Let's consider a simple example of DAO pattern. Let Person is a value object and PersonDAO is the correspondent trait, which provides methods to store/retrieve Person to/from the database.trait PersonDAO {
def create(p:Person)
def find(id:Int)
def update(p:Person)
def delete(id:Int)
}
We use this pattern (as opposed to Active Record, for example), if we want to separate the business domain and persistence logic.
What if we use another approach instead ?
We will create PersonDatabaseAdaptertrait PersonDatabaseAdapter{
def create
def retrieve(id:Int)
def update
def delete
}
and implicit conversion from Person to it.
implicit def toDatabaseAdapter(person:Person) = new PersonDatabaseAdapter {
def create = ...
def retrieve(id:Int) = ...
def update = ...
def delete = ...
}
Now if we import these conversions, we can write client code to manipulate Persons and store/retrieve them to/from the database in the following manner:
val person1 = new Person
...
person1.create
...
val person2 = new Person
...
person2.retrieve(id)
...
This code looks like Active Record but the business domain and persistence are still separated.
Does it make sense ?
Well, I don't know anything about "obsolete" patters. Pattern is a pattern and you use it where appropriate. Also, I don't know if any pattern should be obsolete in a language unless language itself implements it with the same functionality.
Data access object is not obsolete to my knowledge:
http://java.sun.com/blueprints/corej2eepatterns/Patterns/DataAccessObject.html
http://en.wikipedia.org/wiki/Data_access_object
It seems to me that you are still using the DAO pattern. You have just implemented it differently.
I actually found this question because I was researching whether the DAO pattern is dead in plain ol' Java, given the power of Hibernate. It seems like the Hibernate Session is a generic implementation of a DAO, defining operations such as create, save, saveOrUpdate, and more.
In practice, I have seen little value in using the DAO pattern. When using Hibernate, the DAO interfaces and implementations are redundant wrappers around one-liner Hibernate Session idioms, e.g., getSession().update(...);
What you end up with is duplicate interfaces - a Service interface that redefines all of the methods in the DAO interface plus a few others implemented in terms of those.
It seems that Spring + Hibernate has reduced persistence logic almost to a triviality. Persistence technology portability is NOT needed in almost all applications. Hibernate already gives you database portability. Sure, DAOs would give you the ability to change from Hibernate to Toplink, but in practice, one would never do this. Persistence technologies are already leaky abstractions and applications are built to deal with this fact - such as loading a proxy for setting associations vs. performing a database hit - which necessarily couples them to the persistence technology. Being coupled to Hibernate is not really so bad though since it does its best to get out of the way (no checked exceptions a la JDBC and other nonsense).
In summary, I think that your Scala implementation of the DAO pattern is fine, though you could probably create a completely generic mixin that would give basic CRUD operations to any entity (most competent devs tend to implement a "generic DAO" base class in Java, too). Is that what Active Record does?
/end of random comments/
I believe your PersonDatabaseAdapter mutates Person in its retrieve(id: Int) method. So this pattern forces your domain objects to be mutable, while the Scala community seems to favor immutability due to the functional nature (or features) of the language.
Otherwise, I think the DAO pattern still has the same advantages and disadvantages (listed here) in Scala as it does in Java.
Nowadays I notice the Repository pattern to be quite popular especially as its terminology makes it look like you're dealing with collections.
Related
I have a CacheService class that uses an instance of the scala-redis library
class CacheService(redisClient: RedisClient) extend HealthCheck {
private val client = redisClient
override def health: Future[ServiceHealth] = {
client.info
...
}
In my unit test, I'm mocking the client instance and testing the service
class CacheServiceSpec extends AsyncFlatSpec with AsyncMockFactory {
val clientMock = mock[RedisClient]
val service = new CacheService(clientMock)
"A cache service" must "return a successful future when healthy" in {
(clientMock.info _).expects().returns(Option("blah"))
service.health map {
health => assert(health.status == ServiceStatus.Running)
}
}
}
yet I'm getting this compilation error
Error:(10, 24) method pipeline overrides nothing.
