Is there a reason why assignments in scala evaluate to Unit? [duplicate] - scala

What is the motivation for Scala assignment evaluating to Unit rather than the value assigned?
A common pattern in I/O programming is to do things like this:
while ((bytesRead = in.read(buffer)) != -1) { ...
But this is not possible in Scala because...
bytesRead = in.read(buffer)
.. returns Unit, not the new value of bytesRead.
Seems like an interesting thing to leave out of a functional language.
I am wondering why it was done so?

I advocated for having assignments return the value assigned rather than unit. Martin and I went back and forth on it, but his argument was that putting a value on the stack just to pop it off 95% of the time was a waste of byte-codes and have a negative impact on performance.

I'm not privy to inside information on the actual reasons, but my suspicion is very simple. Scala makes side-effectful loops awkward to use so that programmers will naturally prefer for-comprehensions.
It does this in many ways. For instance, you don't have a for loop where you declare and mutate a variable. You can't (easily) mutate state on a while loop at the same time you test the condition, which means you often have to repeat the mutation just before it, and at the end of it. Variables declared inside a while block are not visible from the while test condition, which makes do { ... } while (...) much less useful. And so on.
Workaround:
while ({bytesRead = in.read(buffer); bytesRead != -1}) { ...
For whatever it is worth.
As an alternate explanation, perhaps Martin Odersky had to face a few very ugly bugs deriving from such usage, and decided to outlaw it from his language.
EDIT
David Pollack has answered with some actual facts, which are clearly endorsed by the fact that Martin Odersky himself commented his answer, giving credence to the performance-related issues argument put forth by Pollack.

This happened as part of Scala having a more "formally correct" type system. Formally-speaking, assignment is a purely side-effecting statement and therefore should return Unit. This does have some nice consequences; for example:
class MyBean {
private var internalState: String = _
def state = internalState
def state_=(state: String) = internalState = state
}
The state_= method returns Unit (as would be expected for a setter) precisely because assignment returns Unit.
I agree that for C-style patterns like copying a stream or similar, this particular design decision can be a bit troublesome. However, it's actually relatively unproblematic in general and really contributes to the overall consistency of the type system.

Perhaps this is due to the command-query separation principle?
CQS tends to be popular at the intersection of OO and functional programming styles, as it creates an obvious distinction between object methods that do or do not have side-effects (i.e., that alter the object). Applying CQS to variable assignments is taking it further than usual, but the same idea applies.
A short illustration of why CQS is useful: Consider a hypothetical hybrid F/OO language with a List class that has methods Sort, Append, First, and Length. In imperative OO style, one might want to write a function like this:
func foo(x):
var list = new List(4, -2, 3, 1)
list.Append(x)
list.Sort()
# list now holds a sorted, five-element list
var smallest = list.First()
return smallest + list.Length()
Whereas in more functional style, one would more likely write something like this:
func bar(x):
var list = new List(4, -2, 3, 1)
var smallest = list.Append(x).Sort().First()
# list still holds an unsorted, four-element list
return smallest + list.Length()
These seem to be trying to do the same thing, but obviously one of the two is incorrect, and without knowing more about the behavior of the methods, we can't tell which one.
Using CQS, however, we would insist that if Append and Sort alter the list, they must return the unit type, thus preventing us from creating bugs by using the second form when we shouldn't. The presence of side effects therefore also becomes implicit in the method signature.

I'd guess this is in order to keep the program / the language free of side effects.
What you describe is the intentional use of a side effect which in the general case is considered a bad thing.

It is not the best style to use an assignment as a boolean expression. You perform two things at the same time which leads often to errors. And the accidential use of "=" instead of "==" is avoided with Scalas restriction.

By the way: I find the initial while-trick stupid, even in Java. Why not somethign like this?
for(int bytesRead = in.read(buffer); bytesRead != -1; bytesRead = in.read(buffer)) {
//do something
}
Granted, the assignment appears twice, but at least bytesRead is in the scope it belongs to, and I'm not playing with funny assignment tricks...

