A brief introduction to functional programming

A brief introduction to functional programming

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  A brief introductionto functional programming Sebastian Wild Stylight GmbH October 31, 2012
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  Functional programming languages Someprogramming concepts Variables and Functions Currying Functions as parameters Accumulators Advanced examples Summary
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  And that languageis fast. I mean, really astoundingly fast, which is why it is so evil. It’s like that psychotic girlfriend that was amazing in bed. You keep trying to break up with her, but she seduces you right back into that abusive relationship. from brool.com Article: The Genius of Python, The Agony of OCaml
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  Functional programming languages Pure Haskell, Charity, Clean, Curry, Hope, Miranda Impure Erlang, F#, Lisp, ML (Standard ML, OCaml), Scala, Spreadsheets
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  First program # p r i n t s t r i n g ” H e l l o , World ! ” ; ; H e l l o , World : u n i t = ( )
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  Variables and Functions # let a = 5;; val a : int = 5 # let a = 5 + 3;; val a : int = 8 (∗ ! ! A t t e n t i o n ! ! Strong type system ∗) # let a = 5 + 3.0;;
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  Variables and Functions # l e t a = (5 , () , ” Hello ” ) ; ; v a l a : i n t ∗ u n i t ∗ s t r i n g = (5 , ( ) , ” H e l l o ”) # let f x = x ∗ x ;; v a l f : i n t −> i n t = <fun>
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  Currying #let f (x , y) = x ∗ y ; ; v a l f : i n t ∗ i n t −> i n t = <fun>
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  Currying #let f x y = x ∗ y ;; v a l f : i n t −> i n t −> i n t = <fun> ( ∗ Types a r e r i g h t b r a c k e t e d ∗ ) i n t −> ( i n t −> i n t )
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  Currying #let f x y = x ∗ y ;; # let a = f 5;; v a l a : i n t −> i n t = <fun> # let b = a 6;; v a l b : i n t = 30 (∗ Function c a l l s are l e f t b r a c k e t e d ∗) # v a l b = ( f 5) 6 ; ; v a l b : i n t = 30
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  Functions as parameters # let a = [1;2;3;4];; val a : int l i s t = [ 1 ; 2; 3; 4] # l e t r e c map f s = match s w i t h [ ] −> [ ] | x : : x s −> ( f x ) : : ( map f x s ) ; ; v a l map : ( ’ a −> ’ b ) −> ’ a l i s t −> ’ b l i s t = <fun> # l e t b = map ( f u n v −> 2 ∗ v ) a ; ; val b : int l i s t = [ 2 ; 4; 6; 8]
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  Functions as parameters L i s t . f o l d l e f t : ( ’ a −> ’ b −> ’ a ) −> ’ a −> ’ b l i s t − L i s t . f o l d l e f t f a [ b1 ; . . . ; bn ] f ( . . . ( f ( f a b1 ) b2 ) . . . ) # L i s t . f o l d l e f t (+) 0 [ 1 ; 2 ; 3 ; 4 ; 5 ; 6 ] ; ; − : i n t = 21
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  Accumulators Faculty of n: # l e t rec fac n = i f n <= 0 t h e n 1 else n ∗ fac (n − 1 ) ; ; v a l f a c : i n t −> i n t = <fun>
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  Accumulator Tailrecursive: # l e t fac n = l e t r e c fac ’ acc n = i f n <= 0 t h e n a c c e l s e f a c ’ ( n∗ a c c ) ( n−1) i n fac ’ 1 n ; ; v a l f a c : i n t −> i n t = <fun>
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  Advanced examples http://www.ffconsultancy.com/ocaml/bunny/index.html http://www.ffconsultancy.com/ocaml/ray tracer/index.html
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  Summary No side effects Strong type system Mathematical functions can be expressed very easily Steep learning curve https://github.com/wildsebastian/AlgorithmsDataStructures