final class RefCountObservable[+A] extends Observable[A]
A RefCountObservable
is an observable that wraps a
ConnectableObservable, initiating the connection on the first
subscribe()
and then staying connected as long as there is at least
one subscription active.
- Source
- RefCountObservable.scala
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- RefCountObservable
- Observable
- Serializable
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Value Members
- final def !=(arg0: Any): Boolean
- Definition Classes
- AnyRef → Any
- final def ##: Int
- Definition Classes
- AnyRef → Any
- final def ++[B >: A](other: => Observable[B]): Observable[B]
Concatenates the source with another observable.
Concatenates the source with another observable.
Ordering of subscription is preserved, so the second observable starts only after the source observable is completed successfully with an
onComplete
. On the other hand, the second observable is never subscribed if the source completes with an error.Visual Example
streamA: a1 -- -- a2 -- -- a3 -- a4 -- -- streamB: b1 -- -- b2 -- b3 -- -- -- -- b4 result: a1, a2, a3, a4, b1, b2, b3, b4
- Definition Classes
- Observable
- final def +:[B >: A](elem: B): Observable[B]
Alias for prepend.
Alias for prepend.
- Definition Classes
- Observable
- final def :+[B >: A](elem: B): Observable[B]
Alias for append.
Alias for append.
- Definition Classes
- Observable
- final def ==(arg0: Any): Boolean
- Definition Classes
- AnyRef → Any
- final def ambWith[B >: A](other: Observable[B]): Observable[B]
Given the source observable and another
Observable
, emits all of the items from the first of these Observables to emit an item and cancel the other.Given the source observable and another
Observable
, emits all of the items from the first of these Observables to emit an item and cancel the other.- Definition Classes
- Observable
- final def append[B >: A](elem: B): Observable[B]
Creates a new Observable that emits the events of the source and then it also emits the given element (appended to the stream).
Creates a new Observable that emits the events of the source and then it also emits the given element (appended to the stream).
- Definition Classes
- Observable
- final def appendAll[B >: A](other: Observable[B]): Observable[B]
A strict variant of ++.
A strict variant of ++.
- Definition Classes
- Observable
- final def asInstanceOf[T0]: T0
- Definition Classes
- Any
- final def asyncBoundary[B >: A](overflowStrategy: OverflowStrategy[B]): Observable[B]
Forces a buffered asynchronous boundary.
Forces a buffered asynchronous boundary. Asynchronous boundary refers to an independent processing of an upstream and a downstream - producer does not have to wait for consumer to acknowledge a new event.
Internally it wraps the observer implementation given to
onSubscribe
into a BufferedSubscriber.Normally Monix's implementation guarantees that events are not emitted concurrently, and that the publisher MUST NOT emit the next event without acknowledgement from the consumer that it may proceed, however for badly behaved publishers, this wrapper provides the guarantee that the downstream Observer given in
subscribe
will not receive concurrent events.WARNING: if the buffer created by this operator is unbounded, it can blow up the process if the data source is pushing events faster than what the observer can consume, as it introduces an asynchronous boundary that eliminates the back-pressure requirements of the data source. Unbounded is the default overflowStrategy, see OverflowStrategy for options.
Usage:
import monix.eval.Task import scala.concurrent.duration._ Observable("A", "B", "C", "D") .mapEval(i => Task { println(s"1: Processing $$i"); i ++ i }) .asyncBoundary(OverflowStrategy.Unbounded) .mapEval(i => Task { println(s"2: Processing $$i") }.delayExecution(100.millis)) // Without asyncBoundary it would process A, AA, B, BB, ... // 1: Processing A // 1: Processing B // 1: Processing C // 1: Processing D // 2: Processing AA // 2: Processing BB // 2: Processing CC // 2: Processing DD
- overflowStrategy
- the overflow strategy used for buffering, which specifies what to do in case we're dealing with a slow consumer - should an unbounded buffer be used, should back-pressure be applied, should the pipeline drop newer or older events, should it drop the whole buffer? See OverflowStrategy for more details.
- Definition Classes
- Observable
- final def behavior[B >: A](initialValue: B)(implicit s: Scheduler): ConnectableObservable[B]
Converts this observable into a multicast observable, useful for turning a cold observable into a hot one (i.e.
Converts this observable into a multicast observable, useful for turning a cold observable into a hot one (i.e. whose source is shared by all observers). The underlying subject used is a BehaviorSubject.
UNSAFE WARNING: this operation can trigger the execution of side effects, which breaks referential transparency and is thus not a pure function.
For FP code these functions shouldn't be called until "the end of the world", which is to say at the end of the program (for a console app), or at the end of a web request.
Otherwise for modifying or operating on streams, prefer its pure functions like publishSelector for sharing the data source, or map or flatMap for operating on its events. Or in case of specialized logic, prefer to suspend these side effects via Observable.suspend. Monix also provides Task which can also be used for suspending side effects and the
Task
was built to interop well withObservable
.- Definition Classes
- Observable
- Annotations
- @UnsafeBecauseImpure()
- final def bracket[B](use: (A) => Observable[B])(release: (A) => Task[Unit]): Observable[B]
Implementation of
bracket
fromcats.effect.Bracket
.Implementation of
bracket
fromcats.effect.Bracket
.See documentation.
- Definition Classes
- Observable
- final def bracketCase[B](use: (A) => Observable[B])(release: (A, ExitCase[Throwable]) => Task[Unit]): Observable[B]
Implementation of
bracketCase
fromcats.effect.Bracket
.Implementation of
bracketCase
fromcats.effect.Bracket
.See documentation.
- Definition Classes
- Observable
- final def bracketCaseF[F[_], B](use: (A) => Observable[B])(release: (A, ExitCase[Throwable]) => F[Unit])(implicit F: TaskLike[F]): Observable[B]
Version of bracketCase that can work with generic
F[_]
tasks, anything that's supported via monix.eval.TaskLike conversions.Version of bracketCase that can work with generic
F[_]
tasks, anything that's supported via monix.eval.TaskLike conversions.So in
release
you can work among others with:cats.effect.IO
monix.eval.Coeval
scala.concurrent.Future
- ...
- Definition Classes
- Observable
- final def bracketF[F[_], B](use: (A) => Observable[B])(release: (A) => F[Unit])(implicit F: TaskLike[F]): Observable[B]
Version of bracket that can work with generic
F[_]
tasks, anything that's supported via monix.eval.TaskLike conversions.Version of bracket that can work with generic
F[_]
tasks, anything that's supported via monix.eval.TaskLike conversions.So in
release
you can work among others with:cats.effect.IO
monix.eval.Coeval
scala.concurrent.Future
- ...
- Definition Classes
- Observable
- final def bufferIntrospective(maxSize: Int): Observable[List[A]]
Buffers signals while busy, after which it emits the buffered events as a single bundle.
Buffers signals while busy, after which it emits the buffered events as a single bundle.
This operator starts applying back-pressure when the underlying buffer's size is exceeded.
Usage:
import monix.eval.Task import scala.concurrent.duration._ Observable.range(1, 6) .doOnNext(l => Task(println(s"Started $$l"))) .bufferIntrospective(maxSize = 2) .doOnNext(l => Task(println(s"Emitted batch $$l"))) .mapEval(l => Task(println(s"Processed batch $$l")).delayExecution(500.millis)) // Started 1 // Emitted batch List(1) // Started 2 // Started 3 // Processed batch List(1) // Emitted batch List(2, 3) // Started 4 // Started 5 // Processed batch List(2, 3) // Emitted batch List(4, 5) // Processed batch List(4, 5)
- Definition Classes
- Observable
- final def bufferSliding(count: Int, skip: Int): Observable[Seq[A]]
Returns an observable that emits buffers of items it collects from the source observable.
Returns an observable that emits buffers of items it collects from the source observable. The resulting observable emits buffers every
skip
items, each containingcount
items.If the source observable completes, then the current buffer gets signaled downstream. If the source triggers an error then the current buffer is being dropped and the error gets propagated immediately.
For
count
andskip
there are 3 possibilities:- in case
skip == count
, then there are no items dropped and no overlap, the call being equivalent tobufferTumbling(count)
- in case
skip < count
, then overlap between buffers happens, with the number of elements being repeated beingcount - skip
- in case
skip > count
, thenskip - count
elements start getting dropped between windows
Usage:
// Emits [2, 3], [5, 6] Observable.range(2, 7) .bufferSliding(count = 2, skip = 3)
// Emits [2, 3, 4], [4, 5, 6] Observable.range(2, 7) .bufferSliding(count = 3, skip = 2)
- count
the maximum size of each buffer before it should be emitted
- skip
how many items emitted by the source observable should be skipped before starting a new buffer. Note that when skip and count are equal, this is the same operation as
bufferTumbling(count)
- Definition Classes
- Observable
- in case
- final def bufferTimed(timespan: FiniteDuration): Observable[Seq[A]]
Periodically gather items emitted by an observable into bundles and emit these bundles rather than emitting the items one at a time.
Periodically gather items emitted by an observable into bundles and emit these bundles rather than emitting the items one at a time.
This version of
buffer
emits a new bundle of items periodically, every timespan amount of time, containing all items emitted by the source Observable since the previous bundle emission.If the source observable completes, then the current buffer gets signaled downstream. If the source triggers an error then the current buffer is being dropped and the error gets propagated immediately.
- timespan
the interval of time at which it should emit the buffered bundle
- Definition Classes
- Observable
- final def bufferTimedAndCounted(timespan: FiniteDuration, maxCount: Int): Observable[Seq[A]]
Periodically gather items emitted by an observable into bundles and emit these bundles rather than emitting the items one at a time.
Periodically gather items emitted by an observable into bundles and emit these bundles rather than emitting the items one at a time.
The resulting observable emits connected, non-overlapping buffers, each of a fixed duration specified by the
timespan
argument or a maximum size specified by themaxCount
argument (whichever is reached first).If the source observable completes, then the current buffer gets signaled downstream. If the source triggers an error then the current buffer is being dropped and the error gets propagated immediately.
- timespan
the interval of time at which it should emit the buffered bundle
- maxCount
is the maximum bundle size, after which the buffered bundle gets forcefully emitted
- Definition Classes
- Observable
- final def bufferTimedWithPressure[AA >: A](period: FiniteDuration, maxSize: Int, sizeOf: (AA) => Int = (_: AA) => 1): Observable[Seq[AA]]
Periodically gather items emitted by an observable into bundles and emit these bundles rather than emitting the items one at a time.
Periodically gather items emitted by an observable into bundles and emit these bundles rather than emitting the items one at a time. Back-pressure the source when the buffer is full.
The resulting observable emits connected, non-overlapping buffers, each of a fixed duration specified by the
period
argument.The bundles are emitted at a fixed rate. If the source is silent, then the resulting observable will start emitting empty sequences.
If the source observable completes, then the current buffer gets signaled downstream. If the source triggers an error then the current buffer is being dropped and the error gets propagated immediately.
A
maxSize
argument is specified as the capacity of the bundle. In case the source is too fast andmaxSize
is reached, then the source will be back-pressured.A
sizeOf
argument is specified as the weight each element represents in the bundle. Defaults to count each element as weighting 1.The difference with bufferTimedAndCounted is that bufferTimedWithPressure applies back-pressure from the time when the buffer is full until the buffer is emitted, whereas bufferTimedAndCounted will forcefully emit the buffer when it's full.
- period
the interval of time at which it should emit the buffered bundle
- maxSize
is the maximum buffer size, after which the source starts being back-pressured
- sizeOf
is the function to compute the weight of each element in the buffer
- Definition Classes
- Observable
- final def bufferTumbling(count: Int): Observable[Seq[A]]
Periodically gather items emitted by an observable into bundles and emit these bundles rather than emitting the items one at a time.
Periodically gather items emitted by an observable into bundles and emit these bundles rather than emitting the items one at a time. This version of
buffer
is emitting items once the internal buffer has reached the given count.If the source observable completes, then the current buffer gets signaled downstream. If the source triggers an error then the current buffer is being dropped and the error gets propagated immediately.
Usage:
// Emits [2, 3], [4, 5], [6] Observable.range(2, 7) .bufferTumbling(count = 2)
- count
the maximum size of each buffer before it should be emitted
- Definition Classes
- Observable
- final def bufferWhile(p: (A) => Boolean): Observable[Seq[A]]
Buffers elements while predicate returns true, after which it emits the buffered events as a single bundle and creates a new buffer.
Buffers elements while predicate returns true, after which it emits the buffered events as a single bundle and creates a new buffer.
Usage:
import monix.eval.Task Observable(1, 1, 1, 2, 2, 1, 3) .bufferWhile(_ == 1) .doOnNext(l => Task(println(s"Emitted batch $$l"))) // Emitted batch List(1, 1, 1) // Emitted batch List(2) // Emitted batch List(2, 1) // Emitted batch List(3)
- Definition Classes
- Observable
- See also
bufferWhileInclusive for a similar operator that includes the value that caused
predicate
to returnfalse
- final def bufferWhileInclusive(p: (A) => Boolean): Observable[Seq[A]]
Buffers elements while predicate returns true, after which it emits the buffered events as a single bundle, including the value that caused
predicate
to returnfalse
and creates a new buffer.Buffers elements while predicate returns true, after which it emits the buffered events as a single bundle, including the value that caused
predicate
to returnfalse
and creates a new buffer.Usage:
import monix.eval.Task Observable(1, 1, 1, 2, 2, 1, 3) .bufferWhileInclusive(_ == 1) .doOnNext(l => Task(println(s"Emitted batch $$l"))) // Emitted batch List(1, 1, 1, 2) // Emitted batch List(2) // Emitted batch List(1, 3)
- Definition Classes
- Observable
- See also
bufferWhile for a similar operator that does not include the value that caused
predicate
to returnfalse
- final def bufferWithSelector[S](selector: Observable[S], maxSize: Int): Observable[Seq[A]]
Periodically gather items emitted by an observable into bundles and emit these bundles rather than emitting the items one at a time, whenever the
selector
observable signals an event.Periodically gather items emitted by an observable into bundles and emit these bundles rather than emitting the items one at a time, whenever the
selector
observable signals an event.The resulting observable collects the elements of the source in a buffer and emits that buffer whenever the given
selector
observable emits anonNext
event, when the buffer is emitted as a sequence downstream and then reset. Thus the resulting observable emits connected, non-overlapping bundles triggered by the givenselector
.If
selector
terminates with anonComplete
, then the resulting observable also terminates normally. Ifselector
terminates with anonError
, then the resulting observable also terminates with an error.If the source observable completes, then the current buffer gets signaled downstream. If the source triggers an error then the current buffer is being dropped and the error gets propagated immediately.
A
maxSize
argument is specified as the capacity of the bundle. In case the source is too fast andmaxSize
is reached, then the source will be back-pressured.- selector
is the observable that triggers the signaling of the current buffer
- maxSize
is the maximum bundle size, after which the source starts being back-pressured
- Definition Classes
- Observable
- final def bufferWithSelector[S](selector: Observable[S]): Observable[Seq[A]]
Periodically gather items emitted by an observable into bundles and emit these bundles rather than emitting the items one at a time, whenever the
selector
observable signals an event.Periodically gather items emitted by an observable into bundles and emit these bundles rather than emitting the items one at a time, whenever the
selector
observable signals an event.The resulting observable collects the elements of the source in a buffer and emits that buffer whenever the given
selector
observable emits anonNext
event, when the buffer is emitted as a sequence downstream and then reset. Thus the resulting observable emits connected, non-overlapping bundles triggered by the givenselector
.If
selector
terminates with anonComplete
, then the resulting observable also terminates normally. Ifselector
terminates with anonError
, then the resulting observable also terminates with an error.If the source observable completes, then the current buffer gets signaled downstream. If the source triggers an error then the current buffer is being dropped and the error gets propagated immediately.
- selector
is the observable that triggers the signaling of the current buffer
- Definition Classes
- Observable
- final def cache(maxCapacity: Int): Observable[A]
Caches the emissions from the source Observable and replays them in order to any subsequent Subscribers.
Caches the emissions from the source Observable and replays them in order to any subsequent Subscribers. This operator has similar behavior to replay except that this auto-subscribes to the source Observable rather than returning a ConnectableObservable for which you must call connect to activate the subscription.
When you call cache, it does not yet subscribe to the source Observable and so does not yet begin caching items. This only happens when the first Subscriber calls the resulting Observable's
subscribe
method.UNSAFE WARNING: this operation can trigger the execution of side effects, which breaks referential transparency and is thus not a pure function.
For FP code these functions shouldn't be called until "the end of the world", which is to say at the end of the program (for a console app), or at the end of a web request.
Otherwise for modifying or operating on streams, prefer its pure functions like publishSelector for sharing the data source, or map or flatMap for operating on its events. Or in case of specialized logic, prefer to suspend these side effects via Observable.suspend. Monix also provides Task which can also be used for suspending side effects and the
Task
was built to interop well withObservable
.- maxCapacity
is the maximum buffer size after which old events start being dropped (according to what happens when using ReplaySubject.createLimited)
- returns
an Observable that, when first subscribed to, caches all of its items and notifications for the benefit of subsequent subscribers
- Definition Classes
- Observable
- Annotations
- @UnsafeBecauseImpure()
- final def cache: Observable[A]
Caches the emissions from the source Observable and replays them in order to any subsequent Subscribers.
Caches the emissions from the source Observable and replays them in order to any subsequent Subscribers. This operator has similar behavior to replay except that this auto-subscribes to the source Observable rather than returning a ConnectableObservable for which you must call connect to activate the subscription.
When you call cache, it does not yet subscribe to the source Observable and so does not yet begin caching items. This only happens when the first Subscriber calls the resulting Observable's
subscribe
method.Note: You sacrifice the ability to cancel the origin when you use the cache operator so be careful not to use this on Observables that emit an infinite or very large number of items that will use up memory.
UNSAFE WARNING: this operation can trigger the execution of side effects, which breaks referential transparency and is thus not a pure function.
For FP code these functions shouldn't be called until "the end of the world", which is to say at the end of the program (for a console app), or at the end of a web request.
Otherwise for modifying or operating on streams, prefer its pure functions like publishSelector for sharing the data source, or map or flatMap for operating on its events. Or in case of specialized logic, prefer to suspend these side effects via Observable.suspend. Monix also provides Task which can also be used for suspending side effects and the
Task
was built to interop well withObservable
.- returns
an Observable that, when first subscribed to, caches all of its items and notifications for the benefit of subsequent subscribers
- Definition Classes
- Observable
- Annotations
- @UnsafeBecauseImpure()
- def clone(): AnyRef
- Attributes
- protected[lang]
- Definition Classes
- AnyRef
- Annotations
- @throws(classOf[java.lang.CloneNotSupportedException]) @native() @HotSpotIntrinsicCandidate()
- final def collect[B](pf: PartialFunction[A, B]): Observable[B]
Applies the given partial function to the source for each element for which the given partial function is defined.
Applies the given partial function to the source for each element for which the given partial function is defined.
- pf
the function that filters and maps the source
- returns
an observable that emits the transformed items by the given partial function
- Definition Classes
- Observable
- final def collectWhile[B](pf: PartialFunction[A, B]): Observable[B]
Takes longest prefix of elements that satisfy the given partial function and returns a new Observable that emits those elements.
Takes longest prefix of elements that satisfy the given partial function and returns a new Observable that emits those elements.
- pf
the function that filters and maps the source
- returns
an observable that emits the transformed items by the given partial function until it is contained in the function's domain
- Definition Classes
- Observable
- final def combineLatest[B](other: Observable[B]): Observable[(A, B)]
Creates a new observable from the source and another given observable, by emitting elements combined in pairs.
Creates a new observable from the source and another given observable, by emitting elements combined in pairs.
It emits an item whenever any of the source Observables emits an item (so long as each of the source Observables has emitted at least one item).
Visual Example
stream1: 1 - - 2 - - 3 - 4 - - stream2: 1 - - 2 - 3 - - - - 4 result: (1, 1), (2, 2), (2, 3), (3, 3), (4, 3), (4, 4)
See zip for an alternative that pairs the items in strict sequence.
- other
is an observable that gets paired with the source
- Definition Classes
- Observable
- final def combineLatestMap[B, R](other: Observable[B])(f: (A, B) => R): Observable[R]
Creates a new observable from the source and another given observable, by emitting elements combined in pairs.
Creates a new observable from the source and another given observable, by emitting elements combined in pairs.
It emits an item whenever any of the source Observables emits an item (so long as each of the source Observables has emitted at least one item).
Visual Example
stream1: 1 - - 2 - - 3 - 4 - - stream2: 1 - - 2 - 3 - - - - 4 result: (1, 1), (2, 2), (2, 3), (3, 3), (4, 3), (4, 4)
See zipMap for an alternative that pairs the items in strict sequence.
- other
is an observable that gets paired with the source
- f
is a mapping function over the generated pairs
- Definition Classes
- Observable
- final def completed: Observable[Nothing]
Ignores all items emitted by the source Observable and only calls onCompleted or onError.
Ignores all items emitted by the source Observable and only calls onCompleted or onError.
