object Source
- Source
- Source.scala
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def
actorPublisher[T](props: Props): Source[T, ActorRef]
Creates a
Source
that is materialized to an akka.actor.ActorRef which points to an Actor created according to the passed in akka.actor.Props.Creates a
Source
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 theprops
must be akka.stream.actor.ActorPublisher. -
def
actorRef[T](bufferSize: Int, overflowStrategy: OverflowStrategy): Source[T, ActorRef]
Creates a
Source
that is materialized as an akka.actor.ActorRef.Creates a
Source
that is materialized as an akka.actor.ActorRef. Messages sent to this actor will be emitted to the stream if there is demand from downstream, otherwise they will be buffered until request for demand is received.Depending on the defined akka.stream.OverflowStrategy it might drop elements if there is no space available in the buffer.
The strategy akka.stream.OverflowStrategy.backpressure is not supported, and an IllegalArgument("Backpressure overflowStrategy not supported") will be thrown if it is passed as argument.
The buffer can be disabled by using
bufferSize
of 0 and then received messages are dropped if there is no demand from downstream. WhenbufferSize
is 0 theoverflowStrategy
does not matter. An async boundary is added after this Source; as such, it is never safe to assume the downstream will always generate demand.The stream can be completed successfully by sending the actor reference a akka.actor.Status.Success (whose content will be ignored) in which case already buffered elements will be signaled before signaling completion, or by sending akka.actor.PoisonPill in which case completion will be signaled immediately.
The stream can be completed with failure by sending a akka.actor.Status.Failure to the actor reference. In case the Actor is still draining its internal buffer (after having received a akka.actor.Status.Success) before signaling completion and it receives a akka.actor.Status.Failure, the failure will be signaled downstream immediately (instead of the completion signal).
The actor will be stopped when the stream is completed, failed or canceled from downstream, i.e. you can watch it to get notified when that happens.
See also akka.stream.scaladsl.Source.queue.
- bufferSize
The size of the buffer in element count
- overflowStrategy
Strategy that is used when incoming elements cannot fit inside the buffer
-
def
apply[T](iterable: Iterable[T]): Source[T, NotUsed]
Helper to create Source from
Iterable
.Helper to create Source from
Iterable
. Example usage:Source(Seq(1,2,3))
Starts a new
Source
from the givenIterable
. This is like starting from an Iterator, but every Subscriber directly attached to the Publisher of this stream will see an individual flow of elements (always starting from the beginning) regardless of when they subscribed. -
def
asSubscriber[T]: Source[T, Subscriber[T]]
Creates a
Source
that is materialized as a org.reactivestreams.Subscriber -
def
combine[T, U](first: Source[T, _], second: Source[T, _], rest: Source[T, _]*)(strategy: (Int) ⇒ Graph[UniformFanInShape[T, U], NotUsed]): Source[U, NotUsed]
Combines several sources with fun-in strategy like
Merge
orConcat
and returnsSource
. -
def
cycle[T](f: () ⇒ Iterator[T]): Source[T, NotUsed]
Create Source that will continually produce given elements in specified order.
Create Source that will continually produce given elements in specified order.
Start a new 'cycled'
Source
from the given elements. The producer stream of elements will continue infinitely by repeating the sequence of elements provided by function parameter. -
def
empty[T]: Source[T, NotUsed]
A
Source
with no elements, i.e.A
Source
with no elements, i.e. an empty stream that is completed immediately for every connectedSink
. -
def
failed[T](cause: Throwable): Source[T, NotUsed]
Create a
Source
that immediately ends the stream with thecause
error to every connectedSink
. -
def
fromCompletionStage[T](future: CompletionStage[T]): Source[T, NotUsed]
Start a new
Source
from the givenFuture
.Start a new
Source
from the givenFuture
. The stream will consist of one element when theFuture
is completed with a successful value, which may happen before or after materializing theFlow
. The stream terminates with a failure if theFuture
is completed with a failure. -
def
fromFuture[T](future: Future[T]): Source[T, NotUsed]
Start a new
Source
from the givenFuture
.Start a new
Source
from the givenFuture
. The stream will consist of one element when theFuture
is completed with a successful value, which may happen before or after materializing theFlow
. The stream terminates with a failure if theFuture
is completed with a failure. -
def
fromGraph[T, M](g: Graph[SourceShape[T], M]): Source[T, M]
A graph with the shape of a source logically is a source, this method makes it so also in type.
