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

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
...