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An Introduction to Functional Programming at the Jozi Java User Group

Polyglot Software Developer. Functional Programming Enthusiast. Agile aficionado. at Jemstep, Inc. (Acquired by Invesco)
Jul. 28, 2014
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An Introduction to Functional Programming at the Jozi Java User Group

  1. Introduction Definition Function Recap Common Idioms Imperative Comparison Challenges! Industry Use Now what? An Introduction to Functional Programming Andreas Pauley – @apauley Jozi JUG July 28, 2014
  2. Introduction Definition Function Recap Common Idioms Imperative Comparison Challenges! Industry Use Now what? @lambdaluminary We meet once a month, on the second Monday of the month. http://www.meetup.com/lambda-luminaries/
  3. Introduction Definition Function Recap Common Idioms Imperative Comparison Challenges! Industry Use Now what? Jemstep Retirement portfolio analysis in Scala. http://www.jemstep.com/
  4. Introduction Definition Function Recap Common Idioms Imperative Comparison Challenges! Industry Use Now what?
  5. Introduction Definition Function Recap Common Idioms Imperative Comparison Challenges! Industry Use Now what? Who likes FP? “ And that’s why I think functional programming is a natural successor to object-oriented programming. ” — Dave Thomas, Pragmatic Programmers [2] “ Without understanding functional programming, you can’t invent MapReduce ” — Joel Spolsky [3] “ ...it’s almost certainly true that functional programming is the next big thing. ” — Uncle Bob Martin [4]
  6. Introduction Definition Function Recap Common Idioms Imperative Comparison Challenges! Industry Use Now what? “ No matter what language you work in, programming in a functional style provides benefits. You should do it whenever it is convenient, and you should think hard about the decision when it isn’t convenient. ” — John Carmack, ID Software [5]
  7. Introduction Definition Function Recap Common Idioms Imperative Comparison Challenges! Industry Use Now what? But what exactly is “Functional Programming”?
  8. Introduction Definition Function Recap Common Idioms Imperative Comparison Challenges! Industry Use Now what? A simple programming example Say I give you an array of integers, and I want every one of them doubled. How would you write it?
  9. Introduction Definition Function Recap Common Idioms Imperative Comparison Challenges! Industry Use Now what? A simple programming example I have this: [1,3,6] I want this: [2,6,12]
  10. Introduction Definition Function Recap Common Idioms Imperative Comparison Challenges! Industry Use Now what? A simple programming example public static void doubleAll(int[] numbers) { for (int i=0; i < numbers.length; i++) { numbers[i] = numbers[i] * 2; } }
  11. Introduction Definition Function Recap Common Idioms Imperative Comparison Challenges! Industry Use Now what? A simple programming example Sorry, I forgot to mention that you cannot do in-place mutation on the list of numbers I give you. Please try again.
  12. Introduction Definition Function Recap Common Idioms Imperative Comparison Challenges! Industry Use Now what? A simple programming example Our first try had a void return type: public static void doubleAll(int[] numbers) { for (int i=0; i < numbers.length; i++) { numbers[i] = numbers[i] * 2; } } Now we have to return a result: public static int[] doubleAll(int[] numbers) { int[] nums2 = new int[numbers.length]; for (int i=0; i < numbers.length; i++) { nums2[i] = numbers[i] * 2; } return nums2; }
  13. Introduction Definition Function Recap Common Idioms Imperative Comparison Challenges! Industry Use Now what? A simple programming example Looking much better, but you can’t mutate any collection, appending to the new array won’t work. Also, you can’t vary your variables (i++). Please try again.
