Scala actor kills itself inconsistently - scala

I am a newbie to scala and I am writing scala code to implement pastry protocol. The protocol itself does not matter. There are nodes and each node has a routing table which I want to populate.
Here is the part of the code:
def act () {
def getMatchingNode (initialMatch :String) : Int = {
val len = initialMatch.length
for (i <- 0 to noOfNodes-1) {
var flag : Int = 1
for (j <- 0 to len-1) {
if (list(i).key.charAt(j) == initialMatch(j)) {
continue
}
else {
flag = 0
}
}
if (flag == 1) {
return i
}
}
return -1
}
// iterate over rows
for (ii <- 0 to rows - 1) {
for (jj <- 0 to 15) {
var initialMatch = ""
for (k <- 0 to ii-1) {
initialMatch = initialMatch + key.charAt(k)
}
initialMatch += jj
println("initialMatch",initialMatch)
if (getMatchingNode(initialMatch) != -1) {
Routing(0)(jj) = list(getMatchingNode(initialMatch)).key
}
else {
Routing(0)(jj) = "NULL"
}
}
}
}// act
The problem is when the function call to getMatchingNode takes place then the actor dies suddenly by itself. 'list' is the list of all nodes. (list of node objects)
Also this behaviour is not consistent. The call to getMatchingNode should take place 15 times for each actor (for 10 nodes).
But while debugging the actor kills itself in the getMatchingNode function call after one call or sometimes after 3-4 calls.
The scala library code which gets executed is this :
def run() {
try {
beginExecution()
try {
if (fun eq null)
handler(msg)
else
fun()
} catch {
case _: KillActorControl =>
// do nothing
case e: Exception if reactor.exceptionHandler.isDefinedAt(e) =>
reactor.exceptionHandler(e)
}
reactor.kill()
}
Eclipse shows that this code has been called from the for loop in the getMatchingNode function
def getMatchingNode (initialMatch :String) : Int = {
val len = initialMatch.length
for (i <- 0 to noOfNodes-1)
The strange thing is that sometimes the loop behaves normally and sometimes it goes to the scala code which kills the actor.
Any inputs what wrong with the code??
Any help would be appreciated.

Got the error..
The 'continue' clause in the for loop caused the trouble.
I thought we could use continue in Scala as we do in C++/Java but it does not seem so.
Removing the continue solved the issue.

From the book: "Programming in Scala 2ed" by M.Odersky
You may have noticed that there has been no mention of break or continue.
Scala leaves out these commands because they do not mesh well with function
literals, a feature described in the next chapter. It is clear what continue
means inside a while loop, but what would it mean inside a function literal?
While Scala supports both imperative and functional styles of programming,
in this case it leans slightly towards functional programming in exchange
for simplifying the language. Do not worry, though. There are many ways to
program without break and continue, and if you take advantage of function
literals, those alternatives can often be shorter than the original code.
I really suggest reading the book if you want to learn scala
Your code is based on tons of nested for loops, which can be more often than not be rewritten using the Higher Order Functions available on the most appropriate Collection.
You can rewrite you function like the following [I'm trying to make it approachable for newcomers]:
//works if "list" contains "nodes" with an attribute "node.key: String"
def getMatchingNode (initialMatch :String) : Int = {
//a new list with the corresponding keys
val nodeKeys = list.map(node => node.key)
//zips each key (creates a pair) with the corresponding index in the list and then find a possible match
val matchOption: Option[(String, Int)] = (nodeKeys.zipWithIndex) find {case (key, index) => key == initialMatch}
//we convert an eventual result contained in the Option, with the right projection of the pair (which contains the index)
val idxOption = matchOption map {case (key, index) => index} //now we have an Option[Int] with a possible index
//returns the content of option if it's full (Some) or a default value of "-1" if there was no match (None). See Option[T] for more details
idxOption.getOrElse(-1)
}
The potential to easily transform or operate on the Collection's elements is what makes continues, and for loops in general, less used in Scala
You can convert the row iteration in a similar way, but I would suggest that if you need to work a lot with the collection's indexes, you want to use an IndexedSeq or one of its implementations, like ArrayBuffer.

