I looked at past discussion but could not see why any of the answers are actually correct.
Applicative
<*> :: f (a -> b) -> f a -> f b
Monad
(>>=) :: m a -> (a -> m b) -> m b
So if I get it right, the claim is that >>= cannot be written by only assuming the existence of <*>
Well, let's assume I have <*>.
And I want to create >>=.
So I have f a.
I have f (a -> b).
Now when you look at it, f (a -> b) can be written as (a -> b) (if something is a function of x, y , z - then it's also a function of x, y).
So from the existence of <*> we get (a -> b) -> f a -> f b which again can be written as ((a -> b) -> f a) -> f b, which can be written as (a -> f b).
So we have f a, we have (a -> f b), and we know that <*> results in f b, so we get:
f a -> (a -> f b) -> f b
which is a monad.
Actually, in a more intuitive language: when implementing <*>, I extract (a -> b) out of f(a -> b), I extract a out of f a, and then I apply (a -> b) on a and get b which I wrap with f to finally get f b.
So I do almost the same to create >>=. After applying (a -> b) on a and getting b, do one more step and wrap it with f, so I return f b, hence I know I have a function (a -> f b).
Now when you look at it, f(a -> b) can be written as (a -> b)
No. It can't. Your intuition is (dangerously) far off at this point. That's like saying a hammer is perfect for driving screws in, since it already works for a nail*. You can't simply drop f here, it's part of the type**.
Instead, let's get the facts straight. An Applicative has three associated functions, counting Functor's fmap:
fmap :: Functor f => (a -> b) -> f a -> f b
pure :: Applicative f => a -> f a
(<*>) :: Applicative f => f (a -> b) -> f a -> f b
Here's another fact: you can define bind ((>>=)) in terms of join and vice versa:
join :: Monad m => m (m a) -> m a
join k = k >>= id
(>>=) :: Monad m => m a -> (a -> m b) -> m b
k >>= f = join (fmap f k)
are the implementations of join and bind you provided here part of the Monad definition, or are only join and bind signatures part of the Monad definition? [...] So now I ask myself why would they bother.
Those aren't the official definitions of course, since they would never terminate. You have to define (>>=) for your type if you want to make it a a monad:
instance Monad YourType where
k >>= f = ...
Also, your join definition uses id which is not in the Monad interface, why is it mathematically legitimate?
First of all, id :: a -> a is defined for any type. Second, the mathematical definition of a monad is actually via join. So it's "more"*** legitimate. But most important of all, we can define the monad laws in terms of join (exercise).
If we created join via Applicative, we could also create bind. If we cannot create join via Applicative methods, neither can we derive bind. And join's type actually makes it obvious that we cannot derive it from Applicative:
join :: Monad m => m (m a) -> m a
-- ^ ^ ^
Join is able to drop one of the m layers. Let's check whether it's possible to do the same in the other methods:
fmap :: Functor f => (a -> b) -> f a -> f b
^ ^
0 here 1 here
pure :: Applicative f => a -> f a
^ | ^
0 here | 1 here
(<*>) :: Applicative f => f (a -> b) -> f a -> f b
^ ^
1 here 1 here
The answer is no: none of the tools we're given by Applicative enables us collapse multiple m's into a single one. And that's also what is written in the Typeclassopedia right after the cited paragraph in the other question:
To see the increased power of Monad from a different point of view, let’s see what happens if we try to implement (>>=) in terms of fmap, pure, and (<*>). We are given a value x of type m a, and a function k of type a -> m b, so the only thing we can do is apply k to x. We can’t apply it directly, of course; we have to use fmap to lift it over the m. But what is the type of fmap k? Well, it’s m a -> m (m b). So after we apply it to x, we are left with something of type m (m b)—but now we are stuck; what we really want is an m b, but there’s no way to get there from here. We can add m’s using pure, but we have no way to collapse multiple m’s into one.
Note that join doesn't make it possible to get rid of m completely, that would be a total extraction, and—depending on some other functions—a feature of a comonad. Either way, make sure that you don't let your intuition go astray; trust and use the types.
* That comparison is a little bit bad, because you could actually try to dive a screw in with a hammer into a piece of wood. So think of a plastic screw, a rubber hammer and a carbon steel plate you want to drive the nail in. Good luck.
** Well, you can drop it, but then the type changes drastically.
*** Given that (>>=) and join are equivalent of power and any (>>=) using formula can be transformed to one only using join, they are of course both mathematical sound.
