I want to write a function that flattens a List.
object Flat {
def flatten[T](list: List[T]): List[T] = list match {
case Nil => Nil
case head :: Nil => List(head)
case head :: tail => (head match {
case l: List[T] => flatten(l)
case i => List(i)
}) ::: flatten(tail)
}
}
object Main {
def main(args: Array[String]) = {
println(Flat.flatten(List(List(1, 1), 2, List(3, List(5, 8)))))
}
}
I don't know why it don't work, it returns List(1, 1, 2, List(3, List(5, 8))) but it should be List(1, 1, 2, 3, 5, 8).
Can you give me a hint?
You don't need to nest your match statements. Instead do the matching in place like so:
def flatten(xs: List[Any]): List[Any] = xs match {
case Nil => Nil
case (head: List[_]) :: tail => flatten(head) ++ flatten(tail)
case head :: tail => head :: flatten(tail)
}
My, equivalent to SDJMcHattie's, solution.
def flatten(xs: List[Any]): List[Any] = xs match {
case List() => List()
case (y :: ys) :: yss => flatten(y :: ys) ::: flatten(yss)
case y :: ys => y :: flatten(ys)
}
By delete line 4
case head :: Nil => List(head)
You will get right answer.
Think about the test case
List(List(List(1)))
With line 4 last element in list will not be processed
def flatten(ls: List[Any]): List[Any] = ls flatMap {
case ms: List[_] => flatten(ms)
case e => List(e)
}
If someone does not understand this line of the accepted solution, or did not know that you can annotate a pattern with a type:
case (head: List[_]) :: tail => flatten(head) ++ flatten(tail)
Then look at an equivalent without the type annotation:
case (y :: ys) :: tail => flatten3(y :: ys) ::: flatten3(tail)
case Nil :: tail => flatten3(tail)
So, just for better understanding some alternatives:
def flatten2(xs: List[Any]): List[Any] = xs match {
case x :: xs => x match {
case y :: ys => flatten2(y :: ys) ::: flatten2(xs)
case Nil => flatten2(xs)
case _ => x :: flatten2(xs)
}
case x => x
}
def flatten3(xs: List[Any]): List[Any] = xs match {
case Nil => Nil
case (y :: ys) :: zs => flatten3(y :: ys) ::: flatten3(zs)
case Nil :: ys => flatten3(ys)
case y :: ys => y :: flatten3(ys)
}
val yss = List(List(1,2,3), List(), List(List(1,2,3), List(List(4,5,6))))
flatten2(yss) // res2: List[Any] = List(1, 2, 3, 1, 2, 3, 4, 5, 6)
flatten3(yss) // res2: List[Any] = List(1, 2, 3, 1, 2, 3, 4, 5, 6)
By the way, the second posted answer will do the following, which you probably don't want.
val yss = List(List(1,2,3), List(), List(List(1,2,3), List(List(4,5,6))))
flatten(yss) // res1: List[Any] = List(1, 2, 3, List(), 1, 2, 3, 4, 5, 6)
Related
How can i achieve this? Where xs is a List[Any].
def flatten(xs: List[Any]): List[Any] = {
xs match {
case x: List[Any] :: t => flatten(x) ::: flatten(t)
case x :: t => x :: flatten(t)
case Nil => Nil
}
}
The first case does not work properly. For some reason I cannot give a type to the head of the list x.
As #Luis mentioned, this is really bad idea to use List[Any] but you still want to write flatten, then using reflection you can do like this:
val xs: List[Any] = List(List(1, 2), 3, 4)
def flatten(xs: List[Any]): List[Any] = {
xs match {
case x :: t if x.isInstanceOf[List[_]] => flatten(x.asInstanceOf[List[Any]]) ::: flatten(t)
case x :: t => x :: flatten(t)
case Nil => Nil
}
}
println(flatten(xs)) // List(1, 2, 3, 4)
I write function that group list elements by index, with odd index in first list, even in second. But I don not know how to make it with simple recursion and don not get type mismatch.
Here is the code:
// Simple recursion
def group1(list: List[Int]): (List[Int], List[Int]) = list match {
case Nil => (Nil, Nil)
case head :: Nil => (List(head), Nil)
case head :: tail => // how can I make this case?
}
group1(List(2, 6, 7, 9, 0, 4, 1))
// Tail recursion
def group2(list: List[Int]): (List[Int], List[Int]) = {
def group2Helper(list: List[Int], listA: List[Int], listB: List[Int]): (List[Int], List[Int]) = list match {
case Nil => (listA.reverse, listB.reverse)
case head :: Nil => ((head :: listA).reverse, listB.reverse)
case head :: headNext :: tail => group2Helper(tail, head :: listA, headNext :: listB)
}
group2Helper(list, Nil, Nil)
}
group2(List(2, 6, 7, 9, 0, 4, 1))
You have to invoke the next recursion, unpack the result tuple, pre-pend each head element to the proper List, and repackage the new result tuple.
def group1(list: List[Int]) :(List[Int], List[Int]) = list match {
case Nil => (Nil, Nil)
case head :: Nil => (List(head), Nil)
case hdA :: hdB :: tail => val (lstA, lstB) = group1(tail)
(hdA :: lstA, hdB :: lstB)
}
I want to remove duplicates from the list recursively using pattern matching with Scala
here is my input
val xs = List(1,2,3,4,6,3,2,7,9,4)
Tried code:
def removeDuplicates(xs : List[Int]) : List[Int] = xs match {
case Nil =>Nil
case x::ys => {
if(ys.contains(x)){
removeDuplicates(ys)
} else {
}
/// ???