Related

Scala: what is the interest in using Iterators?

I have used Iterators after have worked with Regexes in Scala but I don't really understand the interest.
I know that it has a state and if I call the next() method on it, it will output a different result every time, but I don't see anything I can do with it and that is not possible with an Iterable.
And it doesn't seem to work as Akka Streams (for example) since the following example directly prints all the numbers (without waiting one second as I would expect it):
lazy val a = Iterator({Thread.sleep(1000); 1}, {Thread.sleep(1000); 2}, {Thread.sleep(1000); 3})
while(a.hasNext){ println(a.next()) }
So what is the purpose of using Iterators?
Perhaps, the most useful property of iterators is that they are lazy.
Consider something like this:
(1 to 10000)
.map { x => x * x }
.map { _.toString }
.find { _ == "4" }
This snippet will square 10000 numbers, then generate 10000 strings, and then return the second one.
This on the other hand:
(1 to 10000)
.iterator
.map { x => x * x }
.map { _.toString }
.find { _ == "4" }
... only computes two squares, and generates two strings.
Iterators are also often useful when you need to wrap around some poorly designed (java?) objects in order to be able to handle them in functional style:
val rs: ResultSet = jdbcQuery.executeQuery()
new Iterator {
def next = rs
def hasNext = rs.next
}.map { rs =>
fetchData(rs)
}
Streams are similar to iterators - they are also lazy, and also useful for wrapping:
Stream.continually(rs).takeWhile { _.next }.map(fetchData)
The main difference though is that streams remember the data that gets materialized, so that you can traverse them more than once. This is convenient, but may be costly if the original amount of data is very large, especially, if it gets filtered down to much smaller size:
Source
.fromFile("huge_file.txt")
.getLines
.filter(_ == "")
.toList
This only uses, roughly (ignoring buffering, object overhead, and other implementation specific details), the amount of memory, necessary to keep one line in memory, plus however many empty lines there are in the file.
This on the other hand:
val reader = new FileReader("huge_file.txt")
Stream
.continually(reader.readLine)
.takeWhile(_ != null)
.filter(_ == "")
.toList
... will end up with the entire content of the huge_file.txt in memory.
Finally, if I understand the intent of your example correctly, here is how you could do it with iterators:
val iterator = Seq(1,2,3).iterator.map { n => Thread.sleep(1000); n }
iterator.foreach(println)
// Or while(iterator.hasNext) { println(iterator.next) } as you had it.
There is a good explanation of what iterator is http://www.scala-lang.org/docu/files/collections-api/collections_43.html
An iterator is not a collection, but rather a way to access the
elements of a collection one by one. The two basic operations on an
iterator it are next and hasNext. A call to it.next() will return the
next element of the iterator and advance the state of the iterator.
Calling next again on the same iterator will then yield the element
one beyond the one returned previously. If there are no more elements
to return, a call to next will throw a NoSuchElementException.
First of all you should understand what is wrong with your example:
lazy val a = Iterator({Thread.sleep(1); 1}, {Thread.sleep(1); 2},
{Thread.sleep(2); 3}) while(a.hasNext){ println(a.next()) }
if you look at the apply method of Iterator, you'll see there are no calls by name,so all Thread.sleep are calling at the same time when apply method calls. Also Thread.sleep takes parameter of time to sleep in milliseconds, so if you want to sleep your thread on one second you should pass Thread.sleep(1000).
The companion object has additional methods which allow you do the next:
val a = Iterator.iterate(1)(x => {Thread.sleep(1000); x+1})
Iterator is very useful when you need to work with large data. Also you can implement your own:
val it = new Iterator[Int] {
var i = -1
def hasNext = true
def next(): Int = { i += 1; i }
}
I don't see anything I can do with it and that is not possible with an Iterable
In fact, what most collection can do can also be done with Array, but we don't do that because it's much less convenient
So same reason apply to iterator, if you want to model a mutable state, then iterator makes more sense.
For example, Random is implemented in a way resemble to iterator because it's use case fit more naturally in iterator, rather than iterable.

