1 import scala.concurrent._  2  import scala.concurrent.duration._  3   import scalaz.stream.async.mutable._  4   import scala.concurrent.ExecutionContext.Implicits.global
 5   val sharedData: Topic[BigStringResult] = async.topic()  6        //> sharedData : scalaz.stream.async.mutable.Topic[demo.ws.blogStream.BigStringResult] = scalaz.stream.async.package$$anon$1@797badd3
 7   val subscriber = sharedData.subscribe.runLog    //> subscriber : scalaz.concurrent.Task[Vector[demo.ws.blogStream.BigStringResult]] = scalaz.concurrent.Task@226a82c4
 8   val otherThread = future {  9     subscriber.run // Added this here - now subscriber is really attached to the topic
10   }                //> otherThread : scala.concurrent.Future[Vector[demo.ws.blogStream.BigStringResult]] = List() 11   // Need to give subscriber some time to start up. 12   // I doubt you'd do this in actual code. 13 
14   // topics seem more useful for hooking up things like 15   // sensors that produce a continual stream of data, 16 
17   // and where individual values can be dropped on 18   // floor.
19   Thread.sleep(100) 20 
21   sharedData.publishOne(longGet(1)).run // don't just call publishOne; need to run the resulting task
22   sharedData.close.run // Don't just call close; need to run the resulting task 23 
24   // Need to wait for the output
25   val result = Await.result(otherThread, Duration.Inf) 26        //> result : Vector[demo.ws.blogStream.BigStringResult] = Vector(Some large data sets from job#1)