I am currently reading Learn You a Haskell for Great Good! and am stumbling on the explanation for the evaluation of a certain code block. I've read the explanations several times and am starting to doubt if even the author understands what this piece of code is doing.
ghci> (+) <$> (+3) <*> (*100) $ 5
508
An applicative functor applies a function in some context to a value in some context to get some result in some context. I have spent a few hours studying this code block and have come up with a few explanations for how this expression is evaluated, and none of them are satisfactory. I understand that (5+3)+(5*100) is 508, but the problem is getting to this expression. Does anyone have a clear explanation for this piece of code?
The other two answers have given the detail of how this is calculated - but I thought I might chime in with a more "intuitive" answer to explain how, without going through a detailed calculation, one can "see" that the result must be 508.
As you implied, every Applicative (in fact, even every Functor) can be viewed as a particular kind of "context" which holds values of a given type. As simple examples:
Maybe a is a context in which a value of type a might exist, but might not (usually the result of a computation which may fail for some reason)
[a] is a context which can hold zero or more values of type a, with no upper limit on the number - representing all possible outcomes of a particular computation
IO a is a context in which a value of type a is available as a result of interacting with "the outside world" in some way. (OK that one isn't so simple...)
And, relevant to this example:
r -> a is a context in which a value of type a is available, but its particular value is not yet known, because it depends on some (as yet unknown) value of type r.
The Applicative methods can be very well understood on the basis of values in such contexts. pure embeds an "ordinary value" in a "default context" in which it behaves as closely as possible in that context to a "context-free" one. I won't go through this for each of the 4 examples above (most of them are very obvious), but I will note that for functions, pure = const - that is, a "pure value" a is represented by the function which always produces a no matter what the source value.
Rather than dwell on how <*> can best be described using the "context" metaphor though, I want to dwell on the particular expression:
f <$> a <*> b
where f is a function between 2 "pure values" and a and b are "values in a context". This expression in fact has a synonym as a function: liftA2. Although using the liftA2 function is generally considered less idiomatic than the "applicative style" using <$> and <*>, the name emphasies that the idea is to "lift" a function on "ordinary values" to one on "values in a context". And when thought of like this, I think it is usually very intuitive what this does, given a particular "context" (ie. a particular Applicative instance).
So the expression:
(+) <$> a <*> b
for values a and b of type say f Int for an Applicative f, behaves as follows for different instances f:
if f = Maybe, then the result, if a and b are both Just values, is to add up the underlying values and wrap them in a Just. If either a or b is Nothing, then the whole expression is Nothing.
if f = [] (the list instance) then the above expression is a list containing all sums of the form a' + b' where a' is in a and b' is in b.
if f = IO, then the above expression is an IO action that performs all the I/O effects of a followed by those of b, and results in the sum of the Ints produced by those two actions.
So what, finally, does it do if f is the function instance? Since a and b are both functions describing how to get a given Int given an arbitrary (Int) input, it is natural that lifting the (+) function over them should be the function that, given an input, gets the result of both the a and b functions, and then adds the results.
And that is, of course, what it does - and the explicit route by which it does that has been very ably mapped out by the other answers. But the reason why it works out like that - indeed, the very reason we have the instance that f <*> g = \x -> f x (g x), which might otherwise seem rather arbitrary (although in actual fact it's one of the very few things, if not the only thing, that will type-check), is so that the instance matches the semantics of "values which depend on some as-yet-unknown other value, according to the given function". And in general, I would say it's often better to think "at a high level" like this than to be forced to go down to the low-level details of exactly how computations are performed. (Although I certainly don't want to downplay the importance of also being able to do the latter.)
[Actually, from a philosophical point of view, it might be more accurate to say that the definition is as it is just because it's the "natural" definition that type-checks, and that it's just happy coincidence that the instance then takes on such a nice "meaning". Mathematics is of course full of just such happy "coincidences" which turn out to have very deep reasons behind them.]
