Let's say we have this list of tuples:
val data = List(('a', List(1, 0)), ('b', List(1, 1)), ('c', List(0)))
The list has this signature:
List[(Char, List[Int])]
My task is to get the "List[Int]" element from a tuple inside "data" whose key is, for instance, letter "b". If I implement a method like "findIntList(data, 'b')", then I expect List(1, 1) as a result. I have tried the following approaches:
data.foreach { elem => if (elem._1 == char) return elem._2 }
data.find(x=> x._1 == ch)
for (elem <- data) yield elem match {case (x, y: List[Bit]) => if (x == char) y}
for (x <- data) yield if (x._1 == char) x._2
With all the approaches (except Approach 1, where I employ an explicit "return"), I get either a List[Option] or List[Any] and I don't know how to extract the "List[Int]" out of it.
One of many ways:
data.toMap.get('b').get
toMap converts a list of 2-tuples into a Map from the first element of the tuples to the second. get gives you the value for the given key and returns an Option, thus you need another get to actually get the list.
Or you can use:
data.find(_._1 == 'b').get._2
Note: Only use get on Option when you can guarantee that you'll have a Some and not a None. See http://www.scala-lang.org/api/current/index.html#scala.Option for how to use Option idiomatic.
Update: Explanation of the result types you see with your different approaches
Approach 2: find returns an Option[List[Int]] because it can not guarantee that a matching element gets found.
Approach 3: here you basically do a map, i.e. you apply a function to each element of your collection. For the element you are looking for the function returns your List[Int] for all other elements it contains the value () which is the Unit value, roughly equivalent to void in Java, but an actual type. Since the only common super type of ´List[Int]´ and ´Unit´ is ´Any´ you get a ´List[Any]´ as the result.
Approach 4 is basically the same as #3
Another way is
data.toMap.apply('b')
Or with one intermediate step this is even nicer:
val m = data.toMap
m('b')
where apply is used implicitly, i.e., the last line is equivalent to
m.apply('b')
There are multiple ways of doing it. One more way:
scala> def listInt(ls:List[(Char, List[Int])],ch:Char) = ls filter (a => a._1 == ch) match {
| case Nil => List[Int]()
| case x ::xs => x._2
| }
listInt: (ls: List[(Char, List[Int])], ch: Char)List[Int]
scala> listInt(data, 'b')
res66: List[Int] = List(1, 1)
You can try something like(when you are sure it exists) simply by adding type information.
val char = 'b'
data.collect{case (x,y:List[Int]) if x == char => y}.head
or use headOption if your not sure the character exists
data.collect{case (x,y:List[Int]) if x == char => y}.headOption
You can also solve this using pattern matching. Keep in mind you need to make it recursive though. The solution should look something like this;
def findTupleValue(tupleList: List[(Char, List[Int])], char: Char): List[Int] = tupleList match {
case (k, list) :: _ if char == k => list
case _ :: theRest => findTupleValue(theRest, char)
}
What this will do is walk your tuple list recursively. Check whether the head element matches your condition (the key you are looking for) and then returns it. Or continues with the remainder of the list.
Related
I do a group-by and I get key -> Stream(of values)
I then need to do a pattern match on the stream collection to access the last item
but the pattern match doesn't work.
When I manually build the list of values using Seq the same pattern match code works
So my question is there a way to convert the Stream to Seq or List?
The IDE says toSeq is redundant
When I manually build the list of values using Seq the same pattern match code works
In scala 2.12, Seq (or sequence) are defaulted to List, see this question:
scala> Seq(1,2,3)
res3: Seq[Int] = List(1, 2, 3)
This is probably why the pattern matching works on your sequence (which happens to be a List) but not an a Stream, see this question.
The IDE says toSeq is redundant
Stream are indeed Seq:
Stream(1,2,3).toSeq
res4: collection.immutable.Seq[Int] = Stream(1, 2, 3)
So my question is there a way to convert the Stream to Seq or List?
