Recursive Streams and collection in Scala

Recursive forms have their definition in terms of themselves like we have subfolders in folders which can further have subfolders. Recursive methods calling themselves is also a recursive form. Similar forms can be used to create a recursive stream. Example 1: Creating a lazy list 

scala

// Scala program for  recursive stream
// creating object
object Geeks
{

    // Main method
    def main(args: Array[String])
    {
        // second con can be recursive
        lazy val geek = Stream.cons(1, Stream.cons(5, Stream.empty))

        println (geek)

        (geek take 4) foreach {
            x => println(x)

        }
    }
}

Output : 

Stream(1, ?)
1
5

In the code above the second con can be recursive. Example 2: Create a lazy list by placing a recursive call to method 

scala

// Scala program for resursive stream

// creating object
object Geeks
{

    // Main method
    def main(args: Array[String])
    {
        // con can be recursive
        def geek(n: Int): Stream[Int] = Stream.cons(n, geek(n+1))

        // Creating lazy val
        lazy val q = geek(5)

        println(q)
    }
}

Output : 

Stream(5, ?)

Example 3: Create a lazy list by placing a recursive call to method in a brief and clear manner 

scala

// Scala program for resursive stream

// creating object
object Geeks
{

    // Main method
    def main(args: Array[String])
    {
        // recursive stream
        def geek(n: Int):Stream[Int] = n #:: geek(n+1)

        // Lazy value
        lazy val q = geek(5)

        println(q)

    }
}

Output : 

Stream(5, ?)

Stream Collections

Stream collections in scala are very important as it allows need not to be explicitly lopped over. Declaratively things can be performed using functional combinators like map, filter, and flatMap. Streams are lazy lost collections. Example 4: 

scala

// Scala program for stream collection

// creating object
object Geeks
{

    // Main method
    def main(args: Array[String])
    {
        // creating Stream
        def geek(n: Int):Stream[Int] = n #:: geek(n+1)

        lazy val g = geek(0)

        println (g)
        println (g.take(10).mkString(" ; "))
    }
}

Output : 

Stream(0, ?)
0 ; 1 ; 2 ; 3 ; 4 ; 5 ; 6 ; 7 ; 8 ; 9)

Example 5: Using filter 

scala

// Scala program for filter list

// creating object
object Geeks
{

    // Main method
    def main(args: Array[String])
    {
        // Creating list
        val geek = List(1, 2, 3, 4)

        // Using filter
        val abc = geek filter { x => x > 2 }
        println(abc)
    }
}

Output :

List(3, 4)

filter is called over the list geek. It takes function as an argument and returns a Boolean, which is a function predicate. Every element is run through the function and elements are filtered out where the function returns false. It results in a new list and the original “geek” list is remain persistent. Example 6: Using filter in a much concise manner 

scala

// Scala program for collection

// creating object
object Geeks
{

    // Main method
    def main(args: Array[String])
    {
        // Creating list
        val geek = List(1, 2, 3, 4)

        // Filter list
        val abc = geek filter { _ > 2 }
        println(abc)

    }
}

Output :

List(3, 4)

In the code above, there is no need to name the element. The element is referred by a shorter form via a_. Also there is no need to qualify the method call.