  14. Introduction Definition Function Recap Common Idioms Imperative Comparison Challenges! Industry Use Now what? A simple programming example ??? public static int[] doubleAll(int[] numbers) { int[] nums2 = new int[numbers.length]; for (int i=0; i < numbers.length; i++) { nums2[i] = numbers[i] * 2; } return nums2; }
  15. Introduction Definition Function Recap Common Idioms Imperative Comparison Challenges! Industry Use Now what? Let’s try giving a definition of Functional Programming
  16. Introduction Definition Function Recap Common Idioms Imperative Comparison Challenges! Industry Use Now what? Functional Programming, noun: Functional Programming is a list of things you CAN’T do. [10]
  17. Introduction Definition Function Recap Common Idioms Imperative Comparison Challenges! Industry Use Now what? You can’t vary your variables 1> X = 42. 42 2> X = X + 1. ** exception error: no match of right hand side value 43
  18. Introduction Definition Function Recap Common Idioms Imperative Comparison Challenges! Industry Use Now what? No while/for loops. Sorry :-( int i; for (i=1; i<=3; i++) { System.out.println(i); }
  19. Introduction Definition Function Recap Common Idioms Imperative Comparison Challenges! Industry Use Now what? You can’t mutate/change your data structures Python >>> list1 = [1,2,3] >>> list2 = list1 >>> print list1.reverse() None >>> list1 [3, 2, 1] >>> list2 [3, 2, 1] Haskell > let list1 = [1,2,3] > let list2 = list1 > reverse(list1) [3,2,1] > list1 [1,2,3] > list2 [1,2,3]
  20. Introduction Definition Function Recap Common Idioms Imperative Comparison Challenges! Industry Use Now what? You can’t have any side e↵ects
  21. Introduction Definition Function Recap Common Idioms Imperative Comparison Challenges! Industry Use Now what? Are you kidding me? How can anyone program like this???
  22. Introduction Definition Function Recap Common Idioms Imperative Comparison Challenges! Industry Use Now what? GOTO 10 This sounds like “You can’t have GOTO statements” See Hughes and Dijkstra [1, 6]
  23. Introduction Definition Function Recap Common Idioms Imperative Comparison Challenges! Industry Use Now what? It’s not about what we cannot do.
  24. Introduction Definition Function Recap Common Idioms Imperative Comparison Challenges! Industry Use Now what? We need a better definition of Functional Programming.
  25. Introduction Definition Function Recap Common Idioms Imperative Comparison Challenges! Industry Use Now what? Programming Paradigms (Very Simplified) Imperative Declarative
  26. Introduction Definition Function Recap Common Idioms Imperative Comparison Challenges! Industry Use Now what? Functional Programming, noun: “ Functional programming is so called because a program consists entirely of functions. ” — John Hughes, Why Functional Programming Matters [1, p. 1]
  27. Introduction Definition Function Recap Common Idioms Imperative Comparison Challenges! Industry Use Now what? OK... so what exactly is a function?
  28. Introduction Definition Function Recap Common Idioms Imperative Comparison Challenges! Industry Use Now what? An example function f(x) = 2x2 2x + 3 1 1 2 3 4 6 8 10 12 14 x y
  29. Introduction Definition Function Recap Common Idioms Imperative Comparison Challenges! Industry Use Now what? Variables in functions f(x) = 2x2 2x + 3 When we evaluate the function: f(2) = 8 4 + 3 = 7 • The value of x will not change inside the function body.
  30. Introduction Definition Function Recap Common Idioms Imperative Comparison Challenges! Industry Use Now what? Variables in functions f(x) = 2x2 2x + 3 When we evaluate the function: f(2) = 8 4 + 3 = 7 • The value of x will not change inside the function body. • Same input, same output. Every time. (Referential Transparency)
  31. Introduction Definition Function Recap Common Idioms Imperative Comparison Challenges! Industry Use Now what? Variables in functions f(x) = 2x2 2x + 3 When we evaluate the function: f(2) = 8 4 + 3 = 7 • The value of x will not change inside the function body. • Same input, same output. Every time. (Referential Transparency) • We can call f multiple times without any side e↵ects.
  32. Introduction Definition Function Recap Common Idioms Imperative Comparison Challenges! Industry Use Now what? Variables in functions f(x) = 2x2 2x + 3 When we evaluate the function: f(2) = 8 4 + 3 = 7 • The value of x will not change inside the function body. • Same input, same output. Every time. (Referential Transparency) • We can call f multiple times without any side e↵ects. • We don’t have to recalculate f(2), we can replace any occurrence of f(2) with 7.
