I'm guessing that there must be a better functional way of expressing the following:
def foo(i: Any) : Int
if (foo(a) < foo(b)) a else b
So in this example f == foo
and p == _ < _
. There's bound to be some masterful cleverness in scalaz for this! I can see that using BooleanW
I can write:
p(f(a), f(b)).option(a).getOrElse(b)
But I was sure that I would be able to write some code which only referred to a and b once. If this exists it must be on some combination of Function1W
and something else but scalaz is a bit of a mystery to me!
EDIT: I guess what I'm asking here is not "how do I write this?" but "What is the correct name and signature for such a function and does it have anything to do with FP stuff I do not yet understand like Kleisli, Comonad etc?"
Just in case it's not in Scalaz:
def x[T,R](f : T => R)(p : (R,R) => Boolean)(x : T*) =
x reduceLeft ((l, r) => if(p(f(l),f(r))) r else l)
scala> x(Math.pow(_ : Int,2))(_ < _)(-2, 0, 1)
res0: Int = -2
Alternative with some overhead but nicer syntax.
class MappedExpression[T,R](i : (T,T), m : (R,R)) {
def select(p : (R,R) => Boolean ) = if(p(m._1, m._2)) i._1 else i._2
}
class Expression[T](i : (T,T)){
def map[R](f: T => R) = new MappedExpression(i, (f(i._1), f(i._2)))
}
implicit def tupleTo[T](i : (T,T)) = new Expression(i)
scala> ("a", "bc") map (_.length) select (_ < _)
res0: java.lang.String = a
I don't think that Arrows or any other special type of computation can be useful here. Afterall, you're calculating with normal values and you can usually lift a pure computation that into the special type of computation (using arr
for arrows or return
for monads).
However, one very simple arrow is arr a b
is simply a function a -> b
. You could then use arrows to split your code into more primitive operations. However, there is probably no reason for doing that and it only makes your code more complicated.
You could for example lift the call to foo
so that it is done separately from the comparison. Here is a simiple definition of arrows in F# - it declares ***
and >>>
arrow combinators and also arr
for turning pure functions into arrows:
type Arr<'a, 'b> = Arr of ('a -> 'b)
let arr f = Arr f
let ( *** ) (Arr fa) (Arr fb) = Arr (fun (a, b) -> (fa a, fb b))
let ( >>> ) (Arr fa) (Arr fb) = Arr (fa >> fb)
Now you can write your code like this:
let calcFoo = arr <| fun a -> (a, foo a)
let compareVals = arr <| fun ((a, fa), (b, fb)) -> if fa < fb then a else b
(calcFoo *** calcFoo) >>> compareVals
The ***
combinator takes two inputs and runs the first and second specified function on the first, respectively second argument. >>>
then composes this arrow with the one that does comparison.
But as I said - there is probably no reason at all for writing this.
Here's the Arrow based solution, implemented with Scalaz. This requires trunk.
You don't get a huge win from using the arrow abstraction with plain old functions, but it is a good way to learn them before moving to Kleisli or Cokleisli arrows.
import scalaz._
import Scalaz._
def mod(n: Int)(x: Int) = x % n
def mod10 = mod(10) _
def first[A, B](pair: (A, B)): A = pair._1
def selectBy[A](p: (A, A))(f: (A, A) => Boolean): A = if (f.tupled(p)) p._1 else p._2
def selectByFirst[A, B](f: (A, A) => Boolean)(p: ((A, B), (A, B))): (A, B) =
selectBy(p)(f comap first) // comap adapts the input to f with function first.
val pair = (7, 16)
// Using the Function1 arrow to apply two functions to a single value, resulting in a Tuple2
((mod10 &&& identity) apply 16) assert_≟ (6, 16)
// Using the Function1 arrow to perform mod10 and identity respectively on the first and second element of a `Tuple2`.
val pairs = ((mod10 &&& identity) product) apply pair
pairs assert_≟ ((7, 7), (6, 16))
// Select the tuple with the smaller value in the first element.
selectByFirst[Int, Int](_ < _)(pairs)._2 assert_≟ 16
// Using the Function1 Arrow Category to compose the calculation of mod10 with the
// selection of desired element.
val calc = ((mod10 &&& identity) product) ⋙ selectByFirst[Int, Int](_ < _)
calc(pair)._2 assert_≟ 16
If you love us? You can donate to us via Paypal or buy me a coffee so we can maintain and grow! Thank you!
Donate Us With