Now when you look at it, f (a -> b) can be written as (a -> b)
Everyone has already contributed explaining that this is not a fact. Let me prove it to you.
If we genuinely had what you state then we should be able to write a function
expose :: f (a -> b) -> (a -> b)
Moreover, for any concrete data type we like, call it F, we ought to be able to write
expose_F :: F (a -> b) -> (a -> b)
expose_F = expose
Let's worry only about writing expose_F since if we can show that expose_F cannot be written for some F then we have surely shown that expose cannot be written.
Let me provide us a test F. It will certainly be non-intuitive feeling as I'm intending to use it to break intuition, but I'm happy to confirm all day long that there is nothing funny at all about
data F a = F
Indeed, it is a Functor
instance Functor F where
fmap _ F = F
and an Applicative for that matter
instance Applicative F where
pure _ = F
F <*> F = F
even a Monad
instance Monad F where
return _ = F
F >>= _ = F
You can verify yourself that all of these typecheck. There's nothing wrong at all about F.
So what's just right about, F? Why did I choose it? Well F is interesting in that values of F a fail to contain anything related at all to a within them. Often people like to talk about data types (or Functors) as "containers" or "boxes". F forces us to remember that in a certain sense a box that's 0 inches deep is still a box. [0]
So surely we cannot write
expose_F :: F (a -> b) -> (a -> b)
There are a number of ways of proving this. The easiest is to appeal to my supposition that you, for instance, believe that there is no coerce function. But, if we had expose_F there would be!
coerce :: a -> b
coerce = expose_F F
More specifically, let me introduce another pathological type (which I again assure you is totally fine)
data Void
There are zero constructors of Void and we like to say therefore that Void has no members. It cannot be made to exist. But we can make one with expose_F.
void :: Void
void = expose_F F ()
In Haskell we're not technically sound enough to execute the above proofs. If you dislike the way I talk about impossibility then you can conjure up whatever types you like with a convenient infinite loop, casual call to
error "Madness rides the star-wind... claws and teeth sharpened on centuries of corpses... dripping death astride a bacchanale of bats from nigh-black ruins of buried temples of Belial..."
or perhaps an unassuming undefined. But these are all on the path of madness.
There is no expose_F and therefore there is no expose.
[0] And to be completely clear, thinking of data types as boxes at all is often flawed. Instances of Functor tend to be "box-like", but here's another interesting data type which is difficult to think of as a box
data Unbox a = Unbox (a -> Bool)
unless perhaps you consider Unbox a to be a box containing a Bool and a negative a or something like that. Perhaps an IOU a.
Related
This is the common implementation for kleisli composition:
kleisli :: Monad m => (a -> m b) -> (b -> m c) -> a -> m c
kleisli = \f g x -> f x >>= g
Why doesn't it expect a value in a monadic context instead? I'm sure there is a good reason. I just haven't managed to see it.
kleisli' :: Monad m => (a -> m b) -> (b -> m c) -> m a -> m c
kleisli' = \f g x -> x >>= f >>= g
The type seems better composable and return can be used in case we have only a pure value on the call site.
Kleisli composition is actually one of the easiest ways to answer the commonly asked question: what are monads useful for?
One of the most useful things we can do with ordinary functions is to compose them. Given f :: a -> b and g :: b -> c, we can perform first f and then g on the result, giving us g . f :: a -> c.
That's fantastic as long as we only have to work with "ordinary" functions. But as soon as we start programming in the "real world", we're likely to run into situations where we can't keep on using such functions, if we wish our language to remain pure and referentially transparent. Indeed, in such situations, other languages which are less principled than Haskell abandon any pretence of being pure. Consider these everyday situations:
our function f might sometimes fail to return a value. In many other languages this would be denoted by returning null, but you can't then feed it into g. (You could of course adapt g in order to cope with null inputs, but this will quickly get repetitive.)
In Haskell we don't have nulls, we have the Maybe type constructor to explicitly signal that there might be no value. This would mean f needs to have type a -> Maybe b. g will have type b -> Maybe c for the same reason. But in doing this we have lost the ability to compose the two functions, as we can't directly feed a value of type Maybe b to one which expects an input of type b.
the result of f might depend on some side effects (eg input from the user, or the result of a database query). This is no problem in impure languages, but in Haskell, to keep purity, we have to implement this in the form of a function of type a -> IO b. Once again, g will end up with the same form, b -> IO c, and we have lost the ability to naively compose the two functions.