You can have a workaround for this as long as you have a reference type for indirection. In a naïve implementation, you can use the following for arbitrary types.
case class Ref[T](var value: T) {
def := (newval: => T)(pred: T => Boolean): Boolean = {
this.value = newval
pred(this.value)
}
}
Then, under the constraint that you’ll have to use ref.value to access the reference afterwards, you can write your while predicate as
val bytesRead = Ref(0) // maybe there is a way to get rid of this line
while ((bytesRead := in.read(buffer)) (_ != -1)) { // ...
println(bytesRead.value)
}
and you can do the checking against bytesRead in a more implicit manner without having to type it.

Related

When is it okay to use "var" in Scala?

I know that Scala has var (for mutable state) but pure functional programming discourages use of any mutable state and rather focuses on using val for everything.
Coming from an imperative world it's hard to let go of mutable state.
My question is when is it okay to use var in your Scala code ? Can all code really be done using just val. If yes, then why does Scala have vars?
Here are some reasons for vars in Scala:
Scala is a multi-paradigm language, it encourages functional programming, but it leaves the choice to the programmer.
Comptibility: Many Java APIs expose mutable variables.
Performance: Sometimes using a var gives you the best possible performance.
When people say that everything can be done without vars, that is correct in the sense that Scala would still be turing complete without vars. However, it doesn't change anything about the validity of the previous points.
Even from a functional programming point of view, you can use vars (or mutable objects) locally, if they don't leave the scope where they are defined.
For instance, consider this (contrived) function, which returns the size of a list:
def dumbSize( lst: List[Int] ): Int = {
var i = 0
var rest = lst
while( rest != Nil ) {
i += 1
rest = rest.tail
}
i
}
Although this (ugly) function uses vars, it is still pure. There are no side effects and it will always return the same result for a given argument value.
Another example of "mutable-state-encapsulation" is the actor model, where actor state is often mutable.

Why does assignment return Unit? (Why aren't assignments chainable?) [duplicate]

What is the motivation for Scala assignment evaluating to Unit rather than the value assigned?
A common pattern in I/O programming is to do things like this:
while ((bytesRead = in.read(buffer)) != -1) { ...
But this is not possible in Scala because...
bytesRead = in.read(buffer)
.. returns Unit, not the new value of bytesRead.
Seems like an interesting thing to leave out of a functional language.
I am wondering why it was done so?
I advocated for having assignments return the value assigned rather than unit. Martin and I went back and forth on it, but his argument was that putting a value on the stack just to pop it off 95% of the time was a waste of byte-codes and have a negative impact on performance.
I'm not privy to inside information on the actual reasons, but my suspicion is very simple. Scala makes side-effectful loops awkward to use so that programmers will naturally prefer for-comprehensions.
It does this in many ways. For instance, you don't have a for loop where you declare and mutate a variable. You can't (easily) mutate state on a while loop at the same time you test the condition, which means you often have to repeat the mutation just before it, and at the end of it. Variables declared inside a while block are not visible from the while test condition, which makes do { ... } while (...) much less useful. And so on.
Workaround:
while ({bytesRead = in.read(buffer); bytesRead != -1}) { ...
For whatever it is worth.
As an alternate explanation, perhaps Martin Odersky had to face a few very ugly bugs deriving from such usage, and decided to outlaw it from his language.
