pekko/akka-stream/src/main/scala/akka/stream/javadsl/Sink.scala

/**
 * Copyright (C) 2015 Typesafe Inc. <http://www.typesafe.com>
 */
package akka.stream.javadsl

import akka.actor.{ ActorRef, Props }
import akka.japi.function
import akka.stream.impl.StreamLayout
import akka.stream.{ javadsl, scaladsl, _ }
import org.reactivestreams.{ Publisher, Subscriber }

import scala.concurrent.duration.FiniteDuration
import scala.concurrent.{ ExecutionContext, Future }
import scala.util.Try

/** Java API */
object Sink {
  /**
   * A `Sink` that will invoke the given function for every received element, giving it its previous
   * output (or the given `zero` value) and the element as input.
   * The returned [[scala.concurrent.Future]] will be completed with value of the final
   * function evaluation when the input stream ends, or completed with `Failure`
   * if there is a failure is signaled in the stream.
   */
  def fold[U, In](zero: U, f: function.Function2[U, In, U]): javadsl.Sink[In, Future[U]] =
    new Sink(scaladsl.Sink.fold[U, In](zero)(f.apply))

  /**
   * Helper to create [[Sink]] from `Subscriber`.
   */
  def create[In](subs: Subscriber[In]): Sink[In, Unit] =
    new Sink(scaladsl.Sink(subs))

  /**
   * A `Sink` that immediately cancels its upstream after materialization.
   */
  def cancelled[T](): Sink[T, Unit] =
    new Sink(scaladsl.Sink.cancelled)

  /**
   * A `Sink` that will consume the stream and discard the elements.
   */
  def ignore[T](): Sink[T, Future[Unit]] =
    new Sink(scaladsl.Sink.ignore)

  /**
   * A `Sink` that materializes into a [[org.reactivestreams.Publisher]].
   * that can handle `maxNumberOfSubscribers` [[org.reactivestreams.Subscriber]]s.
   *
   * If `maxNumberOfSubscribers` is greater than 1, the size of the `inputBuffer` configured for this stage
   * becomes the maximum number of elements that the fastest [[org.reactivestreams.Subscriber]] can be ahead
   * of the slowest one before slowing the processing down due to back pressure.
   */
  def publisher[In](maxNumberOfSubscribers: Int): Sink[In, Publisher[In]] =
    new Sink(scaladsl.Sink.publisher(maxNumberOfSubscribers))

  /**
   * A `Sink` that will invoke the given procedure for each received element. The sink is materialized
   * into a [[scala.concurrent.Future]] will be completed with `Success` when reaching the
   * normal end of the stream, or completed with `Failure` if there is a failure is signaled in
   * the stream..
   */
  def foreach[T](f: function.Procedure[T]): Sink[T, Future[Unit]] =
    new Sink(scaladsl.Sink.foreach(f.apply))

  /**
   * A `Sink` that will invoke the given procedure for each received element in parallel. The sink is materialized
   * into a [[scala.concurrent.Future]].
   *
   * If `f` throws an exception and the supervision decision is
   * [[akka.stream.Supervision.Stop]] the `Future` will be completed with failure.
   *
   * If `f` throws an exception and the supervision decision is
   * [[akka.stream.Supervision.Resume]] or [[akka.stream.Supervision.Restart]] the
   * element is dropped and the stream continues.
   */
  def foreachParallel[T](parallel: Int)(f: function.Procedure[T])(ec: ExecutionContext): Sink[T, Future[Unit]] =
    new Sink(scaladsl.Sink.foreachParallel(parallel)(f.apply)(ec))

  /**
   * A `Sink` that when the flow is completed, either through a failure or normal
   * completion, apply the provided function with [[scala.util.Success]]
   * or [[scala.util.Failure]].
   */
  def onComplete[In](callback: function.Procedure[Try[Unit]]): Sink[In, Unit] =
    new Sink(scaladsl.Sink.onComplete[In](x ⇒ callback.apply(x)))

  /**
   * A `Sink` that materializes into a `Future` of the first value received.
   */
  def head[In](): Sink[In, Future[In]] =
    new Sink(scaladsl.Sink.head[In])