Scala - Iterate Over Two Arrays

How do you iterate over two arrays of the same size, accessing the same index each iteration The Scala Way™?
for ((aListItem, bListItem) <- (aList, bList)) {
// do something with items
}
The Java way applied to Scala:
for(i <- 0 until aList.length ) {
aList(i)
bList(i)
}
Assume both lists are the same size.
tl;dr: There are trade-offs between speed and convenience; you need to know your use case to pick appropriately.
If you know both arrays are the same length and you don't need to worry how fast it is, the easiest and most canonical is to use zip inside a for-comprehension:
for ((a,b) <- aList zip bList) { ??? }
The zip method creates a new single array, however. To avoid that overhead you can use zipped on a tuple which will present the elements in pairs to methods like foreach and map:
(aList, bList).zipped.foreach{ (a,b) => ??? }
Faster still is to index into the arrays, especially if the arrays contain primitives like Int, since the generic code above has to box them. There is a handy method indices that you can use:
for (i <- aList.indices) { ??? }
Finally, if you need to go as fast as you possibly can, you can fall back to manual while loops or recursion, like so:
// While loop
var i = 0
while (i < aList.length) {
???
i += 1
}
// Recursion
def loop(i: Int) {
if (i < aList.length) {
???
loop(i+1)
}
}
loop(0)
If you are computing some value, rather than having it be a side effect, it's sometimes faster with recursion if you pass it along:
// Recursion with explicit result
def loop(i: Int, acc: Int = 0): Int =
if (i < aList.length) {
val nextAcc = ???
loop(i+1, nextAcc)
}
else acc
Since you can drop a method definition in anywhere, you can use recursion without restriction. You can add an #annotation.tailrec annotation to make sure it can be compiled down to a fast loop with jumps instead of actual recursion that eats stack space.
Taking all these different approaches to calculate a dot product on length 1024 vectors, we can compare these to a reference implementation in Java:
public class DotProd {
public static int dot(int[] a, int[] b) {
int s = 0;
for (int i = 0; i < a.length; i++) s += a[i]*b[i];
return s;
}
}
plus an equivalent version where we take the dot product of the lengths of strings (so we can assess objects vs. primitives)
normalized time
-----------------
primitive object method
--------- ------ ---------------------------------
100% 100% Java indexed for loop (reference)
100% 100% Scala while loop
100% 100% Scala recursion (either way)
185% 135% Scala for comprehension on indices
2100% 130% Scala zipped
3700% 800% Scala zip
This is particularly bad, of course, with primitives! (You get similarly huge jumps in time taken if you try to use ArrayLists of Integer instead of Array of int in Java.) Note in particular that zipped is quite a reasonable choice if you have objects stored.
Do beware of premature optimization, though! There are advantages to in clarity and safety to functional forms like zip. If you always write while loops because you think "every little bit helps", you're probably making a mistake because it takes more time to write and debug, and you could be using that time optimizing some more important part of your program.
But, assuming your arrays are the same length is dangerous. Are you sure? How much effort will you make to be sure? Maybe you shouldn't make that assumption?
If you don't need it to be fast, just correct, then you have to choose what to do if the two arrays are not the same length.
If you want to do something with all the elements up to the length of the shorter, then zip is still what you use:
// The second is just shorthand for the first
(aList zip bList).foreach{ case (a,b) => ??? }
for ((a,b) <- (aList zip bList)) { ??? }
// This avoids an intermediate array
(aList, bList).zipped.foreach{ (a,b) => ??? }
If you instead want to pad the shorter one with a default value, you would
aList.zipAll(bList, aDefault, bDefault).foreach{ case (a,b) => ??? }
for ((a,b) <- aList.zipAll(bList, aDefault, bDefault)) { ??? }
In any of these cases, you can use yield with for or map instead of foreach to generate a collection.
If you need the index for a calculation or it really is an array and you really need it to be fast, you will have to do the calculation manually. Padding missing elements is awkward (I leave that as an exercise to the reader), but the basic form would be:
for (i <- 0 until math.min(aList.length, bList.length)) { ??? }
where you then use i to index into aList and bList.
If you really need maximum speed you would again use (tail) recursion or while loops:
val n = math.min(aList.length, bList.length)
var i = 0
while (i < n) {
???
i += 1
}
def loop(i: Int) {
if (i < aList.length && i < bList.length) {
???
loop(i+1)
}
}
loop(0)
Something like:
for ((aListItem, bListItem) <- (aList zip bList)) {
// do something with items
}
Or with map like:
(aList zip bList).map{ case (alistItem, blistItem) => // do something }
Updated:
For iterating without creating an intermediates, you can try:
for (i <- 0 until xs.length) ... //xs(i) & ys(i) to access element
or simply
for (i <- xs.indices) ...
I would do something like this:
aList.indices foreach { i =>
val (aListItem, bListItem) = (aList(i), bList(i))
// do something with items
}
for {
i <- 0 until Math.min(list1.size, list2.size)
} yield list1(i) + list2(i)
Or something like that which checks bounds etc.

