I need all the method names in a scala trait I've defined. I know this sounds like a trivial problem but I could not find any answers relating to the trait, they all revolved around classes.
To be specific, I need names for all the abstract methods. But if I can get the name of all methods regardless of abstract or not, that works too.
Say I have this trait A
trait A {
def myDefinedInt: Int = 2
def myAbstractString: String
}
I need a list of all methods (or preferably just the abstract ones)
I'm relatively new to scala so although I get classes and interfaces. Traits are new to me.
Thanks in advance!
You can get all methods with getDeclaredMethods and then just filter for abstract methods:
import java.lang.reflect.Modifier
classOf[A]
.getDeclaredMethods
.filter(m => Modifier.isAbstract(m.getModifiers))
.map(_.getName)
.foreach(println)
It prints: myAbstractString.
I am a little bit confused using companion objects in scala. When you want to provide multiple constructors, usually you declare a companion object and overload the apply method. But what is the difference between this two ways of doing it?:
case class Node(....)
object Node {
def apply(...) = new Node(....) // 1 way
def apply(...) = Node(...) // second way
}
Almost all examples I've seen use the first form:
When to use companion object factory versus the new keyword
"new" keyword in Scala
http://alvinalexander.com/scala/how-to-create-scala-object-instances-without-new-apply-case-class
But my code seems to work the same using both forms. Does using new keyword only have sense when we have a normal class? (Not a case class)?
When you call
val n = Node(..)
The compiler will expand the code to a Node.apply call. Now, one of these apply methods will internally have to call new in order to create an instance of the type. Case classes provide companion objects with an apply method for you out of the box to allow the shorter syntax.
When you want to provide multiple constructors, usually you declare a companion object and overload the apply method
This is the case for case classes. You can also provide additional auxiliary constructors using this():
class Foo(i: Int) {
def this() {
this(0)
}
}
Note this will not provide the syntax sugar apply does, you'll need to use new.
When you declare a case class. A companion object is generated by the compiler with apply method in it whose implementation creates the object of the case class using new keyword.
So you need not create a companion object again with apply method creating object of the case class using new keyword. This work will be done by the compiler
I have a trait for which I know that reference equality is never the correct implementation of equals. Implementations of the trait can be written by many users, and practice shows that sometimes they fail to override equals. Is there a way to require it?
In practice implementations are usually case classes, which override equals automatically, and we can approach requiring that by having Product as the self-type of the trait, however, I'd like to see a solution which allows non-case classes overriding equals as well (EDIT: Using scala.Equals as the self-type is a closer approximation to what I want, since it's still implemented automatically by case classes, but can be usefully implemented by non-case classes and isn't a large burden on people writing implementations).
One more approach I thought of while writing this question is to override equals in the trait to call an abstract method, but unfortunately, this doesn't work for case class implementations.
Why not use typeclass contract instead of pure trait? We have one already in scalaz, and it's easy to glue it with Equals trait:
import scalaz._
case class X(a:Int,b:Int)
class Y(a:Int,b:Int)
implicit def provideDefaultEqual[T <: Equals]:Equal[T] = new Equal[T] {
def equal(a1: T, a2: T) = a1 == a2
}
implicitly[Equal[X]]
implicitly[Equal[Y]] //compile error
If you need to wire this with your trait, there is your own nice solution
Are there cases where it's preferable to mixin traits to access the functionality of "static" methods, rather than importing objects with those methods?
Say we want to access the functionality of a method a(). Would we ever extend a trait that contains a() rather than import an object that contains a()?
If we look at the following example:
1)
trait A {
def a() {}
}
...
class B extends A {
val b = a()
}
vs.
2)
object A {
def a() {}
}
...
import A._
class B {
val b = a()
}
Is there any reason to prefer the first approach, even if there is no "is-a" relationship between the two classes B and A?
Maybe things that extend B don't want to keep re-importing A?
Maybe the method relies upon other "static" methods but you actually want to override the implementation?
If B is final (or an object) and the methods really are static (and don't refer to implementations that you might want to change in B), then there's not much point in mixing in a trait. The only exception is if there are implicit conversions defined, where if you mix in the implicit it will have lower priority than if you declare it yourself.
(Check out scala.LowPriorityImplicits which is mixed into scala.Predef for examples.)
All that Rex said...
And keep in mind as well that an import brings artifacts (methods, fields) into the current scope, but doesn't expose them on the new class' interface.
Mixing in a trait may expose artifacts (either public, protected, or ...) by making them "part of" the new class/trait interface.
As I understand from this blog post "type classes" in Scala is just a "pattern" implemented with traits and implicit adapters.
As the blog says if I have trait A and an adapter B -> A then I can invoke a function, which requires argument of type A, with an argument of type B without invoking this adapter explicitly.