I'm sure you can see where this is going. In both cases (and more could easily be provided, one for each monad) we have had to replace a simple function of type a -> b with one of type a -> m b in order to account for a particular type of "side effect" - or, if you prefer, some particular kind of "context" which applies to the function result. And in so doing we lose the ability to compose two functions, which we had in the "side effect free" world.
What monads are really for is to overcome this, and let us recover a form of composition for such "impure functions". That of course is exactly what Kleisli composition gives us, a composition of functions of the form a -> m b which satisfies exactly the properties we expect of function composition (namely associativity, and an "identity function" on each type, which here is return :: a -> m a).
Your suggestion of a "not-quite-composition", of type (a -> m b) -> (b -> m c) -> (m a -> m c) simply wouldn't be useful that often, as the resulting function needs a monadic value as its input, when the main way monadic values arise in practice is as outputs. You can still do this when you need to though, just by taking the "proper" Kleisli composition, and feeding the monadic value to it via >>=.
A Kleisli arrow from a to b is defined as a function a -> m b. Let's notate it a ~> b (leaving the m assumed). What does it mean to compose two of these arrows? It should have this type:
(<=<) :: (b ~> c) -> (a ~> b) -> (a ~> c)
Now, if we expand that:
(<=<) :: (b -> m c) -> (a -> m b) -> (a -> m c)
And there you have it. It looks like you are looking at the flipped version (>=>) but it's the same idea.
These operators are defined in Control.Monad.
There is also a more formal definition of Kleisli arrows in the standard library.
newtype Kleisli m a b = Kleisli { runKleisli :: a -> m b }
It comes with a Category instance that implements this composition as the (.) operator (but you have to futz around with newtype wrapping).
Looking at the Haskell documentation, lifting seems to be basically a generalization of fmap, allowing for the mapping of functions with more than one argument.
The Wikipedia article on lifting gives a different view however, defining a "lift" in terms of a morphism in a category, and how it relates to the other objects and morphisms in the category (I won't give the details here). I suppose that that could be relevant to the Haskell situation if we are considering Cat (the category of categories, thus making our morphisms functors), but I can't see how this category-theoretic notion of a lift relates the the one in Haskell based on the linked article, if it does at all.
If the two concepts aren't really related, and just have a similar name, are the lifts (category theory) used in Haskell at all?
Lifts, and the dual notion of extensions, are absolutely used in Haskell, perhaps most prominently in the guise of comonadic extend and monadic bind. (Confusingly, extend is a lift, not an extension.) A comonad w's extend lets us take a function w a -> b and lift it along extract :: w b -> b to get a map w a -> w b. In ASCII art, given the diagram
w b
|
V
w a ---> b
where the vertical arrow is extract, extend gives us a diagonal arrow (making the diagram commute):
-> w b
/ |
/ V
w a ---> b
More familiar to most Haskellers is the dual notion of bind (>>=) for a monad m. Given a function a -> m b and return :: a -> m a, we can "extend" our function along return to get a function m a -> m b. In ASCII art:
a ---> m b
|
V
m a
gives us
a ---> m b
| __A
V /
m a
(That A is an arrowhead!)
So yes, extend could have been called lift, and bind could have been called extend. As for Haskell's lifts, I have no idea why they're called that!
EDIT: Actually, I think that again, Haskell's lifts are actually extensions. If f is applicative, and we have a function a -> b -> c, we can compose this function with pure :: c -> f c to get a function a -> b -> f c. Uncurrying, this is the same as a function (a, b) -> f c. Now we can also hit (a, b) with pure to get a function (a, b) -> f (a, b). Now, by fmaping fst and snd, we get a functions f (a, b) -> f a and f (a, b) -> f b, which we can combine to get a function f (a, b) -> (f a, f b). Composing with our pure from before gives (a, b) -> (f a, f b). Phew! So to recap, we have the ASCII art diagram
(a, b) ---> f c
|
V
(f a, f b)
Now liftA2 gives us a function (f a, f b) -> f c, which I won't draw because I'm sick of making terrible diagrams. But the point is, the diagram commutes, so liftA2 actually gives us an extension of the horizontal arrow along the vertical one.