EDIT
David Pollack has answered with some actual facts, which are clearly endorsed by the fact that Martin Odersky himself commented his answer, giving credence to the performance-related issues argument put forth by Pollack.
This happened as part of Scala having a more "formally correct" type system. Formally-speaking, assignment is a purely side-effecting statement and therefore should return Unit. This does have some nice consequences; for example:
class MyBean {
private var internalState: String = _
def state = internalState
def state_=(state: String) = internalState = state
}
The state_= method returns Unit (as would be expected for a setter) precisely because assignment returns Unit.
I agree that for C-style patterns like copying a stream or similar, this particular design decision can be a bit troublesome. However, it's actually relatively unproblematic in general and really contributes to the overall consistency of the type system.
Perhaps this is due to the command-query separation principle?
CQS tends to be popular at the intersection of OO and functional programming styles, as it creates an obvious distinction between object methods that do or do not have side-effects (i.e., that alter the object). Applying CQS to variable assignments is taking it further than usual, but the same idea applies.
A short illustration of why CQS is useful: Consider a hypothetical hybrid F/OO language with a List class that has methods Sort, Append, First, and Length. In imperative OO style, one might want to write a function like this:
func foo(x):
var list = new List(4, -2, 3, 1)
list.Append(x)
list.Sort()
# list now holds a sorted, five-element list
var smallest = list.First()
return smallest + list.Length()
Whereas in more functional style, one would more likely write something like this:
func bar(x):
var list = new List(4, -2, 3, 1)
var smallest = list.Append(x).Sort().First()
# list still holds an unsorted, four-element list
return smallest + list.Length()
These seem to be trying to do the same thing, but obviously one of the two is incorrect, and without knowing more about the behavior of the methods, we can't tell which one.
Using CQS, however, we would insist that if Append and Sort alter the list, they must return the unit type, thus preventing us from creating bugs by using the second form when we shouldn't. The presence of side effects therefore also becomes implicit in the method signature.
I'd guess this is in order to keep the program / the language free of side effects.
What you describe is the intentional use of a side effect which in the general case is considered a bad thing.
It is not the best style to use an assignment as a boolean expression. You perform two things at the same time which leads often to errors. And the accidential use of "=" instead of "==" is avoided with Scalas restriction.
By the way: I find the initial while-trick stupid, even in Java. Why not somethign like this?
for(int bytesRead = in.read(buffer); bytesRead != -1; bytesRead = in.read(buffer)) {
//do something
}
Granted, the assignment appears twice, but at least bytesRead is in the scope it belongs to, and I'm not playing with funny assignment tricks...
You can have a workaround for this as long as you have a reference type for indirection. In a naïve implementation, you can use the following for arbitrary types.
case class Ref[T](var value: T) {
def := (newval: => T)(pred: T => Boolean): Boolean = {
this.value = newval
pred(this.value)
}
}
Then, under the constraint that you’ll have to use ref.value to access the reference afterwards, you can write your while predicate as
val bytesRead = Ref(0) // maybe there is a way to get rid of this line
while ((bytesRead := in.read(buffer)) (_ != -1)) { // ...
println(bytesRead.value)
}
and you can do the checking against bytesRead in a more implicit manner without having to type it.