To transform a Stream into a List, you can call the .toList method:
Stream(1,2,3).toList
res5: List[Int] = List(1, 2, 3)
Or with this Answer you don't have to transform to List:
val n: Seq[Any] = Stream(..)
n match {
case Nil => "Empty"
case h :: t => "Non-empty"
case h #:: t => "Non-empty stream"
}
For Stream, the concat symbol should be #::, the pattern match should like:
Make sure you reverse the Stream - so you get the last element, here an example:
n.reverse match {
case Nil => "Empty"
case h #:: _ => s"last element is $h"
}
Check it here ScalaFiddle
Suppose that I use a sequence of various maps and/or flatMaps to generate a sequence of collections. Is it possible to access information about the "current" collection from within any of those methods? For example, without knowing anything specific about the functions used in the previous maps or flatMaps, and without using any intermediate declarations, how can I get the maximum value (or length, or first element, etc.) of the collection upon which the last map acts?
List(1, 2, 3)
.flatMap(x => f(x) /* some unknown function */)
.map(x => x + ??? /* what is the max element of the collection? */)
Edit for clarification:
In the example, I'm not looking for the max (or whatever) of the initial List. I'm looking for the max of the collection after the flatMap has been applied.
By "without using any intermediate declarations" I mean that I do not want to use any temporary collections en route to the final result. So, the example by Steve Waldman below, while giving the desired result, is not what I am seeking. (I include this condition is mostly for aesthetic reasons.)
Edit for clarification, part 2:
The ideal solution would be some magic keyword or syntactic sugar that lets me reference the current collection:
List(1, 2, 3)
.flatMap(x => f(x))
.map(x => x + theCurrentList.max)
I'm prepared to accept the fact, however, that this simply is not possible.
Maybe just define the list as a val, so you can name it? I don't know of any facility built into map(...) or flatMap(...) that would help.
val myList = List(1, 2, 3)
myList
.flatMap(x => f(x) /* some unknown function */)
.map(x => x + myList.max /* what is the max element of the List? */)
Update: By this approach at least, if you have multiple transformations and want to see the transformed version, you'd have to name that. You could get away with
val myList = List(1, 2, 3).flatMap(x => f(x) /* some unknown function */)
myList.map(x => x + myList.max /* what is the max element of the List? */)
Or, if there will be multiple transformations, get in the habit of naming the stages.
val rawList = List(1, 2, 3)
val smordified = rawList.flatMap(x => f(x) /* some unknown function */)
val maxified = smordified.map(x => x + smordified.max /* what is the max element of the List? */)
maxified
Update 2: Watch it work in the REPL even with heterogenous types:
scala> def f( x : Int ) : Vector[Double] = Vector(x * math.random, x * math.random )
f: (x: Int)Vector[Double]
scala> val rawList = List(1, 2, 3)
rawList: List[Int] = List(1, 2, 3)
scala> val smordified = rawList.flatMap(x => f(x) /* some unknown function */)
smordified: List[Double] = List(0.40730853571901315, 0.15151641399798665, 1.5305929709857609, 0.35211231420067435, 0.644241939254793, 0.15530230501048903)
scala> val maxified = smordified.map(x => x + smordified.max /* what is the max element of the List? */)
maxified: List[Double] = List(1.937901506704774, 1.6821093849837476, 3.0611859419715217, 1.8827052851864352, 2.1748349102405538, 1.6858952759962498)
scala> maxified
res3: List[Double] = List(1.937901506704774, 1.6821093849837476, 3.0611859419715217, 1.8827052851864352, 2.1748349102405538, 1.6858952759962498)
It is possible, but not pretty, and not likely something you want if you are doing it for "aesthetic reasons."
import scala.math.max
def f(x: Int): Seq[Int] = ???
