Introduction to Functional Programming with Swift

Transcript

1. Introduction to Functional Programming Hiroshi Kori
2. What is Functional Programming?
3. Functional Programming is a style
4. Programming Language matters?
5. Concept of Functional Programming • Pure functions (Referential Transparency) • Immutability • First-class and higher-order functions • Recursion • Strict vs non-strict (lazy) evaluation • Type systems Functional Programming Imperative Programming
6. Pure functions (Referential Transparency) • No side effect! (No dependency on mutable states) • Same result for the same arguments • Testability • Easier to expect result • More room of optimization • Side effect or state is essential in some cases (I/O, GUI)
7. Immutability • Binding vs Assignment • Keep it as immutable as possible
8. Immutability Immutability https://www.cs.kent.ac.uk/people/staff/dat/miranda/whyfp90.pdf Functional programmers argue that there are great material benefits - that a functional programmer is an order of magnitude more productive than his conventional counterpart, because functional programs are an order of magnitude shorter. Yet why should this be? The only faintly plausible reason one can suggest on the basis of these “advantages” is that conventional programs consist of 90% assignment statements, and in functional programs these can be omitted!
9. First-class and higher-order functions • Flexibility to compose problem solver • Helps to solve complex problem
10. First-class and higher-order functions • map • reduce • filter "Richard Waters (1979) developed a program that automatically analyzes traditional Fortran programs, viewing them in terms of maps, filters, and accumulations. He found that fully 90 percent of the code in the Fortran Scientific Subroutine Package fits neatly into this paradigm."
11. Recursion factorial(3) = 3 * 2 * 1
12. Recursion Recursive function call consumes stack? What happens if they are called with `n = 1,000,000`?
13. Recursion vs https://github.com/k-ori/Introduction-to-FP-playground/blob/master/TCOTests.swift
14. Recursion vs Tail Call Optimization
15. Strict vs non-strict (lazy) evaluation at least 6980 times faster (0.382 sec in for-loop with array) https://github.com/k-ori/Introduction-to-FP-playground/blob/master/lazyStreamTests.swift
16. • Swift: Strict evaluation + Lazy evaluation library • Haskell: Lazy evaluation by default Strict vs non-strict (lazy) evaluation
17. Type systems • Dynamically typed language: Lisp, JavaScript • Statically typed language: Swift, Haskell, Scala
18. Type systems • Algebraic data type • product types (A X B) • sum types (A | B) Noodle Food = Ramen (Noodle (Thin | Thick) x Soup (Salt | Soy sauce)) | Pasta (Noodle (Thin | Thick) x Sauce (Tomato | Basil)) | Pho (Noodle (Thin | Thick) x Soup (Salt | Soy sauce)) Complicated type can be represented
19. Case study 1 Let’s build and manipulate linked list From “Why Functional Programming Matters” https://www.cs.kent.ac.uk/people/staff/dat/miranda/whyfp90.pdf Find code from https://github.com/k-ori/Introduction-to-FP-playground
20. Case study 2 Let’s implement run-length encoding Find code from https://github.com/k-ori/Introduction-to-FP-playground