- returns
an empty Observable that only calls onCompleted or onError, based on which one is called by the source Observable
- Definition Classes
- Observable
- final def completedF[F[_]](implicit F: TaskLift[F]): F[Unit]
Polymorphic version of completedL that can work with generic
F[_]
tasks, anything that's supported via monix.eval.TaskLift conversions.Polymorphic version of completedL that can work with generic
F[_]
tasks, anything that's supported via monix.eval.TaskLift conversions.So you can work among others with:
cats.effect.IO
monix.eval.Coeval
scala.concurrent.Future
- ...
- Definition Classes
- Observable
- final def completedL: Task[Unit]
Creates a new Task that will consume the source observable and upon completion of the source it will complete with
Unit
.Creates a new Task that will consume the source observable and upon completion of the source it will complete with
Unit
.- Definition Classes
- Observable
- final def concat[B](implicit ev: <:<[A, Observable[B]]): Observable[B]
Concatenates the sequence of observables emitted by the source into one observable, without any transformation.
Concatenates the sequence of observables emitted by the source into one observable, without any transformation.
You can combine the items emitted by multiple observables so that they act like a single sequence by using this operator.
This operation is the "monadic bind", implementing the
flatMap
operation of cats.Monad.Concat vs Merge
The difference between the concat operation and merge is that
concat
cares about the ordering of sequences (e.g. all items emitted by the first observable in the sequence will come before the elements emitted by the second observable), whereasmerge
doesn't care about that (elements get emitted as they come). Because of back-pressure applied to observables,concat
is safe to use in all contexts, whereasmerge
requires buffering. Or in other wordsconcat
has deterministic, lawful behavior (being the "monadic bind"), whereasmerge
has non-deterministic behavior.Equivalence with concatMap
The
concat
operation is basicallyconcatMap
with the identity function, as you can count on this equivalence:stream.concat <-> stream.concatMap(x => x)
Visual Example
streamA: a1 -- -- a2 -- -- a3 -- a4 -- -- streamB: b1 -- -- b2 -- b3 -- -- -- -- b4 result: a1, a2, a3, a4, b1, b2, b3, b4
- returns
an observable that emits the merged events of all streams created by the source
- Definition Classes
- Observable
- final def concatDelayErrors[B](implicit ev: <:<[A, Observable[B]]): Observable[B]
Version of concat that delays errors emitted by child observables until the stream completes.
Version of concat that delays errors emitted by child observables until the stream completes.
Delaying Errors
This version is reserving
onError
notifications until all of the observables complete and only then passing the issued errors(s) downstream. Note that the streamed error is a CompositeException, since multiple errors from multiple streams can happen.Example
val dummy1 = new RuntimeException("dummy1") val dummy2 = new RuntimeException("dummy2") val stream = Observable( Observable(1).endWithError(dummy1), Observable.raiseError(dummy2), Observable(2, 3) ) val concatenated = stream.concatDelayErrors
The resulting stream in this example emits
1, 2, 3
in order and then completes with aCompositeException
of bothdummy1
anddummy2
.- returns
an observable that emits the merged events of all streams created by the source
- Definition Classes
- Observable
- final def concatMap[B](f: (A) => Observable[B]): Observable[B]
Applies a function that you supply to each item emitted by the source observable, where that function returns observables, and then concatenating those resulting sequences and emitting the results of this concatenation.
Applies a function that you supply to each item emitted by the source observable, where that function returns observables, and then concatenating those resulting sequences and emitting the results of this concatenation.
This implements the lawful "monadic bind", the
flatMap
operation of cats.Monad.Example
Observable(1, 2, 3).concatMap { x => for { _ <- Observable.eval(println(s"Processing $$x")) x <- Observable(x, x) } yield x }
Concat vs Merge
The difference between the concat operation and merge is that
concat
cares about the ordering of sequences (e.g. all items emitted by the first observable in the sequence will come before the elements emitted by the second observable), whereasmerge
doesn't care about that (elements get emitted as they come). Because of back-pressure applied to observables,concat
is safe to use in all contexts, whereasmerge
requires buffering. Or in other wordsconcat
has deterministic, lawful behavior (being the "monadic bind"), whereasmerge
has non-deterministic behavior.- f
is a generator for the streams being concatenated
- returns
an observable that emits the merged events of all streams created by the source
- Definition Classes
- Observable
- final def concatMapDelayErrors[B](f: (A) => Observable[B]): Observable[B]
Applies a function that you supply to each item emitted by the source observable, where that function returns sequences and then concatenating those resulting sequences and emitting the results of this concatenation.
Applies a function that you supply to each item emitted by the source observable, where that function returns sequences and then concatenating those resulting sequences and emitting the results of this concatenation.
Delaying Errors
This version is reserving
onError
notifications until all of the observables complete and only then passing the issued errors(s) downstream. Note that the streamed error is a CompositeException, since multiple errors from multiple streams can happen.Example
val dummy1 = new RuntimeException("dummy1") val dummy2 = new RuntimeException("dummy2") Observable(1, 2, 3).concatMapDelayErrors { case 1 => Observable(1).endWithError(dummy1) case 2 => Observable.raiseError(dummy2) case x => Observable(x, x) }
The resulting stream in this example emits
1, 3, 3
in order and then completes with aCompositeException
of bothdummy1
anddummy2
.- f
is a generator for the streams being concatenated
- returns
an observable that emits the merged events of all streams created by the source
- Definition Classes
- Observable
- final def concatMapIterable[B](f: (A) => Iterable[B]): Observable[B]
Applies a function that you supply to each item emitted by the source observable, where that function returns a sequence of elements, and then concatenating those resulting sequences and emitting the results of this concatenation.
Applies a function that you supply to each item emitted by the source observable, where that function returns a sequence of elements, and then concatenating those resulting sequences and emitting the results of this concatenation.
Example
Observable(1, 2, 3).concatMapIterable( x => List(x, x * 10, x * 100))
Visual Example
stream: 1 -- -- 2 -- -- 3 -- -- result: 1, 10, 100, 2, 20, 200, 3, 30, 300
- f
is a generator for the sequences being concatenated
- Definition Classes
- Observable
- final def consumeWith[R](f: Consumer[A, R]): Task[R]
On execution, consumes the source observable with the given Consumer, effectively transforming the source observable into a Task.
On execution, consumes the source observable with the given Consumer, effectively transforming the source observable into a Task.
- Definition Classes
- Observable
- final def consumeWithF[F[_], R](f: Consumer[A, R])(implicit F: TaskLift[F]): F[R]
Polymorphic version consumeWith that can work with generic
F[_]
tasks, anything that's supported via monix.eval.TaskLift conversions.Polymorphic version consumeWith that can work with generic
F[_]
tasks, anything that's supported via monix.eval.TaskLift conversions.So you can work among others with:
cats.effect.IO
monix.eval.Coeval
scala.concurrent.Future
- ...
- Definition Classes
- Observable
- final def count: Observable[Long]
Creates a new Observable that emits the total number of
onNext
events that were emitted by the source.Creates a new Observable that emits the total number of
onNext
events that were emitted by the source.Note that this Observable emits only one item after the source is complete. And in case the source emits an error, then only that error will be emitted.
- Definition Classes
- Observable
- final def countL: Task[Long]
Creates a task that emits the total number of
onNext
events that were emitted by the source.Creates a task that emits the total number of
onNext
events that were emitted by the source.- Definition Classes
- Observable
- final def debounce(timeout: FiniteDuration): Observable[A]
Only emit an item from an observable if a particular timespan has passed without it emitting another item.
Only emit an item from an observable if a particular timespan has passed without it emitting another item.
Note: If the source observable keeps emitting items more frequently than the length of the time window, then no items will be emitted by the resulting observable.
Usage:
import scala.concurrent.duration._ (Observable("M", "O", "N", "I", "X") ++ Observable.never) .delayOnNext(100.millis) .scan("")(_ ++ _) .debounce(200.millis) .dump("O") // Output: // 0: O --> MONIX
- timeout
the length of the window of time that must pass after the emission of an item from the source observable in which that observable emits no items in order for the item to be emitted by the resulting observable
- Definition Classes
- Observable
- See also
echoOnce for a similar operator that also mirrors the source observable
- final def debounceRepeated(period: FiniteDuration): Observable[A]
Emits the last item from the source Observable if a particular timespan has passed without it emitting another item, and keeps emitting that item at regular intervals until the source breaks the silence.
Emits the last item from the source Observable if a particular timespan has passed without it emitting another item, and keeps emitting that item at regular intervals until the source breaks the silence.
So compared to regular debounceTo this version keeps emitting the last item of the source.
Note: If the source Observable keeps emitting items more frequently than the length of the time window then no items will be emitted by the resulting Observable.
- period
the length of the window of time that must pass after the emission of an item from the source Observable in which that Observable emits no items in order for the item to be emitted by the resulting Observable at regular intervals, also determined by period
- Definition Classes
- Observable
- See also
echoRepeated for a similar operator that also mirrors the source observable
- final def debounceTo[B](timeout: FiniteDuration, f: (A) => Observable[B]): Observable[B]
Doesn't emit anything until a
timeout
period passes without the source emitting anything.Doesn't emit anything until a
timeout
period passes without the source emitting anything. When that timeout happens, we subscribe to the observable generated by the given function, an observable that will keep emitting until the source will break the silence by emitting another event.Note: If the source observable keeps emitting items more frequently than the length of the time window, then no items will be emitted by the resulting Observable.
- timeout
the length of the window of time that must pass after the emission of an item from the source Observable in which that Observable emits no items in order for the item to be emitted by the resulting Observable
- f
is a function that receives the last element generated by the source, generating an observable to be subscribed when the source is timing out
- Definition Classes
- Observable
- final def defaultIfEmpty[B >: A](default: => B): Observable[B]
Emit items from the source, or emit a default item if the source completes after emitting no items.
Emit items from the source, or emit a default item if the source completes after emitting no items.
- Definition Classes
- Observable
- final def delayExecution(timespan: FiniteDuration): Observable[A]
Hold an Observer's subscription request for a specified amount of time before passing it on to the source Observable.
Hold an Observer's subscription request for a specified amount of time before passing it on to the source Observable.
- timespan
is the time to wait before the subscription is being initiated.
- Definition Classes
- Observable
- final def delayExecutionWith[B](trigger: Observable[B]): Observable[A]
Hold an Observer's subscription request until the given
trigger
observable either emits an item or completes, before passing it on to the source Observable.Hold an Observer's subscription request until the given
trigger
observable either emits an item or completes, before passing it on to the source Observable.If the given
trigger
completes in error, then the subscription is terminated withonError
.- trigger
the observable that must either emit an item or complete in order for the source to be subscribed.
- Definition Classes
- Observable
- final def delayExecutionWithF[F[_], B](trigger: F[B])(implicit F: ObservableLike[F]): Observable[A]
Version of delayExecutionWith that can work with generic
F[_]
tasks, anything that's supported via ObservableLike conversions.Version of delayExecutionWith that can work with generic
F[_]
tasks, anything that's supported via ObservableLike conversions.So you can work among others with:
cats.effect.IO
monix.eval.Coeval
scala.concurrent.Future
- ...
- Definition Classes
- Observable
- final def delayOnComplete(delay: FiniteDuration): Observable[A]
Delays emitting the final
onComplete
event by the specified amount.Delays emitting the final
onComplete
event by the specified amount.- Definition Classes
- Observable
- final def delayOnNext(duration: FiniteDuration): Observable[A]
Returns an Observable that emits the items emitted by the source Observable shifted forward in time by a specified delay.
Returns an Observable that emits the items emitted by the source Observable shifted forward in time by a specified delay.
Each time the source Observable emits an item, delay starts a timer, and when that timer reaches the given duration, the Observable returned from delay emits the same item.
NOTE: this delay refers strictly to the time between the
onNext
event coming from our source and the time it takes the downstream observer to get this event. On the other hand the operator is also applying back-pressure, so on slow observers the actual time passing between two successive events may be higher than the specifiedduration
.- duration
- the delay to shift the source by
- returns
the source Observable shifted in time by the specified delay
- Definition Classes
- Observable
- final def delayOnNextBySelector[B](selector: (A) => Observable[B]): Observable[A]
Returns an Observable that emits the items emitted by the source Observable shifted forward in time.
Returns an Observable that emits the items emitted by the source Observable shifted forward in time.
This variant of
delay
sets its delay duration on a per-item basis by passing each item from the source Observable into a function that returns an Observable and then monitoring those Observables. When any such Observable emits an item or completes, the Observable returned by delay emits the associated item.- selector
is a function that returns an Observable for each item emitted by the source Observable, which is then used to delay the emission of that item by the resulting Observable until the Observable returned from
selector
emits an item- returns
the source Observable shifted in time by the specified delay
- Definition Classes
- Observable
- final def dematerialize[B](implicit ev: <:<[A, Notification[B]]): Observable[B]
Converts the source Observable that emits
Notification[A]
(the result of materialize) back to an Observable that emitsA
.Converts the source Observable that emits
Notification[A]
(the result of materialize) back to an Observable that emitsA
.- Definition Classes
- Observable
- final def distinctUntilChanged[AA >: A](implicit A: Eq[AA]): Observable[AA]
Suppress duplicate consecutive items emitted by the source.
Suppress duplicate consecutive items emitted by the source.
Example:
// Needed to bring standard Eq instances in scope: import cats.implicits._ // Yields 1, 2, 1, 3, 2, 4 val stream = Observable(1, 1, 1, 2, 2, 1, 1, 3, 3, 3, 2, 2, 4, 4, 4) .distinctUntilChanged
Duplication is detected by using the equality relationship provided by the cats.Eq type class. This allows one to override the equality operation being used (e.g. maybe the default
.equals
is badly defined, or maybe you want reference equality, so depending on use case).Cats Eq and Scala Interop
Monix prefers to work with cats.Eq for assessing the equality of elements that have an ordering defined, instead of scala.math.Equiv.
We do this because Scala's
Equiv
has a default instance defined that's based on universal equality and that's a big problem, because when using theEq
type class, it is universal equality that we want to avoid and there have been countless of bugs in the ecosystem related to both universal equality andEquiv
. Thankfully people are working to fix it.We also do this for consistency, as Monix is now building on top of Cats. This may change in the future, depending on what happens with typelevel/cats#2455.
Defining
Eq
instance is easy and we can use universal equality in our definitions as well:import cats.Eq case class Address(host: String, port: Int) implicit val eqForAddress: Eq[Address] = Eq.fromUniversalEquals
- A
is the cats.Eq instance that defines equality for the elements emitted by the source
- Definition Classes
- Observable
- final def distinctUntilChangedByKey[K](key: (A) => K)(implicit K: Eq[K]): Observable[A]
Given a function that returns a key for each element emitted by the source, suppress consecutive duplicate items.
Given a function that returns a key for each element emitted by the source, suppress consecutive duplicate items.
Example:
// Needed to bring standard instances in scope: import cats.implicits._ // Yields 1, 2, 3, 4 val stream = Observable(1, 3, 2, 4, 2, 3, 5, 7, 4) .distinctUntilChangedByKey(_ % 2)
Duplication is detected by using the equality relationship provided by the cats.Eq type class. This allows one to override the equality operation being used (e.g. maybe the default
.equals
is badly defined, or maybe you want reference equality, so depending on use case).Cats Eq and Scala Interop
Monix prefers to work with cats.Eq for assessing the equality of elements that have an ordering defined, instead of scala.math.Equiv.
We do this because Scala's
Equiv
has a default instance defined that's based on universal equality and that's a big problem, because when using theEq
type class, it is universal equality that we want to avoid and there have been countless of bugs in the ecosystem related to both universal equality andEquiv
. Thankfully people are working to fix it.We also do this for consistency, as Monix is now building on top of Cats. This may change in the future, depending on what happens with typelevel/cats#2455.
Defining
Eq
instance is easy and we can use universal equality in our definitions as well:import cats.Eq case class Address(host: String, port: Int) implicit val eqForAddress: Eq[Address] = Eq.fromUniversalEquals
- key
is a function that returns a
K
key for each element, a value that's then used to do the deduplication- K
is the cats.Eq instance that defines equality for the key type
K
- Definition Classes
- Observable
- final def doAfterSubscribe(task: Task[Unit]): Observable[A]
Executes the given callback just _after_ the subscription happens.
Executes the given callback just _after_ the subscription happens.
The executed
Task
executes after the subscription happens and it will delay the first event being emitted. For example this would delay the emitting of the first event by 1 second:import monix.eval.Task import scala.concurrent.duration._ Observable.range(0, 100) .doAfterSubscribe(Task.sleep(1.second))
- Definition Classes
- Observable
- See also
doOnSubscribe for executing a callback just before a subscription happens.
- final def doAfterSubscribeF[F[_]](task: F[Unit])(implicit F: TaskLike[F]): Observable[A]
Version of doAfterSubscribe that can work with generic
F[_]
tasks, anything that's supported via monix.eval.TaskLike conversions.Version of doAfterSubscribe that can work with generic
F[_]
tasks, anything that's supported via monix.eval.TaskLike conversions.So you can work among others with:
cats.effect.IO
monix.eval.Coeval
scala.concurrent.Future
- ...
import cats.effect._ import cats.effect.Timer import scala.concurrent.duration._ import monix.execution.Scheduler.Implicits.global import monix.catnap.SchedulerEffect // Needed for IO.sleep implicit val timer: Timer[IO] = SchedulerEffect.timerLiftIO[IO](global) Observable.range(0, 100) .doAfterSubscribeF(IO.sleep(1.second))
- Definition Classes
- Observable
- final def doOnComplete(task: Task[Unit]): Observable[A]
Evaluates the given task when the stream has ended with an
onComplete
event, but before the complete event is emitted.Evaluates the given task when the stream has ended with an
onComplete
event, but before the complete event is emitted.The task gets evaluated and is finished *before* the
onComplete
signal gets sent downstream.import monix.eval.Task Observable.range(0, 10) .doOnComplete(Task(println("Completed!")))
NOTE: in most cases what you want is guaranteeCase or bracketCase. This operator is available for fine-grained control.
- task
the task to execute when the
onComplete
event gets emitted
- Definition Classes
- Observable
- final def doOnCompleteF[F[_]](task: F[Unit])(implicit F: TaskLike[F]): Observable[A]
Version of doOnComplete that can work with generic
F[_]
tasks, anything that's supported via monix.eval.TaskLike conversions.Version of doOnComplete that can work with generic
F[_]
tasks, anything that's supported via monix.eval.TaskLike conversions.So you can work among others with:
cats.effect.IO
monix.eval.Coeval
scala.concurrent.Future
- ...
import cats.effect.IO Observable.range(0, 10) .doOnCompleteF(IO(println("Completed!")))
- Definition Classes
- Observable
- final def doOnEarlyStop(task: Task[Unit]): Observable[A]
Executes the given task when the streaming is stopped due to a downstream Stop signal returned by onNext.
Executes the given task when the streaming is stopped due to a downstream Stop signal returned by onNext.
The given
task
gets evaluated *before* the upstream receives theStop
event (is back-pressured).Example:
import monix.eval.Task val stream = Observable.range(0, Int.MaxValue) .doOnEarlyStop(Task(println("Stopped early!"))) .take(100)
NOTE: in most cases what you want is guaranteeCase or bracketCase. This operator is available for fine-grained control.
- Definition Classes
- Observable
- final def doOnEarlyStopF[F[_]](task: F[Unit])(implicit F: TaskLike[F]): Observable[A]
Version of doOnEarlyStop that can work with generic
F[_]
tasks, anything that's supported via monix.eval.TaskLike conversions.Version of doOnEarlyStop that can work with generic
F[_]
tasks, anything that's supported via monix.eval.TaskLike conversions.So you can work among others with:
cats.effect.IO
monix.eval.Coeval
scala.concurrent.Future
- ...
Example:
import cats.effect.IO val stream = Observable.range(0, Int.MaxValue) .doOnEarlyStopF(IO(println("Stopped early!"))) .take(100)
NOTE: in most cases what you want is guaranteeCase or bracketCase. This operator is available for fine-grained control.
- Definition Classes
- Observable
- final def doOnError(cb: (Throwable) => Task[Unit]): Observable[A]
Executes the given task when the stream is interrupted with an error, before the
onError
event is emitted downstream.Executes the given task when the stream is interrupted with an error, before the
onError
event is emitted downstream.Example:
import monix.eval.Task val dummy = new RuntimeException("dummy") (Observable.range(0, 10) ++ Observable.raiseError(dummy)) .doOnError { e => Task(println(s"Triggered error: $$e")) }
NOTE: should protect the code in this callback, because if it throws an exception the
onError
event will prefer signaling the original exception and otherwise the behavior is undefined.NOTE: in most cases what you want is guaranteeCase or bracketCase. This operator is available for fine-grained control.
- Definition Classes
- Observable
- final def doOnErrorF[F[_]](cb: (Throwable) => F[Unit])(implicit F: TaskLike[F]): Observable[A]
Version of doOnError that can work with generic
F[_]
tasks, anything that's supported via monix.eval.TaskLike conversions.Version of doOnError that can work with generic
F[_]
tasks, anything that's supported via monix.eval.TaskLike conversions.So you can work among others with:
cats.effect.IO
monix.eval.Coeval
scala.concurrent.Future
- ...
import cats.effect.IO val dummy = new RuntimeException("dummy") (Observable.range(0, 10) ++ Observable.raiseError(dummy)) .doOnErrorF { e => IO(println(s"Triggered error: $$e")) }
- Definition Classes
- Observable
- final def doOnNext(cb: (A) => Task[Unit]): Observable[A]
Evaluates the given callback for each element generated by the source Observable, useful for triggering async side-effects.
