How to do this with Scala generic - scala

Currently I have couple of methods that are very similar and I would like to merge them into 1 method. Here are the 2 methods
def toInt(attrType: String, attrValue: String): Int = {
attrType match {
case "N" => attrValue.toInt
case _ => -1
}
}
def toString(attrType: String, attrValue: String): String = {
attrType match {
case "S" => attrValue
case _ => ""
}
}
I am thinking there is an easier way to do this in Scala using generic?

You could do the following:
trait Converter[T] {
def convert(attrType: String, attrValue: String): T
}
object ConverterTest {
implicit object IntConverter extends Converter[Int] {
def convert(attrType: String, attrValue: String): Int = {
attrType match {
case "N" => attrValue.toInt
case _ => -1
}
}
}
implicit object StringConverter extends Converter[String] {
def convert(attrType: String, attrValue: String): String = {
attrType match {
case "S" => attrValue
case _ => ""
}
}
}
def to[T: Converter](attrType: String, attrValue: String): T = {
implicitly[Converter[T]].convert(attrType, attrValue)
}
def main(args: Array[String]) {
println(to[String]("S", "B"))
println(to[String]("N", "B"))
println(to[Int]("S", "23"))
println(to[Int]("N", "23"))
}
}
Its more code, and I couldn't get type inferencing to work, so it is probably of limited use.
But it is a single method plus a bunch of converters that can get controlled at the call site, so you get some extra flexibility.
Is it worth the effort? Depends on the actual use case.

Related

scala use case match output depending on type

How to modify Foobar process method so I can use case match output and call run(data) once and not three times? Is it possible to set some common type for ClassA, ClassB, ClassC and if case match output is specific type then call run(data) else if unknown mode then raise exception?
This is my code:
object Foobar {
def process(someConfig: String, someVar: String, data: Seq[String]) = {
someConfig match {
case "a" => new ClassA(someVar).run(data)
case "b" => new ClassB(someVar).run(data)
case "c" => new ClassC(someVar).run(data)
case _ => throw new IllegalArgumentException("Unknown mode")
class ClassA(someVar: String) {
def run(data: Seq[String]) = {
// do some processing 1 with data & someVar
...
}
class ClassB(someVar: String) {
def run(data: Seq[String]) = {
// do some processing 2 with data & someVar
...
}
class ClassC(someVar: String) {
def run(data: Seq[String]) = {
// do some processing 3 with data & someVar
...
}
What I would do, is define a trait with def run(data: Seq[String]): Unit method, and then extend if from the other classes. Something like:
trait Letter {
def run(data: Seq[String]): Unit
}
class ClassA(someVar: String) extends Letter {
override def run(data: Seq[String]) = {
println(data)
}
}
class ClassB(someVar: String) extends Letter {
override def run(data: Seq[String]) = {
println(data)
}
}
class ClassC(someVar: String) extends Letter {
override def run(data: Seq[String]) = {
println(data)
}
}
object Foobar {
def process(someConfig: String, someVar: String, data: Seq[String]) = {
val letter = someConfig match {
case "a" => new ClassA(someVar)
case "b" => new ClassB(someVar)
case "c" => new ClassC(someVar)
case _ => throw new IllegalArgumentException("Unknown mode")
}
letter.run(data)
}
}
You can use implicit mappers for that
sealed trait Letter { def run(data: Seq[String]): Unit }
case class A(someVar: String) extends Letter { override def run(data: Seq[String]): Unit = println("A") }
case class B(someVar: String) extends Letter { override def run(data: Seq[String]): Unit = println("B") }
case class C(someVar: String) extends Letter { override def run(data: Seq[String]): Unit = println("C") }
// This can be in mappers object
implicit class ClassesMapper(someConfig: String) {
def toClass(someVar: String): Letter = {
someConfig match {
case "a" => A(someVar)
case "b" => B(someVar)
case "c" => C(someVar)
case _ => throw new IllegalArgumentException("<exception>")
}
}
}
object Foobar {
def process(someConfig: String, someVar: String, data: Seq[String]) = {
someConfig.toClass(someVar).run(data)
}
}
Foobar.process("a", "someVar", Nil)
Output: A

How to pass implicit parameter explicitly?

