How to apply implicit conversions between tuples?

Question

I'm experimenting with currying/tupled as an alternative means to pass parameters to a function. In this journey, I'm facing some type difficulties.

I'd like to use implicit conversions to transform a tuple of parameters to the target type. This is what I expect:

Given (REPL example):

case class Cont(value:String) // a simplified container class
val paramTuple = (Cont("One"),Cont("2"))
def operate(s:String, i:Int): String = s+i // my target operation
implicit def contToString(c:Cont): String = c.value
implicit def contToInt(c:Cont): Int = c.value.toInt

//This works - obviously

operate(paramTuple._1, paramTuple._2)
>res4: String = One2

//This is what I want, but doesn't work

(operate _).tupled(params)
<console>:14: error: type mismatch;
 found   : (Cont, Cont)
 required: (String, Int)

Q1: Why the tuple conversion doesn't work? (I'm expecting that an answer to that goes in the lines of: What's required is an implicit conversion between Tuple2[Cont,Cont] to Tuple2[String,Int] but that does not scale up)

Q2: What are my options to have such conversion working? Keep in mind that I'd like to have a solution for an N-tuple, so defining a specific Tuple2 to Tuple2 is not really a good solution in this case. AFAIK, the magnet pattern works similarly, so I hope there's a way.

Answer 1

Q1: Why the tuple conversion doesn't work? (I'm expecting that an answer to that goes in the lines of: What's required is an implicit conversion between Tuple2[Cont,Cont] to Tuple2[String,Int] but that does not scale up)

Yes, you've got that right.

What are my options to have such conversion working?

You could do it this way:

implicit def liftImplicitTuple2[A, B, A1, B1](tuple: (A, B))
  (implicit f1: A => A1, f2: B => B1): (A1, B1) =
  (f1(tuple._1), f2(tuple._2))

implicit def liftImplicitTuple3[A, B, C, A1, B1, C1](tuple: (A, B, C))
  (implicit f1: A => A1, f2: B => B1, f3: C => C1): (A1, B1, C1) =
  (f1(tuple._1), f2(tuple._2), f3(tuple._3))

// etc for tuples as large as you need