I want to write an arch unit test to assert that a class extends AnyVal type.
val rule = classes().should().beAssignableTo(classOf[AnyVal])
val importedClasses = new ClassFileImporter().importPackages("a.b.c")
isAnyVal.check(importedClasses) // Always returns true
The above code doesn't actually catch anything and passes for classes that don't extend AnyVal also.
classOf[AnyVal] is java.lang.Object, so you are just asking that all classes extend Object, which they do.
From ArchUnit user guide:
It does so by analyzing given Java bytecode, importing all classes into a Java code structure.
I was hoping you'd get Class etc. and could go into Scala reflection from there, even if you wouldn't get the nice DSL, but they use their own API instead.
So to answer Scala-specific questions, it would need to parse #ScalaSignature annotations and that would probably be a very large effort for the developers (not to mention maintenance, or dependence on specific Scala version at least until Scala 3).
Related
Considering a simple use case to extract fields of an object in Java reflection:
val fields = this.getClass.getDeclaredFields
it may return incomplete information if generic type is used, but it is short, fast and can handle most cases.
In Scala reflection module (scala.reflect), it appears that such one-liner doesn't exist, the shortest code I know of that can successfully handle this case is:
trait Thing[T <: Thing[T]{
implicit ev: TypeTag[T]
scala.reflect.runtime.universe.typeOf[T].members
}
This uses a redundant F-bounded polymorphism and a TypeTag doesn't carry extra information comparing to a Java class, is there any way to make it shorter, at least as short as Java (which is a very verbose language)?
Thanks a lot for your advice
I'm not sure that in this specific case
this.getClass.getDeclaredFields
is much shorter than
def fields[T: TypeTag](t: T) = typeOf[T].decls
fields(this)
Anyway you can still use Java reflection in Scala.
Sometimes Scala reflection is more verbose than Java reflection but Scala reflection allows to do things (in Scala terms) that can't be done with Java reflection (for example if corresponding Scala concepts are absent in Java).
It's not true that
TypeTag doesn't carry extra information comparing to a Java class
Types and classes are different concepts. Maybe you meant ClassTags.
To use or not to use F-bounded polymorphism is your choice.
I have a quite puzzling question. I am playing with squeryl, and found when I used:
package models
import org.squeryl.{Schema, KeyedEntity}
object db extends Schema {
val userTable = table[User]("User")
on(userTable)(b => declare(
b.email is(unique,indexed("idxEmailAddresses"))
))
}
I had to import import org.squeryl.PrimitiveTypeMode._
But this does not make sense to me. Here is is defined in org.squeryl.dsl.NonNumericalExpression, but why do I have to include the seemingly irrelevant import org.squeryl.PrimitiveTypeMode._?
Thank you.
I agree with #sschaef that this is due to required implicit conversions. When APIs (like squeryl) decide to build a DSL (domain specific language) in order to get a slick looking way to code against their API, implicit conversions will be required. The core API probably takes certain types of objects that it might be cumbersome/ugly to be instantiating directly in the code. Thus, they will use implicit conversions to do some of the lifting for you and keep the DSL as clean as possible. If you check out the Scaladoc for the PrimitiveTypeMode object, you can see the many implicit defs that are defined on it. Implicit conversions (used in pimping libraries) will 'upconvert' from one type into another to gain access to more functionality on the pimped out class. When the code is the implicit things are explicitly included into the final compiled code.
http://squeryl.org/api/index.html#org.squeryl.PrimitiveTypeMode$
Also, I believe the implicit conversion you are looking for is:
import org.squeryl.PrimitiveTypeMode.string2ScalarString
which is inherited from org.squeryl.dsl.QueryDsl.
In groovy one can do:
class Foo {
Integer a,b
}
Map map = [a:1,b:2]
def foo = new Foo(map) // map expanded, object created
I understand that Scala is not in any sense of the word, Groovy, but am wondering if map expansion in this context is supported
Simplistically, I tried and failed with:
case class Foo(a:Int, b:Int)
val map = Map("a"-> 1, "b"-> 2)
Foo(map: _*) // no dice, always applied to first property
A related thread that shows possible solutions to the problem.