why use foldLeft instead of procedural version?

So in reading this question it was pointed out that instead of the procedural code:
def expand(exp: String, replacements: Traversable[(String, String)]): String = {
var result = exp
for ((oldS, newS) <- replacements)
result = result.replace(oldS, newS)
result
}
You could write the following functional code:
def expand(exp: String, replacements: Traversable[(String, String)]): String = {
replacements.foldLeft(exp){
case (result, (oldS, newS)) => result.replace(oldS, newS)
}
}
I would almost certainly write the first version because coders familiar with either procedural or functional styles can easily read and understand it, while only coders familiar with functional style can easily read and understand the second version.
But setting readability aside for the moment, is there something that makes foldLeft a better choice than the procedural version? I might have thought it would be more efficient, but it turns out that the implementation of foldLeft is actually just the procedural code above. So is it just a style choice, or is there a good reason to use one version or the other?
Edit: Just to be clear, I'm not asking about other functions, just foldLeft. I'm perfectly happy with the use of foreach, map, filter, etc. which all map nicely onto for-comprehensions.
Answer: There are really two good answers here (provided by delnan and Dave Griffith) even though I could only accept one:
Use foldLeft because there are additional optimizations, e.g. using a while loop which will be faster than a for loop.
Use fold if it ever gets added to regular collections, because that will make the transition to parallel collections trivial.
It's shorter and clearer - yes, you need to know what a fold is to understand it, but when you're programming in a language that's 50% functional, you should know these basic building blocks anyway. A fold is exactly what the procedural code does (repeatedly applying an operation), but it's given a name and generalized. And while it's only a small wheel you're reinventing, but it's still a wheel reinvention.
And in case the implementation of foldLeft should ever get some special perk - say, extra optimizations - you get that for free, without updating countless methods.
Other than a distaste for mutable variable (even mutable locals), the basic reason to use fold in this case is clarity, with occasional brevity. Most of the wordiness of the fold version is because you have to use an explicit function definition with a destructuring bind. If each element in the list is used precisely once in the fold operation (a common case), this can be simplified to use the short form. Thus the classic definition of the sum of a collection of numbers
collection.foldLeft(0)(_+_)
is much simpler and shorter than any equivalent imperative construct.
One additional meta-reason to use functional collection operations, although not directly applicable in this case, is to enable a move to using parallel collection operations if needed for performance. Fold can't be parallelized, but often fold operations can be turned into commutative-associative reduce operations, and those can be parallelized. With Scala 2.9, changing something from non-parallel functional to parallel functional utilizing multiple processing cores can sometimes be as easy as dropping a .par onto the collection you want to execute parallel operations on.
One word I haven't seen mentioned here yet is declarative:
Declarative programming is often defined as any style of programming that is not imperative. A number of other common definitions exist that attempt to give the term a definition other than simply contrasting it with imperative programming. For example:
A program that describes what computation should be performed and not how to compute it
Any programming language that lacks side effects (or more specifically, is referentially transparent)
A language with a clear correspondence to mathematical logic.
These definitions overlap substantially.
Higher-order functions (HOFs) are a key enabler of declarativity, since we only specify the what (e.g. "using this collection of values, multiply each value by 2, sum the result") and not the how (e.g. initialize an accumulator, iterate with a for loop, extract values from the collection, add to the accumulator...).
Compare the following:
// Sugar-free Scala (Still better than Java<5)
def sumDoubled1(xs: List[Int]) = {
var sum = 0 // Initialized correctly?
for (i <- 0 until xs.size) { // Fenceposts?
sum = sum + (xs(i) * 2) // Correct value being extracted?
// Value extraction and +/* smashed together
}
sum // Correct value returned?
}
// Iteration sugar (similar to Java 5)
def sumDoubled2(xs: List[Int]) = {
var sum = 0
for (x <- xs) // We don't need to worry about fenceposts or
sum = sum + (x * 2) // value extraction anymore; that's progress
sum
}
// Verbose Scala
def sumDoubled3(xs: List[Int]) = xs.map((x: Int) => x*2). // the doubling
reduceLeft((x: Int, y: Int) => x+y) // the addition
// Idiomatic Scala
def sumDoubled4(xs: List[Int]) = xs.map(_*2).reduceLeft(_+_)
// ^ the doubling ^
// \ the addition
Note that our first example, sumDoubled1, is already more declarative than (most would say superior to) C/C++/Java<5 for loops, because we haven't had to micromanage the iteration state and termination logic, but we're still vulnerable to off-by-one errors.
Next, in sumDoubled2, we're basically at the level of Java>=5. There are still a couple things that can go wrong, but we're getting pretty good at reading this code-shape, so errors are quite unlikely. However, don't forget that a pattern that's trivial in a toy example isn't always so readable when scaled up to production code!
With sumDoubled3, desugared for didactic purposes, and sumDoubled4, the idiomatic Scala version, the iteration, initialization, value extraction and choice of return value are all gone.
Sure, it takes time to learn to read the functional versions, but we've drastically foreclosed our options for making mistakes. The "business logic" is clearly marked, and the plumbing is chosen from the same menu that everyone else is reading from.
It is worth pointing out that there is another way of calling foldLeft which takes advantages of:
The ability to use (almost) any Unicode symbol in an identifier
The feature that if a method name ends with a colon :, and is called infix, then the target and parameter are switched
For me this version is much clearer, because I can see that I am folding the expr value into the replacements collection
def expand(expr: String, replacements: Traversable[(String, String)]): String = {
(expr /: replacements) { case (r, (o, n)) => r.replace(o, n) }
}

What is the motivation for Scala assignment evaluating to Unit rather than the value assigned?

