I have a function that expects a variable number of parameters of the same type, which sounds like the textbook use case for varargs:
def myFunc[A](as: A*) = ???
The problem I have is that myFunc cannot accept empty parameter lists. There's a trivial way of enforcing that at runtime:
def myFunc[A](as: A*) = {
require(as.nonEmpty)
???
}
The problem with that is that it happens at runtime, as opposed to compile time. I would like the compiler to reject myFunc().
One possible solution would be:
def myFunc[A](head: A, tail: A*) = ???
And this works when myFunc is called with inline arguments, but I'd like users of my library to be able to pass in a List[A], which this syntax makes very awkward.
I could try to have both:
def myFunc[A](head: A, tail: A*) = myFunc(head +: tail)
def myFunc[A](as: A*) = ???
But we're right back where we started: there's now a way of calling myFunc with an empty parameter list.
I'm aware of scalaz's NonEmptyList, but in as much as possible, I'd like to stay with stlib types.
Is there a way to achieve what I have in mind with just the standard library, or do I need to accept some runtime error handling for something that really feels like the compiler should be able to deal with?
What about something like this?
scala> :paste
// Entering paste mode (ctrl-D to finish)
def myFunc()(implicit ev: Nothing) = ???
def myFunc[A](as: A*) = println(as)
// Exiting paste mode, now interpreting.
myFunc: ()(implicit ev: Nothing)Nothing <and> [A](as: A*)Unit
myFunc: ()(implicit ev: Nothing)Nothing <and> [A](as: A*)Unit
scala> myFunc(3)
WrappedArray(3)
scala> myFunc(List(3): _*)
List(3)
scala> myFunc()
<console>:13: error: could not find implicit value for parameter ev: Nothing
myFunc()
^
scala>
Replacing Nothing with a class that has an appropriate implicitNotFound annotation should allow for a sensible error message.
Let's start out with what I think is your base requirement: the ability to define myFunc in some way such that the following occurs at the Scala console when a user provides literals. Then maybe if we can achieve that, we can try to go for varargs.
myFunc(List(1)) // no problem
myFunc(List[Int]()) // compile error!
Moreover, we don't want to have to force users either to split a list into a head and tail or have them convert to a ::.
Well when we're given literals, since we have access to the syntax used to construct the value, we can use macros to verify that a list is non-empty. Moreover, there's already a library that'll do it for us, namely refined!
scala> refineMV[NonEmpty]("Hello")
res2: String Refined NonEmpty = Hello
scala> refineMV[NonEmpty]("")
<console>:39: error: Predicate isEmpty() did not fail.
refineMV[NonEmpty]("")
^
Unfortunately this is still problematic in your case, because you'll need to put refineMV into the body of your function at which point the literal syntactically disappears and macro magic fails.
Okay what about the general case that doesn't rely on syntax?
// Can we do this?
val xs = getListOfIntsFromStdin() // Pretend this function exists
myFunc(xs) // compile error if xs is empty
Well now we're up against a wall; there's no way a compile time error can happen here since the code has already been compiled and yet clearly xs could be empty. We'll have to deal with this case at runtime, either in a type-safe manner with Option and the like or with something like runtime exceptions. But maybe we can do a little better than just throw our hands up in the air. There's two possible paths of improvement.
Somehow provide implicit evidence that xs is nonempty. If the compiler can find that evidence, then great! If not, it's on the user to provide it somehow at runtime.
Track the provenance of xs through your program and statically prove that it must be non-empty. If this cannot be proved, either error out at compile time or somehow force the user to handle the empty case.
Once again, unfortunately this is problematic.
I strongly suspect this is not possible (but this is still only a suspicion and I would be happy to be proved wrong). The reason is that ultimately implicit resolution is type-directed which means that Scala gets the ability to do type-level computation on types, but Scala has no mechanism that I know of to do type-level computation on values (i.e. dependent typing). We require the latter here because List(1, 2, 3) and List[Int]() are indistinguishable at the type level.
Now you're in SMT solver land, which does have some efforts in other languages (hello Liquid Haskell!). Sadly I don't know of any such efforts in Scala (and I imagine it would be a harder task to do in Scala).
