I never understood it from the contrived unmarshalling and verbing nouns ( an AddTwo class has an apply that adds two!) examples.
I understand that it's syntactic sugar, so (I deduced from context) it must have been designed to make some code more intuitive.
What meaning does a class with an apply function give? What is it used for, and what purposes does it make code better (unmarshalling, verbing nouns etc)?
how does it help when used in a companion object?
Mathematicians have their own little funny ways, so instead of saying "then we call function f passing it x as a parameter" as we programmers would say, they talk about "applying function f to its argument x".
In mathematics and computer science, Apply is a function that applies
functions to arguments.
Wikipedia
apply serves the purpose of closing the gap between Object-Oriented and Functional paradigms in Scala. Every function in Scala can be represented as an object. Every function also has an OO type: for instance, a function that takes an Int parameter and returns an Int will have OO type of Function1[Int,Int].
// define a function in scala
(x:Int) => x + 1
// assign an object representing the function to a variable
val f = (x:Int) => x + 1
Since everything is an object in Scala f can now be treated as a reference to Function1[Int,Int] object. For example, we can call toString method inherited from Any, that would have been impossible for a pure function, because functions don't have methods:
f.toString
Or we could define another Function1[Int,Int] object by calling compose method on f and chaining two different functions together:
val f2 = f.compose((x:Int) => x - 1)
Now if we want to actually execute the function, or as mathematician say "apply a function to its arguments" we would call the apply method on the Function1[Int,Int] object:
f2.apply(2)
Writing f.apply(args) every time you want to execute a function represented as an object is the Object-Oriented way, but would add a lot of clutter to the code without adding much additional information and it would be nice to be able to use more standard notation, such as f(args). That's where Scala compiler steps in and whenever we have a reference f to a function object and write f (args) to apply arguments to the represented function the compiler silently expands f (args) to the object method call f.apply (args).
Every function in Scala can be treated as an object and it works the other way too - every object can be treated as a function, provided it has the apply method. Such objects can be used in the function notation:
// we will be able to use this object as a function, as well as an object
object Foo {
var y = 5
def apply (x: Int) = x + y
}
Foo (1) // using Foo object in function notation
There are many usage cases when we would want to treat an object as a function. The most common scenario is a factory pattern. Instead of adding clutter to the code using a factory method we can apply object to a set of arguments to create a new instance of an associated class:
List(1,2,3) // same as List.apply(1,2,3) but less clutter, functional notation
// the way the factory method invocation would have looked
// in other languages with OO notation - needless clutter
List.instanceOf(1,2,3)
So apply method is just a handy way of closing the gap between functions and objects in Scala.
It comes from the idea that you often want to apply something to an object. The more accurate example is the one of factories. When you have a factory, you want to apply parameter to it to create an object.
Scala guys thought that, as it occurs in many situation, it could be nice to have a shortcut to call apply. Thus when you give parameters directly to an object, it's desugared as if you pass these parameters to the apply function of that object:
class MyAdder(x: Int) {
def apply(y: Int) = x + y
}
val adder = new MyAdder(2)
val result = adder(4) // equivalent to x.apply(4)
It's often use in companion object, to provide a nice factory method for a class or a trait, here is an example:
trait A {
val x: Int
def myComplexStrategy: Int
}
object A {
def apply(x: Int): A = new MyA(x)
private class MyA(val x: Int) extends A {
val myComplexStrategy = 42
}
}
From the scala standard library, you might look at how scala.collection.Seq is implemented: Seq is a trait, thus new Seq(1, 2) won't compile but thanks to companion object and apply, you can call Seq(1, 2) and the implementation is chosen by the companion object.
Here is a small example for those who want to peruse quickly
object ApplyExample01 extends App {
class Greeter1(var message: String) {
println("A greeter-1 is being instantiated with message " + message)
}
class Greeter2 {
def apply(message: String) = {
println("A greeter-2 is being instantiated with message " + message)
}
}
val g1: Greeter1 = new Greeter1("hello")
val g2: Greeter2 = new Greeter2()
g2("world")
}
output
A greeter-1 is being instantiated with message hello
A greeter-2 is being instantiated with message world
TLDR for people comming from c++
It's just overloaded operator of ( ) parentheses
So in scala:
class X {
def apply(param1: Int, param2: Int, param3: Int) : Int = {
// Do something
}
}
Is same as this in c++:
class X {
int operator()(int param1, int param2, int param3) {
// do something
}
};
1 - Treat functions as objects.