What is the motivation for Scala assignment evaluating to Unit rather than the value assigned?
A common pattern in I/O programming is to do things like this:
while ((bytesRead = in.read(buffer)) != -1) { ...
But this is not possible in Scala because...
bytesRead = in.read(buffer)
.. returns Unit, not the new value of bytesRead.
Seems like an interesting thing to leave out of a functional language.
I am wondering why it was done so?
I advocated for having assignments return the value assigned rather than unit. Martin and I went back and forth on it, but his argument was that putting a value on the stack just to pop it off 95% of the time was a waste of byte-codes and have a negative impact on performance.
I'm not privy to inside information on the actual reasons, but my suspicion is very simple. Scala makes side-effectful loops awkward to use so that programmers will naturally prefer for-comprehensions.
It does this in many ways. For instance, you don't have a for loop where you declare and mutate a variable. You can't (easily) mutate state on a while loop at the same time you test the condition, which means you often have to repeat the mutation just before it, and at the end of it. Variables declared inside a while block are not visible from the while test condition, which makes do { ... } while (...) much less useful. And so on.
Workaround:
while ({bytesRead = in.read(buffer); bytesRead != -1}) { ...
For whatever it is worth.
As an alternate explanation, perhaps Martin Odersky had to face a few very ugly bugs deriving from such usage, and decided to outlaw it from his language.
EDIT
David Pollack has answered with some actual facts, which are clearly endorsed by the fact that Martin Odersky himself commented his answer, giving credence to the performance-related issues argument put forth by Pollack.
This happened as part of Scala having a more "formally correct" type system. Formally-speaking, assignment is a purely side-effecting statement and therefore should return Unit. This does have some nice consequences; for example:
class MyBean {
private var internalState: String = _
def state = internalState
def state_=(state: String) = internalState = state
}
The state_= method returns Unit (as would be expected for a setter) precisely because assignment returns Unit.
I agree that for C-style patterns like copying a stream or similar, this particular design decision can be a bit troublesome. However, it's actually relatively unproblematic in general and really contributes to the overall consistency of the type system.
Perhaps this is due to the command-query separation principle?
CQS tends to be popular at the intersection of OO and functional programming styles, as it creates an obvious distinction between object methods that do or do not have side-effects (i.e., that alter the object). Applying CQS to variable assignments is taking it further than usual, but the same idea applies.
A short illustration of why CQS is useful: Consider a hypothetical hybrid F/OO language with a List class that has methods Sort, Append, First, and Length. In imperative OO style, one might want to write a function like this:
func foo(x):
var list = new List(4, -2, 3, 1)
list.Append(x)
list.Sort()
# list now holds a sorted, five-element list
var smallest = list.First()
return smallest + list.Length()
Whereas in more functional style, one would more likely write something like this:
func bar(x):
var list = new List(4, -2, 3, 1)
var smallest = list.Append(x).Sort().First()
# list still holds an unsorted, four-element list
return smallest + list.Length()
These seem to be trying to do the same thing, but obviously one of the two is incorrect, and without knowing more about the behavior of the methods, we can't tell which one.
Using CQS, however, we would insist that if Append and Sort alter the list, they must return the unit type, thus preventing us from creating bugs by using the second form when we shouldn't. The presence of side effects therefore also becomes implicit in the method signature.
I'd guess this is in order to keep the program / the language free of side effects.
What you describe is the intentional use of a side effect which in the general case is considered a bad thing.
It is not the best style to use an assignment as a boolean expression. You perform two things at the same time which leads often to errors. And the accidential use of "=" instead of "==" is avoided with Scalas restriction.
By the way: I find the initial while-trick stupid, even in Java. Why not somethign like this?
for(int bytesRead = in.read(buffer); bytesRead != -1; bytesRead = in.read(buffer)) {
//do something
}
Granted, the assignment appears twice, but at least bytesRead is in the scope it belongs to, and I'm not playing with funny assignment tricks...
You can have a workaround for this as long as you have a reference type for indirection. In a naïve implementation, you can use the following for arbitrary types.
case class Ref[T](var value: T) {
def := (newval: => T)(pred: T => Boolean): Boolean = {
this.value = newval
pred(this.value)
}
}
Then, under the constraint that you’ll have to use ref.value to access the reference afterwards, you can write your while predicate as
val bytesRead = Ref(0) // maybe there is a way to get rid of this line
while ((bytesRead := in.read(buffer)) (_ != -1)) { // ...
println(bytesRead.value)
}
and you can do the checking against bytesRead in a more implicit manner without having to type it.

Why should I avoid using local modifiable variables in Scala?

