This is the problem that I did solve, however being a total imperative Scala noob, I feel I found something totally not elegant. Any ideas of improvement appreciated.
val l1 = 4 :: 1 :: 2 :: 3 :: 4 :: Nil // original list
val insert = List(88,99) // list I want to insert on certain places
// method that finds all indexes of a particular element in a particular list
def indexesOf(element:Any, inList:List[Any]) = {
var indexes = List[Int]()
for(i <- 0 until inList.length) {
if(inList(i) == element) indexes = indexes :+ i
}
indexes
}
var indexes = indexesOf(4, l1) // get indexes where 4 appears in the original list
println(indexes)
var result = List[Any]()
// iterate through indexes and insert in front
for(i <- 0 until indexes.length) {
var prev = if(i == 0) 0 else indexes(i-1)
result = result ::: l1.slice(prev, indexes(i)) ::: insert
}
result = result ::: l1.drop(indexes.last) // append the last bit from original list
println(result)
I was thinking more elegant solution would be achievable with something like this, but that's just pure speculation.
var final:List[Any] = (0 /: indexes) {(final, i) => final ::: ins ::: l1.slice(i, indexes(i))
def insert[A](xs: List[A], extra: List[A])(p: A => Boolean) = {
xs.map(x => if (p(x)) extra ::: List(x) else List(x)).flatten
}
scala> insert(List(4,1,2,3,4),List(88,99)){_ == 4}
res3: List[Int] = List(88, 99, 4, 1, 2, 3, 88, 99, 4)
Edit: explanation added.
Our goal here is to insert a list (called extra) in front of selected elements in another list (here called xs--commonly used for lists, as if one thing is x then lots of them must be the plural xs). We want this to work on any type of list we might have, so we annotate it with the generic type [A].
Which elements are candidates for insertion? When writing the function, we don't know, so we provide a function that says true or false for each element (p: A => Boolean).
Now, for each element in the list x, we check--should we make the insertion (i.e. is p(x) true)? If yes, we just build it: extra ::: List(x) is just the elements of extra followed by the single item x. (It might be better to write this as extra :+ x--add the single item at the end.) If no, we have only the single item, but we make it List(x) instead of just x because we want everything to have the same type. So now, if we have something like
4 1 2 3 4
and our condition is that we insert 5 6 before 4, we generate
List(5 6 4) List(1) List(2) List(3) List(5 6 4)
This is exactly what we want, except we have a list of lists. To get rid of the inner lists and flatten everything into a single list, we just call flatten.
The flatten trick is cute, I wouldn't have thought of using map here myself. From my perspective this problem is a typical application for a fold, as you want go through the list and "collect" something (the result list). As we don't want our result list backwards, foldRight (a.k.a. :\) is here the right version:
def insert[A](xs: List[A], extra: List[A])(p: A => Boolean) =
xs.foldRight(List[A]())((x,xs) => if (p(x)) extra ::: (x :: xs) else x :: xs)
Here's another possibility, using Seq#patch to handle the actual inserts. You need to foldRight so that later indices are handled first (inserts modify the indices of all elements after the insert, so it would be tricky otherwise).
def insert[A](xs: Seq[A], ys: Seq[A])(pred: A => Boolean) = {
val positions = xs.zipWithIndex filter(x => pred(x._1)) map(_._2)
positions.foldRight(xs) { (pos, xs) => xs patch (pos, ys, 0) }
}
Related
I am trying to get the index of a row using Scala from a list consisting of lists of integers List[List[Int]]. I already have two functions that given the row index/column index and the grid as parameters, it outputs all the elements in that row. What I need is a function that given a particular element (eg: 0), it finds its row index and column index and puts them in a list: List[(Int, Int)]. I tried to code a function that gives back an index when encountering 0 and then I passed the function to the whole grid. I don't know if I'm doing it the right way. Also, I couldn't figure out how to return the list.
Also, I cannot use any loops.
Thanks in advance.
def Possibilities(): List[Int] = {
def getRowIndex(elem: Int): Int = elem match
{
case 0 => sudoku.grid.indexOf(sudoku.row(elem))
case x => x
}
val result1 = sudoku.grid map {row => row map getRowIndex}
}
I think with two dimensions it is much easier to write such a method with for comprehensions.