}
}
I was stuck at the question mark, how to appened my result to the mutable list and return it.
Thank you.
You're close:
def removeDuplicates(xs : List[Int]) : List[Int] = xs match {
case Nil => Nil
case x::ys => if (ys.contains (x)) removeDuplicates (ys) else
x :: removeDuplicates (ys)
}
scala> removeDuplicates (List (1,2,3,4,6,3,2,7,9,4))
res143: List[Int] = List(1, 6, 3, 2, 7, 9, 4)
While this is a brief solution, it isn't tail recursive and therefore vulnerable for stackoverflows - whereas Jean Logearts solution solves the problem.
Here is an alternative solution with an inner function, tailrecursive too:
def removeDuplicates (xsOuter : List[Int]) : List[Int] = {
#annotation.tailrec
def removeDuplicates (xs: List[Int], collected: List[Int]) : List[Int] = xs match {
case Nil => collected
case x :: ys => if (collected.contains (x)) removeDuplicates (ys, collected) else
removeDuplicates (ys, x :: collected)
}
removeDuplicates (xsOuter, Nil)
}
scala> removeDuplicates (List (1,2,3,4,6,3,2,7,9,4))
res151: List[Int] = List(9, 7, 6, 4, 3, 2, 1)
with a bias to the first elements, but with the result reversed, which can be easily corrected by returning collected.reverse in the Nil case, if it is important.
The outer function serves the job to provide a simple, one-argument interface to the user, so he doesn't need to provide an empty List.
Note, that the solution is crying for a type annotation, since it doesn't depend at all on the List elements being of type Int:
scala> def removeDuplicates [A] (xsOuter : List[A]) : List[A] = {
|
| #annotation.tailrec
| def removeDuplicates (xs: List[A], collected: List[A]) : List[A] = xs match {
| case Nil => collected
| case x :: ys => if (collected.contains (x)) removeDuplicates (ys, collected) else
| removeDuplicates (ys, x :: collected)
| }
|
| removeDuplicates (xsOuter, Nil)
| }
removeDuplicates: [A](xsOuter: List[A])List[A]
scala> removeDuplicates (List (1,2,3,4,6,3,2,7,9,4))
res152: List[Int] = List(9, 7, 6, 4, 3, 2, 1)
You need to keep track of the current state: already seen elements using a set (for fast lookup), and the new list being constructed:
#tailrec
def removeDuplicatesRec(
remaining: List[Int],
seen: Set[Int],
acc: List[Int]
): List[Int] = remaining match {
case Nil => acc
case head :: tail =>
if (!seen.contains(head)) removeDuplicatesRec(tail, seen + head, acc :+ head)
else removeDuplicatesRec(tail, seen, acc)
}
def removeDuplicates(xs: List[Int]): List[Int] =
removeDuplicatesRec(xs, Set.empty, List.empty)
Here's a classic approach using an inner function and tail recursion. The tail recursion may not be necessary for small lists but it is easier for me to reason about.
def removeDuplicates(xs : List[Int]) : List[Int] = {
#scala.annotation.tailrec
def accumulator(xs: List[Int], acc: List[Int]):List[Int] = xs match {
case Nil => acc
case h::t if(!acc.contains(h)) => accumulator(t, h :: acc)
case h::t if(acc.contains(h)) => accumulator(t, acc)
}
accumulator(xs, List[Int]())
}
scala> removeDuplicates(List(1,2,3,4,6,3,2,7,9,4))
res16: List[Int] = List(9, 7, 6, 4, 3, 2, 1)
Of course, distinct is the preferred way to do this but this is a good exercise. distinct can be used to verify your solution though.
scala> List(1,2,3,4,6,3,2,7,9,4).distinct == removeDuplicates(List(1,2,3,4,6,3,2,7,9,4)).sorted
res21: Boolean = true
I have the following unit test:
FlattenArray.flatten(
List(0, 2, List(List(2, 3), 8, List(List(100)), null, List(List(null))), -2))
should be(List(0, 2, 2, 3, 8, 100, -2))
With my implementation as follow:
object FlattenArray {
def flatten(list: List[Any]): List[Any] = {
list match {
case Nil => Nil
case (x: List[Any]) :: tail => flatten(x) ::: flatten(tail)
case x :: tail => x :: flatten(tail)
}
}
}
The test if failing because, on case Nil I should add no value to the flatten list: any suggestion on how to do so?
