Say I have some function like this:
def doSomeCode(code: => Unit): Unit = {
println("Doing some code!")
code
}
It takes in a function, prints out "Doing some code!" and then calls the passed function. If for example we called it like:
doSomeCode {
println("Some code done!")
}
It would print out "Doing some code!", followed by "Some code done!".
But I would like to disallow the use of outside variables inside that code block, for example:
def otherFunction(): Unit = {
val number = 10
doSomeCode{
println("The number is " + number)
}
}
This will print out "Doing some code!", followed by "The number is 10". But I would like it to instead throw an error because I do not want number to be in the scope of doSomeCode. Is this possible to achieve in Scala?
To be clear I am not asking if this is a good idea, I just want to know if it is possible.
Edit:
The reason I want this is because I am trying to make a syntax that is perfectly functional, I want a block with no side effects. Ideally the syntax would look like:
val a = 1
val b = 2
val c = 3
val d = 4
val sum = use(a, c, d){
val total = a + c + d
total
}
This way I as a programmer know that the only variables used are a, c, and d and that sum is the only output. Trying to use anything else, eg b, would result in an error. Currently it is not possible to know at a glance what variables a block is using. I can achieve this by just making and using a function like this:
def example(): Unit = {
val a = 1
val b = 2
val c = 3
val d = 4
val sum = sum(a, c, d)
}
def sum(a: Int, b: Int, c: Int): Int = {
val total = a + b + c
total
}
This behaves exactly like how I want it to, but I would like it to be inline with the other code, not outside as an external function.
scala> def mkClosure(i: Int) = { s: String => s"$i - $s" }
mkClosure: (i: Int)String => String
scala> mkClosure(5)
res0: String => String = <function1>
Since whether the function depends on values which aren't parameters isn't encoded in the type system, there's no compiler-enforceable difference in Scala between such a function and a pure one. It's unlikely to be possible with macros: a compiler plugin is probably your best bet, especially if you want to allow certain values (e.g. println) to be used inside a block.
Learning Scala and functional programming in general. In the following tail-recursive factorial implementation:
def factorialTailRec(n: Int) : Int = {
#tailrec
def factorialRec(n: Int, f: => Int): Int = {
if (n == 0) f else factorialRec(n - 1, n * f)
}
factorialRec(n, 1)
}
I wonder whether there is any benefit to having the second parameter called by value vs called by name (as I have done). In the first case, every stack frame is burdened with a product. In the second case, if my understanding is correct, the entire chain of products will be carried over to the case if ( n== 0) at the nth stack frame, so we will still have to perform the same number of multiplications. Unfortunately, this is not a product of form a^n, which can be calculated in log_2n steps through repeated squaring, but a product of terms that differ by 1 every time. So I can't see any possible way of optimizing the final product: it will still require the multiplication of O(n) terms.
Is this correct? Is call by value equivalent to call by name here, in terms of complexity?
Let me just expand a little bit what you've already been told in comments.
That's how by-name parameters are desugared by the compiler:
#tailrec
def factorialTailRec(n: Int, f: => Int): Int = {
if (n == 0) {
val fEvaluated = f
fEvaluated
} else {
val fEvaluated = f // <-- here we are going deeper into stack.
factorialTailRec(n - 1, n * fEvaluated)
}
}
Through experimentation I found out that with the call by name formalism, the method becomes... non-tail recursive! I made this example code to compare factorial tail-recursively, and factorial non-tail-recursively:
package example
import scala.annotation.tailrec
object Factorial extends App {
val ITERS = 100000
def factorialTailRec(n: Int) : Int = {
#tailrec
def factorialTailRec(n: Int, f: => Int): Int = {
if (n == 0) f else factorialTailRec(n - 1, n * f)
}
factorialTailRec(n, 1)
}
for(i <-1 to ITERS) println("factorialTailRec(" + i + ") = " + factorialTailRec(i))
def factorial(n:Int) : Int = {
if(n == 0) 1 else n * factorial(n-1)
}
for(i <-1 to ITERS) println("factorial(" + i + ") = " + factorial(i))
}
Observe that the inner tailRec function calls the second argument by name. for which the #tailRec annotation still does NOT throw a compile-time error!