List(1, 2, 3).
flatMap(x => f(x) /* some unknown function */).
foldRight((List[Int](),List[Int]())) {
case (x, (xs, Nil)) => ((x :: xs), List.fill(xs.size + 1)(x))
case (x, (xs, xMax :: _)) => ((x :: xs), List.fill(xs.size + 1)(max(x, xMax)))
}.
zipped.
map {
case (x, xMax) => x + xMax
}
// Or alternately, a slightly more efficient version using Streams.
List(1, 2, 3).
flatMap(x => f(x) /* some unknown function */).
foldRight((List[Int](),Stream[Int]())) {
case (x, (xs, Stream())) =>
((x :: xs), Stream.continually(x))
case (x, (xs, curXMax #:: _)) =>
val newXMax = max(x, curXMax)
((x :: xs), Stream.continually(newXMax))
}.
zipped.
map {
case (x, xMax) => x + xMax
}
Seriously though, I just took this on to see if I could do it. While the code didn't turn out as bad as I expected, I still don't think it's particularly readable. I'd discourage using this over something similar to Steve Waldman's answer. Sometimes, it's simply better to just introduce a val, rather than being dogmatic about it.
You could define a mapWithSelf (resp. flatMapWithSelf) operation along these lines and add it as an implicit enrichment to the collection. For List it might look like:
// Scala 2.13 APIs
object Enrichments {
implicit class WithSelfOps[A](val lst: List[A]) extends AnyVal {
def mapWithSelf[B](f: (A, List[A]) => B): List[B] =
lst.map(f(_, lst))
def flatMapWithSelf[B](f: (A, List[A]) => IterableOnce[B]): List[B] =
lst.flatMap(f(_, lst))
}
}
The enrichment basically fixes the value of the collection before the operation and threads it through. It should be possible to generify this (at least for the strict collections), though it would look a little different in 2.12 vs. 2.13+.
Usage would look like
import Enrichments._
val someF: Int => IterableOnce[Int] = ???
List(1, 2, 3)
.flatMap(someF)
.mapWithSelf { (x, lst) =>
x + lst.max
}
So at the usage site, it's aesthetically pleasant. Note that if you're computing something which traverses the list, you'll be traversing the list every time (leading to a quadratic runtime). You can get around that with some mutability or by just saving the intermediate list after the flatMap.
One somewhat-simple way of referencing prior output within the current map/collect operation is to use a named reference outside the map, then reference it from within the map block:
var prevOutput = ... // starting value of whatever is referenced within the map
myValues.map {
prevOutput = ... // expression that references prior `prevOutput`
prevOutput // return above computed value for the map to collect
}
This draws attention to the fact that we're referencing prior elements while building the new sequence.
This would be more messy, though, if you wanted to reference arbitrarily previous values, not just the previous one.
Let's say I want to print duplicates in a list with their count. So I have 3 options as shown below:
def dups(dup:List[Int]) = {
//1)
println(dup.groupBy(identity).collect { case (x,ys) if ys.lengthCompare(1) > 0 => (x,ys.size) }.toSeq)
//2)
println(dup.groupBy(identity).collect { case (x, List(_, _, _*)) => x }.map(x => (x, dup.count(y => x == y))))
//3)
println(dup.distinct.map((a:Int) => (a, dup.count((b:Int) => a == b )) ).filter( (pair: (Int,Int) ) => { pair._2 > 1 } ))
}
Questions:
-> For option 2, is there any way to name the list parameter so that it can be used to append the size of the list just like I did in option 1 using ys.size?
-> For option 1, is there any way to avoid the last call to toSeq to return a List?
-> which one of the 3 choices is more efficient by using the least amount of loops?
