I am trying to create a method that will take a list of Objects and a list of Types and then check whether a particular object matches a particular type.
I tried to create a dummy example. In the following code validate method takes list of objects and a List of type then tried to validate the types of each object. I know following code is wrong but I just created to communicate the problem, it would be really great if you can tell me how can I do this in Scala.
object T extends App {
trait MyT
case class A(a: Int) extends MyT
case class B(b: Int) extends MyT
def validate(values: Seq[Any], types: Seq[MyT]): Seq[Boolean] =
for ((v, ty: MyT) ← values.zip(types)) yield v.isInstanceOf[ty]
// create objects
val a = A(1)
val b = B(1)
// call validate method
validate(Seq(a, b), Seq(A, B))
}
Types are not values, so you can't have a list of them.
But, you may use Class instead:
def validate(values: Seq[Any], types: Seq[Class[_ <: MyT]]): Seq[Boolean] =
values.lazyZip(types).map {
case (v, c) =>
c.isInstance(v)
}
Which can be used like this:
validate(Seq(a, b), Seq(classOf[A], classOf[B]))
// res: Seq[Boolean] = List(true, true)
You can see the code running here.
However, note that this will break if your classes start to have type parameters due to type erasure.
Note, I personally don't recommend this code since, IMHO, the very definition of validate is a code smell and I would bet you have a design error that lead to this situation.
I recommend searching for a way to avoid this situation and solve the root problem.
Related
I am trying to port a solution for DomainEventHandlers and -Dispatcher from PHP8 to Scala 3. Handlers should specify a list of events they can handle (in a type-safe way, preferably, by their classes). Handlers are dynamically registered with the Dispatcher, which should aggregate a map from the elements of the lists from each Handler to a List of Handlers for those events.
When an event is raised with the Dispatcher, it should check the class of the current event against the keys from the map, and pass the event to each Handler in each list of Handlers for a key if and only if the event's class is identical to or a subclass of the class specified by the key.
In dynamically typed OOP languages like PHP8, this is easy - a Handler stores a list of class-names, which can be reified simply by [ClassName]::class, then the Dispatcher gets the event's class via $event::class and performs an is_a-check for each HashMap-key, which checks both exact match and subclass-relationship.
In Scala 3, I can't seem to find a good way to do this. Working with underlying Java-reflections via getClass or Class[?] produces problems due to the mismatch between the Scala and Java type-systems (specifically, trailing $ being either present or not). In Scala 2, Tags would probably have been the way to go - but Scala 3 reflection is a different beast, and I have not found a way to utilize it to implement the above, and would appreciate advice.
Concretely, let's say we have
trait DomainEvent[D1 <: Serializable, D2 <: Serializable, A <: Aggregate]
extends Event[D1, D2]:
type AggregateType = A
val aggregateIdentifier: (String, UUID)
def applyAsPatch(aggregate: AggregateType): AggregateType
trait DomainEventHandler:
val handles: List[???]
def handle(event: DomainEvent[?, ?, ?]): ZIO[Any, Throwable, Unit]
object DomainEventDispatcher:
val registeredHandlers: scala.collection.mutable.Map[???, List[DomainEventHandler]] =
scala.collection.mutable.Map()
def registerHandler(handler: DomainEventHandler): Unit = ???
def raiseEvent(event: DomainEvent[?, ?, ?]): ZIO[Any, Throwable, Unit] = ???
I am unsure what to use in place of ??? in the DomainEventHandler's List and the Dispatcher's Map - the registerHandler and raiseEvent-implementations will follow from that.
Well, if your concrete event classes that you match aren't parametrized, it's pretty simple:
trait Event[A]
case class IntEvent(x: Int) extends Event[Int]
case class StringEvent(x: String) extends Event[String]
object Dispatcher {
var handlers = List.empty[PartialFunction[Event[_], String]]
def register(h: PartialFunction[Event[_], String]): Unit = { handlers = h :: handlers }
def dispatch(event: Event[_]) = handlers.flatMap { _.lift(event) }
}
Dispatcher.register { case e: IntEvent => s"Handled $e" }
Dispatcher.register {
case e: IntEvent => s"Handled ${e.x}"
case e: StringEvent => s"Handled ${e.x}"
}
Dispatcher.dispatch(new IntEvent()) // List(Handled 1, Handled IntEvent(1))
Dispatcher.dispatch(new StringEvent("foo")) // List(Handled foo)
But if you want to match on things like Event[Int], that makes things significantly more difficult. I wasn't able to find a good way to do it (though, I am by no means an expert in scala 3 features).