Generating ScalaCheck tests with Cucumber JVM - Generic Functions

To avoid X & Y problems, a little background:
I'm trying to set up a web project where I'm going to be duplicating business logic server and client side, client obviously in Javascript and the server in Scala. I plan to write business logic in Cucumber so I can make sure the tests and functionality line up on both sides. Finally, I'd like to have a crack at bringing ScalaCheck and JSCheck into this, generated input data rather than specified.
Basically, the statements would work like this:
Given statements select add generators.
When statements specify functions to act upon those values in sequence.
Then statements take the input data and the final result data and run a property.
The objective is to make this sort of thing composable so you could specify several generators, a set of actions to run on each of them, and then a set of properties that would each get run on the inputs and result.
Done this already in Javascript (technically Coffeescript), and of course with a dynamic language is straightforward to do. Basically what I want to be able to do in my scala step definitions is this, excuse the arbitrary test data:
class CucumberSteps extends ScalaDsl with EN
with ShouldMatchers with QuickCheckCucumberSteps {
Given("""^an list of integer between 0 and 100$""") {
addGenerator(Gen.containerOf[List, Int](Gen.choose(0,100)))
}
Given("""^an list of random string int 500 and 700$""") {
addGenerator(Gen.containerOf[List, Int](Gen.choose(500,700)))
}
When("""^we concatenate the two lists$""") {
addAction {(l1: List[Int], l2: List[Int]) => l1 ::: l2 }
}
Then("""^then the size of the result should equal the sum of the input sizes$""") {
runProperty { (inputs: (List[Int], List[Int]), result: (List[Int])) =>
inputs._1.size + inputs._2.size == result._1.size
}
}
}
So the key thing I want to do is create a trait QuickCheckCucumberSteps that will be the API, implementing addGenerator, addAction and runProperty.
Here's what I've roughed out so far, and where I get stuck:
trait QuickCheckCucumberSteps extends ShouldMatchers {
private var generators = ArrayBuffer[Gen[Any]]()
private var actions = ArrayBuffer[""AnyFunction""]()
def addGenerator(newGen: Gen[Any]): Unit =
generators += newGen
def addAction(newFun: => ""AnyFunction""): Unit =
actions += newFun
def buildPartialProp = {
val li = generators
generators.length match {
case 1 => forAll(li(0))_
case 2 => forAll(li(0), li(1))_
case 3 => forAll(li(0), li(1), li(2))_
case 4 => forAll(li(0), li(1), li(2), li(3))_
case _ => forAll(li(0), li(1), li(2), li(3), li(4))_
}
}
def runProperty(propertyFunc: => Any): Prop = {
val partial = buildPartialProp
val property = partial {
??? // Need a function that takes x number of generator inputs,
// applies each action in sequence
// and then applies the `propertyFunc` to the
// inputs and results.
}
val result = Test.check(new Test.Parameters.Default {},
property)
result.status match {
case Passed => println("passed all tests")
case Failed(a, l) => fail(format(pretty(result), "", "", 75))
case _ => println("other cases")
}
}
}
My key issue is this, I want to have the commented block become a function that takes all the added actions, apply them in order and then run and return the result of the property function. Is this possible to express with Scala's type system, and if so, how do I get started? Happy to do reading and earn this one, but I need at least a way forward as I don't know how to express it at this point. Happy to drop in my Javascript code if what I'm trying to make here isn't clear.
If I were you, I wouldn't put ScalaCheck generator code within your Cucumber Given/When/Then statements :). The ScalaCheck api calls are part of the "test rig" - so not under test. Try this (not compiled/tested):
class CucumberSteps extends ScalaDsl with EN with ShouldMatchers {
forAll(Gen.containerOf[List, Int](Gen.choose(0,100)),
Gen.containerOf[List, Int](Gen.choose(500,700)))
((l1: List[Int], l2: List[Int]) => {
var result: Int = 0
Given(s"""^a list of integer between 0 and 100: $l1 $""") { }
Given(s"""^a list of integer between 0 and 100: $l2 $""") { }
When("""^we concatenate the two lists$""") { result = l1 ::: l2 }
Then("""^the size of the result should equal the sum of the input sizes$""") {
l1.size + l2.size == result.size }
})
}

