As far as I understand, the Scala for-comprehension notation relies on the first generator to define how elements are to be combined. Namely, for (i <- list) yield i returns a list and for (i <- set) yield i returns a set.
I was wondering if there was a way to specify how elements are combined independently of the properties of the first generator. For instance, I would like to get "the set of all elements from a given list", or "the sum of all elements from a given set". The only way I have found is to first build a list or a set as prescribed by the for-comprehension notation, then apply a transformation function to it - building a useless data structure in the process.
What I have in mind is a general "algebraic" comprehension notation as it exists for instance in Ateji PX:
`+ { i | int i : set } // the sum of all elements from a given set
set() { i | int i : list } // the set of all elements from a given list
concat(",") { s | String s : list } // string concatenation with a separator symbol
Here the first element (`+, set(), concat(",")) is a so-called "monoid" that defines how elements are combined, independently of the structure of the first generator (there can be multiple generators and filters, I just tried to keep the examples concise).
Any idea about how to achieve a similar result in Scala while keeping a nice and concise notation ? As far as I understand, the for-comprehension notation is hard-wired in the compiler and cannot be upgraded.
Thanks for your feedback.
About the for comprehension
The for comprehension in scala is syntactic sugar for calls to flatMap, filter, map and foreach. In exactly the same way as calls to those methods, the type of the target collection leads to the type of the returned collection. That is:
list map f //is a List
vector map f // is a Vector
This property is one of the underlying design goals of the scala collections library and would be seen as desirable in most situations.
Answering the question
You do not need to construct any intermediate collection of course:
(list.view map (_.prop)).toSet //uses list.view
(list.iterator map (_.prop)).toSet //uses iterator
(for { l <- list.view} yield l.prop).toSet //uses view
(Set.empty[Prop] /: coll) { _ + _.prop } //uses foldLeft
Will all yield Sets without generating unnecessary collections. My personal preference is for the first. In terms of idiomatic scala collection manipulation, each "collection" comes with these methods:
//Conversions
toSeq
toSet
toArray
toList
toIndexedSeq
iterator
toStream
//Strings
mkString
//accumulation
sum
The last is used where the element type of a collection has an implicit Numeric instance in scope; such as:
Set(1, 2, 3, 4).sum //10
Set('a, 'b).sum //does not compile
Note that the String concatenation example in scala looks like:
list.mkString(",")
And in the scalaz FP library might look something like (which uses Monoid to sum Strings):
list.intercalate(",").asMA.sum
Your suggestions do not look anything like Scala; I'm not sure whether they are inspired by another language.
foldLeft? That's what you're describing.
The sum of all elements from a given set:
(0 /: Set(1,2,3))(_ + _)
the set of all elements from a given list
(Set[Int]() /: List(1,2,3,2,1))((acc,x) => acc + x)
String concatenation with a separator symbol:
("" /: List("a", "b"))(_ + _) // (edit - ok concat a bit more verbose:
("" /: List("a", "b"))((acc,x) => acc + (if (acc == "") "" else ",") + x)
You can also force the result type of the for comprehension by explicitly supplying the implicit CanBuildFrom parameter as scala.collection.breakout and specifying the result type.
Consider this REPL session:
scala> val list = List(1, 1, 2, 2, 3, 3)
list: List[Int] = List(1, 1, 2, 2, 3, 3)
scala> val res = for(i <- list) yield i
res: List[Int] = List(1, 1, 2, 2, 3, 3)
scala> val res: Set[Int] = (for(i <- list) yield i)(collection.breakOut)
res: Set[Int] = Set(1, 2, 3)
It results in a type error when not specifying the CanBuildFrom explicitly:
scala> val res: Set[Int] = for(i <- list) yield i
<console>:8: error: type mismatch;
found : List[Int]
required: Set[Int]
val res: Set[Int] = for(i <- list) yield i
^
For a deeper understanding of this I suggest the following read:
http://www.scala-lang.org/docu/files/collections-api/collections-impl.html
If you want to use for comprehensions and still be able to combine your values in some result value you could do the following.