Not sure why they dropped ClassTag support ... I am taking it as a sign that matching on type parameters like this is no longer considered a good practice, and the "proper" solution to your problem is now naming all classes you want to match without type parameters.
I'm confused about the generic type. I expect that 2.asInstanceOf[A] is cast to the type A, meanwhile, it's cast to Int.
Besides that, the input is java.lang.Long whereas the output is a list of Int (according to the definition the input and the output should be the same type). Why is that?
def whatever[A](x: A): List[A] = {
val two = 2.asInstanceOf[A]
val l = List(1.asInstanceOf[A],2.asInstanceOf[A])
println(f"Input type inside the function for 15L: ${x.getClass}")
println(f"The class of two: ${two.getClass}, the value of two: $two")
println(f"The class of the first element of l: ${l.head.getClass}, first element value: ${l.head}")
l
}
println(f"Returned from whatever function: ${whatever(15L)}")
the outupt:
Input type inside the function for 15L: class java.lang.Long
The class of two: class java.lang.Integer, the value of two: 2
The class of the first element of l: class java.lang.Integer, first element value: 1
Returned from whatever function: List(1, 2)
a.asInstanceOf[B] means:
Dear compiler;
Please forget what you think the type of a is. I know better. I know that if a isn't actually type B then my program could blow up, but I'm really very smart and that's not going to happen.
Sincerely yours, Super Programmer
In other words val b:B = a.asInstanceOf[B] won't create a new variable of type B, it will create a new variable that will be treated as if it were type B. If the actual underlying type of a is compatible with type B then everything is fine. If a's real type is incompatible with B then things blow up.
Type erasure. For the purposes of type checking 2 is cast to A; but at a later compilation stage A is erased to Object, so your code becomes equivalent to
def whatever(x: Object): List[Object] = {
val two = 2.asInstanceOf[Object]
val l = List(1.asInstanceOf[Object],2.asInstanceOf[Object])
println(f"Input type inside the function for 15L: ${x.getClass}")
println(f"The class of two: ${two.getClass}, the value of two: $two")
println(f"The class of the first element of l: ${l.head.getClass}, first element value: ${l.head}")
l
}
2.asInstanceOf[Object] is a boxing operation returning a java.lang.Integer.
If you try to actually use the return value as a List[Long] you'll eventually get a ClassCastException, e.g.
val list = whatever(15L)
val x = list(0)
x will be inferred to be Long and a cast inserted to unbox the expected java.lang.Long.
The answer from #jwvh is on point. Here I'll only add a solution in case you want to fix the problem of safely converting an Int to an A in whatever, without knowing what A is. This is of course only possible if you provide a way to build a particular A from an Int. We can do this in using a type-class:
trait BuildableFromInt[+A] {
def fromInt(i: Int): A
}
Now you only have to implicitly provide BuildableFromInt for any type A you wish to use in whatever:
object BuildableFromInt {
implicit val longFromInt: BuildableFromInt[Long] = Long.box(_)
}
and now define whatever to only accept compliant types A:
def whatever[A : BuildableFromInt](x: A): List[A] = {
val two = implicitly[BuildableFromInt[A]].fromInt(2)
// Use two like any other "A"
// ...
}
Now whatever can be used with any type for which a BuildableFromInt is available.
I want to be able to create a class/trait that behaves somewhat like an enumeration (HEnum in the first snippet below). I can't use a plain enumeration because each enum value could have a different type (though the container class will be the same): Key[A]. I'd like to be able to construct the enum roughly like this:
class Key[A](val name: String)
object A extends HEnum {
val a = new Key[String]("a")
val b = new Key[Int]("b")
val c = new Key[Float]("c")
}
And then I'd like to be able to perform more or less basic HList operations like:
A.find[String] // returns the first element with type Key[String]
A.find("b") // returns the first element with name "b", type should (hopefully) be Key[Int]
So far I've been playing with an HList as the underlying data structure, but constructing one with the proper type has proven difficult. My most successful attempt looks like this:
class Key[A](val name: String)
object Key {
def apply[A, L <: HList](name: String, l: L): (Key[A], Key[A] :: L) = {
val key = new Key[A](name)
(key, key :: l)
}
}
object A {
val (a, akeys) = Key[String, HNil]("a", HNil)
val (b, bkeys) = Key[Int, Key[String] :: HList]("b", akeys)
val (c, ckeys) = Key[Float, Key[Int] :: HList]("c", bkeys)
val values = ckeys // use this for lookups, etc
def find[A]: Key[A] = values.select[A]
def find[A](name: String): Key[A] = ...
