This was a good excuse for me to look into Shapeless, something I always wanted to do at some point :)
$ git clone git@github.com:milessabin/shapeless.git
...
$ cd shapeless
(1)
Shapeless provides some abstractions over arity, and especially the representation as heterogeneous list (HList
). A function of arbitrary arity can be seen as FnHList
(a function that takes an HList
as argument).
$ sbt shapeless-core/console
scala> import shapeless._
import shapeless._
scala> def isFunction[A](fun: A)(implicit fnh: FnHLister[A]) {}
isFunction: [A](fun: A)(implicit fnh: shapeless.FnHLister[A])Unit
scala> isFunction(math.sqrt _)
scala> isFunction(math.random _)
(2)
Now let's require that the function returns a Double
:
scala> def isFunReturningDouble[A](fun: A)(implicit fnh: FnHLister[A] { type Result = Double }) {}
isFunReturningDouble: [A](fun: A)(implicit fnh: shapeless.FnHLister[A]{type Result = Double})Unit
scala> isFunReturningDouble(math.sqrt _)
scala> isFunReturningDouble(math.signum _)
<console>:12: error: could not find implicit value for parameter fnh: shapeless.FnHLister[Int => Int]{type Result = Double}
isFunReturningDouble(math.signum _)
^
(3)
The LUBConstraint
type class can witness the upper bound of the argument list:
scala> def isValidFun[A, B <: HList](fun: A)(implicit fnh: FnHLister[A] { type Result = Double; type Args = B }, lub: LUBConstraint[B, Double]) {}
isValidFun: [A, B <: shapeless.HList](fun: A)(implicit fnh: shapeless.FnHLister[A]{type Result = Double; type Args = B}, implicit lub: shapeless.LUBConstraint[B,Double])Unit
scala> isValidFun(math.random _)
scala> isValidFun((i: Int) => i.toDouble)
<console>:12: error: could not find implicit value for parameter lub: shapeless.LUBConstraint[B,Double]
isValidFun((i: Int) => i.toDouble)
^
(4)
Now we still need to extract the arity somehow. On the type level this would be Length
which is provided for HList
. To get a runtime value, another type class ToInt
is needed.
Here is the final function:
import shapeless._
def doubleFunArity[A, B <: HList, C <: Nat](fun: A)(implicit
fnh: FnHLister[A] { type Result = Double; type Args = B },
lub: LUBConstraint[B, Double],
len: Length[B] { type Out = C },
res: ToInt[C]
): Int = res()
Test:
scala> doubleFunArity(math.sqrt _)
res15: Int = 1
scala> doubleFunArity(math.random _)
res16: Int = 0
scala> val g: (Double, Double) => Double = math.max _
g: (Double, Double) => Double = <function2>
scala> doubleFunArity(g)
res17: Int = 2
Note that unfortunately many math
operations are overloaded, and without strong type constraint, Scala will not give you the Double
version automatically, but will use the Int
version for some reason:
scala> math.max _
res18: (Int, Int) => Int = <function2>
So I need the indirection math.max _: ((Double, Double) => Double)
to make this work.
Not saying that this is the best way to do it in your concrete case, but I think it was a fun exploration.
g
takes an n-tuple, but your exampleMath.max
is an n-ary function, not aFunction1
that takes a tuple. You should clarify that. – 0__