"Lifting" comes up many times in functional programming, not only in fmap but in many other contexts. Examples of "liftings" include:
fmap :: (a -> b) -> F a -> F b where F is a functor
cmap :: (b -> a) -> F a -> F b where F is a contrafunctor
bind :: (a -> M b) -> M a -> M b where M is a monad
ap :: F (a -> b) -> F a -> F b where F is an applicative functor
point :: (_ -> a) -> _ -> F a where F is a pointed functor
filtMap :: (a -> Maybe b) -> F a -> F b where F is a filterable functor
extend :: (M a -> b) -> M a -> M b where M is a comonad
Other examples include applicative contrafunctor, filterable contrafunctor, and co-pointed functor.
All these type signatures are similar in one way: they map one kind of function between a and b into another kind of function between a and b.
In these different cases, the function types are not simply a -> b but have some kind of "twisted" types: e.g. a -> M b or F (a -> b) or M a -> b or F a -> F b and so on. However, each time the laws are very similar: twisted function types need to have identity and composition laws, and twisted composition needs to be associative.
For example, for applicative functors, we need to be able to compose functions of type F (a -> b). So we need to define a special "twisted" identity function (pure id :: F (a -> a) ) and a "twisted" composition operation, call it apcomp, with type signature F (a -> b) -> F (b -> c) -> F (a -> c). This operation needs to have identity and associativity laws. The ap operation needs to have identity and composition laws ("twisted identity maps to twisted identity" and "twisted composition maps to twisted composition").
Once we go through all these examples and derive the laws, we can prove that the laws turn out to be the same in all cases, if we formulate the laws via the "twisted" operations.
This is because we can formulate all these operations as functors in the sense of category theory. For example, for the applicative functor, we define two categories: the F-applicative category (objects a, b, ..., morphisms F(a -> b)) and the F-lifted category (objects F a, F b, ..., morphisms F a -> F b). A functor between these two categories requires us to have a lifting of morphisms, ap :: F(a -> b) -> F a -> F b. The laws of ap are completely equivalent to the standard laws of that functor.
Similar arguments hold for other typeclasses. We need to define categories, morphisms, composition operations, identity morphisms, and functors in each case. Once we verify that the laws hold, we will see that each of these typeclasses has an associated pair of categories and a functor between them, such that the laws of the typeclass are equivalent to the laws of these categories and the functor.
What have we gained? We have formulated the laws of many typeclasses in the same way (as the laws of categories and functors). This is a great economy of thought: we don't need to memorize all these laws each time; we can just memorize which categories and which functors need to be written down for each typeclass, as long as the methods of the typeclass can be reduced to some kind of "twisted lifting".
In this way, we can say that "liftings" are important and provide an application of category theory in functional programming.
I have made a presentation about this, https://www.youtube.com/watch?v=Zau8CxsfxOo and I'm writing a new free book where all derivations will be shown. https://github.com/winitzki/sofp
Let's say that we have two monadic functions:
f :: a -> m b
g :: b -> m c
h :: a -> m c
The bind function is defined as
(>>=) :: m a -> (a -> m b) -> m b
My question is why can not we do something like below. Declare a function which would take a monadic value and returns another monadic value?
f :: a -> m b
g :: m b -> m c
h :: a -> m c
The bind function is defined as
(>>=) :: m a -> (ma -> m b) -> m b
What is in the haskell that restricts a function from taking a monadic value as it's argument?
EDIT: I think I did not make my question clear. The point is, when you are composing functions using bind operator, why is that the second argument for bind operator is a function which takes non-monadic value (b)? Why can't it take a monadic value (mb) and give back mc . Is it that, when you are dealing with monads and the function you would compose will always have the following type.
f :: a -> m b
g :: b -> m c
h :: a -> m c
and h = f 'compose' g
I am trying to learn monads and this is something I am not able to understand.
A key ability of Monad is to "look inside" the m a type and see an a; but a key restriction of Monad is that it must be possible for monads to be "inescapable," i.e., the Monad typeclass operations should not be sufficient to write a function of type Monad m => m a -> a. (>>=) :: Monad m => m a -> (a -> m b) -> m b gives you exactly this ability.