Evaluates the given callback for each element generated by the source Observable, useful for triggering async side-effects.
- returns
a new Observable that executes the specified callback for each element
- Definition Classes
- Observable
- See also
doOnNext for a simpler version that doesn't allow asynchronous execution.
- final def doOnNextAck(cb: (A, Ack) => Task[Unit]): Observable[A]
Executes the given callback on each acknowledgement received from the downstream subscriber, executing a generated Task and back-pressuring until the task is done.
Executes the given callback on each acknowledgement received from the downstream subscriber, executing a generated Task and back-pressuring until the task is done.
This method helps in executing logic after messages get processed, for example when messages are polled from some distributed message queue and an acknowledgement needs to be sent after each message in order to mark it as processed.
- Definition Classes
- Observable
- See also
doOnNextAckF for a version that can do evaluation with any data type via monix.eval.TaskLike
- final def doOnNextAckF[F[_]](cb: (A, Ack) => F[Unit])(implicit F: TaskLike[F]): Observable[A]
Version of doOnNextAck that can work with generic
F[_]
tasks, anything that's supported via monix.eval.TaskLike conversions.Version of doOnNextAck that can work with generic
F[_]
tasks, anything that's supported via monix.eval.TaskLike conversions.So you can work among others with:
cats.effect.IO
monix.eval.Coeval
scala.concurrent.Future
- ...
- Definition Classes
- Observable
- final def doOnNextF[F[_]](cb: (A) => F[Unit])(implicit F: TaskLike[F]): Observable[A]
Version of doOnNext that can work with generic
F[_]
tasks, anything that's supported via monix.eval.TaskLike conversions.Version of doOnNext that can work with generic
F[_]
tasks, anything that's supported via monix.eval.TaskLike conversions.So you can work among others with:
cats.effect.IO
monix.eval.Coeval
scala.concurrent.Future
- ...
- returns
a new Observable that executes the specified callback for each element
- Definition Classes
- Observable
- final def doOnStart(cb: (A) => Task[Unit]): Observable[A]
Executes the given callback only for the first element generated by the source Observable, useful for doing a piece of computation only when the stream starts.
Executes the given callback only for the first element generated by the source Observable, useful for doing a piece of computation only when the stream starts.
For example this observable will have a "delayed execution" of 1 second, plus a delayed first element of another 1 second, therefore it will take a total of 2 seconds for the first element to be emitted:
import monix.eval._ import scala.concurrent.duration._ Observable.range(0, 100) .delayExecution(1.second) .doOnStart { a => for { _ <- Task.sleep(1.second) _ <- Task(println(s"Started with: $$a")) } yield () }
- returns
a new Observable that executes the specified task only for the first element
- Definition Classes
- Observable
- final def doOnStartF[F[_]](cb: (A) => F[Unit])(implicit F: Effect[F]): Observable[A]
Version of doOnStart that can work with generic
F[_]
tasks, anything that's supported via monix.eval.TaskLike conversions.Version of doOnStart that can work with generic
F[_]
tasks, anything that's supported via monix.eval.TaskLike conversions.So you can work among others with:
cats.effect.IO
monix.eval.Coeval
scala.concurrent.Future
- ...
import cats.implicits._ import cats.effect._ import cats.effect.Timer import scala.concurrent.duration._ import monix.execution.Scheduler.Implicits.global import monix.catnap.SchedulerEffect // Needed for IO.sleep implicit val timer: Timer[IO] = SchedulerEffect.timerLiftIO[IO](global) Observable.range(0, 100) .delayExecution(1.second) .doOnStartF { a => for { _ <- IO.sleep(1.second) _ <- IO(println(s"Started with: $$a")) } yield () }
- Definition Classes
- Observable
- final def doOnSubscribe(task: Task[Unit]): Observable[A]
Executes the given callback just _before_ the subscription to the source happens.
Executes the given callback just _before_ the subscription to the source happens.
For example this is equivalent with delayExecution:
import monix.eval.Task import scala.concurrent.duration._ Observable.range(0, 10) .doOnSubscribe(Task.sleep(1.second))
- Definition Classes
- Observable
- See also
doAfterSubscribe for executing a callback just after a subscription happens.
- final def doOnSubscribeF[F[_]](task: F[Unit])(implicit F: TaskLike[F]): Observable[A]
Version of doOnSubscribe that can work with generic
F[_]
tasks, anything that's supported via monix.eval.TaskLike conversions.Version of doOnSubscribe that can work with generic
F[_]
tasks, anything that's supported via monix.eval.TaskLike conversions.So you can work among others with:
cats.effect.IO
monix.eval.Coeval
scala.concurrent.Future
- ...
For example this is equivalent with delayExecution:
import cats.effect._ import cats.effect.Timer import scala.concurrent.duration._ import monix.execution.Scheduler.Implicits.global import monix.catnap.SchedulerEffect // Needed for IO.sleep implicit val timer: Timer[IO] = SchedulerEffect.timerLiftIO[IO](global) Observable.range(0, 10) .doOnSubscribeF(IO.sleep(1.second))
- Definition Classes
- Observable
- final def doOnSubscriptionCancel(task: Task[Unit]): Observable[A]
Executes the given callback when the connection is being cancelled, via the Cancelable reference returned on subscribing to the created observable.
Executes the given callback when the connection is being cancelled, via the Cancelable reference returned on subscribing to the created observable.
Example:
import monix.eval.Task import monix.execution.Scheduler implicit val s = Scheduler.global val cancelable = Observable .range(0, Int.MaxValue) .doOnSubscriptionCancel(Task(println("Cancelled!"))) .subscribe() cancelable.cancel()
NOTE: in most cases what you want is guaranteeCase or bracketCase. This operator is available for fine-grained control.
- Definition Classes
- Observable
- final def doOnSubscriptionCancelF[F[_]](task: F[Unit])(implicit F: TaskLike[F]): Observable[A]
Version of doOnSubscriptionCancel that can work with generic
F[_]
tasks, anything that's supported via monix.eval.TaskLike conversions.Version of doOnSubscriptionCancel that can work with generic
F[_]
tasks, anything that's supported via monix.eval.TaskLike conversions.So you can work among others with:
cats.effect.IO
monix.eval.Coeval
scala.concurrent.Future
- ...
Example:
import cats.effect.IO import monix.execution.Scheduler implicit val s = Scheduler.global val cancelable = Observable .range(0, Int.MaxValue) .doOnSubscriptionCancelF(IO(println("Cancelled!"))) .subscribe() cancelable.cancel()
NOTE: in most cases what you want is guaranteeCase or bracketCase. This operator is available for fine-grained control.
- Definition Classes
- Observable
- final def drop(n: Long): Observable[A]
Drops the first
n
elements (from the start).Drops the first
n
elements (from the start).- n
the number (Long) of elements to drop
- returns
a new Observable that drops the first n elements emitted by the source
- Definition Classes
- Observable
- final def drop(n: Int): Observable[A]
Overload of drop(Long).
Overload of drop(Long).
- Definition Classes
- Observable
- final def dropByTimespan(timespan: FiniteDuration): Observable[A]
Creates a new observable that drops the events of the source, only for the specified
timestamp
window.Creates a new observable that drops the events of the source, only for the specified
timestamp
window.- timespan
the window of time during which the new observable must drop events emitted by the source
- Definition Classes
- Observable
- final def dropLast(n: Int): Observable[A]
Drops the last
n
elements (from the end).Drops the last
n
elements (from the end).- n
the number of elements to drop
- returns
a new Observable that drops the first n elements emitted by the source
- Definition Classes
- Observable
- final def dropUntil(trigger: Observable[Any]): Observable[A]
Discard items emitted by the source until a second observable emits an item or completes.
Discard items emitted by the source until a second observable emits an item or completes.
If the
trigger
observable completes in error, then the resulting observable will also end in error when it notices it (next time an element is emitted by the source).- trigger
the observable that has to emit an item before the source begin to be mirrored by the resulting observable
- Definition Classes
- Observable
- final def dropWhile(p: (A) => Boolean): Observable[A]
Drops the longest prefix of elements that satisfy the given predicate and returns a new observable that emits the rest.
Drops the longest prefix of elements that satisfy the given predicate and returns a new observable that emits the rest.
- Definition Classes
- Observable
- final def dropWhileInclusive(p: (A) => Boolean): Observable[A]
Drops the longest prefix of elements that satisfy the given predicate, inclusive of the value that caused
predicate
to returnfalse
and returns a new observable that emits the rest.Drops the longest prefix of elements that satisfy the given predicate, inclusive of the value that caused
predicate
to returnfalse
and returns a new observable that emits the rest.- Definition Classes
- Observable
- final def dropWhileWithIndex(p: (A, Int) => Boolean): Observable[A]
Drops the longest prefix of elements that satisfy the given function and returns a new observable that emits the rest.
Drops the longest prefix of elements that satisfy the given function and returns a new observable that emits the rest. In comparison with dropWhile, this version accepts a function that takes an additional parameter: the zero-based index of the element.
- Definition Classes
- Observable
- final def dump(prefix: String, out: PrintStream = System.out): Observable[A]
Utility that can be used for debugging purposes.
Utility that can be used for debugging purposes.
- Definition Classes
- Observable
- final def echoOnce(timeout: FiniteDuration): Observable[A]
Mirror the source observable as long as the source keeps emitting items, otherwise if
timeout
passes without the source emitting anything new then the observable will emit the last item.Mirror the source observable as long as the source keeps emitting items, otherwise if
timeout
passes without the source emitting anything new then the observable will emit the last item.Note: If the source Observable keeps emitting items more frequently than the length of the time window then the resulting observable will mirror the source exactly.
- timeout
the window of silence that must pass in order for the observable to echo the last item
- Definition Classes
- Observable
- final def echoRepeated(timeout: FiniteDuration): Observable[A]
Mirror the source observable as long as the source keeps emitting items, otherwise if
timeout
passes without the source emitting anything new then the observable will start emitting the last item repeatedly.Mirror the source observable as long as the source keeps emitting items, otherwise if
timeout
passes without the source emitting anything new then the observable will start emitting the last item repeatedly.Note: If the source Observable keeps emitting items more frequently than the length of the time window then the resulting observable will mirror the source exactly.
- timeout
the window of silence that must pass in order for the observable to start echoing the last item
- Definition Classes
- Observable
- final def endWith[B >: A](elems: Seq[B]): Observable[B]
Creates a new Observable that emits the events of the source and then it also emits the given elements (appended to the stream).
Creates a new Observable that emits the events of the source and then it also emits the given elements (appended to the stream).
- Definition Classes
- Observable
- final def endWithError(error: Throwable): Observable[A]
Emits the given exception instead of
onComplete
.Emits the given exception instead of
onComplete
.- error
the exception to emit onComplete
- returns
a new Observable that emits an exception onComplete
- Definition Classes
- Observable
- final def eq(arg0: AnyRef): Boolean
- Definition Classes
- AnyRef
- def equals(arg0: AnyRef): Boolean
- Definition Classes
- AnyRef → Any
- final def executeAsync: Observable[A]
Mirrors the source observable, but upon subscription ensure that the evaluation forks into a separate (logical) thread.
Mirrors the source observable, but upon subscription ensure that the evaluation forks into a separate (logical) thread.
The execution is managed by the injected scheduler in
subscribe()
.- Definition Classes
- Observable
- final def executeOn(s: Scheduler, forceAsync: Boolean = true): Observable[A]
Overrides the default Scheduler, possibly forcing an asynchronous boundary on subscription (if
forceAsync
is set totrue
, the default).Overrides the default Scheduler, possibly forcing an asynchronous boundary on subscription (if
forceAsync
is set totrue
, the default).When an
Observable
is subscribed with subscribe, it needs aScheduler
, which is going to be injected in the processing pipeline, to be used for managing asynchronous boundaries, scheduling execution with delay, etc.Normally the Scheduler gets injected implicitly when doing
subscribe
, but this operator overrides the injected subscriber for the given source. And if the source is normally using that injected scheduler (given bysubscribe
), then the effect will be that all processing will now happen on the override.To put it in other words, in Monix it's usually the consumer and not the producer that specifies the scheduler and this operator allows for a different behavior.
This operator also subsumes the effects of subscribeOn, meaning that the subscription logic itself will start on the provided scheduler if
forceAsync = true
(the default).- s
is the Scheduler to use for overriding the default scheduler and for forcing an asynchronous boundary if
forceAsync
istrue
- forceAsync
indicates whether an asynchronous boundary should be forced right before the subscription of the source
Observable
, managed by the providedScheduler
- returns
a new
Observable
that mirrors the source on subscription, but that uses the provided scheduler for overriding the default and possibly force an extra asynchronous boundary on execution
- Definition Classes
- Observable
- See also
observeOn and subscribeOn.
- final def executeWithModel(em: ExecutionModel): Observable[A]
Returns a new observable that will execute the source with a different ExecutionModel.
Returns a new observable that will execute the source with a different ExecutionModel.
This allows fine-tuning the options injected by the scheduler locally. Example:
import monix.execution.ExecutionModel.AlwaysAsyncExecution val stream = Observable(1, 2, 3) .executeWithModel(AlwaysAsyncExecution)
- em
is the ExecutionModel that will be used when evaluating the source.
- Definition Classes
- Observable
- final def exists(p: (A) => Boolean): Observable[Boolean]
Returns an Observable which emits a single value, either true, in case the given predicate holds for at least one item, or false otherwise.
Returns an Observable which emits a single value, either true, in case the given predicate holds for at least one item, or false otherwise.
- p
is a function that evaluates the items emitted by the source Observable, returning
true
if they pass the filter- returns
an Observable that emits only true or false in case the given predicate holds or not for at least one item
- Definition Classes
- Observable
- final def existsL(p: (A) => Boolean): Task[Boolean]
Returns a
Task
which emits eithertrue
, in case the given predicate holds for at least one item, orfalse
otherwise.Returns a
Task
which emits eithertrue
, in case the given predicate holds for at least one item, orfalse
otherwise.- p
is a function that evaluates the items emitted by the source, returning
true
if they pass the filter- returns
a task that emits
true
orfalse
in case the given predicate holds or not for at least one item
- Definition Classes
- Observable
- final def failed: Observable[Throwable]
Returns an observable that emits a single Throwable, in case an error was thrown by the source, otherwise it isn't going to emit anything.
Returns an observable that emits a single Throwable, in case an error was thrown by the source, otherwise it isn't going to emit anything.
- Definition Classes
- Observable
- final def filter(p: (A) => Boolean): Observable[A]
Only emits those items for which the given predicate holds.
Only emits those items for which the given predicate holds.
- p
a function that evaluates the items emitted by the source returning
true
if they pass the filter- returns
a new observable that emits only those items in the source for which the filter evaluates as
true
- Definition Classes
- Observable
- See also
filterEval for a version that works with a monix.eval.Task.
filterEvalF for a version that works with a generic
F[_]
(e.g.cats.effect.IO
, Scala'sFuture
), powered by monix.eval.TaskLike
- final def filterEval(p: (A) => Task[Boolean]): Observable[A]
Version of filter that can work with a predicate expressed by a monix.eval.Task.
Version of filter that can work with a predicate expressed by a monix.eval.Task.
- Definition Classes
- Observable
- See also
filterEvalF for a version that works with a generic
F[_]
(e.g.cats.effect.IO
, Scala'sFuture
), powered by monix.eval.TaskLike
- final def filterEvalF[F[_]](p: (A) => F[Boolean])(implicit F: TaskLike[F]): Observable[A]
Version of filterEval that can work with generic
F[_]
tasks, anything that's supported via monix.eval.TaskLike conversions.Version of filterEval that can work with generic
F[_]
tasks, anything that's supported via monix.eval.TaskLike conversions.So you can work among others with:
cats.effect.IO
monix.eval.Coeval
scala.concurrent.Future
- ...
- Definition Classes
- Observable
- final def filterNot(p: (A) => Boolean): Observable[A]
Only emits those items for which the given predicate doesn't hold.
Only emits those items for which the given predicate doesn't hold.
- p
a function that evaluates the items emitted by the source returning
true
if they should be filtered out- returns
a new observable that emits only those items in the source for which the filter evaluates as
false
- Definition Classes
- Observable
- final def find(p: (A) => Boolean): Observable[A]
Returns an Observable which only emits the first item for which the predicate holds.
Returns an Observable which only emits the first item for which the predicate holds.
- p
is a function that evaluates the items emitted by the source Observable, returning
true
if they pass the filter- returns
an Observable that emits only the first item in the original Observable for which the filter evaluates as
true
- Definition Classes
- Observable
- final def findL(p: (A) => Boolean): Task[Option[A]]
Returns a task which emits the first item for which the predicate holds.
Returns a task which emits the first item for which the predicate holds.
- p
is a function that evaluates the items emitted by the source observable, returning
true
if they pass the filter- returns
a task that emits the first item in the source observable for which the filter evaluates as
true
- Definition Classes
- Observable
- final def firstL: Task[A]
Creates a new Task that upon execution will signal the first generated element of the source observable.
Creates a new Task that upon execution will signal the first generated element of the source observable.
In case the stream was empty, then the
Task
gets completed in error with aNoSuchElementException
.- Definition Classes
- Observable
- final def firstOptionL: Task[Option[A]]
Creates a new Task that upon execution will signal the first generated element of the source observable.
Creates a new Task that upon execution will signal the first generated element of the source observable.
Returns an
Option
because the source can be empty.- Definition Classes
- Observable
- final def firstOrElse[B >: A](default: => B): Observable[B]
Alias for headOrElse.
Alias for headOrElse.
- Definition Classes
- Observable
- final def firstOrElseL[B >: A](default: => B): Task[B]
Creates a new Task that upon execution will signal the first generated element of the source observable.
Creates a new Task that upon execution will signal the first generated element of the source observable.
In case the stream was empty, then the given default gets evaluated and emitted.
- Definition Classes
- Observable
- final def flatMap[B](f: (A) => Observable[B]): Observable[B]
Alias for concatMap.
Alias for concatMap.
NOTE: one primary difference between Monix and other Rx / ReactiveX implementations is that in Monix
flatMap
is an alias forconcatMap
and NOTmergeMap
.- Definition Classes
- Observable
- final def flatMapDelayErrors[B](f: (A) => Observable[B]): Observable[B]
Alias of concatMapDelayErrors.
Alias of concatMapDelayErrors.
- Definition Classes
- Observable
- final def flatMapIterable[B](f: (A) => Iterable[B]): Observable[B]
Alias for concatMapIterable
Alias for concatMapIterable
NOTE: one primary difference between Monix and other Rx / ReactiveX implementations is that in Monix
flatMap
is an alias forconcatMap
and NOTmergeMap
.- Definition Classes
- Observable
- final def flatMapLatest[B](f: (A) => Observable[B]): Observable[B]
Alias of switchMap.
Alias of switchMap.
- Definition Classes
- Observable
- final def flatScan[R](seed: => R)(op: (R, A) => Observable[R]): Observable[R]
Applies a binary operator to a start value and to elements produced by the source observable, going from left to right, producing and concatenating observables along the way.
Applies a binary operator to a start value and to elements produced by the source observable, going from left to right, producing and concatenating observables along the way.
- Definition Classes
- Observable
- See also
flatScan0 for the version that emits seed element at the beginning
- final def flatScan0[R](seed: => R)(op: (R, A) => Observable[R]): Observable[R]
Applies a binary operator to a start value and to elements produced by the source observable, going from left to right, producing and concatenating observables along the way.
Applies a binary operator to a start value and to elements produced by the source observable, going from left to right, producing and concatenating observables along the way.
- Definition Classes
- Observable
- final def flatScan0DelayErrors[R](seed: => R)(op: (R, A) => Observable[R]): Observable[R]
Version of flatScan0 that delays the errors from the emitted streams until the source completes.
Version of flatScan0 that delays the errors from the emitted streams until the source completes.
Delaying Errors
This version is reserving
onError
notifications until all of the observables complete and only then passing the issued errors(s) downstream. Note that the streamed error is a CompositeException, since multiple errors from multiple streams can happen.- Definition Classes
- Observable
- See also
- final def flatScanDelayErrors[R](seed: => R)(op: (R, A) => Observable[R]): Observable[R]
Version of flatScan that delays the errors from the emitted streams until the source completes.
Version of flatScan that delays the errors from the emitted streams until the source completes.
Delaying Errors
This version is reserving
onError
notifications until all of the observables complete and only then passing the issued errors(s) downstream. Note that the streamed error is a CompositeException, since multiple errors from multiple streams can happen.- Definition Classes
- Observable
- See also
- final def flatten[B](implicit ev: <:<[A, Observable[B]]): Observable[B]
Concatenates the sequence of observables emitted by the source into one observable, without any transformation.
Concatenates the sequence of observables emitted by the source into one observable, without any transformation.
You can combine the items emitted by multiple observables so that they act like a single sequence by using this operator.
