Related
In the Scala Odersky book, he has an example explaining partial functions of page 295. It starts with this function:
val second: List[Int] => Int = {
case x :: y :: _ => y
}
So the above function will succeed if you pass it a three element list but not an empty list.
second(List(5,6,7))
works but not
second(List())
The above will throw a MatchError: List
Here is the part that is confusing to me. Odersky writes:
If you want to check whether a partial function is defined, you must first tell the compiler that you know you are working with partial functions.
Why would I want to check whether a partial function is defined. What is a partial function? Is it a function that only applies to some values?
The type List[Int] => Int includes all functions from lists of integers to integers, whether or not the functions are partial. The type that only includes partial functions from lists of integers to integers is written PartialFunction[List[Int], Int].
So the above function returns a function of type List[Int] => Int, I see that, but why do we need to change this function to type PartialFunction[List[Int], Int]?
Here is the function redefined:
val second: PartialFunction[List [Int], Int] = {
case x :: y :: _ => y
}
I don't really get it. What is the benefit? Why do we want to check whether a partial function is defined? What does that even mean?
A partial function is any function, which takes only a single argument, that is defined (i.e. valid) only for a certain range of its argument's values. For example, Math.asin is defined only for argument values in the range [-1.0, 1.0] and is undefined for values outside of that range - so it is a partial function. For example, if we call Math.asin(5.0), we get NaN returned, meaning that the function is not defined for that argument.
Note that a partial function doesn't necessarily have to throw an exception; it just needs to do something other than return a valid value.
A key principle of functional programming is referential transparency (RT), meaning that we should be able to replace an expression (such as a function call) with the value of that expression, without changing the meaning of the program. (For more on this topic, I highly recommend that you read Functional Programming in Scala by Chiusano and Bjarnason.) Clearly, that breaks down if an exception is thrown or if an invalid value is returned. For calls to partial functions to be referentially transparent, we can only call them with argument values for which they are defined, or we need to elegantly handle the undefined values. So how can we tell if a partial function is defined for some arbitrary argument value?
In Scala we can express partial functions as a subclass of scala.PartialFunction that allows us to answer this question.
Let's look at your example in a Scala REPL session...
$ scala
Welcome to Scala 2.12.6 (Java HotSpot(TM) 64-Bit Server VM, Java 1.8.0_171).
Type in expressions for evaluation. Or try :help.
scala> val second: List[Int] => Int = {
| case x :: y :: _ => y
| }
<console>:11: warning: match may not be exhaustive.
It would fail on the following inputs: List(_), Nil
val second: List[Int] => Int = {
^
second: List[Int] => Int = $$Lambda$3181/1894473818#27492c62
So what did we just do? We defined second as a reference to a function that takes a List[Int] argument and returns an Int (the second value in the list).
You'll notice that the Scala compiler recognizes that this is not going to match all cases and warns you of the fact. This is a partial function, in the sense that it will fail for some arguments, but it's not an instance of scala.PartialFunction, as we can verify as follows:
scala> second.isInstanceOf[PartialFunction[List[Int], Int]]
res0: Boolean = false
Incidentally, the type List[Int] => Int is a shorthand for scala.Function1[List[Int], Int] and so seconds type is an instance of that type:
scala> second.isInstanceOf[Function1[List[Int], Int]]
res1: Boolean = true
Calling this version of the function produces the results you indicate:
scala> second(List(1, 2, 3))
res1: Int = 2
scala> second(Nil)
scala.MatchError: List() (of class scala.collection.immutable.Nil$)
at .$anonfun$second$1(<console>:11)
at .$anonfun$second$1$adapted(<console>:11)
... 36 elided
The problem is that if we just have some list value, l, and don't know what is in that list, we don't know whether we'll get an exception if we pass it to the function referenced by second. Now, we could put the call in a try block and catch any exception, but that's verbose and not good functional programming style. Ideally, we'd like to know whether we can call the function first to avoid an exception. Unfortunately, there's no way to tell from a Function1 instance:
scala> second.isDefinedAt(Nil)
<console>:13: error: value isDefinedAt is not a member of List[Int] => Int
second.isDefinedAt(Nil)
^
What we need is to declare second to have the type PartialFunction[List[Int], Int] as follows:
scala> val second: PartialFunction[List[Int], Int] = {
| case x :: y :: _ => y
| }
second: PartialFunction[List[Int],Int] = <function1>
(BTW, note that you have a typo in your question for this code - the above is how this should be defined.)
Now we do not have any warnings! We've told the compiler that this is a PartialFunction instance, so the compiler knows that its undefined for some arguments, so warnings are superfluous. We can now verify that fact:
scala> second.isInstanceOf[PartialFunction[List[Int], Int]]
res6: Boolean = true
We can now also verify whether it's defined for particular values:
scala> second.isDefinedAt(Nil)
res7: Boolean = false
scala> second.isDefinedAt(List(1, 2))
res9: Boolean = true
and so on. (The Scala compiler, as described in the book, is able to implement this magical isDefinedAt function for us.)
