Scala Functional Patterns

Immutable data transformations in Scala use case classes and functional operations like map and fold on collections. Build pure functions that don't modify state, apply higher-order functions to chain operations, and leverage Scala's immutable data structures by default to ensure thread-safe, predictable code.

Option represents an optional value—Some or None—when a computation may or may not produce a result. Either represents success or failure with Either[Error, Success], allowing you to attach error information. Use Option for simple presence checks; use Either when you need to communicate why an operation failed.

For-comprehensions flatten nested monadic calls like Option and Either into readable sequential syntax. Write generators with <- to extract values, apply filters, and yield results; the compiler desugars this into flatMap and map calls, composing operations cleanly without explicit nesting.

Sealed traits create algebraic data types (ADTs) that pattern matching can exhaust at compile time. Define sealed trait base types, extend with case classes for each variant, then match on all cases; the compiler warns if you miss a case, enforcing correctness in domain logic.

Higher-order functions like map, fold, and filter express intent declaratively and compose easily into pipelines. They eliminate mutable loop variables, work naturally with immutable collections, and support function composition, making concurrent or distributed processing safer and more maintainable.

Function composition chains pure functions together using andThen or compose operators, creating reusable pipelines. Build small, single-purpose functions, combine them into larger workflows, and pass the composed function through your application, enabling testability and reuse across concurrent workloads.