This operation is the "monadic bind", implementing the
flatMap
operation of cats.Monad.Concat vs Merge
The difference between the concat operation and merge is that
concat
cares about the ordering of sequences (e.g. all items emitted by the first observable in the sequence will come before the elements emitted by the second observable), whereasmerge
doesn't care about that (elements get emitted as they come). Because of back-pressure applied to observables,concat
is safe to use in all contexts, whereasmerge
requires buffering. Or in other wordsconcat
has deterministic, lawful behavior (being the "monadic bind"), whereasmerge
has non-deterministic behavior.Alias for concat.
- returns
an observable that emits the merged events of all streams created by the source
- Definition Classes
- Observable
- final def flattenDelayErrors[B](implicit ev: <:<[A, Observable[B]]): Observable[B]
Alias for concatDelayErrors.
Alias for concatDelayErrors.
- Definition Classes
- Observable
- final def flattenLatest[B](implicit ev: <:<[A, Observable[B]]): Observable[B]
Alias for switch.
Alias for switch.
- Definition Classes
- Observable
- final def fold[AA >: A](implicit A: Monoid[AA]): Observable[AA]
Given evidence that type
A
has acats.Monoid
implementation, folds the stream with the provided monoid definition.Given evidence that type
A
has acats.Monoid
implementation, folds the stream with the provided monoid definition.For streams emitting numbers, this effectively sums them up. For strings, this concatenates them.
Example:
import cats.implicits._ // Yields 10 val stream1 = Observable(1, 2, 3, 4).fold // Yields "1234" val stream2 = Observable("1", "2", "3", "4").fold
Note, in case you don't have a
Monoid
instance in scope, but you feel like you should, try this import:import cats.instances.all._
- A
is the
cats.Monoid
type class instance that's needed in scope for folding the source- returns
the result of combining all elements of the source, or the defined
Monoid.empty
element in case the stream is empty
- Definition Classes
- Observable
- See also
foldL for the version that returns a task instead of an observable.
- final def foldL[AA >: A](implicit A: Monoid[AA]): Task[AA]
Given evidence that type
A
has acats.Monoid
implementation, folds the stream with the provided monoid definition.Given evidence that type
A
has acats.Monoid
implementation, folds the stream with the provided monoid definition.For streams emitting numbers, this effectively sums them up. For strings, this concatenates them.
Example:
import cats.implicits._ // Yields 10 val stream1 = Observable(1, 2, 3, 4).foldL // Yields "1234" val stream2 = Observable("1", "2", "3", "4").foldL
- A
is the
cats.Monoid
type class instance that's needed in scope for folding the source- returns
the result of combining all elements of the source, or the defined
Monoid.empty
element in case the stream is empty
- Definition Classes
- Observable
- See also
fold for the version that returns an observable instead of a task.
- final def foldLeft[R](seed: => R)(op: (R, A) => R): Observable[R]
Applies a binary operator to a start value and all elements of this Observable, going left to right and returns a new Observable that emits only one item before
onComplete
.Applies a binary operator to a start value and all elements of this Observable, going left to right and returns a new Observable that emits only one item before
onComplete
.- seed
is the initial state, specified as a possibly lazy value; it gets evaluated when the subscription happens and if it triggers an error then the subscriber will get immediately terminated with an error
- op
is an operator that will fold the signals of the source observable, returning the next state
- Definition Classes
- Observable
- final def foldLeftL[R](seed: => R)(op: (R, A) => R): Task[R]
Applies a binary operator to a start value and all elements of the source, going left to right and returns a new
Task
that upon evaluation will eventually emit the final result.Applies a binary operator to a start value and all elements of the source, going left to right and returns a new
Task
that upon evaluation will eventually emit the final result.- Definition Classes
- Observable
- final def foldWhileLeft[S](seed: => S)(op: (S, A) => Either[S, S]): Observable[S]
Folds the source observable, from start to finish, until the source completes, or until the operator short-circuits the process by returning
false
.Folds the source observable, from start to finish, until the source completes, or until the operator short-circuits the process by returning
false
.Note that a call to foldLeft is equivalent to this function being called with an operator always returning
true
as the first member of its result.Example:
// Sums first 10 items val stream1 = Observable.range(0, 1000).foldWhileLeft((0L, 0)) { case ((sum, count), e) => val next = (sum + e, count + 1) if (count + 1 < 10) Left(next) else Right(next) } // Implements exists(predicate) val stream2 = Observable(1, 2, 3, 4, 5).foldWhileLeft(false) { (default, e) => if (e == 3) Right(true) else Left(default) } // Implements forall(predicate) val stream3 = Observable(1, 2, 3, 4, 5).foldWhileLeft(true) { (default, e) => if (e != 3) Right(false) else Left(default) }
- seed
is the initial state, specified as a possibly lazy value; it gets evaluated when the subscription happens and if it triggers an error then the subscriber will get immediately terminated with an error
- op
is the binary operator returning either
Left
, signaling that the state should be evolved or aRight
, signaling that the process can be short-circuited and the result returned immediately- returns
the result of inserting
op
between consecutive elements of this observable, going from left to right with theseed
as the start value, orseed
if the observable is empty
- Definition Classes
- Observable
- See also
foldWhileLeftL for a version that returns a task instead of an observable.
- final def foldWhileLeftL[S](seed: => S)(op: (S, A) => Either[S, S]): Task[S]
Folds the source observable, from start to finish, until the source completes, or until the operator short-circuits the process by returning
false
.Folds the source observable, from start to finish, until the source completes, or until the operator short-circuits the process by returning
false
.Note that a call to foldLeftL is equivalent to this function being called with an operator always returning
Left
results.Example:
// Sums first 10 items val stream1 = Observable.range(0, 1000).foldWhileLeftL((0L, 0)) { case ((sum, count), e) => val next = (sum + e, count + 1) if (count + 1 < 10) Left(next) else Right(next) } // Implements exists(predicate) val stream2 = Observable(1, 2, 3, 4, 5).foldWhileLeftL(false) { (default, e) => if (e == 3) Right(true) else Left(default) } // Implements forall(predicate) val stream3 = Observable(1, 2, 3, 4, 5).foldWhileLeftL(true) { (default, e) => if (e != 3) Right(false) else Left(default) }
- seed
is the initial state, specified as a possibly lazy value; it gets evaluated when the subscription happens and if it triggers an error then the subscriber will get immediately terminated with an error
- op
is the binary operator returning either
Left
, signaling that the state should be evolved or aRight
, signaling that the process can be short-circuited and the result returned immediately- returns
the result of inserting
op
between consecutive elements of this observable, going from left to right with theseed
as the start value, orseed
if the observable is empty
- Definition Classes
- Observable
- See also
foldWhileLeft for a version that returns an observable instead of a task.
- final def forall(p: (A) => Boolean): Observable[Boolean]
Returns an Observable that emits a single boolean, either true, in case the given predicate holds for all the items emitted by the source, or false in case at least one item is not verifying the given predicate.
Returns an Observable that emits a single boolean, either true, in case the given predicate holds for all the items emitted by the source, or false in case at least one item is not verifying the given predicate.
- p
is a function that evaluates the items emitted by the source Observable, returning
true
if they pass the filter- returns
an Observable that emits only true or false in case the given predicate holds or not for all the items
- Definition Classes
- Observable
- final def forallL(p: (A) => Boolean): Task[Boolean]
Returns a
Task
that emits a single boolean, either true, in case the given predicate holds for all the items emitted by the source, or false in case at least one item is not verifying the given predicate.Returns a
Task
that emits a single boolean, either true, in case the given predicate holds for all the items emitted by the source, or false in case at least one item is not verifying the given predicate.- p
is a function that evaluates the items emitted by the source observable, returning
true
if they pass the filter- returns
a task that emits only true or false in case the given predicate holds or not for all the items
- Definition Classes
- Observable
- final def foreach(cb: (A) => Unit)(implicit s: Scheduler): CancelableFuture[Unit]
Subscribes to the source
Observable
and foreach element emitted by the source it executes the given callback.Subscribes to the source
Observable
and foreach element emitted by the source it executes the given callback.- Definition Classes
- Observable
- Annotations
- @UnsafeBecauseImpure()
- final def foreachL(cb: (A) => Unit): Task[Unit]
Creates a new Task that will consume the source observable, executing the given callback for each element.
Creates a new Task that will consume the source observable, executing the given callback for each element.
- Definition Classes
- Observable
- final def getClass(): Class[_ <: AnyRef]
- Definition Classes
- AnyRef → Any
- Annotations
- @native() @HotSpotIntrinsicCandidate()
- final def groupBy[K](keySelector: (A) => K)(implicit os: Synchronous[Nothing] = OverflowStrategy.Unbounded): Observable[GroupedObservable[K, A]]
Groups the items emitted by an Observable according to a specified criterion, and emits these grouped items as GroupedObservables, one GroupedObservable per group.
Groups the items emitted by an Observable according to a specified criterion, and emits these grouped items as GroupedObservables, one GroupedObservable per group.
Note: A GroupedObservable will cache the items it is to emit until such time as it is subscribed to. For this reason, in order to avoid memory leaks, you should not simply ignore those GroupedObservables that do not concern you. Instead, you can signal to them that they may discard their buffers by doing something like
source.take(0)
.- keySelector
a function that extracts the key for each item
- Definition Classes
- Observable
- final def guarantee(f: Task[Unit]): Observable[A]
Given a routine make sure to execute it whenever the current stream reaches the end, successfully, in error, or canceled.
Given a routine make sure to execute it whenever the current stream reaches the end, successfully, in error, or canceled.
Implements
cats.effect.Bracket.guarantee
.Example:
import monix.eval.Task Observable.suspend(???).guarantee(Task.eval { println("Releasing resources!") })
- f
is the function to execute on early stop
- Definition Classes
- Observable
- final def guaranteeCase(f: (ExitCase[Throwable]) => Task[Unit]): Observable[A]
Returns a new
Observable
in whichf
is scheduled to be executed when the source is completed, in success, error or when cancelled.Returns a new
Observable
in whichf
is scheduled to be executed when the source is completed, in success, error or when cancelled.Implements
cats.effect.Bracket.guaranteeCase
.This would typically be used to ensure that a finalizer will run at the end of the stream.
Example:
import cats.effect.ExitCase import monix.eval.Task val stream = Observable.suspend(???).guaranteeCase(err => Task { err match { case ExitCase.Completed => println("Completed successfully!") case ExitCase.Error(e) => e.printStackTrace() case ExitCase.Canceled => println("Was stopped early!") } })
NOTE this is using
cats.effect.ExitCase
to signal the termination condition, like this:- if completed via
onComplete
or viaStop
signalled by the consumer, then the function receivesExitCase.Completed
- if completed via
onError
or in certain cases in which errors are detected (e.g. the consumer returns an error), then the function receivesExitCase.Error(e)
- if the subscription was cancelled, then the function receives
ExitCase.Canceled
In other words
Completed
is for normal termination conditions,Error
is for exceptions being detected andCanceled
is for when the subscription gets canceled.- f
is the finalizer to execute when streaming is terminated, by successful completion, error or cancellation; for specifying the side effects to use
- Definition Classes
- Observable
- if completed via
- final def guaranteeCaseF[F[_]](f: (ExitCase[Throwable]) => F[Unit])(implicit F: TaskLike[F]): Observable[A]
Version of guaranteeCase that can work with generic
F[_]
tasks, anything that's supported via monix.eval.TaskLike conversions.Version of guaranteeCase that can work with generic
F[_]
tasks, anything that's supported via monix.eval.TaskLike conversions.So you can work among others with:
cats.effect.IO
monix.eval.Coeval
scala.concurrent.Future
- ...
- Definition Classes
- Observable
- final def guaranteeF[F[_]](f: F[Unit])(implicit F: TaskLike[F]): Observable[A]
Version of guarantee that can work with generic
F[_]
tasks, anything that's supported via monix.eval.TaskLike conversions.Version of guarantee that can work with generic
F[_]
tasks, anything that's supported via monix.eval.TaskLike conversions.So you can work among others with:
cats.effect.IO
monix.eval.Coeval
scala.concurrent.Future
- ...
- Definition Classes
- Observable
- def hashCode(): Int
- Definition Classes
- AnyRef → Any
- Annotations
- @native() @HotSpotIntrinsicCandidate()
- final def head: Observable[A]
Only emits the first element emitted by the source observable, after which it's completed immediately.
Only emits the first element emitted by the source observable, after which it's completed immediately.
- Definition Classes
- Observable
- final def headL: Task[A]
Alias for firstL.
Alias for firstL.
- Definition Classes
- Observable
- final def headOptionL: Task[Option[A]]
Alias for firstOptionL.
Alias for firstOptionL.
- Definition Classes
- Observable
- final def headOrElse[B >: A](default: => B): Observable[B]
Emits the first element emitted by the source, or otherwise if the source is completed without emitting anything, then the
default
is emitted.Emits the first element emitted by the source, or otherwise if the source is completed without emitting anything, then the
default
is emitted.- Definition Classes
- Observable
- final def headOrElseL[B >: A](default: => B): Task[B]
Alias for firstOrElseL.
Alias for firstOrElseL.
- Definition Classes
- Observable
- final def ignoreElements: Observable[Nothing]
Alias for completed.
Alias for completed. Ignores all items emitted by the source and only calls onCompleted or onError.
- returns
an empty sequence that only calls onCompleted or onError, based on which one is called by the source Observable
- Definition Classes
- Observable
- final def interleave[B >: A](other: Observable[B]): Observable[B]
Creates a new observable from this observable and another given observable by interleaving their items into a strictly alternating sequence.
Creates a new observable from this observable and another given observable by interleaving their items into a strictly alternating sequence.
So the first item emitted by the new observable will be the item emitted by
self
, the second item will be emitted by the other observable, and so forth; when eitherself
orother
callsonCompletes
, the items will then be directly coming from the observable that has not completed; whenonError
is called by eitherself
orother
, the new observable will callonError
and halt.See merge for a more relaxed alternative that doesn't emit items in strict alternating sequence.
- other
is an observable that interleaves with the source
- returns
a new observable sequence that alternates emission of the items from both child streams
- Definition Classes
- Observable
- final def intersperse[B >: A](start: B, separator: B, end: B): Observable[B]
Creates a new observable from this observable that will emit the
start
element followed by the upstream elements paired with theseparator
, and lastly theend
element.Creates a new observable from this observable that will emit the
start
element followed by the upstream elements paired with theseparator
, and lastly theend
element.Usage sample:
// Yields "begin a : b : c : d end" Observable("a", "b", "c", "d") .intersperse("begin ", " : ", " end") .foldLeftL("")(_ ++ _)
- start
is the first element emitted
- separator
is the separator
- end
the last element emitted
- Definition Classes
- Observable
- final def intersperse[B >: A](separator: B): Observable[B]
Creates a new observable from this observable that will emit a specific
separator
between every pair of elements.Creates a new observable from this observable that will emit a specific
separator
between every pair of elements.Usage sample:
// Yields "a : b : c : d" Observable("a", "b", "c", "d") .intersperse(" : ") .foldLeftL("")(_ ++ _)
- separator
is the separator
- Definition Classes
- Observable
- final def isEmpty: Observable[Boolean]
Returns an Observable that emits true if the source Observable is empty, otherwise false.
Returns an Observable that emits true if the source Observable is empty, otherwise false.
- Definition Classes
- Observable
- final def isEmptyL: Task[Boolean]
Returns a task that emits
true
if the source observable is empty, otherwisefalse
.Returns a task that emits
true
if the source observable is empty, otherwisefalse
.- Definition Classes
- Observable
- final def isInstanceOf[T0]: Boolean
- Definition Classes
- Any
- final def last: Observable[A]
Only emits the last element emitted by the source observable, after which it's completed immediately.
Only emits the last element emitted by the source observable, after which it's completed immediately.
- Definition Classes
- Observable
- final def lastL: Task[A]
Returns a Task that upon execution will signal the last generated element of the source observable.
Returns a Task that upon execution will signal the last generated element of the source observable.
In case the stream was empty, then the
Task
gets completed in error with aNoSuchElementException
.- Definition Classes
- Observable
- final def lastOptionL: Task[Option[A]]
Returns a Task that upon execution will signal the last generated element of the source observable.
Returns a Task that upon execution will signal the last generated element of the source observable.
Returns an
Option
because the source can be empty.- Definition Classes
- Observable
- final def lastOrElseL[B >: A](default: => B): Task[B]
Creates a new Task that upon execution will signal the last generated element of the source observable.
Creates a new Task that upon execution will signal the last generated element of the source observable.
In case the stream was empty, then the given default gets evaluated and emitted.
- Definition Classes
- Observable
- final def liftByOperator[B](operator: Operator[A, B]): Observable[B]
Transforms the source using the given operator.
Transforms the source using the given operator.
- Definition Classes
- Observable
- final def map[B](f: (A) => B): Observable[B]
Returns a new observable that applies the given function to each item emitted by the source and emits the result.
Returns a new observable that applies the given function to each item emitted by the source and emits the result.
- Definition Classes
- Observable
- final def mapAccumulate[S, R](seed: => S)(op: (S, A) => (S, R)): Observable[R]
Applies a binary operator to a start value and all elements of this Observable, going left to right and returns a new Observable that emits on each step the result element of the applied function.
Applies a binary operator to a start value and all elements of this Observable, going left to right and returns a new Observable that emits on each step the result element of the applied function.
Similar to scan, but the supplied function returns a tuple of the next accumulator state and the result type emitted by the returned observable.
- Definition Classes
- Observable
- final def mapEval[B](f: (A) => Task[B]): Observable[B]
Maps elements from the source using a function that can do asynchronous processing by means of Task.
Maps elements from the source using a function that can do asynchronous processing by means of Task.
Example:
import monix.eval.Task import scala.concurrent.duration._ Observable.range(0, 100) .mapEval(x => Task(x).delayExecution(1.second))
- Definition Classes
- Observable
- See also
mapEvalF for a version that works with a generic
F[_]
(e.g.cats.effect.IO
, Scala'sFuture
), powered by monix.eval.TaskLike
- final def mapEvalF[F[_], B](f: (A) => F[B])(implicit F: TaskLike[F]): Observable[B]
Version of mapEval that can work with generic
F[_]
tasks, anything that's supported via monix.eval.TaskLike conversions.Version of mapEval that can work with generic
F[_]
tasks, anything that's supported via monix.eval.TaskLike conversions.So you can work among others with:
cats.effect.IO
monix.eval.Coeval
scala.concurrent.Future
- ...
Example:
import cats.implicits._ import cats.effect.IO import cats.effect.Timer import scala.concurrent.duration._ import monix.execution.Scheduler.Implicits.global import monix.catnap.SchedulerEffect // Needed for IO.sleep implicit val timer: Timer[IO] = SchedulerEffect.timerLiftIO[IO](global) Observable.range(0, 100).mapEvalF { x => IO.sleep(1.second) *> IO(x) }
- Definition Classes
- Observable
- See also
- final def mapParallelOrdered[B](parallelism: Int)(f: (A) => Task[B])(implicit os: OverflowStrategy[B] = OverflowStrategy.Default): Observable[B]
Given a mapping function that maps events to tasks, applies it in parallel on the source, but with a specified
parallelism
, which indicates the maximum number of tasks that can be executed in parallel returning them preserving original order.Given a mapping function that maps events to tasks, applies it in parallel on the source, but with a specified
parallelism
, which indicates the maximum number of tasks that can be executed in parallel returning them preserving original order.Similar in spirit with Consumer.loadBalance, but expressed as an operator that executes Task instances in parallel.
Note that when the specified
parallelism
is 1, it has the same behavior as mapEval.- parallelism
is the maximum number of tasks that can be executed in parallel, over which the source starts being back-pressured
- f
is the mapping function that produces tasks to execute in parallel, which will eventually produce events for the resulting observable stream
- Definition Classes
- Observable
- See also
mapParallelUnordered for a variant that does not preserve order which may lead to faster execution times
mapEval for serial execution
- final def mapParallelOrderedF[F[_], B](parallelism: Int)(f: (A) => F[B])(implicit os: OverflowStrategy[B] = OverflowStrategy.Default, F: TaskLike[F]): Observable[B]
Version of mapParallelOrderedF that can work with generic
F[_]
tasks, anything that's supported via monix.eval.TaskLike conversions.Version of mapParallelOrderedF that can work with generic
F[_]
tasks, anything that's supported via monix.eval.TaskLike conversions.So you can work among others with:
cats.effect.IO
monix.eval.Coeval
scala.concurrent.Future
- ...
- parallelism
is the maximum number of tasks that can be executed in parallel, over which the source starts being back-pressured
- f
is the mapping function that produces tasks to execute in parallel, which will eventually produce events for the resulting observable stream
- Definition Classes
- Observable
- See also
mapParallelUnorderedF for a variant that does not preserve order which may lead to faster execution times
mapEvalF for serial execution
- final def mapParallelUnordered[B](parallelism: Int)(f: (A) => Task[B])(implicit os: OverflowStrategy[B] = OverflowStrategy.Default): Observable[B]
Given a mapping function that maps events to tasks, applies it in parallel on the source, but with a specified
parallelism
, which indicates the maximum number of tasks that can be executed in parallel.Given a mapping function that maps events to tasks, applies it in parallel on the source, but with a specified
parallelism
, which indicates the maximum number of tasks that can be executed in parallel.Similar in spirit with Consumer.loadBalance, but expressed as an operator that executes Task instances in parallel.