}
The problem here is that the interface is clunky. Adding a new value anywhere besides the end of the list of values is error prone and no matter what, you have to manually update values any time a new value is introduced. My solution without HList involved a List[Key[_]] and error prone/unsafe casting to the proper type when needed.
EDIT
I should also mention that the enum example found here is not particularly helpful to me (although, if that can be adapted, then great). The added compiler checks for exhaustive pattern matches are nice (and I would ultimately want that) but this enum still only allows a homogeneous collection of enum values.
I understand covariance and contravariance in scala. Covariance has many applications in the real world, but I can not think of any for contravariance applications, except the same old examples for Functions.
Can someone shed some light on real world examples of contravariance use?
In my opinion, the two most simple examples after Function are ordering and equality. However, the first is not contra-variant in Scala's standard library, and the second doesn't even exist in it. So, I'm going to use Scalaz equivalents: Order and Equal.
Next, I need some class hierarchy, preferably one which is familiar and, of course, it both concepts above must make sense for it. If Scala had a Number superclass of all numeric types, that would have been perfect. Unfortunately, it has no such thing.
So I'm going to try to make the examples with collections. To make it simple, let's just consider Seq[Int] and List[Int]. It should be clear that List[Int] is a subtype of Seq[Int], ie, List[Int] <: Seq[Int].
So, what can we do with it? First, let's write something that compares two lists:
def smaller(a: List[Int], b: List[Int])(implicit ord: Order[List[Int]]) =
if (ord.order(a,b) == LT) a else b
Now I'm going to write an implicit Order for Seq[Int]:
implicit val seqOrder = new Order[Seq[Int]] {
def order(a: Seq[Int], b: Seq[Int]) =
if (a.size < b.size) LT
else if (b.size < a.size) GT
else EQ
}
With these definitions, I can now do something like this:
scala> smaller(List(1), List(1, 2, 3))
res0: List[Int] = List(1)
Note that I'm asking for an Order[List[Int]], but I'm passing a Order[Seq[Int]]. This means that Order[Seq[Int]] <: Order[List[Int]]. Given that Seq[Int] >: List[Int], this is only possible because of contra-variance.
The next question is: does it make any sense?
Let's consider smaller again. I want to compare two lists of integers. Naturally, anything that compares two lists is acceptable, but what's the logic of something that compares two Seq[Int] being acceptable?
Note in the definition of seqOrder how the things being compared becomes parameters to it. Obviously, a List[Int] can be a parameter to something expecting a Seq[Int]. From that follows that a something that compares Seq[Int] is acceptable in place of something that compares List[Int]: they both can be used with the same parameters.
What about the reverse? Let's say I had a method that only compared :: (list's cons), which, together with Nil, is a subtype of List. I obviously could not use this, because smaller might well receive a Nil to compare. It follows that an Order[::[Int]] cannot be used instead of Order[List[Int]].
Let's proceed to equality, and write a method for it:
def equalLists(a: List[Int], b: List[Int])(implicit eq: Equal[List[Int]]) = eq.equal(a, b)
Because Order extends Equal, I can use it with the same implicit above:
scala> equalLists(List(4, 5, 6), List(1, 2, 3)) // we are comparing lengths!
res3: Boolean = true
The logic here is the same one. Anything that can tell whether two Seq[Int] are the same can, obviously, also tell whether two List[Int] are the same. From that, it follows that Equal[Seq[Int]] <: Equal[List[Int]], which is true because Equal is contra-variant.