How to yield a single element from for loop in scala?

Much like this question:
Functional code for looping with early exit
Say the code is
def findFirst[T](objects: List[T]):T = {
for (obj <- objects) {
if (expensiveFunc(obj) != null) return /*???*/ Some(obj)
}
None
}
How to yield a single element from a for loop like this in scala?
I do not want to use find, as proposed in the original question, i am curious about if and how it could be implemented using the for loop.
* UPDATE *
First, thanks for all the comments, but i guess i was not clear in the question. I am shooting for something like this:
val seven = for {
x <- 1 to 10
if x == 7
} return x
And that does not compile. The two errors are:
- return outside method definition
- method main has return statement; needs result type
I know find() would be better in this case, i am just learning and exploring the language. And in a more complex case with several iterators, i think finding with for can actually be usefull.
Thanks commenters, i'll start a bounty to make up for the bad posing of the question :)
If you want to use a for loop, which uses a nicer syntax than chained invocations of .find, .filter, etc., there is a neat trick. Instead of iterating over strict collections like list, iterate over lazy ones like iterators or streams. If you're starting with a strict collection, make it lazy with, e.g. .toIterator.
Let's see an example.
First let's define a "noisy" int, that will show us when it is invoked
def noisyInt(i : Int) = () => { println("Getting %d!".format(i)); i }
Now let's fill a list with some of these:
val l = List(1, 2, 3, 4).map(noisyInt)
We want to look for the first element which is even.
val r1 = for(e <- l; val v = e() ; if v % 2 == 0) yield v
The above line results in:
Getting 1!
Getting 2!
Getting 3!
Getting 4!
r1: List[Int] = List(2, 4)
...meaning that all elements were accessed. That makes sense, given that the resulting list contains all even numbers. Let's iterate over an iterator this time:
val r2 = (for(e <- l.toIterator; val v = e() ; if v % 2 == 0) yield v)
This results in:
Getting 1!
Getting 2!
r2: Iterator[Int] = non-empty iterator
Notice that the loop was executed only up to the point were it could figure out whether the result was an empty or non-empty iterator.
To get the first result, you can now simply call r2.next.
If you want a result of an Option type, use:
if(r2.hasNext) Some(r2.next) else None
Edit Your second example in this encoding is just:
val seven = (for {
x <- (1 to 10).toIterator
if x == 7
} yield x).next
...of course, you should be sure that there is always at least a solution if you're going to use .next. Alternatively, use headOption, defined for all Traversables, to get an Option[Int].
You can turn your list into a stream, so that any filters that the for-loop contains are only evaluated on-demand. However, yielding from the stream will always return a stream, and what you want is I suppose an option, so, as a final step you can check whether the resulting stream has at least one element, and return its head as a option. The headOption function does exactly that.