case class WithCollector[B, A](init: B)(p: (B, A) => B) {
var x: B = init
val collect = { (y: A) => { x = p(x, y) } }
def apply(pr: (A => Unit) => Unit) = {
pr(collect)
x
}
}
// Some examples
object Test {
def main(args: Array[String]): Unit = {
// It's still functional
val r1 = WithCollector[Int, Int](0)(_ + _) { collect =>
for (i <- 1 to 10; if i % 2 == 0; j <- 1 to 3) collect(i + j)
}
println(r1) // 120
import collection.mutable.Set
val r2 = WithCollector[Set[Int], Int](Set[Int]())(_ += _) { collect =>
for (i <- 1 to 10; if i % 2 == 0; j <- 1 to 3) collect(i + j)
}
println(r2) // Set(9, 10, 11, 6, 13, 4, 12, 3, 7, 8, 5)
}
}
Related
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.
ScalaCheck generators work with the syntactic sugar in Scala's for expressions:
for( s1 <- Gen.choose(1, 10); s2 <- Gen.choose(10, 100) ) yield ( s1, s2 )
I'd like to be able to mix "traditional" Scala for expressions with ScalaCheck expressions. For example:
for( s0 <- 0 until 10; s1 <- Gen.choose(1, 10); s2 <- Gen.choose(10, 100) ) yield ( s0, s1, s2 )
However, this won't compile, since the 0 until 10 expressions isn't a type of Gen.
How can I achieve this (and Seq and/or Traversable expressions in general) within the same for loop?
EDIT: The consensus in the answers seems to be that the kind of syntactic sugar I'm looking for is not possible.
However, could this not be done with some form of stateful Gen? In particular, one which used the state monad?
I'd like to be able to mix "traditional" Scala for expressions with ScalaCheck expressions.
You cannot do that; at least, not as you suggest. What you can do is to define a generator that produces 10-long lists (i.e. lists of length 10) of triples, in which
the first element is not random (but instead ranges from 0 to 10),
the second element is randomly chosen between 1 and 10,
the third element is randomly chosen between 10 and 100.
Generator implementation
I'm assuming that org.scalacheck.Gen is in scope.
Define a generator for a pair composed of the second and third elements of a triple:
val pairGen: Gen[(Int, Int)] = for {
s1 <- Gen.choose(1, 10)
s2 <- Gen.choose(10, 100)
} yield (s1, s2)
Define a generator for a 10-long list of such pairs:
val listOfPairsGen: Gen[List[(Int, Int)]] = Gen.listOfN(10, pairGen)
Define
val intList: List[Int] = (0 until 10).toList
Zip intList with the result of listOfPairsGen, and "flatten each element to a triple":
val myGen: Gen[List[(Int, Int, Int)]] =
listOfPairsGen map { list: List[(Int, Int)] =>
(intList zip list) map { case (a, (b, c)) => (a, b, c) }
}
Examples
scala> myGen.sample.head
res0: List[(Int, Int, Int)] = List((0,2,58), (1,10,34), (2,3,94), (3,2,91), (4,6,15), (5,7,99), (6,4,82), (7,10,69), (8,8,78), (9,10,27))
scala> myGen.sample.get
res1: List[(Int, Int, Int)] = List((0,2,56), (1,2,83), (2,4,76), (3,4,87), (4,4,55), (5,6,80), (6,4,94), (7,7,67), (8,10,92), (9,4,84))
scala> myGen.sample.get
res2: List[(Int, Int, Int)] = List((0,10,40), (1,9,48), (2,10,63), (3,5,100), (4,5,67), (5,4,73), (6,8,56), (7,6,58), (8,6,82), (9,10,86))
scala> myGen.sample.get
res3: List[(Int, Int, Int)] = List((0,6,56), (1,7,94), (2,4,40), (3,7,27), (4,1,91), (5,3,50), (6,1,70), (7,6,90), (8,7,23), (9,7,49))
As Jubobs already explained, you cannot
mix "traditional" Scala for expressions with ScalaCheck expressions
However, you could achieve the described result with a somewhat less idiomatic approach using an index:
def indexedGenerator = {
val index = new AtomicInteger(0)
for (s1 <- Gen.choose(1, 10); s2 <- Gen.choose(10, 100)) yield (index.getAndIncrement(), s1, s2)
}
val gen = indexedGenerator
println(gen.sample) |-> Some((0,1,60))
println(gen.sample) |-> Some((1,8,82))
println(gen.sample) |-> Some((2,9,29))
println(gen.sample) |-> Some((3,6,76))
println(gen.sample) |-> Some((4,5,32))
Though you would have to be cautious about when and where to instantiate a Generator like this, as the count var will not be reset for every property check. Thus, you need to create a new local instance every time you need the index to start at 0.