Note: the super classes of <$anon: com.redis.RedisClient> contain the following, non final members named pipeline:
def pipeline(f: PipelineClient => Any): Option[List[Any]]
val clientMock = mock[RedisClient]
My research so far indicates ScalaMock 4 is NOT capable of mocking companion objects. The author suggests refactoring the code with Dependency Injection.
Am I doing DI correctly (I chose constructor args injection since our codebase is still relatively small and straightforward)? Seems like the author is suggesting putting a wrapper over the client instance. If so, I'm looking for an idiomatic approach.
Should I bother with swapping out for another redis library? The libraries being actively maintained, per redis.io's suggestion, use companion objects as well. I personally think this is is not a problem of these libraries.
I'd appreciate any further recommendations. My goal here is to create a health check for our external services (redis, postgres database, emailing and more) that is at least testable. Criticism is welcomed since I'm still new to the Scala ecosystem.
Am I doing DI correctly (I chose constructor args injection since our
codebase is still relatively small and straightforward)? Seems like
the author is suggesting putting a wrapper over the client instance.
If so, I'm looking for an idiomatic approach.
Yes, you are right and this seems to be a known issue(link1). Ideally, there needs to a wrapper around the client instance. One approach could be to create a trait that has a method say connect and extend it to RedisCacheDao and implement the connect method to give you the client instance whenever you require. Then, all you have to do is to mock this connection interface and you will be able to test.
Another approach could be to use embedded redis for unit testing though usually, it is used for integration testing.You can start a simple redis server where the tests are running via code and close it once the testing is done.
Should I bother with swapping out for another redis library? The
libraries being actively maintained, per redis.io's suggestion, use
companion objects as well. I personally think this is is not a problem
of these libraries.
You can certainly do that. I would prefer Jedis as it is easy and it's performance is better than scala-redis(while performing mget).
Let me know if it helps!!
For me, I would use an implicit class under the following scenarios:
don't have access to the underlying type to be able to add the method I want.
the method I want doesn't make sense in a "global" sense.
i am splitting the functionality into another library of "extensions"
actually converting to a new type adds semantic/readability value (the new type actually means something)
However, I am fairly new to Scala (<6 months) and I'm noticing the developers around me are using implicit classes when it breaks the scenarios above. When I asked why, the answer was "because that's what I've always done".
So my question is, is there an official recommendation for when one should use an implicit class over a normal function added to the class definition? (I couldn't find anything here: https://docs.scala-lang.org/overviews/core/implicit-classes.html)
As per the SIP,
Motivation for the implicit class was that the popular extension method pattern, sometimes called the Pimp My Library pattern was used in Scala to extend pre-existing classes with new methods, fields, and interfaces.
There was also another common ‘extension’ use case known as type traits or type classes (see scala.math.Numeric). Type classes offered an alternative to pure inheritance hierarchies that was very similar to the extension method pattern.
The main drawback to both of these techniques was that they suffered the creation of an extra object at every invocation to gain the convenient syntax. This made these useful patterns unsuitable for use in performance-critical code. In these situations it was common to remove use of the pattern and resort to using an object with static helper methods.
And implicit class syntax was thus added to solve these issues.
The rock. They allow to make your own DSLs. Take a look to the Spray code, one of our classic and beloved projects:
trait TransformerPipelineSupport {
...
implicit class WithTransformation[A](value: A) {
def ~>[B](f: A ⇒ B): B = f(value)
}
...
}
The ~> allows to compose Spray directives... There are many more examples
Recently I read following SO question :
Is there any use cases for employing the Visitor Pattern in Scala?
Should I use Pattern Matching in Scala every time I would have used
the Visitor Pattern in Java?
The link to the question with title:
Visitor Pattern in Scala. The accepted answer begins with
Yes, you should probably start off with pattern matching instead of
the visitor pattern. See this
http://www.artima.com/scalazine/articles/pattern_matching.html
My question (inspired by above mentioned question) is which GOF Design pattern(s) has entirely different implementation in Scala? Where should I be careful and not follow java based programming model of Design Patterns (Gang of Four), if I am programming in Scala?
