Let’s try to solve one specific problem using the State monad and monad transformers to see how pure stateful computations work in Haskell and how they can be used to write better interfaces. This blog post shouldn’t be considered as a tutorial on the State monad or monad transformers, but if you’re already familiar with those concepts, you may find the following use case interesting.

The blog post also contains several exercises, so you can follow the code by yourself and try to expand the presented solution along with solving exercises.

Consider the following data type:

data Value = BoolValue Bool | IntValue Int

This is a plain Haskell sum type that represents possible options of parsing the string into a more structured type.

NOTE: how to parse a string into a Value is out of the scope of this blog post.

Let’s assume that you received a list of such values from some external data source and you want to convert this list to your custom data type. More precisely, you want to implement the following function:

decodeValues :: [ Value ] -> Either VeryGoodErrorMessage MyType

The need for such a function may appear in various situations. The list of Value s can represent many things:

A row in some CSV file. A row in some SQL query result. An array in some JSON object.

Basically, any form of unstructured data that you want to decode to structured types.

I’m going to describe in detail, a possible general solution for implementing decodeValues with an explanatory error message.

Naive solution🔗

Suppose that you have this Haskell data type:

data User = User { userAge :: Int , userIsHaskeller :: Bool }

It’s quite easy to implement a naive decoder from [Value] to User with a poor error message:

decodeValues :: [ Value ] -> Maybe User IntValue age, BoolValue hask] = Just $ User age hask decodeValues [age,hask]age hask = Nothing decodeValues _

This function is elementary and only uses basic pattern matching to convert a list of unstructured data to a custom Haskell data type. Sadly, the error message is completely non-informative. Ideally, Maybe should only be used when your function can fail because of a single reason. However, in our case there are multiple possible failure scenarios for the decodeValues function:

Given list is too small. Given list is too big. Value at any index is different from what we expect.

It would be tedious to implement good error reporting using only basic pattern matching. Moreover, the size of the function wouldn’t be small, which would and up being a problem when you need to write variations of your function for different types.

Exercise #1🔗 Try to implement the decodeValues function for User that reports good error messages and uses only pattern matching.

The following sections of the blog post show a general solution to this problem with fine-grained error messages.

Parsing a single value🔗

First of all, like any other good Haskeller, I am going to decompose this huge problem into a few smaller ones. In the previous section, we started from decoding whole list of values, but let’s now learn how to decode a single value. Before that, however, we need to think about the data type of the error message. To have a clear understanding of what’s wrong with a single value, we need to know what the received value was and what we expected it to be:

data SingleValueError = SingleValueError { singleValueErrorExpected :: Text , singleValueErrorActual :: Value }

With that, we can implement functions for decoding a single Value :

valToBool :: Value -> Either SingleValueError Bool BoolValue b) = Right b valToBool (b) = Left $ SingleValueError "Bool" v valToBool v valToInt :: Value -> Either SingleValueError Int IntValue i) = Right i valToInt (i) = Left $ SingleValueError "Int" v valToInt v

NOTE: we can remove some code duplication already at this stage! If you have a function like typeName :: Typeable a => Text (see the implementation here) and you derive prisms for the Value data type, you can implement a single generic fromValue function. But for the sake of simplicity, we won’t mind a bit of boilerplate code.

Once we’ve learned how to decode a single value, let’s proceed with expanding this approach for a list of values.

Parsing a list of values: State🔗

Just like in the previous section, let’s start with creating the data type for our error messages:

data ListValueError = UnexpectedEndOfList | ExpectedEndOfList ( NonEmpty Value ) | WrongValue SingleValueError

Let’s look closer at the constructors of this error messages data type:

UnexpectedEndOfList : this error means that the list was too short. ExpectedEndOfList : this error means that we were given a bigger list than we expected. This error contains the remaining Value s. Note that here we use a NonEmpty list to store the remaining items because if the list was bigger than we expected, then it’s guaranteed to have a non-empty remainder. This also prevents us from writing the wrong implementation of the function. WrongValue : this constructor stores the error for parsing a single value.

The idea of using the State monad comes to mind after noticing the following: we can store the list of values in the state and in our stateful action we can decode the current head of the list and put the remaining list back to the state. Just as in basic State monad tutorials where a stack data structure is used as an example.

So, initially we should create the data type for our state:

newtype Values = Values { unValues :: [ Value ] } ] }

That was easy. Now we need to specialize the State monad with our type and give it some meaningful name. We can use type aliases but let’s be good Haskellers and create the newtype as a wrapper around the State monad:

newtype Decoder a = Decoder { runDecoder :: State Values a } deriving ( Functor , Applicative , Monad , MonadState Values )

Before writing the code itself, it makes sense to describe the logic behind the single value stateful decoder upfront:

We need to take a list of values from our state. If the list is empty, we need to throw an error reporting that the list is empty and stop decoding. If the list is not empty, we need to apply the given single value decoder to the head of the list and pattern match on the result of the decoder. If the decoder results in error, we need to rethrow that error. If the decoder is successful, we need to return our value and put the remaining list to the state. Check the remaining list and if it’s not empty then throw the ExpectedEndOfList error.

