When you use isInstanceOf[Class] checks, that’s an anti-pattern, as Scala has a much better way of discriminating between types. Scala has implicit parameters, with which you can describe type classes.

When C# developers try Java, one primary complaint is about the lack of reification for Java’s generics and by that they mean the ability to discriminate between different type parameters, so to differentiate between List[Int] and List[String] via isInstanceOf checks. Java and Scala do type erasure so a List[String] at runtime becomes a List[Any] .



Interestingly this complaint is not valid for Scala. Because of Scala’s expressiveness, you shouldn’t need to do isInstanceOf checks, unless it’s for interoperability or for awkward micro optimizations that have no place in high level code. Reification is a runtime construct and Scala solves the associated use cases by moving all of that at compile time, via implicit parameters.

Let’s do an exercise …

Given some piece of heavy logic, let’s say you want to describe a function that can execute a block of code, along with some finalizer, something like this:

def guarantee [ R ]( f : => R )( finalizer : => Unit ) : R = try f finally finalizer

And usage:

guarantee { println ( "Executing!" ) 1 + 1 } { println ( "Done!" ) }

Then one of your colleagues comes along and tries it with Future :

import scala.concurrent.Future import scala.concurrent.ExecutionContext.Implicits.global guarantee { Future { println ( "Executing!" ) 1 + 1 } } { println ( "Done!" ) } //=> Done! //=> Executing!

Oops! This doesn’t work, so one of you might get the bright idea to do this instead:

import scala.util.control.NonFatal def guarantee [ R ]( f : => R )( finalizer : => Unit ) : R = try { f match { // Anti-pattern case ref : Future [ _ ] => ref . transform { r => finalizer ; r } . asInstanceOf [ R ] case result => finalizer result } } catch { case NonFatal ( e ) => finalizer throw e }

This logic isn’t extensible — What happens when you’ll want to introduce logic for Java’s CompletableFuture , Monix’s Task , Cats-Effect’s IO and so on? Each type gets its own branch?

We’ve run into the expression problem and yet our R data type is not a tagged union, meaning that the set of possible values in that pattern match is endless.

The second problem is the default branch. We are assuming that, in case R is not a Future , then we are dealing with a side effectful function that executes synchronously. So one of your colleagues comes along and does this:

import monix.eval.Task guarantee { // Oh noes! Task { println ( "Executing!" ) 1 + 1 } } { println ( "Done!" ) } //=> Done!

Oops again! Now we’ve got a bug.

Type Classes to the rescue #

Let us define a type class for discriminating between types at compile-time:

trait CanGuarantee [ R ] { def guarantee ( f : => R )( finalizer : => Unit ) : R }

Now our function can look like this:

def guarantee [ R: CanGuarantee ]( f : => R )( finalizer : => Unit ) : R = implicitly [ CanGuarantee [ R ]]. guarantee ( f )( finalizer )

To get the behavior of the original sample, we can define the default instances in the companion object like this:

object CanGuarantee { // Future instance implicit def futureInstance [ A ] : CanGuarantee [ Future [ A ]] = new CanGuarantee [ Future [ A ]] { def guarantee ( f : => Future [ A ])( finalizer : => Unit ) : Future [ A ] = Future ( f ). flatten . transform { r => finalizer r } } // Default instance implicit def syncInstance [ R ] : CanGuarantee [ R ] = new CanGuarantee [ R ] { def guarantee ( f : => R )( finalizer : => Unit ) : R = try f finally finalizer } }

The upside is that now the mechanism is extensible, without modifying the original function:

final class Thunk [ A ]( val run : () => A ) object Thunk { // Extending our logic with a new data type implicit def canGuarantee [ A ] : CanGuarantee [ Thunk [ A ]] = new CanGuarantee [ Thunk [ A ]] { def guarantee ( f : => Thunk [ A ])( finalizer : => Unit ) : Thunk [ A ] = new Thunk (() => { try f . run () finally finalizer }) } }

The problem with defaults #

What happens in case you don’t define CanGuarantee[Thunk[A]] ?

guarantee { new Thunk { () => println ( "Calculating!" ) 1 + 1 } } { println ( "Done!" ) }

The syncInstance that we defined above is incorrect for Thunk . This means that we can introduce silent bugs. What should happen here?

import java.util.concurrent.CompletableFuture guarantee { CompletableFuture . runAsync { () => println ( "Running!" ) } } { println ( "Done!" ) } //=> Done! //=> Running!

This is a bug waiting to happen.

Therefore one can make the case that the default instance, if it doesn’t have the intended behavior for all data types, should not exist. But you can still provide a helper for creating one:

import scala.annotation.implicitNotFound @implicitNotFound ( """Cannot find implicit value for CanGuarantee[${R}]. If this value is synchronously calculated via an effectful function, then use CanGuarantee.synchronous to create one.""" ) trait CanGuarantee [ R ] { def guarantee ( f : => R )( finalizer : => Unit ) : R } object CanGuarantee { // No longer implicit def synchronous [ R ] : CanGuarantee [ R ] = new CanGuarantee [ R ] { def guarantee ( f : => R )( finalizer : => Unit ) : R = try f finally finalizer } // Future instance implicit def futureInstance [ A ] : CanGuarantee [ Future [ A ]] = new CanGuarantee [ Future [ A ]] { def guarantee ( f : => Future [ A ])( finalizer : => Unit ) : Future [ A ] = Future ( f ). flatten . transform { r => finalizer r } } }

Notice the usage of Scala’s @implicitNotFound annotation for providing a nice error message.

Let’s see what happens now when we try running the CompletableFuture code again:

error: Cannot find implicit value for CanGuarantee[CompletableFuture[Void]]. If this value is synchronously calculated via an effectful function, then use CanGuarantee.synchronous to create one.

That’s better. This now goes for Unit as well:

scala> guarantee { println("Executing!") } { println("Done!") } error: Cannot find implicit value for CanGuarantee[Unit]. If this value is synchronously calculated via an effectful function, then use CanGuarantee.synchronous[Unit] to create one. guarantee { println("Executing!") } { println("Done!") } ^

If you want to work with Unit , you have to create an instance for it, but notice how the error message tells you exactly what to do:

implicit val ev = CanGuarantee . synchronous [ Unit ] guarantee { println ( "Executing!" ) } { println ( "Done!" ) }

In conclusion #

Friends don’t let friends use isInstanceOf checks, because Scala has better ways of handling the related use cases.

Enjoy~