If we define the following function:
def methodWithImplicit(explicit: String)(implicit imp: String) = {
println(explicit + imp)
}
we can call it as follows:
methodWithImplicit("abc")("efg") //abc - explicit, efg - imp
And it works fine. Now consider the following TypeClass:
trait MyTypeClass[T] {
def accept(t: T): T
}
which is going to be used inside extractor object:
object TestExtractor {
def unapply(str: String)(implicit myTypeClass: MyTypeClass[String]): Option[String] =
if (!str.isEmpty)
Some(myTypeClass.accept(str))
else
None
}
So if we use it as follows:
implicit val myTypeClass:MyTypeClass[String] = new MyTypeClass[String] {
override def accept(t: String): Unit = t
}
"123" match {
case TestExtractor(str) => println(str)
}
It works ok. But how to pass the parameter explicitly when using with pattern matching? I tried
"123" match {
case TestExtractor(str)(myTypeClass) => println(str) //compile error
}
and
"123" match {
case TestExtractor(myTypeClass)(str) => println(str) //compile error
}
But it does not compile.
Since the left hand side seems to accept essentially nothing but trees built from stable identifiers, constant literals, and lower-case letters for variable names, I don't see any way to get closer to the desired syntax than this:
val `TestExtractor(myTypeClass)` = TestExtractor(myTypeClass)
"hello" match {
case `TestExtractor(myTypeClass)`(str) => println(str)
}
This of course requires that you define the weirdly named value TestExtractor(myTypeClass) (in backticks) right before the match-case, so you can use it as a single symbol.
Full code:
trait MyTypeClass[T] {
def accept(t: T): T
}
object TestExtractor { outer =>
def unapply(str: String)(implicit myTypeClass: MyTypeClass[String]): Option[String] =
if (!str.isEmpty)
Some(myTypeClass.accept(str))
else
None
class ExplicitTestExtractor(tc: MyTypeClass[String]) {
def unapply(t: String) = outer.unapply(t)(tc)
}
def apply(tc: MyTypeClass[String]): ExplicitTestExtractor =
new ExplicitTestExtractor(tc)
}
implicit val myTypeClass:MyTypeClass[String] = new MyTypeClass[String] {
override def accept(t: String): String = t.toUpperCase
}
val `TestExtractor(myTypeClass)` = TestExtractor(myTypeClass)
"hello" match {
case `TestExtractor(myTypeClass)`(str) => println(str)
}