So, does that mean we should now write code like this:
def getSecondValue(l: List[Int]): Option[Int] = {
// Check if second is defined for this argument. If so, call it and wrap in Some.
if(second.isDefinedAt(l)) Some(second(l))
// Otherwise, we do not have a second value.
else None
}
Well, that's a little verbose too. Fortunately, once second is a PartialFunction instance, we can rewrite the above as:
def getSecondValue(l: List[Int]): Option[Int] = second.lift(l)
The lift method turns a partial function into a complete function that returns a defined value for every argument: if the argument to second is defined, then we get a Some(value); otherwise, we get None.
You'll find the concept of partial functions, and PartialFunction, more useful as you become more familiar with functional programming. If you don't get it right now, don't worry; all will become clear.
A partial function is a function that does not provide an answer for every possible input value it can be given. It provides an answer only for a subset of possible data, and defines the data it can handle. In Scala, a partial function can also be queried to determine if it can handle a particular value.
As a simple example, imagine a normal function that divides one number by another:
val divide = (x: Int) => 42 / x
As defined, this function blows up when the input parameter is zero:
scala> divide(0)
java.lang.ArithmeticException: / by zero
Although you can handle this particular situation by catching and throwing an exception, Scala lets you define the divide function as a PartialFunction. When doing so, you also explicitly state that the function is defined when the input parameter is not zero:
val divide = new PartialFunction[Int, Int] {
def apply(x: Int) = 42 / x
def isDefinedAt(x: Int) = x != 0
}
https://alvinalexander.com/scala/how-to-define-use-partial-functions-in-scala-syntax-examples
You can refer to the above link.
I read Scala Functions (part of Another tour of Scala). In that post he stated:
Methods and functions are not the same thing
But he didn't explain anything about it. What was he trying to say?
Jim has got this pretty much covered in his blog post, but I'm posting a briefing here for reference.
First, let's see what the Scala Specification tell us. Chapter 3 (types) tell us about Function Types (3.2.9) and Method Types (3.3.1). Chapter 4 (basic declarations) speaks of Value Declaration and Definitions (4.1), Variable Declaration and Definitions (4.2) and Functions Declarations and Definitions (4.6). Chapter 6 (expressions) speaks of Anonymous Functions (6.23) and Method Values (6.7). Curiously, function values is spoken of one time on 3.2.9, and no where else.
A Function Type is (roughly) a type of the form (T1, ..., Tn) => U, which is a shorthand for the trait FunctionN in the standard library. Anonymous Functions and Method Values have function types, and function types can be used as part of value, variable and function declarations and definitions. In fact, it can be part of a method type.
A Method Type is a non-value type. That means there is no value - no object, no instance - with a method type. As mentioned above, a Method Value actually has a Function Type. A method type is a def declaration - everything about a def except its body.
Value Declarations and Definitions and Variable Declarations and Definitions are val and var declarations, including both type and value - which can be, respectively, Function Type and Anonymous Functions or Method Values. Note that, on the JVM, these (method values) are implemented with what Java calls "methods".
A Function Declaration is a def declaration, including type and body. The type part is the Method Type, and the body is an expression or a block. This is also implemented on the JVM with what Java calls "methods".
Finally, an Anonymous Function is an instance of a Function Type (ie, an instance of the trait FunctionN), and a Method Value is the same thing! The distinction is that a Method Value is created from methods, either by postfixing an underscore (m _ is a method value corresponding to the "function declaration" (def) m), or by a process called eta-expansion, which is like an automatic cast from method to function.
That is what the specs say, so let me put this up-front: we do not use that terminology! It leads to too much confusion between so-called "function declaration", which is a part of the program (chapter 4 -- basic declarations) and "anonymous function", which is an expression, and "function type", which is, well a type -- a trait.
The terminology below, and used by experienced Scala programmers, makes one change from the terminology of the specification: instead of saying function declaration, we say method. Or even method declaration. Furthermore, we note that value declarations and variable declarations are also methods for practical purposes.
So, given the above change in terminology, here's a practical explanation of the distinction.
A function is an object that includes one of the FunctionX traits, such as Function0, Function1, Function2, etc. It might be including PartialFunction as well, which actually extends Function1.
Let's see the type signature for one of these traits:
trait Function2[-T1, -T2, +R] extends AnyRef
This trait has one abstract method (it has a few concrete methods as well):
def apply(v1: T1, v2: T2): R
And that tell us all that there is to know about it. A function has an apply method which receives N parameters of types T1, T2, ..., TN, and returns something of type R. It is contra-variant on the parameters it receives, and co-variant on the result.
That variance means that a Function1[Seq[T], String] is a subtype of Function1[List[T], AnyRef]. Being a subtype means it can be used in place of it. One can easily see that if I'm going to call f(List(1, 2, 3)) and expect an AnyRef back, either of the two types above would work.