The bottom line is that when it comes to error checking there is no free lunch. A compiler can't magically make error handling go away (although it can tell you when you don't strictly need it), the best it can do is yell at you when you forget to handle certain classes of errors, which is itself very valuable. To underscore the no free lunch point, let's return to a language that does have dependent types (Idris) and see how it handles non-empty values of List and the prototypical function that breaks on empty lists, List.head.
First we get a compile error on empty lists
Idris> List.head []
(input):1:11:When checking argument ok to function Prelude.List.head:
Can't find a value of type
NonEmpty []
Good, what about non-empty lists, even if they're obfuscated by a couple of leaps?
Idris> :let x = 5
-- Below is equivalent to
-- val y = identity(Some(x).getOrElse(3))
Idris> :let y = maybe 3 id (Just x)
-- Idris makes a distinction between Natural numbers and Integers
-- Disregarding the Integer to Nat conversion, this is
-- val z = Stream.continually(2).take(y)
Idris> :let z = Stream.take (fromIntegerNat y) (Stream.repeat 2)
Idris> List.head z
2 : Integer
It somehow works! What if we really don't let the Idris compiler know anything about the number we pass along and instead get one at runtime from the user? We blow up with a truly gargantuan error message that starts with When checking argument ok to function Prelude.List.head: Can't find a value of type NonEmpty...
import Data.String
generateN1s : Nat -> List Int
generateN1s x = Stream.take x (Stream.repeat 1)
parseOr0 : String -> Nat
parseOr0 str = case parseInteger str of
Nothing => 0
Just x => fromIntegerNat x
z : IO Int
z = do
x <- getLine
let someNum = parseOr0 x
let firstElem = List.head $ generateN1s someNum -- Compile error here
pure firstElem
Hmmm... well what's the type signature of List.head?
Idris> :t List.head
-- {auto ...} is roughly the same as Scala's implicit
head : (l : List a) -> {auto ok : NonEmpty l} -> a
Ah so we just need to provide a NonEmpty.
data NonEmpty : (xs : List a) -> Type where
IsNonEmpty : NonEmpty (x :: xs)
Oh a ::. And we're back at square one.
Use scala.collection.immutable.::
:: is the cons of the list
defined in std lib
::[A](head: A, tail: List[A])
use :: to define myFunc
def myFunc[A](list: ::[A]): Int = 1
def myFunc[A](head: A, tail: A*): Int = myFunc(::(head, tail.toList))
Scala REPL
scala> def myFunc[A](list: ::[A]): Int = 1
myFunc: [A](list: scala.collection.immutable.::[A])Int
scala> def myFunc[A](head: A, tail: A*): Int = myFunc(::(head, tail.toList))
myFunc: [A](head: A, tail: A*)Int
Related
In the Scala Odersky book, he has an example explaining partial functions of page 295. It starts with this function:
val second: List[Int] => Int = {
case x :: y :: _ => y
}
So the above function will succeed if you pass it a three element list but not an empty list.
second(List(5,6,7))
works but not
second(List())
The above will throw a MatchError: List
Here is the part that is confusing to me. Odersky writes:
If you want to check whether a partial function is defined, you must first tell the compiler that you know you are working with partial functions.
Why would I want to check whether a partial function is defined. What is a partial function? Is it a function that only applies to some values?
The type List[Int] => Int includes all functions from lists of integers to integers, whether or not the functions are partial. The type that only includes partial functions from lists of integers to integers is written PartialFunction[List[Int], Int].
So the above function returns a function of type List[Int] => Int, I see that, but why do we need to change this function to type PartialFunction[List[Int], Int]?
Here is the function redefined:
val second: PartialFunction[List [Int], Int] = {
case x :: y :: _ => y
}
I don't really get it. What is the benefit? Why do we want to check whether a partial function is defined? What does that even mean?
A partial function is any function, which takes only a single argument, that is defined (i.e. valid) only for a certain range of its argument's values. For example, Math.asin is defined only for argument values in the range [-1.0, 1.0] and is undefined for values outside of that range - so it is a partial function. For example, if we call Math.asin(5.0), we get NaN returned, meaning that the function is not defined for that argument.
Note that a partial function doesn't necessarily have to throw an exception; it just needs to do something other than return a valid value.