It is using the applicative instance for functions. Your code
(+) <$> (+3) <*> (*100) $ 5
is evaluated as
( (\a->\b->a+b) <$> (\c->c+3) <*> (\d->d*100) ) 5 -- f <$> g
( (\x -> (\a->\b->a+b) ((\c->c+3) x)) <*> (\d->d*100) ) 5 -- \x -> f (g x)
( (\x -> (\a->\b->a+b) (x+3)) <*> (\d->d*100) ) 5
( (\x -> \b -> (x+3)+b) <*> (\d->d*100) ) 5
( (\x->\b->(x+3)+b) <*> (\d->d*100) ) 5 -- f <*> g
(\y -> ((\x->\b->(x+3)+b) y) ((\d->d*100) y)) 5 -- \y -> (f y) (g y)
(\y -> (\b->(y+3)+b) (y*100)) 5
(\y -> (y+3)+(y*100)) 5
(5+3)+(5*100)
where <$> is fmap or just function composition ., and <*> is ap if you know how it behaves on monads.
Let us first take a look how fmap and (<*>) are defined for a function:
instance Functor ((->) r) where
fmap = (.)
instance Applicative ((->) a) where
pure = const
(<*>) f g x = f x (g x)
liftA2 q f g x = q (f x) (g x)
The expression we aim to evaluate is:
(+) <$> (+3) <*> (*100) $ 5
or more verbose:
((+) <$> (+3)) <*> (*100) $ 5
If we thus evaluate (<$>), which is an infix synonym for fmap, we thus see that this is equal to:
(+) . (+3)
so that means our expression is equivalent to:
((+) . (+3)) <*> (*100) $ 5
Next we can apply the sequential application. Here f is thus equal to (+) . (+3) and g is (*100). This thus means that we construct a function that looks like:
\x -> ((+) . (+3)) x ((*100) x)
We can now simplify this and rewrite this into:
\x -> ((+) (x+3)) ((*100) x)
and then rewrite it to:
\x -> (+) (x+3) ((*100) x)
We thus have constructed a function that looks like:
\x -> (x+3) + 100 * x
or simpler:
\x -> 101 * x + 3
If we then calculate:
(\x -> 101*x + 3) 5
then we of course obtain:
101 * 5 + 3
and thus:
505 + 3
which is the expected:
508
For any applicative,
a <$> b <*> c = liftA2 a b c
For functions,
liftA2 a b c x
= a (b x) (c x) -- by definition;
= (a . b) x (c x)
= ((a <$> b) <*> c) x
Thus
(+) <$> (+3) <*> (*100) $ 5
=
liftA2 (+) (+3) (*100) 5
=
(+) ((+3) 5) ((*100) 5)
=
(5+3) + (5*100)
(the long version of this answer follows.)
Pure math has no time. Pure Haskell has no time. Speaking in verbs ("applicative functor applies" etc.) can be confusing ("applies... when?...").
Instead, (<*>) is a combinator which combines a "computation" (denoted by an applicative functor) carrying a function (in the context of that type of computations) and a "computation" of the same type, carrying a value (in like context), into one combined "computation" that carries out the application of that function to that value (in such context).
"Computation" is used to contrast it with a pure Haskell "calculations" (after Philip Wadler's "Calculating is better than Scheming" paper, itself referring to David Turner's Kent Recursive Calculator language, one of predecessors of Miranda, the (main) predecessor of Haskell).
"Computations" might or might not be pure themselves, that's an orthogonal issue. But mainly what it means, is that "computations" embody a generalized function call protocol. They might "do" something in addition to / as part of / carrying out the application of a function to its argument. Or in types,
( $ ) :: (a -> b) -> a -> b
(<$>) :: (a -> b) -> f a -> f b
(<*>) :: f (a -> b) -> f a -> f b
(=<<) :: (a -> f b) -> f a -> f b
With functions, the context is application (another one), and to recover the value -- be it a function or an argument -- the application to a common argument is to be performed.
(bear with me, we're almost there).