Now, what is the similarity of a method and a function? Well, if f is a function and m is a method local to the scope, then both can be called like this:
val o1 = f(List(1, 2, 3))
val o2 = m(List(1, 2, 3))
These calls are actually different, because the first one is just a syntactic sugar. Scala expands it to:
val o1 = f.apply(List(1, 2, 3))
Which, of course, is a method call on object f. Functions also have other syntactic sugars to its advantage: function literals (two of them, actually) and (T1, T2) => R type signatures. For example:
val f = (l: List[Int]) => l mkString ""
val g: (AnyVal) => String = {
case i: Int => "Int"
case d: Double => "Double"
case o => "Other"
}
Another similarity between a method and a function is that the former can be easily converted into the latter:
val f = m _
Scala will expand that, assuming m type is (List[Int])AnyRef into (Scala 2.7):
val f = new AnyRef with Function1[List[Int], AnyRef] {
def apply(x$1: List[Int]) = this.m(x$1)
}
On Scala 2.8, it actually uses an AbstractFunction1 class to reduce class sizes.
Notice that one can't convert the other way around -- from a function to a method.
Methods, however, have one big advantage (well, two -- they can be slightly faster): they can receive type parameters. For instance, while f above can necessarily specify the type of List it receives (List[Int] in the example), m can parameterize it:
def m[T](l: List[T]): String = l mkString ""
I think this pretty much covers everything, but I'll be happy to complement this with answers to any questions that may remain.
One big practical difference between a method and a function is what return means. return only ever returns from a method. For example:
scala> val f = () => { return "test" }
<console>:4: error: return outside method definition
val f = () => { return "test" }
^
Returning from a function defined in a method does a non-local return:
scala> def f: String = {
| val g = () => { return "test" }
| g()
| "not this"
| }
f: String
scala> f
res4: String = test
Whereas returning from a local method only returns from that method.
scala> def f2: String = {
| def g(): String = { return "test" }
| g()
| "is this"
| }
f2: String
scala> f2
res5: String = is this
function A function can be invoked with a list of arguments to produce a
result. A function has a parameter list, a body, and a result type.
Functions that are members of a class, trait, or singleton object are
called methods. Functions defined inside other functions are called
local functions. Functions with the result type of Unit are called procedures.
Anonymous functions in source code are called function literals.
At run time, function literals are instantiated into objects called
function values.
Programming in Scala Second Edition.
Martin Odersky - Lex Spoon - Bill Venners
Let Say you have a List
scala> val x =List.range(10,20)
x: List[Int] = List(10, 11, 12, 13, 14, 15, 16, 17, 18, 19)
Define a Method
scala> def m1(i:Int)=i+2
m1: (i: Int)Int
Define a Function
scala> (i:Int)=>i+2
res0: Int => Int = <function1>
scala> x.map((x)=>x+2)
res2: List[Int] = List(12, 13, 14, 15, 16, 17, 18, 19, 20, 21)
Method Accepting Argument
scala> m1(2)
res3: Int = 4
Defining Function with val
scala> val p =(i:Int)=>i+2
p: Int => Int = <function1>
Argument to function is Optional
scala> p(2)
res4: Int = 4
scala> p
res5: Int => Int = <function1>
Argument to Method is Mandatory
scala> m1
<console>:9: error: missing arguments for method m1;
follow this method with `_' if you want to treat it as a partially applied function
Check the following Tutorial that explains passing other differences with examples like other example of diff with Method Vs Function, Using function as Variables, creating function that returned function
Functions don't support parameter defaults. Methods do. Converting from a method to a function loses parameter defaults. (Scala 2.8.1)
There is a nice article here from which most of my descriptions are taken.
Just a short comparison of Functions and Methods regarding my understanding. Hope it helps:
Functions:
They are basically an object. More precisely, functions are objects with an apply method; Therefore, they are a little bit slower than methods because of their overhead. It is similar to static methods in the sense that they are independent of an object to be invoked.
A simple example of a function is just like bellow:
val f1 = (x: Int) => x + x
f1(2) // 4
The line above is nothing except assigning one object to another like object1 = object2. Actually the object2 in our example is an anonymous function and the left side gets the type of an object because of that. Therefore, now f1 is an object(Function). The anonymous function is actually an instance of Function1[Int, Int] that means a function with 1 parameter of type Int and return value of type Int.
Calling f1 without the arguments will give us the signature of the anonymous function (Int => Int = )
Methods:
They are not objects but assigned to an instance of a class,i.e., an object. Exactly the same as method in java or member functions in c++ (as Raffi Khatchadourian pointed out in a comment to this question) and etc.
