As also seen in the scaladoc, sets are invariant :( So what do you do when you wish treat one as if it were covariant?
I have a constructor object:
object SimpleGraph {
def apply[ID](vertices: List[AbstractVertex[ID]], edges: Set[AbstractEdge[ID]]) = {
val simpleGraph = new SimpleGraph[ID, AbstractVertex[ID], AbstractEdge[ID]]
vertices.map(simpleGraph.addNode)
edges.map(simpleGraph.addEdge)
simpleGraph
}
}
Given the invariance, sets of types that adhere to T <: AbstractEdge[ID] won't make it through into my apply function. The compilation error suggests using a wildcard type, which as much as I fathom means circumventing type safety altogether (?). My own solution is ugly because it uses cpu cycles and more memory to get over the invariance: changing the prototype's type from Set to List and converting back and forth between a list and a set to get the data through.
Have you got a better suggestion?
Thanks!
I am not terribly sure about it, because I am currently not able to test it properly, But wouldn't it work to tell your apply the exact type of the items in the set by type parameter?
object SimpleGraph {
def apply[ID, EDGE <: AbstractEdge[ID]](vertices: List[AbstractVertex[ID]], edges: Set[EDGE]) = {
val simpleGraph = new SimpleGraph[ID, AbstractVertex[ID], AbstractEdge[ID]]
vertices.foreach(simpleGraph.addNode)
edges.foreach(simpleGraph.addEdge)
simpleGraph
}
}
Related
Sorry I'm not very familiar with Scala, but I'm curious if this is possible and haven't been able to figure out how.
Basically, I want to create some convenience initializers that can generate a random sample of data (in this case a grid). The grid will always be filled with instances of a particular type (in this case a Location). But in different cases I might want grids filled with different subtypes of Location, e.g. Farm or City.
In Python, this would be trivial:
def fillCollection(klass, size):
return [klass() for _ in range(size)]
class City: pass
cities = fillCollection(City, 10)
I tried to do something similar in Scala but it does not work:
def fillGrid[T <: Location](size): Vector[T] = {
Vector.fill[T](size, size) {
T()
}
}
The compiler just says "not found: value T"
So, it it possible to approximate the above Python code in Scala? If not, what's the recommended way to handle this kind of situation? I could write an initializer for each subtype, but in my real code there's a decent amount of boilerplate overlap between them so I'd like to share code if possible.
The best workaround I've come up with so far is to pass a closure into the initializer (which seems to be how the fill method on Vectors already works), e.g.:
def fillGrid[T <: Location](withElem: => T, size: Int = 100): Vector[T] = {
Vector.fill[T](n1 = size, n2 = size)(withElem)
}
That's not a huge inconvenience, but it makes me curious why Scala doesn't support the "simpler" Python-style construct (if it in fact doesn't). I sort of get why having a "fully generic" initializer could cause trouble, but in this case I can't see what the harm would be generically initializing instances that are all known to be subtypes of a given parent type.
You are correct, in that what you have is probably the simplest option. The reason Scala can't do things the pythonic way is because the type system is much stronger, and it has to contend with type erasure. Scala can not guarantee at compile time that any subclass of Location has a particular constructor, and it will only allow you to do things that it can guarantee will conform to the types (unless you do tricky things with reflection).
If you want to clean it up a little bit, you can make it work more like python by using implicits.
implicit def emptyFarm(): Farm = new Farm
implicit def emptyCity(): City = new City
def fillGrid[T <: Location](size: Int = 100)(implicit withElem: () => T): Vector[Vector[T]] = {
Vector.fill[T](n1 = size, n2 = size)(withElem())
}
fillGrid[farm](3)
To make this more usable in a library, it's common to put the implicits in a companion object of Location, so they can all be brought into scope where appropriate.
sealed trait Location
...
object Location
{
implicit def emptyFarm...
implicit def emptyCity...
}
...
import Location._
fillGrid[Farm](3)
You can use reflection to accomplish what you want...
This is a simple example that will only work if all your subclasses have a zero args constructor.
sealed trait Location
class Farm extends Location
class City extends Location
def fillGrid[T <: Location](size: Int)(implicit TTag: scala.reflect.ClassTag[T]): Vector[Vector[T]] = {
val TClass = TTag.runtimeClass
Vector.fill[T](size, size) { TClass.newInstance().asInstanceOf[T] }
}
However, I have never been a fan of runtime reflection, and I hope there could be another way.
