Is there a better explanation than "this is how it works". I mean I tried this one:
class TestShortMatch[T <: AnyRef] {
def foo(t: T): Unit = {
val f = (_: Any) match {
case Val(t) => println(t)
case Sup(l) => println(l)
}
}
class Val(t: T)
class Sup(l: Number)
}
and compiler complaints:
Cannot resolve symbol 'Val'
Cannot resolve symbol 'Sup'
Of course if I add case before each of the classes it will work fine. But what is the reason? Does compiler make some optimization and generate a specific byte-code?
The reason is twofold. Pattern matching is just syntactic sugar for using extractors and case classes happen to give you a couple methods for free, one of which is an extractor method that corresponds to the main constructor.
If you want your example above to work, you need to define an unapply method inside objects Val and Sup. To do that you'd need extractor methods (which are only defined on val fields, so you'll have to make your fields vals):
class Val[T](val t: T)
class Sup(val l: Number)
object Val {
def unapply[T](v: Val[T]): Option[T] = Some(v.t)
}
object Sup {
def unapply(s: Sup): Option[Number] = Some(s.l)
}
And which point you can do something like val Val(v) = new Val("hi"). More often than not, though, it is better to make your class a case class. Then, the only times you should be defining extra extractors.
The usual example (to which I can't seem to find a reference) is coordinates:
case class Coordinate(x: Double, val: Double)
And then you can define a custom extractors like
object Polar {
def unapply(c: Coordinate): Option[(Double,Double)] = {...}
}
object Cartesian {
def unapply(c: Coordinate): Option[(Double,Double)] = Some((c.x,c.y))
}
to convert to the two different representations, all when you pattern match.
You can use pattern matching on arbitrary classes, but you need to implement an unapply method, used to "de-construct" the object.
With a case class, the unapply method is automatically generated by the compiler, so you don't need to implement it yourself.
When you write match exp { case Val(pattern) => ... case ... }, that is equivalent to something like this:
match Val.unapply(exp) {
case Some(pattern) =>
...
case _ =>
// code to match the other cases goes here
}
That is, it uses the result of the companion object's unapply method to see whether the match succeeded.
If you define a case class, it automatically defines a companion object with a suitable unapply method. For a normal class it doesn't. The motivation for that is the same as for the other things that gets automatically defined for case classes (like equals and hashCode for example): By declaring a class as a case class, you're making a statement about how you want the class to behave. Given that, there's a good chance that the auto generated will do what you want. For a general class, it's up to you to define these methods like you want them to behave.
Note that parameters for case classes are vals by default, which isn't true for normal classes. So your class class Val(t: T) doesn't even have any way to access t from the outside. So it isn't even possible to define an unapply method that gets at the value of t. That's another reason why you don't get an automatically generated unapply for normal classes: It isn't even possible to generate one unless all parameters are vals.
Related
I am trying to understand how a case class can be passed as an argument to a function which accepts functions as arguments. Below is an example:
Consider the below function
def !![B](h: Out[B] => A): In[B] = { ... }
If I understood correctly, this is a polymorphic method which has a type parameter B and accepts a function h as a parameter. Out and In are other two classes defined previously.
This function is then being used as shown below:
case class Q(p: boolean)(val cont: Out[R])
case class R(p: Int)
def g(c: Out[Q]) = {
val rin = c !! Q(true)_
...
}
I am aware that currying is being used to avoid writing the type annotation and instead just writing _. However, I cannot grasp why and how the case class Q is transformed to a function (h) of type Out[B] => A.
EDIT 1 Updated !! above and the In and Out definitions:
abstract class In[+A] {
def future: Future[A]
def receive(implicit d: Duration): A = {
Await.result[A](future, d)
}
def ?[B](f: A => B)(implicit d: Duration): B = {
f(receive)
}
}
abstract class Out[-A]{
def promise[B <: A]: Promise[B]
def send(msg: A): Unit = promise.success(msg)
def !(msg: A) = send(msg)
def create[B](): (In[B], Out[B])
}
These code samples are taken from the following paper: http://drops.dagstuhl.de/opus/volltexte/2016/6115/
TLDR;
Using a case class with multiple parameter lists and partially applying it will yield a partially applied apply call + eta expansion will transform the method into a function value:
val res: Out[Q] => Q = Q.apply(true) _
Longer explanation
To understand the way this works in Scala, we have to understand some fundamentals behind case classes and the difference between methods and functions.
