in c++ , compiler used name mangaling is to differntiate the function that are overloaded.In C# how the function overloading is handled
The signature of the method is used (types and numbers of parameters) to distinguish the different overloads.
See this and this (rather dated, but still pretty accurate) articles on MSDN.
Before invoking the method, the compiler automatically finds out the best overloaded method matching the list of arguments type.
Related
I am learning Editor Script of Unity recently, and I come across a piece of code in Unity Manual like this:
EditorWindowTest window = (EditorWindowTest)EditorWindow.GetWindow(typeof(EditorWindowTest), true, "My Empty Window");
I don't know why bother casting the result with (EditorWindowTest) again since the type has been specified in the parameter field of GetWindow().
Thanks in advance :)
There are multiple overloads of the EditorWindow.GetWindow method.
The one used in your code snippet is one of the non-generic ones. It accepts a Type argument which it can use at runtime to create the right type of window. However, since it doesn't use generics, it's not possible to know the type of the window at compile time, so the method just returns an EditorWindow, as that's the best it can do.
You can hover over a method in your IDE to see the return type of any method for yourself.
When using one of the generic overloads of the GetWindow method, you don't need to do any manual casting, since the method already knows at compile time the exact type of the window and returns an instance of that type directly.
The generic variants should be used when possible, because it makes the code safer by removing the need for casting at runtime, which could cause exceptions.
If you closely look, GetWindow's return type is EditorWindow. Not the EditorWindowTest, so typecasting makes sense.
https://docs.unity3d.com/ScriptReference/EditorWindow.GetWindow.html
Is it possible in Matlab to say what the function expects? something like this:
function functionA( obj, uint8(param) )
Here I am saying that the function expects one parameter of type uint8.
Not on the function signature. Typically, you do this via an assert block:
function (obj, param)
assert(isa(param, 'uint8'),...
[mfilename ':invalid_datatype'],...
'Parameter ''param'' must be of class ''uint8''; received ''%s''.',...
class(param));
To complement Rody's answer, there are four ways that you can do this:
Use a conditional and raise an exception if the argument is not of the expected type. The problem with this method is that you have to write a lot of code.
Use an assertion. See Rody's answer or here. One can argue that this is not what assertions are supposed to be used for, but you can certainly use them this way.
Use the validateattributesfunction. See here. This is a very good balance between simplicity and utility. It allows you to check for a number of properties in an argument (and generally, any variable at any part of code)
Use the inputParser class. See here. This is the most powerful method of parsing inputs, but may be overkill. Also, the cost of creating an inputParser object means that it may not be a good idea for functions that are called repeatedly. Nevertheless, it's very good for the public API.
I'm trying to understand how the programming technique known as currying differs from an ordinary callback interface (such as the Observer/Observable interfaces in Java, or the classic Visitor design pattern).
I understand what currying is, I just don't understand why it's uniquely useful to the point that it requires its own terminology and language support.
Could someone explain a programming situation that is better solved by currying than by a callback method? What's the practical significance of the fact that currying uses a separate function for each argument?
[update:] to summarize the answers I got: currying comes part and parcel with the fact that functions are "first class" citizens, ie objects that can be created and passed around like any other object reference. This makes it possible to return a function from a function, in other words currying.
As for the reason why currying is useful, currying provides a syntax to let you concisely decorate function calls so that derived functions can be created with minimal boilerplate code overhead. Whereas in java you might create several overloaded or "wrapper" methods for each partial parameter set which ultimately invoke a master method containing all the parameters, currying provides a lighter syntax that lets you generate these "function wrappers" as needed in your code.
Currying and callbacks are two completely different technologies.
Callbacks are essentially a synonym for "passing a function to a function" (i.e. higher-order function that consumes a function); currying is a form of partial application, i.e. a function which isn't passed all of the parameters it expects returns a new function that only expects the free parameters.
Accordingly, they are not alternatives at all.
Currying is useful because it makes it much easier to concisely create functions that can be used as, for example, callbacks, or in a pointfree programme. It also means that you can, e.g. pass a callback to a function like map, and have a new function that applies your callback to every element of any list you care to pass to it.
Well, it's a point of language support.
In Java, for example, you can define all sorts of callback interfaces: one for parmeterless methods, one for methods with one argument, one for methods with two arguments, and so forth.
But wehn functions are first class citiziens, one does not need this: Single argument functions will do the job, because functions can be returned. Hence, one important interface in all "functional java" projects will be some interface of the form:
interface Fun<A,B> {
public B apply(A a);
}
or the like that covers this pattern.
