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Functional Programming, simplified
The document discusses various programming paradigms, focusing on procedural, object-oriented, and functional programming. It highlights the advantages of functional programming, such as modularity and safety, and provides examples of functional programming constructs like functions, monads, and data manipulation techniques. It also recommends transitioning from traditional programming practices to more functional approaches, promoting the use of expressions, optional types, and functional utilities.
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Functional Programming, simplified
- 1. FP, simplified forjava programmers Naveen Muguda
- 4. Programming Paradigms • Wikipedialists about 30+ paradigms
- 5. Programming Paradigms(..continued) • Twoparadigms are largely prevalent • Procedural (vast majority) • Object Oriented (occasional) • Functional (old kid making a come back)
- 6.
- 7. Paradigm:Data Shared/Hidden Mutable/Immutable Procedural SharedMutable Object Oriented Hidden Mutable Functional Shared Immutable
- 8. Paradigm: snippets • Findelements of a list Procedural find(list) Object Oriented list.find(y) Functional list.filter(x -> (x == y));
- 10. Snippets(..continued) even list.filter(x ->(x % 2) == 0) odd list.filter(x -> (x % 2) != 0) prime list.filter(Primes::isPrime) Multiple of list.filter(x -> isMultiple(x, 4))
- 12. Building block: Function •Functions return value vs stack.push() • Functions are methods which have no side effects vs list.add() • Functions always return the same value for the same input vs stack.pop() • Functions don’t access data in other contexts* vs list.size()
- 13. Side effects • Haveto be managed • push():pop() • lock():unlock() • allocate():free()
- 14. Control abstractions Have sideeffects Don’t have side effects statement Expression procedure function
- 15. Higher order functions •x, f, f(x) • filter(Predicate predicate) • … • if(predicate.test(x) == true) • result.add(x)
- 16. Granularity • filter(Predicate<X> predicate) •map(Function<X, Y> mapper) • fold(T zero, Bifunction<T, T>combiner)
- 17. parameterization • fold(1, (x,y) -> (x * y)) • fold(0, (x, y) -> (x + y)) • fold(Integer.Minimum, (x, y)-> max(x, y))
- 18. composability • f(g(h(x))) • map(h).map(g).map(f) •filter(m).find(f).map(g).orElse(y)
- 19. ..benefits • Functions areeasier to reason • Functions are modular • Functions are safer
- 21. Monad • wrap data •accept a chain of functions • create a chain of monads • Provide utility around wrapped data
- 22.
- 23. Monads Monad Value Identity storage Streamparallelising pipeline Promise deferring pipeline execution Optional creates non-null and null pipelines, provides null safety Either creates two pipelines, usually happy path and other path, encapsulates concerns Try Creates two pipelines, happy path and exception path, encapsulates concerns
- 25. Modularization in non-FPworld Modularization in FP world
- 26. Where is FPbeing used? • map/reduce • Java Streams • Reactive • Spark • Kafka
- 27. recommendations • statements ->expressions • procedures-> functions • null check -> Optional • if-else-> Either • if-else-> ternary • for-> stream • try-catch-> Try
- 28. catch • Sorting, insertingare all painful • great for queries, figuring out for mutations