: Prologue -> IO ()
consumePrologueGL p = do
colourClearFlag <- setupAndReturnClearFlag GL.ColorBuffer ( clearColour p ) (\(Colour4 r g b a) -> GL.clearColor $= (GL.Color4 r g b a))
depthClearFlag <- setupAndReturnClearFlag GL.DepthBuffer ( clearDepth p ) (\d -> GL.clearDepthf $= d)
stencilClearFlag <- setupAndReturnClearFlag GL.StencilBuffer ( clearStencil p ) (\s -> GL.clearStencil $= fromIntegral s)
GL.clear $ catMaybes [colourClearFlag, depthClearFlag, stencilClearFlag]
logGLErrors
where
setupAndReturnClearFlag flag mValue function = case mValue of
Nothing -> return Nothing
Just value -> (function value) >> return (Just flag)
My question is : is there any way to hide the liftIO in consumeRenderStageGL' and more importantly would this be a good or a bad idea?
One way I can think of hiding/getting rid of the liftIO is to bring both my consumePrologueGL & consumeEpilogueGL into my state monad but this seems wrong in the sense that those function do not need (and should not) interact with it ; all this just to reduce code noise.
The other option I can think of is to simply create the lifted version of the functions and call them in consumeRenderStageGL' - this would reduce the code noise but be identical in execution/evaluation.
The third option, which is how my logGLErrors works is that I have used a type class which has an instance defined for both IO & my state monads.
I look forward to reading what your opinions, advices and practices are.
Thanks in advance!
There are a few solutions. A common one is to make your basic actions MonadIO m => m … instead of IO …:
consumePrologueGL :: (MonadIO m) => Prologue -> m ()
consumePrologueGL p = liftIO $ do
…
Then you can use them in StateT RenderStageContext IO () without wrapping, due to MonadIO m => MonadIO (StateT s m), and of course MonadIO IO where liftIO is the identity function.
You can also abstract over the StateT part using MonadState from mtl, so if you add another transformer above/below it, you won’t have the same issue of lifting from/to StateT.
pushDebugGroupGL
:: (MonadIO m, MonadState RenderStageContext m)
=> String -> m ()
Generally, a concrete stack of transformers types is fine, it just helps to wrap all your basic operations for convenience so that all the lifts are in one place.
mtl helps remove the lift noise from your code altogether, and working in a polymorphic type m means you have to declare which effects a function actually uses, and can substitute different implementations of all the effects (except for MonadIO) for testing. Using monad transformers as an effect system like this is great if you have few types of effects; if you want something finer-grained or more flexible, you’ll start hitting the pain points that make people reach for algebraic effects instead.
It’s also worth assessing whether you need StateT over IO. Typically if you’re in IO, you don’t need the pure state offered by StateT, so instead of StateT MutableState IO you might as well use ReaderT (IORef MutableState) IO.
It’s also possible to make that (or a newtype wrapper for it) an instance of MonadState MutableState, so your code using get/put/modify wouldn’t even need to change:
{-# Language GeneralizedNewtypeDeriving #-}
import Data.Coerce (coerce)
newtype MutT s m a = MutT
{ getMutT :: ReaderT (IORef s) m a }
deriving
( Alternative
, Applicative
, Functor
, Monad
, MonadIO
, MonadTrans
)
evalMutT :: MutT s m a -> IORef s -> m a
evalMutT = coerce
instance (MonadIO m) => MonadState s (MutT s m) where
state f = MutT $ do
r <- ask
liftIO $ do
-- NB: possibly lazier than you want.
(a, s) <- f <$> readIORef r
a <$ writeIORef r s
This combo of ReaderT & IO is a pretty common design pattern.
I am trying to define a family of state machines with somewhat different kinds of states. In particular, the more "complex" state machines have states which are formed by combining the states of simpler state machines.
(This is similar to an object oriented setting where an object has several attributes which are also objects.)
Here is a simplified example of what I want to achieve.
data InnerState = MkInnerState { _innerVal :: Int }
data OuterState = MkOuterState { _outerTrigger :: Bool, _inner :: InnerState }
innerStateFoo :: Monad m => StateT InnerState m Int
innerStateFoo = do
i <- _innerVal <$> get
put $ MkInnerState (i + 1)
return i
outerStateFoo :: Monad m => StateT OuterState m Int
outerStateFoo = do
b <- _outerTrigger <$> get
if b
then
undefined
-- Here I want to "invoke" innerStateFoo
-- which should work/mutate things
-- "as expected" without
-- having to know about the outerState it
-- is wrapped in
else
return 666
More generally, I want a generalized framework where these nestings are more complex. Here is something I wish to know how to do.
class LegalState s
data StateLess
data StateWithTrigger where
StateWithTrigger :: LegalState s => Bool -- if this trigger is `True`, I want to use
-> s -- this state machine
-> StateWithTrigger
data CombinedState where
CombinedState :: LegalState s => [s] -- Here is a list of state machines.