A simple example of a method is just like bellow:
def m1(x: Int) = x + x
m1(2) // 4
The line above is not a simple value assignment but a definition of a method. When you invoke this method with the value 2 like the second line, the x is substituted with 2 and the result will be calculated and you get 4 as an output. Here you will get an error if just simply write m1 because it is method and need the input value. By using _ you can assign a method to a function like bellow:
val f2 = m1 _ // Int => Int = <function1>
Here is a great post by Rob Norris which explains the difference, here is a TL;DR
Methods in Scala are not values, but functions are. You can construct a function that delegates to a method via η-expansion (triggered by the trailing underscore thingy).
with the following definition:
a method is something defined with def and a value is something you can assign to a val
In a nutshell (extract from the blog):
When we define a method we see that we cannot assign it to a val.
scala> def add1(n: Int): Int = n + 1
add1: (n: Int)Int
scala> val f = add1
<console>:8: error: missing arguments for method add1;
follow this method with `_' if you want to treat it as a partially applied function
val f = add1
Note also the type of add1, which doesn’t look normal; you can’t declare a variable of type (n: Int)Int. Methods are not values.
However, by adding the η-expansion postfix operator (η is pronounced “eta”), we can turn the method into a function value. Note the type of f.
scala> val f = add1 _
f: Int => Int = <function1>
scala> f(3)
res0: Int = 4
The effect of _ is to perform the equivalent of the following: we construct a Function1 instance that delegates to our method.
scala> val g = new Function1[Int, Int] { def apply(n: Int): Int = add1(n) }
g: Int => Int = <function1>
scala> g(3)
res18: Int = 4
Practically, a Scala programmer only needs to know the following three rules to use functions and methods properly:
Methods defined by def and function literals defined by => are functions. It is defined in page 143, Chapter 8 in the book of Programming in Scala, 4th edition.
Function values are objects that can be passed around as any values. Function literals and partially applied functions are function values.
You can leave off the underscore of a partially applied function if a function value is required at a point in the code. For example: someNumber.foreach(println)
After four editions of Programming in Scala, it is still an issue for people to differentiate the two important concepts: function and function value because all editions don't give a clear explanation. The language specification is too complicated. I found the above rules are simple and accurate.
In Scala 2.13, unlike functions, methods can take/return
type parameters (polymorphic methods)
implicit parameters
dependent types
However, these restrictions are lifted in dotty (Scala 3) by Polymorphic function types #4672, for example, dotty version 0.23.0-RC1 enables the following syntax
Type parameters
def fmet[T](x: List[T]) = x.map(e => (e, e))
val ffun = [T] => (x: List[T]) => x.map(e => (e, e))
Implicit parameters (context parameters)
def gmet[T](implicit num: Numeric[T]): T = num.zero
val gfun: [T] => Numeric[T] ?=> T = [T] => (using num: Numeric[T]) => num.zero
Dependent types
class A { class B }
def hmet(a: A): a.B = new a.B
val hfun: (a: A) => a.B = hmet
For more examples, see tests/run/polymorphic-functions.scala
The difference is subtle but substantial and it is related to the type system in use (besides the nomenclature coming from Object Oriented or Functional paradigm).
When we talk about a function, we talk about the type Function: it being a type, an instance of it can be passed around as input or output to other functions (at least in the case of Scala).
When we talk about a method (of a class), we are actually talking about the type represented by the class it is part of: that is, the method is just a component of a larger type, and cannot be passed around by itself. It must be passed around with the instance of the type it is part of (i.e. the instance of the class).
A method belongs to an object (usually the class, trait or object in which you define it), whereas a function is by itself a value, and because in Scala every value is an object, therefore, a function is an object.
For example, given a method and a function below:
def timesTwoMethod(x :Int): Int = x * 2
def timesTwoFunction = (x: Int) => x * 2
The second def is an object of type Int => Int (the syntactic sugar for Function1[Int, Int]).
Scala made functions objects so they could be used as first-class entities. This way you can pass functions to other functions as arguments.
However, Scala can also treat methods as functions via a mechanism called Eta Expansion.
For example, the higher-order function map defined on List, receives another function f: A => B as its only parameter. The next two lines are equivalent:
List(1, 2, 3).map(timesTwoMethod)
List(1, 2, 3).map(timesTwoFunction)
When the compiler sees a def given in a place where a function is needed, it automatically converts the method into an equivalent function.
A method operates on an object but a function doesn't.
Scala and C++ has Fuction but in JAVA, you have to imitate them with static methods.
I read Scala Functions (part of Another tour of Scala). In that post he stated:
Methods and functions are not the same thing
But he didn't explain anything about it. What was he trying to say?
Jim has got this pretty much covered in his blog post, but I'm posting a briefing here for reference.
First, let's see what the Scala Specification tell us. Chapter 3 (types) tell us about Function Types (3.2.9) and Method Types (3.3.1). Chapter 4 (basic declarations) speaks of Value Declaration and Definitions (4.1), Variable Declaration and Definitions (4.2) and Functions Declarations and Definitions (4.6). Chapter 6 (expressions) speaks of Anonymous Functions (6.23) and Method Values (6.7). Curiously, function values is spoken of one time on 3.2.9, and no where else.