Creational patterns
Abstract Factory
Builder
Factory Method
Prototype
Singleton : Directly create an Object (scala)
Structural patterns
Adapter
Bridge
Composite
Decorator
Facade
Flyweight
Proxy
Behavioral patterns
Chain of responsibility
Command
Interpreter
Iterator
Mediator
Memento
Observer
State
Strategy
Template method
Visitor : Patten Matching (scala)
For almost all of these, there are Scala alternatives that cover some but not all of the use cases for these patterns. All of this is IMO, of course, but:
Creational Patterns
Builder
Scala can do this more elegantly with generic types than can Java, but the general idea is the same. In Scala, the pattern is most simply implemented as follows:
trait Status
trait Done extends Status
trait Need extends Status
case class Built(a: Int, b: String) {}
class Builder[A <: Status, B <: Status] private () {
private var built = Built(0,"")
def setA(a0: Int) = { built = built.copy(a = a0); this.asInstanceOf[Builder[Done,B]] }
def setB(b0: String) = { built = built.copy(b = b0); this.asInstanceOf[Builder[A,Done]] }
def result(implicit ev: Builder[A,B] <:< Builder[Done,Done]) = built
}
object Builder {
def apply() = new Builder[Need, Need]
}
(If you try this in the REPL, make sure that the class and object Builder are defined in the same block, i.e. use :paste.) The combination of checking types with <:<, generic type arguments, and the copy method of case classes make a very powerful combination.
Factory Method (and Abstract Factory Method)
Factory methods' main use is to keep your types straight; otherwise you may as well use constructors. With Scala's powerful type system, you don't need help keeping your types straight, so you may as well use the constructor or an apply method in the companion object to your class and create things that way. In the companion-object case in particular, it is no harder to keep that interface consistent than it is to keep the interface in the factory object consistent. Thus, most of the motivation for factory objects is gone.
Similarly, many cases of abstract factory methods can be replaced by having a companion object inherit from an appropriate trait.
Prototype
Of course overridden methods and the like have their place in Scala. However, the examples used for the Prototype pattern on the Design Patterns web site are rather inadvisable in Scala (or Java IMO). However, if you wish to have a superclass select actions based on its subclasses rather than letting them decide for themselves, you should use match rather than the clunky instanceof tests.
Singleton
Scala embraces these with object. They are singletons--use and enjoy!
Structural Patterns
Adapter
Scala's trait provides much more power here--rather than creating a class that implements an interface, for example, you can create a trait which implements only part of the interface, leaving the rest for you to define. For example, java.awt.event.MouseMotionListener requires you to fill in two methods:
def mouseDragged(me: java.awt.event.MouseEvent)
def mouseMoved(me: java.awt.event.MouseEvent)
Maybe you want to ignore dragging. Then you write a trait:
trait MouseMoveListener extends java.awt.event.MouseMotionListener {
def mouseDragged(me: java.awt.event.MouseEvent) {}
}
Now you can implement only mouseMoved when you inherit from this. So: similar pattern, but much more power with Scala.
Bridge
You can write bridges in Scala. It's a huge amount of boilerplate, though not quite as bad as in Java. I wouldn't recommend routinely using this as a method of abstraction; think about your interfaces carefully first. Keep in mind that with the increased power of traits that you can often use those to simplify a more elaborate interface in a place where otherwise you might be tempted to write a bridge.
In some cases, you may wish to write an interface transformer instead of the Java bridge pattern. For example, perhaps you want to treat drags and moves of the mouse using the same interface with only a boolean flag distinguishing them. Then you can
trait MouseMotioner extends java.awt.event.MouseMotionListener {
def mouseMotion(me: java.awt.event.MouseEvent, drag: Boolean): Unit
def mouseMoved(me: java.awt.event.MouseEvent) { mouseMotion(me, false) }
def mouseDragged(me: java.awt.event.MouseEvent) { mouseMotion(me, true) }
}
This lets you skip the majority of the bridge pattern boilerplate while accomplishing a high degree of implementation independence and still letting your classes obey the original interface (so you don't have to keep wrapping and unwrapping them).
Composite
The composite pattern is particularly easy to achieve with case classes, though making updates is rather arduous. It is equally valuable in Scala and Java.
Decorator
Decorators are awkward. You usually don't want to use the same methods on a different class in the case where inheritance isn't exactly what you want; what you really want is a different method on the same class which does what you want instead of the default thing. The enrich-my-library pattern is often a superior substitute.