I've been playing around with different values for the ITERS variable, and for a value of 100,000, I receive a... StackOverflowError!
(The result of zero is there because of overflow of Int.)
So I went ahead and changed the signature of factorialTailRec/2, to:
def factorialTailRec(n: Int, f: Int): Int
i.e call by value for the argument f. This time, the portion of main that runs factorialTailRec finishes absolutely fine, whereas, of course, factorial/1 crashes at the exact same integer.
Very, very interesting. It seems as if call by name in this situation maintains the stack frames because of the need of computation of the products themselves all the way back to the call chain.
As I understand it, in Scala, a function may be called either
by-value or
by-name
For example, given the following declarations, do we know how the function will be called?
Declaration:
def f (x:Int, y:Int) = x;
Call
f (1,2)
f (23+55,5)
f (12+3, 44*11)
What are the rules please?
The example you have given only uses call-by-value, so I will give a new, simpler, example that shows the difference.
First, let's assume we have a function with a side-effect. This function prints something out and then returns an Int.
def something() = {
println("calling something")
1 // return value
}
Now we are going to define two function that accept Int arguments that are exactly the same except that one takes the argument in a call-by-value style (x: Int) and the other in a call-by-name style (x: => Int).
def callByValue(x: Int) = {
println("x1=" + x)
println("x2=" + x)
}
def callByName(x: => Int) = {
println("x1=" + x)
println("x2=" + x)
}
Now what happens when we call them with our side-effecting function?
scala> callByValue(something())
calling something
x1=1
x2=1
scala> callByName(something())
calling something
x1=1
calling something
x2=1
So you can see that in the call-by-value version, the side-effect of the passed-in function call (something()) only happened once. However, in the call-by-name version, the side-effect happened twice.
This is because call-by-value functions compute the passed-in expression's value before calling the function, thus the same value is accessed every time. Instead, call-by-name functions recompute the passed-in expression's value every time it is accessed.
Here is an example from Martin Odersky:
def test (x:Int, y: Int)= x*x
We want to examine the evaluation strategy and determine which one is faster (less steps) in these conditions:
test (2,3)
call by value: test(2,3) -> 2*2 -> 4
call by name: test(2,3) -> 2*2 -> 4
Here the result is reached with the same number of steps.
test (3+4,8)
call by value: test (7,8) -> 7*7 -> 49
call by name: (3+4) (3+4) -> 7(3+4)-> 7*7 ->49
Here call by value is faster.
test (7,2*4)
call by value: test(7,8) -> 7*7 -> 49
call by name: 7 * 7 -> 49
Here call by name is faster
test (3+4, 2*4)
call by value: test(7,2*4) -> test(7, 8) -> 7*7 -> 49
call by name: (3+4)(3+4) -> 7(3+4) -> 7*7 -> 49
The result is reached within the same steps.
In the case of your example all the parameters will be evaluated before it's called in the function , as you're only defining them by value.
If you want to define your parameters by name you should pass a code block:
def f(x: => Int, y:Int) = x
This way the parameter x will not be evaluated until it's called in the function.
This little post here explains this nicely too.
To iteratate #Ben's point in the above comments, I think it's best to think of "call-by-name" as just syntactic sugar. The parser just wraps the expressions in anonymous functions, so that they can be called at a later point, when they are used.
In effect, instead of defining
def callByName(x: => Int) = {
println("x1=" + x)
println("x2=" + x)
}
and running:
scala> callByName(something())
calling something
x1=1
calling something
x2=1
You could also write:
def callAlsoByName(x: () => Int) = {
println("x1=" + x())
println("x2=" + x())
}
And run it as follows for the same effect:
callAlsoByName(() => {something()})
calling something
x1=1
calling something
x2=1
I will try to explain by a simple use case rather than by just providing an example
Imagine you want to build a "nagger app" that will Nag you every time since time last you got nagged.