  33. Introduction Definition Function Recap Common Idioms Imperative Comparison Challenges! Industry Use Now what? Varying variables does not make sense x = x + 1 x x = 1 0 = 1 ) x 6= x + 1
  34. Introduction Definition Function Recap Common Idioms Imperative Comparison Challenges! Industry Use Now what? Values are functions Constant values are just functions with no input parameters x = 42 Python function definition: def x(): return 42 Haskell function definition: x = 42
  35. Introduction Definition Function Recap Common Idioms Imperative Comparison Challenges! Industry Use Now what? Functions can be composed h(x) = (f g)(x) = f(g(x)) or h = f g
  36. Introduction Definition Function Recap Common Idioms Imperative Comparison Challenges! Industry Use Now what? Higher-order Functions Functions can take functions as input. Functions can return functions as the result. h(f, g, x) = f(x) + g(2)
  37. Introduction Definition Function Recap Common Idioms Imperative Comparison Challenges! Industry Use Now what? Higher-order Functions The derivative of f(x) returns another function. f(x) = 2x2 2x + 3 d dxf(x) = 4x 2 1 1 2 3 5 10 15 x y
  38. Introduction Definition Function Recap Common Idioms Imperative Comparison Challenges! Industry Use Now what? A functional program consists entirely of functions def main(): time = datetime.now() args = sys.argv[1:] print outputString(time, args) def outputString(time, args): return str(time) + " " + joinArgs(args) def joinArgs(args): return "-".join(args) $ ./justfunctions.py Hello from Python 2014-02-15 10:36:42.062697 Hello-from-Python
  39. Introduction Definition Function Recap Common Idioms Imperative Comparison Challenges! Industry Use Now what? A functional program consists entirely of functions main :: IO() main = do time <- getCurrentTime args <- getArgs putStrLn (outputString time args) outputString :: UTCTime -> [String] -> String outputString time args = show(time) ++ " " ++ joinArgs(args) joinArgs :: [String] -> String joinArgs = intercalate "-" $ ./justfunctions Hello from Haskell 2014-02-15 08:36:50.822728 UTC Hello-from-Haskell
  40. Introduction Definition Function Recap Common Idioms Imperative Comparison Challenges! Industry Use Now what? Some Haskell Syntax Python: def outputString(time, args): return str(time) + " " + joinArgs(args) Haskell: outputString :: UTCTime -> [String] -> String outputString time args = show(time) ++ " " ++ joinArgs(args)
  41. Introduction Definition Function Recap Common Idioms Imperative Comparison Challenges! Industry Use Now what? Recursive function: Haskell doubleAll :: [Int] -> [Int] doubleAll [] = [] doubleAll (x:xs) = x*2 : doubleAll xs Example use in the interactive interpreter: Prelude Main> doubleAll [8,2,3] [16,4,6]
  42. Introduction Definition Function Recap Common Idioms Imperative Comparison Challenges! Industry Use Now what? Recursive function expanded doubleAll [] = [] doubleAll (x:xs) = x*2 : doubleAll xs doubleAll [8,2,3] 16 : (doubleAll [2,3]) 16 : 4 : (doubleAll [3]) 16 : 4 : 6 : (doubleAll []) 16 : 4 : 6 : [] 16 : 4 : [6] 16 : [4,6] [16,4,6]
  43. Introduction Definition Function Recap Common Idioms Imperative Comparison Challenges! Industry Use Now what? Recursive function: Python def doubleAll(numbers): if numbers == []: return [] else: first = numbers[0] rest = numbers[1:] return [first * 2] + doubleAll(rest) Example use in the interactive interpreter: >>> doubleAll([8,2,3]) [16, 4, 6]
  44. Introduction Definition Function Recap Common Idioms Imperative Comparison Challenges! Industry Use Now what? Pattern Matching: Haskell doubleAll :: [Int] -> [Int] doubleAll [] = [] doubleAll (x:xs) = x*2 : doubleAll xs
  45. Introduction Definition Function Recap Common Idioms Imperative Comparison Challenges! Industry Use Now what? Higher-order Functions 3 Basic List Operations Map Convert each element of a list into some other value.
  46. Introduction Definition Function Recap Common Idioms Imperative Comparison Challenges! Industry Use Now what? Higher-order Functions 3 Basic List Operations Map Convert each element of a list into some other value. Filter Get a subset of a list based on some condition.