I have been reading about methods and functions in Scala. Jim's post and Daniel's complement to it do a good job of explaining what the differences between these are. Here is what I took with me:
functions are objects, methods are not;
as a consequence functions can be passed as argument, but methods can not;
methods can be type-parametrised, functions can not;
methods are faster.
I also understand the difference between def, val and var.
Now I have actually two questions:
Why can't we parametrise the apply method of a function to parametrise the function? And
Why can't the method be called by the function object to run faster? Or the caller of the function be made calling the original method directly?
Looking forward to your answers and many thanks in advance!
1 - Parameterizing functions.
It is theoretically possible for a compiler to parameterize the type of a function; one could add that as a feature. It isn't entirely trivial, though, because functions are contravariant in their argument and covariant in their return value:
trait Function1[+T,-R] { ... }
which means that another function that can take more arguments counts as a subclass (since it can process anything that the superclass can process), and if it produces a smaller set of results, that's okay (since it will also obey the superclass construct that way). But how do you encode
def fn[A](a: A) = a
in that framework? The whole point is that the return type is equal to the type passed in, whatever that type has to be. You'd need
Function1[ ThisCanBeAnything, ThisHasToMatch ]
as your function type. "This can be anything" is well-represented by Any if you want a single type, but then you could return anything as the original type is lost. This isn't to say that there is no way to implement it, but it doesn't fit nicely into the existing framework.
2 - Speed of functions.
This is really simple: a function is the apply method on another object. You have to have that object in order to call its method. This will always be slower (or at least no faster) than calling your own method, since you already have yourself.
As a practical matter, JVMs can do a very good job inlining functions these days; there is often no difference in performance as long as you're mostly using your method or function, not creating the function object over and over. If you're deeply nesting very short loops, you may find yourself creating way too many functions; moving them out into vals outside of the nested loops may save time. But don't bother until you've benchmarked and know that there's a bottleneck there; typically the JVM does the right thing.
Think about the type signature of a function. It explicitly says what types it takes. So then type-parameterizing apply() would be inconsistent.
A function is an object, which must be created, initialized, and then garbage-collected. When apply() is called, it has to grab the function object in addition to the parent.
Some time ago Oracle decided that adding Closures to Java 8 would be an good idea. I wonder how design problems are solved there in comparison to Scala, which had closures since day one.
Citing the Open Issues from javac.info:
Can Method Handles be used for Function Types?
It isn't obvious how to make that work. One problem is that Method Handles reify type parameters, but in a way that interferes with function subtyping.
Can we get rid of the explicit declaration of "throws" type parameters?
The idea would be to use disjuntive type inference whenever the declared bound is a checked exception type. This is not strictly backward compatible, but it's unlikely to break real existing code. We probably can't get rid of "throws" in the type argument, however, due to syntactic ambiguity.
Disallow #Shared on old-style loop index variables
Handle interfaces like Comparator that define more than one method, all but one of which will be implemented by a method inherited from Object.
The definition of "interface with a single method" should count only methods that would not be implemented by a method in Object and should count multiple methods as one if implementing one of them would implement them all. Mainly, this requires a more precise specification of what it means for an interface to have only a single abstract method.
Specify mapping from function types to interfaces: names, parameters, etc.
We should fully specify the mapping from function types to system-generated interfaces precisely.
Type inference. The rules for type inference need to be augmented to accomodate the inference of exception type parameters. Similarly, the subtype relationships used by the closure conversion should be reflected as well.
Elided exception type parameters to help retrofit exception transparency.
Perhaps make elided exception type parameters mean the bound. This enables retrofitting existing generic interfaces that don't have a type parameter for the exception, such as java.util.concurrent.Callable, by adding a new generic exception parameter.
How are class literals for function types formed?
Is it #void().class ? If so, how does it work if object types are erased? Is it #?(?).class ?
The system class loader should dynamically generate function type interfaces.
The interfaces corresponding to function types should be generated on demand by the bootstrap class loader, so they can be shared among all user code. For the prototype, we may have javac generate these interfaces so prototype-generated code can run on stock (JDK5-6) VMs.
Must the evaluation of a lambda expression produce a fresh object each time?
Hopefully not. If a lambda captures no variables from an enclosing scope, for example, it can be allocated statically. Similarly, in other situations a lambda could be moved out of an inner loop if it doesn't capture any variables declared inside the loop. It would therefore be best if the specification promises nothing about the reference identity of the result of a lambda expression, so such optimizations can be done by the compiler.
