Return a class from function in Scala - scala

I need to instantiate a different class depending on a the value of a particular argument in my application. Something like:
class x { val z = 5}
class y { val z = 10}
def myClass(input:String): Class[_] = {
input match{
case "x" => x
case "y" => y
}
}
val a = new myClass("x")
Any ideas how to do this or if this is possible? It tried the above code and I get a type mismatch with the output so maybe it's as simple as specifying the output type correctly, which I'm pretty sure I'm not.
Thanks.

You should clarify what you're trying to accomplish because runtime reflection would allow you to do this, but 99.9% of the time it's the wrong way to solve your problems.
You can do something like:
trait A
case class B(value: String) extends A
case class C(value: Int) extends A
def doSomething(input: String): A = input match {
case "x" => B("Wahoo")
case "y" => C(123)
}

It's not clear what it is you are actually trying to do: on one hand, you are saying that you need to instantiate the class, on the other, your function is declared to return the Class itself, not an instance.
So, if you are trying to create an instance, something like this would work:
def myClass(input: String): AnyRef = input match {
case "x" => new x
case "y" => new y
}
Note: there are two problems with this function. First, it will throw an exception if input happens to be neither x nor y ... This is not very nice. It is a better idea to make it return an Option, and add a default to None, when input isn't matched:
def myClass(input: String): Option[_] = Option(input) collect {
case "x" => new x
case "y" => new y
}
Another problem is that you cannot do very much with the value returned by this function the way it is written, because you don't know what type it has, so, you can't access any of it's members (other than the common stuff like toString, equals etc.).
It may be a better idea to define a common trait like the other answer suggests, and narrow down the return type of the function to that trait:
trait Foo { def z: Int }
class x extends Foo { val z = 5 }
class y extends Foo { val z = 10 }
def myClass(input: String): Option[Foo] = Option(input) collect {
case "x" => new x
case "y" => new y
}
Finally, if what you wanted was to actually return the Class object, and not an instance, then you almost have it, except, you need to add a classOf keyword (it's still better to make the result optional, in case input does not match):
def myClass(input: String): Option[Class[_]] = Option(input) collect {
case "x" => classOf[x]
case "y" => classOf[y]
}
Or, better, with the type boundary:
def myClass(input: String): Option[Class[_ <: Foo]] = Option(input) collect {
case "x" => classOf[x]
case "y" => classOf[y]
}

Related

Can I avoid using asInstanceOf in a pattern match when matching a stateful subclass object?

As I was modelling expressions like Var("x") or Number(7) and writing an eval function with pattern matching, I ran into a case where I could not avoid using the ´asInstanceOf` method.
2 restrictions
I do not want to avoid pattern matching by declaring an eval method in Expr and define it in its subclasses (cf. Expression problem, I prefer pattern match).
I also do not want something like Var("x", 7).
sealed trait Expr
object Expr {
def eval(e: Expr): Int = e match {
case Number(n) => n
case Var(_) => e.asInstanceOf[Var].getValue()
}
}
case class Number(n: Int) extends Expr
case class Var(s: String) extends Expr {
var value = 0
def getValue(): Int = value
def updateValue(x: Int): Unit = {
this.value = x
}
}
val x = Var("x")
x.updateValue(1)
Expr.eval(x) // 1
When I define the second case like this: case Var(x) => Var(x).getValue(), i get Expr.eval(x) // 0. This is, because Var(x) on the right side will construct a fresh Var with value 0.
I'm ok with using asInstanceOf but in the sense of improvement, I wonder if there is a cleaner solution than using asInstanceOf, which I haven't found yet.
You can use # to bind a variable to a pattern. Use it like this:
def eval(e: Expr): Int = e match {
case Number(n) => n
case v#Var(_) => v.getValue()
}
You can also check the type of a variable in a pattern match
def eval(e: Expr): Int = e match {
case Number(n) => n
case v: Var => v.getValue()
}

Scala, pattern matching on a tuple of generic trait, checking if types are equal

I know a lot of questions exist about type erasure and pattern matching on generic types, but I could not understand what should I do in my case from answers to those, and I could not explain it better in title.
Following code pieces are simplified to present my case.
So I have a trait
trait Feature[T] {
value T
def sub(other: Feature[T]): Double
}
// implicits for int,float,double etc to Feature with sub mapped to - function
...