Examine the following implementations:
object main {
def main(args: Array[String]) {
def onTime(time: Long) {
while(time != time) println("Time to Nag!")
println("no nags for you!")
}
def onRealtime(time: => Long) {
while(time != time) println("Realtime Nagging executed!")
}
onTime(System.nanoTime())
onRealtime(System.nanoTime())
}
}
In the above implementation the nagger will work only when passing by name
the reason is that, when passing by value it will re-used and therefore the value will not be re-evaluated while when passing by name the value will be re-evaluated every time the variables is accessed
Typically, parameters to functions are by-value parameters; that is, the value of the parameter is determined before it is passed to the function. But what if we need to write a function that accepts as a parameter an expression that we don't want evaluated until it's called within our function? For this circumstance, Scala offers call-by-name parameters.
A call-by-name mechanism passes a code block to the callee and each time the callee accesses the parameter, the code block is executed and the value is calculated.
object Test {
def main(args: Array[String]) {
delayed(time());
}
def time() = {
println("Getting time in nano seconds")
System.nanoTime
}
def delayed( t: => Long ) = {
println("In delayed method")
println("Param: " + t)
t
}
}
1. C:/>scalac Test.scala
2. scala Test
3. In delayed method
4. Getting time in nano seconds
5. Param: 81303808765843
6. Getting time in nano seconds
As i assume, the call-by-value function as discuss above pass just the values to the function. According to Martin Odersky It is a Evaluation strategy follow by a Scala that play the important role in function evaluation. But, Make it simple to call-by-name. its like a pass the function as a argument to the method also know as Higher-Order-Functions. When the method access the value of passed parameter, it call the implementation of passed functions. as Below:
According to #dhg example, create the method first as:
def something() = {
println("calling something")
1 // return value
}
This function contain one println statement and return an integer value. Create the function, who have arguments as a call-by-name:
def callByName(x: => Int) = {
println("x1=" + x)
println("x2=" + x)
}
This function parameter, is define an anonymous function who have return one integer value. In this x contain an definition of function who have 0 passed arguments but return int value and our something function contain same signature. When we call the function, we pass the function as a argument to callByName. But in the case of call-by-value its only pass the integer value to the function. We call the function as below:
scala> callByName(something())
calling something
x1=1
calling something
x2=1
In this our something method called twice, because when we access the value of x in callByName method, its call to the defintion of something method.
Call by value is general use case as explained by many answers here..
Call-by-name passes a code block to the caller and each time the
caller accesses the parameter, the code block is executed and the
value is calculated.
I will try to demonstrate call by name more simple way with use cases below
Example 1:
Simple example/use case of call by name is below function, which takes function as parameter and gives the time elapsed.
/**
* Executes some code block and prints to stdout the
time taken to execute the block
for interactive testing and debugging.
*/
def time[T](f: => T): T = {
val start = System.nanoTime()
val ret = f
val end = System.nanoTime()
println(s"Time taken: ${(end - start) / 1000 / 1000} ms")
ret
}
Example 2:
apache spark (with scala) uses logging using call by name way see Logging trait
in which its lazily evaluates whether log.isInfoEnabled or not from the below method.
protected def logInfo(msg: => String) {
if (log.isInfoEnabled) log.info(msg)
}
In a Call by Value, the value of the expression is pre-computed at the time of the function call and that particular value is passed as the parameter to the corresponding function. The same value will be used all throughout the function.
Whereas in a Call by Name, the expression itself is passed as a parameter to the function and it is only computed inside the function, whenever that particular parameter is called.
The difference between Call by Name and Call by Value in Scala could be better understood with the below example:
Code Snippet
object CallbyExample extends App {
// function definition of call by value
def CallbyValue(x: Long): Unit = {
println("The current system time via CBV: " + x);
println("The current system time via CBV " + x);
}
// function definition of call by name
def CallbyName(x: => Long): Unit = {
println("The current system time via CBN: " + x);
println("The current system time via CBN: " + x);
}
// function call
CallbyValue(System.nanoTime());
println("\n")
CallbyName(System.nanoTime());
}
Output
The current system time via CBV: 1153969332591521
The current system time via CBV 1153969332591521
The current system time via CBN: 1153969336749571
The current system time via CBN: 1153969336856589
In the above code snippet, for the function call CallbyValue(System.nanoTime()), the system nano time is pre-calculated and that pre-calculated value has been passed a parameter to the function call.
