case class ZipOp[A, B](a: Rx[A], b: Rx[B]) extends RxStream[(A, B)] with Product with Serializable
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def
andThen[B](f: ((A, B)) ⇒ Future[B])(implicit ex: ExecutionContext): RxStream[B]
Combine Rx stream and Future operators.
Combine Rx stream and Future operators.
This method is useful when you need to call RPC multiple times and chain the next operation after receiving the response.
Rx.intervalMillis(1000) .andThen { i => callRpc(...) } // Returns Future .map { (rpcReturnValue) => ... } // Use the Future response
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asInstanceOf[T0]: T0
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def
cache[A1 >: (A, B)]: RxStreamCache[A1]
Cache the last item, and emit the cached value if available.
Cache the last item, and emit the cached value if available.
The cached value will be preserved to the operator itself even after cancelling the subscription. Re-subscription of this operator will immediately return the cached value to the downstream operator.
This operator is useful if we need to involve time-consuming process, and want to reuse the last result:
val v = Rx.intervalMillis(1000).map(i => (heavy process)).cache v.map { x => ... }- Definition Classes
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concat[A1 >: (A, B)](other: Rx[A1]): RxStream[A1]
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debug(message: Any, cause: Throwable): Unit
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debug(message: Any): Unit
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eq(arg0: AnyRef): Boolean
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error(message: Any, cause: Throwable): Unit
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error(message: Any): Unit
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def
filter(f: ((A, B)) ⇒ Boolean): RxStream[(A, B)]
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flatMap[B](f: ((A, B)) ⇒ Rx[B]): RxStream[B]
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getClass(): Class[_]
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info(message: Any): Unit
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def
join[B, C, D](b: Rx[B], c: Rx[C], d: Rx[D]): RxStream[((A, B), B, C, D)]
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def
join[B, C](b: Rx[B], c: Rx[C]): RxStream[((A, B), B, C)]
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def
join[B](other: Rx[B]): RxStream[((A, B), B)]
Emit a new output if one of Rx[A] or Rx[B] is changed.
Emit a new output if one of Rx[A] or Rx[B] is changed.
This method is useful when you need to monitor multiple Rx objects.
Using joins will be more intuitive than nesting multiple Rx operators like Rx[A].map { x => ... Rx[B].map { ...} }.
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def
lastOption: RxOption[(A, B)]
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logAt(logLevel: LogLevel, message: Any): Unit
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lazy val
logger: Logger
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map[B](f: ((A, B)) ⇒ B): RxStream[B]
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ne(arg0: AnyRef): Boolean
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notify(): Unit
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notifyAll(): Unit
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def
recover[U](f: PartialFunction[Throwable, U]): RxStream[U]
Recover from a known error and emit a replacement value
Recover from a known error and emit a replacement value
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- Rx
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def
recoverWith[A](f: PartialFunction[Throwable, Rx[A]]): RxStream[A]
Recover from a known error and emit replacement values from a given Rx
Recover from a known error and emit replacement values from a given Rx
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def
run[U](effect: ((A, B)) ⇒ U): Cancelable
Evaluate this Rx[A] and apply the given effect function.
Evaluate this Rx[A] and apply the given effect function. Once OnError(e) or OnCompletion is observed, it will stop the evaluation.
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def
runContinuously[U](effect: ((A, B)) ⇒ U): Cancelable
Keep evaluating Rx[A] even if OnError(e) or OnCompletion is reported.
Keep evaluating Rx[A] even if OnError(e) or OnCompletion is reported. This is useful for keep processing streams.
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def
sample(timeWindow: Long, unit: TimeUnit = TimeUnit.MILLISECONDS): RxStream[(A, B)]
Emit the most recent item of the source within periodic time intervals.
Emit the most recent item of the source within periodic time intervals.
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def
startWith[A1 >: (A, B)](lst: Seq[A1]): RxStream[A1]
Emit the given items first before returning the items from the source.
Emit the given items first before returning the items from the source.
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- RxStream
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def
startWith[A1 >: (A, B)](a: A1): RxStream[A1]
Emit the given item first before returning the items from the source.
Emit the given item first before returning the items from the source.
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def
subscribe[U](subscriber: ((A, B)) ⇒ U): Cancelable
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def
synchronized[T0](arg0: ⇒ T0): T0
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def
take(n: Long): RxStream[(A, B)]
Take an event up to n elements.
Take an event up to n elements. This may receive fewer events than n if the upstream operator completes before generating n elements.
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- RxStream
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def
throttleFirst(timeWindow: Long, unit: TimeUnit = TimeUnit.MILLISECONDS): RxStream[(A, B)]
Emit the first item of the source within each sampling period.
Emit the first item of the source within each sampling period. For example, this is useful to prevent double-clicks of buttons.
- Definition Classes
- RxStream
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def
throttleLast(timeWindow: Long, unit: TimeUnit = TimeUnit.MILLISECONDS): RxStream[(A, B)]
Emit the most recent item of the source within periodic time intervals.
Emit the most recent item of the source within periodic time intervals.
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- RxStream
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def
toOption[X, A1 >: (A, B)](implicit ev: <:<[A1, Option[X]]): RxOption[X]
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- def toRxStream: RxStream[(A, B)]
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def
toSeq: Seq[(A, B)]
Materialize the stream as Seq[A].
Materialize the stream as Seq[A]. This works only for the finite stream and for Scala JVM.
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trace(message: Any, cause: Throwable): Unit
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trace(message: Any): Unit
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wait(arg0: Long, arg1: Int): Unit
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wait(arg0: Long): Unit
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warn(message: Any, cause: Throwable): Unit
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warn(message: Any): Unit
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def
withFilter(f: ((A, B)) ⇒ Boolean): RxStream[(A, B)]
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def
withName(name: String): RxStream[(A, B)]
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def
zip[B, C, D](b: Rx[B], c: Rx[C], d: Rx[D]): RxStream[((A, B), B, C, D)]
- Definition Classes
- RxStream
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def
zip[B, C](b: Rx[B], c: Rx[C]): RxStream[((A, B), B, C)]
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- RxStream
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def
zip[B](other: Rx[B]): RxStream[((A, B), B)]
Combine two Rx streams to form a sequence of pairs.
Combine two Rx streams to form a sequence of pairs. This will emit a new pair when both of the streams are updated.
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- RxStream
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