Given a List[List[Int]] like this:
val grid = List(
List(1, 2, 3),
List(4, 5, 6),
List(3, 2, 1))
we can simply walk through all the rows and columns, and check whether each element is the one we are looking for:
def possibilities(findElem: Int): List[(Int, Int)] = {
for (
(row, rowIndex) <- grid.zipWithIndex;
(elem, colIndex) <- row.zipWithIndex
if elem == findElem
) yield (rowIndex, colIndex)
}
The yield keyword creates a collection of the results of the for loop. You can find more details on Scala's forloop syntax here (and a more thorough discussion on how this relates to map, flatMap, etc. here).
So, if you don't want to use a for loop, simply 'translate' it into an equivalent expression using map. flatMap, and withFilter:
def possibilities(findElem: Int): List[(Int, Int)] = {
grid.zipWithIndex flatMap { rowAndIndex =>
rowAndIndex._1.zipWithIndex.withFilter(_._1 == findElem) map { colAndIndex =>
(rowAndIndex._2, colAndIndex._2)
}
}
}
Step 1, create a collection of all possible tuples of indices, with a for comprehension (for looks like a loop but it is not)
val tuples = for (i <- grid.indices; j <- grid.head.indices) yield (i, j)
Step 2, filter this collection
tuples.filter { case (i, j) => grid(i)(j) == valueToFind }
Maybe this might be easy to fix but can you help me out or guide me to a solution. I have a remove function that goes through a List of tuples "List[(String,Any)]" and im trying to replace the 1 index of the value with Nil when the list is being looped over.
But when I try to replace the current v with Nil, it say the v is assigned to "val". Now I understand that scala lists are immutable. So maybe this is what is going wrong?
I tried a Tail recursion implementation as will but when I get out of the def there is a type mismatch. ie: is unit but required: Option[Any]
// remove(k) removes one value v associated with key k
// from the dictionary, if any, and returns it as Some(v).
// It returns None if k is associated to no value.
def remove(key:String):Option[Any] = {
for((k,v) <- d){
if(k == key){
var temp:Option[Any] = Some(v)
v = Nil
return temp
}
}; None
}
Here was the other way of trying to figure out
def remove(key:String):Option[Any] = {
def removeHelper(l:List[(String,Any)]):List[(String,Any)] =
l match {
case Nil => Nil
case (k,v)::t => if (key == k) t else (k,v)::removeHelper(t)
}
d = removeHelper(d)
}
Any Suggestions? This is a homework/Project for school thought I might add that for the people that don't like to help with homework.
Well, there are many ways of answering that question. I'll be outlining the ones I can think of here with my own implementations, but the list is by no means exhaustive (nor, probably, the implementations optimal).
First, you can try with existing combinators - the usual suspects are map, flatMap, foldLeft and foldRight:
def remove_flatMap(key: String, list: List[(String, Any)]): List[(String, Any)] =
// The Java developer in me rebels against creating that many "useless" instances.
list.flatMap {a => if(a._1 == key) Nil else List(a)}
def remove_foldLeft(key: String, list: List[(String, Any)]): List[(String, Any)] =
list.foldLeft(List[(String, Any)]()) {(acc, a) =>
if(a._1 == key) acc
else a :: acc
// Note the call to reverse here.
}.reverse
// This is more obviously correct than the foldLeft version, but is not tail-recursive.
def remove_foldRight(key: String, list: List[(String, Any)]): List[(String, Any)] =
list.foldRight(List[(String, Any)]()) {(a, acc) =>
if(a._1 == key) acc
else a :: acc
}
The problem with these is that, as far as I'm aware, you cannot stop them once a certain condition has been reached: I don't think they solve your problem directly, since they remove all instances of key rather than the first.
You also want to note that:
foldLeft must reverse the list once it's done, since it appends elements in the "wrong" order.
foldRight doesn't have that flaw, but is not tail recursive: it will cause memory issues on large lists.
map cannot be used for your problem, since it only lets us modify a list's values but not its structure.