I wanted to write it functionally, and the best I could do was:
list.zipWithIndex.filter((tt:Tuple2[Thing,Int])=>(tt._2%3==0)).unzip._1
to get elements 0, 3, 6,...
Is there a more readable Scala idiom for this?
If efficiency is not an issue, you could do the following:
list.grouped(3).map(_.head)
Note that this constructs intermediate lists.
Alternatively you can use a for-comprehension:
for {
(x,i) <- list zipWithIndex
if i % 3 == 0
} yield x
This is of course almost identical to your original solution, just written differently.
My last alternative for you is the use of collect on the zipped list:
list.zipWithIndex.collect {
case (x,i) if i % 3 == 0 => x
}
Not much clear, but still:
xs.indices.collect { case i if i % 3 == 0 => xs(i) }
A nice, functional solution, without creating temporary vectors, lists, and so on:
def everyNth[T](xs: List[T], n:Int): List[T] = xs match {
case hd::tl => hd::everyNth(tl.drop(n-1), n)
case Nil => Nil
}
Clojure has a take-nth function that does what you want, but I was surprised to find that there's not an equivalent method in Scala. You could code up a similar recursive solution based off the Clojure code, or you could read this blog post:
Scala collections: Filtering each n-th element
The author actually has a nice graph at the end showing the relative performance of each of his solutions.
I would do it like in Octave mathematical program.
val indices = 0 until n by 3 // Range 0,3,6,9 ...
and then I needed some way to select the indices from a collection. Obviously I had to have a collection with random-access O(1). Like Array or Vector. For example here I use Vector. To wrap the access into a nice DSL I'd add an implicit class:
implicit class VectorEnrichedWithIndices[T](v:Vector[T]) {
def apply(indices:TraversableOnce[Int]):Vector[T] = {
// some implementation
indices.toVector.map(v)
}
}
The usage would look like:
val vector = list.toVector
val every3rdElement = vector(0 until vector.size by 3)
Ah, how about this?
val l = List(10,9,8,7,6,5,4,3,2,1,0)
for (i <- (0 to l.size - 1 by 3).toList) yield l(i)
//res0: List[Int] = List(10, 7, 4, 1)
which can be made more general by
def seqByN[A](xs: Seq[A], n: Int): Seq[A] = for (i <- 0 to xs.size - 1 by n) yield xs(i)
scala> seqByN(List(10,9,8,7,6,5,4,3,2,1,0), 3)
res1: Seq[Int] = Vector(10,7,4,1)
scala> seqByN(List(10,9,8,7,6,5,4,3,2,1,0), 3).toList
res2: Seq[Int] = List(10,7,4,1)
scala> seqByN(List[Int](), 3)
res1: Seq[Int] = Vector()
But by functional do you mean only using the various List combinator functions? Otherwise, are Streams functional enough?
def fromByN[A](xs: List[A], n: Int): Stream[A] = if (xs.isEmpty) Stream.empty else
xs.head #:: fromByN(xs drop n, n)
scala> fromByN(List(10,9,8,7,6,5,4,3,2,1,0), 3).toList
res17: List[Int] = List(10, 7, 4, 1)
I am writing a Scala program in which there is an operation that creates a sequence. The operation might fail, so I enclose it inside a Try. I want to do sequence creation and enumeration inside a for comprehension, so that a successfully-created sequence yields a sequence of tuples where the first element is the sequence and the second is an element of it.
