Discussing implementation of list flattener function in scala - list

The flatten function is a function which take a list of list and return a list which is the concatenation of all the lists. As an exercise for functional programming in scala, we have to implement that function with a linear complexity. My solution is :
def flatten[A](l: List[List[A]]): List[A] = {
def outer(ll: List[List[A]]):List[A] = {
ll match {
case Nil => Nil
case Cons(h,t) => inner(t, h)
}
}
def inner(atEnd: List[List[A]], ll: List[A]): List[A] = {
ll match {
case Nil => outer(atEnd)
case Cons(h,t) => Cons(h, inner(atEnd, t))
}
}
outer(l)
}
It works. Now I looked at the solution proposed :
def append[A](a1: List[A], a2: List[A]): List[A] =
a1 match {
case Nil => a2
case Cons(h,t) => Cons(h, append(t, a2))
}
def flatten2[A](l: List[List[A]]): List[A] =
foldRight(l, Nil:List[A])(append)
I am suspicious that flatten2 is really linear. At each iteration of foldLeft, the function append is called. This function will parse all the nodes of the accumulator. The first time, the accumulator is Nil, the second it is l.get(1) then l.get(1) + l.get(2)... So the first list in l won't be crossed only once, but l.length - 1 until the end of the function. Am I right ?
While my implementation really cross each list only once. Is my implementation really faster ?

Consider for example flatten2 (List(List(1,2,3), List(4,5), List(6))), which expands to:
append(List(1,2,3),
append(List(4,5),
append(List(6),
Nil)))
As a comment in the link says, "append takes time proportional to its first argument" and therefore "this function is linear in the total length of all lists". (On the other hand, neither flatten2 nor flatten is tail-recursive, though.)

Related

Optimize solution for the given coding problem

I am a newbie in Scala and I am trying to resolve the following simple coding problem:
Write a listOfLists recursive method that takes a number of strings as varargs and then
creates a list of lists of strings, with one less string in each, so for example:
listOfLists("3","2","1") should give back: List(List("3","2","1"), List("2","1"), List("1"))
The solution I've found is the following:
def listOfLists(strings: String*): List[List[String]] = {
val strLength = strings.length
#tailrec
def recListOfList(result: List[List[String]], accumulator: Int): List[List[String]] = {
accumulator match {
case x if x < strLength =>
recListOfList(result :+ (strings.toList.takeRight(strings.length - accumulator)), accumulator + 1 )
case _ => result
}
}
val res: List[List[String]] = List(strings.toList)
recListOfList(res, 1)
}
The solution works, however I think it could be written much more better.
A problem I can see is that I convert the varargs to a List with the toList method, but a hint that the problem gave me is to use the eta expansion _* but I don't know how to use it in this context.
Then, I tried to find another way to write in a more efficient way the following instruction:
strings.toList.takeRight(strings.length - accumulator))
but this is the only solution that came up in my mind.
Any review is welcome (also say that this solution is a total mess :D (providing the right reasons))
This meets all the specified requirements.
def listOfLists(strings: String*): List[List[String]] =
if (strings.isEmpty) Nil
else strings.toList :: listOfLists(strings.tail:_*)
You can do this:
def listOfLists(strings: String*): List[List[String]] = {
#annotation.tailrec
def loop(remaining: List[String], acc: List[List[String]]): List[List[String]] =
remaining match {
case head :: tail =>
loop(remaining = tail, (head :: tail) :: acc)
case Nil =>
acc.reverse
}
loop(remaining = strings.toList, acc = List.empty)
}
I believe the code is self-explanatory; but, feel free to ask any questions you may have.
You can see the code running here.
Not a recursive method but worth noting that tails in the standard library can do most of this. Then map and filter to convert to correct type and filter out empty list.
def listOfLists(strings: String *): List[List[String]] = strings.tails.map(_.toList).filter(_.nonEmpty).toList
Test:
scala> listOfLists("a","b","c")
val res6: List[List[String]] = List(List(a, b, c), List(b, c), List(c))
Using almost the same idea you can rewrite your solution in cleaner way:
def listOfLists(strings: String*): List[List[String]] = {
#tailrec
def recListOfList(curr: List[String], accumulator: Seq[List[String]]): Seq[List[String]] = {
curr match {
case head :: tail => recListOfList(tail, curr +: accumulator)
case _ => accumulator
}
}
recListOfList(strings.toList, Nil)
.reverse
.toList
}
With the splat(_*) operator, which adapts a sequence (Array, List, Seq, Vector, etc.) to varargs parameter you can create a shorter solution, but it will not be tail-recursive:
def listOfLists(strings: String*): List[List[String]] = {
val curr = strings.toList
curr match {
case Nil => Nil
case x :: tail => curr :: listOfLists(tail:_*)
}
}
From Scala 2.13 you can use List.unfold and Option.when:
def listOfLists(strings: String*): List[List[String]] = {
List.unfold(strings) { s =>
Option.when(s.nonEmpty)(s.toList, s.tail)
}
}
Code run at Scastie.

