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Seamless Java Interop

Scala runs on the JVM, so Java and Scala stacks can be freely mixed for totally seamless integration.

Type Inference

So the type system doesn’t feel so static. Don’t work for the type system. Let the type system work for you!

Concurrency & Distribution

Use data-parallel operations on collections, use actors for concurrency and distribution, or futures for asynchronous programming.

class Author(val firstName: String,
    val lastName: String) extends Comparable[Author] {

  override def compareTo(that: Author) = {
    val lastNameComp = this.lastName compareTo that.lastName
    if (lastNameComp != 0) lastNameComp
    else this.firstName compareTo that.firstName

object Author {
  def loadAuthorsFromFile(file: List[Author] = ???
import static scala.collection.JavaConversions.asJavaCollection;

public class App {
    public List<Author> loadAuthorsFromFile(File file) {
        return new ArrayList<Author>(asJavaCollection(

    public void sortAuthors(List<Author> authors) {

    public void displaySortedAuthors(File file) {
        List<Author> authors = loadAuthorsFromFile(file);
        for (Author author : authors) {
                author.lastName() + ", " + author.firstName());

Combine Scala and Java seamlessly

Scala classes are ultimately JVM classes. You can create Java objects, call their methods and inherit from Java classes transparently from Scala. Similarly, Java code can reference Scala classes and objects.

In this example, the Scala class Author implements the Java interface Comparable<T> and works with Java Files. The Java code uses a method from the companion object Author, and accesses fields of the Author class. It also uses JavaConversions to convert between Scala collections and Java collections.

Type inference
scala> class Person(val name: String, val age: Int) {
     |   override def toString = s"$name ($age)"
     | }
defined class Person

scala> def underagePeopleNames(persons: List[Person]) = {
     |   for (person <- persons; if person.age < 18)
     |     yield
     | }
underagePeopleNames: (persons: List[Person])List[String]

scala> def createRandomPeople() = {
     |   val names = List("Alice", "Bob", "Carol",
     |       "Dave", "Eve", "Frank")
     |   for (name <- names) yield {
     |     val age = (Random.nextGaussian()*8 + 20).toInt
     |     new Person(name, age)
     |   }
     | }
createRandomPeople: ()List[Person]

scala> val people = createRandomPeople()
people: List[Person] = List(Alice (16), Bob (16), Carol (19), Dave (18), Eve (26), Frank (11))

scala> underagePeopleNames(people)
res1: List[String] = List(Alice, Bob, Frank)

Let the compiler figure out the types for you

The Scala compiler is smart about static types. Most of the time, you need not tell it the types of your variables. Instead, its powerful type inference will figure them out for you.

In this interactive REPL session (Read-Eval-Print-Loop), we define a class and two functions. You can observe that the compiler infers the result types of the functions automatically, as well as all the intermediate values.

val x = Future { someExpensiveComputation() }
val y = Future { someOtherExpensiveComputation() }
val z = for (a <- x; b <- y) yield a*b
for (c <- z) println("Result: " + c)
println("Meanwhile, the main thread goes on!")

Go Concurrent or Distributed with Futures & Promises

In Scala, futures and promises can be used to process data asynchronously, making it easier to parallelize or even distribute your application.

In this example, the Future{} construct evaluates its argument asynchronously, and returns a handle to the asynchronous result as a Future[Int]. For-comprehensions can be used to register new callbacks (to post new things to do) when the future is completed, i.e., when the computation is finished. And since all this is executed asynchronously, without blocking, the main program thread can continue doing other work in the meantime.


Combine the flexibility of Java-style interfaces with the power of classes. Think principled multiple-inheritance.

Pattern Matching

Think “switch” on steroids. Match against class hierarchies, sequences, and more.

Higher-order functions

Functions are first-class objects. Compose them with guaranteed type safety. Use them anywhere, pass them to anything.

abstract class Spacecraft {
  def engage(): Unit
trait CommandoBridge extends Spacecraft {
  def engage(): Unit = {
    for (_ <- 1 to 3)
  def speedUp(): Unit
trait PulseEngine extends Spacecraft {
  val maxPulse: Int
  var currentPulse: Int = 0
  def speedUp(): Unit = {
    if (currentPulse < maxPulse)
      currentPulse += 1
class StarCruiser extends Spacecraft
                     with CommandoBridge
                     with PulseEngine {
  val maxPulse = 200

Flexibly Combine Interface & Behavior

In Scala, multiple traits can be mixed into a class to combine their interface and their behavior.

Here, a StarCruiser is a Spacecraft with a CommandoBridge that knows how to engage the ship (provided a means to speed up) and a PulseEngine that specifies how to speed up.

Switch on the structure of your data

In Scala, case classes are used to represent structural data types. They implicitly equip the class with meaningful toString, equals and hashCode methods, as well as the ability to be deconstructed with pattern matching.