Conditional Behavior With Free Monads

I'm following the tutorial here: http://typelevel.org/cats/datatypes/freemonad.html and trying to modify it to work with a cache in front of the key value store. This is what I've come up with so far but I'm getting a compiler error with valueGetOperation. I understand why I get the compile error, I just don't understand how to work around it. What's the best practice for conditional behavior when using a free monad?
import cats.data.Coproduct
import cats.free.{Free, Inject}
object KvStore {
sealed trait KvOp[A]
case class Get[T](key: String) extends KvOp[Option[T]]
case class Put[T](key: String, value: T) extends KvOp[Unit]
case class Delete[T](key: String) extends KvOp[Unit]
}
object CacheStore {
sealed trait CacheOp[A]
case class Get[T](key: String) extends CacheOp[Option[T]]
case class Put[T](key: String, value: T) extends CacheOp[Unit]
case class Delete[T](key: String) extends CacheOp[Unit]
}
type WriteThruCache[A] = Coproduct[KvStore.KvOp, CacheStore.CacheOp, A]
class KvOps[F[_]](implicit I: Inject[KvStore.KvOp, F]) {
import KvStore._
def get[T](key: String): Free[F, Option[T]] = Free.inject[KvOp, F](Get(key))
def put[T](key: String, value: T): Free[F, Unit] = Free.inject[KvOp, F](Put(key, value))
def delete[T](key: String): Free[F, Unit] = Free.inject[KvOp, F](Delete(key))
}
object KvOps {
implicit def kvOps[F[_]](implicit I: Inject[KvStore.KvOp, F]): KvOps[F] = new KvOps[F]
}
class CacheOps[F[_]](implicit I: Inject[CacheStore.CacheOp, F]) {
import CacheStore._
def get[T](key: String): Free[F, Option[T]] = Free.inject[CacheOp, F](Get(key))
def put[T](key: String, value: T): Free[F, Unit] = Free.inject[CacheOp, F](Put(key, value))
def delete[T](key: String): Free[F, Unit] = Free.inject[CacheOp, F](Delete(key))
}
object CacheOps {
implicit def cacheOps[F[_]](implicit I: Inject[CacheStore.CacheOp, F]): CacheOps[F] = new CacheOps[F]
}
def valueWriteOperation[T](implicit Kv: KvOps[WriteThruCache], Cache: CacheOps[WriteThruCache]): ((String, T) => Free[WriteThruCache, Unit]) = {
(key: String, value: T) =>
for {
_ <- Kv.put(key, value)
_ <- Cache.put(key, value)
} yield ()
}
// This is where I'm stuck
// desired behavior: If the value isn't in the cache, load it from the kv store and put it in the cache
def valueGetOperation[T](implicit Kv: KvOps[WriteThruCache], Cache: CacheOps[WriteThruCache]): ((String) => Free[WriteThruCache, Option[T]]) = {
(key: String) =>
for {
cacheOption <- Cache.get[T](key)
kvOption <- Kv.get[T](key) if cacheOption.isEmpty // value withFilter is not a member of cats.free.Free[A$A39.this.WriteThruCache,Option[T]]
} yield cacheOption.orElse(kvOption)
}
As you know in for comprehension, when you use if it is desugared by compiler to calling withFilter method, and if it's not accessible it falls back to filter method. If they are not implemented you will receive compiler error.
However you can simply use if else!
for {
booleanValue <- myfreeAlbebra.checkCondidtion(arg1, arg2)
valueToReturn <- if (booleanValue) {
myfreeAlbebra.someValue
} else {
myfreeAlbebra.someOtherValue
}
} yield valueToReturn
alternatively you can do something like:
for {
booleanValue <- myfreeAlbebra.checkCondidtion(arg1, arg2)
valueToReturnOpt <- myfreeAlbebra.someValue
fallbackValue <- myfreeAlbebra.someOtherValue
} yield valueToReturnOpt.getOrElse(fallbackValue)
The formar one will assign value to valueToReturn depending on booleanValue. As such only one branch will be interpreted. The later will evaluate both values and return one of them depending on whether or not valueToReturnOpt will be empty.
Personally I would try something like:
def valueGetOperation[T](implicit Kv: KvOps[WriteThruCache], Cache: CacheOps[WriteThruCache]): ((String) => Free[WriteThruCache, Option[T]]) = {
(key: String) =>
for {
cacheOption <- Cache.get[T](key)
returnedValue <- if (cacheOption.isEmpty) Cache.get[T](key) else Kv.get[T](key)
} yield returnedValue
}
Following Mateusz' suggestions, this is what I came up with:
def withFallback[A[_], T](loadedValue: Option[T], fallback: => Free[A, Option[T]]): Free[A, Option[T]] = {
if(loadedValue.isDefined) {
Free.pure[A, Option[T]](loadedValue)
} else {
fallback
}
}
def valueGetOperation[T](implicit Kv: KvOps[WriteThruCache], Cache: CacheOps[WriteThruCache]): ((String) => Free[WriteThruCache, Option[T]]) = {
(key: String) =>
for {
cachedOption <- Cache.get[T](key)
actualValue <- withFallback[WriteThruCache, T](cachedOption, fallback = Kv.get[T](key))
} yield actualValue
}
If there's a standard construct to implement withFallback I'd be glad to know about it.
You could also use OptionT#orElse.
import cats.data.OptionT
type KV[A] = Free[WriteThruCache, A]
def valueGetOperation[T](
implicit
Kv: KvOps[WriteThruCache],
Cache: CacheOps[WriteThruCache]
): String => KV[Option[T]] =
key => OptionT[KV, T](Cache.get[T](key)).orElse(OptionT[KV, T](Kv.get[T](key))).value
Or OptionT#orElseF :
def valueGetOperation[T](
implicit
Kv: KvOps[WriteThruCache],
Cache: CacheOps[WriteThruCache]
): String => KV[Option[T]] =
key => OptionT[KV, T](Cache.get[T](key)).orElseF(Kv.get[T](key)).value
Note that with the -Ypartial-unification flag in Scala 2.12 you don't need the KV type alias and you can write OptionT(...) instead of OptionT[KV, T](...).

Is there something like Map.keySet for a partial function in scala?

