A Swift library providing functional data structures, typeclasses, and operators inspired by Haskell and Scala.
Swiftz is a Swift library for functional programming that defines functional data structures, functions, idioms, and extensions to augment the Swift standard library. It provides higher-level abstractions like Arrows, Lists, HLists, and typeclasses to enable more expressive and type-safe functional programming in Swift.
Swift developers interested in functional programming paradigms, especially those familiar with Haskell, Scala, or OCaml who want similar abstractions in Swift.
It offers a comprehensive set of functional programming tools inspired by established functional languages, allowing developers to write more declarative, composable, and type-safe Swift code with support for advanced abstractions like monoids and arrows.
Functional programming in Swift
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Implements higher-level data types like persistent Lists and Arrows, along with typeclasses such as Semigroup and Monoid, enabling declarative and compositional code as shown in the extensive examples.
Designed to integrate with Swift's type system, drawing inspiration from Haskell and Scala, ensuring type safety and expressiveness without breaking existing Swift idioms.
Includes a suite of operators for point-free style and functional composition, making code more concise and expressive, with support from the linked Operadics library.
Augments Swift's standard library with functional utilities, allowing incremental adoption of functional patterns without overhauling existing codebases.
Assumes familiarity with advanced functional programming concepts like arrows and monoids, which can be alien to Swift developers used to imperative or object-oriented paradigms.
The README details multiple setup methods (Carthage, Git submodules, SPM) with specific steps, which is more complex than simpler dependency management for mainstream libraries.
As a specialized functional library, it has a smaller community compared to popular Swift frameworks, resulting in fewer tutorials, examples, and slower issue resolution.
Persistent data structures and functional abstractions like arrows can introduce runtime overhead, which might not be suitable for performance-critical applications such as games or real-time systems.