I'm pretty new to Scala and most of the time before I've used Java. Right now I have warnings all over my code saying that i should "Avoid mutable local variables" and I have a simple question - why?
Suppose I have small problem - determine max int out of four. My first approach was:
def max4(a: Int, b: Int,c: Int, d: Int): Int = {
var subMax1 = a
if (b > a) subMax1 = b
var subMax2 = c
if (d > c) subMax2 = d
if (subMax1 > subMax2) subMax1
else subMax2
}
After taking into account this warning message I found another solution:
def max4(a: Int, b: Int,c: Int, d: Int): Int = {
max(max(a, b), max(c, d))
}
def max(a: Int, b: Int): Int = {
if (a > b) a
else b
}
It looks more pretty, but what is ideology behind this?
Whenever I approach a problem I'm thinking about it like: "Ok, we start from this and then we incrementally change things and get the answer". I understand that the problem is that I try to change some initial state to get an answer and do not understand why changing things at least locally is bad? How to iterate over collection then in functional languages like Scala?
Like an example: Suppose we have a list of ints, how to write a function that returns sublist of ints which are divisible by 6? Can't think of solution without local mutable variable.
In your particular case there is another solution:
def max4(a: Int, b: Int,c: Int, d: Int): Int = {
val submax1 = if (a > b) a else b
val submax2 = if (c > d) c else d
if (submax1 > submax2) submax1 else submax2
}
Isn't it easier to follow? Of course I am a bit biased but I tend to think it is, BUT don't follow that rule blindly. If you see that some code might be written more readably and concisely in mutable style, do it this way -- the great strength of scala is that you don't need to commit to neither immutable nor mutable approaches, you can swing between them (btw same applies to return keyword usage).
Like an example: Suppose we have a list of ints, how to write a
function that returns the sublist of ints which are divisible by 6?
Can't think of solution without local mutable variable.
It is certainly possible to write such function using recursion, but, again, if mutable solution looks and works good, why not?
It's not so related with Scala as with the functional programming methodology in general. The idea is the following: if you have constant variables (final in Java), you can use them without any fear that they are going to change. In the same way, you can parallelize your code without worrying about race conditions or thread-unsafe code.
In your example is not so important, however imagine the following example:
val variable = ...
new Future { function1(variable) }
new Future { function2(variable) }
Using final variables you can be sure that there will not be any problem. Otherwise, you would have to check the main thread and both function1 and function2.
Of course, it's possible to obtain the same result with mutable variables if you do not ever change them. But using inmutable ones you can be sure that this will be the case.
Edit to answer your edit:
Local mutables are not bad, that's the reason you can use them. However, if you try to think approaches without them, you can arrive to solutions as the one you posted, which is cleaner and can be parallelized very easily.
How to iterate over collection then in functional languages like Scala?
You can always iterate over a inmutable collection, while you do not change anything. For example:
val list = Seq(1,2,3)
for (n <- list)
println n
With respect to the second thing that you said: you have to stop thinking in a traditional way. In functional programming the usage of Map, Filter, Reduce, etc. is normal; as well as pattern matching and other concepts that are not typical in OOP. For the example you give:
Like an example: Suppose we have a list of ints, how to write a function that returns sublist of ints which are divisible by 6?
val list = Seq(1,6,10,12,18,20)
val result = list.filter(_ % 6 == 0)
Firstly you could rewrite your example like this:
def max(first: Int, others: Int*): Int = {
val curMax = Math.max(first, others(0))
if (others.size == 1) curMax else max(curMax, others.tail : _*)
}
This uses varargs and tail recursion to find the largest number. Of course there are many other ways of doing the same thing.
To answer your queston - It's a good question and one that I thought about myself when I first started to use scala. Personally I think the whole immutable/functional programming approach is somewhat over hyped. But for what it's worth here are the main arguments in favour of it:
Immutable code is easier to read (subjective)
Immutable code is more robust - it's certainly true that changing mutable state can lead to bugs. Take this for example:
for (int i=0; i<100; i++) {
for (int j=0; j<100; i++) {
System.out.println("i is " + i = " and j is " + j);
}
}
This is an over simplified example but it's still easy to miss the bug and the compiler won't help you
Mutable code is generally not thread safe. Even trivial and seemingly atomic operations are not safe. Take for example i++ this looks like an atomic operation but it's actually equivalent to:
int i = 0;
int tempI = i + 0;
i = tempI;