2 - The apply method is similar to __call __ in Python, which allows you to use an instance of a given class as a function.
The apply method is what turns an object into a function. The desire is to be able to use function syntax, such as:
f(args)
But Scala has both functional and object oriented syntax. One or the other needs to be the base of the language. Scala (for a variety of reasons) chooses object oriented as the base form of the language. That means that any function syntax has to be translated into object oriented syntax.
That is where apply comes in. Any object that has the apply method can be used with the syntax:
f(args)
The scala infrastructure then translates that into
f.apply(args)
f.apply(args) has correct object oriented syntax. Doing this translation would not be possible if the object had no apply method!
In short, having the apply method in an object is what allows Scala to turn the syntax: object(args) into the syntax: object.apply(args). And object.apply(args) is in the form that can then execute.
FYI, this implies that all functions in scala are objects. And it also implies that having the apply method is what makes an object a function!
See the accepted answer for more insight into just how a function is an object, and the tricks that can be played as a result.
To put it crudely,
You can just see it as custom ()operator. If a class X has an apply() method, whenever you call X() you will be calling the apply() method.
Related
I am trying to understand how a case class can be passed as an argument to a function which accepts functions as arguments. Below is an example:
Consider the below function
def !: In[B] = { ... }
If I understood correctly, this is a polymorphic method which has a type parameter B and accepts a function h as a parameter. Out and In are other two classes defined previously.
This function is then being used as shown below:
case class Q(p: boolean)(val cont: Out[R])
case class R(p: Int)
def g(c: Out[Q]) = {
val rin = c !! Q(true)_
...
}
I am aware that currying is being used to avoid writing the type annotation and instead just writing _. However, I cannot grasp why and how the case class Q is transformed to a function (h) of type Out[B] => A.
EDIT 1 Updated !! above and the In and Out definitions:
abstract class In[+A] {
def future: Future[A]
def receive(implicit d: Duration): A = {
Await.result[A](future, d)
}
def ?[B](f: A => B)(implicit d: Duration): B = {
f(receive)
}
}
abstract class Out[-A]{
def promise[B <: A]: Promise[B]
def send(msg: A): Unit = promise.success(msg)
def !(msg: A) = send(msg)
def create[B](): (In[B], Out[B])
}
These code samples are taken from the following paper: http://drops.dagstuhl.de/opus/volltexte/2016/6115/
TLDR;
Using a case class with multiple parameter lists and partially applying it will yield a partially applied apply call + eta expansion will transform the method into a function value:
val res: Out[Q] => Q = Q.apply(true) _
Longer explanation
To understand the way this works in Scala, we have to understand some fundamentals behind case classes and the difference between methods and functions.
Case classes in Scala are a compact way of representing data. When you define a case class, you get a bunch of convenience methods which are created for you by the compiler, such as hashCode and equals.
In addition, the compiler also generates a method called apply, which allows you to create a case class instance without using the new keyword:
case class X(a: Int)
val x = X(1)
The compiler will expand this call to
val x = X.apply(1)
The same thing will happen with your case class, only that your case class has multiple argument lists:
case class Q(p: boolean)(val cont: Out[R])
val q: Q = Q(true)(new Out[Int] { })
Will get translated to
val q: Q = Q.apply(true)(new Out[Int] { })
On top of that, Scala has a way to transform methods, which are a non value type, into a function type which has the type of FunctionX, X being the arity of the function. In order to transform a method into a function value, we use a trick called eta expansion where we call a method with an underscore.
def foo(i: Int): Int = i
val f: Int => Int = foo _
This will transform the method foo into a function value of type Function1[Int, Int].