How to find the largest element in a list of integers recursively?

I'm trying to write a function which will recursively find the largest element in a list of integers. I know how to do this in Java, but can't understand how to do this at Scala.
Here is what I have so far, but without recursion:
def max(xs: List[Int]): Int = {
if (xs.isEmpty) throw new java.util.NoSuchElementException();
else xs.max;
}
How can we find it recursively with Scala semantic.
This is the most minimal recursive implementation of max I've ever been able to think up:
def max(xs: List[Int]): Option[Int] = xs match {
case Nil => None
case List(x: Int) => Some(x)
case x :: y :: rest => max( (if (x > y) x else y) :: rest )
}
It works by comparing the first two elements on the list, discarding the smaller (or the first, if both are equal) and then calling itself on the remaining list. Eventually, this will reduce the list to one element which must be the largest.
I return an Option to deal with the case of being given an empty list without throwing an exception - which forces the calling code to recognise the possibility and deal with it (up to the caller if they want to throw an exception).
If you want it to be more generic, it should be written like this:
def max[A <% Ordered[A]](xs: List[A]): Option[A] = xs match {
case Nil => None
case x :: Nil => Some(x)
case x :: y :: rest => max( (if (x > y) x else y) :: rest )
}
Which will work with any type which either extends the Ordered trait or for which there is an implicit conversion from A to Ordered[A] in scope. So by default it works for Int, BigInt, Char, String and so on, because scala.Predef defines conversions for them.
We can become yet more generic like this:
def max[A <% Ordered[A]](xs: Seq[A]): Option[A] = xs match {
case s if s.isEmpty || !s.hasDefiniteSize => None
case s if s.size == 1 => Some(s(0))
case s if s(0) <= s(1) => max(s drop 1)
case s => max((s drop 1).updated(0, s(0)))
}
Which will work not just with lists but vectors and any other collection which extends the Seq trait. Note that I had to add a check to see if the sequence actually has a definite size - it might be an infinite stream, so we back away if that might be the case. If you are sure your stream will have a definite size, you can always force it before calling this function - it's going to work through the whole stream anyway. See notes at the end for why I really would not want to return None for an indefinite stream, though. I'm doing it here purely for simplicity.
But this doesn't work for sets and maps. What to do? The next common supertype is Iterable, but that doesn't support updated or anything equivalent. Anything we construct might be very poorly performing for the actual type. So my clean no-helper-function recursion breaks down. We could change to using a helper function but there are plenty of examples in the other answers and I'm going to stick with a one-simple-function approach. So at this point, we can to switch to reduceLeft (and while we are at it, let's go for `Traversable' and cater for all collections):
def max[A <% Ordered[A]](xs: Traversable[A]): Option[A] = {
if (xs.hasDefiniteSize)
xs reduceLeftOption({(b, a) => if (a >= b) a else b})
else None
}
but if you don't consider reduceLeft recursive, we can do this:
def max[A <% Ordered[A]](xs: Traversable[A]): Option[A] = xs match {
case i if i.isEmpty => None
case i if i.size == 1 => Some(i.head)
case i if (i collect { case x if x > i.head => x }).isEmpty => Some(i.head)