-> CombinedState -- The combinedstate state machine runs each of them
instance LegalState StateLess
instance LegalState StateWithTrigger
instance LegalState CombinedState
liftToTrigger :: Monad m, LegalState s => StateT s m o -> StateT StateWithTrigger m o
liftToCombine :: Monad m, LegalState s => [StateT s m o] -> StateT CombinedState m o
For context, this is what I want to achieve with this machinery:
I want to design these things called "Stream Transformers", which are basically stateful functions: They consume a token, mutate their internal state and output something. Specifically, I am interested in a class of Stream Transformers where the output is a Boolean value; we will call these "monitors".
Now, I am trying to design combinators for these objects. Some of them are:
A pre combinator. Suppose that mon is a monitor. Then, pre mon is a monitor which always produces False after the first token is consumed and then mimicks the behaviour of mon as if the previous token is being inserted now. I would want to model the state of pre mon with StateWithTrigger in the example above since the new state is a boolean along with the original state.
An and combinator. Suppose that m1 and m2 are monitors. Then, m1 `and` m2 is a monitor which feeds the token to m1, and then to m2, and then produces True if both of the answers were true. I would want to model the state of m1 `and` m2 with CombinedState in the example above since the state of both monitors must be maintained.
For your first question, as Carl mentioned, zoom from lens does exactly what you want. Your code with lenses could be written like this:
{-# LANGUAGE TemplateHaskell #-}
import Control.Lens
import Control.Monad.State.Lazy
newtype InnerState = MkInnerState { _innerVal :: Int }
deriving (Eq, Ord, Read, Show)
data OuterState = MkOuterState
{ _outerTrigger :: Bool
, _inner :: InnerState
} deriving (Eq, Ord, Read, Show)
makeLenses ''InnerState
makeLenses ''OuterState
innerStateFoo :: Monad m => StateT InnerState m Int
innerStateFoo = do
i <- gets _innerVal
put $ MkInnerState (i + 1)
return i
outerStateFoo :: Monad m => StateT OuterState m Int
outerStateFoo = do
b <- gets _outerTrigger
if b
then zoom inner $ innerStateFoo
else pure 666
Edit: While we're at it, if you're already bringing in lens then innerStateFoo can be written like so:
innerStateFoo :: Monad m => StateT InnerState m Int
innerStateFoo = innerVal <<+= 1
For context, this is what I want to achieve with this machinery:
I want to design these things called "Stream Transformers", which are basically stateful functions: They consume a token, mutate their internal state and output something. Specifically, I am interested in a class of Stream Transformers where the output is a Boolean value; we will call these "monitors".
I think that what you want to achieve doesn't need very much machinery.
newtype StreamTransformer input output = StreamTransformer
{ runStreamTransformer :: input -> (output, StreamTransformer input output)
}
type Monitor input = StreamTransformer input Bool
pre :: Monitor input -> Monitor input
pre st = StreamTransformer $ \i ->
-- NB: the first output of the stream transformer vanishes.
-- Is that OK? Maybe this representation doesn't fit the spec?
let (_, st') = runStreamTransformer st i
in (False, st')
and :: Monitor input -> Monitor input -> Monitor input
and left right = StreamTransformer $ \i ->
let (bleft, mleft) = runStreamTransformer left i
(bright, mright) = runStreamTransformer right i
in (bleft && bright, mleft `and` mright)
This StreamTransformer is not necessarily stateful, but admits stateful ones. You don't need to (and IMO should not! in most cases!!) reach for typeclasses in order to define these (or indeed ever! :) but that's another topic).
notStateful :: StreamTransformer input ()
notStateful = StreamTransformer $ \_ -> ((), notStateful)
stateful :: s -> (input -> s -> (output, s)) -> StreamTransformer input output
stateful s k = StreamTransformer $ \input ->
let (output, s') = k input s
in (output, stateful s' k)
alternateBool :: Monitor anything
alternateBool = stateful True $ \_ s -> (s, not s)
I want to define a function that expects an Int, prints an error in the console depending on the number (x) and then updates the State with Nothing.
How can I join those commands in one function?