Now that we posses this knowledge, let's go back to your example:
val rin = c !! Q(true) _
If we just isolate Q here, this call gets translated into:
val rin = Q.apply(true) _
Since the apply method is curried with multiple argument lists, we'll get back a function that given a Out[Q], will create a Q:
val rin: Out[R] => Q = Q.apply(true) _
I cannot grasp why and how the case class Q is transformed to a function (h) of type Out[B] => A.
It isn't. In fact, the case class Q has absolutely nothing to do with this! This is all about the object Q, which is the companion module to the case class Q.
Every case class has an automatically generated companion module, which contains (among others) an apply method whose signature matches the primary constructor of the companion class, and which constructs an instance of the companion class.
I.e. when you write
case class Foo(bar: Baz)(quux: Corge)
You not only get the automatically defined case class convenience methods such as accessors for all the elements, toString, hashCode, copy, and equals, but you also get an automatically defined companion module that serves both as an extractor for pattern matching and as a factory for object construction:
object Foo {
def apply(bar: Baz)(quux: Corge) = new Foo(bar)(quux)
def unapply(that: Foo): Option[Baz] = ???
}
In Scala, apply is a method that allows you to create "function-like" objects: if foo is an object (and not a method), then foo(bar, baz) is translated to foo.apply(bar, baz).
The last piece of the puzzle is η-expansion, which lifts a method (which is not an object) into a function (which is an object and can thus be passed as an argument, stored in a variable, etc.) There are two forms of η-expansion: explicit η-expansion using the _ operator:
val printFunction = println _
And implicit η-expansion: in cases where Scala knows 100% that you mean a function but you give it the name of a method, Scala will perform η-expansion for you:
Seq(1, 2, 3) foreach println
And you already know about currying.
So, if we put it all together:
Q(true)_
First, we know that Q here cannot possibly be the class Q. How do we know that? Because Q here is used as a value, but classes are types, and like most programming languages, Scala has a strict separation between types and values. Therefore, Q must be a value. In particular, since we know class Q is a case class, object Q is the companion module for class Q.
Secondly, we know that for a value Q
Q(true)
is syntactic sugar for
Q.apply(true)
Thirdly, we know that for case classes, the companion module has an automatically generated apply method that matches the primary constructor, so we know that Q.apply has two parameter lists.
So, lastly, we have
Q.apply(true) _
which passes the first argument list to Q.apply and then lifts Q.apply into a function which accepts the second argument list.
Note that case classes with multiple parameter lists are unusual, since only the parameters in the first parameter list are considered elements of the case class, and only elements benefit from the "case class magic", i.e. only elements get accessors implemented automatically, only elements are used in the signature of the copy method, only elements are used in the automatically generated equals, hashCode, and toString() methods, and so on.
Say I have a local method/function
def withExclamation(string: String) = string + "!"
Is there a way in Scala to transform an instance by supplying this method? Say I want to append an exclamation mark to a string. Something like:
val greeting = "Hello"
val loudGreeting = greeting.applyFunction(withExclamation) //result: "Hello!"
I would like to be able to invoke (local) functions when writing a chain transformation on an instance.
EDIT: Multiple answers show how to program this possibility, so it seems that this feature is not present on an arbitraty class. To me this feature seems incredibly powerful. Consider where in Java I want to execute a number of operations on a String:
appendExclamationMark(" Hello! ".trim().toUpperCase()); //"HELLO!"
The order of operations is not the same as how they read. The last operation, appendExclamationMark is the first word that appears. Currently in Java I would sometimes do:
Function.<String>identity()
.andThen(String::trim)
.andThen(String::toUpperCase)
.andThen(this::appendExclamationMark)
.apply(" Hello "); //"HELLO!"
Which reads better in terms of expressing a chain of operations on an instance, but also contains a lot of noise, and it is not intuitive to have the String instance at the last line. I would want to write:
" Hello "
.applyFunction(String::trim)
.applyFunction(String::toUpperCase)
.applyFunction(this::withExclamation); //"HELLO!"
Obviously the name of the applyFunction function can be anything (shorter please). I thought backwards compatibility was the sole reason Java's Object does not have this.
