Abstract Types vs Parameter

This topic (and the next) are intended to discuss abstract types. A class/trait with an abstract type is quite similar to a class/trait type parameter. For example:

1. trait C[A] {
2.   def get : A
3.   def doit(a:A):A
4. }
6. trait C2 {
7.   type A
8.   def get : A
9.   def doit(a:A):A
10. }

Both implementations have similar properties. However they are NOT the same. At first I thought that I could used them inter-changeably. However, consider the following examples:

1. //compiles
2. def p(c:C[Int]) = c.doit(c.get)
4. // doesn't compile
5. def p2(c:C2) = c.doit(c.get)

So why doesn't p2 compile? Because it returns A. From the signature of p2 it is impossible to know what p2 returns. There are several ways to fix this problem. One make the method return Unit:

1. // compiles because the internals of C2 does not leak out
2. def p(c:C2):Unit = c.doit(c.get)

Another fix would be to change doit to return Unit or an explicit return value like Int

1. trait C2 {
2.   type A
3.   def get : A
4.   def doit(a:A):Int
5. }
7. // compiles correctly
8. def p(c:C2) = c.doit(c.get)

A second difference between parameterized types and types with abstract type values is illustrated below:

1. trait C2 {
2.    type A
3.    def get : A
4. }
6. scala> var c : C2 = new C2 { 
7.      | type A = Int
8.      | def get = 3
9.      | }
10. c: C2 = $anon$1@11a40fff
12. // what is the type of result if at compile time the
13. // value of c is not known
14. scala> var result = c.get
15. result: C2#A = 3
17. scala> c = new C2 {      
18.      |    type A = String
19.      |    def get = "hi"
20.      | }
21. c: C2 = $anon$1@5f154718
23. // crazy eh :) the variable can be anything but does not
24. // have type Any so you cannot assign arbitrary values
25. scala> result = c.get
26. result: C2#A = hi
28. scala> result.isInstanceOf[String]
29. res0: Boolean = true
31. // while the dynamic type of result is a string the
32. // static type is not so you cannot assign a string to result
33. scala> result = "4"
34. < console> :8: error: type mismatch;
35.  found   : java.lang.String("4")
36.  required: C2#A
37.        result = "4"
38.                 ^

The obvious question is what use are abstract types. I don't claim to know them all but the main point is that they do not expose the internal implementation details to the world. The famous cake pattern is one such example usage of abstract types.

I read the following as well (wish I could remember where):

Abstract types are good when extending and there will be concrete subclasses. Param type good for when a type is useful without extension but can handle several types.

A simpler example is examined here. It is loosely based on a real world usecase.
The example below is contrived so that it is smaller than the actual usecase, so consider the design and not the fact that the example could be easier done with other examples. In the real scenario this design reduced the lines of duplicated code from around 500 to 10.

The example below shows how a Traversable like object can be created from InputStreams and Readers. The important aspect is that the type signature of Foreach does not leak information about the implementation. Users of a Foreach object don't care whether it is backed onto an InputStream or Reader. They just care about the type of object contained.

I am leaving this already long post here. The next post will investigate different ways you can get in trouble trying to implement using abstract types.

1. import java.io.{InputStream, Reader, ByteArrayInputStream, StringReader}
2. import java.net.URL
4. object Foreach {
5.   def fromStream(s: => InputStream) = new Foreach[Int] {
6.     type I = InputStream
7.     def source = new Source {
8.       def in = s
9.       def next(_in : InputStream) = _in.read match {
10.         case -1 => None
11.         case i => Some(i)
12.       }
13.     }
14.   }
15.   
16.   def fromReader(s: => Reader) = new Foreach[Char] {
17.     type I = Reader
18.     def source = new Source {
19.       def in = s
20.       def next(_in : Reader) = _in.read match {
21.         case -1 => None
22.         case i => Some(i.toChar)
23.       }
24.     }
25.   }
26.   
27.   
28.   def fromInputAndFunction[A](s: => InputStream, f: Int => A) = new Foreach[A] {
29.     type I = InputStream
30.     def source = new Source {
31.       def in = s
32.       def next(_in : InputStream) = _in.read match {
33.         case -1 => None
34.         case i => Some(f(i))
35.       }
36.     }
37.   }
38.   
39.   
40. }
42. trait Foreach[A] {
43.   type I <: java.io.Closeable
44.   trait Source {
45.     def in : I
46.     def next(in : I) : Option[A]
47.   }
48.   def source : Source
49.   
50.   def foreach[U](f : A => U) : Unit = {
51.     val s = source.in
52.     try {
53.       def processNext : Unit = source.next(s) match {
54.         case None => 
55.           ()
56.         case Some(value) => 
57.           f(value)
58.           processNext
59.       }
60.       
61.       processNext
62.     } finally {
63.       // correctly handle exceptions
64.       s.close
65.     }
66.   }
67. }
69. object Test {
70.   def main(args : Array[String]) = {
71.     val data = "Hello World"
72.     val bytes = data.toArray.map { _.toByte }
73.     import Foreach._
74.     fromStream(new ByteArrayInputStream(bytes)).foreach {a => print(a.toChar)}
75.     
76.     println
78.     fromReader(new StringReader(data)) foreach print
79.     
80.     println
81.     
82.     fromInputAndFunction(new ByteArrayInputStream(bytes), i => i.toChar) foreach print
83.     
84.     println
85.   }
86. }