As an example input: List(1,1,1,2,3,4,5,5,6,100,101,101,102)
Should print: List((1,3), (5,2), (101,2))
Based on #lutzh answer below the best way would be to do the following:
val list: List[(Int, Int)] = dup.groupBy(identity).collect({ case (x, ys # List(_, _, _*)) => (x, ys.size) })(breakOut)
val list2: List[(Int, Int)] = dup.groupBy(identity).collect { case (x, ys) if ys.lengthCompare(1) > 0 => (x, ys.size) }(breakOut)
For option 1 is there any way to avoid the last call to toSeq to
return a List?
collect takes a CanBuildFrom, so if you assign it to something of the desired type you can use breakOut:
import collection.breakOut
val dups: List[(Int,Int)] =
dup
.groupBy(identity)
.collect({ case (x,ys) if ys.size > 1 => (x,ys.size)} )(breakOut)
collect will create a new collection (just like map), using a Builder. Usually the return type is determined by the origin type. With breakOut you basically ignore the origin type and look for a builder for the result type. So when collect creates the resulting collection, it will already create the "right" type, and you don't have to traverse the result again to convert it.
For option 2, is there any way to name the list parameter so that it
can be used to append the size of the list just like I did in option 1
using ys.size?
Yes, you can bind it to a variable with #
val dups: List[(Int,Int)] =
dup
.groupBy(identity)
.collect({ case (x, ys # List(_, _, _*)) => (x, ys.size) } )(breakOut)
which one of the 3 choices is more efficient?
Calling dup.count on a match seems inefficient, as dup needs to be traversed again then, I'd avoid that.
My guess would be that the guard (if lengthCompare(1) > 0) takes a few cycles less than the List(,,_*) pattern, but I haven't measured. And am not planning to.
Disclaimer: There may be a completely different (and more efficient) way of doing it that I can't think of right now. I'm only answering your specific questions.
I was wondering what is the most elegant way of getting the increasing prefix of a given sequence. My idea is as follows, but it is not purely functional or any elegant:
val sequence = Seq(1,2,3,1,2,3,4,5,6)
var currentElement = sequence.head - 1
val increasingPrefix = sequence.takeWhile(e =>
if (e > currentElement) {
currentElement = e
true
} else
false)
The result of the above is:
List(1,2,3)
You can take your solution, #Samlik, and effectively zip in the currentElement variable, but then map it out when you're done with it.
sequence.take(1) ++ sequence.zip(sequence.drop(1)).
takeWhile({case (a, b) => a < b}).map({case (a, b) => b})
Also works with infinite sequences:
val sequence = Seq(1, 2, 3).toStream ++ Stream.from(1)
sequence is now an infinite Stream, but we can peek at the first 10 items:
scala> sequence.take(10).toList
res: List[Int] = List(1, 2, 3, 1, 2, 3, 4, 5, 6, 7)
Now, using the above snippet:
val prefix = sequence.take(1) ++ sequence.zip(sequence.drop(1)).
takeWhile({case (a, b) => a < b}).map({case (a, b) => b})
Again, prefix is a Stream, but not infinite.
scala> prefix.toList
res: List[Int] = List(1, 2, 3)
N.b.: This does not handle the cases when sequence is empty, or when the prefix is also infinite.
If by elegant you mean concise and self-explanatory, it's probably something like the following:
sequence.inits.dropWhile(xs => xs != xs.sorted).next
inits gives us an iterator that returns the prefixes longest-first. We drop all the ones that aren't sorted and take the next one.
If you don't want to do all that sorting, you can write something like this:
sequence.scanLeft(Some(Int.MinValue): Option[Int]) {
case (Some(last), i) if i > last => Some(i)
case _ => None
}.tail.flatten
If the performance of this operation is really important, though (it probably isn't), you'll want to use something more imperative, since this solution still traverses the entire collection (twice).
And, another way to skin the cat:
val sequence = Seq(1,2,3,1,2,3,4,5,6)
sequence.head :: sequence
.sliding(2)
.takeWhile{case List(a,b) => a <= b}
.map(_(1)).toList
// List[Int] = List(1, 2, 3)
I will interpret elegance as the solution that most closely resembles the way we humans think about the problem although an extremely efficient algorithm could also be a form of elegance.
val sequence = List(1,2,3,2,3,45,5)
val increasingPrefix = takeWhile(sequence, _ < _)
I believe this code snippet captures the way most of us probably think about the solution to this problem.