case _ => max(xs collect { case x if x > xs.head => x })
}
It uses the collect combinator to avoid some clumsy method of bodging a new Iterator out of xs.head and xs drop 2.
Either of these will work safely with almost any collection of anything which has an order. Examples:
scala> max(Map(1 -> "two", 3 -> "Nine", 8 -> "carrot"))
res1: Option[(Int, String)] = Some((8,carrot))
scala> max("Supercalifragilisticexpialidocious")
res2: Option[Char] = Some(x)
I don't usually give these others as examples, because it requires more expert knowledge of Scala.
Also, do remember that the basic Traversable trait provides a max method, so this is all just for practice ;)
Note: I hope that all my examples show how careful choice of the sequence of your case expressions can make each individual case expression as simple as possible.
More Important Note: Oh, also, while I am intensely comfortable returning None for an input of Nil, in practice I'd be strongly inclined to throw an exception for hasDefiniteSize == false. Firstly, a finite stream could have a definite or non-definite size dependent purely on the sequence of evaluation and this function would effectively randomly return Option in those cases - which could take a long time to track down. Secondly, I would want people to be able to differentiate between having passed Nil and having passed truly risk input (that is, an infinite stream). I only returned Option in these demonstrations to keep the code as simple as possible.
The easiest approach would be to use max function of TraversableOnce trait, as follows,
val list = (1 to 10).toList
list.max
to guard against the emptiness you can do something like this,
if(list.empty) None else Some(list.max)
Above will give you an Option[Int]
My second approach would be using foldLeft
(list foldLeft None)((o, i) => o.fold(Some(i))(j => Some(Math.max(i, j))))
or if you know a default value to be returned in case of empty list, this will become more simpler.
val default = 0
(list foldLeft default)(Math.max)
Anyway since your requirement is to do it in recursive manner, I propose following,
def recur(list:List[Int], i:Option[Int] = None):Option[Int] = list match {
case Nil => i
case x :: xs => recur(xs, i.fold(Some(x))(j => Some(Math.max(j, x))))
}
or as default case,
val default = 0
def recur(list:List[Int], i:Int = default):Int = list match {
case Nil => i
case x :: xs => recur(xs, i.fold(x)(j => Math.max(j, x)))
}
Note that, this is tail recursive. Therefore stack is also saved.
If you want functional approach to this problem then use reduceLeft:
def max(xs: List[Int]) = {
if (xs.isEmpty) throw new NoSuchElementException
xs.reduceLeft((x, y) => if (x > y) x else y)
}
This function specific for list of ints, if you need more general approach then use Ordering typeclass:
def max[A](xs: List[A])(implicit cmp: Ordering[A]): A = {
if (xs.isEmpty) throw new NoSuchElementException
xs.reduceLeft((x, y) => if (cmp.gteq(x, y)) x else y)
}
reduceLeft is a higher-order function, which takes a function of type (A, A) => A, it this case it takes two ints, compares them and returns the bigger one.
You could use pattern matching like that
def max(xs: List[Int]): Int = xs match {
case Nil => throw new NoSuchElementException("The list is empty")
case x :: Nil => x
case x :: tail => x.max(max(tail)) //x.max is Integer's class method
}
Scala is a functional language whereby one is encourage to think recursively. My solution as below. I recur it base on your given method.