In this example, we define a small set of case classes that represent binary trees of integers (the generic version is omitted for simplicity here). In inOrder, the match construct chooses the right branch, depending on the type of t, and at the same time deconstructs the arguments of a Node.

Pattern matching
// Define a set of case classes for representing binary trees.
sealed abstract class Tree
case class Node(elem: Int, left: Tree, right: Tree) extends Tree
case object Leaf extends Tree

// Return the in-order traversal sequence of a given tree.
def inOrder(t: Tree): List[Int] = t match {
  case Node(e, l, r) => inOrder(l) ::: List(e) ::: inOrder(r)
  case Leaf          => List()

Go Functional with Higher-Order Functions

In Scala, functions are values, and can be defined as anonymous functions with a concise syntax.

val people: Array[Person]

// Partition `people` into two arrays `minors` and `adults`.
// Use the anonymous function `(_.age < 18)` as a predicate for partitioning.
val (minors, adults) = people partition (_.age < 18)
List<Person> people;

List<Person> minors = new ArrayList<Person>(people.size());
List<Person> adults = new ArrayList<Person>(people.size());
for (Person person : people) {
    if (person.getAge() < 18)

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Scala ecosystem

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Forward Compatibility for the Scala 3 Transition

Thursday, November 19, 2020

Forward Compatibility for the Scala 3 Transition

Scala 3 is coming, with a release candidate slated for the end of 2020. With that knowledge comes the inevitable question: should I migrate, and what is the potential cost?

For maintainers of projects, the migration process may become easier with the recent release of Scala 2.13.4, which comes with a new preview feature: reading and compiling against Scala 3 dependencies.


With a guided tutorial, we will show you how Scala 2.13.4 makes the following scenarios easier:

  1. You have an application consisting of many subprojects that may depend on each other, built with Scala 2.13, and would like to transition each one independently to Scala 3.0
  2. You have an application, built with Scala 2.13, and want to use some new features of a library that has migrated to Scala 3.0

The tutorial will proceed as follows:

  • We will take a small multi-module project of two sub-projects, a shared module, containing simple data structures, and an app module that depends on shared.
  • We will in turn migrate each sub-project to Scala 3, and show that it does not matter in which order you migrate the projects, as app will continue to build and run.
  • To finish, we will add a library dependency on the Scala 3 version of ScalaCheck, and use it from Scala 2 to validate data structures in the shared module.

A reader applying the steps in the tutorial to their own project should note that not all features of Scala 3 are forward compatibile with Scala 2, such as inline methods. Consequently, we recommend that the user limits their usage of Scala 3 exclusive features when migrating incrementally. More information is provided in the forward compatibility section.

In addition, we provide a troubleshooting section for the reader, which aims to suggest steps to take when applying this guide to their own projects and a problem occurs.

Status of the Tasty Reader

As a quick aside, If you would like to know how it is possible to mix dependencies between the two compilers, watch the talk Taste the Difference with Scala 3.

To summarise: Scala 3 stores meta information about the code it compiles in TASTy files, and Scala 2.13 can read these files to learn, for example, which terms, types and implicits are defined in a given dependency, and what code needs to be generated to use them correctly. The part of the compiler that manages this is known as the Tasty Reader.

Currently, reading Scala 3 dependencies from Scala 2 requires the compiler flag -Ytasty-reader. The Tasty Reader feature is currently released as a preview for users to evaluate and we invite them to give feedback and report any bugs. As Scala 3 reaches release, we hope to enable the Tasty Reader by default.


The overview section describes two scenarios that we will guide you through in this blog:

  • Migrating multi-module projects incrementally from Scala 2 to Scala 3
  • Taking advantage of new features in a library that is published for Scala 3.

Let’s look at each scenario in turn:

1. Migrate a Multi-Module Project in Any Order

If you want to migrate a multi module project to Scala 3, it does not matter in which order you migrate the modules, they will be able to depend on each other regardless of whether they are compiled with Scala 2.13 or Scala 3.

To illustrate this scenario, we will start with an empty directory and build an sbt project with Scala 2.13 that has two modules, shared, which has some common domain model data structures, and app, which uses those data structures.

For this project, we will pick sbt 1.4.3, this allows you to mix projects of different Scala versions with very little extra effort (thanks to Eugene Yokota).

To begin, our project looks like the following:

// project/
// build.sbt
ThisBuild / scalaVersion := "2.13.4"

lazy val shared = project

lazy val app = project
// shared/src/main/scala/example/Cat.scala
package example

sealed trait Cat extends Product with Serializable
object Cat {
  case object Lion    extends Cat
  case object Tiger   extends Cat
  case object Cheetah extends Cat
// app/src/main/scala/example/Main.scala
package example

object Main extends App {

We can run this application with sbt app/run which will output the following:

[info] Compiling 1 Scala source to blog/shared/target/scala-2.13/classes ...
[info] Compiling 1 Scala source to blog/app/target/scala-2.13/classes ...
[info] running example.Main

At this point we can try something exciting, compile either subproject with Scala 3 and see if it works.