Case classes in Scala are a compact way of representing data. When you define a case class, you get a bunch of convenience methods which are created for you by the compiler, such as hashCode and equals.
In addition, the compiler also generates a method called apply, which allows you to create a case class instance without using the new keyword:
case class X(a: Int)
val x = X(1)
The compiler will expand this call to
val x = X.apply(1)
The same thing will happen with your case class, only that your case class has multiple argument lists:
case class Q(p: boolean)(val cont: Out[R])
val q: Q = Q(true)(new Out[Int] { })
Will get translated to
val q: Q = Q.apply(true)(new Out[Int] { })
On top of that, Scala has a way to transform methods, which are a non value type, into a function type which has the type of FunctionX, X being the arity of the function. In order to transform a method into a function value, we use a trick called eta expansion where we call a method with an underscore.
def foo(i: Int): Int = i
val f: Int => Int = foo _
This will transform the method foo into a function value of type Function1[Int, Int].
Now that we posses this knowledge, let's go back to your example:
val rin = c !! Q(true) _
If we just isolate Q here, this call gets translated into:
val rin = Q.apply(true) _
Since the apply method is curried with multiple argument lists, we'll get back a function that given a Out[Q], will create a Q:
val rin: Out[R] => Q = Q.apply(true) _
I cannot grasp why and how the case class Q is transformed to a function (h) of type Out[B] => A.
It isn't. In fact, the case class Q has absolutely nothing to do with this! This is all about the object Q, which is the companion module to the case class Q.
Every case class has an automatically generated companion module, which contains (among others) an apply method whose signature matches the primary constructor of the companion class, and which constructs an instance of the companion class.
I.e. when you write
case class Foo(bar: Baz)(quux: Corge)
You not only get the automatically defined case class convenience methods such as accessors for all the elements, toString, hashCode, copy, and equals, but you also get an automatically defined companion module that serves both as an extractor for pattern matching and as a factory for object construction:
object Foo {
def apply(bar: Baz)(quux: Corge) = new Foo(bar)(quux)
def unapply(that: Foo): Option[Baz] = ???
}
In Scala, apply is a method that allows you to create "function-like" objects: if foo is an object (and not a method), then foo(bar, baz) is translated to foo.apply(bar, baz).
The last piece of the puzzle is η-expansion, which lifts a method (which is not an object) into a function (which is an object and can thus be passed as an argument, stored in a variable, etc.) There are two forms of η-expansion: explicit η-expansion using the _ operator:
val printFunction = println _
And implicit η-expansion: in cases where Scala knows 100% that you mean a function but you give it the name of a method, Scala will perform η-expansion for you:
Seq(1, 2, 3) foreach println
And you already know about currying.
So, if we put it all together:
Q(true)_
First, we know that Q here cannot possibly be the class Q. How do we know that? Because Q here is used as a value, but classes are types, and like most programming languages, Scala has a strict separation between types and values. Therefore, Q must be a value. In particular, since we know class Q is a case class, object Q is the companion module for class Q.
Secondly, we know that for a value Q
Q(true)
is syntactic sugar for
Q.apply(true)
Thirdly, we know that for case classes, the companion module has an automatically generated apply method that matches the primary constructor, so we know that Q.apply has two parameter lists.
So, lastly, we have
Q.apply(true) _
which passes the first argument list to Q.apply and then lifts Q.apply into a function which accepts the second argument list.
Note that case classes with multiple parameter lists are unusual, since only the parameters in the first parameter list are considered elements of the case class, and only elements benefit from the "case class magic", i.e. only elements get accessors implemented automatically, only elements are used in the signature of the copy method, only elements are used in the automatically generated equals, hashCode, and toString() methods, and so on.
This is a situation I have encountered frequently, but I have not been able to find a solution yet.
Suppose you have a list of persons and you just want to verify the person names.