But in the CallbyName(System.nanoTime()) function call, the expression "System.nanoTime())" itself is passed as a parameter to the function call and the value of that expression is calculated when that parameter is used inside the function.
Notice the function definition of the CallbyName function, where there is a => symbol separating the parameter x and its datatype. That particular symbol there indicates the function is of call by name type.
In other words, the call by value function arguments are evaluated once before entering the function, but the call by name function arguments are evaluated inside the function only when they are needed.
Hope this helps!
Here is a quick example I coded to help a colleague of mine who is currently taking the Scala course. What I thought was interesting is that Martin didn't use the && question answer presented earlier in the lecture as an example. In any event I hope this helps.
val start = Instant.now().toEpochMilli
val calc = (x: Boolean) => {
Thread.sleep(3000)
x
}
def callByValue(x: Boolean, y: Boolean): Boolean = {
if (!x) x else y
}
def callByName(x: Boolean, y: => Boolean): Boolean = {
if (!x) x else y
}
new Thread(() => {
println("========================")
println("Call by Value " + callByValue(false, calc(true)))
println("Time " + (Instant.now().toEpochMilli - start) + "ms")
println("========================")
}).start()
new Thread(() => {
println("========================")
println("Call by Name " + callByName(false, calc(true)))
println("Time " + (Instant.now().toEpochMilli - start) + "ms")
println("========================")
}).start()
Thread.sleep(5000)
The output of the code will be the following:
========================
Call by Name false
Time 64ms
========================
Call by Value false
Time 3068ms
========================
Parameters are usually pass by value, which means that they'll be evaluated before being substituted in the function body.
You can force a parameter to be call by name by using the double arrow when defining the function.
// first parameter will be call by value, second call by name, using `=>`
def returnOne(x: Int, y: => Int): Int = 1
// to demonstrate the benefits of call by name, create an infinite recursion
def loop(x: Int): Int = loop(x)
// will return one, since `loop(2)` is passed by name so no evaluated
returnOne(2, loop(2))
// will not terminate, since loop(2) will evaluate.
returnOne(loop(2), 2) // -> returnOne(loop(2), 2) -> returnOne(loop(2), 2) -> ...
There are already lots of fantastic answers for this question in Internet. I will write a compilation of several explanations and examples I have gathered about the topic, just in case someone may find it helpful
INTRODUCTION
call-by-value (CBV)
Typically, parameters to functions are call-by-value parameters; that is, the parameters are evaluated left to right to determine their value before the function itself is evaluated
def first(a: Int, b: Int): Int = a
first(3 + 4, 5 + 6) // will be reduced to first(7, 5 + 6), then first(7, 11), and then 7
call-by-name (CBN)
But what if we need to write a function that accepts as a parameter an expression that we don't to evaluate until it's called within our function? For this circumstance, Scala offers call-by-name parameters. Meaning the parameter is passed into the function as it is, and its valuation takes place after substitution
def first1(a: Int, b: => Int): Int = a
first1(3 + 4, 5 + 6) // will be reduced to (3 + 4) and then to 7
A call-by-name mechanism passes a code block to the call and each time the call accesses the parameter, the code block is executed and the value is calculated. In the following example, delayed prints a message demonstrating that the method has been entered. Next, delayed prints a message with its value. Finally, delayed returns ‘t’:
object Demo {
def main(args: Array[String]) {
delayed(time());
}
def time() = {
println("Getting time in nano seconds")
System.nanoTime
}
def delayed( t: => Long ) = {
println("In delayed method")
println("Param: " + t)
}
}
In delayed method
Getting time in nano seconds
Param: 2027245119786400
PROS AND CONS FOR EACH CASE
CBN:
+Terminates more often * check below above termination *
+ Has the advantage that a function argument is not evaluated if the corresponding parameter is unused in the evaluation of the function body
-It is slower, it creates more classes (meaning the program takes longer to load) and it consumes more memory.
