kharandziuk - 10 months ago 34

Scala Question

I am trying to implement flatten function in Scala.

I finished with something like this:

`// implementation`

def flatten(xs: List[Any]): List[Any] =

xs match {

case List() => List()

case y::ys => y match {

case k::ks => flatten(List(k)) ::: flatten(ks) ::: flatten(ys)

case _ => y :: flatten(ys)

}

}

// something like tests

def main(args: Array[String]){

val f1 = flatten(List(List(1, 1), 2, List(3, List(5, 8))))

assert(f1 == List(1, 1, 2, 3, 5, 8))

val f2 = flatten(List(List(List(1), List(1)), 2, List(3, List(5, 8))))

assert(f2 == List(1, 1, 2, 3, 5, 8))

}

This implementation works but uses concatenation(it is slow I think). Can somebody provide(or explain) a solution without list concatenation?

I googled a little bit but most of question about built-in flatten

Answer

For starters, as @om-nom-nom pointed out, there is really no point in talking about anything being idiomatic without addressing the `List[Any]`

. Let's see if we can describe this in a better way.

```
sealed trait Tree[A]
case class Node[A](l: List[Tree[A]]) extends Tree[A]
case class Leaf[A](a: A) extends Tree[A]
def flatten[A](tree: Tree[A]): List[A]
```

It becomes a bit easier to fill in the blanks now.

```
def flatten[A](tree: Tree[A]): List[A] = {
def flattenRec(acc: List[A], t: Tree[A]): List[A] = t match {
case Leaf(a) => a :: acc
case Node(ll) => ll.foldLeft(acc)(flattenRec)
}
flattenRec(Nil, tree).reverse
}
```

However, if we add some additional capability to our `Tree`

using scalaz, then this becomes easier, and in fact may help you do whatever you wanted to do with the flattened list of lists. Here I am providing a definition of `scalaz.Foldable[Tree]`

.

```
import scalaz._
import Scalaz._
object Tree {
implicit def treeFoldable = new Foldable[Tree] {
override def foldMap[A, B](fa: Tree[A])(f: (A) => B)(implicit F: Monoid[B]): B = {
fa match {
case Leaf(a) => f(a)
case Node(l) => l.foldLeft(F.zero)((acc, tree) => F.append(acc, foldMap(tree)(f)))
}
}
override def foldRight[A, B](fa: Tree[A], z: => B)(f: (A, => B) => B): B = fa match {
case Leaf(a) => f(a, z)
case Node(l) => l.foldRight(z)((tree, zz) => foldRight[A, B](tree, zz)(f))
}
}
}
```

Now our flatten becomes simply

```
def flatten2[A](tree: Tree[A]): List[A] = {
Foldable[Tree].foldLeft(tree, List.empty[A])((acc, a) => a :: acc).reverse
}
```

or using the foldable syntax imports

```
def flatten2[A](tree: Tree[A]): List[A] = {
tree.foldLeft(List.empty[A])((acc, a) => a :: acc).reverse
}
```

If we had `Tree[Int]`

we could sum all of the values

```
val numbers: Tree[Int] = Node(List(Leaf(1), Node(List(Leaf(2), Leaf(3))), Leaf(4)))
val sum = numbers.foldLeft(0)(_ + _)
```

As it turns out, scalaz has a very similar Tree already, something I've found incredibly useful. The difference is that scalaz.Tree contains an `A`

with each `Node[A]`

.

Source (Stackoverflow)