This example is from the last project I was working on. Say you have a type-class PrettyPrinter[A] that provides logic for pretty-printing objects of type A. Now if B >: A (i.e. if B is superclass of A) and you know how to pretty-print B (i.e. have an instance of PrettyPrinter[B] available) then you can use the same logic to pretty-print A. In other words, B >: A implies PrettyPrinter[B] <: PrettyPrinter[A]. So you can declare PrettyPrinter[A] contravariant on A.
scala> trait Animal
defined trait Animal
scala> case class Dog(name: String) extends Animal
defined class Dog
scala> trait PrettyPrinter[-A] {
| def pprint(a: A): String
| }
defined trait PrettyPrinter
scala> def pprint[A](a: A)(implicit p: PrettyPrinter[A]) = p.pprint(a)
pprint: [A](a: A)(implicit p: PrettyPrinter[A])String
scala> implicit object AnimalPrettyPrinter extends PrettyPrinter[Animal] {
| def pprint(a: Animal) = "[Animal : %s]" format (a)
| }
defined module AnimalPrettyPrinter
scala> pprint(Dog("Tom"))
res159: String = [Animal : Dog(Tom)]
Some other examples would be Ordering type-class from Scala standard library, Equal, Show (isomorphic to PrettyPrinter above), Resource type-classes from Scalaz etc.
Edit:
As Daniel pointed out, Scala's Ordering isn't contravariant. (I really don't know why.) You may instead consider scalaz.Order which is intended for the same purpose as scala.Ordering but is contravariant on its type parameter.
Addendum:
Supertype-subtype relationship is but one type of relationship that can exist between two types. There can be many such relationships possible. Let's consider two types A and B related with function f: B => A (i.e. an arbitrary relation). Data-type F[_] is said to be a contravariant functor if you can define an operation contramap for it that can lift a function of type B => A to F[A => B].
The following laws need to be satisfied:
x.contramap(identity) == x
x.contramap(f).contramap(g) == x.contramap(f compose g)
All of the data types discussed above (Show, Equal etc.) are contravariant functors. This property lets us do useful things such as the one illustrated below:
Suppose you have a class Candidate defined as:
case class Candidate(name: String, age: Int)
You need an Order[Candidate] which orders candidates by their age. Now you know that there is an Order[Int] instance available. You can obtain an Order[Candidate] instance from that with the contramap operation:
val byAgeOrder: Order[Candidate] =
implicitly[Order[Int]] contramap ((_: Candidate).age)
An example based on a real-world event-driven software system. Such a system is based on broad categories of events, like events related to the functioning of the system (system events), events generated by user actions (user events) and so on.
A possible event hierarchy:
trait Event
trait UserEvent extends Event
trait SystemEvent extends Event
trait ApplicationEvent extends SystemEvent
trait ErrorEvent extends ApplicationEvent
Now the programmers working on the event-driven system need to find a way to register/process the events generated in the system. They will create a trait, Sink, that is used to mark components in need to be notified when an event has been fired.
trait Sink[-In] {
def notify(o: In)
}
As a consequence of marking the type parameter with the - symbol, the Sink type became contravariant.
A possible way to notify interested parties that an event happened is to write a method and to pass it the corresponding event. This method will hypothetically do some processing and then it will take care of notifying the event sink:
def appEventFired(e: ApplicationEvent, s: Sink[ApplicationEvent]): Unit = {
// do some processing related to the event
// notify the event sink
s.notify(e)
}
def errorEventFired(e: ErrorEvent, s: Sink[ErrorEvent]): Unit = {
// do some processing related to the event
// notify the event sink
s.notify(e)
}
A couple of hypothetical Sink implementations.
trait SystemEventSink extends Sink[SystemEvent]
val ses = new SystemEventSink {
override def notify(o: SystemEvent): Unit = ???
}
trait GenericEventSink extends Sink[Event]
val ges = new GenericEventSink {
override def notify(o: Event): Unit = ???
}
The following method calls are accepted by the compiler:
appEventFired(new ApplicationEvent {}, ses)
errorEventFired(new ErrorEvent {}, ges)
appEventFired(new ApplicationEvent {}, ges)
Looking at the series of calls you notice that it is possible to call a method expecting a Sink[ApplicationEvent] with a Sink[SystemEvent] and even with a Sink[Event]. Also, you can call the method expecting a Sink[ErrorEvent] with a Sink[Event].
