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

Online Courses

Functional Programming Principles in Scala

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Functional Program Design in Scala

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Parallel Programming

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Big Data Analysis with Scala and Spark

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Functional Programming in Scala Capstone

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Programming Reactive Systems

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Upcoming Training

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

Rob Norris joins Scala Center’s Advisory Board as a new Community Representative

Monday, March 18, 2019

The Scala Center Advisory Board welcomes Rob Norris as a Community Representative.

Rob succeeds Lars Hupel in the Community Representative role. (Bill Venners continues as the other Community Representative.)

The Scala Center team sincerely thanks Lars for his great work since the beginning of the Center three years ago. He has written and presented community proposals (see: SCP-011; SCP-013) and relayed community feedback and sentiment to the board.

We are grateful that Rob has accepted our invitation, and we look forward to working together during his time on the board.

Rob, aka tpolecat, is familiar in the Scala community for:

  • his leadership role in Typelevel
  • his popular open-source projects, including Doobie (a database library) and Tut (a tool for machine-checked documentation)
  • his many conference talks on pure-functional programming
  • his tireless efforts on Gitter and IRC to help newcomers learn Scala and functional programming

At his day job, he writes Scala code at the Gemini Observatory, supporting astronomy research. 🔭✨

Keep reading to find out more about the Community Representative role, how to get in touch, share your opinion or submit a proposal.

Did you know? The Scala Center’s Advisory Board is a forum for proposing and discussing initiatives which benefit the Scala open-source ecosystem or the Scala educational landscape. Each board member, in consultation with the Scala Center, may propose initiatives for consideration. We expect the initiatives to cover a variety of different activities in the Scala community, including (but not limited to):

  • Development and maintenance of open-source Scala libraries
  • Producing documentation and learning materials
  • Developing tools and services of benefit to the Scala community as a whole

Did you know? The community representative role is to be:

  • Spokesperson for the Scala community at Advisory Board quarterly meetings
  • Gathering and expressing community’s opinion on certain topic related to Scala Center proposals
  • Point of contact for community members/groups to review and help shaping community proposals
  • Presents and defends community proposals at AB meetings

Feel free to contact our Representatives by filling in this short form.

Did you know? Advisory Board members are eligible to send in a project proposal that they believe the Scala Center should work on. As part of the Board, the community is invited to submit proposals, through the Community Representatives. Check out the proposal template or previous proposals.

Did you know? The Scala Center turned 3 years old, check out our first announcement back in 2016, or watch this short video where Martin explains how the idea came about. We also recommend to watch Prof. Heather Miller’s full talk, to understand better how Scala Center fits in the wider effort of open source sustainable development.

For more useful topics, check out:

Scala Center activities, Scala Center AB minutes

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