Can this be written as a single line?
assertThat(actualDeltas)
.filteredOn(delta -> delta instanceof Replacement)
.asInstanceOf(InstanceOfAssertFactories.list(Replacement.class))
I expected asInstanceOf to do the filtering. Alternatively, I searched for extractors or other concepts, but couldn't find any simple solution.
Is that possible with assertj?
By design, the purpose of asInstanceOf is only to provide type-narrowed assertions for cases where the type of the object under assertion is not visible at compile time.
When you provide InstanceOfAssertFactories.list(Replacement.class) as a parameter for asInstanceOf, you are telling AssertJ that you expect the object under assertion to be a List with elements of type Replacement.
While asInstanceOf will make sure that the object under test is a List, it will neither filter nor enforce that all the list elements are of type Replacement. The Replacement will ensure type-safety with subsequent methods that can be chained, for example with extracting(Function).
Currently, filteredOn(Predicate) or any other filteredOn variant is the right way to take out elements that should not be part of the assertion. If the filtering would happen outside (e.g., via Stream API), no asInstanceOf call would be needed as assertThat() could detect the proper element type based on the input declaration.
I'm trying to implement some sort of polymorphic cache when translating a source AST1 to a target AST2 (building a DSL compiler in scala). Since I wanted the cache to retain precise types for the translation results I had a go with shapeless HMap. It works as intended, however at some point I need to iterate on the cache contents to dump it to a file that must document the translation process, and would later be used to construct a backtranslation from A2 to A1. By looking at the source code of HMap I saw there is an underlying HashMap[Any, Any] that I cannot access since it is not a val in the HMap, and I saw that the HMap was in fact a Polymorphic function value, which means I can apply it over an HList which types correspond to a subset of the HMap key's types, but what I would really like to do is to be able to fold a polymorphic function which accepts polymorhic (key,value) arguments over this HMap to retrieve its contents in another form (for instance sliced in a tuple of standard HashMaps). Is there any way to do that?
Best.
As per my understanding, partial functions are functions that are defined for a subset of input values.
So should I use partial functions for DAO's. For example:
getUserById(userId: Long): User
There is always an input userId which does not exists in db. So can I say it is not defined. And lift it when I call this function.
If yes where do I stop. Should I use partial functions for all methods which are not defined, say for null.
PartialFunction is used when function is undefined for some elements of input data (input data may be Seq etc.)
For your case Option is better choice: it says that return data may be absent:
getUserById(userId:Long):Option[User]
I would avoid using partial functions at all, because scala makes it very easy to call a partial function as though it were a total function. Instead it's better to use a function that returns Option as #Sergey suggests; that way the "partial-ness" is always explicit.
Idiomatic scala does not use null so I wouldn't worry about methods which are not defined for null, but certainly it's worth returning Option for methods which are only defined for some of their possible input values. Better still, though, is to only accept suitable types as input. E.g. if you have a function that's only valid for non-empty lists, it should take (scalaz) NonEmptyList as input rather than List.
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.