By replacing invariance with a contravariance constraint, a Sink[SystemEvent] becomes a subtype of Sink[ApplicationEvent]. Therefore, contravariance can also be thought of as a ‘widening’ relationship, since types are ‘widened’ from more specific to more generic.
Conclusion
This example has been described in a series of articles about variance found on my blog
In the end, I think it helps to also understand the theory behind it...
Short answer that might help people who were super confused like me and didn't want to read these long winded examples:
Imagine you have 2 classes Animal, and Cat, which extends Animal. Now, imagine that you have a type Printer[Cat], that contains the functionality for printing Cats. And you have a method like this:
def print(p: Printer[Cat], cat: Cat) = p.print(cat)
but the thing is, that since Cat is an Animal, Printer[Animal] should also be able to print Cats, right?
Well, if Printer[T] were defined like Printer[-T], i.e. contravariant, then we could pass Printer[Animal] to the print function above and use its functionality to print cats.
This is why contravariance exists. Another example, from C#, for example, is the class IComparer which is contravariant as well. Why? Because we should be able to use Animal comparers to compare Cats, too.
Let's say I have a case class that represents personas, people on different social networks. Instances of that class are fully immutable, and are held in immutable collections, to be eventually modified by an Akka actor.
Now, I have a case class with many fields, and I receive a message that says I must update one of the fields, something like this:
case class Persona(serviceName : String,
serviceId : String,
sentMessages : Set[String])
// Somewhere deep in an actor
val newPersona = Persona(existingPersona.serviceName,
existingPersona.serviceId,
existingPersona.sentMessages + newMessage)
Notice I have to specify all fields, even though only one changes. Is there a way to clone existingPersona and replace only one field, without specifying all the fields that don't change? Can I write that as a trait and use it for all my case classes?
If Persona was a Map-like instance, it would be easy to do.
case classcomes with a copy method that is dedicated exactly to this usage:
val newPersona = existingPersona.copy(sentMessages =
existingPersona.sentMessages + newMessage)
Since 2.8, Scala case classes have a copy method that takes advantage of named/default params to work its magic:
val newPersona =
existingPersona.copy(sentMessages = existing.sentMessages + newMessage)
You can also create a method on Persona to simplify usage:
case class Persona(
svcName : String,
svcId : String,
sentMsgs : Set[String]
) {
def plusMsg(msg: String) = this.copy(sentMsgs = this.sentMsgs + msg)
}
then
val newPersona = existingPersona plusMsg newMsg
existingPersona.copy(sentMessages = existingPersona.sentMessages + newMessage)
Consider using lens in Shapeless library:
import shapeless.lens
case class Persona(serviceName : String,
serviceId : String,
sentMessages : Set[String])
// define the lens
val messageLens = lens[Persona] >> 'sentMessages
val existingPersona = Persona("store", "apple", Set("iPhone"))
// When you need the new copy, by setting the value,
val newPersona1 = messageLens.set(existingPersona)(Set.empty)
// or by other operation based on current value.
val newPersona2 = messageLens.modify(existingPersona)(_ + "iPad")
// Results:
// newPersona1: Persona(store,apple,Set())
// newPersona2: Persona(store,apple,Set(iPhone, iPad))
Moreover, in case you have nested case classes, the getter and setter methods can be a bit tedious to compose. It will be a good chance to simplify by using lens library.
Please also refer to:
Shapeless Github / Boilerplate-free lenses for arbitrary case classes
Quicklens Github
Lens in scala
I didn't want to include a big library to do complex lenses that let you set values deep in nested case classes. It turns out it is just a few lines of code in the scalaz library:
/** http://stackoverflow.com/a/5597750/329496 */
case class Lens[A, B](get: A => B, set: (A, B) => A) extends ((A) => B) with Immutable {
def apply(whole: A): B = get(whole)
def mod(a: A, f: B => B) = set(a, f(this (a)))
def compose[C](that: Lens[C, A]) = Lens[C, B](
c => this(that(c)),
(c, b) => that.mod(c, set(_, b))
)
def andThen[C](that: Lens[B, C]) = that compose this
}
You can then create lenses that set deeply nested values far easier than using the built in copy feature. Here is a link to a big set if complex lenses that that my library uses to set heavily nested values.