Here's what I got:
type Env = [(Variable,Int)]
newtype StateError a = StateError { runStateError :: Env -> Maybe (a, Env) }
class Monad m => MonadError m where
throw :: Monad m => a -> m a
instance MonadError StateError where
throw x = StateError (\s -> Nothing)
But I can't figure out how to perform the IO side-effect and then the State update in the same function definition
No
A function in the state monad, such as a -> State s b, is a pure function (no IO) that happens to have an extra function argument s hidden though some handy plumbing.
You can't print to the console from the state monad.
However, Yes!
However! You can use a monad transformer to get both State and some underlying monad such as IO.
I'll provide an example using transformers instead of a custom monad and mtl as it appears you were using. With mtl you can use classes like MonadError to leverage a throw that works well with other libraries that use the mtl classes. On the other hand, if you are the end consumer of this transformer it is less important.
First we'll import the modules that give us MonadIO, StateT, MaybeT, and use newtype deriving so we don't have to type out the monad instance boilerplate:
{-# LANGUAGE GeneralizedNewtypeDeriving #-}
import qualified Control.Monad.Trans.State as S
import Control.Monad.IO.Class
import Control.Monad.Trans.Maybe
import Control.Monad.Trans
Just to be complete we'll spell out the types useful to your abstraction:
type Variable = String
type Env = [(Variable,Int)]
Now we can get to the interesting part - a Monad definition and functions for plumbing. The monad stack is StateT MaybeT IO:
newtype StateError a = StateError { unStateError :: S.StateT Env (MaybeT IO) a }
deriving (Monad, Applicative, Functor)
And we can run it by first unwrapping the newtype, then running the state, and finally the MaybeT:
run :: StateError a -> IO (Maybe (a, Env))
run = runMaybeT . flip S.runStateT [] . unStateError
Usually you'll write an army of functions that provide your monad abstraction. For this question it's just "update the state" and "print to stdout":
modify :: (Env -> Env) -> StateError ()
modify = StateError . S.modify
emit :: Show a => a -> StateError ()
emit = StateError . liftIO . print . show
Armed with our Monad of Power, we can do fancy things like update state and emit IO messages and track failure or success:
updateAndPrint :: Variable -> Int -> StateError ()
updateAndPrint v i =
do emit (v,i)
modify ((v,i):)
Oh, and failure is pretty simple - just fail in our MaybeT monad:
throw :: a -> StateError b
throw _ = fail "" -- same as 'MaybeT (pure Nothing)'
We can use this monad as expected:
> run $ updateAndPrint "var" 1
"(\"var\",1)"
Just (() -- ^ return value of `updateAndPrint`
,[("var",1)]) -- ^ resulting state
I am attempting to use the IO monad in a Spock application. The following code does not compile:
get "api/entities" $ do
entities <- loadEntities
let e1 : xs = entities
text $ note e1
loadEntities has the type IO [Entity]
The error is Couldn't match type ‘ActionT IO ()’ with ‘t0 -> IO b0’
Is Spock using a monad other than IO? If so, how do I get the result of loadEntities?
Writing answer so people can see a better explanation.
If you look at get it has the type.
get :: MonadIO m => SpockRoute -> ActionT m () -> SpockT m ()
ActionT is a monad transformer and it requires in inner monad to have an instance of MonadIO. If we look at the typeclass MonadIO it has a function
liftIO :: IO a -> m a
This means every that you call execute functions of the type IO a in that stack by using liftIO. ActionT has an instance of MonadIO also and which is the one you are using here to call your IO function. So to call loadEntities you had to
entities <- liftIO loadEntities
If you end of calling a certain function like that a lot you can create a separate module import it qualified and export a more friendly one.
module Lifted (loadEntities) where
import qualified SomeModule as IO
loadEntities :: MonadIO m => m Entities
loadEntities = liftIO IO.loadEntities
This will make it so you don't always have you use liftIO
First up, a simplified version of the task I want to accomplish: I have several large files (amounting to 30GB) that I want to prune for duplicate entries. To this end, I establish a database of hashes of the data, and open the files one-by-one, hashing each item, and recording it in the database and the output file iff its hash wasn't already in the database.
I know how to do this with iteratees, enumerators, and I wanted to try conduits. I also know how to do it with conduits, but now I want to use conduits & persistent. I'm having problems with the types, and possibly with the entire concept of ResourceT.