A key principle of functional programming is referential transparency (RT), meaning that we should be able to replace an expression (such as a function call) with the value of that expression, without changing the meaning of the program. (For more on this topic, I highly recommend that you read Functional Programming in Scala by Chiusano and Bjarnason.) Clearly, that breaks down if an exception is thrown or if an invalid value is returned. For calls to partial functions to be referentially transparent, we can only call them with argument values for which they are defined, or we need to elegantly handle the undefined values. So how can we tell if a partial function is defined for some arbitrary argument value?
In Scala we can express partial functions as a subclass of scala.PartialFunction that allows us to answer this question.
Let's look at your example in a Scala REPL session...
$ scala
Welcome to Scala 2.12.6 (Java HotSpot(TM) 64-Bit Server VM, Java 1.8.0_171).
Type in expressions for evaluation. Or try :help.
scala> val second: List[Int] => Int = {
| case x :: y :: _ => y
| }
<console>:11: warning: match may not be exhaustive.
It would fail on the following inputs: List(_), Nil
val second: List[Int] => Int = {
^
second: List[Int] => Int = $$Lambda$3181/1894473818#27492c62
So what did we just do? We defined second as a reference to a function that takes a List[Int] argument and returns an Int (the second value in the list).
You'll notice that the Scala compiler recognizes that this is not going to match all cases and warns you of the fact. This is a partial function, in the sense that it will fail for some arguments, but it's not an instance of scala.PartialFunction, as we can verify as follows:
scala> second.isInstanceOf[PartialFunction[List[Int], Int]]
res0: Boolean = false
Incidentally, the type List[Int] => Int is a shorthand for scala.Function1[List[Int], Int] and so seconds type is an instance of that type:
scala> second.isInstanceOf[Function1[List[Int], Int]]
res1: Boolean = true
Calling this version of the function produces the results you indicate:
scala> second(List(1, 2, 3))
res1: Int = 2
scala> second(Nil)
scala.MatchError: List() (of class scala.collection.immutable.Nil$)
at .$anonfun$second$1(<console>:11)
at .$anonfun$second$1$adapted(<console>:11)
... 36 elided
The problem is that if we just have some list value, l, and don't know what is in that list, we don't know whether we'll get an exception if we pass it to the function referenced by second. Now, we could put the call in a try block and catch any exception, but that's verbose and not good functional programming style. Ideally, we'd like to know whether we can call the function first to avoid an exception. Unfortunately, there's no way to tell from a Function1 instance:
scala> second.isDefinedAt(Nil)
<console>:13: error: value isDefinedAt is not a member of List[Int] => Int
second.isDefinedAt(Nil)
^
What we need is to declare second to have the type PartialFunction[List[Int], Int] as follows:
scala> val second: PartialFunction[List[Int], Int] = {
| case x :: y :: _ => y
| }
second: PartialFunction[List[Int],Int] = <function1>
(BTW, note that you have a typo in your question for this code - the above is how this should be defined.)
Now we do not have any warnings! We've told the compiler that this is a PartialFunction instance, so the compiler knows that its undefined for some arguments, so warnings are superfluous. We can now verify that fact:
scala> second.isInstanceOf[PartialFunction[List[Int], Int]]
res6: Boolean = true
We can now also verify whether it's defined for particular values:
scala> second.isDefinedAt(Nil)
res7: Boolean = false
scala> second.isDefinedAt(List(1, 2))
res9: Boolean = true
and so on. (The Scala compiler, as described in the book, is able to implement this magical isDefinedAt function for us.)
So, does that mean we should now write code like this:
def getSecondValue(l: List[Int]): Option[Int] = {
// Check if second is defined for this argument. If so, call it and wrap in Some.
if(second.isDefinedAt(l)) Some(second(l))
// Otherwise, we do not have a second value.
else None
}
Well, that's a little verbose too. Fortunately, once second is a PartialFunction instance, we can rewrite the above as:
def getSecondValue(l: List[Int]): Option[Int] = second.lift(l)
The lift method turns a partial function into a complete function that returns a defined value for every argument: if the argument to second is defined, then we get a Some(value); otherwise, we get None.
You'll find the concept of partial functions, and PartialFunction, more useful as you become more familiar with functional programming. If you don't get it right now, don't worry; all will become clear.
A partial function is a function that does not provide an answer for every possible input value it can be given. It provides an answer only for a subset of possible data, and defines the data it can handle. In Scala, a partial function can also be queried to determine if it can handle a particular value.