def max(xs: List[Int]): Int = {
if(xs.isEmpty == true) 0
else{
val maxVal= max(xs.tail)
if(maxVal >= xs.head) maxVal
else xs.head
}
}
Updated my solution to tail recursive thanks to suggestions.
def max(xs: List[Int]): Int = {
def _max(xs: List[Int], maxNum: Int): Int = {
if (xs.isEmpty) maxNum
else {
val max = {
if (maxNum >= xs.head) maxNum
else xs.head
}
_max(xs.tail, max)
}
}
_max(xs.tail, xs.head)
}
I used just head() and tail()
def max(xs: List[Int]): Int = {
if (xs.isEmpty) throw new NoSuchElementException
else maxRecursive(xs.tail, xs.head)
}
def maxRecursive(xs: List[Int], largest: Int): Int = {
if (!xs.isEmpty) {
if (xs.head > largest) maxRecursive(xs.tail, xs.head)
else maxRecursive(xs.tail, largest)
} else {
largest
}
}
Here is tests for this logic:
test("max of a few numbers") {
assert(max(List(3, 7, 2, 1, 10)) === 10)
assert(max(List(3, -7, 2, -1, -10)) === 3)
assert(max(List(-3, -7, -2, -5, -10)) === -2)
}
Folding can help:
if(xs.isEmpty)
throw new NoSuchElementException
else
(Int.MinValue /: xs)((max, value) => math.max(max, value))
List and pattern matching (updated, thanks to #x3ro)
def max(xs:List[Int], defaultValue: =>Int):Int = {
#tailrec
def max0(xs:List[Int], maxSoFar:Int):Int = xs match {
case Nil => maxSoFar
case head::tail => max0(tail, math.max(maxSoFar, head))
}
if(xs.isEmpty)
defaultValue
else
max0(xs, Int.MinValue)
}
(This solution does not create Option instance every time. Also it is tail-recursive and will be as fast as an imperative solution.)
Looks like you're just starting out with scala so I try to give you the simplest answer to your answer, how do it recursively:
def max(xs: List[Int]): Int = {
def maxrec(currentMax : Int, l: List[Int]): Int = l match {
case Nil => currentMax
case head::tail => maxrec(head.max(currentMax), tail) //get max of head and curretn max
}
maxrec(xs.head, xs)
}
This method defines an own inner method (maxrec) to take care of the recursiveness. It will fail ( exception) it you give it an empty list ( there's no maximum on an empty List)
Here is my code (I am a newbie in functional programming) and I'm assuming whoever lands up under this question will be folks like me. The top answer, while great, is bit too much for newbies to take! So, here is my simple answer. Note that I was asked (as part of a Course) to do this using only head and tail.
/**
* This method returns the largest element in a list of integers. If the
* list `xs` is empty it throws a `java.util.NoSuchElementException`.
*
* #param xs A list of natural numbers
* #return The largest element in `xs`
* #throws java.util.NoSuchElementException if `xs` is an empty list
*/
#throws(classOf[java.util.NoSuchElementException])
def max(xs: List[Int]): Int = find_max(xs.head, xs.tail)
def find_max(max: Int, xs: List[Int]): Int = if (xs.isEmpty) max else if (max >= xs.head) find_max(max, xs.tail) else find_max(xs.head, xs.tail)
Some tests:
test("max of a few numbers") {
assert(max(List(3, 7, 2)) === 7)
intercept[NoSuchElementException] {
max(List())
}
assert(max(List(31,2,3,-31,1,2,-1,0,24,1,21,22)) === 31)
assert(max(List(2,31,3,-31,1,2,-1,0,24,1,21,22)) === 31)
assert(max(List(2,3,-31,1,2,-1,0,24,1,21,22,31)) === 31)
