Haskell/Understanding monads

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There is a certain mystique about monads, and even about the word "monad" itself. While one of our goals of this set of chapters is removing the shroud of mystery that is often wrapped around them, it is not difficult to understand how it comes about. Monads are very useful in Haskell, but the concept is often difficult to grasp at first. Since monads have so many applications, people often explain them from a particular point of view, which can derail your efforts towards understanding them in their full glory.

Historically, monads were introduced into Haskell to perform input and output – that is, I/O operations of the sort we dealt with in the Simple input and output chapter and the prologue to this unit. A predetermined execution order is crucial for things like reading and writing files, and monadic operations lend themselves naturally to sequencing. However, monads are by no means limited to input and output. They can be used to provide a whole range of features, such as exceptions, state, non-determinism, continuations, coroutines, and more. In fact, thanks to the versatility of monads, none of these constructs needed to be built into Haskell as a language; rather, they are defined by the standard libraries.

In the Prologue chapter, we began with an example and used it to steadily introduce several new ideas. Here, we will do it the other way around, starting with a definition of monad and, from that, building connections with what we already know.


A monad is defined by three things:

The function and operator are methods of the Monad type class and have types

    return :: a -> m a
    (>>=)  :: m a -> (a -> m b) -> m b

and are required to obey three laws that will be explained later on.

For a concrete example, take the Maybe monad. The type constructor is m = Maybe, while return and (>>=) are defined like this:

    return :: a -> Maybe a
    return x  = Just x

    (>>=)  :: Maybe a -> (a -> Maybe b) -> Maybe b
    m >>= g = case m of
                 Nothing -> Nothing
                 Just x  -> g x

Maybe is the monad, and return brings a value into it by wrapping it with Just. As for (>>=), it takes a m :: Maybe a value and a g :: a -> Maybe b function. If m is Nothing, there is nothing to do and the result is Nothing. Otherwise, in the Just x case, g is applied to x, the underlying value wrapped in Just, to give a Maybe b result. Note that this result may or may not be Nothing, depending on what g does to x. To sum it all up, if there is an underlying value of type a in m, we apply g to it, which brings the underlying value back into the Maybe monad.

The key first step to understand how return and (>>=) work is tracking which values and arguments are monadic and which ones aren't. As in so many other cases, type signatures are our guide to the process.

Motivation: Maybe[edit]

To see the usefulness of (>>=) and the Maybe monad, consider the following example: Imagine a family database that provides two functions:

    father :: Person -> Maybe Person
    mother :: Person -> Maybe Person

These look up the name of someone's father or mother. In case our database is missing some relevant information, Maybe allows us to return a Nothing value to indicate that the lookup failed, rather than crashing the program.

Let's combine our functions to query various grandparents. For instance, the following function looks up the maternal grandfather (the father of one's mother):

maternalGrandfather :: Person -> Maybe Person
maternalGrandfather p =
    case mother p of
        Nothing -> Nothing
        Just mom -> father mom

Or consider a function that checks whether both grandfathers are in the database:

    bothGrandfathers :: Person -> Maybe (Person, Person)
    bothGrandfathers p =
        case father p of
            Nothing -> Nothing
            Just dad ->
                case father dad of
                    Nothing -> Nothing
                    Just gf1 ->                          -- found first grandfather
                        case mother p of
                            Nothing -> Nothing
                            Just mom ->
                                case father mom of
                                    Nothing -> Nothing
                                    Just gf2 ->          -- found second grandfather
                                        Just (gf1, gf2)

What a mouthful! Every single query might fail by returning Nothing and the whole function must fail with Nothing if that happens.