  47. Introduction Definition Function Recap Common Idioms Imperative Comparison Challenges! Industry Use Now what? Higher-order Functions 3 Basic List Operations Map Convert each element of a list into some other value. Filter Get a subset of a list based on some condition. Fold Reduce a list of items to a single value.
  48. Introduction Definition Function Recap Common Idioms Imperative Comparison Challenges! Industry Use Now what? Map Apply a function to each element of a list, and you get a new list. a1 a2 a3 ... an b1 b2 b3 ... bn f(a1) f(an)
  49. Introduction Definition Function Recap Common Idioms Imperative Comparison Challenges! Industry Use Now what? Map doubleAll :: Num a => [a] -> [a] doubleAll = map (*2) 8 2 3 16 4 6 ⇤2 ⇤2 ⇤2
  50. Introduction Definition Function Recap Common Idioms Imperative Comparison Challenges! Industry Use Now what? Account Data data Bank = ABSA | Capitec | FNB | Nedbank | SBSA data Account = Account {bank :: Bank, accNum :: String, owner :: String, balance :: Amount}
  51. Introduction Definition Function Recap Common Idioms Imperative Comparison Challenges! Industry Use Now what? Account Data [Account {accNum="4076814233", owner="J. Doe", balance=(Amount 123000.23), bank=ABSA}, Account {accNum="6868773585", owner="J. Black", balance=(Amount 5782347.99), bank=FNB}, Account {accNum="4055892156", owner="A. Kay", balance=(Amount 100), bank=ABSA}, Account {accNum="6584539813", owner="S. Jones", balance=(Amount 2937361.45), bank=FNB}]
  52. Introduction Definition Function Recap Common Idioms Imperative Comparison Challenges! Industry Use Now what? Map Map on account data: balances :: [Account] -> [Amount] balances accounts = map balance accounts acc1 acc2 acc3 acc4 acc5 bal1 bal2 bal3 bal4 bal5 balance(acc1) balance(acc5)
  53. Introduction Definition Function Recap Common Idioms Imperative Comparison Challenges! Industry Use Now what? Filter acc1 acc2 acc3 acc4 acc5 acc1 acc3 acc5 in? in? in? in? in?
  54. Introduction Definition Function Recap Common Idioms Imperative Comparison Challenges! Industry Use Now what? Filter Filter on account data: topAccounts :: [Account] -> [Account] topAccounts accounts = filter isRich accounts isRich :: Account -> Bool isRich acc = balance acc >= (Amount 1000000) Output: *Main> topAccounts accounts [FNB 6868773585 (J. Black) R5782347.99, FNB 6584539813 (S. Jones) R2937361.45]
  55. Introduction Definition Function Recap Common Idioms Imperative Comparison Challenges! Industry Use Now what? Fold/Reduce/Inject foldl (+) 0 [8,2,3] 13 0 8 2 3 8 2 3 10 3 13
  56. Introduction Definition Function Recap Common Idioms Imperative Comparison Challenges! Industry Use Now what? Fold/Reduce/Inject balanceSum :: [Account] -> Amount balanceSum accounts = foldl (+) 0 (balances accounts) 0 bal1 bal2 bal3 sum bal2 bal3 sum bal3 sum
  57. Introduction Definition Function Recap Common Idioms Imperative Comparison Challenges! Industry Use Now what? Function Composition balanceSum :: [Account] -> Amount balanceSum accounts = foldl (+) 0 (balances accounts) 0 bal1 bal2 bal3 sum bal2 bal3 sum bal3 sum s2 :: [Account] -> Amount s2 = balances |> (foldl(+)0) h(x) = (f g)(x) = f(g(x)) h = f g s3 = f1 balances s3 :: [Account] -> Amount s3 = (foldl(+)0) . balances
  58. Introduction Definition Function Recap Common Idioms Imperative Comparison Challenges! Industry Use Now what? balancesPerBank foldl insertBalance Map.empty accounts {} acc1 acc2 acc3 map acc2 acc3 map acc3 map
  59. Introduction Definition Function Recap Common Idioms Imperative Comparison Challenges! Industry Use Now what? Fold type BankMap = Map Bank Amount balancesPerBank :: [Account] -> BankMap balancesPerBank = foldl insertBalance Map.empty Output: *Main> balancesPerBank accounts fromList [(ABSA,R123100.23),(FNB,R8719709.44)]
  60. Introduction Definition Function Recap Common Idioms Imperative Comparison Challenges! Industry Use Now what? Fold type BankMap = Map Bank Amount balancesPerBank :: [Account] -> BankMap balancesPerBank = foldl insertBalance Map.empty insertBalance :: BankMap -> Account -> BankMap insertBalance bankmap account = Map.insert key value bankmap where key = bank account value = addBalance bankmap account addBalance :: BankMap -> Account -> Amount addBalance bankmap account = case (Map.lookup (bank account) bankmap) of Nothing -> balance account Just bal -> (balance account) + bal
  61. Introduction Definition Function Recap Common Idioms Imperative Comparison Challenges! Industry Use Now what? Programming Paradigms (Very Simplified) Imperative Declarative
  62. Introduction Definition Function Recap Common Idioms Imperative Comparison Challenges! Industry Use Now what? In imperative programming: • Your variables can vary any time!