A Function Type is (roughly) a type of the form (T1, ..., Tn) => U, which is a shorthand for the trait FunctionN in the standard library. Anonymous Functions and Method Values have function types, and function types can be used as part of value, variable and function declarations and definitions. In fact, it can be part of a method type.
A Method Type is a non-value type. That means there is no value - no object, no instance - with a method type. As mentioned above, a Method Value actually has a Function Type. A method type is a def declaration - everything about a def except its body.
Value Declarations and Definitions and Variable Declarations and Definitions are val and var declarations, including both type and value - which can be, respectively, Function Type and Anonymous Functions or Method Values. Note that, on the JVM, these (method values) are implemented with what Java calls "methods".
A Function Declaration is a def declaration, including type and body. The type part is the Method Type, and the body is an expression or a block. This is also implemented on the JVM with what Java calls "methods".
Finally, an Anonymous Function is an instance of a Function Type (ie, an instance of the trait FunctionN), and a Method Value is the same thing! The distinction is that a Method Value is created from methods, either by postfixing an underscore (m _ is a method value corresponding to the "function declaration" (def) m), or by a process called eta-expansion, which is like an automatic cast from method to function.
That is what the specs say, so let me put this up-front: we do not use that terminology! It leads to too much confusion between so-called "function declaration", which is a part of the program (chapter 4 -- basic declarations) and "anonymous function", which is an expression, and "function type", which is, well a type -- a trait.
The terminology below, and used by experienced Scala programmers, makes one change from the terminology of the specification: instead of saying function declaration, we say method. Or even method declaration. Furthermore, we note that value declarations and variable declarations are also methods for practical purposes.
So, given the above change in terminology, here's a practical explanation of the distinction.
A function is an object that includes one of the FunctionX traits, such as Function0, Function1, Function2, etc. It might be including PartialFunction as well, which actually extends Function1.
Let's see the type signature for one of these traits:
trait Function2[-T1, -T2, +R] extends AnyRef
This trait has one abstract method (it has a few concrete methods as well):
def apply(v1: T1, v2: T2): R
And that tell us all that there is to know about it. A function has an apply method which receives N parameters of types T1, T2, ..., TN, and returns something of type R. It is contra-variant on the parameters it receives, and co-variant on the result.
That variance means that a Function1[Seq[T], String] is a subtype of Function1[List[T], AnyRef]. Being a subtype means it can be used in place of it. One can easily see that if I'm going to call f(List(1, 2, 3)) and expect an AnyRef back, either of the two types above would work.
Now, what is the similarity of a method and a function? Well, if f is a function and m is a method local to the scope, then both can be called like this:
val o1 = f(List(1, 2, 3))
val o2 = m(List(1, 2, 3))
These calls are actually different, because the first one is just a syntactic sugar. Scala expands it to:
val o1 = f.apply(List(1, 2, 3))
Which, of course, is a method call on object f. Functions also have other syntactic sugars to its advantage: function literals (two of them, actually) and (T1, T2) => R type signatures. For example:
val f = (l: List[Int]) => l mkString ""
val g: (AnyVal) => String = {
case i: Int => "Int"
case d: Double => "Double"
case o => "Other"
}
Another similarity between a method and a function is that the former can be easily converted into the latter:
val f = m _
Scala will expand that, assuming m type is (List[Int])AnyRef into (Scala 2.7):
val f = new AnyRef with Function1[List[Int], AnyRef] {
def apply(x$1: List[Int]) = this.m(x$1)
}
On Scala 2.8, it actually uses an AbstractFunction1 class to reduce class sizes.
Notice that one can't convert the other way around -- from a function to a method.
Methods, however, have one big advantage (well, two -- they can be slightly faster): they can receive type parameters. For instance, while f above can necessarily specify the type of List it receives (List[Int] in the example), m can parameterize it:
def m[T](l: List[T]): String = l mkString ""
I think this pretty much covers everything, but I'll be happy to complement this with answers to any questions that may remain.
One big practical difference between a method and a function is what return means. return only ever returns from a method. For example:
scala> val f = () => { return "test" }
<console>:4: error: return outside method definition
val f = () => { return "test" }
^
Returning from a function defined in a method does a non-local return:
scala> def f: String = {
| val g = () => { return "test" }
| g()
| "not this"
| }
f: String
scala> f
res4: String = test
Whereas returning from a local method only returns from that method.
scala> def f2: String = {
| def g(): String = { return "test" }
| g()
| "is this"
| }
f2: String
scala> f2
res5: String = is this
function A function can be invoked with a list of arguments to produce a
result. A function has a parameter list, a body, and a result type.
Functions that are members of a class, trait, or singleton object are
called methods. Functions defined inside other functions are called
local functions. Functions with the result type of Unit are called procedures.