But there's more than one way to achieve that. The Monad class could be defined like this:
class Functor f where
fmap :: (a -> b) -> f a -> f b
class Functor f => Monad m where
return :: a -> m a
join :: m (m a) -> m a
You ask why could we not have a Monad m => m a -> (m a -> m b) -> m b function. Well, given f :: a -> b, fmap f :: ma -> mb is basically that. But fmap by itself doesn't give you the ability to "look inside" a Monad m => m a yet not be able to escape from it. However join and fmap together give you that ability. (>>=) can be written generically with fmap and join:
(>>=) :: Monad m => m a -> (a -> m b) -> m b
ma >>= f = join (fmap f ma)
In fact this is a common trick for defining a Monad instance when you're having trouble coming up with a definition for (>>=)—write the join function for your would-be monad, then use the generic definition of (>>=).
Well, that answers the "does it have to be the way it is" part of the question with a "no." But, why is it the way it is?
I can't speak for the designers of Haskell, but I like to think of it this way: in Haskell monadic programming, the basic building blocks are actions like these:
getLine :: IO String
putStrLn :: String -> IO ()
More generally, these basic building blocks have types that look like Monad m => m a, Monad m => a -> m b, Monad m => a -> b -> m c, ..., Monad m => a -> b -> ... -> m z. People informally call these actions. Monad m => m a is a no-argument action, Monad m => a -> m b is a one-argument action, and so on.
Well, (>>=) :: Monad m => m a -> (a -> m b) -> m b is basically the simplest function that "connects" two actions. getLine >>= putStrLn is the action that first executes getLine, and then executes putStrLn passing it the result that was obtained from executing getLine. If you had fmap and join and not >>= you'd have to write this:
join (fmap putStrLn getLine)
Even more generally, (>>=) embodies a notion much like a "pipeline" of actions, and as such is the more useful operator for using monads as a kind of programming language.
Final thing: make sure you are aware of the Control.Monad module. While return and (>>=) are the basic functions for monads, there's endless other more high-level functions that you can define using those two, and that module gathers a few dozen of the more common ones. Your code should not be forced into a straitjacket by (>>=); it's a crucial building block that's useful both on its own and as a component for larger building blocks.
why can not we do something like below. Declare a function which would take a monadic value and returns another monadic value?
f :: a -> m b
g :: m b -> m c
h :: a -> m c
Am I to understand that you wish to write the following?
compose :: (a -> m b) -> (m b -> m c) -> (a -> m c)
compose f g = h where
h = ???
It turns out that this is just regular function composition, but with the arguments in the opposite order
(.) :: (y -> z) -> (x -> y) -> (x -> z)
(g . f) = \x -> g (f x)
Let's choose to specialize (.) with the types x = a, y = m b, and z = m c
(.) :: (m b -> m c) -> (a -> m b) -> (a -> m c)
Now flip the order of the inputs, and you get the desired compose function
compose :: (a -> m b) -> (m b -> m c) -> (a -> m c)
compose = flip (.)
Notice that we haven't even mentioned monads anywhere here. This works perfectly well for any type constructor m, whether it is a monad or not.
Now let's consider your other question. Suppose we want to write the following:
composeM :: (a -> m b) -> (b -> m c) -> (a -> m c)
Stop. Hoogle time. Hoogling for that type signature, we find there is an exact match! It is >=> from Control.Monad, but notice that for this function, m must be a monad.
Now the question is why. What makes this composition different from the other one such that this one requires m to be a Monad, while the other does not? Well, the answer to that question lies at the heart of understanding what the Monad abstraction is all about, so I'll leave a more detailed answer to the various internet resources that speak about the subject. Suffice it to say that there is no way to write composeM without knowing something about m. Go ahead, try it. You just can't write it without some additional knowledge about what m is, and the additional knowledge necessary to write this function just happens to be that m has the structure of a Monad.
Let me paraphrase your question a little bit:
why can't don't we use functions of type g :: m a -> m b with Monads?
The answer is, we do already, with Functors. There's nothing especially "monadic" about fmap f :: Functor m => m a -> m b where f :: a -> b. Monads are Functors; we get such functions just by using good old fmap:
class Functor f a where
fmap :: (a -> b) -> f a -> f b
If you have two functions f :: m a -> m b and a monadic value x :: m a, you can simply apply f x. You don't need any special monadic operator for that, just function application. But a function such as f can never "see" a value of type a.
Monadic composition of functions is much stronger concept and functions of type a -> m b are the core of monadic computations. If you have a monadic value x :: m a, you cannot "get into it" to retrieve some value of type a. But, if you have a function f :: a -> m b that operates on values of type a, you can compose the value with the function using >>= to get x >>= f :: m b. The point is, f "sees" a value of type a and can work with it (but it cannot return it, it can only return another monadic value). This is the benefit of >>= and each monad is required to provide its proper implementation.