  63. Introduction Definition Function Recap Common Idioms Imperative Comparison Challenges! Industry Use Now what? In imperative programming: • Your variables can vary any time! • You have to use locks to be thread-safe!
  64. Introduction Definition Function Recap Common Idioms Imperative Comparison Challenges! Industry Use Now what? In imperative programming: • Your variables can vary any time! • You have to use locks to be thread-safe! • You have to write your own loops for the most basic list operations!
  65. Introduction Definition Function Recap Common Idioms Imperative Comparison Challenges! Industry Use Now what? In imperative programming: • Your variables can vary any time! • You have to use locks to be thread-safe! • You have to write your own loops for the most basic list operations! • Your data structures are mutable!
  66. Introduction Definition Function Recap Common Idioms Imperative Comparison Challenges! Industry Use Now what? In imperative programming: • Your variables can vary any time! • You have to use locks to be thread-safe! • You have to write your own loops for the most basic list operations! • Your data structures are mutable! • You have to defensively make copies of data to prevent bugs!
  67. Introduction Definition Function Recap Common Idioms Imperative Comparison Challenges! Industry Use Now what? In imperative programming: • Your variables can vary any time! • You have to use locks to be thread-safe! • You have to write your own loops for the most basic list operations! • Your data structures are mutable! • You have to defensively make copies of data to prevent bugs! • You have to defensively check for null values!
  68. Introduction Definition Function Recap Common Idioms Imperative Comparison Challenges! Industry Use Now what? In imperative programming: • Your variables can vary any time! • You have to use locks to be thread-safe! • You have to write your own loops for the most basic list operations! • Your data structures are mutable! • You have to defensively make copies of data to prevent bugs! • You have to defensively check for null values! • You have to think about implicit state! (this, self)
  69. Introduction Definition Function Recap Common Idioms Imperative Comparison Challenges! Industry Use Now what? In imperative programming: • Your variables can vary any time! • You have to use locks to be thread-safe! • You have to write your own loops for the most basic list operations! • Your data structures are mutable! • You have to defensively make copies of data to prevent bugs! • You have to defensively check for null values! • You have to think about implicit state! (this, self) • Code is generally riddled with side e↵ects!
  70. Introduction Definition Function Recap Common Idioms Imperative Comparison Challenges! Industry Use Now what? Are you kidding me? How can anyone program like this???
