Scala

Scalable Language. It interops seamlessly with Java.

When to Use

• Big Data Distributed Processing: Apache Spark, Apache Flink, and large-scale data engineering pipelines.
• High-Concurrency Reactive Systems: Building resilient distributed services with Akka/Pekko actors or Cats Effect/ZIO.
• Type-Level & Purely Functional Programming: Enforcing compile-time domain guarantees with Scala 3 given/using and opaque types.
• Enterprise JVM Microservices: Leveraging the entire Java ecosystem while utilizing concise, expressive FP idioms.

Quick Start

object Hello extends App {
  println("Hello, World!")

  val list = List(1, 2, 3)
  val doubled = list.map(_ * 2)
  println(doubled)
}

Core Concepts

Scala 3 Contextual Abstractions: Given & Using

Type classes and dependency injection unified cleanly without implicit conversions:

// Define type class
trait JsonEncoder[A]:
  def encode(a: A): String

// Given instances (type class implementations)
given JsonEncoder[String] with
  def encode(a: String): String = s"\"${a.replace(""", "\\"")}\""

given JsonEncoder[Int] with
  def encode(a: Int): String = a.toString

// Contextual function with 'using' clause
def toJson[T](value: T)(using encoder: JsonEncoder[T]): String =
  encoder.encode(value)

// Extension methods for clean syntax
extension [T](value: T)(using encoder: JsonEncoder[T])
  def asJson: String = encoder.encode(value)

Algebraic Data Types & Exhaustive Pattern Matching

Modeling domain states with Scala 3 sealed traits and enums:

enum PaymentStatus:
  case Pending
  case Authorized(transactionId: String, amountCents: Long)
  case Failed(reason: String, retryable: Boolean)

def evaluatePayment(status: PaymentStatus): String = status match
  case PaymentStatus.Pending =>
    "Waiting for gateway response..."
  case PaymentStatus.Authorized(txId, amt) =>
    s"Payment $txId confirmed for \$${amt / 100.0}"
  case PaymentStatus.Failed(reason, true) =>
    s"Transient error: $reason. Retrying..."
  case PaymentStatus.Failed(reason, false) =>
    s"Permanent failure: $reason. Contacting customer."

Asynchronous Effect Management with Cats Effect

Pure functional concurrency with resource safety and fiber cancellation:

import cats.effect.{IO, IOApp, Resource}
import scala.concurrent.duration.*

object ServerApp extends IOApp.Simple:
  def acquireDbConnection: IO[String] = IO.println("DB Connected") *> IO.pure("conn-123")
  def releaseDbConnection(conn: String): IO[Unit] = IO.println(s"DB Disconnected: $conn")

  val dbResource: Resource[IO, String] =
    Resource.make(acquireDbConnection)(releaseDbConnection)

  def run: IO[Unit] =
    dbResource.use { conn =>
      for
        fiber <- IO.sleep(100.millis).as("Query result").start
        res   <- fiber.joinWithNever
        _     <- IO.println(s"Executed on $conn: $res")
      yield ()
    }

Common Patterns

Enum and Pattern Matching in Scala 3

Problem: Verbose sealed trait hierarchies for algebraic data types in legacy Scala 2.

Solution: Use Scala 3 concise enum definitions:

enum TransactionStatus:
  case Pending
  case Approved(txId: String, amount: BigDecimal)
  case Rejected(reason: String)

def describe(status: TransactionStatus): String = status match
  case TransactionStatus.Pending => "Transaction is being processed"
  case TransactionStatus.Approved(id, amount) => s"Approved $id: $$$amount"
  case TransactionStatus.Rejected(reason) => s"Declined: $reason"

Best Practices

Do:

• Embrace Scala 3 syntax: use enum, given/using, and top-level definitions instead of Scala 2 package objects.
• Use opaque type aliases for type-safe domain identifiers (e.g. UserId, OrderId) without heap allocation overhead.
• Structure async applications around functional effect systems (Cats Effect 3 or ZIO 2) rather than raw scala.concurrent.Future.
• Enable compiler strictness (-Xfatal-warnings, -Wunused:all) to maintain clean codebases.

Don't:

• Use var or mutable collections in domain logic; use immutable collections and case class .copy().
• Catch raw Throwable without re-throwing non-fatal exceptions; use scala.util.control.NonFatal.
• Use Option.get or Try.get; use getOrElse, pattern matching, or for-comprehensions.

Troubleshooting

References

• Scala Documentation