To simplify the problem, make my sequence a Range of integers and define a createRange function that fails if it is asked to create a range of an odd length. Here is a simple for comprehension that does what I want.
import scala.util.Try
def createRange(n: Int): Try[Range] = {
Try {
if (n % 2 == 1) throw new Exception
else Range(0, n)
}
}
def rangeElements(n: Int) {
for {
r <- createRange(n)
x <- r
} println(s"$r\t$x")
}
def main(args: Array[String]) {
println("Range length 3")
rangeElements(3)
println("Range length 4")
rangeElements(4)
}
If you run this it correctly prints.
Range length 3
Range length 4
Range(0, 1, 2, 3) 0
Range(0, 1, 2, 3) 1
Range(0, 1, 2, 3) 2
Range(0, 1, 2, 3) 3
Now I would like to rewrite my rangeElements function so that instead of printing as a side-effect it returns a sequence of integers, where the sequence is empty if the range was not created. What I want to write is this.
def rangeElements(n: Int):Seq[(Range,Int)] = {
for {
r <- createRange(n)
x <- r
} yield (r, x)
}
// rangeElements(3) returns an empty sequence
// rangeElements(4) returns the sequence (Range(0,1,2,3), 0), (Range(0,1,2,3), 1) etc.
This gives me two type mismatch compiler errors. The r <- createRange(n) line required Seq[Int] but found scala.util.Try[Nothing]. The x <- r line required scala.util.Try[?] but found scala.collection.immutable.IndexedSeq[Int].
Presumably there is some type erasure with the Try that is messing me up, but I can't figure out what it is. I've tried various toOption and toSeq qualifiers on the lines in the for comprehension to no avail.
If I only needed to yield the range elements I could explicitly handle the Success and Failure conditions of createRange myself as suggested by the first two answers below. However, I need access to both the range and its individual elements.
I realize this is a strange-sounding example. The real problem I am trying to solve is a complicated recursive search, but I don't want to add in all its details because that would just confuse the issue here.
How do I write rangeElements to yield the desired sequences?
The problem becomes clear if you translate the for comprehension to its map/flatMap implementation (as described in the Scala Language Spec 6.19). The flatMap has the result type Try[U] but your function expects Seq[Int].
for {
r <- createRange(n)
x <- r
} yield x
createRange(n).flatMap {
case r => r.map {
case x => x
}
}
Is there any reason why you don't use the getOrElse method?
def rangeElements(n: Int):Seq[Int] =
createRange(n) getOrElse Seq.empty
The Try will be Success with a Range when n is even or a Failure with an Exception when n is odd. In rangeElements match and extract those values. Success will contain the valid Range and Failure will contain the Exception. Instead of returning the Exception return an empty Seq.
import scala.util.{Try, Success, Failure}
def createRange(n: Int): Try[Range] = {
Try {
if (n % 2 == 1) throw new Exception
else Range(0, n)
}
}
def rangeElements(n: Int):Seq[Tuple2[Range, Int]] = createRange(n) match {
case Success(s) => s.map(xs => (s, xs))
case Failure(f) => Seq()
}
scala> rangeElements(3)
res35: Seq[(Range, Int)] = List()
scala> rangeElements(4)
res36: Seq[(Range, Int)] = Vector((Range(0, 1, 2, 3),0), (Range(0, 1, 2, 3),1), (Range(0, 1, 2, 3),2), (Range(0, 1, 2,3),3))
I understand Ruby and Python's yield. What does Scala's yield do?
I think the accepted answer is great, but it seems many people have failed to grasp some fundamental points.
First, Scala's for comprehensions are equivalent to Haskell's do notation, and it is nothing more than a syntactic sugar for composition of multiple monadic operations. As this statement will most likely not help anyone who needs help, let's try again… :-)
Scala's for comprehensions is syntactic sugar for composition of multiple operations with map, flatMap and filter. Or foreach. Scala actually translates a for-expression into calls to those methods, so any class providing them, or a subset of them, can be used with for comprehensions.