I found it nice but not particularly useful. Could you give a use case/example, which shows what this feature is useful for ?
One use case, as requested...
Imagine you have a list of things, could be integers, floating point numbers, matrices, strings, waveforms, etc. Given this list, you want to add the contents.
One way to do this would be to have some Addable trait that must be inherited by every single type that can be added together, or an implicit conversion to an Addable if dealing with objects from a third party library that you can't retrofit interfaces to.
This approach becomes quickly overwhelming when you also want to begin adding other such operations that can be done to a list of objects. It also doesn't work well if you need alternatives (for example; does adding two waveforms concatenate them, or overlay them?) The solution is ad-hoc polymorphism, where you can pick and chose behaviour to be retrofitted to existing types.
For the original problem then, you could implement an Addable type class:
trait Addable[T] {
def zero: T
def append(a: T, b: T): T
}
//yup, it's our friend the monoid, with a different name!
You can then create implicit subclassed instances of this, corresponding to each type that you wish to make addable:
implicit object IntIsAddable extends Addable[Int] {
def zero = 0
def append(a: Int, b: Int) = a + b
}
implicit object StringIsAddable extends Addable[String] {
def zero = ""
def append(a: String, b: String) = a + b
}
//etc...
The method to sum a list then becomes trivial to write...
def sum[T](xs: List[T])(implicit addable: Addable[T]) =
xs.FoldLeft(addable.zero)(addable.append)
//or the same thing, using context bounds:
def sum[T : Addable](xs: List[T]) = {
val addable = implicitly[Addable[T]]
xs.FoldLeft(addable.zero)(addable.append)
}
The beauty of this approach is that you can supply an alternative definition of some typeclass, either controlling the implicit you want in scope via imports, or by explicitly providing the otherwise implicit argument. So it becomes possible to provide different ways of adding waveforms, or to specify modulo arithmetic for integer addition. It's also fairly painless to add a type from some 3rd-party library to your typeclass.
Incidentally, this is exactly the approach taken by the 2.8 collections API. Though the sum method is defined on TraversableLike instead of on List, and the type class is Numeric (it also contains a few more operations than just zero and append)
Reread the first comment there:
A crucial distinction between type classes and interfaces is that for class A to be a "member" of an interface it must declare so at the site of its own definition. By contrast, any type can be added to a type class at any time, provided you can provide the required definitions, and so the members of a type class at any given time are dependent on the current scope. Therefore we don't care if the creator of A anticipated the type class we want it to belong to; if not we can simply create our own definition showing that it does indeed belong, and then use it accordingly. So this not only provides a better solution than adapters, in some sense it obviates the whole problem adapters were meant to address.
I think this is the most important advantage of type classes.
Also, they handle properly the cases where the operations don't have the argument of the type we are dispatching on, or have more than one. E.g. consider this type class:
case class Default[T](val default: T)
object Default {
implicit def IntDefault: Default[Int] = Default(0)
implicit def OptionDefault[T]: Default[Option[T]] = Default(None)
...
}
I think of type classes as the ability to add type safe metadata to a class.
So you first define a class to model the problem domain and then think of metadata to add to it. Things like Equals, Hashable, Viewable, etc. This creates a separation of the problem domain and the mechanics to use the class and opens up subclassing because the class is leaner.
Except for that, you can add type classes anywhere in the scope, not just where the class is defined and you can change implementations. For example, if I calculate a hash code for a Point class by using Point#hashCode, then I'm limited to that specific implementation which may not create a good distribution of values for the specific set of Points I have. But if I use Hashable[Point], then I may provide my own implementation.
[Updated with example]
As an example, here's a use case I had last week. In our product there are several cases of Maps containing containers as values. E.g., Map[Int, List[String]] or Map[String, Set[Int]]. Adding to these collections can be verbose:
map += key -> (value :: map.getOrElse(key, List()))
So I wanted to have a function that wraps this so I could write
map +++= key -> value
The main issue is that the collections don't all have the same methods for adding elements. Some have '+' while others ':+'. I also wanted to retain the efficiency of adding elements to a list, so I didn't want to use fold/map which create new collections.
The solution is to use type classes:
trait Addable[C, CC] {
def add(c: C, cc: CC) : CC
def empty: CC
}
object Addable {
implicit def listAddable[A] = new Addable[A, List[A]] {
def empty = Nil
def add(c: A, cc: List[A]) = c :: cc
}
implicit def addableAddable[A, Add](implicit cbf: CanBuildFrom[Add, A, Add]) = new Addable[A, Add] {
def empty = cbf().result
def add(c: A, cc: Add) = (cbf(cc) += c).result
}
}
Here I defined a type class Addable that can add an element C to a collection CC. I have 2 default implementations: For Lists using :: and for other collections, using the builder framework.