Is there any technical reason why this was not added on, say, the Any or AnyRef classes?
You can do this with an implicit class which provides a way to extend an existing type with your own methods:
object StringOps {
implicit class RichString(val s: String) extends AnyVal {
def withExclamation: String = s"$s!"
}
def main(args: Array[String]): Unit = {
val m = "hello"
println(m.withExclamation)
}
}
Yields:
hello!
If you want to apply any functions (anonymous, converted from methods, etc.) in this way, you can use a variation on Yuval Itzchakov's answer:
object Combinators {
implicit class Combinators[A](val x: A) {
def applyFunction[B](f: A => B) = f(x)
}
}
A while after asking this question, I noticed that Kotlin has this built in:
inline fun <T, R> T.let(block: (T) -> R): R
Calls the specified function block with this value as its argument and returns
its result.
A lot more, quite useful variations of the above function are provided on all types, like with, also, apply, etc.
I'm learning Scala and I don't really understand the following example :
object Test extends App {
def method1 = println("method 1")
val x = {
def method2 = "method 2" // method inside a block
"this is " + method2
}
method1 // statement inside an object
println(x) // same
}
I mean, it feels inconsistent to me because here I see two different concepts :
Objects/Classes/Traits, which contains members.
Blocks, which contains statements, the last statement being the value of the block.
But here we have a method part of a block, and statements part of an object. So, does it mean that blocks are objects too ? And how are handled the statements part of an object, are they members too ?
Thanks.
Does it mean that blocks are objects too?
No, blocks are not objects. Blocks are used for scoping the binding of variables. Scala enables not only defining expressions inside blocks but also to define methods. If we take your example and compile it, we can see what the compiler does:
object Test extends Object {
def method1(): Unit = scala.Predef.println("method 1");
private[this] val x: String = _;
<stable> <accessor> def x(): String = Test.this.x;
final <static> private[this] def method2$1(): String = "method 2";
def <init>(): tests.Test.type = {
Test.super.<init>();
Test.this.x = {
"this is ".+(Test.this.method2$1())
};
Test.this.method1();
scala.Predef.println(Test.this.x());
()
}
}
What the compiler did is extract method2 to an "unnamed" method on method2$1 and scoped it to private[this] which is scoped to the current instance of the type.
And how are handled the statements part of an object, are they members
too?
The compiler took method1 and println and calls them inside the constructor when the type is initialized. So you can see val x and the rest of the method calls are invoked at construction time.
method2 is actually not a method. It is a local function. Scala allows you to create named functions inside local scopes for organizing your code into functions without polluting the namespace.
It is most often used to define local tail-recursive helper functions. Often, when making a function tail-recursive, you need to add an additional parameter to carry the "state" on the call stack, but this additional parameter is a private internal implementation detail and shouldn't be exposed to clients. In languages without local functions, you would make this a private helper alongside the primary method, but then it would still be within the namespace of the class and callable by all other methods of the class, when it is really only useful for that particular method. So, in Scala, you can instead define it locally inside the method:
// non tail-recursive
def length[A](ls: List[A]) = ls match {
case Nil => 0
case x :: xs => length(xs) + 1
}
//transformation to tail-recursive, Java-style:
def length[A](ls: List[A]) = lengthRec(ls, 0)
private def lengthRec[A](ls: List[A], len: Int) = ls match {
case Nil => len
case x :: xs => lengthRec(xs, len + 1)
}
//tail-recursive, Scala-style:
def length[A](ls: List[A]) = {
//note: lengthRec is nested and thus can access `ls`, there is no need to pass it
def lengthRec(len: Int) = ls match {
case Nil => len
case x :: xs => lengthRec(xs, len + 1)
}
lengthRec(ls, 0)
}
Now you might say, well I see the value in defining local functions inside methods, but what's the value in being able to define local functions in blocks? Scala tries to as simple as possible and have as few corner cases as possible. If you can define local functions inside methods, and local functions inside local functions … then why not simplify that rule and just say that local functions behave just like local fields, you can simply define them in any block scope. Then you don't need different scope rules for local fields and local functions, and you have simplified the language.