First, let's talk about the translations. There are very simple rules:
This
for(x <- c1; y <- c2; z <-c3) {...}
is translated into
c1.foreach(x => c2.foreach(y => c3.foreach(z => {...})))
This
for(x <- c1; y <- c2; z <- c3) yield {...}
is translated into
c1.flatMap(x => c2.flatMap(y => c3.map(z => {...})))
This
for(x <- c; if cond) yield {...}
is translated on Scala 2.7 into
c.filter(x => cond).map(x => {...})
or, on Scala 2.8, into
c.withFilter(x => cond).map(x => {...})
with a fallback into the former if method withFilter is not available but filter is. Please see the section below for more information on this.
This
for(x <- c; y = ...) yield {...}
is translated into
c.map(x => (x, ...)).map((x,y) => {...})
When you look at very simple for comprehensions, the map/foreach alternatives look, indeed, better. Once you start composing them, though, you can easily get lost in parenthesis and nesting levels. When that happens, for comprehensions are usually much clearer.
I'll show one simple example, and intentionally omit any explanation. You can decide which syntax was easier to understand.
l.flatMap(sl => sl.filter(el => el > 0).map(el => el.toString.length))
or
for {
sl <- l
el <- sl
if el > 0
} yield el.toString.length
withFilter
Scala 2.8 introduced a method called withFilter, whose main difference is that, instead of returning a new, filtered, collection, it filters on-demand. The filter method has its behavior defined based on the strictness of the collection. To understand this better, let's take a look at some Scala 2.7 with List (strict) and Stream (non-strict):
scala> var found = false
found: Boolean = false
scala> List.range(1,10).filter(_ % 2 == 1 && !found).foreach(x => if (x == 5) found = true else println(x))
1
3
7
9
scala> found = false
found: Boolean = false
scala> Stream.range(1,10).filter(_ % 2 == 1 && !found).foreach(x => if (x == 5) found = true else println(x))
1
3
The difference happens because filter is immediately applied with List, returning a list of odds -- since found is false. Only then foreach is executed, but, by this time, changing found is meaningless, as filter has already executed.
In the case of Stream, the condition is not immediatelly applied. Instead, as each element is requested by foreach, filter tests the condition, which enables foreach to influence it through found. Just to make it clear, here is the equivalent for-comprehension code:
for (x <- List.range(1, 10); if x % 2 == 1 && !found)
if (x == 5) found = true else println(x)
for (x <- Stream.range(1, 10); if x % 2 == 1 && !found)
if (x == 5) found = true else println(x)
This caused many problems, because people expected the if to be considered on-demand, instead of being applied to the whole collection beforehand.
Scala 2.8 introduced withFilter, which is always non-strict, no matter the strictness of the collection. The following example shows List with both methods on Scala 2.8:
scala> var found = false
found: Boolean = false
scala> List.range(1,10).filter(_ % 2 == 1 && !found).foreach(x => if (x == 5) found = true else println(x))
1
3
7
9
scala> found = false
found: Boolean = false
scala> List.range(1,10).withFilter(_ % 2 == 1 && !found).foreach(x => if (x == 5) found = true else println(x))
1
3
This produces the result most people expect, without changing how filter behaves. As a side note, Range was changed from non-strict to strict between Scala 2.7 and Scala 2.8.
It is used in sequence comprehensions (like Python's list-comprehensions and generators, where you may use yield too).
It is applied in combination with for and writes a new element into the resulting sequence.
Simple example (from scala-lang)
/** Turn command line arguments to uppercase */
object Main {
def main(args: Array[String]) {
val res = for (a <- args) yield a.toUpperCase
println("Arguments: " + res.toString)
}
}
The corresponding expression in F# would be
[ for a in args -> a.toUpperCase ]
or
from a in args select a.toUpperCase
in Linq.
Ruby's yield has a different effect.
Yes, as Earwicker said, it's pretty much the equivalent to LINQ's select and has very little to do with Ruby's and Python's yield. Basically, where in C# you would write
from ... select ???
in Scala you have instead
for ... yield ???