  71. Introduction Definition Function Recap Common Idioms Imperative Comparison Challenges! Industry Use Now what?
  72. Introduction Definition Function Recap Common Idioms Imperative Comparison Challenges! Industry Use Now what? Unit tests Start writing the unit tests for your existing code in a functional programming language
  73. Introduction Definition Function Recap Common Idioms Imperative Comparison Challenges! Industry Use Now what? Join the anti-for campaign Less loops, more map/filter/fold http://weblogs.asp.net/podwysocki/archive/2009/06/26/ the-anti-for-campaign.aspx
  74. Introduction Definition Function Recap Common Idioms Imperative Comparison Challenges! Industry Use Now what? Treat side e↵ects as a first-class concern
  75. Introduction Definition Function Recap Common Idioms Imperative Comparison Challenges! Industry Use Now what? Learn a functional language “ A language that doesn’t a↵ect the way you think about programming, is not worth knowing. ” — Alan Perlis[8]
  76. Introduction Definition Function Recap Common Idioms Imperative Comparison Challenges! Industry Use Now what? Disclaim your inheritance Write non-trivial code without using objects and inheritance. Get re-usability with higher-order functions. Try to minimise moving parts instead of encapsulating moving parts. [7]
  77. Introduction Definition Function Recap Common Idioms Imperative Comparison Challenges! Industry Use Now what? Join our group @lambdaluminary We meet once a month, on the second Monday of the month. http://www.meetup.com/lambda-luminaries/
  78. Introduction Definition Function Recap Common Idioms Imperative Comparison Challenges! Industry Use Now what? Get out of your comfort zone Functional Programming is unfamiliar territory for most. “ If you want everything to be familiar you will never learn anything new. ” — Rich Hickey, author of Clojure[9]
  79. Introduction Definition Function Recap Common Idioms Imperative Comparison Challenges! Industry Use Now what? Companies In South Africa Jemstep, Sandton Using Scala for Fund Analysis Allan Gray, Cape Town Using Scala for backend logic and system integration. Yuppiechef, Cape Town Using Clojure for their Warehouse Management System. Cognician, Cape Town Using Clojure to create coaching/learning modules. Eldo Energy, Johannesburg Using Clojure for automated meter reading and intelligent monitoring of consumer energy. Rheo Systems, Pretoria Using Clojure for supply chain integration.
  80. Introduction Definition Function Recap Common Idioms Imperative Comparison Challenges! Industry Use Now what? Companies In South Africa Pattern Matched Technologies, Midrand Using Erlang for all systems, eg. processing high volumes of financial transactions. E↵ective Control Systems, Kyalami Using Erlang for printer management. Mira Networks, Somerset West Using Erlang for billing administration and mobile development. Kotive Using Scala for designing workflow processes.
  81. Introduction Definition Function Recap Common Idioms Imperative Comparison Challenges! Industry Use Now what? Online Courses Functional Thinking by Neal Ford O’ Reilly http://shop.oreilly.com/product/0636920030393.do Functional Programming Principles in Scala EPFL University https://www.coursera.org/course/progfun School of Haskell FP Complete https://www.fpcomplete.com/school Programming Languages University of Washington https://www.coursera.org/course/proglang
  82. Introduction Definition Function Recap Common Idioms Imperative Comparison Challenges! Industry Use Now what? Books Miran Lipovaˇca Learn You a Haskell for Great Good! http://learnyouahaskell.com/ Fred H´ebert Learn You Some Erlang for Great Good! http://learnyousomeerlang.com/ Yaron Minski, Anil Madhavapeddy, Jason Hickey Real World OCaml https://realworldocaml.org/ Paul Chiusano, R´unar Bjarnason Functional Programming in Scala http://www.manning.com/bjarnason/
  83. Introduction Definition Function Recap Common Idioms Imperative Comparison Challenges! Industry Use Now what? References I John Hughes Why Functional Programming Matters http://www.cs.kent.ac.uk/people/staff/dat/miranda/ whyfp90.pdf Dave Thomas Programming Elixir, A Gentle Introduction http://theprosegarden.com/part-1-of/ Joel Spolsky Can Your Programming Language Do This? http: //www.joelonsoftware.com/items/2006/08/01.html
  84. Introduction Definition Function Recap Common Idioms Imperative Comparison Challenges! Industry Use Now what? References II Robert Martin Functional Programming Basics http://pragprog.com/magazines/2013-01/ functional-programming-basics John Carmack Functional Programming in C++ http://www.altdevblogaday.com/2012/04/26/ functional-programming-in-c/ Edsger W. Dijkstra Go To Statement Considered Harmful http://www.u.arizona.edu/~rubinson/copyright_ violations/Go_To_Considered_Harmful.html
  85. Introduction Definition Function Recap Common Idioms Imperative Comparison Challenges! Industry Use Now what? References III Tweet by Michael Feathers https://twitter.com/mfeathers/status/29581296216 Alan Jay Perlis http://www.cs.yale.edu/quotes.html Rich Hickey http: //www.infoq.com/presentations/Simple-Made-Easy Andreas Pauley An Introduction to Functional Programming https://github.com/apauley/fp_presentation
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