Clearly there has to be a better way to write that instead of repeating the case of Nothing again and again! Indeed, that's what the Maybe monad is set out to do. For instance, the function retrieving the maternal grandfather has exactly the same structure as the (>>=) operator, so we can rewrite it as:

    maternalGrandfather p = mother p >>= father

With the help of lambda expressions and return, we can rewrite the two grandfathers function as well:

    bothGrandfathers p =
       father p >>=
           (\dad -> father dad >>=
               (\gf1 -> mother p >>=   -- gf1 is only used in the final return
                   (\mom -> father mom >>=
                       (\gf2 -> return (gf1,gf2) ))))

While these nested lambda expressions may look confusing to you, the thing to take away here is that (>>=) releases us from listing all the Nothings, shifting the focus back to the interesting part of the code.

To be a little more precise: The result of father p is a monadic value (in this case, either Just dad or Nothing, depending on whether p's father is in the database). As the father function takes a regular (non-monadic value), the (>>=) feeds p's dad to it as a non-monadic value. The result of father dad is then monadic again, and the process continues.

So, (>>=) helps us pass non-monadic values to functions without actually leaving a monad. In the case of the Maybe monad, the monadic aspect is the qualifier that we don't know with certainty whether the value will be found.

Type class[edit]

In Haskell, the Monad type class is used to implement monads. It is provided by the Control.Monad module and included in the Prelude. The class has the following methods:

    class Applicative m => Monad m where
        return :: a -> m a
        (>>=)  :: m a -> (a -> m b) -> m b
        (>>)   :: m a -> m b -> m b
        fail   :: String -> m a

Aside from return and bind, there are two additional methods, (>>) and fail. Both of them have default implementations, and so you don't need to provide them when writing an instance.

The operator (>>), spelled "then", is a mere convenience and commonly implemented as

    m >> n = m >>= \_ -> n

(>>) sequences two monadic actions when the second action does not involve the result of the first, which is a common scenario for monads such as IO.

    printSomethingTwice :: String -> IO ()
    printSomethingTwice str = putStrLn str >> putStrLn str

The function fail handles pattern match failures in do notation. It's an unfortunate technical necessity and doesn't really have anything to do with monads. You are advised not to call fail directly in your code.

Monad and Applicative[edit]

An important thing to note is that Applicative is a superclass of Monad.[2] That has a few consequences worth highlighting. First of all, every Monad is also a Functor and an Applicative, and so fmap, pure, (<*>) can all be used with monads. Secondly, actually writing a Monad instance also requires providing Functor and Applicative instances. We will discuss ways of doing that later in this chapter. Thirdly, if you have worked through the Prologue, the types and roles of return and (>>) should look familiar...

(*>) :: Applicative f => f a -> f b -> f b
(>>) :: Monad m => m a -> m b -> m b

pure :: Applicative f => a -> f a
return :: Monad m => a -> m a

The only difference between the types of (*>) and (>>) is that the constraint changes from Applicative to Monad. In fact, that is the only difference between the methods: if you are dealing with a Monad you can always replace (*>) and (>>), and vice-versa. The same goes for pure/return – in fact, it is not even necessary to implement return if there is an independent definition of pure in the Applicative instance, as return = pure is provided as a default definition of return.

Notions of Computation[edit]

We have seen how (>>=) and return are very handy for removing boilerplate code that crops up when using Maybe. That, however, is not enough to justify why monads matter so much. Our next step towards that will be rewriting the two-grandfathers function in a quite different-looking style: using do notation with explicit braces and semicolons. Depending on your experience with other programming languages, you may find this very suggestive:

    bothGrandfathers p = do {
        dad <- father p;
        gf1 <- father dad;
        mom <- mother p;
        gf2 <- father mom;
        return (gf1, gf2);

If this looks like a code snippet of an imperative programming language to you, that's because it is. In particular, this imperative language supports exceptions : father and mother are functions that might fail to produce results, i.e. raise an exception, and when that happens, the whole do-block will fail, i.e. terminate with an exception.

