scala-lang.orgThe Scala Programming Language

⚠️ Beware of Scams : since Feb 2024, scammers are using fake Scala websites to sell courses , please check you are using an official source. New on the blog: Scala 2.13.14 is now available! Learn Install Playground Find a Library Community Blog A programming language that scales with you: from small scripts to large multiplatform applications. Scala 3.4.1 Scala 3.3.3 Scala 2.13.14 All Releases Functional programming with immutable collections Run in playground 1 /4 val fruits = List ( "apple" , "banana" , "avocado" , "papaya" ) val countsToFruits = // count how many ’a’ in each fruit fruits . groupBy ( fruit = fruit . count ( _ == ’a’ )) for ( count , fruits ) - countsToFruits do println ( s "with ’a’ × $count = $fruits" ) // prints: with ’a’ × 1 = List(apple) // prints: with ’a’ × 2 = List(avocado) // prints: with ’a’ × 3 = List(banana, papaya) High-level operations avoid the need for complex and error-prone loops. Encode and decode custom data types to JSON Run in playground 2 /4 case class Pet ( name : String , kind : String ) derives Codec // enable coding Pet to and from text val coco = Pet ( name = "Coco" , kind = "Cat" ) val message = writeJson ( coco ) // ^^^^^^^ contains the text: {"name":"Coco","kind":"Cat"} readJson [ Pet ]( message ) // convert message back to a Pet! The pluggable derivation system gives custom types new capabilities. Target the Web with Scala.js on the frontend Run in playground 3 /4 val counter = Var ( 0 ) // create a counter button that increments on-click def counterButton () = button ( tpe := "button" , "count is " , child . textcounter , onClick{ event = counter . update ( c = c + 1 ) }, ) val app = dom . document . getElementById ( "app" ) render ( app , counterButton ()) Share code full-stack, interact with the DOM or use any JS library. Define data types and pattern match on them with ease Run in playground 4 /4 enum Payment : case Card ( name: String , digits: Long , expires : Date ) case PayPal ( email : String ) def process ( kind : Payment ) = kind match case Card ( name , digits , expires ) = s "Processing credit card $name, $digits, $expires" case PayPal ( email ) = s "Processing PayPal account $email" process ( Card ( name , digits , expires )) Model domains precisely, and make choices based on the shape of data. GET STARTED Overview • Guide • Courses DOCUMENTATION API Docs • Migrate to Scala 3 Why Scala?Expressive Scala lets you write less to do more. As a high-level language, its modern features increase productivity and lead to more readable code. With Scala, you can combine both functional and object-oriented programming styles to help structure programs. Scalable Scala is well suited to building fast, concurrent, and distributed systems with its JVM, JavaScript and Native runtimes. Scala prioritises interoperability, giving easy access to many ecosystems of industry-proven libraries. Safe Scala’s static types help you to build safe systems by default. Smart built-in checks and actionable error messages, combined with thread-safe data structures and collections, prevent many tricky bugs before the program first runs. Proven Use Cases People around the world trust Scala to build useful software. Popular domains include Server-side High-throughput HTTP servers and clients. Safe, scalable, and principled concurrency. Reliable data validation with powerful transformations. Creating Services Principled Concurrency Scala’s expressivity and compiler-enforced safety makes it easier to construct reliable concurrent code. With Scala, your programs take full advantage of multi-core and distributed architectures, ensure safe access to resources, and apply back-pressure to data producers according to your processing rate. One popular open-source option for managing concurrency in Scala is Cats Effect , combined with http4s for defining servers and routing. Click below to see other solutions. libraries for Concurrency and distribution Express high-level concurrency with http4s and Cats Effect // HTTP server routing definition val service = HttpRoutes.of: case GET - Root / "weather" = // route ’/weather’ for winner - fetch1.race(fetch2).timeout(10.seconds) response - Ok(WeatherReport.from(winner)) yield response def fetch1 = fetchWeather(server1) // expensive Network IO def fetch2 = fetchWeather(server2) // expensive Network IO A Mature Ecosystem of Libraries Use the best of Scala, or leverage libraries from the Java and JavaScript ecosystems. Build with monolithic or microservice architectures. Retain resource-efficiency. Persist your data to any kind of database. Transform, validate, and serialize data into any format (JSON, protobuf, Parquet, etc.). Whether you compile for the Node.js or Java platform, Scala’s interop with both gives you access to even more widely-proven libraries. Find the right library for your next Scala project Compute accross distributed nodes with Akka actors def Device(lastTemp: Option[Double]): Behavior[Message] = Behaviors.receiveMessage: case RecordTemperature(id, value, replyTo) = replyTo ! TemperatureRecorded(id) Device(lastTemp = Some(value)) case ReadTemperature(id, replyTo) = replyTo ! RespondTemperature(id, lastTemp) Behaviors.same Case Study: Reusable Code with Tapir Harness the Code as Data” Paradigm: define once, use everywhere. Scala’s rich type system and metaprogramming facilities give the power to automatically derive helpful utilities from your code. One such example library is Tapir , letting you use Scala as a declarative language to describe your HTTP endpoints. From this single source of truth, you can automatically derive their server implementation, their client implementation, and both human-readable and machine-readable documentation. Because everything is derived from a type-safe definition, endpoint invocations are checked to be safe at compile-time, across the frontend and backend. Read more in the Tapir docs Describe service endpoints as data with Tapir // type-safe endpoint definition val reportEndpoint = endpoint .in("api" / "report" / path[String]("reportId")) .out(jsonBody[Report]) // derived Docs, Server and Client val apiDocs = docsReader .toOpenAPI(reportEndpoint, "Fetch Report", "1.0.0") val server = serverBuilder(port = "8080") .addEndpoint(reportEndpoint.handle(fetchReport)) .start() val client = clientReader .toRequest(reportEndpoint, "http://localhost:8080") val report: Future[Report] = client("5ca1a-78fc8d6") // call like any functionData Processing Pick your favorite notebook. Run massively distributed big data pipelines; train NLP or ML models; perform numerical analysis; visualize data and more. Processing data Big Data Analysis Analyse petabytes of data in parallel on single-node machines or on clusters. Compute either in batches or in real-time. Execute fast, distributed relational operations on your data, or train machine learning algorithms. Work with popular storage and computation engines such as Spark , Kafka , Hadoop , Flink , Cassandra , Delta Lake and more. Libraries for processing big data Analyse data across a cluster with Spark // Count the number of words in a text source val textFile = spark.textFile("hdfs://...") val counts = textFile .flatMap(line = line.split(" ")) .map(word = (word, 1)) .reduceByKey(_ + _) counts.saveAsTextFile("hdfs://...") Notebooks Explore data in web-based notebooks and produce rich, interactive output. Combine code, data, and visualizations in a single document. Make changes and instantly see results. Share and collaborate with others. Along many cloud-hosted solutions, open-source notebooks for Scala include the almond Jupyter kernel , Zeppelin and Polynote . Libraries for big data and visualisation Zeppelin Command Line Superpower your scripts with the Scala command. Get hands-on with the Scala Toolkit. Easily add libraries. Build CLI apps with instant startup. Scripting Utilities The power of Scala in one file Scala CLI gives all the tools you need to create simple Scala projects. Import your...