scala
21 09 2016
Yes, I know its a code smell. But I live in the real world, and sometimes you need to mock nested objects. This is a scenario like:
when(a.b.c.d).thenReturn(e)
The usual pattern here is to create a mock for each object and return the previous mock:
val a = mock[A]
val b = mock[B]
val c = mock[C]
val d = mock[D]
when(a.b).thenReturn(b)
when(b.c).thenReturn(c)
when(c.d).thenReturn(d)
But again, in the real world the signatures are longer, the types are nastier, and its never quite so clean. I figured I’d sit down and solve this for myself once and for all and came up with:
import org.junit.runner.RunWith
import org.mockito.Mockito
import org.scalatest.junit.JUnitRunner
import org.scalatest.{FlatSpec, Matchers}
@RunWith(classOf[JUnitRunner])
class Tests extends FlatSpec with Matchers {
"Mockito" should "proxy nested objects" in {
val parent = Mocks.mock[Parent]
Mockito.when(
parent.
mock(_.getChild1).
mock(_.getChild2).
mock(_.getChild3).
value.doWork()
).thenReturn(3)
parent.value.getChild1.getChild2.getChild3.doWork() shouldEqual 3
}
}
class Child3 {
def doWork(): Int = 0
… Read more
mockito, scala, testing
3 08 2016
I have a soft spot in me for AST’s ever since I went through the exercise of building my own language. Working in Java I missed the dynamic ability to get compile time information, though I knew it was available as part of the annotation processing pipleine during compilation (which is how lombok works). Scala has something similiar in the concept of macros: a way to hook into the compiler, manipulate or inspect the syntax tree, and rewrite or inject whatever you want. It’s a wonderfully elegant system that reminds me of Lisp/Clojure macros.
I ran into a situation (as always) where I really wanted to get the name of a function dynamically. i.e.
class Foo {
val field: String = ""
def method(): Unit = {}
}
val name: String = ??.field // = "field"
In .NET this is pretty easy since at runtime you can create an … Read more
ast, macro, scala
25 07 2016
Every time this hits me I have to think about it. The compiler barfs at you with something ambiguous like
[error] error: bad symbolic reference. the classpath might be incompatible with the version used when compiling Foo.class.
What this really is saying is that Foo.class references some import or class whose namespace isn’t on the classpath or has fields missing. I usually get this when I have a project level circular dependency via transitive includes. I.e.
Repo 1/
/project A
/project B -> depends on C and A
Repo 2
/project C -> depends on A
So here the dependency C pulls in a version of A but that version may not be the same that project B pulls in. If I do namespace refactoring in project A, then project B won’t compile if those namespaces are used by project C. It’s a mess.
Thankfully scala lets you maintain folder … Read more
dependencies, maven, scala
2 06 2016
Something that’s come up a few times in my career is the difficulty of validating if and when your code can handle actual DNS changes. A lot of times testing that you have the right JVM settings and that your 3rd party clients can handle it involves mucking with hosts files, nameservers, or stuff like Route53 and waiting around. Then its hard to automate and deterministically reproduce. However, you can hook into the DNS resolution in the JVM to control what gets resolved to what. And this way you can tweak the resolution in a test and see what breaks! I found some info at this blog post and cleaned it up a bit for usage in scala.
The magic sauce to pull this off is to make sure you override the default sun.net.spi.nameservice.NameServiceDescriptor. Internally in the InetAddress class it tries to load an instance of the interface NameServiceDescriptor… Read more
dns, java, scala
23 03 2016
I think consistent hashing is pretty fascinating. It lets you define a ring of machines that shard out data by a hash value. Imagine that your hash space is 0 -Int.Max, and you have 2 machines. Well one machine gets all values hashed from 0 -Int.Max/2 and the other from Int.Max/2 -Int.Max. Clever. This is one of the major algorithms of distributed systems like cassandra and dynamoDB.
For a good visualization, check out this blog post.
The fun stuff happens when you want to add replication and fault tolerance to your hashing. Now you need to have replicants and manage when machines join and add. When someone joins, you need to re-partition the space evenly and re-distribute the values that were previously held.