Immutable data structures won't allow you to do something like this so you would need to explicitly think about how to handle it. Of course as you point out local variables are generally threadsafe, but there is no guarantee. It's possible to pass a ListBuffer instance variable as a parameter to a method for example
However there are downsides to immutable and functional programming styles:
Performance. It is generally slower in both compilation and runtime. The compiler must enforce the immutability and the JVM must allocate more objects than would be required with mutable data structures. This is especially true of collections.
Most scala examples show something like val numbers = List(1,2,3) but in the real world hard coded values are rare. We generally build collections dynamically (from a database query etc). Whilst scala can reassign the values in a colection it must still create a new collection object every time you modify it. If you want to add 1000 elements to a scala List (immutable) the JVM will need to allocate (and then GC) 1000 objects
Hard to maintain. Functional code can be very hard to read, it's not uncommon to see code like this:
val data = numbers.foreach(_.map(a => doStuff(a).flatMap(somethingElse)).foldleft("", (a : Int,b: Int) => a + b))
I don't know about you but I find this sort of code really hard to follow!
Hard to debug. Functional code can also be hard to debug. Try putting a breakpoint halfway into my (terrible) example above
My advice would be to use a functional/immutable style where it genuinely makes sense and you and your colleagues feel comfortable doing it. Don't use immutable structures because they're cool or it's "clever". Complex and challenging solutions will get you bonus points at Uni but in the commercial world we want simple solutions to complex problems! :)
Your two main questions:
Why warn against local state changes?
How can you iterate over collections without mutable state?
I'll answer both.
Warnings
The compiler warns against the use of mutable local variables because they are often a cause of error. That doesn't mean this is always the case. However, your sample code is pretty much a classic example of where mutable local state is used entirely unnecessarily, in a way that not only makes it more error prone and less clear but also less efficient.
Your first code example is more inefficient than your second, functional solution. Why potentially make two assignments to submax1 when you only ever need to assign one? You ask which of the two inputs is larger anyway, so why not ask that first and then make one assignment? Why was your first approach to temporarily store partial state only halfway through the process of asking such a simple question?
Your first code example is also inefficient because of unnecessary code duplication. You're repeatedly asking "which is the biggest of two values?" Why write out the code for that 3 times independently? Needlessly repeating code is a known bad habit in OOP every bit as much as FP and for precisely the same reasons. Each time you needlessly repeat code, you open a potential source of error. Adding mutable local state (especially when so unnecessary) only adds to the fragility and to the potential for hard to spot errors, even in short code. You just have to type submax1 instead of submax2 in one place and you may not notice the error for a while.
Your second, FP solution removes the code duplication, dramatically reducing the chance of error, and shows that there was simply no need for mutable local state. It's also, as you yourself say, cleaner and clearer - and better than the alternative solution in om-nom-nom's answer.
(By the way, the idiomatic Scala way to write such a simple function is
def max(a: Int, b: Int) = if (a > b) a else b
which terser style emphasises its simplicity and makes the code less verbose)
Your first solution was inefficient and fragile, but it was your first instinct. The warning caused you to find a better solution. The warning proved its value. Scala was designed to be accessible to Java developers and is taken up by many with a long experience of imperative style and little or no knowledge of FP. Their first instinct is almost always the same as yours. You have demonstrated how that warning can help improve code.
There are cases where using mutable local state can be faster but the advice of Scala experts in general (not just the pure FP true believers) is to prefer immutability and to reach for mutability only where there is a clear case for its use. This is so against the instincts of many developers that the warning is useful even if annoying to experienced Scala devs.
It's funny how often some kind of max function comes up in "new to FP/Scala" questions. The questioner is very often tripping up on errors caused by their use of local state... which link both demonstrates the often obtuse addiction to mutable state among some devs while also leading me on to your other question.
Functional Iteration over Collections
There are three functional ways to iterate over collections in Scala
For Comprehensions
Explicit Recursion
Folds and other Higher Order Functions
For Comprehensions
Your question:
Suppose we have a list of ints, how to write a function that returns sublist of ints which are divisible by 6? Can't think of solution without local mutable variable