This works:
persons.map(_.name) should contain theSameElementsAs(List("A","B"))
Instead, I would rather write this like
val toName: Person => String = _.name
persons should contain theSameElementsAs(List("A","B")) (after mapping toName)
because this is how you would say this.
Sometimes however, you'd like to use a custom matcher which matches more than just one property of the object. How would it be possible to use
persons should contain(..)
syntax, but somehow be able to use a custom matcher?
Both these situations I could easily solve using JUnit or TestNG using Hamcrest matchers, but I have not found a way to do this with ScalaTest.
I have tried to use the 'after being' syntax from the Explicitly trait, but that's not possible since this takes a 'Normalization' which defines that the 'normalized' method uses the same type for the argument and return type. So it's not possible to change a Person to a String.
Also I have not succeeded yet in implementing an 'Explicitly' like trait because it does not like the Equality[.] type I return and/or it does not know anymore what the original list type was, so using '_.name' does not compile.
Any suggestions are welcome.
You can manage something similar via the word decided and moderate abuse of the Equality trait. This is because the Equality trait's areEqual method takes a parameter of the generic type and one of type Any, so you can use that to compare Person with String, and decided by simply takes an Equality object which means you don't have to futz around with Normality.
import org.scalactic.Equality
import org.scalatest.{FreeSpec, Matchers}
final class Test extends FreeSpec with Matchers {
case class Person(name: String)
val people = List(Person("Alice"), Person("Eve"))
val namesBeingEqual = MappingEquality[Person, String](p => p.name)
"test should pass" in {
(people should contain theSameElementsAs List("Alice", "Eve"))(
decided by namesBeingEqual)
}
"test should fail" in {
(people should contain theSameElementsAs List("Alice", "Bob"))(
decided by namesBeingEqual)
}
case class MappingEquality[S, T](map: S => T) extends Equality[S] {
override def areEqual(s: S, b: Any): Boolean = b match {
case t: T => map(s) == t
case _ => false
}
}
}
I'm not sure I'd say this is a good idea since it doesn't exactly behave in the way one would expect anything called Equality to behave, but it works.
You can even get the beingMapped syntax you suggest by adding it to after via implicit conversion:
implicit class AfterExtensions(aft: TheAfterWord) {
def beingMapped[S, T](map: S => T): Equality[S] = MappingEquality(map)
}
}
I did try getting it work with after via the Uniformity trait, which has similar methods involving Any, but ran into problems because the normalization is the wrong way around: I can create a Uniformity[String] object from your example, but not a Uniformity[Person] one. (The reason is that there's a normalized method returning the generic type which is used to construct the Equality object, meaning that in order to compare strings with strings the left-side input must be a string.) This means that the only way to write it is with the expected vs actual values in the opposite order from normally:
"test should succeed" in {
val mappedToName = MappingUniformity[Person, String](person => person.name)
(List("Alice", "Eve") should contain theSameElementsAs people)(
after being mappedToName)
}
case class MappingUniformity[S, T](map: S => T) extends Uniformity[T] {
override def normalizedOrSame(b: Any): Any = b match {
case s: S => map(s)
case t: T => t
}
override def normalizedCanHandle(b: Any): Boolean =
b.isInstanceOf[S] || b.isInstanceOf[T]
override def normalized(s: T): T = s
}
Definitely not how you'd usually want to write this.
use inspectors
forAll (xs) { x => x should be < 3 }
Part of a current project involves converting from types coupled to a database and a generic type used when serializing the results out to clients via Json, the current implementation in Scala uses type inference to correctly perform the transformation, using Scala's TypeTag:
def Transform[A: TypeTag](objects:Seq[A]):Seq[Children] = typeOf[A] match {
case pc if pc =:= typeOf[ProductCategory] =>
TransformProductCategory(objects.asInstanceOf[Seq[ProductCategory]])
case pa if pa =:= typeOf[ProductArea] =>
TransformProductArea(objects.asInstanceOf[Seq[ProductArea]])
case pg if pg =:= typeOf[ProductGroup] =>
TransformProductGroup(objects.asInstanceOf[Seq[ProductGroup]])
case psg if psg =:= typeOf[ProductSubGroup] =>
TransformProductSubGroup(objects.asInstanceOf[Seq[ProductSubGroup]])
case _ =>
throw new IllegalArgumentException("Invalid transformation")
}
The types used as input are all case classes and are defined internally within the application, for example:
case class ProductCategory(id: Long, name: String,
thumbnail: Option[String],
image:Option[String],
sequence:Int)
This approach, although suitable at the moment, doesn't feel functional or scalable when potentially more DB types are added. I also feel using asInstanceOf should be redundant as the type has already been asserted. My limited knowledge of implicits suggests they could be used instead to perform the transformation, and remove the need for the above Transform[A: TypeTag](objects:Seq[A]):Seq[Children] method altogether. Or maybe there is a different approach I should have used instead?