Scala cannot do this kind of thing directly because it's not type safe. It will not work if you pass a class without a zero-argument constructor. The Python version throws an error at runtime if you try to do this.
The closure is probably the best way to go.
This is a "real life" OO design question. I am working with Scala, and interested in specific Scala solutions, but I'm definitely open to hear generic thoughts.
I am implementing a branch-and-bound combinatorial optimization program. The algorithm itself is pretty easy to implement. For each different problem we just need to implement a class that contains information about what are the allowed neighbor states for the search, how to calculate the cost, and then potentially what is the lower bound, etc...
I also want to be able to experiment with different data structures. For instance, one way to store a logic formula is using a simple list of lists of integers. This represents a set of clauses, each integer a literal. We can have a much better performance though if we do something like a "two-literal watch list", and store some extra information about the formula in general.
That all would mean something like this
object BnBSolver[S<:BnBState]{
def solve(states: Seq[S], best_state:Option[S]): Option[S] = if (states.isEmpty) best_state else
val next_state = states.head
/* compare to best state, etc... */
val new_states = new_branches ++ states.tail
solve(new_states, new_best_state)
}
class BnBState[F<:Formula](clauses:F, assigned_variables) {
def cost: Int
def branches: Seq[BnBState] = {
val ll = clauses.pick_variable
List(
BnBState(clauses.assign(ll), ll :: assigned_variables),
BnBState(clauses.assign(-ll), -ll :: assigned_variables)
)
}
}
case class Formula[F<:Formula[F]](clauses:List[List[Int]]) {
def assign(ll: Int) :F =
Formula(clauses.filterNot(_ contains ll)
.map(_.filterNot(_==-ll))))
}
Hopefully this is not too crazy, wrong or confusing. The whole issue here is that this assign method from a formula would usually take just the current literal that is going to be assigned. In the case of two-literal watch lists, though, you are doing some lazy thing that requires you to know later what literals have been previously assigned.
One way to fix this is you just keep this list of previously assigned literals in the data structure, maybe as a private thing. Make it a self-standing lazy data structure. But this list of the previous assignments is actually something that may be naturally available by whoever is using the Formula class. So it makes sense to allow whoever is using it to just provide the list every time you assign, if necessary.
The problem here is that we cannot now have an abstract Formula class that just declares a assign(ll:Int):Formula. In the normal case this is OK, but if this is a two-literal watch list Formula, it is actually an assign(literal: Int, previous_assignments: Seq[Int]).
From the point of view of the classes using it, it is kind of OK. But then how do we write generic code that can take all these different versions of Formula? Because of the drastic signature change, it cannot simply be an abstract method. We could maybe force the user to always provide the full assigned variables, but then this is a kind of a lie too. What to do?
The idea is the watch list class just becomes a kind of regular assign(Int) class if I write down some kind of adapter method that knows where to take the previous assignments from... I am thinking maybe with implicit we can cook something up.
I'll try to make my answer a bit general, since I'm not convinced I'm completely following what you are trying to do. Anyway...
Generally, the first thought should be to accept a common super-class as a parameter. Obviously that won't work with Int and Seq[Int].
You could just have two methods; have one call the other. For instance just wrap an Int into a Seq[Int] with one element and pass that to the other method.
You can also wrap the parameter in some custom class, e.g.
class Assignment {
...
}
def int2Assignment(n: Int): Assignment = ...
def seq2Assignment(s: Seq[Int]): Assignment = ...
case class Formula[F<:Formula[F]](clauses:List[List[Int]]) {
def assign(ll: Assignment) :F = ...
}
And of course you would have the option to make those conversion methods implicit so that callers just have to import them, not call them explicitly.
Lastly, you could do this with a typeclass:
trait Assigner[A] {
...
}
implicit val intAssigner = new Assigner[Int] {
...
}
implicit val seqAssigner = new Assigner[Seq[Int]] {
...
}
case class Formula[F<:Formula[F]](clauses:List[List[Int]]) {
def assign[A : Assigner](ll: A) :F = ...
}
You could also make that type parameter at the class level:
case class Formula[A:Assigner,F<:Formula[A,F]](clauses:List[List[Int]]) {
def assign(ll: A) :F = ...
}
Which one of these paths is best is up to preference and how it might fit in with the rest of the code.