To compare the two concepts:
If you have g :: m a -> m b, you can compose it with return to get g . return :: a -> m b (and then work with >>=), but
not vice versa. In general there is no way of creating a function of type m a -> m b from a function of type a -> m b.
So composing functions of types like a -> m b is a strictly stronger concept than composing functions of types like m a -> m b.
For example: The list monad represents computations that can give a variable number of answers, including 0 answers (you can view it as non-deterministic computations). The key elements of computing within list monad are functions of type a -> [b]. They take some input and produce a variable number of answers. Composition of these functions takes the results from the first one, applies the second function to each of the results, and merges it into a single list of all possible answers.
Functions of type [a] -> [b] would be different: They'd represent computations that take multiple inputs and produce multiple answers. They can be combined too, but we get something less strong than the original concept.
Perhaps even more distinctive example is the IO monad. If you call getChar :: IO Char and used only functions of type IO a -> IO b, you'd never be able to work with the character that was read. But >>= allows you to combine such a value with a function of type a -> IO b that can "see" the character and do something with it.
As others have pointed out, there is nothing that restricts a function to take a monadic value as argument. The bind function itself takes one, but not the function that is given to bind.
I think you can make this understandable to yourself with the "Monad is a Container" metaphor. A good example for this is Maybe. While we know how to unwrap a value from the Maybe conatiner, we do not know it for every monad, and in some monads (like IO) it is entirely impossible.
The idea is now that the Monad does this behind the scenes in a way you don't have to know about. For example, you indeed need to work with a value that was returned in the IO monad, but you cannot unwrap it, hence the function that does this needs to be in the IO monad itself.
I like to think of a monad as a recipe for constructing a program with a specific context. The power that a monad provides is the ability to, at any stage within your constructed program, branch depending upon the previous value. The usual >>= function was chosen as being the most generally useful interface to this branching ability.
As an example, the Maybe monad provides a program that may fail at some stage (the context is the failure state). Consider this psuedo-Haskell example:
-- take a computation that produces an Int. If the current Int is even, add 1.
incrIfEven :: Monad m => m Int -> m Int
incrIfEven anInt =
let ourInt = currentStateOf anInt
in if even ourInt then return (ourInt+1) else return ourInt
In order to branch based on the current result of a computation, we need to be able to access that current result. The above psuedo-code would work if we had access to currentStateOf :: m a -> a, but that isn't generally possible with monads. Instead we write our decision to branch as a function of type a -> m b. Since the a isn't in a monad in this function, we can treat it like a regular value, which is much easier to work with.
incrIfEvenReal :: Monad m => m Int -> m Int
incrIfEvenReal anInt = anInt >>= branch
where branch ourInt = if even ourInt then return (ourInt+1) else return ourInt
So the type of >>= is really for ease of programming, but there are a few alternatives that are sometimes more useful. Notably the function Control.Monad.join, which when combined with fmap gives exactly the same power as >>= (either can be defined in terms of the other).
The reason (>>=)'s second argument does not take a monad as input is because there is no need to bind such a function at all. Just apply it:
m :: m a
f :: a -> m b
g :: m b -> m c
h :: c -> m b
(g (m >>= f)) >>= h
You don't need (>>=) for g at all.
The function can take a monadic value if it wants. But it is not forced to do so.
Consider the following contrived definitions, using the list monad and functions from Data.Char:
m :: [[Int]]
m = [[71,72,73], [107,106,105,104]]
f :: [Int] -> [Char]
f mx = do
g <- [toUpper, id, toLower]
x <- mx
return (g $ chr x)
You can certainly run m >>= f; the result will have type [Char].
(It's important here that m :: [[Int]] and not m :: [Int]. >>= always "strips off" one monadic layer from its first argument. If you don't want that to happen, do f m instead of m >>= f.)
As others have mentioned, nothing restricts such functions from being written.
There is, in fact, a large family of functions of type :: m a -> (m a -> m b) -> m b:
f :: Monad m => Int -> m a -> (m a -> m b) -> m b
f n m mf = replicateM_ n m >>= mf m
where
f 0 m mf = mf m
f 1 m mf = m >> mf m
f 2 m mf = m >> m >> mf m
... etc. ...
(Note the base case: when n is 0, it's simply normal functional application.)