The pattern a <$> b <*> c is also expressible as liftA2 a b c. And so, the "functions" applicative functor "computation" type is defined by
liftA2 h x y s = let x' = x s -- embellished application of h to x and y
y' = y s in -- in context of functions, or Reader
h x' y'
-- liftA2 h x y = let x' = x -- non-embellished application, or Identity
-- y' = y in
-- h x' y'
-- liftA2 h x y s = let (x',s') = x s -- embellished application of h to x and y
-- (y',s'') = y s' in -- in context of
-- (h x' y', s'') -- state-passing computations, or State
-- liftA2 h x y = let (x',w) = x -- embellished application of h to x and y
-- (y',w') = y in -- in context of
-- (h x' y', w++w') -- logging computations, or Writer
-- liftA2 h x y = [h x' y' | -- embellished application of h to x and y
-- x' <- x, -- in context of
-- y' <- y ] -- nondeterministic computations, or List
-- ( and for Monads we define `liftBind h x k =` and replace `y` with `k x'`
-- in the bodies of the above combinators; then liftA2 becomes liftBind: )
-- liftA2 :: (a -> b -> c) -> f a -> f b -> f c
-- liftBind :: (a -> b -> c) -> f a -> (a -> f b) -> f c
-- (>>=) = liftBind (\a b -> b) :: f a -> (a -> f b) -> f b
And in fact all the above snippets can be just written with ApplicativeDo as liftA2 h x y = do { x' <- x ; y' <- y ; pure (h x' y') } or even more intuitively as
liftA2 h x y = [h x' y' | x' <- x, y' <- y], with Monad Comprehensions, since all the above computation types are monads as well as applicative functors. This shows by the way that (<*>) = liftA2 ($), which one might find illuminating as well.
Indeed,
> :t let liftA2 h x y r = h (x r) (y r) in liftA2
:: (a -> b -> c) -> (t -> a) -> (t -> b) -> (t -> c)
> :t liftA2 -- the built-in one
liftA2 :: Applicative f => (a -> b -> c) -> f a -> f b -> f c
i.e. the types match when we take f a ~ (t -> a) ~ (->) t a, i.e. f ~ (->) t.
And so, we're already there:
(+) <$> (+3) <*> (*100) $ 5
=
liftA2 (+) (+3) (*100) 5
=
(+) ((+3) 5) ((*100) 5)
=
(+) (5+3) (5*100)
=
(5+3) + (5*100)
It's just how liftA2 is defined for this type, Applicative ((->) t) => ...:
instance Applicative ((->) t) where
pure x t = x
liftA2 h x y t = h (x t) (y t)
There's no need to define (<*>). The source code says:
Minimal complete definition
pure, ((<*>) | liftA2)
So now you've been wanting to ask for a long time, why is it that a <$> b <*> c is equivalent to liftA2 a b c?
The short answer is, it just is. One can be defined in terms of the other -- i.e. (<*>) can be defined via liftA2,
g <*> x = liftA2 id g x -- i.e. (<*>) = liftA2 id = liftA2 ($)
-- (g <*> x) t = liftA2 id g x t
-- = id (g t) (x t)
-- = (id . g) t (x t) -- = (id <$> g <*> x) t
-- = g t (x t)
(which is exactly as it is defined in the source),
and it is a law that every Applicative Functor must follow, that h <$> g = pure h <*> g.
Lastly,
liftA2 h g x == pure h <*> g <*> x
-- h g x == (h g) x
because <*> associates to the left: it is infixl 4 <*>.
I understand the definition of >>= in term of join
xs >>= f = join (fmap f xs)
which also tells us that fmap + join yields >>=
I was wondering if for the List monad it's possible to define without join, as we do for example for Maybe:
>>= m f = case m of
Nothing -> Nothing
Just x -> f x
Sure. The actual definition in GHC/Base.hs is in terms of the equivalent list comprehension:
instance Monad [] where
xs >>= f = [y | x <- xs, y <- f x]
Alternatively, you could try the following method of working it out from scratch from the type:
(>>=) :: [a] -> (a -> [b]) -> [b]
We need to handle two cases:
[] >>= f = ???
