# Haskell/Monad transformers

* Monad transformers (Solutions)
* Monads
* Prologue: IO, an applicative functor
* Understanding monads
* Maybe List
* do notation
* IO State
* Alternative and MonadPlus
* Monad transformers
We have seen how monads can help handling IO actions, Maybe, lists, and state. With monads providing a common way to use such useful general-purpose tools, a natural thing we might want to do is using the capabilities of several monads at once. For instance, a function could use both I/O and Maybe exception handling. While a type like IO (Maybe a) would work just fine, it would force us to do pattern matching within IO do-blocks to extract values, something that the Maybe monad was meant to spare us from.
Enter monad transformers: special types that allow us to roll two monads into a single one that shares the behavior of both.

## Passphrase validation

Consider a real-life problem for IT staff worldwide: getting users to create strong passphrases. One approach: force the user to enter a minimum length with various irritating requirements (such as at least one capital letter, one number, one non-alphanumeric character, etc.)
Here's a Haskell function to acquire a passphrase from a user:
First and foremost, getPassphrase is an IO action, as it needs to get input from the user. We also use Maybe, as we intend to return Nothing in case the password does not pass the isValid. Note, however, that we aren't actually using Maybe as a monad here: the do block is in the IO monad, and we just happen to return a Maybe value inside it.
Monad transformers not only make it easier to write getPassphrase but also simplify all the code instances. Our passphrase acquisition program could continue like this:
The code uses one line to generate the maybe_value variable followed by further validation of the passphrase.
With monad transformers, we will be able to extract the passphrase in one go — without any pattern matching (or equivalent bureaucracy like isJust). The gains for our simple example might seem small but will scale up for more complex situations.

## A simple monad transformer: MaybeT

To simplify getPassphrase and the code that uses it, we will define a monad transformer that gives the IO monad some characteristics of the Maybe monad; we will call it MaybeT. That follows a convention where monad transformers have a "T" appended to the name of the monad whose characteristics they provide.
MaybeT is a wrapper around m (Maybe a), where m can be any monad (IO in our example):
This data type definition specifies a MaybeT type constructor, parameterized over m, with a data constructor, also called MaybeT, and a convenient accessor function runMaybeT, with which we can access the underlying representation.
The whole point of monad transformers is that they transform monads into monads; and so we need to make MaybeT m an instance of the Monad class:
It would also have been possible (though arguably less readable) to write the return function as: return = MaybeT . return . return.
Starting from the first line of the do block:
* First, the runMaybeT accessor unwraps x into an m (Maybe a) computation. That shows us that the whole do block is in m.
* Still in the first line, <- extracts a Maybe a value from the unwrapped computation.
* The case statement tests maybe_value:
** With Nothing, we return Nothing into m;
** With Just, we apply f to the value from the Just. Since f has MaybeT m b as result type, we need an extra runMaybeT to put the result back into the m monad.
* Finally, the do block as a whole has m (Maybe b) type; so it is wrapped with the MaybeT constructor.
It may look a bit complicated, but aside from the copious amounts of wrapping and unwrapping, the implementation of MaybeT's bind works the same way as the implementation of Maybe's familiar bind operator:
Why use the MaybeT constructor before the do block while we have the accessor runMaybeT within do? Well, the do block must be in the m monad, not in MaybeT m (which lacks a defined bind operator at this point).
As usual, we also have to provide instances for the superclasses of Monad, Applicative and Functor:
In addition, it is convenient to make MaybeT m an instance of a few other classes:
MonadTrans implements the lift function, so we can take functions from the m monad and bring them into the MaybeT m monad in order to use them in do blocks. As for Alternative and MonadPlus, since Maybe is an instance of those classes it makes sense to make the MaybeT m an instance too.

### Passphrase validation, simplified

The above passphrase validation example can now be simplified using the MaybeT monad transformer as follows:
The code is now simpler, especially in the user function askPassphrase. Most importantly, we do not have to manually check whether the result is Nothing or Just: the bind operator takes care of that for us.
Note how we use lift to bring the functions getLine and putStrLn into the MaybeT IO monad. Also, since MaybeT IO is an instance of Alternative, checking for passphrase validity can be taken care of by a guard statement, which will return empty (i.e. IO Nothing) in case of a bad passphrase.
Incidentally, with the help of MonadPlus it also becomes very easy to ask the user ad infinitum for a valid passphrase:
Running your new version of askPassphrase on ghci is easy:

## A plethora of transformers

The transformers package provides modules with transformers for many common monads (MaybeT, for instance, can be found in Control.Monad.Trans.Maybe). These are defined consistently with their non-transformer versions; that is, the implementation is basically the same except with the extra wrapping and unwrapping needed to thread the other monad. From this point on, we will use precursor monad to refer to the non-transformer monad (e.g. Maybe in MaybeT) on which a transformer is based and base monad to refer to the other monad (e.g. IO in MaybeT IO) on which the transformer is applied.
To pick an arbitrary example, ReaderT Env IO String is a computation which involves reading values from some environment of type Env (the semantics of Reader, the precursor monad) and performing some IO in order to give a value of type String. Since the bind operator and return for the transformer mirror the semantics of the precursor monad, a do block of type ReaderT Env IO String will, from the outside, look a lot like a do block of the Reader monad, except that IO actions become trivial to embed by using lift.

### Type juggling

We have seen that the type constructor for MaybeT is a wrapper for a Maybe value in the base monad. So, the corresponding accessor runMaybeT gives us a value of type m (Maybe a) - i.e. a value of the precursor monad returned in the base monad. Similarly, for the ListT and ExceptT transformers, which are built around lists and Either respectively:
and
Not all transformers are related to their precursor monads in this way, however. Unlike the precursor monads in the two examples above, the Writer, Reader, State, and Cont monads have neither multiple constructors nor constructors with multiple arguments. For that reason, they have run... functions which act as simple unwrappers, analogous to the run...T of the transformer versions. The table below shows the result types of the run... and run...T functions in each case, which may be thought of as the types wrapped by the base and transformed monads respectively.
| Precursor | Transformer | Original Type ("wrapped" by precursor) | Combined Type ("wrapped" by transformer) |
| Writer | WriterT | (a, w) | m (a, w) |
| Reader | ReaderT | r -> a | r -> m a |
| State | StateT | s -> (a, s) | s -> m (a, s) |
| Cont | ContT | (a -> r) -> r | (a -> m r) -> m r |
Notice that the precursor monad type constructor is absent in the combined types. Without interesting data constructors (of the sort that Maybe and lists have), there is no reason to retain the precursor monad type after unwrapping the transformed monad. It is also worth noting that in the latter three cases we have function types being wrapped. StateT, for instance, turns state-transforming functions of the form s -> (a, s) into state-transforming functions of the form s -> m (a, s); only the result type of the wrapped function goes into the base monad. ReaderT is analogous.ContT is different because of the semantics of Cont (the continuation monad): the result types of both the wrapped function and its function argument must be the same, and so the transformer puts both into the base monad. In general, there is no magic formula to create a transformer version of a monad; the form of each transformer depends on what makes sense in the context of its non-transformer type.

## Lifting

We will now have a more detailed look at the lift function, which is critical in day-to-day use of monad transformers. The first thing to clarify is the name "lift". One function with a similar name that we already know is liftM. As we have seen in Understanding monads, it is a monad-specific version of fmap:
liftM applies a function (a -> b) to a value within a monad m. We can also look at it as a function of just one argument:
liftM converts a plain function into one that acts within m. By "lifting", we refer to bringing something into something else — in this case, a function into a monad.
liftM allows us to apply a plain function to a monadic value without needing do-blocks or other such tricks:
| bind notation | do notation | liftM |
| monadicValue >>= \x -> return (f x) | do x <- monadicValue return (f x) | liftM f monadicValue |
The lift function plays an analogous role when working with monad transformers. It brings (or, to use another common word for that, promotes) base monad computations to the combined monad. By doing so, it allows us to easily insert base monad computations as part of a larger computation in the combined monad.
lift is the single method of the MonadTrans class, found in Control.Monad.Trans.Class. All monad transformers are instances of MonadTrans, and so lift is available for them all.
There is a variant of lift specific to IO operations, called liftIO, which is the single method of the MonadIO class in Control.Monad.IO.Class.
liftIO can be convenient when multiple transformers are stacked into a single combined monad. In such cases, IO is always the innermost monad, and so we typically need more than one lift to bring IO values to the top of the stack. liftIO is defined for the instances in a way that allows us to bring an IO value from any depth while writing the function a single time.