As a simple example, imagine a normal function that divides one number by another:
val divide = (x: Int) => 42 / x
As defined, this function blows up when the input parameter is zero:
scala> divide(0)
java.lang.ArithmeticException: / by zero
Although you can handle this particular situation by catching and throwing an exception, Scala lets you define the divide function as a PartialFunction. When doing so, you also explicitly state that the function is defined when the input parameter is not zero:
val divide = new PartialFunction[Int, Int] {
def apply(x: Int) = 42 / x
def isDefinedAt(x: Int) = x != 0
}
https://alvinalexander.com/scala/how-to-define-use-partial-functions-in-scala-syntax-examples
You can refer to the above link.
so here's the problem I keep running into various situations with Scala - it seemingly ignores the implied type, even when the situation is clear. Granted this could be my understanding I admit, but when it comes to underscore placeholders I keep running into trouble. For example below (this is fictional just to prove the point).The 2nd position of trait X has to be <:X[,] of some kind. There's no ambiguity here - so anywhere that scala sees this position, regardless of how weak it's coded - the contact is X and I should have access to functions like "doesX". Isn't that indisputable? No matter how poorly I deal with that position in the code, I must at least get X. Why does Scala constantly ignore this fact when you get deep into the type system? Any pointers would be appreciated, thank you!
object TestRun extends App {
trait X[T, Y<:X[_,_]] {
def doesX:Unit
def providesY:Y
}
class Test extends X[Int,Test]{
override def doesX: Unit = println("etc..")
def providesY:Test = new Test
}
val a:X[_,_] = new Test //yes I know I could define a better here, its just to demo. I shouldn't have to explicitly relabel the 2nd _ as _<:X[_,<:X[ etc..
val b = a.providesY //clearly this has to be at least a (something) WITH X, but scala claims this as "Any"
b.doesX //error won't compile!!
//trait
}
When you write:
val a: X[_, _] = new Test
^
// This is treated as if the type parameter is Any, for the most part
You are telling the compiler that a is an X, where you don't care what its type parameters are. That is, the unbounded wildcard _ is assumed to have an upper-bound of Any, and that's it.
providesY uses the second type parameter of X to determine its return type, but for a the compiler was told that to discard it. So b is just an Any. This is easier to see using the REPL:
scala> val a: X[_, _] = new Test
a: X[_, _] = Test#27abe2cd
scala> val b = a.providesY
b: Any = Test#f5f2bb7
Therefore, b.doesX fails to compile because the compiler now thinks it is Any. The simple solution is not to use wild cards for types (or any existential types in general, most of the time you do not want this).
scala> val a: X[Int, Test] = new Test
a: X[Int,Test] = Test#1134affc
scala> val b = a.providesY
b: Test = Test#6fc6f14e
scala> b.doesX
etc..
Or you could simply leave off the type annotation, and let the compiler infer the correct type.
Consider the following example:
case class C[T](x:T) {
def f(t:T) = println(t)
type ValueType = T
}
val list = List(1 -> C(2), "hello" -> C("goodbye"))
for ((a,b) <- list) {
b.f(a)
}
In this example, I know (runtime guarantee) that the type of a will be some T, and b will have type C[T] with the same T. Of course, the compiler cannot know that, hence we get a typing error in b.f(a).
To tell the compiler that this invocation is OK, we need to do a typecast à la b.f(a.asInstanceOf[T]). Unfortunately, T is not known here. So my question is: How do I rewrite b.f(a) in order to make this code compile?
I am looking for a solution that does not involve complex constructions (to keep the code readable), and that is "clean" in the sense that we should not rely on code erasure to make it work (see the first approach below).
I have some working approaches, but I find them unsatisfactory for various reasons.