(x:xs) >>= f = ???
The first is easy. We have no elements of type a, so we can't apply f. The only thing we can do is return an empty list:
[] >>= f = []
For the second, x is a value of type a, so we can apply f giving us a value of f x of type [b]. That's the beginning of our list, and we can concatenate it with the rest of the list generated by a recursive call:
(x:xs) >>= f = f x ++ (xs >>= f)
After looking up the Control.Monad documentation, I'm confused about
this passage:
The above laws imply:
fmap f xs = xs >>= return . f
How do they imply that?
Control.Applicative says
As a consequence of these laws, the Functor instance for f will satisfy
fmap f x = pure f <*> x
The relationship between Applicative and Monad says
pure = return
(<*>) = ap
ap says
return f `ap` x1 `ap` ... `ap` xn
is equivalent to
liftMn f x1 x2 ... xn
Therefore
fmap f x = pure f <*> x
= return f `ap` x
= liftM f x
= do { v <- x; return (f v) }
= x >>= return . f
Functor instances are unique, in the sense that if F is a Functor and you have a function foobar :: (a -> b) -> F a -> F b such that foobar id = id (that is, it follows the first functor law) then foobar = fmap. Now, consider this function:
liftM :: Monad f => (a -> b) -> f a -> f b
liftM f xs = xs >>= return . f
What is liftM id xs, then?
liftM id xs
xs >>= return . id
-- id does nothing, so...
xs >>= return
-- By the second monad law...
xs
liftM id xs = xs; that is, liftM id = id. Therefore, liftM = fmap; or, in other words...
fmap f xs = xs >>= return . f
epheriment's answer, which routes through the Applicative laws, is also a valid way of reaching this conclusion.
Please excuse the terminology, my mind is still bending.
The tree:
data Ftree a = Empty | Leaf a | Branch ( Ftree a ) ( Ftree a )
deriving ( Show )
I have a few questions:
If Ftree could not be Empty, would it no longer be a Monoid since there is no identity value.
How would you implement mappend with this tree? Can you just arbitrarily graft two trees together willy nilly?
For binary search trees, would you have to introspect some of the elements in both trees to make sure the result of mappend is still a BST?
For the record, some other stuff Ftree could do here:
instance Functor Ftree where
fmap g Empty = Empty
fmap g ( Leaf a ) = Leaf ( g a )
fmap g ( Branch tl tr ) = Branch ( fmap g tl ) ( fmap g tr )
instance Monad Ftree where
return = Leaf
Empty >>= g = Empty
Leaf a >>= g = g a
Branch lt rt >>= g = Branch ( lt >>= g ) ( rt >>= g )
There are three answers to your question, one captious and one unhelpful and one abstract:
The captious answer
instance Monoid (Ftree a) where
mempty = Empty
mappend = Branch
This is an instance of the Monoid type class, but does not satisfy any of the required properties.
The unhelpful answer
What Monoid do you want? Just asking for a monoid instance without further information is like asking for a solution without giving the problem. Sometimes there is a natural monoid instance (e.g. for lists) or there is only one (e.g. for (), disregarding questions of definedness). I don’t think either is the case here.
BTW: There would be an interesting monoid instance if your tree would have data at internal nodes that combines two trees recursively...
The abstract answer
Since you gave a Monad (Ftree a) instance, there is a generic way to get a Monoid instance:
instance (Monoid a, Monad f) => Monoid (f a) where
mempty = return mempty
mappend f g = f >>= (\x -> (mappend x) `fmap` g)
Lets check if this is a Monoid. I use <> = mappend. We assume that the Monad laws hold (I did not check that for your definition). At this point, recall the Monad laws written in do-notation.