Anonymous functions in source code are called function literals.
At run time, function literals are instantiated into objects called
function values.
Programming in Scala Second Edition.
Martin Odersky - Lex Spoon - Bill Venners
Let Say you have a List
scala> val x =List.range(10,20)
x: List[Int] = List(10, 11, 12, 13, 14, 15, 16, 17, 18, 19)
Define a Method
scala> def m1(i:Int)=i+2
m1: (i: Int)Int
Define a Function
scala> (i:Int)=>i+2
res0: Int => Int = <function1>
scala> x.map((x)=>x+2)
res2: List[Int] = List(12, 13, 14, 15, 16, 17, 18, 19, 20, 21)
Method Accepting Argument
scala> m1(2)
res3: Int = 4
Defining Function with val
scala> val p =(i:Int)=>i+2
p: Int => Int = <function1>
Argument to function is Optional
scala> p(2)
res4: Int = 4
scala> p
res5: Int => Int = <function1>
Argument to Method is Mandatory
scala> m1
<console>:9: error: missing arguments for method m1;
follow this method with `_' if you want to treat it as a partially applied function
Check the following Tutorial that explains passing other differences with examples like other example of diff with Method Vs Function, Using function as Variables, creating function that returned function
Functions don't support parameter defaults. Methods do. Converting from a method to a function loses parameter defaults. (Scala 2.8.1)
There is a nice article here from which most of my descriptions are taken.
Just a short comparison of Functions and Methods regarding my understanding. Hope it helps:
Functions:
They are basically an object. More precisely, functions are objects with an apply method; Therefore, they are a little bit slower than methods because of their overhead. It is similar to static methods in the sense that they are independent of an object to be invoked.
A simple example of a function is just like bellow:
val f1 = (x: Int) => x + x
f1(2) // 4
The line above is nothing except assigning one object to another like object1 = object2. Actually the object2 in our example is an anonymous function and the left side gets the type of an object because of that. Therefore, now f1 is an object(Function). The anonymous function is actually an instance of Function1[Int, Int] that means a function with 1 parameter of type Int and return value of type Int.
Calling f1 without the arguments will give us the signature of the anonymous function (Int => Int = )
Methods:
They are not objects but assigned to an instance of a class,i.e., an object. Exactly the same as method in java or member functions in c++ (as Raffi Khatchadourian pointed out in a comment to this question) and etc.
A simple example of a method is just like bellow:
def m1(x: Int) = x + x
m1(2) // 4
The line above is not a simple value assignment but a definition of a method. When you invoke this method with the value 2 like the second line, the x is substituted with 2 and the result will be calculated and you get 4 as an output. Here you will get an error if just simply write m1 because it is method and need the input value. By using _ you can assign a method to a function like bellow:
val f2 = m1 _ // Int => Int = <function1>
Here is a great post by Rob Norris which explains the difference, here is a TL;DR
Methods in Scala are not values, but functions are. You can construct a function that delegates to a method via η-expansion (triggered by the trailing underscore thingy).
with the following definition:
a method is something defined with def and a value is something you can assign to a val
In a nutshell (extract from the blog):
When we define a method we see that we cannot assign it to a val.
scala> def add1(n: Int): Int = n + 1
add1: (n: Int)Int
scala> val f = add1
<console>:8: error: missing arguments for method add1;
follow this method with `_' if you want to treat it as a partially applied function
val f = add1
Note also the type of add1, which doesn’t look normal; you can’t declare a variable of type (n: Int)Int. Methods are not values.
However, by adding the η-expansion postfix operator (η is pronounced “eta”), we can turn the method into a function value. Note the type of f.
scala> val f = add1 _
f: Int => Int = <function1>
scala> f(3)
res0: Int = 4
The effect of _ is to perform the equivalent of the following: we construct a Function1 instance that delegates to our method.
scala> val g = new Function1[Int, Int] { def apply(n: Int): Int = add1(n) }
g: Int => Int = <function1>
scala> g(3)
res18: Int = 4
Practically, a Scala programmer only needs to know the following three rules to use functions and methods properly:
Methods defined by def and function literals defined by => are functions. It is defined in page 143, Chapter 8 in the book of Programming in Scala, 4th edition.
Function values are objects that can be passed around as any values. Function literals and partially applied functions are function values.
You can leave off the underscore of a partially applied function if a function value is required at a point in the code. For example: someNumber.foreach(println)
After four editions of Programming in Scala, it is still an issue for people to differentiate the two important concepts: function and function value because all editions don't give a clear explanation. The language specification is too complicated. I found the above rules are simple and accurate.