Facade
Facade works better in Scala than in Java because you can have traits carry partial implementations around so you don't have to do all the work yourself when you combine them.
Flyweight
Although the flyweight idea is as valid in Scala as Java, you have a couple more tools at your disposal to implement it: lazy val, where a variable is not created unless it's actually needed (and thereafter is reused), and by-name parameters, where you only do the work required to create a function argument if the function actually uses that value. That said, in some cases the Java pattern stands unchanged.
Proxy
Works the same way in Scala as Java.
Behavioral Patterns
Chain of responsibility
In those cases where you can list the responsible parties in order, you can
xs.find(_.handleMessage(m))
assuming that everyone has a handleMessage method that returns true if the message was handled. If you want to mutate the message as it goes, use a fold instead.
Since it's easy to drop responsible parties into a Buffer of some sort, the elaborate framework used in Java solutions rarely has a place in Scala.
Command
This pattern is almost entirely superseded by functions. For example, instead of all of
public interface ChangeListener extends EventListener {
void stateChanged(ChangeEvent e)
}
...
void addChangeListener(ChangeListener listener) { ... }
you simply
def onChange(f: ChangeEvent => Unit)
Interpreter
Scala provides parser combinators which are dramatically more powerful than the simple interpreter suggested as a Design Pattern.
Iterator
Scala has Iterator built into its standard library. It is almost trivial to make your own class extend Iterator or Iterable; the latter is usually better since it makes reuse trivial. Definitely a good idea, but so straightforward I'd hardly call it a pattern.
Mediator
This works fine in Scala, but is generally useful for mutable data, and even mediators can fall afoul of race conditions and such if not used carefully. Instead, try when possible to have your related data all stored in one immutable collection, case class, or whatever, and when making an update that requires coordinated changes, change all things at the same time. This won't help you interface with javax.swing, but is otherwise widely applicable:
case class Entry(s: String, d: Double, notes: Option[String]) {}
def parse(s0: String, old: Entry) = {
try { old.copy(s = s0, d = s0.toDouble) }
catch { case e: Exception => old }
}
Save the mediator pattern for when you need to handle multiple different relationships (one mediator for each), or when you have mutable data.
Memento
lazy val is nearly ideal for many of the simplest applications of the memento pattern, e.g.
class OneRandom {
lazy val value = scala.util.Random.nextInt
}
val r = new OneRandom
r.value // Evaluated here
r.value // Same value returned again
You may wish to create a small class specifically for lazy evaluation:
class Lazily[A](a: => A) {
lazy val value = a
}
val r = Lazily(scala.util.Random.nextInt)
// not actually called until/unless we ask for r.value
Observer
This is a fragile pattern at best. Favor, whenever possible, either keeping immutable state (see Mediator), or using actors where one actor sends messages to all others regarding the state change, but where each actor can cope with being out of date.
State
This is equally useful in Scala, and is actually the favored way to create enumerations when applied to methodless traits:
sealed trait DayOfWeek
final trait Sunday extends DayOfWeek
...
final trait Saturday extends DayOfWeek
(often you'd want the weekdays to do something to justify this amount of boilerplate).
Strategy
This is almost entirely replaced by having methods take functions that implement a strategy, and providing functions to choose from.
def printElapsedTime(t: Long, rounding: Double => Long = math.round) {
println(rounding(t*0.001))
}
printElapsedTime(1700, math.floor) // Change strategy
Template Method
Traits offer so many more possibilities here that it's best to just consider them another pattern. You can fill in as much code as you can from as much information as you have at your level of abstraction. I wouldn't really want to call it the same thing.
Visitor
Between structural typing and implicit conversion, Scala has astoundingly more capability than Java's typical visitor pattern. There's no point using the original pattern; you'll just get distracted from the right way to do it. Many of the examples are really just wishing there was a function defined on the thing being visited, which Scala can do for you trivially (i.e. convert an arbitrary method to a function).
Ok, let's have a brief look at these patterns. I'm looking at all these patterns purely from a functional programming point of view, and leaving out many things that Scala can improve from an OO point of view. Rex Kerr answer provides an interesting counter-point to my own answers (I only read his answer after writing my own).