In other words, the expression father p, which has type Maybe Person, is interpreted as a statement of an imperative language that returns a Person as result. This is true for all monads: a value of type M a is interpreted as a statement of an imperative language that returns a value of type a as result; and the semantics of this language are determined by the monad M.[3]

Under this interpretation, the bind operator (>>=) is simply a function version of the semicolon. Just like a let expression can be written as a function application,

   let x = foo in x + 3          corresponds to      (\x -> x + 3) foo

an assignment and semicolon can be written as the bind operator:

   x <- foo; return (x + 3)      corresponds to      foo >>= (\x -> return (x + 3))

The return function lifts a plain value a to M a, a statement of the imperative language corresponding to the monad M.


The fact that (>>=), and therefore Monad, lies behind the left arrows in do-blocks explains why we were not able to explain them in the Prologue, when we only knew about Functor and Applicative. Applicative would be enough to provide some, but not all, of the functionality of a do-block.

Different semantics of the imperative language correspond to different monads. The following table shows the classic selection that every Haskell programmer should know. If the idea behind monads is still unclear to you, studying each of the examples in the following chapters will not only give you a well-rounded toolbox but also help you understand the common abstraction behind them.

Monad Imperative Semantics Wikibook chapter
Maybe Exception (anonymous) Haskell/Understanding monads/Maybe
Error Exception (with error description) Haskell/Understanding monads/Error
State Global state Haskell/Understanding monads/State
IO Input/Output Haskell/Understanding monads/IO
[] (lists) Nondeterminism Haskell/Understanding monads/List
Reader Environment Haskell/Understanding monads/Reader
Writer Logger Haskell/Understanding monads/Writer

Furthermore, these different semantics need not occur in isolation. As we will see in a few chapters, it is possible to mix and match them by using monad transformers to combine the semantics of multiple monads in a single monad.

Monad Laws[edit]

In Haskell, every instance of the Monad type class (and thus all implementations of bind (>>=) and return) must obey the following three laws:

    m >>= return     =  m                        -- right unit
    return x >>= f   =  f x                      -- left unit

    (m >>= f) >>= g  =  m >>= (\x -> f x >>= g)  -- associativity

Return as neutral element[edit]

The behavior of return is specified by the left and right unit laws. They state that return doesn't perform any computation, it just collects values. For instance,

    maternalGrandfather p = do
            mom <- mother p
            gf  <- father mom
            return gf

is exactly the same as

    maternalGrandfather p = do
            mom  <- mother p
            father mom

by virtue of the right unit law.

Associativity of bind[edit]

The law of associativity makes sure that (like the semicolon) the bind operator (>>=) only cares about the order of computations, not about their nesting; e.g. we could have written bothGrandfathers like this (compare with our earliest version without do):

    bothGrandfathers p =
       (father p >>= father) >>=
           (\gf1 -> (mother p >>= father) >>=
               (\gf2 -> return (gf1,gf2) ))

The associativity of the then operator (>>) is a special case:

   (m >> n) >> o  =  m >> (n >> o)

Monadic composition[edit]

It is easier to picture the associativity of bind by recasting the law as

   (f >=> g) >=> h  =  f >=> (g >=> h)

where (>=>) is the monad composition operator, a close analogue of the function composition operator (.), only with flipped arguments. It is defined as:

   (>=>) :: Monad m => (a -> m b) -> (b -> m c) -> a -> m c
   f >=> g = \x -> f x >>= g

There is also (<=<), which is flipped version of (>=>). When using it, the order of composition matches that of (.), so that in (f <=< g) g comes first.[4]

Monads and Category Theory[edit]

Monads originally come from a branch of mathematics called Category Theory. Fortunately, it is entirely unnecessary to understand category theory in order to understand and use monads in Haskell. The definition of monads in Category Theory actually uses a slightly different presentation. Translated into Haskell, this presentation gives an alternative yet equivalent definition of a monad which can give us some additional insight.[5]

So far, we have defined monads in terms of (>>=) and return. The alternative definition, instead, treats monads as functors with two additional combinators:

    fmap   :: (a -> b) -> M a -> M b  -- functor

    return :: a -> M a
    join   :: M (M a) -> M a

For the purposes of this discussion, we will use the functors-as-containers metaphor discussed in the chapter on the functor class. According to it, a functor M can be thought of as container, so that M a "contains" values of type a, with a corresponding mapping function, i.e. fmap, that allows functions to be applied to values inside it.

