Say I've got a function taking one argument
def fun(x: Int) = x
Based on that, I want to generate a new function with the same calling convention, but that'll apply some transformation to its arguments before delegating to the original function. For that, I could
def wrap_fun(f: (Int) => Int) = (x: Int) => f(x * 2)
wrap_fun(fun)(2) // 4
How might one go about doing the same thing, except to functions of any arity that only have the part of the arguments to apply the transformation to in common?
def fun1(x: Int, y: Int) = x
def fun2(x: Int, foo: Map[Int,Str], bar: Seq[Seq[Int]]) = x
wrap_fun(fun1)(2, 4) // 4
wrap_fun(fun2)(2, Map(), Seq()) // 4
How would a wrap_fun
definition making the above invocations work look like?
=> is syntactic sugar for creating instances of functions. Recall that every function in scala is an instance of a class. For example, the type Int => String , is equivalent to the type Function1[Int,String] i.e. a function that takes an argument of type Int and returns a String .
One reason to use higher-order functions is to reduce redundant code. Let's say you wanted some methods that could raise someone's salaries by various factors. Without creating a higher-order function, it might look something like this: Scala 2.
Difference between Scala Functions & Methods: Function is a object which can be stored in a variable. But a method always belongs to a class which has a name, signature bytecode etc. Basically, you can say a method is a function which is a member of some object.
Scala - Functions with Named Arguments Named arguments allow you to pass arguments to a function in a different order. The syntax is simply that each argument is preceded by a parameter name and an equals sign. Try the following program, it is a simple example to show the functions with named arguments.
This can be done in fairly straightforwardly using shapeless's facilities for abstracting over function arity,
import shapeless._
import HList._
import Functions._
def wrap_fun[F, T <: HList, R](f : F)
(implicit
hl : FnHListerAux[F, (Int :: T) => R],
unhl : FnUnHListerAux[(Int :: T) => R, F]) =
((x : Int :: T) => f.hlisted(x.head*2 :: x.tail)).unhlisted
val f1 = wrap_fun(fun _)
val f2 = wrap_fun(fun1 _)
val f3 = wrap_fun(fun2 _)
Sample REPL session,
scala> f1(2)
res0: Int = 4
scala> f2(2, 4)
res1: Int = 4
scala> f3(2, Map(), Seq())
res2: Int = 4
Note that you can't apply the wrapped function immediately (as in the question) rather than via an assigned val (as I've done above) because the explicit argument list of the wrapped function will be confused with the implicit argument list of wrap_fun
. The closest we can get to the form in the question is to explicitly name the apply
method as below,
scala> wrap_fun(fun _).apply(2)
res3: Int = 4
scala> wrap_fun(fun1 _).apply(2, 4)
res4: Int = 4
scala> wrap_fun(fun2 _).apply(2, Map(), Seq())
res5: Int = 4
Here the explicit mention of apply
syntactically marks off the first application (of wrap_fun
along with its implicit argument list) from the second application (of the transformed function with its explicit argument list).
As usual in Scala, there's yet another way to achieve what you want to do.
Here is a take based on currying of the first argument together with the compose
of Function1
:
def fun1(x : Int)(y : Int) = x
def fun2(x : Int)(foo : Map[Int, String], bar : Seq[Seq[Int]]) = x
def modify(x : Int) = 2*x
The resulting types as REPL shows you will be:
fun1: (x: Int)(y: Int)Int
fun2: (x: Int)(foo: Map[Int,String], bar: Seq[Seq[Int]])Int
modify: (x: Int)Int
And instead of wrapping the functions fun1
and fun2
, you compose
them, as technically, they are now both Function1
objects. This allows you to make calls like the following:
(fun1 _ compose modify)(2)(5)
(fun2 _ compose modify)(2)(Map(), Seq())
Both of which will return 4. Granted, the syntax is not that nice, given that you have to add the _
to distinguish fun1
's application from the function object itself (on which you want to call the compose
method in this case).
So Luigi's argument that it is impossible in general remains valid, but if you are free to curry your functions you can do it in this nice way.
Since functions taking different numbers of arguments are different, unrelated types, you cannot do this generically. trait Function1 [-T1, +R] extends AnyRef
and nothing else. You will need a separate method for each arity.
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