CBV:
+ It is often exponentially more efficient than CBN, because it avoids this repeated recomputation of arguments expressions that call by name entails. It evaluates every function argument only once
+ It plays much nicer with imperative effects and side effects, because you tend to know much better when expressions will be evaluated.
-It may lead to a loop during its parameters evaluation * check below above termination *
What if termination is not guaranteed?
-If CBV evaluation of an expression e terminates, then CBN evaluation of e terminates too
-The other direction is not true
Non-termination example
def first(x:Int, y:Int)=x
Consider the expression first(1,loop)
CBN: first(1,loop) → 1
CBV: first(1,loop) → reduce arguments of this expression. Since one is a loop, it reduce arguments infinivly. It doesn’t terminate
DIFFERENCES IN EACH CASE BEHAVIOUR
Let's define a method test that will be
Def test(x:Int, y:Int) = x * x //for call-by-value
Def test(x: => Int, y: => Int) = x * x //for call-by-name
Case1 test(2,3)
test(2,3) → 2*2 → 4
Since we start with already evaluated arguments it will be the same amount of steps for call-by-value and call-by-name
Case2 test(3+4,8)
call-by-value: test(3+4,8) → test(7,8) → 7 * 7 → 49
call-by-name: (3+4)*(3+4) → 7 * (3+4) → 7 * 7 → 49
In this case call-by-value performs less steps
Case3 test(7, 2*4)
call-by-value: test(7, 2*4) → test(7,8) → 7 * 7 → 49
call-by-name: (7)*(7) → 49
We avoid the unnecessary computation of the second argument
Case4 test(3+4, 2*4)
call-by-value: test(7, 2*4) → test(7,8) → 7 * 7 → 49
call-by-name: (3+4)*(3+4) → 7*(3+4) → 7*7 → 49
Different approach
First, let's assume we have a function with a side-effect. This function prints something out and then returns an Int.
def something() = {
println("calling something")
1 // return value
}
Now we are going to define two function that accept Int arguments that are exactly the same except that one takes the argument in a call-by-value style (x: Int) and the other in a call-by-name style (x: => Int).
def callByValue(x: Int) = {
println("x1=" + x)
println("x2=" + x)
}
def callByName(x: => Int) = {
println("x1=" + x)
println("x2=" + x)
}
Now what happens when we call them with our side-effecting function?
scala> callByValue(something())
calling something
x1=1
x2=1
scala> callByName(something())
calling something
x1=1
calling something
x2=1
So you can see that in the call-by-value version, the side-effect of the passed-in function call (something()) only happened once. However, in the call-by-name version, the side-effect happened twice.
This is because call-by-value functions compute the passed-in expression's value before calling the function, thus the same value is accessed every time. However, call-by-name functions recompute the passed-in expression's value every time it is accessed.
EXAMPLES WHERE IT IS BETTER TO USE CALL-BY-NAME
From: https://stackoverflow.com/a/19036068/1773841
Simple performance example: logging.
Let's imagine an interface like this:
trait Logger {
def info(msg: => String)
def warn(msg: => String)
def error(msg: => String)
}
And then used like this:
logger.info("Time spent on X: " + computeTimeSpent)
If the info method doesn't do anything (because, say, the logging level was configured for higher than that), then computeTimeSpent never gets called, saving time. This happens a lot with loggers, where one often sees string manipulation which can be expensive relative to the tasks being logged.
Correctness example: logic operators.
You have probably seen code like this:
if (ref != null && ref.isSomething)
Imagine you would declare && method like this:
trait Boolean {
def &&(other: Boolean): Boolean
}
then, whenever ref is null, you'll get an error because isSomething will be called on a nullreference before being passed to &&. For this reason, the actual declaration is:
trait Boolean {
def &&(other: => Boolean): Boolean =
if (this) this else other
}
Going through an example should help you better understand the difference.
