This is a good (and fairly simple) application for the kind of generic programming techniques exemplified in shapeless.
Given your definition,
object CombinatorParser extends RegexParsers {
lazy val a = "a"
lazy val b = "b"
lazy val c = "c"
lazy val content = a ~ b ~ c
}
We can recursively define a type class that will flatten it's results as follows,
import CombinatorParser._
First we define a trait which (abstractly) flattens an arbitrary match M to a List[String],
trait Flatten[M] extends (M => List[String]) {
def apply(m : M) : List[String]
}
Then we provide type class instances for all the shapes of M that we're interested in: in this case, String, A ~ B and ParseResult[T] (where A, B and T are all types for which there are Flatten instances),
// Flatten instance for String
implicit def flattenString = new Flatten[String] {
def apply(m : String) = List(m)
}
// Flatten instance for `A ~ B`. Requires Flatten instances for `A` and `B`.
implicit def flattenPattern[A, B]
(implicit flattenA : Flatten[A], flattenB : Flatten[B]) =
new Flatten[A ~ B] {
def apply(m : A ~ B) = m match {
case a ~ b => flattenA(a) ::: flattenB(b)
}
}
// Flatten instance for ParseResult[T]. Requires a Flatten instance for T.
implicit def flattenParseResult[T]
(implicit flattenT : Flatten[T]) = new Flatten[ParseResult[T]] {
def apply(p : ParseResult[T]) = (p map flattenT) getOrElse Nil
}
Finally we can define a convenience function to simplify applying Flatten instances to parse results,
def flatten[P](p : P)(implicit flatten : Flatten[P]) = flatten(p)
And now we're ready to go,
val testChar = "abc"
val output = parseAll(content, testChar)
println(output) // ((a~b)~c) but I want List(a, b, c)
val flattenedOutput = flatten(output)
println(flattenedOutput) // List(a, b, c)