Answer: assuming xs is a list (or some other sequence) of integers, then
for (x <- xs; if x % 6 == 0) yield x
will give you a sequence (of the same type as xs) containing only those items which are divisible by 6, if any. No mutable state required. Scala just iterates over the sequence for you and returns anything matching your criteria.
If you haven't yet learned the power of for comprehensions (also known as sequence comprehensions) you really should. Its a very expressive and powerful part of Scala syntax. You can even use them with side effects and mutable state if you want (look at the final example on the tutorial I just linked to). That said, there can be unexpected performance penalties and they are overused by some developers.
Explicit Recursion
In the question I linked to at the end of the first section, I give in my answer a very simple, explicitly recursive solution to returning the largest Int from a list.
def max(xs: List[Int]): Option[Int] = xs match {
case Nil => None
case List(x: Int) => Some(x)
case x :: y :: rest => max( (if (x > y) x else y) :: rest )
}
I'm not going to explain how the pattern matching and explicit recursion work (read my other answer or this one). I'm just showing you the technique. Most Scala collections can be iterated over recursively, without any need for mutable state. If you need to keep track of what you've been up to along the way, you pass along an accumulator. (In my example code, I stick the accumulator at the front of the list to keep the code smaller but look at the other answers to those questions for more conventional use of accumulators).
But here is a (naive) explicitly recursive way of finding those integers divisible by 6
def divisibleByN(n: Int, xs: List[Int]): List[Int] = xs match {
case Nil => Nil
case x :: rest if x % n == 0 => x :: divisibleByN(n, rest)
case _ :: rest => divisibleByN(n, rest)
}
I call it naive because it isn't tail recursive and so could blow your stack. A safer version can be written using an accumulator list and an inner helper function but I leave that exercise to you. The result will be less pretty code than the naive version, no matter how you try, but the effort is educational.
Recursion is a very important technique to learn. That said, once you have learned to do it, the next important thing to learn is that you can usually avoid using it explicitly yourself...
Folds and other Higher Order Functions
Did you notice how similar my two explicit recursion examples are? That's because most recursions over a list have the same basic structure. If you write a lot of such functions, you'll repeat that structure many times. Which makes it boilerplate; a waste of your time and a potential source of error.
Now, there are any number of sophisticated ways to explain folds but one simple concept is that they take the boilerplate out of recursion. They take care of the recursion and the management of accumulator values for you. All they ask is that you provide a seed value for the accumulator and the function to apply at each iteration.
For example, here is one way to use fold to extract the highest Int from the list xs
xs.tail.foldRight(xs.head) {(a, b) => if (a > b) a else b}
I know you aren't familiar with folds, so this may seem gibberish to you but surely you recognise the lambda (anonymous function) I'm passing in on the right. What I'm doing there is taking the first item in the list (xs.head) and using it as the seed value for the accumulator. Then I'm telling the rest of the list (xs.tail) to iterate over itself, comparing each item in turn to the accumulator value.
This kind of thing is a common case, so the Collections api designers have provided a shorthand version:
xs.reduce {(a, b) => if (a > b) a else b}
(If you look at the source code, you'll see they have implemented it using a fold).
Anything you might want to do iteratively to a Scala collection can be done using a fold. Often, the api designers will have provided a simpler higher-order function which is implemented, under the hood, using a fold. Want to find those divisible-by-six Ints again?
xs.foldRight(Nil: List[Int]) {(x, acc) => if (x % 6 == 0) x :: acc else acc}
That starts with an empty list as the accumulator, iterates over every item, only adding those divisible by 6 to the accumulator. Again, a simpler fold-based HoF has been provided for you:
xs filter { _ % 6 == 0 }
Folds and related higher-order functions are harder to understand than for comprehensions or explicit recursion, but very powerful and expressive (to anybody else who understands them). They eliminate boilerplate, removing a potential source of error. Because they are implemented by the core language developers, they can be more efficient (and that implementation can change, as the language progresses, without breaking your code). Experienced Scala developers use them in preference to for comprehensions or explicit recursion.
tl;dr
Learn For comprehensions
Learn explicit recursion
Don't use them if a higher-order function will do the job.
It is always nicer to use immutable variables since they make your code easier to read. Writing a recursive code can help solve your problem.
def max(x: List[Int]): Int = {
if (x.isEmpty == true) {
0
}
else {
Math.max(x.head, max(x.tail))
}
}
val a_list = List(a,b,c,d)
max_value = max(a_list)