Note that when the specified
parallelism
is 1, it has the same behavior as mapEval.- parallelism
is the maximum number of tasks that can be executed in parallel, over which the source starts being back-pressured
- f
is the mapping function that produces tasks to execute in parallel, which will eventually produce events for the resulting observable stream
- Definition Classes
- Observable
- See also
mapParallelOrdered for a variant that does preserve order
mapEval for serial execution
- final def mapParallelUnorderedF[F[_], B](parallelism: Int)(f: (A) => F[B])(implicit os: OverflowStrategy[B] = OverflowStrategy.Default, F: TaskLike[F]): Observable[B]
Version of mapParallelUnordered that can work with generic
F[_]
tasks, anything that's supported via monix.eval.TaskLike conversions.Version of mapParallelUnordered that can work with generic
F[_]
tasks, anything that's supported via monix.eval.TaskLike conversions.So you can work among others with:
cats.effect.IO
monix.eval.Coeval
scala.concurrent.Future
- ...
Note that when the specified
parallelism
is 1, it has the same behavior as mapEval.
- parallelism
is the maximum number of tasks that can be executed in parallel, over which the source starts being back-pressured
- f
is the mapping function that produces tasks to execute in parallel, which will eventually produce events for the resulting observable stream
- Definition Classes
- Observable
- See also
mapParallelOrdered for a variant that does preserve order
mapEval for serial execution
- final def materialize: Observable[Notification[A]]
Converts the source Observable that emits
A
into an Observable that emitsNotification[A]
.Converts the source Observable that emits
A
into an Observable that emitsNotification[A]
.- Definition Classes
- Observable
- final def max[AA >: A](implicit A: Order[AA]): Observable[AA]
Given a cats.Order over the stream's elements, returns the maximum element in the stream.
Given a cats.Order over the stream's elements, returns the maximum element in the stream.
Example
// Needed to bring the standard Order instances in scope: import cats.implicits._ // Yields Observable(20) val stream1 = Observable(10, 7, 6, 8, 20, 3, 5).max // Yields Observable.empty val stream2 = Observable.empty[Int].max
Cats Order and Scala Interop
Monix prefers to work with cats.Order for assessing the order of elements that have an ordering defined, instead of scala.math.Ordering.
We do this for consistency, as Monix is now building on top of Cats. This may change in the future, depending on what happens with typelevel/cats#2455.
Building a
cats.Order
is easy to do if you already have a ScalaOrdering
instance:import cats.Order case class Person(name: String, age: Int) // Starting from a Scala Ordering implicit val scalaOrderingForPerson: Ordering[Person] = new Ordering[Person] { def compare(x: Person, y: Person): Int = x.age.compareTo(y.age) match { case 0 => x.name.compareTo(y.name) case o => o } } // Building a cats.Order from it implicit val catsOrderForPerson: Order[Person] = Order.fromOrdering
You can also do that in reverse, so you can prefer
cats.Order
(due to Cats also exposing laws and tests for free) and build a ScalaOrdering
when needed:val scalaOrdering = catsOrderForPerson.toOrdering
- A
is the cats.Order type class instance that's going to be used for comparing elements
- returns
the maximum element of the source stream, relative to the defined
Order
- Definition Classes
- Observable
- See also
maxL for the version that returns a Task instead of an observable.
- final def maxBy[K](key: (A) => K)(implicit K: Order[K]): Observable[A]
Takes the elements of the source observable and emits the element that has the maximum key value, where the key is generated by the given function.
Takes the elements of the source observable and emits the element that has the maximum key value, where the key is generated by the given function.
Example
// Needed to bring the standard Order instances in scope: import cats.implicits._ case class Person(name: String, age: Int) // Yields Observable(Person("Alex", 34)) Observable(Person("Alex", 34), Person("Alice", 27)) .maxBy(_.age)
Cats Order and Scala Interop
Monix prefers to work with cats.Order for assessing the order of elements that have an ordering defined, instead of scala.math.Ordering.
We do this for consistency, as Monix is now building on top of Cats. This may change in the future, depending on what happens with typelevel/cats#2455.
Building a
cats.Order
is easy to do if you already have a ScalaOrdering
instance:import cats.Order case class Person(name: String, age: Int) // Starting from a Scala Ordering implicit val scalaOrderingForPerson: Ordering[Person] = new Ordering[Person] { def compare(x: Person, y: Person): Int = x.age.compareTo(y.age) match { case 0 => x.name.compareTo(y.name) case o => o } } // Building a cats.Order from it implicit val catsOrderForPerson: Order[Person] = Order.fromOrdering
You can also do that in reverse, so you can prefer
cats.Order
(due to Cats also exposing laws and tests for free) and build a ScalaOrdering
when needed:val scalaOrdering = catsOrderForPerson.toOrdering
- key
is the function that returns the key for which the given ordering is defined
- K
is the cats.Order type class instance that's going to be used for comparing elements
- returns
the maximum element of the source stream, relative to its key generated by the given function and the given ordering
- Definition Classes
- Observable
- See also
maxByL for the version that returns a Task instead of an observable.
- final def maxByL[K](key: (A) => K)(implicit K: Order[K]): Task[Option[A]]
Takes the elements of the source observable and emits the element that has the maximum key value, where the key is generated by the given function.
Takes the elements of the source observable and emits the element that has the maximum key value, where the key is generated by the given function.
Example
// Needed to bring the standard Order instances in scope: import cats.implicits._ case class Person(name: String, age: Int) // Yields Some(Person("Alex", 34)) Observable(Person("Alex", 34), Person("Alice", 27)) .maxByL(_.age)
Cats Order and Scala Interop
Monix prefers to work with cats.Order for assessing the order of elements that have an ordering defined, instead of scala.math.Ordering.
We do this for consistency, as Monix is now building on top of Cats. This may change in the future, depending on what happens with typelevel/cats#2455.
Building a
cats.Order
is easy to do if you already have a ScalaOrdering
instance:import cats.Order case class Person(name: String, age: Int) // Starting from a Scala Ordering implicit val scalaOrderingForPerson: Ordering[Person] = new Ordering[Person] { def compare(x: Person, y: Person): Int = x.age.compareTo(y.age) match { case 0 => x.name.compareTo(y.name) case o => o } } // Building a cats.Order from it implicit val catsOrderForPerson: Order[Person] = Order.fromOrdering
You can also do that in reverse, so you can prefer
cats.Order
(due to Cats also exposing laws and tests for free) and build a ScalaOrdering
when needed:val scalaOrdering = catsOrderForPerson.toOrdering
- key
is the function that returns the key for which the given ordering is defined
- K
is the cats.Order type class instance that's going to be used for comparing elements
- returns
the maximum element of the source stream, relative to its key generated by the given function and the given ordering
- Definition Classes
- Observable
- See also
maxBy for the version that returns an observable instead of a
Task
.
- final def maxL[AA >: A](implicit A: Order[AA]): Task[Option[AA]]
Given a cats.Order over the stream's elements, returns the maximum element in the stream.
Given a cats.Order over the stream's elements, returns the maximum element in the stream.
Example
// Needed to bring the standard Order instances in scope: import cats.implicits._ // Yields Some(20) val stream1 = Observable(10, 7, 6, 8, 20, 3, 5).maxL // Yields Observable.empty val stream2 = Observable.empty[Int].maxL
Cats Order and Scala Interop
Monix prefers to work with cats.Order for assessing the order of elements that have an ordering defined, instead of scala.math.Ordering.
We do this for consistency, as Monix is now building on top of Cats. This may change in the future, depending on what happens with typelevel/cats#2455.
Building a
cats.Order
is easy to do if you already have a ScalaOrdering
instance:import cats.Order case class Person(name: String, age: Int) // Starting from a Scala Ordering implicit val scalaOrderingForPerson: Ordering[Person] = new Ordering[Person] { def compare(x: Person, y: Person): Int = x.age.compareTo(y.age) match { case 0 => x.name.compareTo(y.name) case o => o } } // Building a cats.Order from it implicit val catsOrderForPerson: Order[Person] = Order.fromOrdering
You can also do that in reverse, so you can prefer
cats.Order
(due to Cats also exposing laws and tests for free) and build a ScalaOrdering
when needed:val scalaOrdering = catsOrderForPerson.toOrdering
- A
is the cats.Order type class instance that's going to be used for comparing elements
- returns
the maximum element of the source stream, relative to the defined
Order
- Definition Classes
- Observable
- See also
maxF for the version that returns an observable instead of a
Task
.
- final def merge[B](implicit ev: <:<[A, Observable[B]], os: OverflowStrategy[B] = OverflowStrategy.Default[B]): Observable[B]
Concurrently merges the observables emitted by the source, into a single observable.
Concurrently merges the observables emitted by the source, into a single observable.
Equivalence with mergeMap
The
merge
operation is mergeMap with the identity function:stream.merge <-> stream.mergeMap(x => x)
Concat vs Merge
The difference between the concat operation and merge is that
concat
cares about the ordering of sequences (e.g. all items emitted by the first observable in the sequence will come before the elements emitted by the second observable), whereasmerge
doesn't care about that (elements get emitted as they come). Because of back-pressure applied to observables,concat
is safe to use in all contexts, whereasmerge
requires buffering. Or in other wordsconcat
has deterministic, lawful behavior (being the "monadic bind"), whereasmerge
has non-deterministic behavior.Visual Example
streamA: a1 -- -- a2 -- -- a3 -- a4 -- -- streamB: b1 -- -- b2 -- b3 -- -- -- -- b4 result: a1, b1, a2, b2, b3, a3, a4, b4
- returns
an observable containing the merged events of all streams created by the source
- Definition Classes
- Observable
- Note
this operation needs to do buffering and by not specifying an OverflowStrategy, the default strategy is being used.
- final def mergeDelayErrors[B](implicit ev: <:<[A, Observable[B]], os: OverflowStrategy[B] = OverflowStrategy.Default): Observable[B]
This version is reserving
onError
notifications until all of the observables complete and only then passing the issued errors(s) downstream.Delaying Errors
This version is reserving
onError
notifications until all of the observables complete and only then passing the issued errors(s) downstream. Note that the streamed error is a CompositeException, since multiple errors from multiple streams can happen.- returns
an observable containing the merged events of all streams created by the source
- Definition Classes
- Observable
- Note
this operation needs to do buffering and by not specifying an OverflowStrategy, the default strategy is being used.
- final def mergeMap[B](f: (A) => Observable[B])(implicit os: OverflowStrategy[B] = OverflowStrategy.Default): Observable[B]
Concurrently merges the observables emitted by the source with the given generator function into a single observable.
Concurrently merges the observables emitted by the source with the given generator function into a single observable.
Concat vs Merge
The difference between the concat operation and merge is that
concat
cares about the ordering of sequences (e.g. all items emitted by the first observable in the sequence will come before the elements emitted by the second observable), whereasmerge
doesn't care about that (elements get emitted as they come). Because of back-pressure applied to observables,concat
is safe to use in all contexts, whereasmerge
requires buffering. Or in other wordsconcat
has deterministic, lawful behavior (being the "monadic bind"), whereasmerge
has non-deterministic behavior.Example
Observable(1, 2, 3).mergeMap { x => Observable.eval(println(s"Processing $$x")) .executeAsync .flatMap(_ => Observable(x, x)) }
In this example the source will yield 3 streams and those 3 streams are being subscribed immediately, therefore the order of the events will be non-deterministic, as the streams will be evaluated concurrently.
Visual Example
streamA: a1 -- -- a2 -- -- a3 -- a4 -- -- streamB: b1 -- -- b2 -- b3 -- -- -- -- b4 result: a1, b1, a2, b2, b3, a3, a4, b4
- f
is a generator for the streams that will get merged
- returns
an observable that emits the result of applying the transformation function to each item emitted by the source observable and merging the results of the observables obtained from this transformation.
- Definition Classes
- Observable
- final def mergeMapDelayErrors[B](f: (A) => Observable[B])(implicit os: OverflowStrategy[B] = OverflowStrategy.Default): Observable[B]
Creates a new observable by applying a function that you supply to each item emitted by the source observable, where that function returns an observable, and then merging those resulting observable and emitting the results of this merger.
Creates a new observable by applying a function that you supply to each item emitted by the source observable, where that function returns an observable, and then merging those resulting observable and emitting the results of this merger.
Concat vs Merge
The difference between the concat operation and merge is that
concat
cares about the ordering of sequences (e.g. all items emitted by the first observable in the sequence will come before the elements emitted by the second observable), whereasmerge
doesn't care about that (elements get emitted as they come). Because of back-pressure applied to observables,concat
is safe to use in all contexts, whereasmerge
requires buffering. Or in other wordsconcat
has deterministic, lawful behavior (being the "monadic bind"), whereasmerge
has non-deterministic behavior.Delaying Errors
This version is reserving
onError
notifications until all of the observables complete and only then passing the issued errors(s) downstream. Note that the streamed error is a CompositeException, since multiple errors from multiple streams can happen.- f
is a generator for the streams that will get merged
- returns
an observable that emits the result of applying the transformation function to each item emitted by the source observable and merging the results of the observables obtained from this transformation.
- Definition Classes
- Observable
- final def min[AA >: A](implicit A: Order[AA]): Observable[AA]
Given a cats.Order over the stream's elements, returns the minimum element in the stream.
Given a cats.Order over the stream's elements, returns the minimum element in the stream.
Example
// Needed to bring the standard Order instances in scope: import cats.implicits._ // Yields Observable(3) val stream1 = Observable(10, 7, 6, 8, 20, 3, 5).min // Yields Observable.empty val stream2 = Observable.empty[Int].min
Cats Order and Scala Interop
Monix prefers to work with cats.Order for assessing the order of elements that have an ordering defined, instead of scala.math.Ordering.
We do this for consistency, as Monix is now building on top of Cats. This may change in the future, depending on what happens with typelevel/cats#2455.
Building a
cats.Order
is easy to do if you already have a ScalaOrdering
instance:import cats.Order case class Person(name: String, age: Int) // Starting from a Scala Ordering implicit val scalaOrderingForPerson: Ordering[Person] = new Ordering[Person] { def compare(x: Person, y: Person): Int = x.age.compareTo(y.age) match { case 0 => x.name.compareTo(y.name) case o => o } } // Building a cats.Order from it implicit val catsOrderForPerson: Order[Person] = Order.fromOrdering
You can also do that in reverse, so you can prefer
cats.Order
(due to Cats also exposing laws and tests for free) and build a ScalaOrdering
when needed:val scalaOrdering = catsOrderForPerson.toOrdering
- A
is the cats.Order type class instance that's going to be used for comparing elements
- returns
the minimum element of the source stream, relative to the defined
Order
- Definition Classes
- Observable
- See also
minL for the version that returns a Task instead of an observable.
- final def minBy[K](key: (A) => K)(implicit K: Order[K]): Observable[A]
Takes the elements of the source observable and emits the element that has the minimum key value, where the key is generated by the given function.
Takes the elements of the source observable and emits the element that has the minimum key value, where the key is generated by the given function.
Example:
// Needed to bring the standard Order instances in scope: import cats.implicits._ case class Person(name: String, age: Int) // Yields Observable(Person("Alice", 27)) val stream = Observable(Person("Alex", 34), Person("Alice", 27)) .minBy(_.age)
Cats Order and Scala Interop
Monix prefers to work with cats.Order for assessing the order of elements that have an ordering defined, instead of scala.math.Ordering.
We do this for consistency, as Monix is now building on top of Cats. This may change in the future, depending on what happens with typelevel/cats#2455.
Building a
cats.Order
is easy to do if you already have a ScalaOrdering
instance:import cats.Order case class Person(name: String, age: Int) // Starting from a Scala Ordering implicit val scalaOrderingForPerson: Ordering[Person] = new Ordering[Person] { def compare(x: Person, y: Person): Int = x.age.compareTo(y.age) match { case 0 => x.name.compareTo(y.name) case o => o } } // Building a cats.Order from it implicit val catsOrderForPerson: Order[Person] = Order.fromOrdering
You can also do that in reverse, so you can prefer
cats.Order
(due to Cats also exposing laws and tests for free) and build a ScalaOrdering
when needed:val scalaOrdering = catsOrderForPerson.toOrdering
- key
is the function that returns the key for which the given ordering is defined
- K
is the cats.Order type class instance that's going to be used for comparing elements
- returns
the minimum element of the source stream, relative to its key generated by the given function and the given ordering
- Definition Classes
- Observable
- final def minByL[K](key: (A) => K)(implicit K: Order[K]): Task[Option[A]]
Takes the elements of the source observable and emits the element that has the minimum key value, where the key is generated by the given function.
Takes the elements of the source observable and emits the element that has the minimum key value, where the key is generated by the given function.
Example
// Needed to bring the standard Order instances in scope: import cats.implicits._ case class Person(name: String, age: Int) // Yields Some(Person("Alice", 27)) Observable(Person("Alex", 34), Person("Alice", 27)) .minByL(_.age)
Cats Order and Scala Interop
Monix prefers to work with cats.Order for assessing the order of elements that have an ordering defined, instead of scala.math.Ordering.
We do this for consistency, as Monix is now building on top of Cats. This may change in the future, depending on what happens with typelevel/cats#2455.
Building a
cats.Order
is easy to do if you already have a ScalaOrdering
instance:import cats.Order case class Person(name: String, age: Int) // Starting from a Scala Ordering implicit val scalaOrderingForPerson: Ordering[Person] = new Ordering[Person] { def compare(x: Person, y: Person): Int = x.age.compareTo(y.age) match { case 0 => x.name.compareTo(y.name) case o => o } } // Building a cats.Order from it implicit val catsOrderForPerson: Order[Person] = Order.fromOrdering
You can also do that in reverse, so you can prefer
cats.Order
(due to Cats also exposing laws and tests for free) and build a ScalaOrdering
when needed:val scalaOrdering = catsOrderForPerson.toOrdering
- key
is the function that returns the key for which the given ordering is defined
- K
is the cats.Order type class instance that's going to be used for comparing elements
- returns
the minimum element of the source stream, relative to its key generated by the given function and the given ordering
- Definition Classes
- Observable
- final def minL[AA >: A](implicit A: Order[AA]): Task[Option[AA]]
Given a cats.Order over the stream's elements, returns the minimum element in the stream.
Given a cats.Order over the stream's elements, returns the minimum element in the stream.
Example
// Needed to bring the standard Order instances in scope: import cats.implicits._ // Yields Some(3) val stream1 = Observable(10, 7, 6, 8, 20, 3, 5).minL // Yields None val stream2 = Observable.empty[Int].minL
Cats Order and Scala Interop
Monix prefers to work with cats.Order for assessing the order of elements that have an ordering defined, instead of scala.math.Ordering.
We do this for consistency, as Monix is now building on top of Cats. This may change in the future, depending on what happens with typelevel/cats#2455.
Building a
cats.Order
is easy to do if you already have a ScalaOrdering
instance:import cats.Order case class Person(name: String, age: Int) // Starting from a Scala Ordering implicit val scalaOrderingForPerson: Ordering[Person] = new Ordering[Person] { def compare(x: Person, y: Person): Int = x.age.compareTo(y.age) match { case 0 => x.name.compareTo(y.name) case o => o } } // Building a cats.Order from it implicit val catsOrderForPerson: Order[Person] = Order.fromOrdering
You can also do that in reverse, so you can prefer
cats.Order
(due to Cats also exposing laws and tests for free) and build a ScalaOrdering
when needed:val scalaOrdering = catsOrderForPerson.toOrdering
- A
is the cats.Order type class instance that's going to be used for comparing elements
- returns
the minimum element of the source stream, relative to the defined
Order
- Definition Classes
- Observable
- See also
minF for the version that returns an observable instead of a
Task
.
- final def multicast[B >: A, R](pipe: Pipe[B, R])(implicit s: Scheduler): ConnectableObservable[R]
Converts this observable into a multicast observable, useful for turning a cold observable into a hot one (i.e.
Converts this observable into a multicast observable, useful for turning a cold observable into a hot one (i.e. whose source is shared by all observers).
UNSAFE WARNING: this operation can trigger the execution of side effects, which breaks referential transparency and is thus not a pure function.
For FP code these functions shouldn't be called until "the end of the world", which is to say at the end of the program (for a console app), or at the end of a web request.
Otherwise for modifying or operating on streams, prefer its pure functions like publishSelector for sharing the data source, or map or flatMap for operating on its events. Or in case of specialized logic, prefer to suspend these side effects via Observable.suspend. Monix also provides Task which can also be used for suspending side effects and the
Task
was built to interop well withObservable
.- Definition Classes
- Observable
- Annotations
- @UnsafeBecauseImpure()
- final def ne(arg0: AnyRef): Boolean
- Definition Classes
- AnyRef
- final def nonEmpty: Observable[Boolean]
Returns an Observable that emits false if the source Observable is empty, otherwise true.
Returns an Observable that emits false if the source Observable is empty, otherwise true.