You can define a trait like this:
trait Transformer[A] {
def transformImpl(x: Seq[A]): Seq[Children]
}
Then you can define some instances:
object Transformer {
implicit val forProduct = new Transformer[ProductCategory] {
def transformImpl(x: Seq[ProductCategory]) = ...
}
...
}
And then finally:
def transform[A: Transformer](objects:Seq[A]): Seq[Children] =
implicitly[Transformer[A]].transformImpl(objects)
Preferably, you should define your implicit instances either in Transformer object or in objects corresponding to your category classes.
I'm not sure how your program is supposed to work exactly, nor do I know if any of your Transforms are self-made types or something you pulled from a library, however I may have a solution anyway
Something match is really good with, is case classes
So rather than manually checking the type of the input data, you could maybe wrap them all in case classes (if you need to bring data with you) or case objects (if you don't)
That way you can do something like this:
// this code assumes ProductCategory, ProductArea, etc.
// all extends the trait ProductType
def Transform(pType: ProductType): Seq[Children] = pType match {
case ProductCategory(objects) => TransformProductCategory(objects)
case ProductArea(objects) => TransformProductArea(objects)
case ProductGroup(objects) => TransformProductGroup(objects)
case ProductSubGroup(objects) => TransformProductSubGroup(objects)
}
By wrapping everything in a case class, you can specify exactly which type of data you want to bring along, and so long as they (the case classes, not the data) all inherit from the same class/trait, you should be fine
And since there's only a little handful of classes that extend ProductType you don't need the default case, because there is no default case!
Another benefit of this, is that it's infinitely expandable; just add more cases and case classes!
Note that this solution requires you to refactor your code a LOT, so bare that in mind before you throw yourself into it.
I have the following code:
sealed trait A
case class B[T](v: T) extends A
case class C[T](v: T) extends A
object Test {
def swap(a: A): A = a match {
case a: B[t] => C[t](a.v) // works!
case C[t](v) => B[t](v) // error: C[t] does not take parameters
}
}
I would expect either both cases to fail or both of them to work. What's the meaning of the error for the second case? Is there a syntax destructuring parametric case-classes?
Note: Here, 't' in lower case is essential. If it were 'T', the checker would be looking for it in the type parameters of the method.
When you do a match { case C(v) => ??? }, you actually call unapply method of the C companion object, something like this: C.unapply(a) match {Some(v) => ???}
There is only one C object, not an entire family of C[t]. There is no object you can refer to as C[Int], so case C[t](v) => doesn't make sense.
In your example, you use B[t] as a type, not as a pattern, and that's why it works. Note that while the match may succeed, you won't get anything in t, because of type erasure.
When you call C[t](a.v), then first of all, compiler erases type t anyway, and second, this is rewritten to a call to apply method on the companion object: C.apply[t](a.v). Note that the type parameter is on the method call, not on the object.
Simply put, it is not part of the language.
When used in this position, the compiler is looking for the type in the environment, as if it were a usual uppercase type. The type capturing that you are trying to do seems to only work in the case x:Y[z] => ... form of a case statement.
Type capturing in this fashion is not a well know part of the language and had me running to the Scala reference document for the details (Section 8.3). I personally find the that the distinction between upper and lowercase here not to my liking.
In your example t takes on the type of Any as the type information for the parameter is not available from A.