Something similar when you have a node leave, you need to make sure that whatever it was responsible for in its primray space … Read more
distributed, scala, toy
7 05 2015
Back in akka land! I’m using the ask pattern to get results back from actors since I have a requirement to block and get a result (I can’t wait for an actor to push at a later date). Thats fine, but converting from scala futures to java completable futures is a pain. I also, (like mentioned in another post) want to make sure that my async responses capture and set the MDC for proper logging.
My final usage should look something like:
private <Response, Request> Future<Response> askActorForResponseAsync(Request source) {
final FiniteDuration askTimeout = new FiniteDuration(config.getAskForResultTimeout().toMillis(), TimeUnit.MILLISECONDS);
final Timeout timeout = new Timeout(askTimeout);
final scala.concurrent.Future<Object> ask = Patterns.ask(master.getActor(), new PersistableMessageContext(source), timeout);
return FutureConverter.fromScalaFuture(ask)
.executeOn(actorSystem.dispatcher())
.thenApply(i -> (Response) i);
}
The idea is that I’m going to translate a scala future with a callback into a completable future java promise.
Next up, the future converter:
public class FutureConverter {
public static <T> … Read more
akka, async, futures, java, scala
11 03 2015
I’m working on a project where I need to multiplex many requests through a finite set of open sockets. For example, I have 200 messages, but I can only have at max 10 sockets open. To accomplish this I’ve wrapped the sockets in akka actors and am using an akka routing mechanism to “share” the 10 open sockets through a roundrobin queue.
This works out great, since now the consumers (who are rabbit mq listeners) just post messages to a facacde on the resource, and akka will route the request and do the appropriate work for me.
However, I wanted to know of a clean way to be able to add more resources (or remove them). Say at runtime I am asked to add 10 more open connections, or that suddenly we need to scale down to 5 connections. I’d like the router to be able to manage that for … Read more
akka, scala
4 02 2015
Previously I wrote about generating value type wrappers on top of C# primitives for better handling of domain level knowledge. This time I decided to try it out in scala as I’m jumping into the JVM world.
With scala we don’t have the value type capability that c# has, but we can sort of get there with implicits and case classes.
The simple gist is to generate stuff like
package com.devshorts.data
case class foo(data : String)
case class bar(data : String)
case class bizBaz(data : Int)
case class Data(data : java.util.UUID)
And the implicit conversions
package com.devshorts.data
object Conversions{
implicit def convertfoo(i : foo) : String = i.data
implicit def convertbar(i : bar) : String = i.data
implicit def convertbizBaz(i : bizBaz) : Int = i.data
implicit def convertData(i : Data) : java.util.UUID = i.data
}
Now you get a similar feel of primitive wrapping with function level unboxing and … Read more
scala
3 02 2015
I’m still toying around with the scala play! framework and I wanted to check out how I can make logging contextual information easy. In the past with .NET I’ve used and written libraries that wrap the current log provider and give you extra niceties with logging. One of my favorites was being able to do stuff like
var foo = "1";
var bar = "2";
logger.With(new { foo, bar }).Info("data")
Which would output a log line like
data, foo=1; bar=2
The logger’s “with” was even chainable so you could capture a previously built “with” context and re-use it. It was really nice when you want to create a baseline logging context for complex functions.
Java doesn’t have the concept of anonymous classes and I’m not sure you can do optimizations with reflection like you can with .NET (creating reflective based property invokers into delegates).
Either way, this makes for a … Read more
logging, scala
30 01 2015
It’s been a crazy year for me. For those who don’t know I moved from the east coast to the west coast to work for a rather large softare company in seattle (I’ll let you figure which one out) and after a few short weeks realized I made a horrible mistake and left the team. I then found a cool job at a smaller .net startup that was based in SF and met some awesome people and learned a lot. But, I’ve been poached by an old coworker and am now going to go work at a place that uses more open source things so I decided to kick into gear and investigate scala and play.
For the most part I’m doing a mental mapping of .NET’s web api framework to the scala play framework, but the more I play in play (pun intended) the more I like it.
On … Read more
dependency injection, guice, java, scala