How to execute monadic function combining state management and random generation

[emcarter]

I have created a monadic computation that combines state handling with random number generation:

import Control.Monad.State
import Control.Monad.Identity  
import Control.Monad.Random.Class

-- coin flip simulation
coinFlip :: MonadRandom m => m Bool
coinFlip = (\val -> val <= 0.5) <$> getRandomR (0,1 :: Double)

-- main function I need help with
myFunction :: (MonadState Bool m, MonadRandom m) => m Bool
myFunction = coinFlip >>= \result -> put result >> return result

I’m trying to figure out the proper way to execute myFunction such that it returns True approximately 50% of the time when run multiple times. What’s the correct approach to run this computation that requires both state and randomness capabilities?

[JackHero77]

You need to pick the right base monad for your transformer stack. Skip RandT (StateT Bool Identity) and go with StateT Bool (Rand StdGen) instead - it handles random generation way more naturally.

import Control.Monad.Trans.State
import Control.Monad.Random
import System.Random

executeFunction :: StdGen -> Bool -> (Bool, Bool)
executeFunction gen initialState = 
  runRand (runStateT myFunction initialState) gen

This gives you direct access to both result and final state. I’ve built similar stuff before and this ordering just makes more sense - the random generator becomes your base monad. Test the distribution by mapping over multiple generators or use split for independent random streams. You’ll get 50% True results when you sample enough times.

[AdventurousHiker17]

You could also use evalStateT with evalRandIO directly - much simpler than handling generators yourself. Just wrap it like evalStateT myFunction False >>= evalRandIO and run it in IO. Perfect for testing distributions without dealing with transformer unwrapping.

[Harry47]

You need monad transformers to stack your monads properly. Since your function needs both MonadState and MonadRandom constraints, use StateT with RandT from the MonadRandom package. This worked for me:

import Control.Monad.Trans.State
import Control.Monad.Random
import System.Random

runMyFunction :: IO (Bool, Bool)
runMyFunction = do
  gen <- newStdGen
  return $ evalRand (runStateT myFunction False) gen

Get the order right - runStateT gives you the stateful computation, then evalRand handles randomness with a generator. I struggled with this until I figured out the monad stack needs unwrapping in the correct sequence. Test multiple runs by calling runMyFunction repeatedly and you’ll see roughly 50% True results over many iterations.