Then I have a class
class Data(val features: IndexedSeq[Feature[_]]) {
def sub(other: Data): IndexedSeq[Double] = {
features.zip(other.features).map {
case(e1: Feature[t], e2: Feature[y]) => e1 sub e2.asInstanceOf[Feature[t]]
}
}
}
And I have a test case like this
case class TestFeature(val value: String) extends Feature[String] {
def sub(other: Feature[String]): Double = value.length - other.length
}
val testData1 = new Data(IndexedSeq(8, 8.3f, 8.232d, TestFeature("abcd"))
val testData2 = new Data(IndexedSeq(10, 10.1f, 10.123d, TestFeature("efg"))
testData1.sub(testData2).zipWithIndex.foreach {
case (res, 0) => res should be (8 - 10)
case (res, 1) => res should be (8.3f - 10.1f)
case (res, 2) => res should be (8.232d - 10.123d)
case (res, 3) => res should be (1)
}
This somehow works. If I try sub operation with instances of Data that have different types in same index of features, I get a ClassCastException. This actually satisfies my requirements, but if possible I would like to use Option instead of throwing an exception. How can I make following code work?
class Data(val features: IndexedSeq[Feature[_]]) {
def sub(other: Data): IndexedSeq[Double] = {
features.zip(other.features).map {
// of course this does not work, just to give idea
case(e1: Feature[t], e2: Feature[y]) if t == y => e1 sub e2.asInstanceOf[Feature[t]]
}
}
}
Also I am really inexperienced in Scala, so I would like to get feedback on this type of structure. Are there another ways to do this and which way would make most sense?
Generics don't exist at runtime, and an IndexedSeq[Feature[_]] has forgotten what the type parameter is even at compile time (#Jatin's answer won't allow you to construct a Data with a list of mixed types of Feature[_]). The easiest answer might be just to catch the exception (using catching and opt from scala.util.control.Exception). But, to answer the question as written:
You could check the classes at runtime:
case (e1: Feature[t], e2: Feature[y]) if e1.value.getClass ==
e2.value.getClass => ...
Or include the type information in the Feature:
trait Feature[T] {
val value: T
val valueType: ClassTag[T] // write classOf[T] in subclasses
def maybeSub(other: Feature[_]) = other.value match {
case valueType(v) => Some(actual subtraction)
case _ => None
}
}
The more complex "proper" solution is probably to use Shapeless HList to preserve the type information in your lists:
// note the type includes the type of all the elements
val l1: Feature[Int] :: Feature[String] :: HNil = f1 :: f2 :: HNil
val l2 = ...
// a 2-argument function that's defined for particular types
// this can be applied to `Feature[T], Feature[T]` for any `T`
object subtract extends Poly2 {
implicit def caseFeatureT[T] =
at[Feature[T], Feature[T]]{_ sub _}
}
// apply our function to the given HLists, getting a HList
// you would probably inline this
// could follow up with .toList[Double]
// since the resulting HList is going to be only Doubles
def subAll[L1 <: HList, L2 <: HList](l1: L1, l2: L2)(
implicit zw: ZipWith[L1, L2, subtract.type]) =
l1.zipWith(l2)(subtract)
That way subAll can only be called for l1 and l2 all of whose elements match, and this is enforced at compile time. (If you really want to do Options you can have two ats in the subtract, one for same-typed Feature[T]s and one for different-typed Feature[_]s, but ruling it out entirely seems like a better solution)
You could do something like this:
class Data[T: TypeTag](val features: IndexedSeq[Feature[T]]) {
val t = implicitly[TypeTag[T]]
def sub[E: TypeTag](other: Data[E]): IndexedSeq[Double] = {
val e = implicitly[TypeTag[E]]
features.zip(other.features).flatMap{
case(e1, e2: Feature[y]) if e.tpe == t.tpe => Some(e1 sub e2.asInstanceOf[Feature[T]])
case _ => None
}
}
}
And then:
case class IntFeature(val value: Int) extends Feature[Int] {
def sub(other: Feature[Int]): Double = value - other.value
}
val testData3 = new Data(IndexedSeq(TestFeature("abcd")))
val testData4 = new Data(IndexedSeq(IntFeature(1)))
println(testData3.sub(testData4).zipWithIndex)
gives Vector()

Can I implement a method from a trait using a case statement?

I am trying to implement a method using a case statement, but the following code does not compile.