Approaches I tried:
b.asInstanceOf[C[Any]].f(a)
This works, and is reasonably readable, but it is based on a "lie". b is not of type C[Any], and the only reason we do not get a runtime error is because we rely on the limitations of the JVM (type erasure). I think it is good style only to use x.asInstanceOf[X] when we know that x is really of type X.
b.f(a.asInstanceOf[b.ValueType])
This should work according to my understanding of the type system. I have added the member ValueType to the class C in order to be able to explicitly refer to the type parameter T. However, in this approach we get a mysterious error message:
Error:(9, 22) type mismatch;
found : b.ValueType
(which expands to) _1
required: _1
b.f(a.asInstanceOf[b.ValueType])
^
Why? It seems to complain that we expect type _1 but got type _1! (But even if this approach works, it is limited to the cases where we have the possibility to add a member ValueType to C. If C is some existing library class, we cannot do that either.)
for ((a,b) <- list.asInstanceOf[List[(T,C[T]) forSome {type T}]]) {
b.f(a)
}
This one works, and is semantically correct (i.e., we do not "lie" when invoking asInstanceOf). The limitation is that this is somewhat unreadable. Also, it is somewhat specific to the present situation: if a,b do not come from the same iterator, then where can we apply this type cast? (This code also has the side effect of being too complex for Intelli/J IDEA 2016.2 which highlights it as an error in the editor.)
val (a2,b2) = (a,b).asInstanceOf[(T,C[T]) forSome {type T}]
b2.f(a2)
I would have expected this one to work since a2,b2 now should have types T and C[T] for the same existential T. But we get a compile error:
Error:(10, 9) type mismatch;
found : a2.type (with underlying type Any)
required: T
b2.f(a2)
^
Why? (Besides that, the approach has the disadvantage of incurring runtime costs (I think) because of the creation and destruction of a pair.)
b match {
case b : C[t] => b.f(a.asInstanceOf[t])
}
This works. But enclosing the code with a match makes the code much less readable. (And it also is too complicated for Intelli/J.)
The cleanest solution is, IMO, the one you found with the type-capture pattern match. You can make it concise, and hopefully readable, by integrating the pattern directly inside your for comprehension, as follows:
for ((a, b: C[t]) <- list) {
b.f(a.asInstanceOf[t])
}
Fiddle: http://www.scala-js-fiddle.com/gist/b9030033133ee94e8c18ad772f3461a0
If you are not in a for comprehension already, unfortunately the corresponding pattern assignment does not work:
val (c, d: C[t]) = (a, b)
d.f(c.asInstanceOf[t])
That's because t is not in scope anymore on the second line. In that case, you would have to use the full pattern matching.
Maybe I'm confused about what you are trying to achieve, but this compiles:
case class C[T](x:T) {
def f(t:T) = println(t)
type ValueType = T
}
type CP[T] = (T, C[T])
val list = List[CP[T forSome {type T}]](1 -> C(2), "hello" -> C("goodbye"))
for ((a,b) <- list) {
b.f(a)
}
Edit
If the type of the list itself is out of your control, you can still cast it to this "correct" type.
case class C[T](x:T) {
def f(t:T) = println(t)
type ValueType = T
}
val list = List(1 -> C(2), "hello" -> C("goodbye"))
type CP[T] = (T, C[T])
for ((a,b) <- list.asInstanceOf[List[CP[T forSome { type T }]]]) {
b.f(a)
}
Great question! Lots to learn here about Scala.
Other answers and comments have already addressed most of the issues here, but I'd like to address a few additional points.
You asked why this variant doesn't work:
val (a2,b2) = (a,b).asInstanceOf[(T,C[T]) forSome {type T}]
b2.f(a2)
You aren't the only person who's been surprised by this; see e.g. this recent very similar issue report: SI-9899.
As I wrote there:
I think this is working as designed as per SLS 6.1: "The following skolemization rule is applied universally for every expression: If the type of an expression would be an existential type T, then the type of the expression is assumed instead to be a skolemization of T."
Basically, every time you write a value-level expression that the compiler determines to have an existential type, the existential type is instantiated. b2.f(a2) has two subexpressions with existential type, namely b2 and a2, so the existential gets two different instantiations.
As for why the pattern-matching variant works, there isn't explicit language in SLS 8 (Pattern Matching) covering the behavior of existential types, but 6.1 doesn't apply because a pattern isn't technically an expression, it's a pattern. The pattern is analyzed as a whole and any existential types inside only get instantiated (skolemized) once.
As a postscript, note that yes, when you play in this area, the error messages you get are often confusing or misleading and ought to be improved. See for example https://github.com/scala/scala-dev/issues/205
A wild guess, but is it possible that you need something like this:
case class C[+T](x:T) {
def f[A >: T](t: A) = println(t)
}
val list = List(1 -> C(2), "hello" -> C("goodbye"))
for ((a,b) <- list) {
b.f(a)
}
?