assert(max(List(Int.MaxValue,2,3,-31,1,2,-1,0,24,1,21,222,3,-31,1,2,-1,0,24,1,21,222,3,-31,1,2,-1,0,24,1,21,222,3,-31,1,2,-1,0,24,1,21,222,3,-31,1,2,-1,0,24,1,21,222,3,-31,1,2,-1,0,24,1,21,222,3,-31,1,2,-1,0,24,1,21,222,3,-31,1,2,-1,0,24,1,21,222,3,-31,1,2,-1,0,24,1,21,222,3,-31,1,2,-1,0,24,1,21,222,3,-31,1,2,-1,0,24,1,21,222,3,-31,1,2,-1,0,24,1,21,222,3,-31,1,2,-1,0,24,1,21,222,3,-31,1,2,-1,0,24,1,21,222,3,-31,1,2,-1,0,24,1,21,222,3,-31,1,2,-1,0,24,1,21,222,3,-31,1,2,-1,0,24,1,21,222,3,-31,1,2,-1,0,24,1,21,222,3,-31,1,2,-1,0,24,1,21,222,3,-31,1,2,-1,0,24,1,21,222,3,-31,1,2,-1,0,24,1,21,222,3,-31,1,2,-1,0,24,1,21,222,3,-31,1,2,-1,0,24,1,21,222,3,-31,1,2,-1,0,24,1,21,222,3,-31,1,2,-1,0,24,1,21,222,3,-31,1,2,-1,0,24,1,21,222,3,-31,1,2,-1,0,24,1,21,222,3,-31,1,2,-1,0,24,1,21,222,3,-31,1,2,-1,0,24,1,21,222,3,-31,1,2,-1,0,24,1,21,222,3,-31,1,2,-1,0,24,1,21,222,3,-31,1,2,-1,0,24,1,21,222,3,-31,1,2,-1,0,24,1,21,222,3,-31,1,2,-1,0,24,1,21,222,3,-31,1,2,-1,0,24,1,21,222,3,-31,1,2,-1,0,24,1,21,222,3,-31,1,2,-1,0,24,1,21,222,3,-31,1,2,-1,0,24,1,21,222,3,-31,1,2,-1,0,24,1,21,222,3,-31,1,2,-1,0,24,1,21,222,3,-31,1,2,-1,0,24,1,21,222,3,-31,1,2,-1,0,24,1,21,222,3,-31,1,2,-1,0,24,1,21,222,3,-31,1,2,-1,0,24,1,21,222,3,-31,1,2,-1,0,24,1,21,222,3,-31,1,2,-1,0,24,1,21,222,3,-31,1,2,-1,0,24,1,21,222,3,-31,1,2,-1,0,24,1,21,222,3,-31,1,2,-1,0,24,1,21,222,3,-31,1,2,-1,0,24,1,21,222,3,-31,1,2,-1,0,24,1,21,222,3,-31,1,2,-1,0,24,1,21,222,3,-31,1,2,-1,0,24,1,21,222,3,-31,1,2,-1,0,24,1,21,222,3,-31,1,2,-1,0,24,1,21,222,3,-31,1,2,-1,0,24,1,21,222,3,-31,1,2,-1,0,24,1,21,222,3,-31,1,2,-1,0,24,1,21,222,3,-31,1,2,-1,0,24,1,21,222,3,-31,1,2,-1,0,24,1,21,222,3,-31,1,2,-1,0,24,1,21,222,3,-31,1,2,-1,0,24,1,21,222,3,-31,1,2,-1,0,24,1,21,222,3,-31,1,2,-1,0,24,1,21,222,3,-31,1,2,-1,0,24,1,21,222,3,-31,1,2,-1,0,24,1,21,222,3,-31,1,2,-1,0,24,1,21,222,3,-31,1,2,-1,0,24,1,21,222,3,-31,1,2,-1,0,24,1,21,222,3,-31,1,2,-1,0,24,1,21,222,3,-31,1,2,-1,0,24,1,21,22)) === Int.MaxValue)
}
list.sortWith(_ > ).head & list.sortWith( > _).reverse.head for greatest and smallest number
If you are required to write a recursive max function on a list using isEmpty, head and tail and throw exception for empty list:
def max(xs: List[Int]): Int =
if (xs.isEmpty) throw new NoSuchElementException("max of empty list")
else if (xs.tail.isEmpty) xs.head
else if (xs.head > xs.tail.head) max(xs.head :: xs.tail.tail)
else max(xs.tail)
if you were to use max function on list it is simply (you don't need to write your own recursive function):
val maxInt = List(1, 2, 3, 4).max
def max(xs: List[Int]): Int = {
def _max(xs: List[Int], maxAcc:Int): Int = {
if ( xs.isEmpty )
maxAcc
else
_max( xs.tail, Math.max( maxAcc, xs.head ) ) // tail call recursive
}
if ( xs.isEmpty )
throw new NoSuchElementException()
else
_max( xs, Int.MinValue );
}
With tail-recursion
#tailrec
def findMax(x: List[Int]):Int = x match {
case a :: Nil => a
case a :: b :: c => findMax( (if (a > b) a else b) ::c)
}
With pattern matching to find max and return zero in case empty
def findMax(list: List[Int]) = {
def max(list: List[Int], n: Int) : Int = list match {
case h :: t => max(t, if(h > n) h else n)
case _ => n
}
max(list,0)
}
I presume this is for the progfun-example
This is the simplest recursive solution I could come up with
def max(xs: List[Int]): Int = {
if (xs.isEmpty) throw new NoSuchElementException("The list is empty")
val tail = xs.tail
if (!tail.isEmpty) maxOfTwo(xs.head, max(xs.tail))
else xs.head
}
def maxOfTwo(x: Int, y: Int): Int = {
if (x >= y) x
else y
}
def max(xs: List[Int]): Int = xs match {
case Nil => throw new NoSuchElementException("empty list!")
case x :: Nil => x
case x :: tail => if (x > max(tail)) x else max(tail)
}