def findFirst[T](objects: List[T], expensiveFunc: T => Boolean): Option[T] =
(for (obj <- objects.toStream if expensiveFunc(obj)) yield obj).headOption
Why not do exactly what you sketched above, that is, return from the loop early? If you are interested in what Scala actually does under the hood, run your code with -print. Scala desugares the loop into a foreach and then uses an exception to leave the foreach prematurely.
So what you are trying to do is to break out a loop after your condition is satisfied. Answer here might be what you are looking for. How do I break out of a loop in Scala?.
Overall, for comprehension in Scala is translated into map, flatmap and filter operations. So it will not be possible to break out of these functions unless you throw an exception.
If you are wondering, this is how find is implemented in LineerSeqOptimized.scala; which List inherits
override /*IterableLike*/
def find(p: A => Boolean): Option[A] = {
var these = this
while (!these.isEmpty) {
if (p(these.head)) return Some(these.head)
these = these.tail
}
None
}
This is a horrible hack. But it would get you the result you wished for.
Idiomatically you'd use a Stream or View and just compute the parts you need.
def findFirst[T](objects: List[T]): T = {
def expensiveFunc(o : T) = // unclear what should be returned here
case class MissusedException(val data: T) extends Exception
try {
(for (obj <- objects) {
if (expensiveFunc(obj) != null) throw new MissusedException(obj)
})
objects.head // T must be returned from loop, dummy
} catch {
case MissusedException(obj) => obj
}
}
Why not something like
object Main {
def main(args: Array[String]): Unit = {
val seven = (for (
x <- 1 to 10
if x == 7
) yield x).headOption
}
}
Variable seven will be an Option holding Some(value) if value satisfies condition
I hope to help you.
I think ... no 'return' impl.
object TakeWhileLoop extends App {
println("first non-null: " + func(Seq(null, null, "x", "y", "z")))
def func[T](seq: Seq[T]): T = if (seq.isEmpty) null.asInstanceOf[T] else
seq(seq.takeWhile(_ == null).size)
}
object OptionLoop extends App {
println("first non-null: " + func(Seq(null, null, "x", "y", "z")))
def func[T](seq: Seq[T], index: Int = 0): T = if (seq.isEmpty) null.asInstanceOf[T] else
Option(seq(index)) getOrElse func(seq, index + 1)
}
object WhileLoop extends App {
println("first non-null: " + func(Seq(null, null, "x", "y", "z")))
def func[T](seq: Seq[T]): T = if (seq.isEmpty) null.asInstanceOf[T] else {
var i = 0
def obj = seq(i)
while (obj == null)
i += 1
obj
}
}
objects iterator filter { obj => (expensiveFunc(obj) != null } next
The trick is to get some lazy evaluated view on the colelction, either an iterator or a Stream, or objects.view. The filter will only execute as far as needed.

