I was trying to look into trait and object in scala when it seems like we can use trait and object to do a similar task.
What should be the guiding principles on when to use trait and when to use object?
Edit:
As many of you are asking for an example
object PercentileStats {
def addPercentile(df: DataFrame): DataFrame // implementation
}
trait PercentileStats {
def addPercentile(df: DataFrame): DataFrame // implementation
}
There is a Process class which can use the object
object Process {
def doSomething(df: DataFrame): DataFrame {
PercentileStats.addPercentile(df)
}
}
We can also make it use the trait
object Process with PercentileStats {
def doSomething(df: DataFrame): DataFrame {
addPercentile(df)
}
}
I think the real question here is Where do I put stand-alone functions?
There are three options.
In the package
You can put stand-alone functions in the outer package scope. This makes them immediately available to the whole package but the name has to be meaningful across the whole package.
def addPercentile(df: DataFrame): DataFrame // implementation
In an object
You can group stand-alone functions in an object to provide a simple namespace. This means that you have to use the name of the object to access the functions, but it keeps them out of the global namespace and allows the names to be simpler:
object PercentileStats {
def add(df: DataFrame): DataFrame // implementation
}
In a trait
You can group stand-alone functions in a trait. This also removes them from the package namespace, but allows them to be accessed without a qualifier from classes that have that trait. But this also makes the method visible outside the class, and allows them to be overridden. To avoid this you should mark them protected final:
trait PercentileStats {
protected final def addPercentile(df: DataFrame): DataFrame // implementation
}
Which is best?
The choice really depends on how the function will be used. If a function is only to be used in a particular scope then it might make sense to put it in a trait, otherwise the other options are better. If there are a number of related function then grouping them in an object makes sense. One-off functions for general use can just go in the package.
Object - is a class that has exactly one instance. It is created lazily when it is referenced, like a lazy val.
As a top-level value, an object is a singleton.
Traits - are used to share interfaces and fields between classes.
Classes and objects can extend while traits cannot be instantiated and therefore have no parameters.
So, it means that if you prefer singleton type implementation with no new instance happen then use Object but if you want to inherit implementation to other class or objects then you can use trait.
Traits: are equivalent to interfaces in Java. So you can use it to define public contracts like interfaces in Java. In addition, a trait can be used to share values (beside methods) between classes extends the trait.
Objects in Scala is actually quite flexible. Example use cases include:
singletons: If you think that your objects are singletons (exactly
one instance exists in the program), you can use object.
factory: for instance, companion object of a class can be used as factory for creating instances of the class.
to share static methods: for example, common utilities can be declared in one object.
You also have to consider how you would want to use / import it.
trait Foo {
def test(): String
}
object Bar extends Foo
import Bar._
Objects enable you to import rather than mix in your class.
It is a life saver when you want to mock - with scalamock - a class that mixes a lot of traits and expose more than 22 methods that you don't really need exposed in the scope.
import scala.reflect.runtime.{universe => ru}
trait someTrait{
def getType[T: ru.TypeTag](obj: T) = ru.typeOf[T]
def reflect()={
println(getType(this)) // got someTrait type, not A type.
}
}
class A extends someTrait{
}
main(){
new A().reflect()
}
When I run main function, I got someTrait type printed out.
How can I get A type in reflect function?
Using TypeTags or ClassTags, you can't (without doing extra work in every subtype, as Ramesh's answer does). Because the compiler inserts them based on static types only.
When it sees getType(this), it first infers type parameter to getType[someTrait](this), and then turns into getType[someTrait](this)(typeTag[someTrait]). You can see A is never considered and it can't be.
As the scala document says, we cant use java reflectoin since it might cause problem.
No, Scala documentation certainly doesn't say you can't use Java reflection for this. You need to understand its limitations but exactly the same applies to Scala reflection.
I'm pretty new to Scala. I'm trying to write an abstract class whose methods will be required to be implemented on a subclass. I want to use generics to enforce that the method takes a parameter of the current class.
abstract class MySuper{
def doSomething:(MyInput[thisclass]=>MyResult)
}
class MySub extends MySuper{
override def doSomething:(MyInput[MySub]=>MyResult)
}
I know that thisclass above is invalid, but I think it kind of expresses what I want to say. Basically I want to reference the implementing class. What would be the valid way to go about this?
You can do this with a neat little trick:
trait MySuper[A <: MySuper[A]]{
def doSomething(that: A)
}
class Limited extends MySuper[Limited]{
def doSomething(that: Limited)
}
There are other approaches but I find this one works fairly well at expressing what you'd like.
I'm rather new to Scala, and I am trying to use lift-squeryl-record in Lift. Scala is 2.8.1 and Lift is 2.3. My problem is that I wanted to use (Mega)ProtoUser from Record, but it conflicts with lift-squeryl-record.
I followed the instruction of:
lift-squeryl-record example
which did not use ProtoUser, and tried to define my user like this:
trait AbstractUser[MyType <: AbstractUser[MyType]] extends
ProtoUser[MyType] with Record[MyType] with KeyedRecord[Long] {
NB: KeyedRecord is from package net.liftweb.squerylrecord, not net.liftweb.record
Then I get the following error:
overriding lazy value id in trait ProtoUser of type net.liftweb.record.field.LongField[MyType]; method id in trait KeyedRecord of type => Long needsoverride' modifier`
Because both KeyedRecord and ProtoUser define a differing id method. Since I do not control the code of neither classes/traits, is there any "Scala" way around it, like renaming one of the methods? I really don't want to have to choose between the two. :(
No you cannot rename methods in a subclass. If there are two conflicting method signatures from parent types, you will need to resort to another pattern, such as indirection through delegation ( http://en.wikipedia.org/wiki/Delegation_pattern )
trait AbstractUser[MyType <: AbstractUser[MyType]] extends ProtoUser[MyType] {
def record: Record[MyType] with KeyedRecord[Long]
}
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.