-
def
fromIterator[T](f: () ⇒ Iterator[T]): Source[T, NotUsed]
Helper to create Source from
Iterator
.Helper to create Source from
Iterator
. Example usage:Source.fromIterator(() => Iterator.from(0))
Start a new
Source
from the given function that produces anIterator. The produced stream of elements will continue until the iterator runs empty or fails during evaluation of thenext()
method. Elements are pulled out of the iterator in accordance with the demand coming from the downstream transformation steps. -
def
fromPublisher[T](publisher: Publisher[T]): Source[T, NotUsed]
Helper to create Source from
Publisher
.Helper to create Source from
Publisher
.Construct a transformation starting with given publisher. The transformation steps are executed by a series of org.reactivestreams.Processor instances that mediate the flow of elements downstream and the propagation of back-pressure upstream.
-
def
lazily[T, M](create: () ⇒ Source[T, M]): Source[T, Future[M]]
Creates a
Source
that is not materialized until there is downstream demand, when the source gets materialized the materialized future is completed with its value, if downstream cancels or fails without any demand the create factory is never called and the materializedFuture
is failed. -
def
maybe[T]: Source[T, Promise[Option[T]]]
Create a
Source
which materializes a scala.concurrent.Promise which controls what element will be emitted by the Source.Create a
Source
which materializes a scala.concurrent.Promise which controls what element will be emitted by the Source. If the materialized promise is completed with a Some, that value will be produced downstream, followed by completion. If the materialized promise is completed with a None, no value will be produced downstream and completion will be signalled immediately. If the materialized promise is completed with a failure, then the returned source will terminate with that error. If the downstream of this source cancels before the promise has been completed, then the promise will be completed with None. -
def
queue[T](bufferSize: Int, overflowStrategy: OverflowStrategy): Source[T, SourceQueueWithComplete[T]]
Creates a
Source
that is materialized as an akka.stream.scaladsl.SourceQueue.Creates a
Source
that is materialized as an akka.stream.scaladsl.SourceQueue. You can push elements to the queue and they will be emitted to the stream if there is demand from downstream, otherwise they will be buffered until request for demand is received. Elements in the buffer will be discarded if downstream is terminated.Depending on the defined akka.stream.OverflowStrategy it might drop elements if there is no space available in the buffer.
Acknowledgement mechanism is available. akka.stream.scaladsl.SourceQueue.offer returns
Future[QueueOfferResult]
which completes withQueueOfferResult.Enqueued
if element was added to buffer or sent downstream. It completes withQueueOfferResult.Dropped
if element was dropped. Can also complete withQueueOfferResult.Failure
- when stream failed orQueueOfferResult.QueueClosed
when downstream is completed.The strategy akka.stream.OverflowStrategy.backpressure will not complete last
offer():Future
call when buffer is full.You can watch accessibility of stream with akka.stream.scaladsl.SourceQueue.watchCompletion. It returns future that completes with success when stream is completed or fail when stream is failed.
The buffer can be disabled by using
bufferSize
of 0 and then received message will wait for downstream demand unless there is another message waiting for downstream demand, in that case offer result will be completed according to the overflow strategy.SourceQueue that current source is materialized to is for single thread usage only.
- bufferSize
size of buffer in element count
- overflowStrategy
Strategy that is used when incoming elements cannot fit inside the buffer
-
def
repeat[T](element: T): Source[T, NotUsed]
Create a
Source
that will continually emit the given element. -
def
shape[T](name: String): SourceShape[T]
INTERNAL API
-
def
single[T](element: T): Source[T, NotUsed]
Create a
Source
with one element.Create a
Source
with one element. Every connectedSink
of this stream will see an individual stream consisting of one element. -
def
tick[T](initialDelay: FiniteDuration, interval: FiniteDuration, tick: T): Source[T, Cancellable]
Elements are emitted periodically with the specified interval.