The other thing you mentioned, being able to execute code in the bode of a template, that's actually the primary constructor (so to speak … it's technically more like an initializer). Remember: the primary constructor's signature is defined with parentheses after the class name … but where would you put the code for the constructor then? Well, you put it in the body of the class!
What is the reason behind the design decision in Scala that monads do not have a return/unit function in contrast to Haskell where each monad has a return function that puts a value into a standard monadic context for the given monad?
For example why List, Option, Set etc... do not have a return/unit functions defined in the standard library as shown in the slides below?
I am asking this because in the reactive Coursera course Martin Odersky explicitly mentioned this fact, as can be seen below in the slides, but did not explain why Scala does not have them even though unit/return is an essential property of a monad.
As Ørjan Johansen said, Scala does not support method dispatching on return type. Scala object system is built over JVM one, and JVM invokevirtual instruction, which is the main tool for dynamic polymorphism, dispatches the call based on type of this object.
As a side note, dispatching is a process of selecting concrete method to call. In Scala/Java all methods are virtual, that is, the actual method which is called depends on actual type of the object.
class A { def hello() = println("hello method in A") }
class B extends A { override def hello() = println("hello method in B") }
val x: A = new A
x.hello() // prints "hello method in A"
val y: A = new B
y.hello() // prints "hello method in B"
Here, even if y variable is of type A, hello method from B is called, because JVM "sees" that the actual type of the object in y is B and invokes appropriate method.
However, JVM only takes the type of the variable on which the method is called into account. It is impossible, for example, to call different methods based on runtime type of arguments without explicit checks. For example:
class A {
def hello(x: Number) = println(s"Number: $x")
def hello(y: Int) = println(s"Integer: $y")
}
val a = new A
val n: Number = 10: Int
a.hello(n) // prints "Number: 10"
Here we have two methods with the same name, but with different parameter type. And even if ns actual type is Int, hello(Number) version is called - it is resolved statically based on n static variable type (this feature, static resolution based on argument types, is called overloading). Hence, there is no dynamic dispatch on method arguments. Some languages support dispatching on method arguments too, for example, Common Lisp's CLOS or Clojure's multimethods work like that.
Haskell has advanced type system (it is comparable to Scala's and in fact they both originate in System F, but Scala type system supports subtyping which makes type inference much more difficult) which allows global type inference, at least, without certain extensions enabled. Haskell also has a concept of type classes, which is its tool for dynamic polymorphism. Type classes can be loosely thought of as interfaces without inheritance but with dispatch on parameter and return value types. For example, this is a valid type class:
class Read a where
read :: String -> a
instance Read Integer where
read s = -- parse a string into an integer
instance Read Double where
read s = -- parse a string into a double
Then, depending on the context where method is called, read function for Integer or Double can be called:
x :: Integer
x = read "12345" // read for Integer is called
y :: Double
y = read "12345.0" // read for Double is called
This is a very powerful technique which has no correspondence in bare JVM object system, so Scala object system does not support it too. Also the lack of full-scale type inference would make this feature somewhat cumbersome to use. So, Scala standard library does not have return/unit method anywhere - it is impossible to express it using regular object system, there is simply no place where such a method could be defined. Consequently, monad concept in Scala is implicit and conventional - everything with appropriate flatMap method can be considered a monad, and everything with the right methods can be used in for construction. This is much like duck typing.
However, Scala type system together with its implicits mechanism is powerful enough to express full-featured type classes, and, by extension, generic monads in formal way, though due to difficulties in full type inference it may require adding more type annotations than in Haskell.