First, add the dotty plugin (this helps with managing and inspecting the scalaVersion setting with Scala 3)

// project/plugins.sbt
addSbtPlugin("ch.epfl.lamp" % "sbt-dotty" % "0.4.5")

Then we can change the scalaVersion of app:

 // build.sbt
 ThisBuild / scalaVersion := "2.13.4"

 lazy val shared = project

 lazy val app = project
+  .settings(scalaVersion := "3.0.0-M1")

To recap, app is now compiled by Scala 3 and depends on shared, which is compiled by Scala 2.13.

If we do sbt app/run we should see the app project recompile and it will run as before.

Now lets try the other way around, in this case we also have to enable reading Scala 3 dependencies in Scala 2 with the flag -Ytasty-reader:

 // build.sbt
 ThisBuild / scalaVersion := "2.13.4"

 lazy val shared = project
+  .settings(scalaVersion := "3.0.0-M1")

 lazy val app = project
-  .settings(scalaVersion := "3.0.0-M1")
+  .settings(scalacOptions += "-Ytasty-reader")

Here we have the opposite, app is compiled by Scala 2.13 and depends on shared, which is compiled by Scala 3. We can see this more clearly using the command sbt 'show app/dependencyTree', which outputs the following:

app:app_2.13:0.1.0-SNAPSHOT [S]
    +-org.scala-lang:scala3-library_3.0.0-M1:3.0.0-M1 [S]

If we then try sbt app/run both shared and app subprojects will recompile and it should work as it always has. If in your own project there are issues in changing the Scala versions, check out the troubleshooting section.

To summarise this part, we have shown that it is possible to migrate subprojects to Scala 3 from Scala 2.13 in any order, gradually, and continue to build and run them if they mix versions.

2. Using a Scala 3 Library Dependency

In the section above, we have seen how it is possible for a subproject compiled with Scala 2.13 to depend on a subproject compiled with Scala 3. The same relationship extends to library dependencies.

To demonstrate using a third party library dependency, we will create a test suite for our example.Cat data structure, using ScalaCheck. Here we add it as a library dependency:

 // build.sbt
 ThisBuild / scalaVersion := "2.13.4"

 lazy val shared = project
   .settings(scalaVersion := "3.0.0-M1")

 lazy val app = project
   .settings(scalacOptions += "-Ytasty-reader")
+  .settings(
+    libraryDependencies += "org.scalacheck" % "scalacheck_3.0.0-M1" % "1.15.0"
+  )

Notice that in the above snippet, we are using the Scala 3 version of ScalaCheck. To force a specific Scala version, we take a standard module id and change it as so:

-"org.scalacheck" %% "scalacheck" % "1.15.0"
+"org.scalacheck" % "scalacheck_3.0.0-M1" % "1.15.0"

By replacing %% with %, we can then manually specify the binary version, leading us to add _3.0.0-M1 to the name of the module.

As a preliminary, now that Cat is compiled with Scala 3, we will change the definition of Cat to an enumeration, giving us convenient ways to reflect over its members:

 // shared/src/main/scala/example/Cat.scala
 package example

-sealed trait Cat extends Product with Serializable
-object Cat {
+enum Cat {
-  case object Lion    extends Cat
-  case object Tiger   extends Cat
-  case object Cheetah extends Cat
+  case Lion, Tiger, Cheetah

Let’s now make our test suite. As a demonstration we will check two properties:

  • given two example.Cat with the same label, they should refer to the same object.
  • given two example.Cat that refer to the same object, they should have the same label.

Here is the source code:

// app/src/test/scala/example/CatSpecification.scala
package example

import org.scalacheck.{Properties, Gen}
import org.scalacheck.Prop.forAll

object CatSpecification extends Properties("Cat") {

  val allCats = Cat.values

  val genCat: Gen[Cat] =
    for (x <- Gen.choose(0, 100)) yield allCats(x % allCats.length)

  property("`sameName -> identical`") = forAll(genCat, genCat) { (a: Cat, b: Cat) =>
    a.productPrefix != b.productPrefix || a.eq(b)

  property("`identical -> sameName`") = forAll(genCat, genCat) { (a: Cat, b: Cat) => || a.productPrefix == b.productPrefix


If we then use the command sbt app/test we should see the following output:

[info] + Cat.`identical -> sameName`: OK, passed 100 tests.
[info] + Cat.`sameName -> identical`: OK, passed 100 tests.