Our mappend, written in do-Notation, is:
mappend f g = do
x <- f
y <- g
return (f <> g)
So we can verify the monoid laws now:
Left identity
mappend mempty g
≡ -- Definition of mappend
do
x <- mempty
y <- g
return (x <> y)
≡ -- Definition of mempty
do
x <- return mempty
y <- g
return (x <> y)
≡ -- Monad law
do
y <- g
return (mempty <> y)
≡ -- Underlying monoid laws
do
y <- g
return y
≡ -- Monad law
g
Right identity
mappend f mempty
≡ -- Definition of mappend
do
x <- f
y <- mempty
return (x <> y)
≡ -- Monad law
do
x <- f
return (x <> mempty)
≡ -- Underlying monoid laws
do
x <- f
return x
≡ -- Monad law
f
And finally the important associativity law
mappend f (mappend g h)
≡ -- Definition of mappend
do
x <- f
y <- do
x' <- g
y' <- h
return (x' <> y')
return (x <> y)
≡ -- Monad law
do
x <- f
x' <- g
y' <- h
y <- return (x' <> y')
return (x <> y)
≡ -- Monad law
do
x <- f
x' <- g
y' <- h
return (x <> (x' <> y'))
≡ -- Underlying monoid law
do
x <- f
x' <- g
y' <- h
return ((x <> x') <> y')
≡ -- Monad law
do
x <- f
x' <- g
z <- return (x <> x')
y' <- h
return (z <> y')
≡ -- Monad law
do
z <- do
x <- f
x' <- g
return (x <> x')
y' <- h
return (z <> y')
≡ -- Definition of mappend
mappend (mappend f g) h
So for every (proper) Monad (and even for every applicative functor, as Jake McArthur pointed out on #haskell), there is a Monoid instance. It may or may not be the one that you are looking for.
From time to time I stumble over the problem that I want to express "please use the last argument twice", e.g. in order to write pointfree style or to avoid a lambda. E.g.
sqr x = x * x
could be written as
sqr = doubleArgs (*) where
doubleArgs f x = f x x
Or consider this slightly more complicated function (taken from this question):
ins x xs = zipWith (\ a b -> a ++ (x:b)) (inits xs) (tails xs)
I could write this code pointfree if there were a function like this:
ins x = dup (zipWith (\ a b -> a ++ (x:b))) inits tails where
dup f f1 f2 x = f (f1 x) (f2 x)
But as I can't find something like doubleArgs or dup in Hoogle, so I guess that I might miss a trick or idiom here.
From Control.Monad:
join :: (Monad m) -> m (m a) -> m a
join m = m >>= id
instance Monad ((->) r) where
return = const
m >>= f = \x -> f (m x) x
Expanding:
join :: (a -> a -> b) -> (a -> b)
join f = f >>= id
= \x -> id (f x) x
= \x -> f x x
So, yeah, Control.Monad.join.
Oh, and for your pointfree example, have you tried using applicative notation (from Control.Applicative):
ins x = zipWith (\a b -> a ++ (x:b)) <$> inits <*> tails
(I also don't know why people are so fond of a ++ (x:b) instead of a ++ [x] ++ b... it's not faster -- the inliner will take care of it -- and the latter is so much more symmetrical! Oh well)
What you call 'doubleArgs' is more often called dup - it is the W combinator (called warbler in To Mock a Mockingbird) - "the elementary duplicator".
What you call 'dup' is actually the 'starling-prime' combinator.
Haskell has a fairly small "combinator basis" see Data.Function, plus some Applicative and Monadic operations add more "standard" combinators by virtue of the function instances for Applicative and Monad (<*> from Applicative is the S - starling combinator for the functional instance, liftA2 & liftM2 are starling-prime). There doesn't seem to be much enthusiasm in the community for expanding Data.Function, so whilst combinators are good fun, pragmatically I've come to prefer long-hand in situations where a combinator is not directly available.
Here is another solution for the second part of my question: Arrows!
import Control.Arrow
ins x = inits &&& tails >>> second (map (x:)) >>> uncurry (zipWith (++))
The &&& ("fanout") distributes an argument to two functions and returns the pair of the results. >>> ("and then") reverses the function application order, which allows to have a chain of operations from left to right. second works only on the second part of a pair. Of course you need an uncurry at the end to feed the pair in a function expecting two arguments.