This of course requires defining takeWhile:
/**
* Takes elements from a sequence by applying a predicate over two elements at a time.
* #param xs The list to take elements from
* #param f The predicate that operates over two elements at a time
* #return This function is guaranteed to return a sequence with at least one element as
* the first element is assumed to satisfy the predicate as there is no previous
* element to provide the predicate with.
*/
def takeWhile[A](xs: Traversable[A], f: (Int, Int) => Boolean): Traversable[A] = {
// function that operates over tuples and returns true when the predicate does not hold
val not = f.tupled.andThen(!_)
// Maybe one day our languages will be better than this... (dependant types anyone?)
val twos = sequence.sliding(2).map{case List(one, two) => (one, two)}
val indexOfBreak = twos.indexWhere(not)
// Twos has one less element than xs, we need to compensate for that
// An intuition is the fact that this function should always return the first element of
// a non-empty list
xs.take(i + 1)
}
So this might not be the best way to tackle it but my initial thought was a for expression.
Say I have a List like
List(List('a','b','c'),List('d','e','f'),List('h','i','j'))
I would like to find the row and column for a character, say 'e'.
def findChar(letter: Char, list: List[List[Char]]): (Int, Int) =
for {
r <- (0 until list.length)
c <- (0 until list(r).length)
if list(r)(c) == letter
} yield (r, c)
If there is a more elegant way I'm all ears but I would also like to understand what's wrong with this. Specifically the error the compiler gives me here is
type mismatch; found : scala.collection.immutable.IndexedSeq[(Int, Int)] required: (Int, Int)
on the line assigning to r. It seems to be complaining that my iterator doesn't match the return type but I don't quite understand why this is or what to do about it ...
In the signature of findChar you are telling the compiler that it returns (Int, Int). However, the result of your for expression (as inferred by Scala) is IndexedSeq[(Int, Int)] as the error message indicates. The reason is that (r, c) after yield is produced for every "iteration" in the for expression (i.e., you are generating a sequence of results, not just a single result).
EDIT: As for findChar, you could do:
def findChar(letter: Char, list: List[List[Char]]) = {
val r = list.indexWhere(_ contains letter)
val c = list(r).indexOf(letter)
(r, c)
}
It is not the most efficient solution, but relatively short.
EDIT: Or reuse your original idea:
def findAll(letter: Char, list: List[List[Char]]) =
for {
r <- 0 until list.length
c <- 0 until list(r).length
if list(r)(c) == letter
} yield (r, c)
def findChar(c: Char, xs: List[List[Char]]) = findAll(c, xs).head
In both cases, be aware that an exception occurs if the searched letter is not contained in the input list.
EDIT: Or you write a recursive function yourself, like:
def findPos[A](c: A, list: List[List[A]]) = {
def aux(i: Int, xss: List[List[A]]) : Option[(Int, Int)] = xss match {
case Nil => None
case xs :: xss =>
val j = xs indexOf c
if (j < 0) aux(i + 1, xss)
else Some((i, j))
}
aux(0, list)
}
where aux is a (locally defined) auxiliary function that does the actual recursion (and remembers in which sublist we are, the index i). In this implementation a result of None indicates that the searched element was not there, whereas a successful result might return something like Some((1, 1)).
For your other ear, the question duplicates
How to capture inner matched value in indexWhere vector expression?
scala> List(List('a','b','c'),List('d','e','f'),List('h','i','j'))
res0: List[List[Char]] = List(List(a, b, c), List(d, e, f), List(h, i, j))
scala> .map(_ indexOf 'e').zipWithIndex.find(_._1 > -1)
res1: Option[(Int, Int)] = Some((1,1))