If we then run again sbt 'show app/dependencyTree' we see the following:

app:app_2.13:0.1.0-SNAPSHOT [S]
  | +-org.scala-lang:scala3-library_3.0.0-M1:3.0.0-M1 [S]
  | +-org.scala-sbt:test-interface:1.0
    +-org.scala-lang:scala3-library_3.0.0-M1:3.0.0-M1 [S]

To summarise, in this section we have shown how it is possible to use a third party library dependency, compiled with Scala 3, from Scala 2.13. If there are issues with changing the binary version of a particular dependency you have, check out the troubleshooting section.

Forward Compatibility

When migrating a subproject to Scala 3, where downstream consuming subprojects are likely to be on Scala 2.13, we would recommend restricting the usage of new features in Scala 3. This will maximise compatibility as you migrate each subproject. However, it is possible to start using some features of Scala 3 without issue, this is due to a limited forward compatibility in Scala 2.13 with some new Scala 3 features.

Forward compatibility means that many definitions created by using new Scala 3 features can be used from Scala 2.13, however they will be remapped to features that exist in Scala 2.13. For example, extension methods can only be used as ordinary methods. So for cross-compatible code we recommend to continue using implicit classes to encode extension methods.

On the other hand, some features of Scala 3 are not mappable to features in Scala 2.13, and will cause a compile-time error when using them. A longer list can be seen in the migration guide, describing how Scala 2 reacts to different Scala 3 features.

For unsupported features, a best effort is made to report errors at the use-site that is problematic. For example, match types are not supported. If we define in the shared project the type Elem:

// shared/src/main/scala/example/MatchTypes.scala
package example

object MatchTypes {
  type Elem[X] = X match {
    case List[t] => t
    case Array[t] => t

and then try to use it in the app project:

// app/src/main/scala/example/TestMatchTypes.scala
package example

object TestMatchTypes {
  def test: MatchTypes.Elem[List[String]] = "hello"

we get the following error when calling sbt app/run:

[error] TestMatchTypes.scala:5:25: Unsupported Scala 3 match type in bounds of type Elem; found in object example.MatchTypes.
[error]   def test: MatchTypes.Elem[List[String]] = "hello"
[error]                        ^
[error] one error found

The error is standard for all unsupported Scala 3 features, naming the feature, the location of the definition and the location where it is used.


There are some situations where the steps described in the sections above do not work out of the box for your own project, and some other considerations need to be made.

For the multi module project scenario, let’s say you have two subprojects A and B, where B depends on A, both compiled with Scala 2.13.

Source Incompatibilities When Changing to Scala 3

If you change the scalaVersion of A to Scala 3 and A fails to build, and the error is not due to a missing dependency, the source code of A may be incompatible with Scala 3 and you will have to make some changes. You can consult the Scala 3 Migration Guide to see what changes may be required.

Missing Scala 3 Dependencies

If you change the scalaVersion of A to Scala 3 and A fails to build due to a missing dependency, you can try to use the Scala 2.13 version of the dependency. The sbt-dotty plugin provides helper methods for this.

Scala 3 Dependencies That Break Compilation

If you successfully migrate subproject A to Scala 3, but now B fails to compile, there are several likely possibilities:

  1. A has made a deliberate but forward compatible change to its API, and B needs to update to use the new API.
  2. A, or a transitive dependency of A, uses a feature of Scala 3 that is not forwards compatible with Scala 2.13.
  3. A, or a transitive dependency of A, defines a Scala 3 macro but does not provide an equivalent Scala 2 macro (see an example project here for how to provide macros to Scala 2.13 from Scala 3.)
  4. There is a bug in the implementation of reading Scala 3 dependencies in Scala 2.13. Please report here.

Scala 3 Dependencies that Break Runtime Behaviour

If you successfully migrate subproject A to Scala 3, and B compiles successfully, but now fails at runtime, there are two likely possibilities:

  1. The definitions in the Scala 3 dependency were correctly read, but perhaps the API changed subtly, so the code of B must adapt. For example, perhaps a default implicit value has been replaced, or other code has changed its implementation while using the same signature.
  2. There is a bug in the implementation of reading Scala 3 dependencies in Scala 2.13. Please report here.

Third Party Scala 3 Dependencies that Break Compilation/Runtime

If depending on a third party library, compiled with Scala 3, breaks compilation, or disrupts runtime behaviour, please consider the above troubleshooting topics, but instead assume that A is the third party library, and B is your Scala 2.13 project that depends on it.


If you have found an issue with Scala 3 dependencies in Scala 2.13 and want to try fixing it in the Scala 2 compiler, you can see a summary of how to work on the implementation here: Working with the Tasty Reader


In this blog, we have outlined how it is possible to incrementally migrate a project to Scala 3 while continuing to use all the parts together during the transition. We encourage you to try out this process and let us know of any issues with using Scala 3 dependencies from Scala 2.13.

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