As far as I understand 2., 6. and 7. aren't a problem in Scala, because Scala doesn't use Checked Exceptions as some sort of "Shadow type-system" like Java.
What about the rest?
1) Can Method Handles be used for Function Types?
Scala targets JDK 5 and 6 which don't have method handles, so it hasn't tried to deal with that issue yet.
2) Can we get rid of the explicit declaration of "throws" type parameters?
Scala doesn't have checked exceptions.
3) Disallow #Shared on old-style loop index variables.
Scala doesn't have loop index variables. Still, the same idea can be expressed with a certain kind of while loop . Scala's semantics are pretty standard here. Symbols bindings are captured and if the symbol happens to map to a mutable reference cell then on your own head be it.
4) Handle interfaces like Comparator that define more than one method all but one of which come from Object
Scala users tend to use functions (or implicit functions) to coerce functions of the right type to an interface. e.g.
[implicit] def toComparator[A](f : (A, A) => Int) = new Comparator[A] {
def compare(x : A, y : A) = f(x, y)
}
5) Specify mapping from function types to interfaces:
Scala's standard library includes FuncitonN traits for 0 <= N <= 22 and the spec says that function literals create instances of those traits
6) Type inference. The rules for type inference need to be augmented to accomodate the inference of exception type parameters.
Since Scala doesn't have checked exceptions it can punt on this whole issue
7) Elided exception type parameters to help retrofit exception transparency.
Same deal, no checked exceptions.
8) How are class literals for function types formed? Is it #void().class ? If so, how does it work if object types are erased? Is it #?(?).class ?
classOf[A => B] //or, equivalently,
classOf[Function1[A,B]]
Type erasure is type erasure. The above literals produce scala.lang.Function1 regardless of the choice for A and B. If you prefer, you can write
classOf[ _ => _ ] // or
classOf[Function1[ _,_ ]]
9) The system class loader should dynamically generate function type interfaces.
Scala arbitrarily limits the number of arguments to be at most 22 so that it doesn't have to generate the FunctionN classes dynamically.
10) Must the evaluation of a lambda expression produce a fresh object each time?
The Scala specification does not say that it must. But as of 2.8.1 the the compiler does not optimizes the case where a lambda does not capture anything from its environment. I haven't tested with 2.9.0 yet.
I'll address only number 4 here.
One of the things that distinguishes Java "closures" from closures found in other languages is that they can be used in place of interface that does not describe a function -- for example, Runnable. This is what is meant by SAM, Single Abstract Method.
Java does this because these interfaces abound in Java library, and they abound in Java library because Java was created without function types or closures. In their absence, every code that needed inversion of control had to resort to using a SAM interface.
For example, Arrays.sort takes a Comparator object that will perform comparison between members of the array to be sorted. By contrast, Scala can sort a List[A] by receiving a function (A, A) => Int, which is easily passed through a closure. See note 1 at the end, however.
So, because Scala's library was created for a language with function types and closures, there isn't need to support such a thing as SAM closures in Scala.
Of course, there's a question of Scala/Java interoperability -- while Scala's library might not need something like SAM, Java library does. There are two ways that can be solved. First, because Scala supports closures and function types, it is very easy to create helper methods. For example:
def runnable(f: () => Unit) = new Runnable {
def run() = f()
}
runnable { () => println("Hello") } // creates a Runnable
Actually, this particular example can be made even shorter by use of Scala's by-name parameters, but that's beside the point. Anyway, this is something that, arguably, Java could have done instead of what it is going to do. Given the prevalence of SAM interfaces, it is not all that surprising.
The other way Scala handles this is through implicit conversions. By just prepending implicit to the runnable method above, one creates a method that gets automatically (note 2) applied whenever a Runnable is required but a function () => Unit is provided.
Implicits are very unique, however, and still controversial to some extent.
Note 1: Actually, this particular example was choose with some malice... Comparator has two abstract methods instead of one, which is the whole problem with it. Since one of its methods can be implemented in terms of the other, I think they'll just "subtract" defender methods from the abstract list.
And, on the Scala side, even though there's a sort method that uses (A, A) => Boolean, not (A, A) => Int, the standard sorting method calls for a Ordering object, which is quite similar to Java's Comparator! In Scala's case, though, Ordering performs the role of a type class.
Note 2: Implicits are automatically applied, once they have been imported into scope.