Elements are emitted periodically with the specified interval. The tick element will be delivered to downstream consumers that has requested any elements. If a consumer has not requested any elements at the point in time when the tick element is produced it will not receive that tick element later. It will receive new tick elements as soon as it has requested more elements.
-
def
unfold[S, E](s: S)(f: (S) ⇒ Option[(S, E)]): Source[E, NotUsed]
Create a
Source
that will unfold a value of typeS
into a pair of the next stateS
and output elements of typeE
.Create a
Source
that will unfold a value of typeS
into a pair of the next stateS
and output elements of typeE
.For example, all the Fibonacci numbers under 10M:
Source.unfold(0 → 1) { case (a, _) if a > 10000000 ⇒ None case (a, b) ⇒ Some((b → (a + b)) → a) }
-
def
unfoldAsync[S, E](s: S)(f: (S) ⇒ Future[Option[(S, E)]]): Source[E, NotUsed]
Same as unfold, but uses an async function to generate the next state-element tuple.
Same as unfold, but uses an async function to generate the next state-element tuple.
async fibonacci example:
Source.unfoldAsync(0 → 1) { case (a, _) if a > 10000000 ⇒ Future.successful(None) case (a, b) ⇒ Future{ Thread.sleep(1000) Some((b → (a + b)) → a) } }
-
def
unfoldResource[T, S](create: () ⇒ S, read: (S) ⇒ Option[T], close: (S) ⇒ Unit): Source[T, NotUsed]
Start a new
Source
from some resource which can be opened, read and closed.Start a new
Source
from some resource which can be opened, read and closed. Interaction with resource happens in a blocking way.Example:
Source.unfoldResource( () => new BufferedReader(new FileReader("...")), reader => Option(reader.readLine()), reader => reader.close())
You can use the supervision strategy to handle exceptions for
read
function. All exceptions thrown bycreate
orclose
will fail the stream.Restart
supervision strategy will close and create blocking IO again. Default strategy isStop
which means that stream will be terminated on error inread
function by default.You can configure the default dispatcher for this Source by changing the
akka.stream.blocking-io-dispatcher
or set it for a given Source by using ActorAttributes.- create
- function that is called on stream start and creates/opens resource.
- read
- function that reads data from opened resource. It is called each time backpressure signal is received. Stream calls close and completes when
read
returns None.- close
- function that closes resource
-
def
unfoldResourceAsync[T, S](create: () ⇒ Future[S], read: (S) ⇒ Future[Option[T]], close: (S) ⇒ Future[Done]): Source[T, NotUsed]
Start a new
Source
from some resource which can be opened, read and closed.Start a new
Source
from some resource which can be opened, read and closed. It's similar tounfoldResource
but takes functions that returnFutures
instead of plain values.You can use the supervision strategy to handle exceptions for
read
function or failures of producedFutures
. All exceptions thrown bycreate
orclose
as well as fails of returned futures will fail the stream.Restart
supervision strategy will close and create resource. Default strategy isStop
which means that stream will be terminated on error inread
function (or future) by default.You can configure the default dispatcher for this Source by changing the
akka.stream.blocking-io-dispatcher
or set it for a given Source by using ActorAttributes.- create
- function that is called on stream start and creates/opens resource.
- read
- function that reads data from opened resource. It is called each time backpressure signal is received. Stream calls close and completes when
Future
from read function returns None.- close
- function that closes resource
-
def
zipN[T](sources: Seq[Source[T, _]]): Source[Seq[T], NotUsed]
Combine the elements of multiple streams into a stream of sequences.
- def zipWithN[T, O](zipper: (Seq[T]) ⇒ O)(sources: Seq[Source[T, _]]): Source[O, NotUsed]