I am aware I can get this working by using a pattern match, but am curious as to why the case statement is incompatible as a direct implementation....
trait Calculation[Input, Result] {
def calculate(in: Input): Result
}
class CalculationImpl : Calculation[String, int] {
// missing parameter type for expanded function
// The argument types of an anonymous function must be fully known. (SLS 8.5)
def calculate = {
case "one" => 1
case "two" => 2
case s: String => 0
}
}
As a compromise, I could change the semantics of the trait so that calculate becomes a parameterless method which returns a Function1, rather than a method which takes an Input parameter and returns a Result. However, this is not ideal...
trait Calculation[Input, Result] {
def calculate: Input => Result // Works, but semantics have changed.
}
class CalculationImpl : Calculation[String, int] {
def calculate = {
case "one" => 1
case "two" => 2
case s: String => 0
}
}
(note: the above is pseudo-code - I have not tried compiling this exact code)
You just need to fix your syntax and it will work:
def calculate(s: String) = s match {
case "one" => 1
case "two" => 2
case s: String => 0
}
You can get closer to the original semantics and still cut the boilerplate by defining calculate as a function value:
trait Calculation[Input, Result] {
type F = Input => Result
val calculate: F
}
class CalculationImpl extends Calculation[String, Int] {
val calculate: F = {
case "one" => 1
case "two" => 2
case s: String => 0
}
}

Scala: Something like Option (Some, None) but with three states: Some, None, Unknown

I need to return values, and when someone asks for a value, tell them one of three things:
Here is the value
There is no value
We have no information on this value (unknown)
case 2 is subtly different than case 3. Example:
val radio = car.radioType
we know the value: return the radio type, say "pioneer"
b. there is no value: return None
c. we are missing data about this car, we don't know if it has a radio or not
I thought I might extend scala's None and create an Unknown, but that doesn't seem possible.
suggestions?
thanks!
Update:
Ideally I'd like to be able to write code like this:
car.radioType match {
case Unknown =>
case None =>
case Some(radioType : RadioType) =>
}
Here's a barebones implementation. You probably want to look at the source for the Option class for some of the bells and whistles:
package example
object App extends Application {
val x: TriOption[String] = TriUnknown
x match {
case TriSome(s) => println("found: " + s)
case TriNone => println("none")
case TriUnknown => println("unknown")
}
}
sealed abstract class TriOption[+A]
final case class TriSome[+A](x: A) extends TriOption[A]
final case object TriNone extends TriOption[Nothing]
final case object TriUnknown extends TriOption[Nothing]
Don't tell anyone I suggested this, but you could always use null for Unknown rather than writing a new class.
car.radioType match {
case null =>
case None =>
case Some(radioType : RadioType) =>
}
You can grab some stuff from Lift: the Box. It has three states, Full, Failure and Empty. Also, Empty and Failure both inherit from EmptyBox.
You can use scala.Either. Use Left for the exceptional value, and Right for the expected value which can be an Option in this case:
scala> type Result = Either[String, Option[String]]
defined type alias Result
scala> val hasValue: Result = Right(Some("pioneer"))
hasValue: Result = Right(Some(pioneer))
scala> val noValue: Result = Right(None)
noValue: Result = Right(None)
scala> val unknownValue = Left("unknown")
unknownValue: Left[java.lang.String,Nothing] = Left(unknown)
You could create your own with the three possibilities. Or as of one your car.radioType types you could have unknown, and then use guards on your case's to handle it.
If you roll your own, you should include the Product trait as well. liftweb has the Box type, which is an option close that allows for full, empty and erorr to happen.
I did something like similar to classify 3 types of lines in given file, a given line maybe, for instance, Float for header line, Long for a line in the middle (row), or String for the trailer line. Also isHeader, isRow and isTrailer can be used to know which one is. Hopefully helps:
sealed abstract class HRT[+H, +R, +T] {
val isHeader: Boolean
val isRow: Boolean
val isTrailer: Boolean
}
final case class Header[+H, +R, +T](h: H) extends HRT[H, R, T] {
override val isHeader: Boolean = true
override val isRow: Boolean = false
override val isTrailer: Boolean = false
}
final case class Row[+H, +R, +T](r: R) extends HRT[H, R, T] {
override val isHeader: Boolean = false
override val isRow: Boolean = true
override val isTrailer: Boolean = false
}
final case class Trailer[+H, +R, +T](t: T) extends HRT[H, R, T] {
override val isHeader: Boolean = false
override val isRow: Boolean = false
override val isTrailer: Boolean = true
}
object Demo {
def getEntries(): Seq[HRT[Float, Long, String]] =
List(
Header(3.14f),
Row(42),
Trailer("good bye")
)
val entries = getEntries()
entries.foreach {
case Header(f) => printf("header: %f\n", f)
case Row(l) => printf("row: %d\n", l)
case Trailer(s) => printf("trailer: %s\n", s)
}
}
With Scala 3 you can use union types like this:
object Unknown
object Empty
type MaybeRadio = RadioType | Empty.type | Unknown.type
car.radioType match
case Unknown => ???