This is definition of monad type class in Scala:
trait Monad[M[_]] {
def unit[A](a: A): M[A]
def bind[A, B](ma: M[A])(f: A => M[B]): M[B]
}
And this is its implementation for Option:
implicit object OptionMonad extends Monad[Option] {
def unit[A](a: A) = Some(a)
def bind[A, B](ma: Option[A])(f: A => Option[B]): Option[B] =
ma.flatMap(f)
}
Then this can be used in generic way like this:
// note M[_]: Monad context bound
// this is a port of Haskell's filterM found here:
// http://hackage.haskell.org/package/base-4.7.0.1/docs/src/Control-Monad.html#filterM
def filterM[M[_]: Monad, A](as: Seq[A])(f: A => M[Boolean]): M[Seq[A]] = {
val m = implicitly[Monad[M]]
as match {
case x +: xs =>
m.bind(f(x)) { flg =>
m.bind(filterM(xs)(f)) { ys =>
m.unit(if (flg) x +: ys else ys)
}
}
case _ => m.unit(Seq.empty[A])
}
}
// using it
def run(s: Seq[Int]) = {
import whatever.OptionMonad // bring type class instance into scope
// leave all even numbers in the list, but fail if the list contains 13
filterM[Option, Int](s) { a =>
if (a == 13) None
else if (a % 2 == 0) Some(true)
else Some(false)
}
}
run(1 to 16) // returns None
run(16 to 32) // returns Some(List(16, 18, 20, 22, 24, 26, 28, 30, 32))
Here filterM is written generically, for any instance of Monad type class. Because OptionMonad implicit object is present at filterM call site, it will be passed to filterM implicitly, and it will be able to make use of its methods.
You can see from above that type classes allow to emulate dispatching on return type even in Scala. In fact, this is exactly what Haskell does under the covers - both Scala and Haskell are passing a dictionary of methods implementing some type class, though in Scala it is somewhat more explicit because these "dictionaries" are first-class objects there and can be imported on demand or even passed explicitly, so it is not really a proper dispatching as it is not that embedded.
If you need this amount of genericity, you can use Scalaz library which contains a lot of type classes (including monad) and their instances for some common types, including Option.
I don't think you're really saying that Scala's monads don't have a unit function - it's rather just that the name of the unit function can vary. That's what seems to be shown in the second slide's examples.
As for why that is so, I think it's just because Scala runs on the JVM, and those function have to be implemented as JVM methods - which are uniquely identified by:
the class they belong to;
their name;
their parameters types.
But they are not identified by their return type. Since the parameter type generally won't differentiate the various unit functions (it's usually just a generic type), you need different names for them.
In practice, they will often be implemented as the apply(x) method on the companion object of the monad class. For example, for the class List, the unit function is the apply(x) method on the object List. By convention, List.apply(x) can be called as List(x) too, which is more common/idiomatic.
So I guess that Scala at least has a naming convention for the unit function, though it doesn't have a unique name for it :
// Some monad :
class M[T] {
def flatMap[U](f: T => M[U]): M[U] = ???
}
// Companion object :
object M {
def apply(x: T): M[T] = ??? // Unit function
}
// Usage of the unit function :
val x = ???
val m = M(x)
Caveat: I'm still learning Haskell and I'm sort of making up this answer as I go.
First, what you already know - that Haskell's do notation desugars to bind:
Borrowing this example from Wikipedia:
add mx my = do
x <- mx
y <- my
return (x + y)
add mx my =
mx >>= (\x ->
my >>= (\y ->
return (x + y)))
Scala's analogue to do is the for-yield expression. It similarly desugars each step to flatMap (its equivalent of bind).
There's a difference, though: The last <- in a for-yield desugars to map, not to flatMap.
def add(mx: Option[Int], my: Option[Int]) =
for {
x <- mx
y <- my
} yield x + y
def add(mx: Option[Int], my: Option[Int]) =
mx.flatMap(x =>
my.map(y =>
x + y))
So because you don't have the "flattening" on the last step, the expression value already has the monad type, so there's no need to "re-wrap" it with something comparable to return.
Actually there is a return function in scala. It is just hard to find.
Scala slightly differs from Haskell in many aspects. Most of that differences are direct consequences of JVM limitations. JVM can not dispatch methods basing on its return type. So Scala introduced type class polymorphism based on implicit evidence to fix this inconvenience.
It is even used in scala standard collections. You may notice numerous usage of CanBuildFrom and CanBuild implicits used in the scala collection api. See scala.collection.immutable.List for example.
