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.

Author.scala
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: java.io.File): List[Author] = ???
}
App.java
import static scala.collection.JavaConversions.asJavaCollection;

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

    public void sortAuthors(List<Author> authors) {
        Collections.sort(authors);
    }

    public void displaySortedAuthors(File file) {
        List<Author> authors = loadAuthorsFromFile(file);
        sortAuthors(authors);
        for (Author author : authors) {
            System.out.println(
                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 person.name
     | }
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.

Concurrent/Distributed
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.

Traits

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.

Traits
abstract class Spacecraft {
  def engage(): Unit
}
trait CommandoBridge extends Spacecraft {
  def engage(): Unit = {
    for (_ <- 1 to 3)
      speedUp()
  }
  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.

Scala
val people: Array[Person]

// Partition `people` into two arrays `minors` and `adults`.
// Use the higher-order function `(_.age < 18)` as a predicate for partitioning.
val (minors, adults) = people partition (_.age < 18)
Java
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)
        minors.add(person);
    else
        adults.add(person);
}

Run Scala in your browser

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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

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Introducing Scaladoc Tables

Thursday, October 4, 2018

Scala 2.12.7 adds support for markdown tables in Scaladoc comments.

A Simple Example

The markdown for tables follows GitHub Flavored Markdown with some restrictions.

This table shows all three available table elements,

| Trait | Implementations |
| ---   | ---             |
| Set   | HashSet, HashTrieSet |
| Seq   | List, Vector, Empty  |
| Map   | HashTrieMap, ListMap |

A table is comprised of,

  • A header row
  • A delimiter row
  • Zero or more data rows

This is how the above markdown renders,

Example Table 1

On an incidental note, there is no requirement to align header and cell markdown pipes. This is done in the examples to make them easier to scan.

GitHub Flavored Markdown Conformance

Scaladoc tables support the GitHub Flavored Markdown Spec Table Extension.

There are some restrictions,

  • Every row must start and end with the pipe |
  • Rows markdown must start on the left edge of the Scala comment
  • The final row must be followed by a blank line

These restrictions do not restrict the types of tables that can be created but do have the benefit of allowing simple Scaladoc parsing code.

Picking a popular markdown flavor brings several advantages over creating yet another table markdown variation including,

  • No need to explain a new approach
  • IDEs and documentation tools can take advantage of existing markdown parsing libraries

Header Cells, Data Cells

Cell content supports the standard inline styling syntax including bold, italic, monospace, underline, superscript, subscript and links.

This two table example includes bold, monospace, italic, superscript and a link,

/**
  * | Title | ISBN | Authors |
  * | :---:  | ---  | --- |
  * | '''Structured Programming''' | `0-12-200550-3` | ''Dahl, Dijkstra and Hoare'' |
  * | '''Purely functional data structures'''^1^ | `0-521-66350-4` | ''Okasaki'' |
  *
  * | Note | Comment |
  * | ---: | --- |
  * | 1 | [[https://cambridge.org Cambridge University Press]], 1998|
*/
trait Bibliography

Markdown paid, we get this reward,

Example Table 2

Breaking content over several lines is not supported in GFM tables. Use a <br/> tag or go with HTML tables if you have needs beyond the simple tables supported by GFM.

Column Alignment

Specify column alignments using hyphen and colon patterns.

Delimiter Cell Content Alignment Type
--- Left
:--- Left
---: Right
:---: Center

Including pipe (|) in content.

Scala 2.12.8 will support the escaping of the cell delimiter in cell content with \|.

More Examples

For a smorgasbord of examples take a look at examples.

Dotty and Scala 3

With dotty now boosting its share of the development horizon it’s important to place GFM into a dottydoc and hence Scaladoc 3 context.

In overview dottydoc supports the current Scaladoc 2.12 MediaWiki flavored markdown, but it also supports more contemporary flavors of markdown.

Within the realm of table markdown dottydoc supports some extensions via the flexmark-java table extension.

flexmark-java allows tables to be defined using a more expressive variant of GFM table markdown. Tables you create now will have a route to being reused for dottydoc API documentation.

Scala 2.11 Compatibility

Table markdown will not be interpreted by Scala 2.11 nor will it interfere with parsing.

Content using pipes will display in the generated Scaladoc with the pipes included as literal characters. Bear this in mind if cross compiling.

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