case Empty => ???
case radioType: RadioType => ???
See https://docs.scala-lang.org/scala3/book/types-union.html

Hidden features of Scala

Locked. This question and its answers are locked because the question is off-topic but has historical significance. It is not currently accepting new answers or interactions.
What are the hidden features of Scala that every Scala developer should be aware of?
One hidden feature per answer, please.
Okay, I had to add one more. Every Regex object in Scala has an extractor (see answer from oxbox_lakes above) that gives you access to the match groups. So you can do something like:
// Regex to split a date in the format Y/M/D.
val regex = "(\\d+)/(\\d+)/(\\d+)".r
val regex(year, month, day) = "2010/1/13"
The second line looks confusing if you're not used to using pattern matching and extractors. Whenever you define a val or var, what comes after the keyword is not simply an identifier but rather a pattern. That's why this works:
val (a, b, c) = (1, 3.14159, "Hello, world")
The right hand expression creates a Tuple3[Int, Double, String] which can match the pattern (a, b, c).
Most of the time your patterns use extractors that are members of singleton objects. For example, if you write a pattern like
Some(value)
then you're implicitly calling the extractor Some.unapply.
But you can also use class instances in patterns, and that is what's happening here. The val regex is an instance of Regex, and when you use it in a pattern, you're implicitly calling regex.unapplySeq (unapply versus unapplySeq is beyond the scope of this answer), which extracts the match groups into a Seq[String], the elements of which are assigned in order to the variables year, month, and day.
Structural type definitions - i.e. a type described by what methods it supports. For example:
object Closer {
def using(closeable: { def close(): Unit }, f: => Unit) {
try {
f
} finally { closeable.close }
}
}
Notice that the type of the parameter closeable is not defined other than it has a close method
Type-Constructor Polymorphism (a.k.a. higher-kinded types)
Without this feature you can, for example, express the idea of mapping a function over a list to return another list, or mapping a function over a tree to return another tree. But you can't express this idea generally without higher kinds.
With higher kinds, you can capture the idea of any type that's parameterised with another type. A type constructor that takes one parameter is said to be of kind (*->*). For example, List. A type constructor that returns another type constructor is said to be of kind (*->*->*). For example, Function1. But in Scala, we have higher kinds, so we can have type constructors that are parameterised with other type constructors. So they're of kinds like ((*->*)->*).
For example:
trait Functor[F[_]] {
def fmap[A, B](f: A => B, fa: F[A]): F[B]
}
Now, if you have a Functor[List], you can map over lists. If you have a Functor[Tree], you can map over trees. But more importantly, if you have Functor[A] for any A of kind (*->*), you can map a function over A.
Extractors which allow you to replace messy if-elseif-else style code with patterns. I know that these are not exactly hidden but I've been using Scala for a few months without really understanding the power of them. For (a long) example I can replace:
val code: String = ...
val ps: ProductService = ...
var p: Product = null
if (code.endsWith("=")) {
p = ps.findCash(code.substring(0, 3)) //e.g. USD=, GBP= etc
}
else if (code.endsWith(".FWD")) {
//e.g. GBP20090625.FWD
p = ps.findForward(code.substring(0,3), code.substring(3, 9))
}
else {
p = ps.lookupProductByRic(code)
}
With this, which is much clearer in my opinion
implicit val ps: ProductService = ...
val p = code match {
case SyntheticCodes.Cash(c) => c
case SyntheticCodes.Forward(f) => f
case _ => ps.lookupProductByRic(code)
}
I have to do a bit of legwork in the background...
