Partial function example 1

partial_func_example1.scala

/**
  * Partial Functions
  * When a function is only defined for a specific input.
  */
val between3and10: (String, Int) => Boolean = {case (_, num) => num >= 3 && num <= 10}

val wordFrequencies = ("habitual", 6) :: ("and", 56) :: ("consuetudinary", 2) ::
  ("additionally", 27) :: ("homely", 5) :: ("society", 13) :: Nil

wordFrequencies.filter{case (s,i) => between3and10(s,i) }.map(_._1) //res0: List[String] = List(habitual, homely)

/**
  * In above example we filter then map remaining element.  With PF we can reduce
  * this and iterate over sequence only once thus saving  CPU cycles and code length
  * PartialFunction[-A, +B] type extends the type (A) => B (which can also be written
  * as Function1[A, B]), and a pattern matching anonymous function is always of
  * type PartialFunction.
  *
  * Due to this inheritance hierarchy, passing a pattern matching anonymous function to a
  * method that expects a Function1, like map or filter, is perfectly fine, as long as that
  * function is defined for all input values, i.e. there is always a matching case.
  */
val pf: PartialFunction[(String, Int), String] = {
  case (word, freq) if freq > 3 && freq < 10 => word
}
// Collect expects a partial function and knows how to with not matching inputs
wordFrequencies.collect(pf) // res1: List[String] = List(habitual, homely)

// Note, this is a more verbose way of defining PF by extending Partial Function trait
val pf2 = new PartialFunction[(String, Int), String]   {
  def apply(wordFrequency: (String, Int)) = wordFrequency match {
    case (word, freq) if freq > 3 && freq < 25 => word
  }
  def isDefinedAt(wordFrequency: (String, Int)) = wordFrequency match {
    case (word, freq) if freq > 3 && freq < 25 => true
    case _ => false
  }
}