More specifically, I have:
case class Key (key: String)
abstract class abstr {
type MethodMap = PartialFunction[Key, String => Unit]
def myMap: MethodMap // abstract
def useIt (key: Key, value: String) = {
val meth = myMap(key)
meth(value)
}
def report = {
for (key <- myMap.keySet) // how to do this
println("I support "+key)
}
}
I use it like this:
class concrete extends abstr {
var one: Boolean
def method1(v: String): Unit = ???
def method2(v: String): Unit = ???
def map1: MethodMap = {
case Key("AAA") => method1
}
def map2: MethodMap = {
case Key("AAA") => method2
}
override def myMap: MethodMap = if (one) map1 else map2
}
Of course, this is somewhat simplified, but the report function is necessary.
Some history: I first had it implemented using Map but then I changed it to PartialFunction in order to support the following override def myMap: MethodMap = if (one) map1 else map2.
Any suggestion to refactor my code to support everything is also appreciated.
No. PartialFunction can be defined (and often is) on infinite sets. E.g. what do you expect report to return in these situations:
class concrete2 extends abstr {
def myMap = { case Key(_) => ??? }
}
or
class concrete2 extends abstr {
def myMap = { case Key(key) if key.length > 3 => ??? }
}
? If you have a finite list of values you are interested in, you can do
abstract class abstr {
type MethodMap = PartialFunction[Key, String => Unit]
def myMap: MethodMap // abstract
val keys: Seq[Key] = ...
def report = {
for (key <- keys if myMap.isDefined(key))
println("I support "+key)
}
}
Some history: I first had it implemented using Map but then I changed it to PartialFunction in order to support the last line in second part.
Why? This would work just as well with Map.
In your solution, is there any way to define the domain of the partial function to be the finite set keys
def f: MethodMap = { case key if keys.contains(key) => ... }
Of course, the domain isn't part of the type.

Combine two functions under the same name without overloading

Here is the code:
def transform1(f: String => String): Unit = {
val s = getString
f.andThen(putString)(s)
}
def transform2(f: String => Option[String]): Unit = {
val s = getString
f(s).foreach(putString(_))
}
How do you express these two ideas in one single function?
Method overloading does not work and seems discouraged by the community.
I didn't understand that why anyone may want this but here is a way to do it:
def transform(f: Either[(String => String), (String => Option[String])]: Unit = f match {
case Left(f) => // do transform1 here
case Right(f) => //do transform2 here
}
As I said at the begining you probably shouldn't want to do this; perhaps you should directly ask what you want.
The pattern to avoid overloading is to convert disparate arguments to a common, specific type. There could be any number of such conversions.
Not sure this is the most compelling example, however.
object X {
trait MapFlat[-A, +B] { def apply(x: A): B }
implicit class mapper[A](val f: A => A) extends MapFlat[A, A] {
override def apply(x: A) = {
val res = f(x)
println(res)
res
}
}
implicit class flatmapper[A](val f: A => Option[A]) extends MapFlat[A, Option[A]] {
override def apply(x: A) = {
val res = f(x)
res foreach println
res
}
}
def f[B](g: MapFlat[String, B]) = {
g("abc")
}
}
object Test extends App {
import X._
f((s: String) => s)
f((s: String) => Some(s))
}
One way to do it will be type classes, here's a sample -
trait Transformer[T] {
def transform(foo: String => T)
}
object Transformer {
implicit object StringTransformer extends Transformer[String] {
override def transform(foo: (String) => String): Unit = ??? // Your logic here
}
implicit object OptStringTransformer extends Transformer[Option[String]] {
override def transform(foo: (String) => Option[String]): Unit = ??? // Your logic here
}
}
class SampleClass {
def theOneTransformYouWant[T: Transformer](f: String => T) = {
implicitly[Transformer[T]].transform(f)
}
def canUseBothWays(): Unit = {
theOneTransformYouWant((s: String) => s)
theOneTransformYouWant((s: String) => Some(s))
}
}
Another way would be the magnet pattern
http://spray.io/blog/2012-12-13-the-magnet-pattern/
sealed trait TransformationMagnet {
def apply(): Unit
}
object TransformationMagnet {
implicit def fromString(f: String => String): TransformationMagnet =
new TransformationMagnet {
def apply(): Unit = ??? // Your code goes here
}
implicit def fromOptString(f: String => Option[String]): TransformationMagnet =
new TransformationMagnet {
def apply(): Unit = ??? // your code goes here
}
}
class SampleClass {
def theOneTransformYouWant(f: TransformationMagnet) = {
???
}
def hereWeUseItInBothWays(): Unit = {
theOneTransformYouWant((s: String) => s)
theOneTransformYouWant((s: String) => Some(s))
}
}
add a new parameter on the description typeOfTransform
add a conditional inside the function
if (typeOfTransform == type1){
//functionality1
}else {
//functionality2
}
Just for completeness, you can actually overload methods like this by adding implicit arguments which will always be available:
def transform(f: String => Option[String]): Unit = ...
def transform(f: String => String)(implicit d: DummyImplicit): Unit = ...