- Definition Classes
- Observable
- final def nonEmptyL: Task[Boolean]
Returns a task that emits
false
if the source observable is empty, otherwisetrue
.Returns a task that emits
false
if the source observable is empty, otherwisetrue
.- Definition Classes
- Observable
- final def notify(): Unit
- Definition Classes
- AnyRef
- Annotations
- @native() @HotSpotIntrinsicCandidate()
- final def notifyAll(): Unit
- Definition Classes
- AnyRef
- Annotations
- @native() @HotSpotIntrinsicCandidate()
- final def observeOn[B >: A](s: Scheduler, os: OverflowStrategy[B]): Observable[B]
Operator that specifies a different Scheduler, on which subscribers will observe events, instead of the default one.
Operator that specifies a different Scheduler, on which subscribers will observe events, instead of the default one.
This overloaded version of
observeOn
takes an extra OverflowStrategy parameter specifying the behavior of the underlying buffer.- s
is the alternative
Scheduler
reference to use for observing events- os
is the OverflowStrategy to apply to the underlying buffer
- Definition Classes
- Observable
- See also
observeOn(Scheduler) for the version that does not take an
OverflowStrategy
parameter.
- final def observeOn(s: Scheduler): Observable[A]
Operator that specifies a different Scheduler, on which subscribers will observe events, instead of the default one.
Operator that specifies a different Scheduler, on which subscribers will observe events, instead of the default one.
An
Observable
with an appliedobserveOn
call will forward events into a buffer that uses the specifiedScheduler
reference to cycle through events and to makeonNext
calls to downstream listeners.Example:
import monix.execution.Scheduler import monix.execution.Scheduler.Implicits.global val io = Scheduler.io("my-io") Observable(1, 2, 3).map(_ + 1) .observeOn(io) .foreach(x => println(x))
In the above example the first
map
(whatever comes before theobserveOn
call) gets executed using the defaultScheduler
(might execute on the current thread even), however theforeach
that's specified afterobserveOn
will get executed on the indicatedScheduler
.NOTE: this operator does not guarantee that downstream listeners will actually use the specified
Scheduler
to process events, because this depends on the rest of the pipeline. E.g. this will not work OK:import monix.reactive.OverflowStrategy.Unbounded Observable.suspend(???) .observeOn(io).asyncBoundary(Unbounded)
This sample might not do what a user of
observeOn
would want. Indeed the implementation will use the providedio
reference for callingonNext
/onComplete
/onError
events, however because of the following asynchronous boundary created the actual listeners will probably end up being execute on a differentScheduler
.The underlying implementation uses a buffer to forward events. The OverflowStrategy being applied is the default one.
- s
is the alternative
Scheduler
reference to use for observing events
- Definition Classes
- Observable
- See also
observeOn(Scheduler, OverflowStrategy) for the version that allows customizing the OverflowStrategy being used by the underlying buffer.
- final def onCancelTriggerError: Observable[A]
If the connection is cancelled then trigger a
CancellationException
.If the connection is cancelled then trigger a
CancellationException
.A connection can be cancelled with the help of the Cancelable returned on subscribe.
Because the cancellation is effectively concurrent with the signals the Observer receives and because we need to uphold the contract, this operator will effectively synchronize access to onNext, onComplete and onError. It will also watch out for asynchronous Stop events.
In other words, this operator does heavy synchronization, can prove to be inefficient and you should avoid using it because the signaled error can interfere with functionality from other operators that use cancellation internally and cancellation in general is a side-effecting operation that should be avoided, unless it's necessary.
- Definition Classes
- Observable
- final def onErrorFallbackTo[B >: A](that: Observable[B]): Observable[B]
Returns an Observable that mirrors the behavior of the source, unless the source is terminated with an
onError
, in which case the streaming of events continues with the specified backup sequence.Returns an Observable that mirrors the behavior of the source, unless the source is terminated with an
onError
, in which case the streaming of events continues with the specified backup sequence.The created Observable mirrors the behavior of the source in case the source does not end with an error.
NOTE that compared with
onErrorResumeNext
from Rx.NET, the streaming is not resumed in case the source is terminated normally with anonComplete
.- that
is a backup sequence that's being subscribed in case the source terminates with an error.
- Definition Classes
- Observable
- final def onErrorHandle[B >: A](f: (Throwable) => B): Observable[B]
Returns an observable that mirrors the behavior of the source, unless the source is terminated with an
onError
, in which case the streaming of events fallbacks to an observable emitting a single element generated by the backup function.Returns an observable that mirrors the behavior of the source, unless the source is terminated with an
onError
, in which case the streaming of events fallbacks to an observable emitting a single element generated by the backup function.See onErrorRecover for the version that takes a partial function as a parameter.
- f
- a function that matches errors with a backup element that is emitted when the source throws an error.
- Definition Classes
- Observable
- final def onErrorHandleWith[B >: A](f: (Throwable) => Observable[B]): Observable[B]
Returns an Observable that mirrors the behavior of the source, unless the source is terminated with an
onError
, in which case the streaming of events continues with the specified backup sequence generated by the given function.Returns an Observable that mirrors the behavior of the source, unless the source is terminated with an
onError
, in which case the streaming of events continues with the specified backup sequence generated by the given function.See onErrorRecoverWith for the version that takes a partial function as a parameter.
- f
is a function that matches errors with a backup throwable that is subscribed when the source throws an error.
- Definition Classes
- Observable
- final def onErrorRecover[B >: A](pf: PartialFunction[Throwable, B]): Observable[B]
Returns an observable that mirrors the behavior of the source, unless the source is terminated with an
onError
, in which case the streaming of events fallbacks to an observable emitting a single element generated by the backup function.Returns an observable that mirrors the behavior of the source, unless the source is terminated with an
onError
, in which case the streaming of events fallbacks to an observable emitting a single element generated by the backup function.The created Observable mirrors the behavior of the source in case the source does not end with an error or if the thrown
Throwable
is not matched.See onErrorHandle for the version that takes a total function as a parameter.
- pf
is a function that matches errors with a backup element that is emitted when the source throws an error.
- Definition Classes
- Observable
- final def onErrorRecoverWith[B >: A](pf: PartialFunction[Throwable, Observable[B]]): Observable[B]
Returns an Observable that mirrors the behavior of the source, unless the source is terminated with an
onError
, in which case the streaming of events continues with the specified backup sequence generated by the given function.Returns an Observable that mirrors the behavior of the source, unless the source is terminated with an
onError
, in which case the streaming of events continues with the specified backup sequence generated by the given function.The created Observable mirrors the behavior of the source in case the source does not end with an error or if the thrown
Throwable
is not matched.See onErrorHandleWith for the version that takes a total function as a parameter.
- pf
is a function that matches errors with a backup throwable that is subscribed when the source throws an error.
- Definition Classes
- Observable
- final def onErrorRestart(maxRetries: Long): Observable[A]
Returns an Observable that mirrors the behavior of the source, unless the source is terminated with an
onError
, in which case it tries subscribing to the source again in the hope that it will complete without an error.Returns an Observable that mirrors the behavior of the source, unless the source is terminated with an
onError
, in which case it tries subscribing to the source again in the hope that it will complete without an error.The number of retries is limited by the specified
maxRetries
parameter, so for an Observable that always ends in error the total number of subscriptions that will eventually happen ismaxRetries + 1
.- Definition Classes
- Observable
- final def onErrorRestartIf(p: (Throwable) => Boolean): Observable[A]
Returns an Observable that mirrors the behavior of the source, unless the source is terminated with an
onError
, in which case it tries subscribing to the source again in the hope that it will complete without an error.Returns an Observable that mirrors the behavior of the source, unless the source is terminated with an
onError
, in which case it tries subscribing to the source again in the hope that it will complete without an error.The given predicate establishes if the subscription should be retried or not.
- Definition Classes
- Observable
- final def onErrorRestartUnlimited: Observable[A]
Returns an Observable that mirrors the behavior of the source, unless the source is terminated with an
onError
, in which case it tries subscribing to the source again in the hope that it will complete without an error.Returns an Observable that mirrors the behavior of the source, unless the source is terminated with an
onError
, in which case it tries subscribing to the source again in the hope that it will complete without an error.NOTE: The number of retries is unlimited, so something like
Observable.error(new RuntimeException).onErrorRestartUnlimited
will loop forever.- Definition Classes
- Observable
- final def pipeThrough[I >: A, B](pipe: Pipe[I, B]): Observable[B]
Given a Pipe, transform the source observable with it.
Given a Pipe, transform the source observable with it.
- Definition Classes
- Observable
- final def pipeThroughSelector[S >: A, B, R](pipe: Pipe[S, B], f: (Observable[B]) => Observable[R]): Observable[R]
Returns an observable that emits the results of invoking a specified selector on items emitted by a ConnectableObservable, which shares a single subscription to the underlying sequence.
Returns an observable that emits the results of invoking a specified selector on items emitted by a ConnectableObservable, which shares a single subscription to the underlying sequence.
This operators takes a possibly pure Observable, transforms it to Hot Observable in the scope of supplied function and then returns a pure Observable again. The function allows specyfing underlying monix.reactive.subjects.Subject by means of monix.reactive.Pipe.
Example
import monix.reactive._ import monix.eval.Task import scala.concurrent.duration._ implicit val os: OverflowStrategy[Nothing] = OverflowStrategy.Default val obs = Observable(1, 2, 3) .doOnNext(i => Task(println(s"Produced $$i")).delayExecution(1.second)) def consume(name: String, obs: Observable[Int]): Observable[Unit] = obs.mapEval(i => Task(println(s"$$name: got $$i"))) obs.pipeThroughSelector(Pipe.replay[Int], { (hot: Observable[Int]) => Observable( consume("Consumer 1", hot), consume("Consumer 2", hot).delayExecution(2.second) ).merge })
Output
Produced 1 Consumer 1: got 1 Consumer 2: got 1 Produced 2 Consumer 1: got 2 Consumer 2: got 2 Produced 3 Consumer 1: got 3 Consumer 2: got 3
Note how Consumer 2 received the same amount of elements as Consumer 1 despite subscribing later because of underlying ReplaySubject.
- pipe
is the Pipe used to transform the source into a multicast (hot) observable that can be shared in the selector function
- f
is a selector function that can use the multicasted source sequence as many times as needed, without causing multiple subscriptions to the source sequence. Observers to the given source will receive all notifications of the source from the time of the subscription forward.
- Definition Classes
- Observable
- final def prepend[B >: A](elem: B): Observable[B]
Creates a new Observable that emits the given element and then it also emits the events of the source (prepend operation).
Creates a new Observable that emits the given element and then it also emits the events of the source (prepend operation).
- Definition Classes
- Observable
- final def publish(implicit s: Scheduler): ConnectableObservable[A]
Converts this observable into a multicast observable, useful for turning a cold observable into a hot one (i.e.
Converts this observable into a multicast observable, useful for turning a cold observable into a hot one (i.e. whose source is shared by all observers). The underlying subject used is a PublishSubject.
UNSAFE WARNING: this operation can trigger the execution of side effects, which breaks referential transparency and is thus not a pure function.
For FP code these functions shouldn't be called until "the end of the world", which is to say at the end of the program (for a console app), or at the end of a web request.
Otherwise for modifying or operating on streams, prefer its pure functions like publishSelector for sharing the data source, or map or flatMap for operating on its events. Or in case of specialized logic, prefer to suspend these side effects via Observable.suspend. Monix also provides Task which can also be used for suspending side effects and the
Task
was built to interop well withObservable
.- Definition Classes
- Observable
- Annotations
- @UnsafeBecauseImpure()
- final def publishLast(implicit s: Scheduler): ConnectableObservable[A]
Converts this observable into a multicast observable, useful for turning a cold observable into a hot one (i.e.
Converts this observable into a multicast observable, useful for turning a cold observable into a hot one (i.e. whose source is shared by all observers). The underlying subject used is a AsyncSubject.
UNSAFE WARNING: this operation can trigger the execution of side effects, which breaks referential transparency and is thus not a pure function.
For FP code these functions shouldn't be called until "the end of the world", which is to say at the end of the program (for a console app), or at the end of a web request.
Otherwise for modifying or operating on streams, prefer its pure functions like publishSelector for sharing the data source, or map or flatMap for operating on its events. Or in case of specialized logic, prefer to suspend these side effects via Observable.suspend. Monix also provides Task which can also be used for suspending side effects and the
Task
was built to interop well withObservable
.- Definition Classes
- Observable
- Annotations
- @UnsafeBecauseImpure()
- final def publishSelector[R](f: (Observable[A]) => Observable[R]): Observable[R]
Returns an observable that emits the results of invoking a specified selector on items emitted by a ConnectableObservable backed by PublishSubject which shares a single subscription to the underlying sequence.
Returns an observable that emits the results of invoking a specified selector on items emitted by a ConnectableObservable backed by PublishSubject which shares a single subscription to the underlying sequence.
This operators takes a possibly pure Observable, transforms it to Hot Observable in the scope of supplied function and then returns a pure Observable again.
Example
import monix.reactive._ import monix.eval.Task import scala.concurrent.duration._ implicit val os: OverflowStrategy[Nothing] = OverflowStrategy.Default val obs = Observable(1, 2, 3) .doOnNext(i => Task(println(s"Produced $$i")).delayExecution(1.second)) def consume(name: String, obs: Observable[Int]): Observable[Unit] = obs.mapEval(i => Task(println(s"$$name: got $$i"))) obs.publishSelector { hot => Observable( consume("Consumer 1", hot), consume("Consumer 2", hot).delayExecution(2.second) ).merge }
Output
Produced 1 Consumer 1: got 1 Produced 2 Consumer 1: got 2 Consumer 2: got 2 Produced 3 Consumer 1: got 3 Consumer 2: got 3
Note how Consumer 2 received less elements because it subscribed later.
- f
is a selector function that can use the multicasted source sequence as many times as needed, without causing multiple subscriptions to the source sequence. Observers to the given source will receive all notifications of the source from the time of the subscription forward.
- Definition Classes
- Observable
- See also
pipeThroughSelector for a version that allows specifying a type of underlying Subject.
- final def reduce[B >: A](op: (B, B) => B): Observable[B]
Applies a binary operator to a start value and all elements of this Observable, going left to right and returns a new Observable that emits only one item before
onComplete
.Applies a binary operator to a start value and all elements of this Observable, going left to right and returns a new Observable that emits only one item before
onComplete
.- Definition Classes
- Observable
- final def repeat: Observable[A]
Repeats the items emitted by the source continuously.
Repeats the items emitted by the source continuously. It caches the generated items until
onComplete
and repeats them forever.It terminates either on error or if the source is empty.
- Definition Classes
- Observable
- final def replay(bufferSize: Int)(implicit s: Scheduler): ConnectableObservable[A]
Converts this observable into a multicast observable, useful for turning a cold observable into a hot one (i.e.
Converts this observable into a multicast observable, useful for turning a cold observable into a hot one (i.e. whose source is shared by all observers). The underlying subject used is a ReplaySubject.
UNSAFE WARNING: this operation can trigger the execution of side effects, which breaks referential transparency and is thus not a pure function.
For FP code these functions shouldn't be called until "the end of the world", which is to say at the end of the program (for a console app), or at the end of a web request.
Otherwise for modifying or operating on streams, prefer its pure functions like publishSelector for sharing the data source, or map or flatMap for operating on its events. Or in case of specialized logic, prefer to suspend these side effects via Observable.suspend. Monix also provides Task which can also be used for suspending side effects and the
Task
was built to interop well withObservable
.- bufferSize
is the size of the buffer limiting the number of items that can be replayed (on overflow the head starts being dropped)
- Definition Classes
- Observable
- Annotations
- @UnsafeBecauseImpure()
- final def replay(implicit s: Scheduler): ConnectableObservable[A]
Converts this observable into a multicast observable, useful for turning a cold observable into a hot one (i.e.
Converts this observable into a multicast observable, useful for turning a cold observable into a hot one (i.e. whose source is shared by all observers). The underlying subject used is a ReplaySubject.
UNSAFE WARNING: this operation can trigger the execution of side effects, which breaks referential transparency and is thus not a pure function.
For FP code these functions shouldn't be called until "the end of the world", which is to say at the end of the program (for a console app), or at the end of a web request.
Otherwise for modifying or operating on streams, prefer its pure functions like publishSelector for sharing the data source, or map or flatMap for operating on its events. Or in case of specialized logic, prefer to suspend these side effects via Observable.suspend. Monix also provides Task which can also be used for suspending side effects and the
Task
was built to interop well withObservable
.- Definition Classes
- Observable
- Annotations
- @UnsafeBecauseImpure()
- final def restartUntil(p: (A) => Boolean): Observable[A]
Keeps restarting / resubscribing the source until the predicate returns
true
for the the first emitted element, after which it starts mirroring the source.Keeps restarting / resubscribing the source until the predicate returns
true
for the the first emitted element, after which it starts mirroring the source.- Definition Classes
- Observable
- final def runAsyncGetFirst(implicit s: Scheduler, opts: Options = defaultOptions): CancelableFuture[Option[A]]
Creates a new CancelableFuture that upon execution will signal the first generated element of the source observable.
Creates a new CancelableFuture that upon execution will signal the first generated element of the source observable. Returns an
Option
because the source can be empty.UNSAFE WARNING: this operation can trigger the execution of side effects, which breaks referential transparency and is thus not a pure function.
For FP code these functions shouldn't be called until "the end of the world", which is to say at the end of the program (for a console app), or at the end of a web request.
Otherwise for modifying or operating on streams, prefer its pure functions like publishSelector for sharing the data source, or map or flatMap for operating on its events. Or in case of specialized logic, prefer to suspend these side effects via Observable.suspend. Monix also provides Task which can also be used for suspending side effects and the
Task
was built to interop well withObservable
.- Definition Classes
- Observable
- Annotations
- @UnsafeBecauseImpure()
- final def runAsyncGetLast(implicit s: Scheduler, opts: Options = defaultOptions): CancelableFuture[Option[A]]
Creates a new CancelableFuture that upon execution will signal the last generated element of the source observable.
Creates a new CancelableFuture that upon execution will signal the last generated element of the source observable. Returns an
Option
because the source can be empty.UNSAFE WARNING: this operation can trigger the execution of side effects, which breaks referential transparency and is thus not a pure function.
For FP code these functions shouldn't be called until "the end of the world", which is to say at the end of the program (for a console app), or at the end of a web request.
Otherwise for modifying or operating on streams, prefer its pure functions like publishSelector for sharing the data source, or map or flatMap for operating on its events. Or in case of specialized logic, prefer to suspend these side effects via Observable.suspend. Monix also provides Task which can also be used for suspending side effects and the
Task
was built to interop well withObservable
.- Definition Classes
- Observable
- Annotations
- @UnsafeBecauseImpure()
- final def sample(period: FiniteDuration): Observable[A]
Emit the most recent items emitted by the source within periodic time intervals.
Emit the most recent items emitted by the source within periodic time intervals.
Use the
sample
operator to periodically look at an observable to see what item it has most recently emitted since the previous sampling. Note that if the source observable has emitted no items since the last time it was sampled, the observable that results from thesample
operator will emit no item for that sampling period.Usage:
import scala.concurrent.duration._ // emits 3, 8, 10 in 1 second intervals Observable.fromIterable(0 to 10) // without delay, it would return only 10 .delayOnNext(200.millis) .sample(1.second)
- period
the timespan at which sampling occurs
- Definition Classes
- Observable
- See also
sampleBy for fine control
sampleRepeated for repeating the last value on silence
throttle for a version that allows to specify number of elements processed by a period and does not drop any elements
- final def sampleBy[B](sampler: Observable[B]): Observable[A]
Returns an observable that, when the specified sampler emits an item or completes, emits the most recently emitted item (if any) emitted by the source since the previous emission from the sampler.
Returns an observable that, when the specified sampler emits an item or completes, emits the most recently emitted item (if any) emitted by the source since the previous emission from the sampler.
Use the
sampleBy
operator to periodically look at an observable to see what item it has most recently emitted since the previous sampling. Note that if the source observable has emitted no items since the last time it was sampled, the observable that results from thesampleBy
operator will emit no item.- sampler
- the observable to use for sampling the source
- Definition Classes
- Observable
- See also
sample for periodic sampling
sampleRepeatedBy for repeating the last value on silence
- final def sampleRepeated(period: FiniteDuration): Observable[A]
Emit the most recent items emitted by an observable within periodic time intervals.
Emit the most recent items emitted by an observable within periodic time intervals. If no new value has been emitted since the last time it was sampled, it signals the last emitted value anyway.
- period
the timespan at which sampling occurs
- Definition Classes
- Observable
- See also
sample for a variant that doesn't repeat the last value on silence
sampleRepeatedBy for fine control
- final def sampleRepeatedBy[B](sampler: Observable[B]): Observable[A]
Returns an observable that, when the specified sampler observable emits an item or completes, emits the most recently emitted item (if any) emitted by the source Observable since the previous emission from the sampler observable.
Returns an observable that, when the specified sampler observable emits an item or completes, emits the most recently emitted item (if any) emitted by the source Observable since the previous emission from the sampler observable. If no new value has been emitted since the last time it was sampled, it signals the last emitted value anyway.
- sampler
- the Observable to use for sampling the source Observable
- Definition Classes
- Observable
- See also
sampleBy for a variant that doesn't repeat the last value on silence
sampleRepeated for a periodic sampling
- final def scan[S](seed: => S)(op: (S, A) => S): Observable[S]
Applies a binary operator to a start value and all elements of this Observable, going left to right and returns a new Observable that emits on each step the result of the applied function.