Now, from what I've been able to dig up, as of Scala 2.9.1 at least, reflection in regard to case classes is basically a no-op. The net effect then appears to be that one is forced into some form of manual object creation, which, given the power of Scala, is somewhat ironic.
I should mention that the use case involves the servlet request parameters map. Specifically, using Lift, Play, Spray, Scalatra, etc., I would like to take the sanitized params map (filtered via routing layer) and bind it to a target case class instance without needing to manually create the object, nor specify its types. This would require "reliable" reflection and implicits like "str2Date" to handle type conversion errors.
Perhaps in 2.10 with the new reflection library, implementing the above will be cake. Only 2 months into Scala, so just scratching the surface; I do not see any straightforward way to pull this off right now (for seasoned Scala developers, maybe doable)
Well, the good news is that Scala's Product interface, implemented by all case classes, actually doesn't make this very hard to do. I'm the author of a Scala serialization library called Salat that supplies some utilities for using pickled Scala signatures to get typed field information
https://github.com/novus/salat - check out some of the utilities in the salat-util package.
Actually, I think this is something that Salat should do - what a good idea.
Re: D.C. Sobral's point about the impossibility of verifying params at compile time - point taken, but in practice this should work at runtime just like deserializing anything else with no guarantees about structure, like JSON or a Mongo DBObject. Also, Salat has utilities to leverage default args where supplied.
This is not possible, because it is impossible to verify at compile time that all parameters were passed in that map.
I've noticed that the Scala standard library uses two different strategies for organizing classes, traits, and singleton objects.
Using packages whose members are them imported. This is, for example, how you get access to scala.collection.mutable.ListBuffer. This technique is familiar coming from Java, Python, etc.
Using type members of traits. This is, for example, how you get access to the Parser type. You first need to mix in scala.util.parsing.combinator.Parsers. This technique is not familiar coming from Java, Python, etc, and isn't much used in third-party libraries.
I guess one advantage of (2) is that it organizes both methods and types, but in light of Scala 2.8's package objects the same can be done using (1). Why have both these strategies? When should each be used?
The nomenclature of note here is path-dependent types. That's the option number 2 you talk of, and I'll speak only of it. Unless you happen to have a problem solved by it, you should always take option number 1.
What you miss is that the Parser class makes reference to things defined in the Parsers class. In fact, the Parser class itself depends on what input has been defined on Parsers:
abstract class Parser[+T] extends (Input => ParseResult[T])
The type Input is defined like this:
type Input = Reader[Elem]
And Elem is abstract. Consider, for instance, RegexParsers and TokenParsers. The former defines Elem as Char, while the latter defines it as Token. That means the Parser for the each is different. More importantly, because Parser is a subclass of Parsers, the Scala compiler will make sure at compile time you aren't passing the RegexParsers's Parser to TokenParsers or vice versa. As a matter of fact, you won't even be able to pass the Parser of one instance of RegexParsers to another instance of it.
The second is also known as the Cake pattern.
It has the benefit that the code inside the class that has a trait mixed in becomes independent of the particular implementation of the methods and types in that trait. It allows to use the members of the trait without knowing what's their concrete implementation.
trait Logging {
def log(msg: String)
}
trait App extends Logging {
log("My app started.")
}
Above, the Logging trait is the requirement for the App (requirements can also be expressed with self-types). Then, at some point in your application you can decide what the implementation will be and mix the implementation trait into the concrete class.
trait ConsoleLogging extends Logging {
def log(msg: String) = println(msg)
}
object MyApp extends App with ConsoleLogging
This has an advantage over imports, in the sense that the requirements of your piece of code aren't bound to the implementation defined by the import statement. Furthermore, it allows you to build and distribute an API which can be used in a different build somewhere else provided that its requirements are met by mixing in a concrete implementation.
However, there are a few things to be careful with when using this pattern.