In Scala 2.13, unlike functions, methods can take/return
type parameters (polymorphic methods)
implicit parameters
dependent types
However, these restrictions are lifted in dotty (Scala 3) by Polymorphic function types #4672, for example, dotty version 0.23.0-RC1 enables the following syntax
Type parameters
def fmet[T](x: List[T]) = x.map(e => (e, e))
val ffun = [T] => (x: List[T]) => x.map(e => (e, e))
Implicit parameters (context parameters)
def gmet[T](implicit num: Numeric[T]): T = num.zero
val gfun: [T] => Numeric[T] ?=> T = [T] => (using num: Numeric[T]) => num.zero
Dependent types
class A { class B }
def hmet(a: A): a.B = new a.B
val hfun: (a: A) => a.B = hmet
For more examples, see tests/run/polymorphic-functions.scala
The difference is subtle but substantial and it is related to the type system in use (besides the nomenclature coming from Object Oriented or Functional paradigm).
When we talk about a function, we talk about the type Function: it being a type, an instance of it can be passed around as input or output to other functions (at least in the case of Scala).
When we talk about a method (of a class), we are actually talking about the type represented by the class it is part of: that is, the method is just a component of a larger type, and cannot be passed around by itself. It must be passed around with the instance of the type it is part of (i.e. the instance of the class).
A method belongs to an object (usually the class, trait or object in which you define it), whereas a function is by itself a value, and because in Scala every value is an object, therefore, a function is an object.
For example, given a method and a function below:
def timesTwoMethod(x :Int): Int = x * 2
def timesTwoFunction = (x: Int) => x * 2
The second def is an object of type Int => Int (the syntactic sugar for Function1[Int, Int]).
Scala made functions objects so they could be used as first-class entities. This way you can pass functions to other functions as arguments.
However, Scala can also treat methods as functions via a mechanism called Eta Expansion.
For example, the higher-order function map defined on List, receives another function f: A => B as its only parameter. The next two lines are equivalent:
List(1, 2, 3).map(timesTwoMethod)
List(1, 2, 3).map(timesTwoFunction)
When the compiler sees a def given in a place where a function is needed, it automatically converts the method into an equivalent function.
A method operates on an object but a function doesn't.
Scala and C++ has Fuction but in JAVA, you have to imitate them with static methods.
Method with ONLY implicit parameter
scala> def test1 (implicit i:Int )= Option(i)
test1: (implicit i: Int)Option[Int]
In trying to convert test1 into a function as shown below throws following error. I must be missing something obvious here?
scala> def test2(implicit i:Int) = test1 _
<console>:8: error: type mismatch;
found : Option[Int]
required: ? => ?
def test2(implicit i:Int) = test1 _
When using implicit parameter you have one in the scope. Like this:
object test{
implicit var i = 10
def fun(implicit i: Int) = println(i)
}
test.fun
And if you want to make an option isntance of something you should use Some()
Because you have an implicit Int in scope when defining test2, it's applied to test1, so you really end up with test1(i) _, which makes no sense to the compiler.
If it did compile, test2 would return the same function corresponding to test1 independent of the argument. If that's what you actually want, you can fix it by being more explicit: test1(_: Int) or { x: Int => test1(x) } instead of test1 _.
There are several different possible answers here depending on what it is exactly you are trying to achieve. If you meant test2 to be a behaviorally identical method to test1 then there is no need to use the underscore (and indeed you cannot!).
def test3(implicit i: Int) = test1(i)
If you meant test2 to be a behaviorally identical function to test1, then you need to do the following:
val test4 = test1(_: Int)
Note that I am using a val instead of a def here, because when using the underscore, I am turning test1 which was originally a method into an instance of a class (specifically one which extends Function2, i.e. a function). Also note that test4 no longer has implicit parameters as it is a function (and to the best of my knowledge functions cannot have implicit parameters) whereas test1 was a method.
Why you need to do this as opposed to just test1 _ turns out to be pretty complex...
TLDR: Scala is finnicky about the difference between foo(_) and foo _, methods are different from functions, and implicit resolution takes higher precedence over eta-expansion
Turning a method into a function object by way of an anonymous function in Scala is known as "eta-expansion." In general eta-expansion comes from the lambda calculus and refers to turning a term into its equivalent anonymous function (e.g. thing becomes x => thing(x)) or in the language of the lambda calculus, adding an abstraction over a term.
Note that without eta-expansion, programming in Scala would be absolutely torturous because methods are not functions. Therefore they cannot be directly passed as arguments to other methods or other functions. Scala tries to convert methods into functions via eta-expansion whenever possible, so as to give the appearance that you can pass methods to other methods.
So why doesn't the following work?
val test5 = test1 _ // error: could not find implicit value for parameter i: Int
Well let's see what would happen if we tried test4 without a type signature.
val test6 = test1(_) // error: missing parameter type for expanded function ((x$1) => test1(x$1))
Ah ha, different errors!
This is because test1(_) and test1 _ are subtly different things. test1(_) is partially applying the method test1 while test1 _ is a direction to perform eta-expansion on test1 until it is fully applied.