I have a tree object that implements lazy depth-first-search as a TraversableView.
import collection.TraversableView
case class Node[T](label: T, ns: Node[T]*)
case class Tree[T](root: Node[T]) extends TraversableView[T, Traversable[_]] {
protected def underlying = null
def foreach[U](f: (T) => U) {
def dfs(r: Node[T]): TraversableView[T, Traversable[_]] = {
Traversable(r.label).view ++ r.ns.flatMap(dfs(_))
}
dfs(root).foreach(f)
}
}
This is appealingly concise and appears to work; however, the underlying = null method makes me nervous because I don't understand what it means. (IntelliJ wrote that line for me.) I suppose it might be correct, because in this case there is no underlying strict representation of the tree, but I'm not sure.
Is the above code correct, or do I have to do something more with underlying?
Users of views will expect to be able to call force to get a strict collection. With your implementation, calling force on a tree (or any transformation of a tree—e.g., tree.take(10).filter(pred), etc.) will result in a null pointer exception.
This may be fine with you—you'll still be able to force evaluation using toList, for example (although you should follow the advice in DaoWen's comment if you go that route).
The actual contents of underlying should never get used, though, so there's an easy fix—just make it an appropriately typed empty collection:
protected def underlying = Vector.empty[T]
Now if a user calls tree.force, they'll get a vector of labels, statically typed as a Traversable[T].
I'd like to write a type alias to shorten, nice and encapsulated Scala code.
Suppose I got some collection which has the property of being a list of maps, the value of which are tuples.
My type would write something like List[Map[Int, (String, String)]], or anything more generic as my application allows it. I could imagine having a supertype asking for a Seq[MapLike[Int, Any]] or whatever floats my boat, with concrete subclasses being more specific.
I'd then want to write an alias for this long type.
class ConcreteClass {
type DataType = List[Map[Int, (String, String)]]
...
}
I would then happily use ConcreteClass#DataType everywhere I can take one, and use it.
Now suppose I add a function
def foo(a : DataType) { ... }
And I want to call it from outside with an empty list.
I can call foo(List()), but when I want to change my underlying type to be another type of Seq, I'll have to come back and change this code too. Besides, it's not very explicit this empty list is intended as a DataType. And the companion object does not have the associated List methods, so I can't call DataType(), or DataType.empty. It's gonna be even more annoying when I need non-empty lists since I'll have to write out a significant part of this long type.
Is there any way I can ask Scala to understand my type as the same thing, including companion object with its creator methods, in the interest of shortening code and blackboxing it ?
Or, any reason why I should not be doing this in the first place ?
The answer was actually quite simple:
class ConcreteClass {
type DataType = List[String]
}
object ConcreteClass {
val DataType = List
}
val d = ConcreteClass.DataType.empty
This enables my code to call ConcreteClass.DataType to construct lists with all the methods in List and little effort.
Thanks a lot to Oleg for the insight. His answer is also best in case you want not to delegate to List any call to ConcreteClass.DataType, but control precisely what you want to allow callers to do.
What about this?
class ConcreteClass {
type DataType = List[String]
}
object DataType {
def apply(): ConcreteClass#DataType = Nil
}
//...
val a = DataType()
Suppose I have this:
class String2(val x:String) {
def *(times:Int) : String = {
val builder = new StringBuilder()
for( i <- 0 until times) {
builder.append(x)
}
builder.toString()
}
}
now if I add this implicit:
implicit def gimmeString2(y:String) = new String2(y)
I will get a compilation error because stringWrapper also adds this implicit. Is there a way of saying to the compiler "ignore other implicits, use this", so that I don't have to instantiate a String2 object and work on that?
I admit the example code may not be the most appropriate ( for this question ), but I think it will do.
Scala 2.8 added a prioritization system for implicits. It's explained in this SIP on the new Java arrays:
When comparing two different applicable alternatives of an overloaded method or of an implicit, each method gets one point for having more specific arguments, and another point for being defined in a proper subclass. An alternative “wins” over another if it gets a greater number of points in these two comparisons
concluding that if alternatives have identical argument types, the one which is defined in a subclass
wins. Hence I believe that you could declare implicits as follows:
trait LowPriorityImplicits {
//lower priority conversions
}
object HighPriorityImplicits extends LowPriorityImplicits {
//higher-order ones here
}