Is it possible to work with a list of generic values with different type parameters in Scala? - scala

Question

I want to achieve the following:
There is a list of strings I need to process.
There are several different kinds of these processors, each of which knows which part of the string to read.
I need to work in 2 phases: first, processors need to see each input string to build processor-specific data; second, each input string is processed by each of the processors, and the resulting strings are combined into one.
It's easy to do it in a mutable way: there's a common base class for all processors, the different kinds of data they aggregate is encapsulated in the concrete implementations; the interface consists of just 2 functions --- "look at input string and build internal data" and "process input string using your internal data."
As I am writing it in Scala, I am wondering if there exists a pure functional approach. The problem is that now the base trait for these processors is parameterized by the type of their internal data, and there doesn't seem to be a way to have a list of processors of different kinds.
This problem can be demonstrated on a simpler case: say I'd stick with the mutable approach, but for some reason have parameterized the type of what the processor takes from the string:
trait F[V] {
def get(line: String) : V
def aggregate(value: V)
def process(value: V) : String
}
class F1 extends F[Int] // ...
class F2 extends F[HashMap[Int, Int]] // ...
for (s <- List("string1", "string2");
f <- List(new F1(), new F2())
{
f.aggregate(f.get(s)); // Whoops --- doesn't work
}
It doesn't work because f.get(s) returns Any. Looks like I need to express in Scala's type system that List(new F1(), new F2()) contains F[?] that are different but consistent in that if I take an element of that list, it has some concrete value of its type parameter, and f.get(s) is of that type, which should be accepted by f.aggregate().
In the end, I would like to have something like this (with omissions because I don't get how to do it):
trait F[D] {
def initData : D
def aggregate(line: String, data: D) : D
def process(line: String, data: D) : String
}
class F1 extends F[Int] // ...
class F2 extends F[HashMap[Int, Int]] // ...
// Phase 1
// datas --- List of f.initData, how to?
for (s <- List("string1", "string2")) {
for (f <- List(new F1(), new F2()) {
// let fdata be f's data
// update fdata with f.aggregate(s, fdata)
}
}
// Phase 2
for (s <- List("string1", "string2")) {
for (f <- List(new F1(), new F2()) {
// let fdata be f's data
// for all fs, concatenate f.process(s, fdata) into an output string
}
}
Questions:
Is this task solvable in pure functional way in Scala?
Is this task solvable in other functional languages?
This situation looks like quite a general one. Is there a name for it I could search?
Where is the best place to read about it, assuming little to no background on theory of types and functional programming languages?

Answer 1

Also, you may use abstract types instead of generics, so:
trait F {
type D
def initData: D
def aggregate(line: String, data: D): D
def process(line: String, data: D): String
}
class F1 extends F { type D = Int } // ...
class F2 extends F { type D = Map[Int, Int] } // ...
val strings = List("string1", "string2")
for (f <- List(new F1(), new F2())) {
val d = strings.foldLeft(f.initData) { (d, s) => f.aggregate(s, d) }
for (s <- strings)
f.process(s, d)
}
Don't sure, if I undrestood correct order of operation, but it may be a starting point.

Answer 2

Edit Just noticed, that my former solution was overly verbose, consing up a temporary data structure without any need.
I am not sure, what you mean with "purely functional". The following solution (if it is a solution to your problem) is "purely functional", as it has no side effects except the final println call in main.
Note, that the List[F[_]](...) is important, since otherwise, the compiler will infer a very specific internal type for the elements of the list, which doesn't go well with the aggregateAndProcess function.
trait F[D] {
type Data = D // Abbreviation for easier copy+paste below. Does not
// contribute to the actual solution otherwise
def initData: Data
def aggregate(line: String, data: Data) : Data
def process(line: String, aggData: Data): String
}
class F1 extends F[Int] {
def initData: Data = 1
def aggregate(line: String, data: Data) : Data = data + 1
def process(line: String, aggData: Data): String = line + "/F1" + aggData
}
class F2 extends F[Boolean] {
def initData: Data = false
def aggregate(line: String, data: Data) : Data = !data
def process(line: String, aggData: Data): String = line + "/F2" + aggData
}
object Main {
private def aggregateAndProcess[T](line: String, processor: F[T]): String =
processor.process(line, processor.aggregate(line, processor.initData))
def main(args: Array[String]) {
val r = for {
s <- List("a", "b")
d <- List[F[_]](new F1, new F2)
} yield
aggregateAndProcess(s, d)
println(r.toList)
}
}
Note, though, that I am still unsure as to what you actually want to accomplish. The F interface doesn't really specify, which information flows from which method into whatever location at what time, so: this is still a best-guess efford.