object SyntheticCodes {
// Synthetic Code for a CashProduct
object Cash extends (CashProduct => String) {
def apply(p: CashProduct) = p.currency.name + "="
//EXTRACTOR
def unapply(s: String)(implicit ps: ProductService): Option[CashProduct] = {
if (s.endsWith("=")
Some(ps.findCash(s.substring(0,3)))
else None
}
}
//Synthetic Code for a ForwardProduct
object Forward extends (ForwardProduct => String) {
def apply(p: ForwardProduct) = p.currency.name + p.date.toString + ".FWD"
//EXTRACTOR
def unapply(s: String)(implicit ps: ProductService): Option[ForwardProduct] = {
if (s.endsWith(".FWD")
Some(ps.findForward(s.substring(0,3), s.substring(3, 9))
else None
}
}
But the legwork is worth it for the fact that it separates a piece of business logic into a sensible place. I can implement my Product.getCode methods as follows..
class CashProduct {
def getCode = SyntheticCodes.Cash(this)
}
class ForwardProduct {
def getCode = SyntheticCodes.Forward(this)
}
Manifests which are a sort of way at getting the type information at runtime, as if Scala had reified types.
In scala 2.8 you can have tail-recursive methods by using the package scala.util.control.TailCalls (in fact it's trampolining).
An example:
def u(n:Int):TailRec[Int] = {
if (n==0) done(1)
else tailcall(v(n/2))
}
def v(n:Int):TailRec[Int] = {
if (n==0) done(5)
else tailcall(u(n-1))
}
val l=for(n<-0 to 5) yield (n,u(n).result,v(n).result)
println(l)
Case classes automatically mixin the Product trait, providing untyped, indexed access to the fields without any reflection:
case class Person(name: String, age: Int)
val p = Person("Aaron", 28)
val name = p.productElement(0) // name = "Aaron": Any
val age = p.productElement(1) // age = 28: Any
val fields = p.productIterator.toList // fields = List[Any]("Aaron", 28)
This feature also provides a simplified way to alter the output of the toString method:
case class Person(name: String, age: Int) {
override def productPrefix = "person: "
}
// prints "person: (Aaron,28)" instead of "Person(Aaron, 28)"
println(Person("Aaron", 28))
It's not exactly hidden, but certainly a under advertised feature: scalac -Xprint.
As a illustration of the use consider the following source:
class A { "xx".r }
Compiling this with scalac -Xprint:typer outputs:
package <empty> {
class A extends java.lang.Object with ScalaObject {
def this(): A = {
A.super.this();
()
};
scala.this.Predef.augmentString("xx").r
}
}
Notice scala.this.Predef.augmentString("xx").r, which is a the application of the implicit def augmentString present in Predef.scala.
scalac -Xprint:<phase> will print the syntax tree after some compiler phase. To see the available phases use scalac -Xshow-phases.
This is a great way to learn what is going on behind the scenes.
Try with
case class X(a:Int,b:String)
using the typer phase to really feel how useful it is.
You can define your own control structures. It's really just functions and objects and some syntactic sugar, but they look and behave like the real thing.
For example, the following code defines dont {...} unless (cond) and dont {...} until (cond):
def dont(code: => Unit) = new DontCommand(code)
class DontCommand(code: => Unit) {
def unless(condition: => Boolean) =
if (condition) code
def until(condition: => Boolean) = {
while (!condition) {}
code
}
}
Now you can do the following:
/* This will only get executed if the condition is true */
dont {
println("Yep, 2 really is greater than 1.")
} unless (2 > 1)
/* Just a helper function */
var number = 0;
def nextNumber() = {
number += 1
println(number)
number
}
/* This will not be printed until the condition is met. */
dont {
println("Done counting to 5!")
} until (nextNumber() == 5)
#switch annotation in Scala 2.8:
An annotation to be applied to a match
expression. If present, the compiler
will verify that the match has been
compiled to a tableswitch or
lookupswitch, and issue an error if it
instead compiles into a series of
conditional expressions.
Example:
scala> val n = 3
n: Int = 3
scala> import annotation.switch
import annotation.switch
scala> val s = (n: #switch) match {
| case 3 => "Three"
| case _ => "NoThree"
| }
<console>:6: error: could not emit switch for #switch annotated match
val s = (n: #switch) match {
Dunno if this is really hidden, but I find it quite nice.