Applies a binary operator to a start value and all elements of this Observable, going left to right and returns a new Observable that emits on each step the result of the applied function.
Similar to foldLeft, but emits the state on each step. Useful for modeling finite state machines.
- Definition Classes
- Observable
- See also
scan0 for the version that emits seed element at the beginning
- final def scan0[S](seed: => S)(op: (S, A) => S): Observable[S]
Applies a binary operator to a start value and all elements of this Observable, going left to right and returns a new Observable that emits on each step the result of the applied function.
Applies a binary operator to a start value and all elements of this Observable, going left to right and returns a new Observable that emits on each step the result of the applied function.
This is a version of scan that emits seed element at the beginning, similar to
scanLeft
on Scala collections- Definition Classes
- Observable
- final def scanEval[S](seed: Task[S])(op: (S, A) => Task[S]): Observable[S]
Applies a binary operator to a start value and all elements of this stream, going left to right and returns a new stream that emits on each step the result of the applied function.
Applies a binary operator to a start value and all elements of this stream, going left to right and returns a new stream that emits on each step the result of the applied function.
Similar with scan, but this can suspend and evaluate side effects with Task, thus allowing for asynchronous data processing.
Similar to foldLeft and foldWhileLeft, but emits the state on each step. Useful for modeling finite state machines.
Example showing how state can be evolved and acted upon:
import monix.eval.Task sealed trait State[+A] { def count: Int } case object Init extends State[Nothing] { def count = 0 } case class Current[A](current: Option[A], count: Int) extends State[A] case class Person(id: Int, name: String) // TODO: to implement! def requestPersonDetails(id: Int): Task[Option[Person]] = Task.raiseError(new NotImplementedError) // TODO: to implement val source: Observable[Int] = Observable.raiseError(new NotImplementedError) // Initial state val seed = Task.pure(Init : State[Person]) val scanned = source.scanEval(seed) { (state, id) => requestPersonDetails(id).map { person => state match { case Init => Current(person, 1) case Current(_, count) => Current(person, count + 1) } } } val filtered = scanned .takeWhile(_.count < 10) .collect { case Current(a, _) => a }
- seed
is the initial state
- op
is the function that evolves the current state
- returns
a new observable that emits all intermediate states being resulted from applying the given function
- Definition Classes
- Observable
- See also
scanEval0 for the version that emits seed element at the beginning
scan for the version that does not require using
Task
in the provided operator
- final def scanEval0[S](seed: Task[S])(op: (S, A) => Task[S]): Observable[S]
Applies a binary operator to a start value and all elements of this stream, going left to right and returns a new stream that emits on each step the result of the applied function.
Applies a binary operator to a start value and all elements of this stream, going left to right and returns a new stream that emits on each step the result of the applied function.
This is a version of scanEval that emits seed element at the beginning.
- Definition Classes
- Observable
- final def scanEval0F[F[_], S](seed: F[S])(op: (S, A) => F[S])(implicit F: TaskLike[F], A: Applicative[F]): Observable[S]
Applies a binary operator to a start value and all elements of this stream, going left to right and returns a new stream that emits on each step the result of the applied function.
Applies a binary operator to a start value and all elements of this stream, going left to right and returns a new stream that emits on each step the result of the applied function.
This is a version of scanEvalF that emits seed element at the beginning, similar to
scanLeft
on Scala collections- Definition Classes
- Observable
- final def scanEvalF[F[_], S](seed: F[S])(op: (S, A) => F[S])(implicit F: TaskLike[F]): Observable[S]
Applies a binary operator to a start value and all elements of this stream, going left to right and returns a new stream that emits on each step the result of the applied function.
Applies a binary operator to a start value and all elements of this stream, going left to right and returns a new stream that emits on each step the result of the applied function.
Similar with scan, but this can suspend and evaluate side effects with an
F[_]
data type that implements thecats.effect.Effect
type class, thus allowing for lazy or asynchronous data processing.Similar to foldLeft and foldWhileLeft, but emits the state on each step. Useful for modeling finite state machines.
Example showing how state can be evolved and acted upon:
// Using cats.effect.IO for evaluating our side effects import cats.effect.IO sealed trait State[+A] { def count: Int } case object Init extends State[Nothing] { def count = 0 } case class Current[A](current: Option[A], count: Int) extends State[A] case class Person(id: Int, name: String) // TODO: to implement! def requestPersonDetails(id: Int): IO[Option[Person]] = IO.raiseError(new NotImplementedError) // TODO: to implement val source: Observable[Int] = Observable.raiseError(new NotImplementedError) // Initial state val seed = IO.pure(Init : State[Person]) val scanned = source.scanEvalF(seed) { (state, id) => requestPersonDetails(id).map { person => state match { case Init => Current(person, 1) case Current(_, count) => Current(person, count + 1) } } } val filtered = scanned .takeWhile(_.count < 10) .collect { case Current(a, _) => a }
- seed
is the initial state
- op
is the function that evolves the current state
- F
is the
cats.effect.Effect
type class implementation for typeF
, which controls the evaluation.F
can be a data type such as monix.eval.Task orcats.effect.IO
, which implementEffect
.- returns
a new observable that emits all intermediate states being resulted from applying the given function
- Definition Classes
- Observable
- See also
scanEval0F for the version that emits seed element at the beginning
scan for the synchronous, non-lazy version, or scanEval for the Task-specialized version.
- final def scanMap[B](f: (A) => B)(implicit B: Monoid[B]): Observable[B]
Given a mapping function that returns a
B
type for which we have a cats.Monoid instance, returns a new stream that folds the incoming elements of the sources using the providedMonoid[B].combine
, with the initial seed being theMonoid[B].empty
value, emitting the generated values at each step.Given a mapping function that returns a
B
type for which we have a cats.Monoid instance, returns a new stream that folds the incoming elements of the sources using the providedMonoid[B].combine
, with the initial seed being theMonoid[B].empty
value, emitting the generated values at each step.Equivalent with scan applied with the given cats.Monoid, so given our
f
mapping function returns aB
, this law holds:val B = implicitly[Monoid[B]] stream.scanMap(f) <-> stream.scan(B.empty)(B.combine)
Example:
import cats.implicits._ // Yields 2, 6, 12, 20, 30, 42 val stream = Observable(1, 2, 3, 4, 5, 6).scanMap(x => x * 2)
- f
is the mapping function applied to every incoming element of this
Observable
before folding usingMonoid[B].combine
- returns
a new
Observable
that emits all intermediate states being resulted from applyingMonoid[B].combine
function
- Definition Classes
- Observable
- final def scanMap0[B](f: (A) => B)(implicit B: Monoid[B]): Observable[B]
Given a mapping function that returns a
B
type for which we have a cats.Monoid instance, returns a new stream that folds the incoming elements of the sources using the providedMonoid[B].combine
, with the initial seed being theMonoid[B].empty
value, emitting the generated values at each step.Given a mapping function that returns a
B
type for which we have a cats.Monoid instance, returns a new stream that folds the incoming elements of the sources using the providedMonoid[B].combine
, with the initial seed being theMonoid[B].empty
value, emitting the generated values at each step.This is a version of scanMap that emits seed element at the beginning.
- Definition Classes
- Observable
- final def share(implicit s: Scheduler): Observable[A]
Returns a new Observable that multi-casts (shares) the original Observable between multiple consumers.
Returns a new Observable that multi-casts (shares) the original Observable between multiple consumers.
UNSAFE WARNING: this operation can trigger the execution of side effects, which breaks referential transparency and is thus not a pure function.
For FP code these functions shouldn't be called until "the end of the world", which is to say at the end of the program (for a console app), or at the end of a web request.
Otherwise for modifying or operating on streams, prefer its pure functions like publishSelector for sharing the data source, or map or flatMap for operating on its events. Or in case of specialized logic, prefer to suspend these side effects via Observable.suspend. Monix also provides Task which can also be used for suspending side effects and the
Task
was built to interop well withObservable
.- Definition Classes
- Observable
- Annotations
- @UnsafeBecauseImpure()
- final def startWith[B >: A](elems: Seq[B]): Observable[B]
Creates a new Observable that emits the given elements and then it also emits the events of the source (prepend operation).
Creates a new Observable that emits the given elements and then it also emits the events of the source (prepend operation).
- Definition Classes
- Observable
- final def subscribe(nextFn: (A) => Future[Ack], errorFn: (Throwable) => Unit, completedFn: () => Unit)(implicit s: Scheduler): Cancelable
Subscribes to the stream.
Subscribes to the stream.
UNSAFE WARNING: this operation can trigger the execution of side effects, which breaks referential transparency and is thus not a pure function.
For FP code these functions shouldn't be called until "the end of the world", which is to say at the end of the program (for a console app), or at the end of a web request.
Otherwise for modifying or operating on streams, prefer its pure functions like publishSelector for sharing the data source, or map or flatMap for operating on its events. Or in case of specialized logic, prefer to suspend these side effects via Observable.suspend. Monix also provides Task which can also be used for suspending side effects and the
Task
was built to interop well withObservable
.- returns
a subscription that can be used to cancel the streaming.
- Definition Classes
- Observable
- Annotations
- @UnsafeBecauseImpure()
- See also
consumeWith for another way of consuming observables
- final def subscribe(nextFn: (A) => Future[Ack])(implicit s: Scheduler): Cancelable
Subscribes to the stream.
Subscribes to the stream.
UNSAFE WARNING: this operation can trigger the execution of side effects, which breaks referential transparency and is thus not a pure function.
For FP code these functions shouldn't be called until "the end of the world", which is to say at the end of the program (for a console app), or at the end of a web request.
Otherwise for modifying or operating on streams, prefer its pure functions like publishSelector for sharing the data source, or map or flatMap for operating on its events. Or in case of specialized logic, prefer to suspend these side effects via Observable.suspend. Monix also provides Task which can also be used for suspending side effects and the
Task
was built to interop well withObservable
.- returns
a subscription that can be used to cancel the streaming.
- Definition Classes
- Observable
- Annotations
- @UnsafeBecauseImpure()
- See also
consumeWith for another way of consuming observables
- final def subscribe()(implicit s: Scheduler): Cancelable
Subscribes to the stream.
Subscribes to the stream.
UNSAFE WARNING: this operation can trigger the execution of side effects, which breaks referential transparency and is thus not a pure function.
For FP code these functions shouldn't be called until "the end of the world", which is to say at the end of the program (for a console app), or at the end of a web request.
Otherwise for modifying or operating on streams, prefer its pure functions like publishSelector for sharing the data source, or map or flatMap for operating on its events. Or in case of specialized logic, prefer to suspend these side effects via Observable.suspend. Monix also provides Task which can also be used for suspending side effects and the
Task
was built to interop well withObservable
.- returns
a subscription that can be used to cancel the streaming.
- Definition Classes
- Observable
- Annotations
- @UnsafeBecauseImpure()
- See also
consumeWith for another way of consuming observables
- final def subscribe(nextFn: (A) => Future[Ack], errorFn: (Throwable) => Unit)(implicit s: Scheduler): Cancelable
Subscribes to the stream.
Subscribes to the stream.
UNSAFE WARNING: this operation can trigger the execution of side effects, which breaks referential transparency and is thus not a pure function.
For FP code these functions shouldn't be called until "the end of the world", which is to say at the end of the program (for a console app), or at the end of a web request.
Otherwise for modifying or operating on streams, prefer its pure functions like publishSelector for sharing the data source, or map or flatMap for operating on its events. Or in case of specialized logic, prefer to suspend these side effects via Observable.suspend. Monix also provides Task which can also be used for suspending side effects and the
Task
was built to interop well withObservable
.- returns
a subscription that can be used to cancel the streaming.
- Definition Classes
- Observable
- Annotations
- @UnsafeBecauseImpure()
- See also
consumeWith for another way of consuming observables
- final def subscribe(subscriber: Subscriber[A]): Cancelable
Subscribes to the stream.
Subscribes to the stream.
UNSAFE WARNING: this operation can trigger the execution of side effects, which breaks referential transparency and is thus not a pure function.
For FP code these functions shouldn't be called until "the end of the world", which is to say at the end of the program (for a console app), or at the end of a web request.
Otherwise for modifying or operating on streams, prefer its pure functions like publishSelector for sharing the data source, or map or flatMap for operating on its events. Or in case of specialized logic, prefer to suspend these side effects via Observable.suspend. Monix also provides Task which can also be used for suspending side effects and the
Task
was built to interop well withObservable
.- returns
a subscription that can be used to cancel the streaming.
- Definition Classes
- Observable
- Annotations
- @UnsafeBecauseImpure()
- See also
consumeWith for another way of consuming observables
- final def subscribe(observer: Observer[A])(implicit s: Scheduler): Cancelable
Subscribes to the stream.
Subscribes to the stream.
UNSAFE WARNING: this operation can trigger the execution of side effects, which breaks referential transparency and is thus not a pure function.
For FP code these functions shouldn't be called until "the end of the world", which is to say at the end of the program (for a console app), or at the end of a web request.
Otherwise for modifying or operating on streams, prefer its pure functions like publishSelector for sharing the data source, or map or flatMap for operating on its events. Or in case of specialized logic, prefer to suspend these side effects via Observable.suspend. Monix also provides Task which can also be used for suspending side effects and the
Task
was built to interop well withObservable
.- returns
a subscription that can be used to cancel the streaming.
- Definition Classes
- Observable
- Annotations
- @UnsafeBecauseImpure()
- See also
consumeWith for another way of consuming observables
- final def subscribeOn(scheduler: Scheduler): Observable[A]
Returns a new Observable that uses the specified
Scheduler
for initiating the subscription.Returns a new Observable that uses the specified
Scheduler
for initiating the subscription.This is different from executeOn because the given
scheduler
is only used to start the subscription, but does not override the default Scheduler.- Definition Classes
- Observable
- final def sum[AA >: A](implicit A: Numeric[AA]): Observable[AA]
Given a source that emits numeric values, the
sum
operator sums up all values and at onComplete it emits the total.Given a source that emits numeric values, the
sum
operator sums up all values and at onComplete it emits the total.- Definition Classes
- Observable
- final def sumL[B >: A](implicit B: Numeric[B]): Task[B]
Given a source that emits numeric values, the
sum
operator sums up all values and returns the result.Given a source that emits numeric values, the
sum
operator sums up all values and returns the result.- Definition Classes
- Observable
- final def switch[B](implicit ev: <:<[A, Observable[B]]): Observable[B]
Convert an observable that emits observables into a single observable that emits the items emitted by the most-recently-emitted of those observables.
Convert an observable that emits observables into a single observable that emits the items emitted by the most-recently-emitted of those observables.
Similar with flatten, however the source isn't back-pressured when emitting new events. Instead new events being emitted are cancelling the active child observables.
Equivalence with switchMap
The
switch
operation can be expressed in terms of switchMap, as we have this equivalence:stream.switch <-> stream.switchMap(x => x)
- Definition Classes
- Observable
- See also
the description of switchMap for an example.
- final def switchIfEmpty[B >: A](backup: Observable[B]): Observable[B]
In case the source is empty, switch to the given backup.
In case the source is empty, switch to the given backup.
- Definition Classes
- Observable
- final def switchMap[B](f: (A) => Observable[B]): Observable[B]
Convert an observable that emits observables into a single observable that emits the items emitted by the most-recently-emitted of those observables.
Convert an observable that emits observables into a single observable that emits the items emitted by the most-recently-emitted of those observables.
Similar with concatMap, however the source isn't back-pressured when emitting new events. Instead new events being emitted are cancelling the active child observables.
Example
The
switchMap
can express a lot of cool, time-based operations. For example we can express debounce in terms ofswitchMap
:import scala.concurrent.duration._ def debounce[A](stream: Observable[A], d: FiniteDuration): Observable[A] = stream.switchMap { x => Observable.now(x).delayExecution(d) }
- f
is a generator for the streams that are being merged
- Definition Classes
- Observable
- final def synchronized[T0](arg0: => T0): T0
- Definition Classes
- AnyRef
- final def tail: Observable[A]
Drops the first element of the source observable, emitting the rest.
Drops the first element of the source observable, emitting the rest.
- Definition Classes
- Observable
- final def take(n: Long): Observable[A]
Selects the first
n
elements (from the start).Selects the first
n
elements (from the start).- n
the number of elements to take
- returns
a new Observable that emits only the first
n
elements from the source
- Definition Classes
- Observable
- final def takeByTimespan(timespan: FiniteDuration): Observable[A]
Creates a new Observable that emits the events of the source, only for the specified
timestamp
, after which it completes.Creates a new Observable that emits the events of the source, only for the specified
timestamp
, after which it completes.- timespan
the window of time during which the new Observable is allowed to emit the events of the source
- Definition Classes
- Observable
- final def takeEveryNth(n: Int): Observable[A]
Creates a new Observable that emits every n-th event from the source, dropping intermediary events.
Creates a new Observable that emits every n-th event from the source, dropping intermediary events.
- Definition Classes
- Observable
- final def takeLast(n: Int): Observable[A]
Creates a new observable that only emits the last
n
elements emitted by the source.Creates a new observable that only emits the last
n
elements emitted by the source.In case the source triggers an error, then the underlying buffer gets dropped and the error gets emitted immediately.
- Definition Classes
- Observable
- final def takeUntil(trigger: Observable[Any]): Observable[A]
Creates a new observable that mirrors the source until the given
trigger
emits either an element oronComplete
, after which it is completed.Creates a new observable that mirrors the source until the given
trigger
emits either an element oronComplete
, after which it is completed.The resulting observable is completed as soon as
trigger
emits either anonNext
oronComplete
. Iftrigger
emits anonError
, then the resulting observable is also completed with error.- trigger
is an observable that will cancel the streaming as soon as it emits an event
- Definition Classes
- Observable
- final def takeUntilEval(trigger: Task[_]): Observable[A]
Version of takeUntil that can work with a trigger expressed by a monix.eval.Task
Version of takeUntil that can work with a trigger expressed by a monix.eval.Task
- trigger
task that will cancel the stream as soon as it completes.
- Definition Classes
- Observable
- See also
takeUntil for version that works with Observable.
takeUntilEvalF for version that works with generic
F[_]
powered by monix.eval.TaskLike.
- final def takeUntilEvalF[F[_], B](trigger: F[B])(implicit taskLike: TaskLike[F]): Observable[A]
Version of takeUntil that can work with a trigger expressed by a generic
F[_]
provided an implicit monix.eval.TaskLike exists.Version of takeUntil that can work with a trigger expressed by a generic
F[_]
provided an implicit monix.eval.TaskLike exists.- trigger
operation that will cancel the stream as soon as it completes.
- Definition Classes
- Observable
- See also
takeUntil for version that works with Observable.
takeUntilEval for version that works with monix.eval.Task.
- final def takeWhile(p: (A) => Boolean): Observable[A]
Takes longest prefix of elements that satisfy the given predicate and returns a new Observable that emits those elements.
Takes longest prefix of elements that satisfy the given predicate and returns a new Observable that emits those elements.
- Definition Classes
- Observable
- final def takeWhileInclusive(p: (A) => Boolean): Observable[A]
Takes longest prefix of elements that satisfy the given predicate, inclusive of the value that caused
predicate
to returnfalse
and returns a new Observable that emits those elements.Takes longest prefix of elements that satisfy the given predicate, inclusive of the value that caused
predicate
to returnfalse
and returns a new Observable that emits those elements.- Definition Classes
- Observable
- final def takeWhileNotCanceled(c: BooleanCancelable): Observable[A]
Takes longest prefix of elements while given BooleanCancelable is not canceled and returns a new Observable that emits those elements.
Takes longest prefix of elements while given BooleanCancelable is not canceled and returns a new Observable that emits those elements.
- Definition Classes
- Observable
- final def throttle(period: FiniteDuration, n: Int): Observable[A]
Returns an Observable that emits maximum
n
items per givenperiod
.Returns an Observable that emits maximum
n
items per givenperiod
.Unlike Observable!.throttleLast and Observable!.throttleFirst it does not discard any elements.
If the source observable completes, then the current buffer gets signaled downstream. If the source triggers an error then the current buffer is being dropped and the error gets propagated immediately.
Usage:
import scala.concurrent.duration._ // emits two items per second Observable.fromIterable(0 to 10) .throttle(1.second, 2)
- period
time that has to pass before emiting new items
- n
maximum number of items emitted per given
period
- Definition Classes
- Observable
- final def throttleFirst(interval: FiniteDuration): Observable[A]
Returns an Observable that emits only the first item emitted by the source Observable during sequential time windows of a specified duration.
Returns an Observable that emits only the first item emitted by the source Observable during sequential time windows of a specified duration.
This differs from Observable!.throttleLast in that this only tracks passage of time whereas
throttleLast
ticks at scheduled intervals.Usage:
import scala.concurrent.duration._ // emits 0, 5, 10 in 1 second intervals Observable.fromIterable(0 to 10) // without delay, it would return only 0 .delayOnNext(200.millis) .throttleFirst(1.second)
- interval
time to wait before emitting another item after emitting the last item
- Definition Classes
- Observable
- See also
throttle for a version that allows to specify number of elements processed by a period and does not drop any elements
- final def throttleLast(period: FiniteDuration): Observable[A]
Emit the most recent items emitted by the source within periodic time intervals.