But what does this function do? It performs a monadic action multiple times, finally throwing away all the results, and returning the application of mf to m.
Useful sometimes, but hardly generally useful, especially compared to >>=.
A quick Hoogle search doesn't turn up any results; perhaps a telling result.
A Foldable instance is likely to be some sort of container, and so is likely to be a Functor as well. Indeed, this says
A Foldable type is also a container (although the class does not technically require Functor, interesting Foldables are all Functors).
So is there an example of a Foldable which is not naturally a Functor or a Traversable? (which perhaps the Haskell wiki page missed :-) )
Here's a fully parametric example:
data Weird a = Weird a (a -> a)
instance Foldable Weird where
foldMap f (Weird a b) = f $ b a
Weird is not a Functor because a occurs in a negative position.
Here's an easy example: Data.Set.Set. See for yourself.
The reason for this should be apparent if you examine the types of the specialized fold and map functions defined for Set:
foldr :: (a -> b -> b) -> b -> Set a -> b
map :: (Ord a, Ord b) => (a -> b) -> Set a -> Set b
Because the data structure relies on a binary search tree internally, an Ord constraint is needed for elements. Functor instances must allow any element type, so that's not viable, alas.
Folding, on the other hand, always destroys the tree to produce the summary value, so there's no need to sort the intermediate results of the fold. Even if the fold is actually building a new Set, the responsibility for satisfying the Ord constraint lies on the accumulation function passed to the fold, not the fold itself.
The same will probably apply to any container type that's not fully parametric. And given the utility of Data.Set, this makes the remark you quoted about "interesting" Foldables seem a bit suspect, I think!
Reading Beautiful folding
I realized that any Foldable can be made a Functor by wrapping it into
data Store f a b = Store (f a) (a -> b)
with a simple smart contructor:
store :: f a -> Store f a a
store x = Store x id
(This is just a variant of the Store comonad data type.)
Now we can define
instance Functor (Store f a) where
fmap f (Store x g) = Store x (f . g)
instance (F.Foldable f) => F.Foldable (Store f a) where
foldr f z (Store x g) = F.foldr (f . g) z x
This way, we can make both Data.Set.Set and Sjoerd Visscher's Weird a functor. (However, since the structure doesn't memoize its values, repeatedly folding over it could be very inefficient, if the function that we used in fmap is complex.)
Update: This also provides an example of a structure that is a functor, foldable but not traversable. To make Store traversable, we would need to make (->) r traversable. So we'd need to implement
sequenceA :: Applicative f => (r -> (f a)) -> f (r -> a)
Let's take Either b for f. Then we'd need to implement
sequenceA' :: (r -> Either b a) -> Either b (r -> a)
Clearly, there is no such function (you can verify with Djinn). So we can neither realize sequenceA.
I've written code with the following pattern several times recently, and was wondering if there was a shorter way to write it.
foo :: IO String
foo = do
x <- getLine
putStrLn x >> return x
To make things a little cleaner, I wrote this function (though I'm not sure it's an appropriate name):
constM :: (Monad m) => (a -> m b) -> a -> m a
constM f a = f a >> return a
I can then make foo like this:
foo = getLine >>= constM putStrLn
Does a function/idiom like this already exist? And if not, what's a better name for my constM?
Well, let's consider the ways that something like this could be simplified. A non-monadic version would I guess look something like const' f a = const a (f a), which is clearly equivalent to flip const with a more specific type. With the monadic version, however, the result of f a can do arbitrary things to the non-parametric structure of the functor (i.e., what are often called "side effects"), including things that depend on the value of a. What this tells us is that, despite pretending like we're discarding the result of f a, we're actually doing nothing of the sort. Returning a unchanged as the parametric part of the functor is far less essential, and we could replace return with something else and still have a conceptually similar function.
So the first thing we can conclude is that it can be seen as a special case of a function like the following:
doBoth :: (Monad m) => (a -> m b) -> (a -> m c) -> a -> m c
doBoth f g a = f a >> g a
From here, there are two different ways to look for an underlying structure of some sort.