Typeconstructors that take 2 type parameters can be written in infix notation
object Main {
class FooBar[A, B]
def main(args: Array[String]): Unit = {
var x: FooBar[Int, BigInt] = null
var y: Int FooBar BigInt = null
}
}
Scala 2.8 introduced default and named arguments, which made possible the addition of a new "copy" method that Scala adds to case classes. If you define this:
case class Foo(a: Int, b: Int, c: Int, ... z:Int)
and you want to create a new Foo that's like an existing Foo, only with a different "n" value, then you can just say:
foo.copy(n = 3)
in scala 2.8 you can add #specialized to your generic classes/methods. This will create special versions of the class for primitive types (extending AnyVal) and save the cost of un-necessary boxing/unboxing :
class Foo[#specialized T]...
You can select a subset of AnyVals :
class Foo[#specialized(Int,Boolean) T]...
Extending the language. I always wanted to do something like this in Java (couldn't). But in Scala I can have:
def timed[T](thunk: => T) = {
val t1 = System.nanoTime
val ret = thunk
val time = System.nanoTime - t1
println("Executed in: " + time/1000000.0 + " millisec")
ret
}
and then write:
val numbers = List(12, 42, 3, 11, 6, 3, 77, 44)
val sorted = timed { // "timed" is a new "keyword"!
numbers.sortWith(_<_)
}
println(sorted)
and get
Executed in: 6.410311 millisec
List(3, 3, 6, 11, 12, 42, 44, 77)
You can designate a call-by-name parameter (EDITED: this is different then a lazy parameter!) to a function and it will not be evaluated until used by the function (EDIT: in fact, it will be reevaluated every time it is used). See this faq for details
class Bar(i:Int) {
println("constructing bar " + i)
override def toString():String = {
"bar with value: " + i
}
}
// NOTE the => in the method declaration. It indicates a lazy paramter
def foo(x: => Bar) = {
println("foo called")
println("bar: " + x)
}
foo(new Bar(22))
/*
prints the following:
foo called
constructing bar 22
bar with value: 22
*/
You can use locally to introduce a local block without causing semicolon inference issues.
Usage:
scala> case class Dog(name: String) {
| def bark() {
| println("Bow Vow")
| }
| }
defined class Dog
scala> val d = Dog("Barnie")
d: Dog = Dog(Barnie)
scala> locally {
| import d._
| bark()
| bark()
| }
Bow Vow
Bow Vow
locally is defined in "Predef.scala" as:
#inline def locally[T](x: T): T = x
Being inline, it does not impose any additional overhead.
Early Initialization:
trait AbstractT2 {
println("In AbstractT2:")
val value: Int
val inverse = 1.0/value
println("AbstractT2: value = "+value+", inverse = "+inverse)
}
val c2c = new {
// Only initializations are allowed in pre-init. blocks.
// println("In c2c:")
val value = 10
} with AbstractT2
println("c2c.value = "+c2c.value+", inverse = "+c2c.inverse)
Output:
In AbstractT2:
AbstractT2: value = 10, inverse = 0.1
c2c.value = 10, inverse = 0.1
We instantiate an anonymous inner
class, initializing the value field
in the block, before the with
AbstractT2 clause. This guarantees
that value is initialized before the
body of AbstractT2 is executed, as
shown when you run the script.
You can compose structural types with the 'with' keyword
object Main {
type A = {def foo: Unit}
type B = {def bar: Unit}
type C = A with B
class myA {
def foo: Unit = println("myA.foo")
}
class myB {
def bar: Unit = println("myB.bar")
}
class myC extends myB {
def foo: Unit = println("myC.foo")
}
def main(args: Array[String]): Unit = {
val a: A = new myA
a.foo
val b: C = new myC
b.bar
b.foo
}
}
placeholder syntax for anonymous functions
From The Scala Language Specification:
SimpleExpr1 ::= '_'
An expression (of syntactic category Expr) may contain embedded underscore symbols _ at places where identifiers are legal. Such an expression represents an anonymous function where subsequent occurrences of underscores denote successive parameters.
From Scala Language Changes:
_ + 1 x => x + 1
_ * _ (x1, x2) => x1 * x2
(_: Int) * 2 (x: Int) => x * 2
if (_) x else y z => if (z) x else y
_.map(f) x => x.map(f)
_.map(_ + 1) x => x.map(y => y + 1)
Using this you could do something like:
def filesEnding(query: String) =
filesMatching(_.endsWith(query))
Implicit definitions, particularly conversions.