There are two ways of defining a method for two different classes inheriting the same trait in Scala.
sealed trait Z { def minus: String }
case class A() extends Z { def minus = "a" }
case class B() extends Z { def minus = "b" }
The alternative is the following:
sealed trait Z { def minus: String = this match {
case A() => "a"
case B() => "b"
}
case class A() extends Z
case class B() extends Z
The first method repeats the method name, whereas the second method repeats the class name.
I think that the first method is the best to use because the codes are separated. However, I found myself often using the second one for complicated methods, so that adding additional arguments can be done very easily for example like this:
sealed trait Z {
def minus(word: Boolean = false): String = this match {
case A() => if(word) "ant" else "a"
case B() => if(word) "boat" else "b"
}
case class A() extends Z
case class B() extends Z
What are other differences between those practices? Are there any bugs that are waiting for me if I choose the second approach?
EDIT:
I was quoted the open/closed principle, but sometimes, I need to modify not only the output of the functions depending on new case classes, but also the input because of code refactoring. Is there a better pattern than the first one? If I want to add the previous mentioned functionality in the first example, this would yield the ugly code where the input is repeated:
sealed trait Z { def minus(word: Boolean): String ; def minus = minus(false) }
case class A() extends Z { def minus(word: Boolean) = if(word) "ant" else "a" }
case class B() extends Z { def minus(word: Boolean) = if(word) "boat" else "b" }
I would choose the first one.
Why ? Merely to keep Open/Closed Principle.
Indeed, if you want to add another subclass, let's say case class C, you'll have to modify supertrait/superclass to insert the new condition... ugly
Your scenario has a similar in Java with template/strategy pattern against conditional.
UPDATE:
In your last scenario, you can't avoid the "duplication" of input. Indeed, parameter type in Scala isn't inferable.
It still better to have cohesive methods than blending the whole inside one method presenting as many parameters as the method union expects.
Just Imagine ten conditions in your supertrait method. What if you change inadvertently the behavior of one of each? Each change would be risked and supertrait unit tests should always run each time you modify it ...
Moreover changing inadvertently an input parameter (not a BEHAVIOR) is not "dangerous" at all. Why? because compiler would tell you that a parameter/parameter type isn't relevant any more.
And if you want to change it and do the same for every subclasses...ask to your IDE, it loves refactoring things like this in one click.
As this link explains:
Why open-closed principle matters:
No unit testing required.
No need to understand the sourcecode from an important and huge class.
Since the drawing code is moved to the concrete subclasses, it's a reduced risk to affect old functionallity when new functionality is added.
UPDATE 2:
Here a sample avoiding inputs duplication fitting your expectation:
sealed trait Z {
def minus(word: Boolean): String = if(word) whenWord else whenNotWord
def whenWord: String
def whenNotWord: String
}
case class A() extends Z { def whenWord = "ant"; def whenNotWord = "a"}
Thanks type inference :)
Personally, I'd stay away from the second approach. Each time you add a new sub class of Z you have to touch the shared minus method, potentially putting at risk the behavior tied to the existing implementations. With the first approach adding a new subclass has no potential side effect on the existing structures. There might be a little of the Open/Closed Principle in here and your second approach might violate it.
Open/Closed principle can be violated with both approaches. They are orthogonal to each other. The first one allows to easily add new type and implement required methods, it breaks Open/Closed principle if you need to add new method into hierarchy or refactor method signatures to the point that it breaks any client code. It is after all reason why default methods were added to Java8 interfaces so that old API can be extended without requiring client code to adapt.
This approach is typical for OOP.
The second approach is more typical for FP. In this case it is easy to add methods but it is hard to add new type (it breaks O/C here). It is good approach for closed hierarchies, typical example are Algebraic Data Types (ADT). Standardized protocol which is not meant to be extended by clients could be a candidate.
Languages struggle to allow to design API which would have both benefits - easy to add types as well as adding methods. This problem is called Expression Problem. Scala provides Typeclass pattern to solve this problem which allows to add functionality to existing types in ad-hoc and selective manner.
Which one is better depends on your use case.
Starting in Scala 3, you have the possibility to use trait parameters (just like classes have parameters), which simplifies things quite a lot in this case:
trait Z(x: String) { def minus: String = x }
case class A() extends Z("a")
case class B() extends Z("b")
A().minus // "a"
B().minus // "b"