Is it possible to curry the other way around in Scala? - scala

Let's assume this function:
def autoClosing(f: {def close();})(t: =>Unit) = {
t
f.close()
}
and this snippet:
val a = autoClosing(new X)(_)
a {
println("before close")
}
is it possible to curry the first part? Something like:
val a = autoClosing(_) { println("before close") }
so that I could send the objects on which close should be performed, and have the same block executed on them?

Yes, the snippet you have given works, as long as you give the type of the placeholder character.
Therefore, the code you are looking for is:
val a = autoClosing(_: {def close();}) { println("before close") }
which compiles and works as expected :).
A couple of notes:
You can make your life easier if you define a type alias for an AnyRef type having a close method, something like type Closeable = AnyRef {def close()}, or an appropriate interface.
The code snippet autoClosing(_: Closeable){ ... } is actually equivalent to the following expanded anonymous function: c: Closeable => autoClosing(c){ ... }. The wildcard character is just shorthand for a partially applied function. You need to give the type of the _ as the type inferer unfortunately cannot infer the type in this case.
Hope it helps,
-- Flaviu Cipcigan

Alternatively you can flip the parameters:
def flip[A1, A2, B](f: A1 => A2 => B): A2 => A1 => B = x1 => x2 => f(x2)(x1)
In your case:
val a = flip(autoClosing){ println("before close") }
Edit:
I've added some braces to help the human parser:
def flip[A1, A2, B](f: (A1 => (A2 => B))): (A2 => (A1 => B)) = {
x1 => (x2 => f(x2)(x1))
}
Flip converts a function (A1 => (A2 => B)) to (A2 => (A1 => B)).
scala> def x(x1 : Int)(x2 : Long) = 1.0 * x1 / x2
x: (Int)(Long)Double
scala> val f = flip(x)
f: (Long) => (Int) => Double = <function>
scala> val g = f(1)
g: (Int) => Double = <function>
scala> val h = g(2)
h: Double = 2.0
scala> x(1)(2)
res0: Double = 0.5

I'm happy to see so many people answering Scala questions nowadays. It does make it harder for me to come up with something, however. Here's an alternative to Flaviu's solution.
val a: {def close();} => Unit = autoClosing(_) { println("before close") }
Of course, the proper solution is to define autoClosing in a way compatible with how you are going to use it.

Related

How do I chain calls that take blocks as inputs?

Say I have these declarations:
val f1 = EventFilter.info(pattern = s"starting calls: three_step.ps, three_step.ps2, three_step.ps3", occurrences = 1)
val f2 = EventFilter.info(pattern = s"starting calls: three_step.cgrep, three_step.wc", occurrences = 1)
val f = Seq(f1, f2)
Right now I can do this:
f1.intercept { f2.intercept {
... Some code here ...
}}
However, I want that first line to be expressed as a function of val f = Seq(f1, f2) rather than of f1 and f2 directly. I'm not sure how to express this but I want to be able to do this for any Seq[EventFilter] objects
I'm assuming that intercept takes in and returns the same type here, since that's the only way to chain functions in this way.
Most generally, you can use a foldLeft or foldRight to accomplish this sort of chaining.
eventFilters.foldLeft(startingValue) {
case (acc, next) => next.intercept(acc)
}
You might also be interested in Future.chain[T], which chains together a sequence of functions T => T. If you would want to use that, you need to make your Seq[EventFilter] into a Seq[Foo => Foo] (where Foo is the parameter/return type of intercept):
val interceptFuncs = eventFilters.map(_.intercept _) //Seq[Foo => Foo]
Function.chain(interceptFuncs)(startingValue)
This should work in scalaz:
implicit def endofunctionMonoid[A] = new Monoi[Function1[A, A]] {
def append(f1: Function1[A, A], f2: => Function1[A, A]): Function1[A, A] =
f1 _ compose f2 _
def zero: Function1[A, A] = a => a
}
val fs = List(f1, f2) // event filters
fs.foldMap { _.intercept _ } // map the list to Function1s and accumulate via the semigroup operation.