You can also use your own implementation. I've included two versions, one that is tail-recursive and one that is not. The tail-recursive one is obviously the better one, but is also more verbose (I blame the ugliness of using a List[(String, Any)] rather than Map[String, Any]:
def remove_nonTailRec(key: String, list: List[(String, Any)]): List[(String, Any)] = list match {
case h :: t if h._1 == key => t
// This line is the reason our function is not tail-recursive.
case h :: t => h :: remove_nonTailRec(key, t)
case Nil => Nil
}
def remove_tailRec(key: String, list: List[(String, Any)]): List[(String, Any)] = {
#scala.annotation.tailrec
def run(list: List[(String, Any)], acc: List[(String, Any)]): List[(String, Any)] = list match {
// We've been aggregating in the "wrong" order again...
case h :: t if h._1 == key => acc.reverse ::: t
case h :: t => run(t, h :: acc)
case Nil => acc.reverse
}
run(list, Nil)
}
The better solution is of course to use the right tool for the job: a Map[String, Any].
Note that I do not think I answer your question fully: my examples remove key, while you want to set it to Nil. Since this is your homework, I'll let you figure out how to change my code to match your requirements.
List is the wrong collection to use if any key should only exist once. You should be using Map[String,Any]. With a list,
You have to do extra work to prevent duplicate entries.
Retrieval of a key will be slower, the further down the list it appears. Attempting to retrieve a non-existent key will be slow in proportion to the size of the list.
I guess point 2 is maybe why you are trying to replace it with Nil rather than just removing the key from the list. Nil is not the right thing to use here, really. You are going to get different things back if you try and retrieve a non-existent key compared to one that has been removed. Is that really what you want? How much sense does it make to return Some(Nil), ever?
Here's a couple of approaches which work with mutable or immutable lists, but which don't assume that you successfully stopped duplicates creeping in...
val l1: List[(String, Any)] = List(("apple", 1), ("pear", "violin"), ("banana", Unit))
val l2: List[(Int, Any)] = List((3, 1), (4, "violin"), (7, Unit))
def remove[A,B](key: A, xs: List[(A,B)]) = (
xs collect { case x if x._1 == key => x._2 },
xs map { case x if x._1 != key => x; case _ => (key, Nil) }
)
scala> remove("apple", l1)
res0: (List[(String, Any)], List[(String, Any)]) = (List((1)),List((apple, List()),(pear,violin), (banana,object scala.Unit)))
scala> remove(4, l2)
res1: (List[(Int, Any)], List[(Int, Any)]) = (List((violin)),List((3,1), (4, List()), (7,object scala.Unit)))
scala> remove("snark", l1)
res2: (List[Any], List[(String, Any)]) = (List(),List((apple,1), (pear,violin), (banana,object scala.Unit)))
That returns a list of matching values (so an empty list rather than None if no match) and the remaining list, in a tuple. If you want a version that just completely removes the unwanted key, do this...
def remove[A,B](key: A, xs: List[(A,B)]) = (
xs collect { case x if x._1 == key => x._2 },
xs filter { _._1 != key }
)
But also look at this:
scala> l1 groupBy {
case (k, _) if k == "apple" => "removed",
case _ => "kept"
}
res3: scala.collection.immutable.Map[String,List[(String, Any)]] = Map(removed -> List((apple,1)), kept -> List((pear,violin), (banana,object scala.Unit)))
That is something you could develop a bit. All you need to do is add ("apple", Nil) to the "kept" list and extract the value(s) from the "removed" list.
Note that I am using the List combinator functions rather than writing my own recursive code; this usually makes for clearer code and is often as fast or faster than a hand-rolled recursive function.
Note also that I don't change the original list. This means my function works with both mutable and immutable lists. If you have a mutable list, feel free to assign my returned list as the new value for your mutable var. Win, win.