### Implementing lift

Implementing lift is usually pretty straightforward. Consider the MaybeT transformer:
We begin with a monadic value of the base monad. With liftM (fmap would have worked just as fine), we slip the precursor monad (through the Just constructor) underneath, so that we go from m a to m (Maybe a). Finally, we wrap things up with the MaybeT constructor. Note that the liftM here works in the base monad, just like the do-block wrapped by MaybeT in the implementation of (>>=) we saw early on was in the base monad.
* Exercises
* Why is it that the lift function has to be defined separately for each monad, where as liftM can be defined in a universal way?
* Identity is a trivial functor, defined in Data.Functor.Identity as:newtype Identity a = Identity { runIdentity :: a }It has the following Monad instance:
* instance Monad Identity where
* return a = Identity a
* m >>= k = k (runIdentity m)
* Implement a monad transformer IdentityT, analogous to Identity but wrapping values of type m a rather than a. Write at least its Monad and MonadTrans instances.

## Implementing transformers
### The State transformer

As an additional example, we will now have a detailed look at the implementation of StateT. You might want to review the section on the State monad before continuing.
Just as the State monad might have been built upon the definition newtype State s a = State { runState :: (s -> (a,s)) }, the StateT transformer is built upon the definition:
StateT s m will have the following Monad instance, here shown alongside the one for the precursor state monad:
| State | StateT |
| newtype State s a = State { runState :: (s -> (a,s)) } instance Monad (State s) where return a = State $ \s -> (a,s) (State x) >>= f = State $ \s -> let (v,s') = x s in runState (f v) s' | newtype StateT s m a = StateT { runStateT :: (s -> m (a,s)) } instance (Monad m) => Monad (StateT s m) where return a = StateT $ \s -> return (a,s) (StateT x) >>= f = StateT $ \s -> do (v,s') <- x s -- get new value and state runStateT (f v) s' -- pass them to f |
Our definition of return makes use of the return function of the base monad. (>>=) uses a do-block to perform a computation in the base monad.
Note
Incidentally, we can now finally explain why, back in the chapter about State, there was a state function instead of a State constructor. In the transformers and mtl packages, State s is implemented as a type synonym for StateT s Identity, with Identity being the dummy monad introduced in an exercise of the previous section. The resulting monad is equivalent to the one defined using newtype that we have used up to now.
If the combined monads StateT s m are to be used as state monads, we will certainly want the all-important get and put operations. Here, we will show definitions in the style of the mtl package. In addition to the monad transformers themselves, mtl provides type classes for the essential operations of common monads. For instance, the MonadState class, found in Control.Monad.State, has get and put as methods:
Note
instance (Monad m) => MonadState s (StateT s m) should be read as: "For any type s and any instance of Monad m, s and StateT s m together form an instance of MonadState". s and m correspond to the state and the base monad, respectively. s is an independent part of the instance specification so that the methods can refer to it − for instance, the type of put is s -> StateT s m.
There are MonadState instances for state monads wrapped by other transformers, such as MonadState s m => MonadState s (MaybeT m). They bring us extra convenience by making it unnecessary to lift uses of get and put explicitly, as the MonadState instance for the combined monads handles the lifting for us.
It can also be useful to lift instances that might be available for the base monad to the combined monad. For instance, all combined monads in which StateT is used with an instance of MonadPlus can be made instances of MonadPlus:
The implementations of mzero and mplus do the obvious thing; that is, delegating the actual work to the instance of the base monad.
Lest we forget, the monad transformer must have a MonadTrans, so that we can use lift:
The lift function creates a StateT state transformation function that binds the computation in the base monad to a function that packages the result with the input state. If, for instance, we apply StateT to the List monad, a function that returns a list (i.e., a computation in the List monad) can be lifted into StateT s  where it becomes a function that returns a StateT (s -> [(a,s)]). I.e. the lifted computation produces multiple (value,state) pairs from its input state. This "forks" the computation in StateT, creating a different branch of the computation for each value in the list returned by the lifted function. Of course, applying StateT to a different monad will produce different semantics for the lift function.
* Exercises
* Implement state :: MonadState s m => (s -> (a, s)) -> m a in terms of get and put.
* Are MaybeT (State s) and StateT s Maybe equivalent? (Hint: one approach is comparing what the run...T unwrappers produce in each case.)

## Acknowledgements

This module uses a number of excerpts from All About Monads, with permission from its author Jeff Newbern.

## Notes

* ↑ The wrapping interpretation is only literally true for versions of the mtl package older than 2.0.0.0 .
* Monad transformers
* Solutions to exercises
* Monads
* Prologue: IO, an applicative functor
* >> Understanding monads
* >> Maybe >> List
* >> do notation
* >> IO >> State
* >> Alternative and MonadPlus
* >> Monad transformers
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* >> Elementary Haskell
* >> Intermediate Haskell
* >> Monads
* Advanced Haskell
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