Pattern matching on a list in Scala

I'm a little confused regarding pattern matching on a list in Scala.
For example.
val simplelist: List[Char] = List('a', 'b', 'c', 'd')
//> simplelist : List[Char] = List(a, b, c, d)
def simple_fun(list: List[Char]) = list match {
case (x:Char) :: (y:List[Char]) => println(x)
case _ => Nil
}
//> simple_fun: (list: List[Char])Any
simple_fun(simplelist)
//> a
//| res0: Any = ()
This currently prints only one line of output. Should it not run/pattern match on each element of the List ?
EDIT: I fixed the compile errors and copied the output from the REPL.
Unless you are repeatedly calling simple_fun in some way, what you have there will pattern match the first element and nothing more. To get it to match the whole list, you can get simple_fun to call itself recursively, like this:
val simplelist: List[Char] = List('a', 'b', 'c', 'd')
def simple_fun(list: List[Char]): List[Nothing] = list match {
case x :: xs => {
println(x)
simple_fun(xs)
}
case _ => Nil
}
Note I've also left out some of the types as the Scala compiler can infer them, leaving you with less cluttered, more readable code.
As a small side-note, calling println repeatedly inside the function like that is not particularly functional - as it is all about side effects. A more idiomatic approach would be to have the function construct a string describing the list, which is then output with a single call to println - so the side-effects are kept in a single well-defined place. Something like this would be one approach:
def simple_fun(list: List[Char]):String = list match {
case x :: xs => x.toString + simple_fun(xs)
case Nil => ""
}
println(simple_fun(simple_list))
I would also like to mention that the case for lists can be divided not only the head and tail, as well as any N number of list elements:
def anyFunction(list: List[Int]): Unit =
list match {
// ...methods that have already been shown
case first :: second :: Nil => println(s"List has only 2 elements: $first and $second")
case first :: second :: tail => println(s"First: $first \nSecond: $second \nTail: $tail")
}
Hope it will be useful to someone.
I think the following should work:
def flatten(l: List[_]): List[Any] = l match {
case Nil => Nil
case (head: List[_]) :: tail => flatten(head) ::: flatten(tail)
case head :: tail => head :: flatten(tail)
}
The first line is a match for Nil, so if we don't find anything return nothing.
The second line will identify List of Lists and recall the flatten method and flatten the list of lists.

How to replace(fill) None entries on List of Options from another List using idiomatic Scala?