It's also important to understand that for-comprehensions don't just work with sequences, but with any type which defines certain methods, just like LINQ:
If your type defines just map, it allows for-expressions consisting of a
single generator.
If it defines flatMap as well as map, it allows for-expressions consisting
of several generators.
If it defines foreach, it allows for-loops without yield (both with single and multiple generators).
If it defines filter, it allows for-filter expressions starting with an if
in the for expression.
Unless you get a better answer from a Scala user (which I'm not), here's my understanding.
It only appears as part of an expression beginning with for, which states how to generate a new list from an existing list.
Something like:
var doubled = for (n <- original) yield n * 2
So there's one output item for each input (although I believe there's a way of dropping duplicates).
This is quite different from the "imperative continuations" enabled by yield in other languages, where it provides a way to generate a list of any length, from some imperative code with almost any structure.
(If you're familiar with C#, it's closer to LINQ's select operator than it is to yield return).
Consider the following for-comprehension
val A = for (i <- Int.MinValue to Int.MaxValue; if i > 3) yield i
It may be helpful to read it out loud as follows
"For each integer i, if it is greater than 3, then yield (produce) i and add it to the list A."
In terms of mathematical set-builder notation, the above for-comprehension is analogous to
which may be read as
"For each integer , if it is greater than , then it is a member of the set ."
or alternatively as
" is the set of all integers , such that each is greater than ."
The keyword yield in Scala is simply syntactic sugar which can be easily replaced by a map, as Daniel Sobral already explained in detail.
On the other hand, yield is absolutely misleading if you are looking for generators (or continuations) similar to those in Python. See this SO thread for more information: What is the preferred way to implement 'yield' in Scala?
Yield is similar to for loop which has a buffer that we cannot see and for each increment, it keeps adding next item to the buffer. When the for loop finishes running, it would return the collection of all the yielded values. Yield can be used as simple arithmetic operators or even in combination with arrays.
Here are two simple examples for your better understanding
scala>for (i <- 1 to 5) yield i * 3
res: scala.collection.immutable.IndexedSeq[Int] = Vector(3, 6, 9, 12, 15)
scala> val nums = Seq(1,2,3)
nums: Seq[Int] = List(1, 2, 3)
scala> val letters = Seq('a', 'b', 'c')
letters: Seq[Char] = List(a, b, c)
scala> val res = for {
| n <- nums
| c <- letters
| } yield (n, c)
res: Seq[(Int, Char)] = List((1,a), (1,b), (1,c), (2,a), (2,b), (2,c), (3,a), (3,b), (3,c))
Hope this helps!!
val aList = List( 1,2,3,4,5 )
val res3 = for ( al <- aList if al > 3 ) yield al + 1
val res4 = aList.filter(_ > 3).map(_ + 1)
println( res3 )
println( res4 )
These two pieces of code are equivalent.
val res3 = for (al <- aList) yield al + 1 > 3
val res4 = aList.map( _+ 1 > 3 )
println( res3 )
println( res4 )
These two pieces of code are also equivalent.
Map is as flexible as yield and vice-versa.
val doubledNums = for (n <- nums) yield n * 2
val ucNames = for (name <- names) yield name.capitalize
Notice that both of those for-expressions use the yield keyword:
Using yield after for is the “secret sauce” that says, “I want to yield a new collection from the existing collection that I’m iterating over in the for-expression, using the algorithm shown.”
taken from here
According to the Scala documentation, it clearly says "yield a new collection from the existing collection".
Another Scala documentation says, "Scala offers a lightweight notation for expressing sequence comprehensions. Comprehensions have the form for (enums) yield e, where enums refers to a semicolon-separated list of enumerators. An enumerator is either a generator which introduces new variables, or it is a filter. "
yield is more flexible than map(), see example below
val aList = List( 1,2,3,4,5 )
val res3 = for ( al <- aList if al > 3 ) yield al + 1
val res4 = aList.map( _+ 1 > 3 )
println( res3 )
println( res4 )
yield will print result like: List(5, 6), which is good
while map() will return result like: List(false, false, true, true, true), which probably is not what you intend.