# Haskell/Understanding monads

* Understanding monads
* Monads
* Prologue: IO, an applicative functor
* Understanding monads
* Maybe List
* do notation
* IO State
* Alternative and MonadPlus
* Monad transformers
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.

## Definition

A monad is defined by three things:
* a type constructor m;
* a function return;
* an operator (>>=) which is pronounced "bind".
The function and operator are methods of the Monad type class and have types
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:
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

To see the usefulness of (>>=) and the Maybe monad, consider the following example: Imagine a family database that provides two functions:
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):
Or consider a function that checks whether both grandfathers are in the database:
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:
With the help of lambda expressions and return, we can rewrite the two grandfathers function as well:
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 uncertainty about whether a value will be found.

### Type class

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:
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 has the default implementation
(>>) 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.
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

An important thing to note is that Applicative is a superclass of Monad. 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...
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

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:
If this looks like a code snippet in 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, raising an exception instead; when that happens, the whole do-block will fail, i.e. terminate with an exception (meaning, evaluate to Nothing, here).
In other words, the expression father p, which has type Maybe Person, is interpreted as a statement in an imperative language that returns a Person as the result, or fails.
This is true for all monads: a value of type M a is interpreted as a statement in an imperative language M that returns a value of type a as its result; the semantics of this language are determined by the monad M.
Under this interpretation, the then operator (>>) is simply an implementation of the semicolon, and (>>=) of the semicolon and assignment (binding) of the result of a previous computational step. Just like a let expression can be written as a function application,
an assignment and semicolon can be written with the bind operator:
In case of functions, & and id are trivial; in case of a monad, >>= and return are substantial.
The & operator combines two pure calculations, foo and id (x + 3), while creating a new binding for the variable x to hold foo's value, making x available to the second calculational step, id (x + 3).
The bind operator >>= combines two computational steps, foo and return (x + 3), in a manner particular to the monad M, while creating a new binding for the variable x to hold foo's result, making x available to the next computational step, return (x + 3). In the particular case of Maybe, if foo will fail to produce a result, the second step is skipped and the whole combined computation will fail right away as well.
The function return lifts a plain value a to M a, a statement in the imperative language M, which statement, when executed / run, will result in the value a without any additional effects particular to M. This is ensured by Monad Laws, foo >>= return === foo and return x >>= k === k x; see below.
Note
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 |
| 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 |
| State | Global state | Haskell/Understanding monads/State |
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

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

### Return as neutral element

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,
is exactly the same as
by virtue of the right unit law.

### Associativity of bind

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

#### Monadic composition

It is easier to picture the associativity of bind by recasting the law as
where (>=>) is the monad composition operator, a close analogue of the function composition operator (.), only with flipped arguments. It is defined as:
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.

## Monads and Category Theory

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 on the Monad class.
So far, we have defined monads in terms of (>>=) and return. The alternative definition, instead, treats monads as functors with two additional combinators:
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:
Likewise, we could give a definition of fmap and join in terms of (>>=) and return:

## liftM and Friends

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...
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:
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.
Note
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:
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:
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.

## Notes

* ↑ This return function has nothing to do with the return keyword found in imperative languages like C or Java; don't conflate these two.
* ↑ 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.
* ↑ 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.
* ↑ Of course, the functions in regular function composition are non-monadic functions whereas monadic composition takes only monadic functions.
* ↑ Deep into the Advanced Track, we will cover the theoretical side of the story in the chapter on Category Theory.
* Understanding monads
* 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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