Emit the most recent items emitted by the source within periodic time intervals.
Alias for sample.
Usage:
import scala.concurrent.duration._ // emits 3, 8, 10 in 1 second intervals Observable.fromIterable(0 to 10) // without delay, it would return only 10 .delayOnNext(200.millis) .throttleLast(1.second)
- period
duration of windows within which the last item emitted by the source Observable will be emitted
- Definition Classes
- Observable
- See also
throttle for a version that allows to specify number of elements processed by a period and does not drop any elements
- final def throttleLatest(period: FiniteDuration, emitLast: Boolean): Observable[A]
Emit first element emitted by the source and then emit the most recent items emitted by the source within periodic time intervals.
Emit first element emitted by the source and then emit the most recent items emitted by the source within periodic time intervals. Usage:
import scala.concurrent.duration._ // emits 0 after 200 ms and then 4,9 in 1 sec intervals and 10 after the observable completes Observable.fromIterable(0 to 10) // without delay, it would return only 0, 10 .delayOnNext(200.millis) .throttleLatest(1.second, true)
- period
duration of windows within which the last item emitted by the source Observable will be emitted
- emitLast
if true last element will be emitted when source completes no matter if interval has passed or not
- Definition Classes
- Observable
- final def throttleWithTimeout(timeout: FiniteDuration): Observable[A]
Only emit an item from an observable if a particular timespan has passed without it emitting another item.
Only emit an item from an observable if a particular timespan has passed without it emitting another item.
Note: If the source observable keeps emitting items more frequently than the length of the time window, then no items will be emitted by the resulting observable.
Alias for debounce.
- timeout
the length of the window of time that must pass after the emission of an item from the source observable in which that observable emits no items in order for the item to be emitted by the resulting observable
- Definition Classes
- Observable
- See also
echoOnce for a similar operator that also mirrors the source observable
- final def timeoutOnSlowDownstream(timeout: FiniteDuration): Observable[A]
Returns an observable that mirrors the source but that will trigger a DownstreamTimeoutException in case the downstream subscriber takes more than the given timespan to process an
onNext
message.Returns an observable that mirrors the source but that will trigger a DownstreamTimeoutException in case the downstream subscriber takes more than the given timespan to process an
onNext
message.Note that this ignores the time it takes for the upstream to send
onNext
messages. For detecting slow producers see timeoutOnSlowUpstream.- timeout
maximum duration for
onNext
.
- Definition Classes
- Observable
- final def timeoutOnSlowDownstreamTo[B >: A](timeout: FiniteDuration, backup: Observable[B]): Observable[B]
Returns an observable that mirrors the source but applies a timeout for each
onNext
message.Returns an observable that mirrors the source but applies a timeout for each
onNext
message. If downstream subscriber takes more time than the given timespan to process anonNext
message, the source is terminated and downstream gets subscribed to the given backup.Note that this ignores the time it takes for the upstream to send
onNext
messages. For detecting slow producers see timeoutOnSlowUpstream.- timeout
maximum duration for
onNext
.- backup
alternative data source to subscribe to on timeout.
- Definition Classes
- Observable
- final def timeoutOnSlowUpstream(timeout: FiniteDuration): Observable[A]
Returns an observable that mirrors the source but applies a timeout for each emitted item by the upstream.
Returns an observable that mirrors the source but applies a timeout for each emitted item by the upstream. If the next item isn't emitted within the specified timeout duration starting from its predecessor, the resulting Observable terminates and notifies observers of a TimeoutException.
Note that this ignores the time it takes to process
onNext
. If dealing with a slow consumer, see timeoutOnSlowDownstream.- timeout
maximum duration between emitted items before a timeout occurs (ignoring the time it takes to process
onNext
)
- Definition Classes
- Observable
- final def timeoutOnSlowUpstreamTo[B >: A](timeout: FiniteDuration, backup: Observable[B]): Observable[B]
Returns an observable that mirrors the source but applies a timeout for each emitted item by the upstream.
Returns an observable that mirrors the source but applies a timeout for each emitted item by the upstream. If the next item isn't emitted within the specified timeout duration starting from its predecessor, the source is terminated and the downstream gets subscribed to the given backup.
Note that this ignores the time it takes to process
onNext
. If dealing with a slow consumer, see timeoutOnSlowDownstream.- timeout
maximum duration between emitted items before a timeout occurs (ignoring the time it takes to process
onNext
)- backup
is the alternative data source to subscribe to on timeout
- Definition Classes
- Observable
- final def toListL: Task[List[A]]
Returns a
Task
that upon evaluation will collect all items from the source in a ScalaList
and return this list instead.Returns a
Task
that upon evaluation will collect all items from the source in a ScalaList
and return this list instead.WARNING: for infinite streams the process will eventually blow up with an out of memory error.
- Definition Classes
- Observable
- final def toReactivePublisher[B >: A](implicit s: Scheduler): Publisher[B]
Converts this
Observable
into anorg.reactivestreams.Publisher
.Converts this
Observable
into anorg.reactivestreams.Publisher
.Meant for interoperability with other Reactive Streams implementations.
Usage sample:
import monix.eval.Task import monix.execution.rstreams.SingleAssignSubscription import org.reactivestreams.{Publisher, Subscriber, Subscription} def sum(source: Publisher[Int], requestSize: Int): Task[Long] = Task.create { (_, cb) => val sub = SingleAssignSubscription() source.subscribe(new Subscriber[Int] { private[this] var requested = 0L private[this] var sum = 0L def onSubscribe(s: Subscription): Unit = { sub := s requested = requestSize s.request(requestSize) } def onNext(t: Int): Unit = { sum += t if (requestSize != Long.MaxValue) requested -= 1 if (requested <= 0) { requested = requestSize sub.request(requestSize) } } def onError(t: Throwable): Unit = cb.onError(t) def onComplete(): Unit = cb.onSuccess(sum) }) // Cancelable that can be used by Task sub } import monix.execution.Scheduler.Implicits.global val pub = Observable(1, 2, 3, 4).toReactivePublisher // Yields 10 sum(pub, requestSize = 128)
See the Reactive Streams protocol for details.
- Definition Classes
- Observable
- def toString(): String
- Definition Classes
- AnyRef → Any
- def transform[B](transformer: Transformer[A, B]): Observable[B]
Transforms the source using the given transformer function.
Transforms the source using the given transformer function.
- Definition Classes
- Observable
- final def uncancelable: Observable[A]
Makes the source
Observable
uninterruptible such that acancel
signal has no effect.Makes the source
Observable
uninterruptible such that acancel
signal has no effect.Example
import scala.concurrent.duration._ Observable.eval(println("Hello!")) .delayExecution(10.seconds) .uncancelable
The created observable, after
subscribe
, will print "Hello!" even if cancellation is attempted.- Definition Classes
- Observable
- final def unsafeMulticast[B >: A, R](processor: Subject[B, R])(implicit s: Scheduler): ConnectableObservable[R]
Converts this observable into a multicast observable, useful for turning a cold observable into a hot one (i.e.
Converts this observable into a multicast observable, useful for turning a cold observable into a hot one (i.e. whose source is shared by all observers).
UNSAFE PROTOCOL: This operator is unsafe because
Subject
objects are stateful and have to obey theObserver
contract, meaning that they shouldn't be subscribed multiple times, so they are error prone. Only use if you know what you're doing, otherwise prefer the safe multicast operator.UNSAFE WARNING: this operation can trigger the execution of side effects, which breaks referential transparency and is thus not a pure function.
For FP code these functions shouldn't be called until "the end of the world", which is to say at the end of the program (for a console app), or at the end of a web request.
Otherwise for modifying or operating on streams, prefer its pure functions like publishSelector for sharing the data source, or map or flatMap for operating on its events. Or in case of specialized logic, prefer to suspend these side effects via Observable.suspend. Monix also provides Task which can also be used for suspending side effects and the
Task
was built to interop well withObservable
.- Definition Classes
- Observable
- Annotations
- @UnsafeProtocol() @UnsafeBecauseImpure()
- def unsafeSubscribeFn(subscriber: Subscriber[A]): Cancelable
Characteristic function for an
Observable
instance, that creates the subscription and that eventually starts the streaming of events to the given Observer, to be provided by observable implementations.Characteristic function for an
Observable
instance, that creates the subscription and that eventually starts the streaming of events to the given Observer, to be provided by observable implementations.UNSAFE PROTOCOL: This function is "unsafe" to call because it does not protect the calls to the given Observer implementation and thus knowledge of the protocol is needed.
Prefer normal subscribe when consuming a stream, these unsafe subscription methods being useful when building operators and for testing purposes.
Normal
subscribe
protects users in these ways:- it does a best effort attempt to catch and report exceptions that violate the protocol
- the final
onComplete
oronError
message is guaranteed to be signaled after the completion of the acknowledgement received from the lastonNext
; the internal protocol doesn't require back-pressuring of this last message for performance reasons
UNSAFE WARNING: this operation can trigger the execution of side effects, which breaks referential transparency and is thus not a pure function.
For FP code these functions shouldn't be called until "the end of the world", which is to say at the end of the program (for a console app), or at the end of a web request.
Otherwise for modifying or operating on streams, prefer its pure functions like publishSelector for sharing the data source, or map or flatMap for operating on its events. Or in case of specialized logic, prefer to suspend these side effects via Observable.suspend. Monix also provides Task which can also be used for suspending side effects and the
Task
was built to interop well withObservable
.- Definition Classes
- RefCountObservable → Observable
- Annotations
- @tailrec()
- final def unsafeSubscribeFn(observer: Observer[A])(implicit s: Scheduler): Cancelable
Given an observer and a scheduler for managing async boundaries, subscribes to this observable for events.
Given an observer and a scheduler for managing async boundaries, subscribes to this observable for events.
Helper for calling the abstract method.
UNSAFE PROTOCOL: This function is "unsafe" to call because it does not protect the calls to the given Observer implementation and thus knowledge of the protocol is needed.
Prefer normal subscribe when consuming a stream, these unsafe subscription methods being useful when building operators and for testing purposes.
Normal
subscribe
protects users in these ways:- it does a best effort attempt to catch and report exceptions that violate the protocol
- the final
onComplete
oronError
message is guaranteed to be signaled after the completion of the acknowledgement received from the lastonNext
; the internal protocol doesn't require back-pressuring of this last message for performance reasons
UNSAFE WARNING: this operation can trigger the execution of side effects, which breaks referential transparency and is thus not a pure function.
For FP code these functions shouldn't be called until "the end of the world", which is to say at the end of the program (for a console app), or at the end of a web request.
Otherwise for modifying or operating on streams, prefer its pure functions like publishSelector for sharing the data source, or map or flatMap for operating on its events. Or in case of specialized logic, prefer to suspend these side effects via Observable.suspend. Monix also provides Task which can also be used for suspending side effects and the
Task
was built to interop well withObservable
.- Definition Classes
- Observable
- Annotations
- @UnsafeProtocol() @UnsafeBecauseImpure()
- final def wait(arg0: Long, arg1: Int): Unit
- Definition Classes
- AnyRef
- Annotations
- @throws(classOf[java.lang.InterruptedException])
- final def wait(arg0: Long): Unit
- Definition Classes
- AnyRef
- Annotations
- @throws(classOf[java.lang.InterruptedException]) @native()
- final def wait(): Unit
- Definition Classes
- AnyRef
- Annotations
- @throws(classOf[java.lang.InterruptedException])
- def whileBusyAggregateEvents[S](seed: (A) => S)(aggregate: (S, A) => S): Observable[S]
Conflates events when a downstream is slower than the upstream.
Conflates events when a downstream is slower than the upstream.
Emits: Immediately when an element is received if the downstream is waiting for elements. Otherwise emits when the downstream stops backpressuring and there is a conflated element available. Back pressures: Never (conflates instead)
Usage:
import scala.concurrent.duration._ import cats.data.Chain // Emits [0], [1, 2], [3, 4] Observable.range(0, 5) .throttle(1.second, 1) .whileBusyAggregateEvents(Chain.apply(_)){ case (chain, ele) => chain.append(ele) } .throttle(2.seconds, 1)
- Definition Classes
- Observable
- final def whileBusyBuffer[B >: A](overflowStrategy: Synchronous[B]): Observable[B]
While the destination observer is busy, buffers events, applying the given overflowStrategy.
While the destination observer is busy, buffers events, applying the given overflowStrategy.
- overflowStrategy
- the overflow strategy used for buffering, which specifies what to do in case we're dealing with a slow consumer - should an unbounded buffer be used, should back-pressure be applied, should the pipeline drop newer or older events, should it drop the whole buffer? See OverflowStrategy for more details.
- Definition Classes
- Observable
- final def whileBusyDropEvents: Observable[A]
While the destination observer is busy, drop the incoming events.
While the destination observer is busy, drop the incoming events.
- Definition Classes
- Observable
- final def whileBusyDropEventsAndSignal[B >: A](onOverflow: (Long) => B): Observable[B]
While the destination observer is busy, drop the incoming events.
While the destination observer is busy, drop the incoming events. When the downstream recovers, we can signal a special event meant to inform the downstream observer how many events where dropped.
- onOverflow
- a function that is used for signaling a special event used to inform the consumers that an overflow event happened, function that receives the number of dropped events as a parameter (see OverflowStrategy.Evicted)
- Definition Classes
- Observable
- final def whileBusyReduceEvents[B >: A](op: (B, B) => B): Observable[B]
Reduces elements when a downstream is slower than the upstream.
Reduces elements when a downstream is slower than the upstream.
Emits: Immediately when an element is received if the downstream is waiting for elements. Otherwise emits when the downstream stops backpressuring and there is a reduced element available. Back pressures: Never (reduces instead)
Usage:
import scala.concurrent.duration._ import cats.data.Chain // Emits 0, 3 (1+2), 7 (3+4) Observable.range(0, 5) .throttle(1.second, 1) .whileBusyReduceEvents(_ + _) .throttle(2.seconds, 1)
- Definition Classes
- Observable
- final def withFilter(p: (A) => Boolean): Observable[A]
Alias to filter to support syntax in for comprehension, i.e.
Alias to filter to support syntax in for comprehension, i.e.
Example:
case class Person(age: Long) val peopleObservable: Observable[Person] = Observable.range(1, 100).map(Person.apply) for { adult <- peopleObservable if adult.age >= 18 } yield adult
- Definition Classes
- Observable
- final def withLatestFrom[B, R](other: Observable[B])(f: (A, B) => R): Observable[R]
Combines the elements emitted by the source with the latest element emitted by another observable.
Combines the elements emitted by the source with the latest element emitted by another observable.
Similar with
combineLatest
, but only emits items when the single source emits an item (not when any of the Observables that are passed to the operator do, as combineLatest does).Visual Example
stream1: 1 - - 2 - - 3 - 4 - - stream2: 1 - - 2 - 3 - - - - 4 result: (1, 1), (2, 2), (3, 3), (4, 3)
- other
is an observable that gets paired with the source
- f
is a mapping function over the generated pairs
- Definition Classes
- Observable
- final def withLatestFrom2[B1, B2, R](o1: Observable[B1], o2: Observable[B2])(f: (A, B1, B2) => R): Observable[R]
Combines the elements emitted by the source with the latest elements emitted by two observables.
Combines the elements emitted by the source with the latest elements emitted by two observables.
Similar with
combineLatest
, but only emits items when the single source emits an item (not when any of the Observables that are passed to the operator do, as combineLatest does).- o1
is the first observable that gets paired with the source
- o2
is the second observable that gets paired with the source
- f
is a mapping function over the generated pairs
- Definition Classes
- Observable
- final def withLatestFrom3[B1, B2, B3, R](o1: Observable[B1], o2: Observable[B2], o3: Observable[B3])(f: (A, B1, B2, B3) => R): Observable[R]
Combines the elements emitted by the source with the latest elements emitted by three observables.
Combines the elements emitted by the source with the latest elements emitted by three observables.
Similar with
combineLatest
, but only emits items when the single source emits an item (not when any of the Observables that are passed to the operator do, as combineLatest does).- o1
is the first observable that gets paired with the source
- o2
is the second observable that gets paired with the source
- o3
is the third observable that gets paired with the source
- f
is a mapping function over the generated pairs
- Definition Classes
- Observable
- final def withLatestFrom4[B1, B2, B3, B4, R](o1: Observable[B1], o2: Observable[B2], o3: Observable[B3], o4: Observable[B4])(f: (A, B1, B2, B3, B4) => R): Observable[R]
Combines the elements emitted by the source with the latest elements emitted by four observables.
Combines the elements emitted by the source with the latest elements emitted by four observables.
Similar with
combineLatest
, but only emits items when the single source emits an item (not when any of the Observables that are passed to the operator do, as combineLatest does).- o1
is the first observable that gets paired with the source
- o2
is the second observable that gets paired with the source
- o3
is the third observable that gets paired with the source
- o4
is the fourth observable that gets paired with the source
- f
is a mapping function over the generated pairs
- Definition Classes
- Observable
- final def withLatestFrom5[B1, B2, B3, B4, B5, R](o1: Observable[B1], o2: Observable[B2], o3: Observable[B3], o4: Observable[B4], o5: Observable[B5])(f: (A, B1, B2, B3, B4, B5) => R): Observable[R]
Combines the elements emitted by the source with the latest elements emitted by five observables.
Combines the elements emitted by the source with the latest elements emitted by five observables.
Similar with
combineLatest
, but only emits items when the single source emits an item (not when any of the Observables that are passed to the operator do, as combineLatest does).- o1
is the first observable that gets paired with the source
- o2
is the second observable that gets paired with the source
- o3
is the third observable that gets paired with the source
- o4
is the fourth observable that gets paired with the source
- o5
is the fifth observable that gets paired with the source
- f
is a mapping function over the generated pairs
- Definition Classes
- Observable
- final def withLatestFrom6[B1, B2, B3, B4, B5, B6, R](o1: Observable[B1], o2: Observable[B2], o3: Observable[B3], o4: Observable[B4], o5: Observable[B5], o6: Observable[B6])(f: (A, B1, B2, B3, B4, B5, B6) => R): Observable[R]
Combines the elements emitted by the source with the latest elements emitted by six observables.
Combines the elements emitted by the source with the latest elements emitted by six observables.
Similar with
combineLatest
, but only emits items when the single source emits an item (not when any of the Observables that are passed to the operator do, as combineLatest does).- o1
is the first observable that gets paired with the source
- o2
is the second observable that gets paired with the source
- o3
is the third observable that gets paired with the source
- o4
is the fourth observable that gets paired with the source
- o5
is the fifth observable that gets paired with the source
- o6
is the sixth observable that gets paired with the source
- f
is a mapping function over the generated pairs
- Definition Classes
- Observable
- final def zip[B](other: Observable[B]): Observable[(A, B)]
Creates a new observable from this observable and another given observable by combining their items in pairs in a strict sequence.
Creates a new observable from this observable and another given observable by combining their items in pairs in a strict sequence.
So the first item emitted by the new observable will be the tuple of the first items emitted by each of the source observables; the second item emitted by the new observable will be a tuple with the second items emitted by each of those observables; and so forth.
Visual Example
stream1: 1 - - 2 - - 3 - 4 - - stream2: 1 - - 2 - 3 - - - - 4 result: (1, 1), (2, 2), (3, 3), (4, 4)
See combineLatest for a more relaxed alternative that doesn't combine items in strict sequence.
- other
is an observable that gets paired with the source
- returns
a new observable sequence that emits the paired items of the source observables
- Definition Classes
- Observable
- final def zipMap[B, R](other: Observable[B])(f: (A, B) => R): Observable[R]
Creates a new observable from this observable and another given observable by combining their items in pairs in a strict sequence.
Creates a new observable from this observable and another given observable by combining their items in pairs in a strict sequence.
So the first item emitted by the new observable will be the result of the function applied to the first item emitted by each of the source observables; the second item emitted by the new observable will be the result of the function applied to the second item emitted by each of those observables; and so forth.
Visual Example
stream1: 1 - - 2 - - 3 - 4 - - stream2: 1 - - 2 - 3 - - - - 4 result: (1, 1), (2, 2), (3, 3), (4, 4)
See combineLatestMap for a more relaxed alternative that doesn't combine items in strict sequence.
- other
is an observable that gets paired with the source
- f
is a mapping function over the generated pairs
- Definition Classes
- Observable
- final def zipWithIndex: Observable[(A, Long)]
Zips the emitted elements of the source with their indices.
Zips the emitted elements of the source with their indices.
- Definition Classes
- Observable
This is the API documentation for the Monix library.
Package Overview
monix.execution exposes lower level primitives for dealing with asynchronous execution:
Atomic
types, as alternative tojava.util.concurrent.atomic
monix.catnap exposes pure abstractions built on top of the Cats-Effect type classes:
monix.eval is for dealing with evaluation of results, thus exposing Task and Coeval.
monix.reactive exposes the
Observable
pattern:Observable
implementationsmonix.tail exposes Iterant for purely functional pull based streaming:
Batch
andBatchCursor
, the alternatives to Scala'sIterable
andIterator
respectively that we are using within Iterant's encodingYou can control evaluation with type you choose - be it Task, Coeval, cats.effect.IO or your own as long as you provide correct cats-effect or cats typeclass instance.