  /**
   * Sends the elements of the stream to the given `ActorRef`.
   * If the target actor terminates the stream will be canceled.
   * When the stream is completed successfully the given `onCompleteMessage`
   * will be sent to the destination actor.
   * When the stream is completed with failure a [[akka.actor.Status.Failure]]
   * message will be sent to the destination actor.
   *
   * It will request at most `maxInputBufferSize` number of elements from
   * upstream, but there is no back-pressure signal from the destination actor,
   * i.e. if the actor is not consuming the messages fast enough the mailbox
   * of the actor will grow. For potentially slow consumer actors it is recommended
   * to use a bounded mailbox with zero `mailbox-push-timeout-time` or use a rate
   * limiting stage in front of this `Sink`.
   *
   */
  def actorRef[In](ref: ActorRef, onCompleteMessage: Any): Sink[In, Unit] =
    new Sink(scaladsl.Sink.actorRef[In](ref, onCompleteMessage))

  /**
   * Creates a `Sink` that is materialized to an [[akka.actor.ActorRef]] which points to an Actor
   * created according to the passed in [[akka.actor.Props]]. Actor created by the `props` should
   * be [[akka.stream.actor.ActorSubscriber]].
   */
  def actorSubscriber[T](props: Props): Sink[T, ActorRef] =
    new Sink(scaladsl.Sink.actorSubscriber(props))

  /**
   * A graph with the shape of a sink logically is a sink, this method makes
   * it so also in type.
   */
  def fromGraph[T, M](g: Graph[SinkShape[T], M]): Sink[T, M] =
    g match {
      case s: Sink[T, M] ⇒ s
      case other         ⇒ new Sink(scaladsl.Sink.fromGraph(other))
    }

  /**
   * Combine several sinks with fan-out strategy like `Broadcast` or `Balance` and returns `Sink`.
   */
  def combine[T, U](output1: Sink[U, _], output2: Sink[U, _], rest: java.util.List[Sink[U, _]], strategy: function.Function[java.lang.Integer, Graph[UniformFanOutShape[T, U], Unit]]): Sink[T, Unit] = {
    import scala.collection.JavaConverters._
    val seq = if (rest != null) rest.asScala.map(_.asScala) else Seq()
    new Sink(scaladsl.Sink.combine(output1.asScala, output2.asScala, seq: _*)(num ⇒ strategy.apply(num)))
  }

  /**
   * Creates a `Sink` that is materialized as an [[akka.stream.SinkQueue]].
   * [[akka.stream.SinkQueue.pull]] method is pulling element from the stream and returns ``Future[Option[T]]``.
   * `Future` completes when element is available.
   *
   * `Sink` will request at most `bufferSize` number of elements from
   * upstream and then stop back pressure.
   *
   * @param bufferSize The size of the buffer in element count
   * @param timeout Timeout for ``SinkQueue.pull():Future[Option[T] ]``
   */
  def queue[T](bufferSize: Int, timeout: FiniteDuration): Sink[T, SinkQueue[T]] =
    new Sink(scaladsl.Sink.queue(bufferSize, timeout))

}

/**
 * Java API
 *
 * A `Sink` is a set of stream processing steps that has one open input and an attached output.
 * Can be used as a `Subscriber`
 */
final class Sink[-In, +Mat](delegate: scaladsl.Sink[In, Mat]) extends Graph[SinkShape[In], Mat] {

  override def shape: SinkShape[In] = delegate.shape
  private[stream] def module: StreamLayout.Module = delegate.module

  /** Converts this Sink to its Scala DSL counterpart */
  def asScala: scaladsl.Sink[In, Mat] = delegate

  /**
   * Connect this `Sink` to a `Source` and run it.
   */
  def runWith[M](source: Graph[SourceShape[In], M], materializer: Materializer): M =
    asScala.runWith(source)(materializer)

  /**
   * Transform only the materialized value of this Sink, leaving all other properties as they were.
   */
  def mapMaterializedValue[Mat2](f: function.Function[Mat, Mat2]): Sink[In, Mat2] =
    new Sink(delegate.mapMaterializedValue(f.apply _))

  override def withAttributes(attr: Attributes): javadsl.Sink[In, Mat] =
    new Sink(delegate.withAttributes(attr))

  override def named(name: String): javadsl.Sink[In, Mat] =
    new Sink(delegate.named(name))
}