It will type check.
I'm not quite sure what "runtime guarantee" means here, usually it means that you are trying to fool type system (e.g. with asInstanceOf), but then all bets are off and you shouldn't expect type system to be of any help.
UPDATE
Just for the illustration why type casting is an evil:
case class C[T <: Int](x:T) {
def f(t: T) = println(t + 1)
}
val list = List("hello" -> C(2), 2 -> C(3))
for ((a, b: C[t]) <- list) {
b.f(a.asInstanceOf[t])
}
It compiles and fails at runtime (not surprisingly).
UPDATE2
Here's what generated code looks like for the last snippet (with C[t]):
...
val a: Object = x1._1();
val b: Test$C = x1._2().$asInstanceOf[Test$C]();
if (b.ne(null))
{
<synthetic> val x2: Test$C = b;
matchEnd4({
x2.f(scala.Int.unbox(a));
scala.runtime.BoxedUnit.UNIT
})
}
...
Type t simply vanished (as it should have been) and Scala is trying to convert a to an upper bound of T in C, i.e. Int. If there is no upper bound it's going to be Any (but then method f is nearly useless unless you cast again or use something like println which takes Any).
From working on the first problem of the 99 Scala Puzzles I defined my own version of last like so:
def last[A](xs: List[A]): A = xs match {
case x :: Nil => x
case x :: xs => last(xs)
}
My question is: Why is it necessary for last to be directly followed by the type variable, as in last[A]? Why couldn't the compiler just do the right thing if I wrote the function like so:
def last(xs: List[A]): A
.....
(leaving the [A] off the end of last[A]?)
And if the compiler is capable of figuring it out, then what is the rationale for designing the language this way?
A appears 3 times:
last[A]
List[A]
: A(after the argument list)
The 2nd one is needed to specify that the List contains objects of type A. The 3rd one is needed to specify that the function returns an object of type A.
The 1st one is where you actually declare A, so it could be used in the other two places.
You need to write last[A] because A does not exist. Since it does not exist, by declaring it after the name of the function you actually get a chance to define some expectations or constraints for this type.
For example: last[A <: Int] to enforce the fact that A has to be a subtype of Int
Once it's declared, you can use it to define the type of your parameters and your return type.
I got an insight from #Lee's comment:
How would the compiler know that the A in List[A] doesn't refer to an
actual type called A?
To demonstrate to myself that this made sense, I tried substituting the type variable A, with the name of an actual type String, and then passed the function a List[Int], seeing that when last is declared like def last[String](xs: List[String]): String, I was able to pass last a List[Int]:
scala> def last[String](xs: List[String]): String = xs match {
| case x :: Nil => x
| case x :: xs => last(xs)
| }
last: [String](xs: List[String])String
scala> last(List(1,2,3,4))
res7: Int = 4
Therefore proving the identifier String does behave like a type variable, and does not reference the concrete type String.
It would also make debugging more difficult if the compiler just assumed that any identifier not in scope was a type variable. It therefore, makes sense to have to declare it at the beginning of the function definition.
In languages like SML, Erlang and in buch of others we may define functions like this:
fun reverse [] = []
| reverse x :: xs = reverse xs # [x];
I know we can write analog in Scala like this (and I know, there are many flaws in the code below):
def reverse[T](lst: List[T]): List[T] = lst match {
case Nil => Nil
case x :: xs => reverse(xs) ++ List(x)
}
But I wonder, if we could write former code in Scala, perhaps with desugaring to the latter.
Is there any fundamental limitations for such syntax being implemented in the future (I mean, really fundamental -- e.g. the way type inference works in scala, or something else, except parser obviously)?
UPD
Here is a snippet of how it could look like:
type T
def reverse(Nil: List[T]) = Nil
def reverse(x :: xs: List[T]): List[T] = reverse(xs) ++ List(x)
It really depends on what you mean by fundamental.