Apply several transformation functions to string

Suppose I have 2 methods:
def a(s: String) = s + "..."
def b(s: String) = s + ",,,"
And I want to create 3rd method which will call both methods:
def c (s: String) = a(b(s))
How I can do it in idiomatic Scala way?
I think it's better to aggregate this functions into some List and then sequentially apply them:
List(a_, b_)
I think it's better to aggregate this functions into some List and
then sequentially apply them.
You get some help by specifying an expected type:
scala> val fs: List[String => String] = List(a,b)
fs: List[String => String] = List(<function1>, <function1>)
scala> fs.foldLeft("something")((s,f) => f(s))
res0: String = something...,,,
Here is how you can combine a set of functions into one:
// a() and b() are as defined in the question
// the following is equivalent to newfunc(x) = b(a(x))
val newFunc: String => String = List( a _, b _).reduce( _ andThen _ )
You can even create a generic function to combine them:
def functionChaining[A]( functions: A => A *): A => A = functions.reduce( _ andThen _ )
or using foldLeft:
def functionChaining[A]( functions: A => A *): A => A = functions.foldLeft( (x:A) => x )( _ andThen _ )
Here is an example of how to use this on the REPL:
scala> val newFunc: String => String = functionChaining( (x:String) => x + "---", (x:String) => x * 4)
scala> newFunc("|")
res12: String = |---|---|---|---
Many answers use andThen, but that will be give you
b(a(s))
Given that you want
a(b(s))
compose is the way to go (well, that or reversing the list, but what's the point?)
def c(s: String) = List[String => String](a, b).reduce(_ compose _)(s)
// or alternatively
def c(s: String) = List(a _, b _).reduce(_ compose _)(s)
As a result
c("foo") // foo,,,...
Now, speaking of what's idiomatic, I believe that
a(b(s))
is more idiomatic and readable than
List(a _, b _).reduce(_ compose _)(s)
This clearly depends on the number of functions you're composing. If you were to have
a(b(c(d(e(f(g(h(s))))))))
then
List[String => String](a, b, c, d, e, f, g, h).reduce(_ compose _)(s)
is probably neater and more idiomatic as well.
If you really think you need to do this:
val c = a _ andThen b
// (The signature is:)
val c:(String)=>String = a _ andThen b
or, more obviously:
def d(s:String) = a _ andThen b
If chained application is preferred then the below works. Caveats - Implicit syntax is a bit ugly; This being a structural type uses reflection.
object string {
implicit def aPimp(s: String) = new {
def a = "(a- " + s + " -a)"
}
implicit def bPimp(s: String) = new {
def b = "(b- " + s + " -b)"
}
}
scala> import string._
scala> "xyz".a.b
res0: String = (b- (a- xyz -a) -b)
scala> "xyz".b.a
res1: String = (a- (b- xyz -b) -a)
In my opinion, if not for the ugly syntax, this would be idiomatic scala.

Assign an operator to a variable in Scala

Given this spinet of code in Scala:
val mapMerge : (Map[VertexId, Factor], Map[VertexId, Factor]) => Map[VertexId, Factor] = (d1, d2) => d1 ++ d2
That can be shortened to:
val mapMerge : (Map[VertexId, Factor], Map[VertexId, Factor]) => Map[VertexId, Factor] = _ ++ _
What actually the code does is renaming the operator ++ of Map[VertexId, Factor] and therefore: Is there a way to assign that operator to the variable? Like in this imaginary example:
val mapMerge : (Map[VertexId, Factor], Map[VertexId, Factor]) => Map[VertexId, Factor] = Map.++
And probably with type inference it would enough to write
val mapMerge = Map[VertexId,Factor].++
Thanks
Unfortunately, no, because the "operators" in Scala are instance methods — not functions from a typeclass, like in Haskell.
Whey you write _ ++ _, you are creating a new 2-argument function(lambda) with unnamed parameters. This is equivalent to (a, b) => a ++ b, which is in turn equivalent to (a, b) => a.++(b), but not to (a, b) => SomeClass.++(a, b).
You can emulate typeclasses by using implicit arguments (see "typeclasses in scala" presentation)
You can pass "operators" like functions — which are not really operators. And you can have operators which look the same. See this example:
object Main {
trait Concat[A] { def ++ (x: A, y: A): A }
implicit object IntConcat extends Concat[Int] {
override def ++ (x: Int, y: Int): Int = (x.toString + y.toString).toInt
}
implicit class ConcatOperators[A: Concat](x: A) {
def ++ (y: A) = implicitly[Concat[A]].++(x, y)
}
def main(args: Array[String]): Unit = {
val a = 1234
val b = 765
val c = a ++ b // Instance method from ConcatOperators — can be used with infix notation like other built-in "operators"
println(c)
val d = highOrderTest(a, b)(IntConcat.++) // 2-argument method from the typeclass instance
println(d)
// both calls to println print "1234765"
}
def highOrderTest[A](x: A, y: A)(fun: (A, A) => A) = fun(x, y)
}
Here we define Concat typeclass and create an implementation for Int and we use operator-like name for the method in typeclass.
Because you can implement a typeclass for any type, you can use such trick with any type — but that would require writing quite some supporting code, and sometimes it is not worth the result.