After designing our decoding algorithm, we can try to implement it:

value :: ( Value -> Either SingleValueError a) a) -> Decoder ( Either ListValueError a) a) = gets unValues >>= \ case value valDecodergets unValues -> pure $ Left UnexpectedEndOfList [] : vals -> case valDecoder val of valvalsvalDecoder val Left err -> pure $ Left WrongValue err errerr Right a -> Right a <$ put ( Values vals) put (vals)

Exercise #2🔗 In our decoder for the field we don’t report the position of the WrongField error. However, it’s quite easy to patch the decoder to take this into consideration.

We’re using Either ListValueError as the return type of our value decoder to report errors. But because of that, it’s not easy to compose different value decoders. This is how Decoder for User might look like:

user :: Decoder ( Either ListValueError User ) = value valToInt >>= \ case uservalue valToInt Left err -> pure $ Left err errerr Right age -> value valToBool >>= \ case agevalue valToBool Left err -> pure $ Left err errerr Right hask -> pure $ Right $ User age hask haskage hask

In the last section, we are going to solve this particular problem: better composability of the value decoders.

Parsing a list of values: StateT + Either🔗

You may notice that the pattern matching we performed over Either looks familiar. Indeed, it is the Monad instance for Either . We couldn’t use it, because we were already using the State monad. This is when monad transformers come in to save the day! In simple words, with monad transformers we can combine monadic effects of multiple monads so the >>= operator performs actions for every monad in our monad transformer state.

We want to combine State and Either effects, but in this particular case, we should be cautious because the State monad transformer and the Either monad transformer are not commutative. Which means that StateT s Either is not the same as EitherT (State s) . Let’s look at this closely:

StateT s m a ~ s -> m (a, s) s m am (a, s) EitherT e m a ~ m ( Either e a) e m am (e a) 1 . StateT s ( Either e) a ~ s -> Either e (a, s) s (e) ae (a, s) 2 . EitherT e ( State s) a ~ State s ( Either e a) ~ s -> ( Either e a, s) e (s) as (e a)e a, s)

Today, let’s pick the first option. The reason for this is to stop decoding as soon as we face an error. Only after we’ve managed to decode the raw values to our type successfully, we can inspect the remaining list of values in case we need to produce the ExpectedEndOfList error message.

Let’s refactor our existing approach to this new version, and start with patching the type of the Decoder monad:

newtype Decoder a = Decoder { runDecoder :: StateT Values ( Either ListValueError ) a ) a } deriving ( Functor , Applicative , Monad , MonadState Values , MonadError ListValueError )

Then we can rewrite our value decoder to use throwError function to report errors.

value :: ( Value -> Either SingleValueError a) a) -> Decoder a = gets unValues >>= \ case value valDecodergets unValues -> throwError UnexpectedEndOfList []throwError : vals -> case valDecoder val of valvalsvalDecoder val Left err -> throwError $ WrongValue err errthrowErrorerr Right a -> a <$ put ( Values vals) put (vals)

Note how the code became much cleaner! Now it’s quite easy to implement the decoder for the User data type:

user :: Decoder User = User <$> value valToInt <*> value valToBool uservalue valToIntvalue valToBool

And it’s also straightforward to decode the list of values with the given Decoder :

decodeValues :: [ Value ] -> Decoder a -> Either ListValueError a = do -- do-notation for the Either monad decodeValues values decoder <- runStateT (runDecoder decoder) ( Values values) (a, finalState)runStateT (runDecoder decoder) (values) case unValues finalState of unValues finalState -> pure a [] : vals -> Left $ ExpectedEndOfList (val :| vals) valvals(valvals)

And it works like a charm:

> decodeValues [] user ghcidecodeValues [] user Left UnexpectedEndOfList > decodeValues [ IntValue 42 , BoolValue True ] user ghcidecodeValues [] user Right ( User {userAge = 42 , userIsHaskeller = True }) {userAge, userIsHaskeller}) > decodeValues [ BoolValue True , IntValue 42 ] user ghcidecodeValues [] user Left ( WrongValue ( SingleValueError = "Int" , valueErrorActual = BoolValue True })) {valueErrorExpected, valueErrorActual})) > decodeValues [ IntValue 42 , BoolValue True , BoolValue False ] user ghcidecodeValues [] user Left ( ExpectedEndOfList ( BoolValue False :| [])) []))

NOTE: In this blog post I’ve used a function-based approach for decoders. However, it’s also possible to use a typeclasses-based approach to avoid passing explicitly value conversion function for value decoder and Decoder action to decodeValues function.

That’s all folks! I hope that after this blog post you have gained a better insight into the State monad and monad transformers.

Here you can find gist with the full code: