Introduction to Functional programming
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The document introduces functional programming by discussing its motivations, definitions, and key values such as immutability, types, and pure functions. It explains the contrast with object-oriented programming and emphasizes the benefits of expressiveness, reduced code complexity, and easier reasoning. Additionally, it includes examples of high-order functions and provides resources for further exploration of the topic.
![◦ Change external state
▫ Just don’t do it
◦ Modify a value
▫ Remember: immutable
◦ Throwing exception
▫ Return them as sentinel values
▫ Return an [Option] value
▫ Return an [Either] value
◦ I/O
▫ Most functional languages have the IO
monad1
Alternative to side-effects
1 http://en.wikipedia.org/wiki/Monad_%28functional_programming%29#The_I.2FO_monad](https://image.slidesharecdn.com/functionalprogramming-150604125518-lva1-app6891/85/Introduction-to-Functional-programming-23-320.jpg)
Introduction to Functional programming
- 2. ◦ Motivations ◦ Definitions ▫ Values ▫ Types ▫ Functions ◦ Resources AGENDA
- 3. Motivations Why you might want to use functional programming 1
- 4. Object-Oriented Programming Everything is an object ◦ State ◦ Behavior You can consider objects as (badly designed) state machines with a wide space of states and transitions
- 5. Object-Oriented Programming ◦ Reasoning about the code becomes complex quickly ◦ Unit tests to the rescue ▫ 100% coverage ▫ Always more tests !
- 6. Functional Programming ◦ Write expressive code. ◦ Write less code. ◦ Write performant code. ◦ Write code that we can easily reason about. The main goals are to reduce the input and state space and ease reasoning.
- 7. Values Building blocks of Functional Programming 2
- 8. “ If you say “a” is 5, you can’t say it’s something else later because you just said it was 5. What are you, some kind of liar? Miran Lipovaca - http://learnyouahaskell.com/
- 9. Immutability A value or data structure cannot be modified after its initialization
- 10. Values Immutable ◦ You assign a value and can’t reassign another one. Data structure are immutable too. To update them, you return a new instance with the updated state.
- 11. Values are immutable - Java
- 12. Values are immutable - Scala
- 13. Data structures are immutable - Java
- 14. Data structures are immutable - Scala
- 15. ◦ Immutability eliminates state transition ▫ Passing values and data structure reference is safe For lists: Functional languages reuse data and will not duplicate values. Immutability
- 16. Types Building blocks of Functional Programming 2
- 17. Types ◦ Classification of values ◦ The compiler can verify the correctness of values with types
- 18. Types
- 19. Functions Building blocks of Functional Programming 3
- 20. f(x) = y Always. Always. Always. Always.
- 21. ◦ Take an argument and produce a result ◦ Pure functions do not have side-effects ▫ Change external state ▫ Modify a value ▫ Throw an exception ▫ Read from sdtin ▫ Write to disk Functions
- 22. “ Functional programming is a restriction on how we write programs, but not on what we express. Paul Chiusano and Rúnar Bjarnason - Functional Programming in Scala
- 23. ◦ Change external state ▫ Just don’t do it ◦ Modify a value ▫ Remember: immutable ◦ Throwing exception ▫ Return them as sentinel values ▫ Return an [Option] value ▫ Return an [Either] value ◦ I/O ▫ Most functional languages have the IO monad1 Alternative to side-effects 1 http://en.wikipedia.org/wiki/Monad_%28functional_programming%29#The_I.2FO_monad
- 24. Functions example in Java
- 25. Functions example in Scala
- 27. Avoid loops Recursion can do the job.
- 29. Not tail-recursion example What is the last executed statement ?
- 30. Tail-recursion example * This one comes from my editor
- 31. High order functions Functions that return a function and/or take function(s) as parameters.
- 32. High-order functions in Java
- 33. High-order functions in Java
- 34. High-order functions in Scala
- 35. Useful combinators/High-order functions map: Applies a function to each element of a list. flatMap: Applies a function to a collection and flattens the result by one level. fold: Combines elements of a collection by applying a given function recursively. filter: Returns only the element that passes a truth test.
- 36. Resources ◦ Félix-Étienne Trépanier - Confoo slides: http://www.slideshare.net/felixtrepanier/intro-to- functional-programming-confoo ◦ Martin Odersky - Functional Programming Principles in Scala: https://www.coursera.org/course/progfun ◦ Miran Lipocava - Learn you a Haskell for Great Good !: http://learnyouahaskell.com/ ◦ JavaScript allongé: https://leanpub.com/javascriptallongesix ◦ Paul Chiusano and Runr Bjarnason - Functional Programming in Scala: http://www.manning.com/bjarnason/
- 37. Thanks! ANY QUESTIONS? You can find me at @NyloAndry ny.fanilo@gmail.com
- 38. CREDITS Special thanks to all the people who made and released these awesome resources for free: ◦ Presentation template by SlidesCarnival ◦ Photographs by Unsplash Code screenshots: http://www.slideshare.net/felixtrepanier/intro-to- functional-programming-confoo