For example, assume a function which will format an input string to fit to a size, by replacing the middle of it with "...":
def sizeBoundedString(s: String, n: Int): String = {
if (n < 5 && n < s.length) throw new IllegalArgumentException
if (s.length > n) {
val trailLength = ((n - 3) / 2) min 3
val headLength = n - 3 - trailLength
s.substring(0, headLength)+"..."+s.substring(s.length - trailLength, s.length)
} else s
}
You can use that with any String, and, of course, use the toString method to convert anything. But you could also write it like this:
def sizeBoundedString[T](s: T, n: Int)(implicit toStr: T => String): String = {
if (n < 5 && n < s.length) throw new IllegalArgumentException
if (s.length > n) {
val trailLength = ((n - 3) / 2) min 3
val headLength = n - 3 - trailLength
s.substring(0, headLength)+"..."+s.substring(s.length - trailLength, s.length)
} else s
}
And then, you could pass classes of other types by doing this:
implicit def double2String(d: Double) = d.toString
Now you can call that function passing a double:
sizeBoundedString(12345.12345D, 8)
The last argument is implicit, and is being passed automatically because of the implicit de declaration. Furthermore, "s" is being treated like a String inside sizeBoundedString because there is an implicit conversion from it to String.
Implicits of this type are better defined for uncommon types to avoid unexpected conversions. You can also explictly pass a conversion, and it will still be implicitly used inside sizeBoundedString:
sizeBoundedString(1234567890L, 8)((l : Long) => l.toString)
You can also have multiple implicit arguments, but then you must either pass all of them, or not pass any of them. There is also a shortcut syntax for implicit conversions:
def sizeBoundedString[T <% String](s: T, n: Int): String = {
if (n < 5 && n < s.length) throw new IllegalArgumentException
if (s.length > n) {
val trailLength = ((n - 3) / 2) min 3
val headLength = n - 3 - trailLength
s.substring(0, headLength)+"..."+s.substring(s.length - trailLength, s.length)
} else s
}
This is used exactly the same way.
Implicits can have any value. They can be used, for instance, to hide library information. Take the following example, for instance:
case class Daemon(name: String) {
def log(msg: String) = println(name+": "+msg)
}
object DefaultDaemon extends Daemon("Default")
trait Logger {
private var logd: Option[Daemon] = None
implicit def daemon: Daemon = logd getOrElse DefaultDaemon
def logTo(daemon: Daemon) =
if (logd == None) logd = Some(daemon)
else throw new IllegalArgumentException
def log(msg: String)(implicit daemon: Daemon) = daemon.log(msg)
}
class X extends Logger {
logTo(Daemon("X Daemon"))
def f = {
log("f called")
println("Stuff")
}
def g = {
log("g called")(DefaultDaemon)
}
}
class Y extends Logger {
def f = {
log("f called")
println("Stuff")
}
}
In this example, calling "f" in an Y object will send the log to the default daemon, and on an instance of X to the Daemon X daemon. But calling g on an instance of X will send the log to the explicitly given DefaultDaemon.
While this simple example can be re-written with overload and private state, implicits do not require private state, and can be brought into context with imports.
Maybe not too hidden, but I think this is useful:
#scala.reflect.BeanProperty
var firstName:String = _
This will automatically generate a getter and setter for the field that matches bean convention.
Further description at developerworks
Implicit arguments in closures.
A function argument can be marked as implicit just as with methods. Within the scope of the body of the function the implicit parameter is visible and eligible for implicit resolution:
trait Foo { def bar }
trait Base {
def callBar(implicit foo: Foo) = foo.bar
}
object Test extends Base {
val f: Foo => Unit = { implicit foo =>
callBar
}
def test = f(new Foo {
def bar = println("Hello")
})
}
Build infinite data structures with Scala's Streams :
http://www.codecommit.com/blog/scala/infinite-lists-for-the-finitely-patient
Result types are dependent on implicit resolution. This can give you a form of multiple dispatch:
scala> trait PerformFunc[A,B] { def perform(a : A) : B }
defined trait PerformFunc
scala> implicit val stringToInt = new PerformFunc[String,Int] {
def perform(a : String) = 5
}
stringToInt: java.lang.Object with PerformFunc[String,Int] = $anon$1#13ccf137
scala> implicit val intToDouble = new PerformFunc[Int,Double] {
def perform(a : Int) = 1.0
}
intToDouble: java.lang.Object with PerformFunc[Int,Double] = $anon$1#74e551a4
scala> def foo[A, B](x : A)(implicit z : PerformFunc[A,B]) : B = z.perform(x)
foo: [A,B](x: A)(implicit z: PerformFunc[A,B])B
scala> foo("HAI")
res16: Int = 5
scala> foo(1)
res17: Double = 1.0
Scala's equivalent of Java double brace initializer.