Every time you want to build custom collection you should write realization for this implicits. There are not so many guides for writing one though. I recommend you this guide. It shows why CanBuildFrom is so important for collections and how it is used. In fact that is just another form of the return function and anyone familiar with Haskell monads would understand it's importance clearly.
So you may use custom collection as example monads and write other monads basing on provided tutorial.
I understand the difference between zero-parameter and parameterless methods, but what I don't really understand is the language design choice that made parameterless methods necessary.
Disadvantages I can think of:
It's confusing. Every week or two there are questions here or on the Scala mailing list about it.
It's complicated; we also have to distinguish between () => X and => X.
It's ambiguous: does x.toFoo(y) mean what it says, or x.toFoo.apply(y)? (Answer: it depends on what overloads there are x's toFoo method and the overloads on Foo's apply method, but if there's a clash you don't see an error until you try to call it.)
It messes up operator style method calling syntax: there is no symbol to use in place of the arguments, when chaining methods, or at the end to avoid semicolon interference. With zero-arg methods you can use the empty parameter list ().
Currently, you can't have both defined in a class: you get an error saying the method is already defined. They also both convert to a Function0.
Why not just make methods def foo and def foo() exactly the same thing, and allow them to be called with or without parentheses? What are the upsides of how it is?
Currying, That's Why
Daniel did a great job at explaining why parameterless methods are necessary. I'll explain why they are regarded distinctly from zero-parameter methods.
Many people view the distinction between parameterless and zero-parameter functions as some vague form of syntactic sugar. In truth it is purely an artifact of how Scala supports currying (for completeness, see below for a more thorough explanation of what currying is, and why we all like it so much).
Formally, a function may have zero or more parameter lists, with zero or more parameters each.
This means the following are valid: def a, def b(), but also the contrived def c()() and def d(x: Int)()()(y: Int) etc...
A function def foo = ??? has zero parameter lists. A function def bar() = ??? has precisely one parameter list, with zero parameters. Introducing additional rules that conflate the two forms would have undermined currying as a consistent language feature: def a would be equivalent in form to def b() and def c()() both; def d(x: Int)()()(y: Int) would be equivalent to def e()(x: Int)(y: Int)()().
One case where currying is irrelevant is when dealing with Java interop. Java does not support currying, so there's no problem with introducing syntactic sugar for zero-parameter methods like "test".length() (which directly invokes java.lang.String#length()) to also be invoked as "test".length.
A quick explanation of currying
Scala supports a language feature called 'currying', named after mathematician Haskell Curry.
Currying allows you to define functions with several parameter lists, e.g.:
def add(a: Int)(b: Int): Int = a + b
add(2)(3) // 5
This is useful, because you can now define inc in terms of a partial application of add:
def inc: Int => Int = add(1)
inc(2) // 3
Currying is most often seen as a way of introducing control structures via libraries, e.g.:
def repeat(n: Int)(thunk: => Any): Unit = (1 to n) foreach { _ => thunk }
repeat(2) {
println("Hello, world")
}
// Hello, world
// Hello, world
As a recap, see how repeat opens up another opportunity to use currying:
def twice: (=> Any) => Unit = repeat(2)
twice {
println("Hello, world")
}
// ... you get the picture :-)
One nice thing about an issue coming up periodically on the ML is that there are periodic answers.
Who can resist a thread called "What is wrong with us?"
https://groups.google.com/forum/#!topic/scala-debate/h2Rej7LlB2A
From: martin odersky Date: Fri, Mar 2, 2012 at
12:13 PM Subject: Re: [scala-debate] what is wrong with us...
What some people think is "wrong with us" is that we are trying bend
over backwards to make Java idioms work smoothly in Scala. The
principaled thing would have been to say def length() and def length
are different, and, sorry, String is a Java class so you have to write
s.length(), not s.length. We work really hard to paper over it by
admitting automatic conversions from s.length to s.length(). That's
problematic as it is. Generalizing that so that the two are identified
in the type system would be a sure way to doom. How then do you
disambiguate:
type Action = () => () def foo: Action
Is then foo of type Action or ()? What about foo()?
