Scala runs on...

  • JVM
  • JavaScript in your browser
  • Natively with LLVM beta

Scala in a Nutshell

click the boxes below to see Scala in action!

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)

Run Scala in your browser

Scastie is Scala + sbt in your browser! You can use any version of Scala, or even alternate backends such as Dotty, Scala.js, Scala Native, and Typelevel Scala. You can use any published library. You can save and share Scala programs/builds with anybody.

Run Scala code interactively

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Scala ecosystem

The Scala Library Index (or Scaladex) is a representation of a map of all published Scala libraries. With Scaladex, a developer can now query more than 175,000 releases of Scala libraries. Scaladex is officially supported by Scala Center.

The Scala Library Index

What’s New


Community and Communication

Thursday, May 2, 2019

The Scala language is a big tent. It supports object-oriented and functional code working together. The point of Scala was always to show that these paradigms can be combined in a compact set of unified language features. But while the language design stresses unification, the same can not (yet?) be said about the community of Scala programmers.

In fact, Scala is used in many different ways. There are the people who use it as a “better Java” with more powerful object-oriented features, and there are the people who use it as a “poor man’s Haskell”, concentrating on the purely functional language subset. And then there are the many in between who use it in a predominantly functional style with an object-oriented module structure, without being too dogmatic about it.

I see this difference of approaches as a big opportunity. There are so many great ideas to debate and opportunities to learn from each other! Lots of these ideas feed into the design of Scala 3, with the overall goal to make Scala’s integration of paradigms even tighter than it is now, as well as making it simpler and safer.

Unfortunately, sometimes a competition between ideas becomes a fight between people promoting them. This can happen in the heat of debate, but we have to draw a line where personal attacks become persistent, where others are ridiculed or where statements are distorted intentionally.

None of this should be controversial. But if such behavior occurs what should we do about it? And who even is “we”? If we take all Scala users together, the answer is: there’s nothing to be done. Everybody can use a programming language and communicate about it in the way they see fit. If we take us as individuals, the answer is that we can and will stop interacting with people whose behavior we object to. If we talk about organizations such as the Scala Center, or Lightbend, or Typelevel, I believe they also have the right and sometimes the obligation to take a stand. First, they are ultimately made up of individuals, and cannot be disassociated from them. Second, they are tasked to safeguard the health of the projects and communication channels that they own, and that means they should not look away when norms are violated.

This is painful for everyone involved, and tends to be done only in exceptional cases. I take this as a challenge for us to develop better ways of conflict resolution that are inclusive, consensual, and respectful of one another. I also believe it’s important not to let the past hold us up forever. Individuals and their organizations change and decisions should take that into account. The goal must be to resolve controversies of that nature quickly and get back to an intense and friendly competition of ideas in Scala.

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