With that in mind, I'd like to say that it is important to study persistent data structures (functionally pure data structures) and monads. If you want to go deep, I think category theory basics are important -- category theory can formally describe all program structures, including imperative ones.
Creational Patterns
A constructor is nothing more than a function. A parameterless constructor for type T is nothing more than a function () => T, for example. In fact, Scala's syntactical sugar for functions is taken advantage on case classes:
case class T(x: Int)
That is equivalent to:
class T(val x: Int) { /* bunch of methods */ }
object T {
def apply(x: Int) = new T(x)
/* other stuff */
}
So that you can instantiate T with T(n) instead of new T(n). You could even write it like this:
object T extends Int => T {
def apply(x: Int) = new T(x)
/* other stuff */
}
Which turns T into a formal function, without changing any code.
This is the important point to keep in mind when thinking of creational patterns. So let's look at them:
Abstract Factory
This one is unlikely to change much. A class can be thought of as a group of closely related functions, so a group of closely related functions is easily implemented through a class, which is what this pattern does for constructors.
Builder
Builder patterns can be replaced by curried functions or partial function applications.
def makeCar: Size => Engine => Luxuries => Car = ???
def makeLargeCars = makeCar(Size.Large) _
def makeCar: (Size, Engine, Luxuries) => Car = ???
def makeLargeCars = makeCar(Size.Large, _: Engine, _: Luxuries)
Factory Method
Becomes obsolete if you discard subclassing.
Prototype
Doesn't change -- in fact, this is a common way of creating data in functional data structures. See case classes copy method, or all non-mutable methods on collections which return collections.
Singleton
Singletons are not particularly useful when your data is immutable, but Scala object implements this pattern is a safe manner.
Structural Patterns
This is mostly related to data structures, and the important point on functional programming is that the data structures are usually immutable. You'd be better off looking at persistent data structures, monads and related concepts than trying to translate these patterns.
Not that some patterns here are not relevant. I'm just saying that, as a general rule, you should look into the things above instead of trying to translate structural patterns into functional equivalents.
Adapter
This pattern is related to classes (nominal typing), so it remains important as long as you have that, and is irrelevant when you don't.
Bridge
Related to OO architecture, so the same as above.
Composite
Lot at Lenses and Zippers.
Decorator
A Decorator is just function composition. If you are decorating a whole class, that may not apply. But if you provide your functionality as functions, then composing a function while maintaining its type is a decorator.
Facade
Same comment as for Bridge.
Flyweight
If you think of constructors as functions, think of flyweight as function memoization. Also, Flyweight is intrinsic related to how persistent data structures are built, and benefits a lot from immutability.
Proxy
Same comment as for Adapter.
Behavioral Patterns
This is all over the place. Some of them are completely useless, while others are as relevant as always in a functional setting.
Chain of Responsibility
Like Decorator, this is function composition.
Command
This is a function. The undo part is not necessary if your data is immutable. Otherwise, just keep a pair of function and its reverse. See also Lenses.
Interpreter
This is a monad.
Iterator
It can be rendered obsolete by just passing a function to the collection. That's what Traversable does with foreach, in fact. Also, see Iteratee.
Mediator
Still relevant.
Memento
Useless with immutable objects. Also, its point is keeping encapsulation, which is not a major concern in FP.
Note that this pattern is not serialization, which is still relevant.
Observer
Relevant, but see Functional Reactive Programming.
State
This is a monad.
Strategy
A strategy is a function.
Template Method
This is an OO design pattern, so it's relevant for OO designs.
Visitor
A visitor is just a method receiving a function. In fact, that's what Traversable's foreach does.
In Scala, it can also be replaced with extractors.
I suppose, Command pattern not needed in functional languages at all. Instead of encapsulation command function inside object and then selecting appropriate object, just use appropriate function itself.
Flyweight is just cache, and has default implementation in most functional languages (memoize in clojure)
Even Template method, Strategy and State can be implemented with just passing appropriate function in method.
So, I recommend to not go deep in Design Patterns when you tries yourself in functional style but reading some books about functional concepts (high-order functions, laziness, currying, and so on)
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 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