Martin
My favorite bit of paulp fiction from that thread:
On Fri, Mar 2, 2012 at 10:15 AM, Rex Kerr <ich...#gmail.com> wrote:
>This would leave you unable to distinguish between the two with
>structural types, but how often is the case when you desperately
>want to distinguish the two compared to the case where distinguishing
>between the two is a hassle?
/** Note to maintenance programmer: It is important that this method be
* callable by classes which have a 'def foo(): Int' but not by classes which
* merely have a 'def foo: Int'. The correctness of this application depends
* on maintaining this distinction.
*
* Additional note to maintenance programmer: I have moved to zambia.
* There is no forwarding address. You will never find me.
*/
def actOnFoo(...)
So the underlying motivation for the feature is to generate this sort of ML thread.
One more bit of googlology:
On Thu, Apr 1, 2010 at 8:04 PM, Rex Kerr <[hidden email]> wrote: On
Thu, Apr 1, 2010 at 1:00 PM, richard emberson <[hidden email]> wrote:
I assume "def getName: String" is the same as "def getName(): String"
No, actually, they are not. Even though they both call a method
without parameters, one is a "method with zero parameter lists" while
the other is a "method with one empty parameter list". If you want to
be even more perplexed, try def getName()(): String (and create a
class with that signature)!
Scala represents parameters as a list of lists, not just a list, and
List() != List(List())
It's kind of a quirky annoyance, especially since there are so few
distinctions between the two otherwise, and since both can be
automatically turned into the function signature () => String.
True. In fact, any conflation between parameterless methods and
methods with empty parameter lists is entirely due to Java interop.
They should be different but then dealing with Java methods would be
just too painful. Can you imagine having to write str.length() each
time you take the length of a string?
Cheers
First off, () => X and => X has absolutely nothing to do with parameterless methods.
Now, it looks pretty silly to write something like this:
var x() = 5
val y() = 2
x() = x() + y()
Now, if you don't follow what the above has to do with parameterless methods, then you should look up uniform access principle. All of the above are method declarations, and all of them can be replaced by def. That is, assuming you remove their parenthesis.
Besides the convention fact mentioned (side-effect versus non-side-effect), it helps with several cases:
Usefulness of having empty-paren
// short apply syntax
object A {
def apply() = 33
}
object B {
def apply = 33
}
A() // works
B() // does not work
// using in place of a curried function
object C {
def m()() = ()
}
val f: () => () => Unit = C.m
Usefulness of having no-paren
// val <=> def, var <=> two related defs
trait T { def a: Int; def a_=(v: Int): Unit }
trait U { def a(): Int; def a_=(v: Int): Unit }
def tt(t: T): Unit = t.a += 1 // works
def tu(u: U): Unit = u.a += 1 // does not work
// avoiding clutter with apply the other way round
object D {
def a = Vector(1, 2, 3)
def b() = Vector(1, 2, 3)
}
D.a(0) // works
D.b(0) // does not work
// object can stand for no-paren method
trait E
trait F { def f: E }
trait G { def f(): E }
object H extends F {
object f extends E // works
}
object I extends G {
object f extends E // does not work
}
Thus in terms of regularity of the language, it makes sense to have the distinction (especially for the last shown case).
I would say both are possible because you can access mutable state with a parameterless method:
class X(private var x: Int) {
def inc() { x += 1 }
def value = x
}
The method value does not have side effects (it only accesses mutable state). This behavior is explicitly mentioned in Programming in Scala:
Such parameterless methods are quite common in Scala. By contrast, methods defined with empty parentheses, such as def height(): Int, are called empty-paren methods. The recommended convention is to use a parameterless method whenever there are no parameters and the method accesses mutable state only by reading fields of the containing object (in particular, it does not change mutable state).
This convention supports the uniform access principle [...]
To summarize, it is encouraged style in Scala to define methods that take no parameters and have no side effects as parameterless methods, i.e., leaving off the empty parentheses. On the other hand, you should never define a method that has side-effects without parentheses, because then invocations of that method would look like a field selection.