Let's definie a simple function that returns the current time:
def getTime = System.currentTimeMillis
Now we'll define a function, by name, that prints two times delayed by a second:
def getTimeByName(f: => Long) = { println(f); Thread.sleep(1000); println(f)}
And a one by value:
def getTimeByValue(f: Long) = { println(f); Thread.sleep(1000); println(f)}
Now let's call each:
getTimeByName(getTime)
// prints:
// 1514451008323
// 1514451009325
getTimeByValue(getTime)
// prints:
// 1514451024846
// 1514451024846
The result should explain the difference. The snippet is available here.
CallByName is invoked when used and callByValue is invoked whenever the statement is encountered.
For example:-
I have a infinite loop i.e. if you execute this function we will never get scala prompt.
scala> def loop(x:Int) :Int = loop(x-1)
loop: (x: Int)Int
a callByName function takes above loop method as an argument and it is never used inside its body.
scala> def callByName(x:Int,y: => Int)=x
callByName: (x: Int, y: => Int)Int
On execution of callByName method we don't find any problem ( we get scala prompt back ) as we are no where using the loop function inside callByName function.
scala> callByName(1,loop(10))
res1: Int = 1
scala>
a callByValue function takes above loop method as a parameter as a result inside function or expression is evaluated before executing outer function there by loop function executed recursively and we never get scala prompt back.
scala> def callByValue(x:Int,y:Int) = x
callByValue: (x: Int, y: Int)Int
scala> callByValue(1,loop(1))
See this:
object NameVsVal extends App {
def mul(x: Int, y: => Int) : Int = {
println("mul")
x * y
}
def add(x: Int, y: Int): Int = {
println("add")
x + y
}
println(mul(3, add(2, 1)))
}
y: => Int is call by name. What is passed as call by name is add(2, 1). This will be evaluated lazily. So output on console will be "mul" followed by "add", although add seems to be called first. Call by name acts as kind of passing a function pointer.
Now change from y: => Int to y: Int. Console will show "add" followed by "mul"! Usual way of evaluation.
I don't think all the answers here do the correct justification:
In call by value the arguments are computed just once:
def f(x : Int, y :Int) = x
// following the substitution model
f(12 + 3, 4 * 11)
f(15, 4194304)
15
you can see above that all the arguments are evaluated whether needed are not, normally call-by-value can be fast but not always like in this case.
If the evaluation strategy was call-by-name then the decomposition would have been:
f(12 + 3, 4 * 11)
12 + 3
15
as you can see above we never needed to evaluate 4 * 11 and hence saved a bit of computation which may be beneficial sometimes.
Scala variable evaluation explained here in better https://sudarshankasar.medium.com/evaluation-rules-in-scala-1ed988776ae8
def main(args: Array[String]): Unit = {
//valVarDeclaration 2
println("****starting the app***") // ****starting the app***
val defVarDeclarationCall1 = defVarDeclaration // defVarDeclaration 1
val defVarDeclarationCall2 = defVarDeclaration // defVarDeclaration 1
val valVarDeclarationCall1 = valVarDeclaration //
val valVarDeclarationCall2 = valVarDeclaration //
val lazyValVarDeclarationCall1 = lazyValVarDeclaration // lazyValVarDeclaration 3
val lazyValVarDeclarationCall2 = lazyValVarDeclaration //
callByValue({
println("passing the value "+ 10)
10
}) // passing the value 10
// call by value example
// 10
callByName({
println("passing the value "+ 20)
20
}) // call by name example
// passing the value 20
// 20
}
def defVarDeclaration = {
println("defVarDeclaration " + 1)
1
}
val valVarDeclaration = {
println("valVarDeclaration " + 2)
2
}
lazy val lazyValVarDeclaration = {
println("lazyValVarDeclaration " + 3)
3
}
def callByValue(x: Int): Unit = {
println("call by value example ")
println(x)
}
def callByName(x: => Int): Unit = {
println("call by name example ")
println(x)
}
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.