Functional Alternative to Game Loop

I'm just starting out with the Scala and am trying a little toy program - in this case a text based TicTacToe. I wrote a working version based on what I know about scala, but noticed it was mostly imperative and my classes were mutable.
I'm going through and trying to implement some functional idioms and have managed to at least make the classes representing the game state immutable. However, I'm left with a class responsible for performing the game loop relying on mutable state and imperative loop as follows:
var board: TicTacToeBoard = new TicTacToeBoard
def start() {
var gameState: GameState = new XMovesNext
outputState(gameState)
while (!gameState.isGameFinished) {
val position: Int = getSelectionFromUser
board = board.updated(position, gameState.nextTurn)
gameState = getGameState(board)
outputState(gameState)
}
}
What would be a more idiomatic way to program what I'm doing imperatively in this loop?
Full source code is here https://github.com/whaley/TicTacToe-in-Scala/tree/master/src/main/scala/com/jasonwhaley/tictactoe
imho for Scala, the imperative loop is just fine. You can always write a recursive function to behave like a loop. I also threw in some pattern matching.
def start() {
def loop(board: TicTacToeBoard) = board.state match {
case Finished => Unit
case Unfinished(gameState) => {
gameState.output()
val position: Int = getSelectionFromUser()
loop(board.updated(position))
}
}
loop(new TicTacToeBoard)
}
Suppose we had a function whileSome : (a -> Option[a]) a -> (), which runs the input function until its result is None. That would strip away a little boilerplate.
def start() {
def step(board: TicTacToeBoard) = {
board.gameState.output()
val position: Int = getSelectionFromUser()
board.updated(position) // returns either Some(nextBoard) or None
}
whileSome(step, new TicTacToeBoard)
}
whileSome should be trivial to write; it is simply an abstraction of the former pattern. I'm not sure if it's in any common Scala libs, but in Haskell you could grab whileJust_ from monad-loops.
You could implement it as a recursive method. Here's an unrelated example:
object Guesser extends App {
val MIN = 1
val MAX = 100
readLine("Think of a number between 1 and 100. Press enter when ready")
def guess(max: Int, min: Int) {
val cur = (max + min) / 2
readLine("Is the number "+cur+"? (y/n) ") match {
case "y" => println("I thought so")
case "n" => {
def smallerGreater() {
readLine("Is it smaller or greater? (s/g) ") match {
case "s" => guess(cur - 1, min)
case "g" => guess(max, cur + 1)
case _ => smallerGreater()
}
}
smallerGreater()
}
case _ => {
println("Huh?")
guess(max, min)
}
}
}
guess(MAX, MIN)
}
How about something like:
Stream.continually(processMove).takeWhile(!_.isGameFinished)
where processMove is a function that gets selection from user, updates board and returns new state.
I'd go with the recursive version, but here's a proper implementation of the Stream version:
var board: TicTacToeBoard = new TicTacToeBoard
def start() {
def initialBoard: TicTacToeBoard = new TicTacToeBoard
def initialGameState: GameState = new XMovesNext
def gameIterator = Stream.iterate(initialBoard -> initialGameState) _
def game: Stream[GameState] = {
val (moves, end) = gameIterator {
case (board, gameState) =>
val position: Int = getSelectionFromUser
val updatedBoard = board.updated(position, gameState.nextTurn)
(updatedBoard, getGameState(board))
}.span { case (_, gameState) => !gameState.isGameFinished }
(moves ::: end.take(1)) map { case (_, gameState) => gameState }
}
game foreach outputState
}
This looks weirder than it should. Ideally, I'd use takeWhile, and then map it afterwards, but it won't work as the last case would be left out!
If the moves of the game could be discarded, then dropWhile followed by head would work. If I had the side effect (outputState) instead the Stream, I could go that route, but having side-effect inside a Stream is way worse than a var with a while loop.
So, instead, I use span which gives me both takeWhile and dropWhile but forces me to save the intermediate results -- which can be real bad if memory is a concern, as the whole game will be kept in memory because moves points to the head of the Stream. So I had to encapsulate all that inside another method, game. That way, when I foreach through the results of game, there won't be anything pointing to the Stream's head.
Another alternative would be to get rid of the other side effect you have: getSelectionFromUser. You can get rid of that with an Iteratee, and then you can save the last move and reapply it.
OR... you could write yourself a takeTo method and use that.