If you are really asking "if there is a technical showstopper that would prevent to implement this feature", then I would say the answer is no. You are talking about desugaring, and you are on the right track here. All there is to do is to basically stitch several separates cases into one single function, and this can be done as a mere preprocessing step (this only requires syntactic knowledge, no need for semantic knowledge). But for this to even make sense, I would define a few rules:
The function signature is mandatory (in Haskell by example, this would be optional, but it is always optional whether you are defining the function at once or in several parts). We could try to arrange to live without the signature and attempt to extract it from the different parts, but lack of type information would quickly come to byte us. A simpler argument is that if we are to try to infer an implicit signature, we might as well do it for all the methods. But the truth is that there are very good reasons to have explicit singatures in scala and I can't imagine to change that.
All the parts must be defined within the same scope. To start with, they must be declared in the same file because each source file is compiled separately, and thus a simple preprocessor would not be enough to implement the feature. Second, we still end up with a single method in the end, so it's only natural to have all the parts in the same scope.
Overloading is not possible for such methods (otherwise we would need to repeat the signature for each part just so the preprocessor knows which part belongs to which overload)
Parts are added (stitched) to the generated match in the order they are declared
So here is how it could look like:
def reverse[T](lst: List[T]): List[T] // Exactly like an abstract def (provides the signature)
// .... some unrelated code here...
def reverse(Nil) = Nil
// .... another bit of unrelated code here...
def reverse(x :: xs ) = reverse(xs) ++ List(x)
Which could be trivially transformed into:
def reverse[T](list: List[T]): List[T] = lst match {
case Nil => Nil
case x :: xs => reverse(xs) ++ List(x)
}
// .... some unrelated code here...
// .... another bit of unrelated code here...
It is easy to see that the above transformation is very mechanical and can be done by just manipulating a source AST (the AST produced by the slightly modified grammar that accepts this new constructs), and transforming it into the target AST (the AST produced by the standard scala grammar).
Then we can compile the result as usual.
So there you go, with a few simple rules we are able to implement a preprocessor that does all the work to implement this new feature.
If by fundamental you are asking "is there anything that would make this feature out of place" then it can be argued that this does not feel very scala. But more to the point, it does not bring that much to the table. Scala author(s) actually tend toward making the language simpler (as in less built-in features, trying to move some built-in features into libraries) and adding a new syntax that is not really more readable goes against the goal of simplification.
In SML, your code snippet is literally just syntactic sugar (a "derived form" in the terminology of the language spec) for
val rec reverse = fn x =>
case x of [] => []
| x::xs = reverse xs # [x]
which is very close to the Scala code you show. So, no there is no "fundamental" reason that Scala couldn't provide the same kind of syntax. The main problem is Scala's need for more type annotations, which makes this shorthand syntax far less attractive in general, and probably not worth the while.
Note also that the specific syntax you suggest would not fly well, because there is no way to distinguish one case-by-case function definition from two overloaded functions syntactically. You probably would need some alternative syntax, similar to SML using "|".
I don't know SML or Erlang, but I know Haskell. It is a language without method overloading. Method overloading combined with such pattern matching could lead to ambiguities. Imagine following code:
def f(x: String) = "String "+x
def f(x: List[_]) = "List "+x
What should it mean? It can mean method overloading, i.e. the method is determined in compile time. It can also mean pattern matching. There would be just a f(x: AnyRef) method that would do the matching.
Scala also has named parameters, which would be probably also broken.
I don't think that Scala is able to offer more simple syntax than you have shown in general. A simpler syntax may IMHO work in some special cases only.
There are at least two problems:
[ and ] are reserved characters because they are used for type arguments. The compiler allows spaces around them, so that would not be an option.
The other problem is that = returns Unit. So the expression after the | would not return any result
The closest I could come up with is this (note that is very specialized towards your example):
// Define a class to hold the values left and right of the | sign
class |[T, S](val left: T, val right: PartialFunction[T, T])
// Create a class that contains the | operator
class OrAssoc[T](left: T) {
def |(right: PartialFunction[T, T]): T | T = new |(left, right)
}
// Add the | to any potential target
implicit def anyToOrAssoc[S](left: S): OrAssoc[S] = new OrAssoc(left)
object fun {
// Use the magic of the update method
def update[T, S](choice: T | S): T => T = { arg =>
if (choice.right.isDefinedAt(arg)) choice.right(arg)
else choice.left
}
}
// Use the above construction to define a new method
val reverse: List[Int] => List[Int] =
fun() = List.empty[Int] | {
case x :: xs => reverse(xs) ++ List(x)
}
// Call the method
reverse(List(3, 2, 1))