Match Value with Function based on Type

Suppose I have a list of functions as so:
val funcList = List(func1: A => T, func2: B => T, func2: C => T)
(where func1, et al. are defined elsewhere)
I want to write a method that will take a value and match it to the right function based on exact type (match a: A with func1: A => T) or throw an exception if there is no matching function.
Is there a simple way to do this?
This is similar to what a PartialFunction does, but I am not able to change the list of functions in funcList to PartialFunctions. I am thinking I have to do some kind of implicit conversion of the functions to a special class that knows the types it can handle and is able to pattern match against it (basically promoting those functions to a specialized PartialFunction). However, I can't figure out how to identify the "domain" of each function.
Thank you.
You cannot identify the domain of each function, because they are erased at runtime. Look up erasure if you want more information, but the short of it is that the information you want does not exist.
There are ways around type erasure, and you'll find plenty discussions on Stack Overflow itself. Some of them come down to storing the type information somewhere as a value, so that you can match on that.
Another possible solution is to simply forsake the use of parameterized types (generics in Java parlance) for your own customized types. That is, doing something like:
abstract class F1 extends (A => T)
object F1 {
def apply(f: A => T): F1 = new F1 {
def apply(n: A): T = f(n)
}
}
And so on. Since F1 doesn't have type parameters, you can match on it, and you can create functions of this type easily. Say both A and T are Int, then you could do this, for example:
F1(_ * 2)
The usual answer to work around type erasure is to use the help of manifests. In your case, you can do the following:
abstract class TypedFunc[-A:Manifest,+R:Manifest] extends (A => R) {
val retType: Manifest[_] = manifest[R]
val argType: Manifest[_] = manifest[A]
}
object TypedFunc {
implicit def apply[A:Manifest, R:Manifest]( f: A => R ): TypedFunc[A, R] = {
f match {
case tf: TypedFunc[A, R] => tf
case _ => new TypedFunc[A, R] { final def apply( arg: A ): R = f( arg ) }
}
}
}
def applyFunc[A, R, T >: A : Manifest]( funcs: Traversable[TypedFunc[A,R]] )( arg: T ): R = {
funcs.find{ f => f.argType <:< manifest[T] } match {
case Some( f ) => f( arg.asInstanceOf[A] )
case _ => sys.error("Could not find function with argument matching type " + manifest[T])
}
}
val func1 = { s: String => s.length }
val func2 = { l: Long => l.toInt }
val func3 = { s: Symbol => s.name.length }
val funcList = List(func1: TypedFunc[String,Int], func2: TypedFunc[Long, Int], func3: TypedFunc[Symbol, Int])
Testing in the REPL:
scala> applyFunc( funcList )( 'hello )
res22: Int = 5
scala> applyFunc( funcList )( "azerty" )
res23: Int = 6
scala> applyFunc( funcList )( 123L )
res24: Int = 123
scala> applyFunc( funcList )( 123 )
java.lang.RuntimeException: Could not find function with argument matching type Int
at scala.sys.package$.error(package.scala:27)
at .applyFunc(<console>:27)
at .<init>(<console>:14)
...
I think you're misunderstanding how a List is typed. List takes a single type parameter, which is the type of all the elements of the list. When you write
val funcList = List(func1: A => T, func2: B => T, func2: C => T)
the compiler will infer a type like funcList : List[A with B with C => T].
This means that each function in funcList takes a parameter that is a member of all of A, B, and C.
Apart from this, you can't (directly) match on function types due to type erasure.
What you could instead do is match on a itself, and call the appropriate function for the type:
a match {
case x : A => func1(x)
case x : B => func2(x)
case x : C => func3(x)
case _ => throw new Exception
}
(Of course, A, B, and C must remain distinct after type-erasure.)
If you need it to be dynamic, you're basically using reflection. Unfortunately Scala's reflection facilities are in flux, with version 2.10 released a few weeks ago, so there's less documentation for the current way of doing it; see How do the new Scala TypeTags improve the (deprecated) Manifests?.

Why put a generic type next to a function?

When I look at Scala libraries I see code like this. Why put test [A] .
def test[A](block : Int => Unit) : Unit = {
block(10)
}
test { u =>
println(u)
}
This is just as valid I suppose. It runs the same way.
def test(block : Int => Unit) : Unit = {
block(10)
}
I've just been curious what the reasoning(or design pattern) is behind it. Thanks.
The type parameter A makes no sense here because it is not used.
def test[A](block: Int => A): A = block(10)
Here A specifies the return type.
When there a generic type next to the function, it means that the function is a generic function.
The following is a very simple example:
// generic functions which returns type of `A`
def test1[A](x: A) = x
def test2[A](x: => A) = { println("Hello"); x }
val x1 = test1(1)
// x1: Int = 1
val x2 = test1("Hello World")
// x2: java.lang.String = Hello World
val x3 = test2(123.4)
// Hello
// x3: Double = 123.4
val x4 = test2("Test2")
// Hello
// x4: java.lang.String = Test2
As you can see, the return type of test1 and test2 are determined by the type of their arguments.
The following is another use case.
// We could implement `map` function ourself.
// We don't care about what type of List contains,
// so we make it a generic function.
def map[A, B](xs: List[A], f: A => B): List[B] = {
var result: List[B] = Nil
for (i <- xs) {
result ++= List(f(i))
}
result
}
// Now use can map any type of List to another List.
map(List("1", "2", "3"), (x: String) => x.toInt)
//res1: List[Int] = List(1, 2, 3)