Under this interpretation, the functions behave as follows:

  • fmap applies a given function to every element in a container
  • return packages an element into a container,
  • join takes a container of containers and flattens it into a single container.

With these functions, the bind combinator can be defined as follows:

    m >>= g = join (fmap g m)

Likewise, we could give a definition of fmap and join in terms of (>>=) and return:

    fmap f x = x >>= (return . f)
    join x   = x >>= id

liftM and Friends[edit]

Earlier, we pointed out that every Monad is an Applicative, and therefore also a Functor. One of the consequences of that was return and (>>) being monad-only versions of pure and (*>) respectively. It doesn't stop there, though. For one, Control.Monad defines liftM, a function with a strangely familiar type signature...

liftM :: (Monad m) => (a1 -> r) -> m a1 -> m r

As you might suspect, liftM is merely fmap implemented with (>>=) and return, just as we have done in the previous section. liftM and fmap are therefore interchangeable.

Another Control.Monad function with an uncanny type is ap:

ap :: Monad m => m (a -> b) -> m a -> m b

Analogously to the other cases, ap is a monad-only version of (<*>).

There are quite a few more examples of Applicative functions that have versions specialised to Monad in Control.Monad and other base library modules. Their existence is primarily due to historical reasons: several years went by between the introductions of Monad and Applicative in Haskell, and it took an even longer time for Applicative to become a superclass of Monad, thus making usage of the specialised variants optional. While in principle there is little need for using the monad-only versions nowadays, in practice you will see return and (>>) all the time in other people's code – at this point, their usage is well established thanks to more than two decades of Haskell praxis without Applicative being a superclass of Monad.


Given that Applicative is a superclass of Monad, the most obvious way of implementing Monad begins by writing the Functor instance and then moving down the class hierarchy:

instance Functor Foo where
    fmap = -- etc.

instance Applicative Foo where
    pure = -- etc.
    (<*>) = -- etc.

instance Monad Foo where
    (>>=) = -- etc.

While following the next few chapters, you will likely want to write instances of Monad and try them out, be it to run the examples in the book or to do other experiments you might think of. However, writing the instances in the manner shown above requires implementing pure and (<*>), which is not a comfortable task at this point of the book as we haven't covered the Applicative laws yet (we will only do so at the applicative functors chapter). Fortunately, there is a workaround: implementing just (>>=) and return, thus providing a self-sufficient Monad instance, and then using liftM, ap and return to fill in the other instances:

instance Monad Foo where
    return = -- etc.
    (>>=) = -- etc.

instance Applicative Foo where
    pure = return
    (<*>) = ap

instance Functor Foo where
    fmap = liftM

The examples and exercises in this initial series of chapters about monads will not demand writing Applicative instances, and so you can use this workaround until we discuss Applicative in detail.


  1. This return function has nothing to do with the return keyword found in imperative languages like C or Java; don't conflate these two.
  2. This important superclass relationship was, thanks to historic accidents, only implemented quite recently (early 2015) in GHC (version 7.10). If you are using a GHC version older than that, this class constraint will not exist, and so some of the practical considerations we will make next will not apply.
  3. By "semantics", we mean what the language allows you to say. In the case of Maybe, the semantics allow us to express failure, as statements may fail to produce a result, leading to the statements that follow it being skipped.
  4. Of course, the functions in regular function composition are non-monadic functions whereas monadic composition takes only monadic functions.
  5. Deep into the Advanced Track, we will cover the theoretical side of the story in the chapter on Category Theory.