I have a List[Option[MyClass]] with None in random positions and I need to 'fill' that list again, from a List[MyClass], maintaining the order.
Here are sample lists and expected result:
val listA = List(Some(3),None,Some(5),None,None)
val listB = List(7,8,9)
val expectedList = List(Some(3), Some(7), Some(5), Some(8), Some(9))
So, how would be a idiomatic Scala to process that list?
def fillL[T](a:List[Option[T]], b:List[T]) = {
val iterB = b.iterator
a.map(_.orElse(Some(iterB.next)))
}
The iterator solution is arguably idiomatic Scala, and is definitely concise and easy to understand, but it's not functional—any time you call next on an iterator you're firmly in the land of side effects.
A more functional approach would be to use a fold:
def fillGaps[A](gappy: List[Option[A]], filler: List[A]) =
gappy.foldLeft((List.empty[Option[A]], filler)) {
case ((current, fs), Some(item)) => (current :+ Some(item), fs)
case ((current, f :: fs), None) => (current :+ Some(f), fs)
case ((current, Nil), None) => (current :+ None, Nil)
}._1
Here we move through the gappy list while maintaining two other lists: one for the items we've processed, and the other for the remaining filler elements.
This kind of solution isn't necessarily better than the other—Scala is designed to allow you to mix functional and imperative constructions in that way—but it does have potential advantages.
I'd just write it in the straightforward way, matching on the heads of the lists and handling each case appropriately:
def fill[A](l1: List[Option[A]], l2: List[A]) = (l1, l2) match {
case (Nil, _) => Nil
case (_, Nil) => l1
case (Some(x) :: xs, _) => Some(x) :: fill(xs, l2)
case (None :: xs, y :: ys) => Some(y) :: fill(xs, ys)
}
Presumably once you run out of things to fill it with, you just leave the rest of the Nones in there.

How should I remove the first occurrence of an object from a list in Scala?

What is the best way to remove the first occurrence of an object from a list in Scala?
Coming from Java, I'm accustomed to having a List.remove(Object o) method that removes the first occurrence of an element from a list. Now that I'm working in Scala, I would expect the method to return a new immutable List instead of mutating a given list. I might also expect the remove() method to take a predicate instead of an object. Taken together, I would expect to find a method like this:
/**
* Removes the first element of the given list that matches the given
* predicate, if any. To remove a specific object <code>x</code> from
* the list, use <code>(_ == x)</code> as the predicate.
*
* #param toRemove
* a predicate indicating which element to remove
* #return a new list with the selected object removed, or the same
* list if no objects satisfy the given predicate
*/
def removeFirst(toRemove: E => Boolean): List[E]
Of course, I can implement this method myself several different ways, but none of them jump out at me as being obviously the best. I would rather not convert my list to a Java list (or even to a Scala mutable list) and back again, although that would certainly work. I could use List.indexWhere(p: (A) ⇒ Boolean):
def removeFirst[E](list: List[E], toRemove: (E) => Boolean): List[E] = {
val i = list.indexWhere(toRemove)
if (i == -1)
list
else
list.slice(0, i) ++ list.slice(i+1, list.size)
}
However, using indices with linked lists is usually not the most efficient way to go.
I can write a more efficient method like this:
def removeFirst[T](list: List[T], toRemove: (T) => Boolean): List[T] = {
def search(toProcess: List[T], processed: List[T]): List[T] =
toProcess match {
case Nil => list
case head :: tail =>
if (toRemove(head))
processed.reverse ++ tail
else
search(tail, head :: processed)
}
search(list, Nil)
}
Still, that's not exactly succinct. It seems strange that there's not an existing method that would let me do this efficiently and succinctly. So, am I missing something, or is my last solution really as good as it gets?
You can clean up the code a bit with span.
scala> def removeFirst[T](list: List[T])(pred: (T) => Boolean): List[T] = {
| val (before, atAndAfter) = list span (x => !pred(x))
| before ::: atAndAfter.drop(1)
| }
removeFirst: [T](list: List[T])(pred: T => Boolean)List[T]
scala> removeFirst(List(1, 2, 3, 4, 3, 4)) { _ == 3 }
res1: List[Int] = List(1, 2, 4, 3, 4)
The Scala Collections API overview is a great place to learn about some of the lesser known methods.
This is a case where a little bit of mutability goes a long way:
def withoutFirst[A](xs: List[A])(p: A => Boolean) = {
var found = false
xs.filter(x => found || !p(x) || { found=true; false })
}
This is easily generalized to dropping the first n items matching the predicate. (i<1 || { i = i-1; false })
You can also write the filter yourself, though at this point you're almost certainly better off using span since this version will overflow the stack if the list is long:
def withoutFirst[A](xs: List[A])(p: A => Boolean): List[A] = xs match {
case x :: rest => if (p(x)) rest else x :: withoutFirst(rest)(p)
case _ => Nil
}
and anything else is more complicated than span without any clear benefits.