Practical Scala - Higher Order Functions

A basic intro to HOF's for Scala newcomers, Part of the Betabeers series

Transcript

1. Practical Scala HOF
2. Who am I? @raulraja 47deg.com raulraja.com Scala, Java, Objective-C
3. 1. HOF Higher Order Functions A function that takes a function as argument or returns another function e.g. map & filter
4. map transforms data
5. map sadness to happiness :( :( :( => :) :) :)
6. map sadness to happiness - JAVA public List<String> mapSadnessToHappiness (List<String> sadness) { List<String> happiness = new ArrayList<String>(sadness.size()); for (int i = 0; i < sadness.size(); i++) { String sadFace = sadness.get(i); String happyFace = sadFace.replace('(', ')'); happiness.add(happyFace); } return happiness; } List<String> sadness = Arrays.asList(":(", ":(", ":("); List<String> happiness = mapSadnessToHappiness(sadness);
7. map sadness to happiness - Scala List(":(", ":(", ":(").map(face => face.replace('(', ')'))
8. map sadness to happiness - Scala List(":(", ":(", ":(").map(_.replace('(', ')'))
9. filter remove the unwanted
10. filter sadness keeping happiness :) :) :( => :) :)
11. filter sadness keeping happiness List(":)", ":)", ":(").filter(_.contains(":)"))
12. Idiomatic Transformations Count char occurrences on a String - JAVA public static int countCharOccurrences(String haystack, char needle) { int count = 0; for (int i = 0; i < haystack.length(); i++) { if (haystack.charAt(i) == needle) { count++; } } return count; } public static Map<Character, Integer> toCharOccurrenceMap(String haystack) { Map<Character, Integer> map = new HashMap<Character, Integer>(); if (haystack != null) { for (int i = 0; i < haystack.length(); i++) { char character = haystack.charAt(i); int count = countCharOccurrences(haystack, character); map.put(character, count); } } return map; } toCharOccurrenceMap("betabeers");
13. Idiomatic Transformations Count char occurrences on a String "betabeers" groupBy identity mapValues (_.size)
14. Key differentiator Higher Order Functions help with most Collection problems that you usually solve by looping over and manually creating intermediate containers. Transformed results stay immutable and thread safe. No need to reinvent the wheel. Code becomes readable and idiomatic "betabeers" groupBy identity mapValues (_.size)
15. Other Powerful HOF’s examples Sum (1 to 1000).reduceLeft( _ + _ ) (1 to 1000).sum Partition filter val (passed, failed) = List(49, 58, 88, 90) partition ( _ > 60 ) min List(14, 35, -7, 46, 98).min max List(14, 35, -7, 46, 98).max Imperative iteration (1 to 10) foreach (println) Parallel Collections (1 to 10).par foreach(_ => println(Thread.currentThread.getName))
16. Become a Scala Master For comprehensions Case Classes Futures Options Traits Either Pattern Matching Monads Actors DSL’s ...