But please use a map for this. Look how simple things become:
val m1: Map[String, Any] = Map(("apple", 1), ("pear", "violin"), ("banana", Unit))
val m2: Map[Int, Any] = Map((3, 1), (4, "violin"), (7, Unit))
def remove[A,B](key: A, m: Map[A,B]) = (m.get(key), m - key)
scala> remove("apple", m1)
res0: (Option[Any], scala.collection.immutable.Map[String,Any]) = (Some(1),Map(pear -> violin, banana -> object scala.Unit))
scala> remove(4, m2)
res1: (Option[Any], scala.collection.immutable.Map[Int,Any]) = (Some(violin),Map(3 -> 1, 7 -> object scala.Unit))
scala> remove("snark", m1)
res2: res26: (Option[Any], scala.collection.immutable.Map[String,Any]) = (None,Map(apple -> 1, pear -> violin, banana -> object scala.Unit))
The combinator functions make things easier, but when you use the right collection, it becomes so easy that it is hardly worth writing a special function. Unless, of course, you are trying to hide the data structure - in which case you should really be hiding it inside an object.
Given a list of elements of which some are repeated multiple times, i need to produce a new list with tuples, where each tuple contains number of times an element is repeated in a row and an element itself.
For example, given
println(func(List())) // should be empty list
println(func(List(1, 1))) // (2,1) <- 1 is repeated 2 times
println(func(List(1, 1, 2, 1))) // (2,1)(1,2)(1,1)
This is my best attempt at this point. I feel that i am missing something very basic, please help me understand what
def func[X](xs: List[X]): List[(Int, X)] = xs match {
case Nil => Nil
case y :: ys => ys match {
case Nil => (1, y) :: Nil
case z :: zs => if (y != z) (ys.prefixLength(_ == ys.head), y) :: func(ys)
else func(ys)
}
}
After analyzing what the problem is, it seems to me that at the point when i recursively call func(ys), ys does not have enough information to figure out the count of elements. Say we're dealing with List(1,1,1,2). Ok, so, y is 1, z is 1 and (1::(2::Nil)) is zs. Following my logic above, the fact that 1 was seen 2 times is lost for the next call.
The problem may be that i am not thinking about the problem the right way. What i have in mind is "go along the list until you find that this element is not the same as a previous elements, at which point, count the number of occurrences of an element and make it into the tuple")
I recognize that in the above scenario (in my code) the problem is that when numbers are in fact the same (1,1) the fact that we already saw a number is not reflected anywhere. But where can this be done please, given that i am not yet ready to compose a tuple
In answering this question, please stick to case structure. I realize that there maybe other better, cleaner ways to address this problem, i would like to better understand what i am doing wrong here
You're on the right track. The problem is that you can't just incrementally build the result list here—you'll have to pull the head off the list you get from the recursive call and check whether you need to add a new pair or increment the count of the last one:
def func[X](xs: List[X]): List[(Int, X)] = xs match {
case Nil => Nil
case y :: ys => func(ys) match {
case (c, `y`) :: rest => (c + 1, y) :: rest
case rest => ( 1, y) :: rest
}
}
Note the backticks around y in the nested match pattern—this is necessary to avoid just defining a new variable named y.
Here's a simpler solution using span:
def runLength[T](xs: List[T]): List[(Int, T)] = xs match {
case Nil => List()
case x :: l => {
val (front, back) = l.span(_ == x)
(front.length + 1, x) :: runLength(back)
}
}
It is indeed run-length encoding.
Here's a straightforward, though generic,attempt...
package rrs.scribble
object RLE {
def rle[T](tSeq: List[T]): List[(Int, T)] = {
def doRLE(seqT: List[T], rle: List[(Int, T)]): List[(Int, T)] =
seqT match {
case t :: moreT if t == rle.head._2 => doRLE(moreT, (rle.head._1 + 1, t) :: rle.tail)
case t :: moreT => doRLE(moreT, (1, t) :: rle)
case Nil => rle
}
if (tSeq.isEmpty)
List.empty[(Int, T)]
else
doRLE(tSeq, List((0, tSeq.head))).reverse
}
}
In the REPL:
scala> import rrs.scribble.RLE._
import rrs.scribble.RLE._
scala> rle(List(1, 1, 2, 1))
res0: List[(Int, Int)] = List((2,1), (1,2), (1,1))
This is called run-length encoding. Check out problem 10 of 99 Scala Problems (click on the problem numbers for solutions).