Scala allows you to create an anonymous subclass with the body of the class (the constructor) containing statements to initialize the instance of that class.
This pattern is very useful when building component-based user interfaces (for example Swing , Vaadin) as it allows to create UI components and declare their properties more concisely.
See http://spot.colorado.edu/~reids/papers/how-scala-experience-improved-our-java-development-reid-2011.pdf for more information.
Here is an example of creating a Vaadin button:
val button = new Button("Click me"){
setWidth("20px")
setDescription("Click on this")
setIcon(new ThemeResource("icons/ok.png"))
}
Excluding members from import statements
Suppose you want to use a Logger that contains a println and a printerr method, but you only want to use the one for error messages, and keep the good old Predef.println for standard output. You could do this:
val logger = new Logger(...)
import logger.printerr
but if logger also contains another twelve methods that you would like to import and use, it becomes inconvenient to list them. You could instead try:
import logger.{println => donotuseprintlnt, _}
but this still "pollutes" the list of imported members. Enter the über-powerful wildcard:
import logger.{println => _, _}
and that will do just the right thing™.
require method (defined in Predef) that allow you to define additional function constraints that would be checked during run-time. Imagine that you developing yet another twitter client and you need to limit tweet length up to 140 symbols. Moreover you can't post empty tweet.
def post(tweet: String) = {
require(tweet.length < 140 && tweet.length > 0)
println(tweet)
}
Now calling post with inappropriate length argument will cause an exception:
scala> post("that's ok")
that's ok
scala> post("")
java.lang.IllegalArgumentException: requirement failed
at scala.Predef$.require(Predef.scala:145)
at .post(<console>:8)
scala> post("way to looooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooong tweet")
java.lang.IllegalArgumentException: requirement failed
at scala.Predef$.require(Predef.scala:145)
at .post(<console>:8)
You can write multiple requirements or even add description to each:
def post(tweet: String) = {
require(tweet.length > 0, "too short message")
require(tweet.length < 140, "too long message")
println(tweet)
}
Now exceptions are verbose:
scala> post("")
java.lang.IllegalArgumentException: requirement failed: too short message
at scala.Predef$.require(Predef.scala:157)
at .post(<console>:8)
One more example is here.
Bonus
You can perform an action every time requirement fails:
scala> var errorcount = 0
errorcount: Int = 0
def post(tweet: String) = {
require(tweet.length > 0, {errorcount+=1})
println(tweet)
}
scala> errorcount
res14: Int = 0
scala> post("")
java.lang.IllegalArgumentException: requirement failed: ()
at scala.Predef$.require(Predef.scala:157)
at .post(<console>:9)
...
scala> errorcount
res16: Int = 1
Traits with abstract override methods are a feature in Scala that is as not widely advertised as many others. The intend of methods with the abstract override modifier is to do some operations and delegating the call to super. Then these traits have to be mixed-in with concrete implementations of their abstract override methods.
trait A {
def a(s : String) : String
}
trait TimingA extends A {
abstract override def a(s : String) = {
val start = System.currentTimeMillis
val result = super.a(s)
val dur = System.currentTimeMillis-start
println("Executed a in %s ms".format(dur))
result
}
}
trait ParameterPrintingA extends A {
abstract override def a(s : String) = {
println("Called a with s=%s".format(s))
super.a(s)
}
}
trait ImplementingA extends A {
def a(s: String) = s.reverse
}
scala> val a = new ImplementingA with TimingA with ParameterPrintingA
scala> a.a("a lotta as")
Called a with s=a lotta as
Executed a in 0 ms
res4: String = sa attol a
While my example is really not much more than a poor mans AOP, I used these Stackable Traits much to my liking to build Scala interpreter instances with predefined imports, custom bindings and classpathes. The Stackable Traits made it possible to create my factory along the lines of new InterpreterFactory with JsonLibs with LuceneLibs and then have useful imports and scope varibles for the users scripts.