Here's some pseudo code to illustrate the problem:
withSqlConn "foo.db" $ runSqlConn $ runResourceT $
sourceFile "in" $= parseBytes $= dbAction $= serialize $$ sinkFile "out"
The problem lies in the dbAction function. I would like to access the database here, naturally. Since the action it does is basically just a filter, I first thought to write it like that:
dbAction = CL.mapMaybeM p
where p :: (MonadIO m, MonadBaseControl IO (SqlPersist m)) => DataType -> m (Maybe DataType)
p = lift $ putStrLn "foo" -- fine
insert $ undefined -- type error!
return undefined
The specific error I get is:
Could not deduce (m ~ b0 m0)
from the context (MonadIO m, MonadBaseControl IO (SqlPersist m))
bound by the type signature for
p :: (MonadIO m, MonadBaseControl IO (SqlPersist m)) =>
DataType -> m (Maybe DataType)
at tools/clean-wac.hs:(33,1)-(34,34)
`m' is a rigid type variable bound by
the type signature for
p :: (MonadIO m, MonadBaseControl IO (SqlPersist m)) =>
DataType -> m (Maybe (DataType))
at tools/clean-wac.hs:33:1
Expected type: m (Key b0 val0)
Actual type: b0 m0 (Key b0 val0)
Note that this might be due to wrong assumptions I made in designing the type signature. If I comment out the type signature and also remove the lift statement, the error message turns into:
No instance for (PersistStore ResourceT (SqlPersist IO))
arising from a use of `p'
Possible fix:
add an instance declaration for
(PersistStore ResourceT (SqlPersist IO))
In the first argument of `CL.mapMaybeM', namely `p'
So this means that we can't access the PersistStore at all via ResourceT?
I cannot write my own Conduit either, without using CL.mapMaybeM:
dbAction = filterP
filterP :: (MonadIO m, MonadBaseControl IO (SqlPersist m)) => Conduit DataType m DataType
filterP = loop
where loop = awaitE >>= either return go
go s = do lift $ insert $ undefined -- again, type error
loop
This resulted in yet another type error I don't fully understand.
Could not deduce (m ~ b0 m0)
from the context (MonadIO m, MonadBaseControl IO (SqlPersist m))
bound by the type signature for
filterP :: (MonadIO m,
MonadBaseControl IO (SqlPersist m)) =>
Conduit DataType m DataType
`m' is a rigid type variable bound by
the type signature for
filterP :: (MonadIO m,
MonadBaseControl IO (SqlPersist m)) =>
Conduit DataType m DataType
Expected type: Conduit DataType m DataType
Actual type: Pipe
DataType DataType DataType () (b0 m0) ()
In the expression: loop
In an equation for `filterP'
So, my question is: is it possible to use persistent like I intended to inside a conduit at all? And if, how? I am aware that since I can use liftIO inside the conduit, I could just go and use, say HDBC, but I wanted to use persistent explicitly in order to understand how it works, and because I like its db-backend agnosticism.
The code below compiles fine for me. Is it possible that the frameworks have moved on inthe meantime and things now just work?
However note the following changes I had to make as the world has changed a bit or I didn't have all your code. I used conduit-1.0.9.3 and persistent-1.3.0 with GHC 7.6.3.
Omitted parseBytes and serialise as I don't have your definitions and defined DataType = ByteString instead.
Introduced a Proxy parameter and an explicit type signature for the undefined value to avoid problems with type family injectivity. These likely don't arise in your real code because it will have a concrete or externally determined type for val.
Used await rather than awaitE and just used () as the type to substitute for the Left case, as awaitE has been retired.
Passed a dummy Connection creation function to withSqlConn - perhaps I should have used some Sqlite specific function?
Here's the code:
{-# LANGUAGE FlexibleContexts, NoMonomorphismRestriction,
TypeFamilies, ScopedTypeVariables #-}
module So133331988 where
import Control.Monad.Trans
import Database.Persist.Sql
import Data.ByteString
import Data.Conduit
import Data.Conduit.Binary
import Data.Proxy
test proxy =
withSqlConn (return (undefined "foo.db")) $ runSqlConn $ runResourceT $
sourceFile "in" $= dbAction proxy $$ sinkFile "out"
dbAction = filterP
type DataType = ByteString
filterP
:: forall m val
. ( MonadIO m, MonadBaseControl IO (SqlPersist m)
, PersistStore m, PersistEntity val
, PersistEntityBackend val ~ PersistMonadBackend m)
=> Proxy val
-> Conduit DataType m DataType
filterP Proxy = loop
where loop = await >>= maybe (return ()) go
go s = do lift $ insert (undefined :: val)
loop