And it's important to note with Scala, a big part of its complexity comes from the practical philosophy of its creators: purity is sacrificed in order to actually make it work on the JVM the way we want it to.

I used to work with Java on the server-side, but I'm programming almost entirely in Scala now (I'm at a small shop where I was lucky enough to convince the boss to let me give it a go on a project last year) and I've got to say that it's completely changed the way I think about and solve problems. I learned Haskell in university and I'm trying to learn more, but I don't see it ever being accepted in our office.

The Scala syntax does (especially when working with async programming / Futures) suffer from problems, like the nested callback problem that Javascript also has, but there is an elegant solution in the language... you just have to know how to use it. But on the other hand, it doesn't look like a completely foreign language to Java developers and it's not too hard to get our new hires productive with it.

How do you manage nesting from callbacks and matches and such? Inlining short functions like _ + _ is fine, but how do you organize more advanced operations?

(I'm just constantly looking for ways to make my scala code more accessible.)

I am indeed referring to for-comprehensions. Any time you have nested flatMap/maps you can replace it with a for, since that's all a for-comprehension really is...

  computation1.flatMap { result1 =>
    computation2.flatMap { result2 =>
      computation3.map { result3 =>
        result2 + result3
      }
    }
  }

Becomes...

  val foobar = for {
    result1 <- computation1
    result2 <- computation2(result1)
    result3 <- computation3(result2)
  } yield {
    result2 + result3
  }

Or, since I'm using the async Postgres module which returns Futures, to make them run in parallel you need to create the futures beforehand. I often have something like this...

  val fProject = Project.findById(projectId)
  val fTask = Task.findById(taskId)

  for {
    projectOption <- fProject

    taskOption <- fTask

    students <- projectOption match {
      case Some(project) => Student.findByProject(projectId)
      case None => Future.successful(IndexedSeq[Student]())
    }

    result <- (projectOption, taskOption) match {
      case (Some(project), Some(task)) => { 
        /* do something with project, task and students */ 
      }
      case (None, _) => Future.successful(NotFound(s"Project $projectId not found"))
      case (_, None) => Future.successful(NotFound(s"Task $taskId not found"))
    }
  }
  yield result

By creating the futures first, they both run in parallel and their results are 'collected' by the for comprehension. In the first example, the computations necessarily run in sequence.

I'm using Play framework, for me, these for comprehensions are usually found in my controllers and the final result is an HTTP result.

Passing along failure can still be tricky but I find this much more organized than nesting callbacks.

He's probably referring to for-comprehensions.

It's an obviously silly exaggeration: what, did MacLISP, Scheme or Standard ML not exist? It's not as if Erik Meijer has the excuse of never having heard of them...