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.
I have a list l:List[T1] and currently im doing the following:
myfun : T1 -> Option[T2]
val x: Option[T2] = l.map{ myfun(l) }.flatten.find(_=>true)
The myfun function returns None or Some, flatten throws away all the None's and find returns the first element of the list if any.
This seems a bit hacky to me. Im thinking that there might exist some for-comprehension or similar that will do this a bit less wasteful or more clever.
For example: I dont need any subsequent answers if myfun returns any Some during the map of the list l.
How about:
l.toStream flatMap (myfun andThen (_.toList)) headOption
Stream is lazy, so it won't map everything in advance, but it won't remap things either. Instead of flattening things, convert Option to List so that flatMap can be used.
In addition to using toStream to make the search lazy, we can use Stream::collectFirst:
List(1, 2, 3, 4, 5, 6, 7, 8).toStream.map(myfun).collectFirst { case Some(d) => d }
// Option[String] = Some(hello)
// given def function(i: Int): Option[String] = if (i == 5) Some("hello") else None
This:
Transforms the List into a Stream in order to stop the search early.
Transforms elements using myFun as Option[T]s.
Collects the first mapped element which is not None and extract it.
Starting Scala 2.13, with the deprecation of Streams in favor of LazyLists, this would become:
List(1, 2, 3, 4, 5, 6, 7, 8).to(LazyList).map(function).collectFirst { case Some(d) => d }
Well, this is almost, but not quite
val x = (l flatMap myfun).headOption
But you are returning a Option rather than a List from myfun, so this may not work. If so (I've no REPL to hand) then try instead:
val x = (l flatMap(myfun(_).toList)).headOption
Well, the for-comprehension equivalent is pretty easy
(for(x<-l, y<-myfun(x)) yield y).headOption
which, if you actually do the the translation works out the same as what oxbow_lakes gave. Assuming reasonable laziness of List.flatmap, this is both a clean and efficient solution.
As of 2017, the previous answers seem to be outdated. I ran some benchmarks (list of 10 million Ints, first match roughly in the middle, Scala 2.12.3, Java 1.8.0, 1.8 GHz Intel Core i5). Unless otherwise noted, list and map have the following types:
list: scala.collection.immutable.List
map: A => Option[B]
Simply call map on the list: ~1000 ms
list.map(map).find(_.isDefined).flatten
First call toStream on the list: ~1200 ms
list.toStream.map(map).find(_.isDefined).flatten
Call toStream.flatMap on the list: ~450 ms
list.toStream.flatMap(map(_).toList).headOption
Call flatMap on the list: ~100 ms
list.flatMap(map(_).toList).headOption
First call iterator on the list: ~35 ms
list.iterator.map(map).find(_.isDefined).flatten
Recursive function find(): ~25 ms
def find[A,B](list: scala.collection.immutable.List[A], map: A => Option[B]) : Option[B] = {
list match {
case Nil => None
case head::tail => map(head) match {
case None => find(tail, map)
case result # Some(_) => result
}
}
}
Iterative function find(): ~25 ms
def find[A,B](list: scala.collection.immutable.List[A], map: A => Option[B]) : Option[B] = {
for (elem <- list) {
val result = map(elem)
if (result.isDefined) return result
}
return None
}
You can further speed up things by using Java instead of Scala collections and a less functional style.
Loop over indices in java.util.ArrayList: ~15 ms
def find[A,B](list: java.util.ArrayList[A], map: A => Option[B]) : Option[B] = {
var i = 0
while (i < list.size()) {
val result = map(list.get(i))
if (result.isDefined) return result
i += 1
}
return None
}
Loop over indices in java.util.ArrayList with function returning null instead of None: ~10 ms
def find[A,B](list: java.util.ArrayList[A], map: A => B) : Option[B] = {
var i = 0
while (i < list.size()) {
val result = map(list.get(i))
if (result != null) return Some(result)
i += 1
}
return None
}
(Of course, one would usually declare the parameter type as java.util.List, not java.util.ArrayList. I chose the latter here because it's the class I used for the benchmarks. Other implementations of java.util.List will show different performance - most will be worse.)