I could filter out from the flatten list null values: is that the correct implementation?
You can add a special case for null :: tail which returns flatten(tail):
def flatten(list: List[Any]): List[Any] = {
list match {
case Nil => Nil
case null :: tail => flatten(tail)
case (x: List[Any]) :: tail => flatten(x) ::: flatten(tail)
case x :: tail => x :: flatten(tail)
}
}
Given e.g.:
List(5, 2, 3, 3, 3, 5, 5, 3, 3, 2, 2, 2)
I'd like to get to:
List(List(5), List(2), List(3, 3, 3), List(5, 5), List(3, 3), List(2, 2, 2))
I would assume there is a simple List function that does this, but am unable to find it.
This is the trick that I normally use:
def split[T](list: List[T]) : List[List[T]] = list match {
case Nil => Nil
case h::t => val segment = list takeWhile {h ==}
segment :: split(list drop segment.length)
}
Actually... It's not, I usually abstract over the collection type and optimize with tail recursion as well, but wanted to keep the answer simple.
val xs = List(5, 2, 3, 3, 3, 5, 5, 3, 3, 2, 2, 2)
Here's another way.
(List(xs.take(1)) /: xs.tail)((l,r) =>
if (l.head.head==r) (r :: l.head) :: l.tail else List(r) :: l
).reverseMap(_.reverse)
Damn Rex Kerr, for writing the answer I'd go for. Since there are minor stylistic differences, here's my take:
list.tail.foldLeft(List(list take 1)) {
case (acc # (lst # hd :: _) :: tl, el) =>
if (el == hd) (el :: lst) :: tl
else (el :: Nil) :: acc
}
Since the elements are identical, I didn't bother reversing the sublists.
list.foldRight(List[List[Int]]()){
(e, l) => l match {
case (`e` :: xs) :: fs => (e :: e :: xs) :: fs
case _ => List(e) :: l
}
}
Or
list.zip(false :: list.sliding(2).collect{case List(a,b) => a == b}.toList)
.foldLeft(List[List[Int]]())((l,e) => if(e._2) (e._1 :: l.head) :: l.tail
else List(e._1) :: l ).reverse
[Edit]
//find the hidden way
//the beauty must be somewhere
//when we talk scala
def split(l: List[Int]): List[List[Int]] =
l.headOption.map{x => val (h,t)=l.span{x==}; h::split(t)}.getOrElse(Nil)
I have these implementations lying around from working on collections methods. In the end I checked in simpler implementations of inits and tails and left out cluster. Every new method no matter how simple ends up collecting a big tax which is hard to see from the outside. But here's the implementation I didn't use.
import generic._
import scala.reflect.ClassManifest
import mutable.ListBuffer
import annotation.tailrec
import annotation.unchecked.{ uncheckedVariance => uV }
def inits: List[Repr] = repSequence(x => (x, x.init), Nil)
def tails: List[Repr] = repSequence(x => (x, x.tail), Nil)
def cluster[A1 >: A : Equiv]: List[Repr] =
repSequence(x => x.span(y => implicitly[Equiv[A1]].equiv(y, x.head)))
private def repSequence(
f: Traversable[A #uV] => (Traversable[A #uV], Traversable[A #uV]),
extras: Traversable[A #uV]*): List[Repr] = {
def mkRepr(xs: Traversable[A #uV]): Repr = newBuilder ++= xs result
val bb = new ListBuffer[Repr]
#tailrec def loop(xs: Repr): List[Repr] = {
val seq = toCollection(xs)
if (seq.isEmpty)
return (bb ++= (extras map mkRepr)).result
val (hd, tl) = f(seq)
bb += mkRepr(hd)
loop(mkRepr(tl))
}
loop(self.repr)
}
[Edit: I forget other people won't know the internals. This code is written from inside of TraversableLike, so it wouldn't run out of the box.]
Here's a slightly cleaner one:
def groupConsequtive[A](list: List[A]): List[List[A]] = list match {
case head :: tail =>
val (t1, t2) = tail.span(_ == head)
(head :: t1) :: groupConsequtive(t2)
case _ => Nil
}
tail-recursive version
#tailrec
def groupConsequtive[A](list: List[A], acc: List[List[A]] = Nil): List[List[A]] = list match {
case head :: tail =>
val (t1, t2) = tail.span(_ == head)
groupConsequtive(t2, acc :+ (head :: t1))
case _ => acc
}
Here's a tail-recursive solution inspired by #Kevin Wright and #Landei:
#tailrec
def sliceEqual[A](s: Seq[A], acc: Seq[Seq[A]] = Seq()): Seq[Seq[A]] = {
s match {
case fst :: rest =>
val (l, r) = s.span(fst==)
sliceEqual(r, acc :+ l)
case Nil => acc
}
}
this could be simpler:
val input = List(5, 2, 3, 3, 3, 5, 5, 3, 3, 2, 2, 2)
input groupBy identity values