One perspective is to recognize the pattern of splitting a single argument among multiple functions, then recombining the results. This is the concept embodied by the Applicative/Monad instances for functions, like so:
doBoth :: (Monad m) => (a -> m b) -> (a -> m c) -> a -> m c
doBoth f g = (>>) <$> f <*> g
...or, if you prefer:
doBoth :: (Monad m) => (a -> m b) -> (a -> m c) -> a -> m c
doBoth = liftA2 (>>)
Of course, liftA2 is equivalent to liftM2 so you might wonder if lifting an operation on monads into another monad has something to do with monad transformers; in general the relationship there is awkward, but in this case it works easily, giving something like this:
doBoth :: (Monad m) => ReaderT a m b -> ReaderT a m c -> ReaderT a m c
doBoth = (>>)
...modulo appropriate wrapping and such, of course. To specialize back to your original version, the original use of return now needs to be something with type ReaderT a m a, which shouldn't be too hard to recognize as the ask function for reader monads.
The other perspective is to recognize that functions with types like (Monad m) => a -> m b can be composed directly, much like pure functions. The function (<=<) :: Monad m => (b -> m c) -> (a -> m b) -> (a -> m c) gives a direct equivalent to function composition (.) :: (b -> c) -> (a -> b) -> (a -> c), or you can instead make use of Control.Category and the newtype wrapper Kleisli to work with the same thing in a generic way.
We still need to split the argument, however, so what we really need here is a "branching" composition, which Category alone doesn't have; by using Control.Arrow as well we get (&&&), letting us rewrite the function as follows:
doBoth :: (Monad m) => Kleisli m a b -> Kleisli m a c -> Kleisli m a (b, c)
doBoth f g = f &&& g
Since we don't care about the result of the first Kleisli arrow, only its side effects, we can discard that half of the tuple in the obvious way:
doBoth :: (Monad m) => Kleisli m a b -> Kleisli m a c -> Kleisli m a c
doBoth f g = f &&& g >>> arr snd
Which gets us back to the generic form. Specializing to your original, the return now becomes simply id:
constKleisli :: (Monad m) => Kleisli m a b -> Kleisli m a a
constKleisli f = f &&& id >>> arr snd
Since regular functions are also Arrows, the definition above works there as well if you generalize the type signature. However, it may be enlightening to expand the definition that results for pure functions and simplify as follows:
\f x -> (f &&& id >>> arr snd) x
\f x -> (snd . (\y -> (f y, id y))) x
\f x -> (\y -> snd (f y, y)) x
\f x -> (\y -> y) x
\f x -> x.
So we're back to flip const, as expected!
In short, your function is some variation on either (>>) or flip const, but in a way that relies on the differences--the former using both a ReaderT environment and the (>>) of the underlying monad, the latter using the implicit side-effects of the specific Arrow and the expectation that Arrow side effects happen in a particular order. Because of these details, there's not likely to be any generalization or simplification available. In some sense, the definition you're using is exactly as simple as it needs to be, which is why the alternate definitions I gave are longer and/or involve some amount of wrapping and unwrapping.
A function like this would be a natural addition to a "monad utility library" of some sort. While Control.Monad provides some combinators along those lines, it's far from exhaustive, and I could neither find nor recall any variation on this function in the standard libraries. I would not be at all surprised to find it in one or more utility libraries on hackage, however.
Having mostly dispensed with the question of existence, I can't really offer much guidance on naming beyond what you can take from the discussion above about related concepts.
As a final aside, note also that your function has no control flow choices based on the result of a monadic expression, since executing the expressions no matter what is the main goal. Having a computational structure independent of the parametric content (i.e., the stuff of type a in Monad m => m a) is usually a sign that you don't actually need a full Monad, and could get by with the more general notion of Applicative.
Hmm, I don't think constM is appropriate here.
map :: (a -> b) -> [a] -> [b]
mapM :: (Monad m) => (a -> m b) -> [a] -> m b
const :: b -> a -> b
So perhaps:
constM :: (Monad m) => b -> m a -> m b
constM b m = m >> return b
The function you are M-ing seems to be:
f :: (a -> b) -> a -> a
Which has no choice but to ignore its first argument. So this function does not have much to say purely.
I see it as a way to, hmm, observe a value with a side effect. observe, effect, sideEffect may be decent names. observe is my favorite, but maybe just because it is catchy, not because it is clear.
I don't really have a clue this exactly allready exists, but you see this a lot in parser-generators only with different names (for example to get the thing inside brackets) - there it's normaly some kind of operator (>>. and .>> in fparsec for example) for this. To really give a name I would maybe call it ignore?
There's interact:
http://hackage.haskell.org/packages/archive/haskell98/latest/doc/html/Prelude.html#v:interact
It's not quite what you're asking for, but it's similar.