Then using this type class is:
class RichCollectionMap[A, C, B[_], M[X, Y] <: collection.Map[X, Y]](map: M[A, B[C]])(implicit adder: Addable[C, B[C]]) {
def updateSeq[That](a: A, c: C)(implicit cbf: CanBuildFrom[M[A, B[C]], (A, B[C]), That]): That = {
val pair = (a -> adder.add(c, map.getOrElse(a, adder.empty) ))
(map + pair).asInstanceOf[That]
}
def +++[That](t: (A, C))(implicit cbf: CanBuildFrom[M[A, B[C]], (A, B[C]), That]): That = updateSeq(t._1, t._2)(cbf)
}
implicit def toRichCollectionMap[A, C, B[_], M[X, Y] <: col
The special bit is using adder.add to add the elements and adder.empty to create new collections for new keys.
To compare, without type classes I would have had 3 options:
1. to write a method per collection type. E.g., addElementToSubList and addElementToSet etc. This creates a lot of boilerplate in the implementation and pollutes the namespace
2. to use reflection to determine if the sub collection is a List / Set. This is tricky as the map is empty to begin with (of course scala helps here also with Manifests)
3. to have poor-man's type class by requiring the user to supply the adder. So something like addToMap(map, key, value, adder), which is plain ugly
Yet another way I find this blog post helpful is where it describes typeclasses: Monads Are Not Metaphors
Search the article for typeclass. It should be the first match. In this article, the author provides an example of a Monad typeclass.
The forum thread "What makes type classes better than traits?" makes some interesting points:
Typeclasses can very easily represent notions that are quite difficult to represent in the presence of subtyping, such as equality and ordering.
Exercise: create a small class/trait hierarchy and try to implement .equals on each class/trait in such a way that the operation over arbitrary instances from the hierarchy is properly reflexive, symmetric, and transitive.
Typeclasses allow you to provide evidence that a type outside of your "control" conforms with some behavior.
Someone else's type can be a member of your typeclass.
You cannot express "this method takes/returns a value of the same type as the method receiver" in terms of subtyping, but this (very useful) constraint is straightforward using typeclasses. This is the f-bounded types problem (where an F-bounded type is parameterized over its own subtypes).
All operations defined on a trait require an instance; there is always a this argument. So you cannot define for example a fromString(s:String): Foo method on trait Foo in such a way that you can call it without an instance of Foo.
In Scala this manifests as people desperately trying to abstract over companion objects.
But it is straightforward with a typeclass, as illustrated by the zero element in this monoid example.
Typeclasses can be defined inductively; for example, if you have a JsonCodec[Woozle] you can get a JsonCodec[List[Woozle]] for free.
The example above illustrates this for "things you can add together".
One way to look at type classes is that they enable retroactive extension or retroactive polymorphism. There are a couple of great posts by Casual Miracles and Daniel Westheide that show examples of using Type Classes in Scala to achieve this.
Here's a post on my blog
that explores various methods in scala of retroactive supertyping, a kind of retroactive extension, including a typeclass example.
I don't know of any other use case than Ad-hoc polymorhism which is explained here the best way possible.
Both implicits and typeclasses are used for Type-conversion. The major use-case for both of them is to provide ad-hoc polymorphism(i.e) on classes that you can't modify but expect inheritance kind of polymorphism. In case of implicits you could use both an implicit def or an implicit class (which is your wrapper class but hidden from the client). Typeclasses are more powerful as they can add functionality to an already existing inheritance chain(eg: Ordering[T] in scala's sort function).
For more detail you can see https://lakshmirajagopalan.github.io/diving-into-scala-typeclasses/
In scala type classes
Enables ad-hoc polymorphism
Statically typed (i.e. type-safe)
Borrowed from Haskell
Solves the expression problem
Behavior can be extended
- at compile-time
- after the fact
- without changing/recompiling existing code
Scala Implicits
The last parameter list of a method can be marked implicit
Implicit parameters are filled in by the compiler
In effect, you require evidence of the compiler
… such as the existence of a type class in scope
You can also specify parameters explicitly, if needed
Below Example extension on String class with type class implementation extends the class with a new methods even though string is final :)
/**
* Created by nihat.hosgur on 2/19/17.
*/
case class PrintTwiceString(val original: String) {
def printTwice = original + original
}
object TypeClassString extends App {
implicit def stringToString(s: String) = PrintTwiceString(s)
val name: String = "Nihat"
name.printTwice
}
This is an important difference (needed for functional programming):
consider inc:Num a=> a -> a:
a received is the same that is returned, this cannot be done with subtyping
I like to use type classes as a lightweight Scala idiomatic form of Dependency Injection that still works with circular dependencies yet doesn't add a lot of code complexity. I recently rewrote a Scala project from using the Cake Pattern to type classes for DI and achieved a 59% reduction in code size.