All of the classes defined inside the trait will have a reference to the outer class. This can be an issue where performance is concerned, or when you're using serialization (when the outer class is not serializable, or worse, if it is, but you don't want it to be serialized).
If your 'module' gets really large, you will either have a very big trait and a very big source file, or will have to distribute the module trait code across several files. This can lead to some boilerplate.
It can force you to have to write your entire application using this paradigm. Before you know it, every class will have to have its requirements mixed in.
The concrete implementation must be known at compile time, unless you use some sort of hand-written delegation. You cannot mix in an implementation trait dynamically based on a value available at runtime.
I guess the library designers didn't regard any of the above as an issue where Parsers are concerned.
I just read and enjoyed the Cake pattern article. However, to my mind, one of the key reasons to use dependency injection is that you can vary the components being used by either an XML file or command-line arguments.
How is that aspect of DI handled with the Cake pattern? The examples I've seen all involve mixing traits in statically.
Since mixing in traits is done statically in Scala, if you want to vary the traits mixed in to an object, create different objects based on some condition.
Let's take a canonical cake pattern example. Your modules are defined as traits, and your application is constructed as a simple Object with a bunch of functionality mixed in
val application =
new Object
extends Communications
with Parsing
with Persistence
with Logging
with ProductionDataSource
application.startup
Now all of those modules have nice self-type declarations which define their inter-module dependencies, so that line only compiles if your all inter-module dependencies exist, are unique, and well-typed. In particular, the Persistence module has a self-type which says that anything implementing Persistence must also implement DataSource, an abstract module trait. Since ProductionDataSource inherits from DataSource, everything's great, and that application construction line compiles.
But what if you want to use a different DataSource, pointing at some local database for testing purposes? Assume further that you can't just reuse ProductionDataSource with different configuration parameters, loaded from some properties file. What you would do in that case is define a new trait TestDataSource which extends DataSource, and mix it in instead. You could even do so dynamically based on a command line flag.
val application = if (test)
new Object
extends Communications
with Parsing
with Persistence
with Logging
with TestDataSource
else
new Object
extends Communications
with Parsing
with Persistence
with Logging
with ProductionDataSource
application.startup
Now that looks a bit more verbose than we would like, particularly if your application needs to vary its construction on multiple axes. On the plus side, you usually you only have one chunk of conditional construction logic like that in an application (or at worst once per identifiable component lifecycle), so at least the pain is minimized and fenced off from the rest of your logic.
Scala is also a script language. So your configuration XML can be a Scala script. It is type-safe and not-a-different-language.
Simply look at startup:
scala -cp first.jar:second.jar startupScript.scala
is not so different than:
java -cp first.jar:second.jar com.example.MyMainClass context.xml
You can always use DI, but you have one more tool.
The short answer is that Scala doesn't currently have any built-in support for dynamic mixins.
I am working on the autoproxy-plugin to support this, although it's currently on hold until the 2.9 release, when the compiler will have new features making it a much easier task.
In the meantime, the best way to achieve almost exactly the same functionality is by implementing your dynamically added behavior as a wrapper class, then adding an implicit conversion back to the wrapped member.
Until the AutoProxy plugin becomes available, one way to achieve the effect is to use delegation:
trait Module {
def foo: Int
}
trait DelegatedModule extends Module {
var delegate: Module = _
def foo = delegate.foo
}
class Impl extends Module {
def foo = 1
}
// later
val composed: Module with ... with ... = new DelegatedModule with ... with ...
composed.delegate = choose() // choose is linear in the number of `Module` implementations
But beware, the downside of this is that it's more verbose, and you have to be careful about the initialization order if you use vars inside a trait. Another downside is that if there are path dependent types within Module above, you won't be able to use delegation that easily.
But if there is a large number of different implementations that can be varied, it will probably cost you less code than listing cases with all possible combinations.
Lift has something along those lines built in. It's mostly in scala code, but you have some runtime control. http://www.assembla.com/wiki/show/liftweb/Dependency_Injection