For example,
math.pow(_) // error: not enough arguments for method pow: (x: Double, y: Double)Double.
math.pow _ // this is fine
But what about the case where we have just one argument? What's the difference between partial application and eta-expansion of just one abstraction? Not really all that much. One way to view it is that eta-expansion is one way of implementing partial application. Indeed the Scala Spec seems to be silent on the difference between foo(_) and foo _ for a single parameter method. The only difference that matters for us is that the expansion that occurs in foo(_) always "binds" tighter than foo _, indeed it seems to bind as closely as method application does.
That's why test1(_) gives us an error about types. Partial application is treated analogously to normal method application. Because normal method application must always take place before implicit resolution, otherwise we could never replace an implicit value with our own value, partial application takes place before implicit resolution. It just so happens that the way Scala implements partial application is via eta-expansion and therefore we get the expansion into the anonymous function which then complains about the lack of a type for its argument.
My reading of Section 6.26 of the Scala Spec suggests that there is an ordering to the resolution of various conversions. In particular it seems to list resolving implicits as coming before eta-expansion. Indeed, for fully-applied eta-expansion, it would seem that this would necessarily be the case since Scala functions cannot have implicit parameters (only its methods can).
Hence, in the case of test5 as #Alexey says, when we are explicitly telling Scala to eta-expand test1 with test1 _, the implicit resolution takes place first, and then eta-expansion tries to take place, which fails because after implicit resolution Scala's typechecker realizes we have an Option not a method.
So that's why we need test1(_) over test1 _. The final type annotation test1(_: Int) is needed because Scala's type inference isn't robust enough to determine that after eta-expanding test1, the only possible type you can give to the anonymous function is the same as the type signature for the method. In fact, if we gave the type system enough hints, we can get away with test1(_).
val test7: Int => Option[Int] = test1(_) // this works
val test8: Int => Option[Int] = test1 _ // this still doesn't
I'm trying to understand the point of this language feature of multiple parameter clauses and why you would use it.
Eg, what's the difference between these two functions really?
class WTF {
def TwoParamClauses(x : Int)(y: Int) = x + y
def OneParamClause(x: Int, y : Int) = x + y
}
>> val underTest = new WTF
>> underTest.TwoParamClauses(1)(1) // result is '2'
>> underTest.OneParamClause(1,1) // result is '2'
There's something on this in the Scala specification at point 4.6. See if that makes any sense to you.
NB: the spec calls these 'parameter clauses', but I think some people may also call them 'parameter lists'.
Here are three practical uses of multiple parameter lists,
To aid type inference. This is especially useful when using higher order methods. Below, the type parameter A of g2 is inferred from the first parameter x, so the function arguments in the second parameter f can be elided,
def g1[A](x: A, f: A => A) = f(x)
g1(2, x => x) // error: missing parameter type for argument x
def g2[A](x: A)(f: A => A) = f(x)
g2(2) {x => x} // type is inferred; also, a nice syntax
For implicit parameters. Only the last parameter list can be marked implicit, and a single parameter list cannot mix implicit and non-implicit parameters. The definition of g3 below requires two parameter lists,
// analogous to a context bound: g3[A : Ordering](x: A)
def g3[A](x: A)(implicit ev: Ordering[A]) {}
To set default values based on previous parameters,
def g4(x: Int, y: Int = 2*x) {} // error: not found value x
def g5(x: Int)(y: Int = 2*x) {} // OK
TwoParamClause involves two method invocations while the OneParamClause invokes the function method only once. I think the term you are looking for is currying. Among the many use cases, it helps you to breakdown the computation into small steps. This answer may convince you of usefulness of currying.
There is a difference between both versions concerning type inference. Consider
def f[A](a:A, aa:A) = null
f("x",1)
//Null = null
Here, the type A is bound to Any, which is a super type of String and Int. But:
def g[A](a:A)(aa:A) = null
g("x")(1)
error: type mismatch;
found : Int(1)
required: java.lang.String
g("x")(1)
^
As you see, the type checker only considers the first argument list, so A gets bound to String, so the Int value for aa in the second argument list is a type error.
Multiple parameter lists can help scala type inference for more details see: Making the most of Scala's (extremely limited) type inference
Type information does not flow from left to right within an argument list, only from left to right across argument lists. So, even though Scala knows the types of the first two arguments ... that information does not flow to our anonymous function.
...
Now that our binary function is in a separate argument list, any type information from the previous argument lists is used to fill in the types for our function ... therefore we don't need to annotate our lambda's parameters.
There are some cases where this distinction matters:
Multiple parameter lists allow you to have things like TwoParamClauses(2); which is automatically-generated function of type Int => Int which adds 2 to its argument. Of course you can define the same thing yourself using OneParamClause as well, but it will take more keystrokes
If you have a function with implicit parameters which also has explicit parameters, implicit parameters must be all in their own parameter clause (this may seem as an arbitrary restriction but is actually quite sensible)
Other than that, I think, the difference is stylistic.