Equivalent of RxJS throttleTime in Rx.NET - system.reactive

I'm trying to implement the equivalent of RxJS throttleTime using Rx.NET (it's not implemented in .NET).
throttleTime emits a value from the source Observable, then ignores subsequent source values for duration milliseconds, then repeats this process.
This differs from throttle which waits a time before emitting. throttleTime emits the first item and then waits before emitting again.
Any pointers as to how to go about this would be much appreciated.

This should do it:
public static IObservable<T> ThrottleTime<T>(this IObservable<T> source, TimeSpan ts)
{
return ThrottleTime(source, ts, Scheduler.Default);
}
public static IObservable<T> ThrottleTime<T>(this IObservable<T> source, TimeSpan ts, IScheduler scheduler)
{
return source
.Timestamp(scheduler)
.Scan((EmitValue: false, OpenTime: DateTimeOffset.MinValue, Item: default(T)), (state, item) => item.Timestamp > state.OpenTime
? (true, item.Timestamp + ts, item.Value)
: (false, state.OpenTime, item.Value)
)
.Where(t => t.EmitValue)
.Select(t => t.Item);
}
Explanation: Think of ThrottleTime as having a single state variable: The next time the gate opens to a new value. If the source item is before this timed-gate value, then nothing happens. If the source item is after it, then pass it through, and reset the gate value to the latest timestamp.
Scan holds the time value in a tuple (the OpenTime variable). The other fields on the tuple are more helpful downstream.

Related

How can I convert an observable to a maybe?

There are new convenience methods added to rxjava2 added to accomplish a similar thing.
toSingle() converts an Observable that emits a single item into a Single that emits that item
toObservable() converts a Single into an Observable that emits the item emitted by the Single and then completes
How do can I convert an Observable to a Maybe?
(source: http://reactivex.io/documentation/single.html)
You can't directly convert an Observable into a Maybe, because it wouldn't know what to emit in that context: is it the first element? the last? the product of some processing to the elements?
You can, however, decide on that and do what you want:
final Observable<Boolean> sourceBooleans = Observable.just(true, true, false);
final Maybe<Boolean> firstMaybe = sourceBooleans.firstElement();
final Maybe<Boolean> lastMaybe = sourceBooleans.lastElement();
final Maybe<Boolean> secondMaybe = sourceBooleans.elementAt(1);
final Observable<Integer> sourceNumbers = Observable.just(1, 2, 3, 4);
final Maybe<Integer> firstEven = sourceNumbers
.filter(it -> it % 2 == 0)
.firstElement()
You can see what methods return Maybe in the Observable implementation
Note that you can't go from Observable to Single directly either, without choosing what it should emit: there's no toSingle in the Observable class, but methods that return a Single instead (like first(), last(), etc.)

Significance of Publish().RefCount() in this example?

I am in the process of learning RX and have run across a sample on the Intro to Rx site that I have a question about. Here is the example which implements the same functionality as the Window with count extension method:
public static IObservable<IObservable<T>> MyWindow<T>(
this IObservable<T> source,
int count)
{
var shared = source.Publish().RefCount();
var windowEdge = shared
.Select((i, idx) => idx % count)
.Where(mod => mod == 0)
.Publish()
.RefCount();
return shared.Window(windowEdge, _ => windowEdge);
}
I understand the purpose of the var shared = source.Publish().RefCount() line to 'share' the source with the window edge query. What I don't understand is why the windowEdge query was also defined with the .Publish().RefCount()? Can someone please help me understand why this would be necessary?
Good Question!
Long Answer
Aside from performance reasons, the reason windowEdge is ref-counted has to do with the use of Select.
In this example, Select is using the index argument (idx), who's value is determined uniquely for each new subscriber. Therefore, if we did not ref-count windowEdge, each new subscriber would receive an event upon the next item yielded, since mod == 0 will always be true.
This means without ref-counting that each window would consist of exactly two values (assuming no other race conditions are introduced). Example:
When the first event fires, we create a new window and feed in the event, at which point we also use the window-closing selector to obtain an observable which will yield when the window should close. The next event fires, and is sent to the current window. That event also happens to be the first event that is sent to our window-closing observable (because mod == 0 is always true). The window-closing observable has now fired, and the window is closed, leaving us with a window which contains exactly two elements. Repeat.
TLDR
The use of ref-count for windowEdge is necessary to ensure we're only incrementing idx once per "MyWindow" observable.

Scheduling a IEnumerable periodically with .NET reactive extensions

Say for example I have an enumerable
dim e = Enumerable.Range(0, 1024)
I'd like to be able to do
dim o = e.ToObservable(Timespan.FromSeconds(1))
So that the observable would generate values every second
until the enumerable is exhausted. I can't figure a simple way to
do this.
You can use Interval together with Zip to get the desired functionality:
var sequence = Observable.Interval(TimeSpan.FromSeconds(1))
.Zip(e.ToObservable(), (tick, index) => index)
I have also looked for the solution and after reading the intro to rx made my self one:
There is an Observable.Generate() overload which I have used to make my own ToObservable() extension method, taking TimeSpan as period:
public static class MyEx {
public static IObservable<T> ToObservable<T>(this IEnumerable<T> enumerable, TimeSpan period)
{
return Observable.Generate(
enumerable.GetEnumerator(),
x => x.MoveNext(),
x => x,
x => x.Current,
x => period);
}
public static IObservable<T> ToObservable<T>(this IEnumerable<T> enumerable, Func<T,TimeSpan> getPeriod)
{
return Observable.Generate(
enumerable.GetEnumerator(),
x => x.MoveNext(),
x => x,
x => x.Current,
x => getPeriod(x.Current));
}
}
Already tested in LINQPad. Only concerning about what happens with the enumerator instance after the resulting observable is e.g. disposed. Any corrections appreciated.
You'd need something to schedule notifying observers with each value taken from the Enumerable.
You can use the recursive Schedule overload on an Rx scheduler.
Public Shared Function Schedule ( _
scheduler As IScheduler, _
dueTime As TimeSpan, _
action As Action(Of Action(Of TimeSpan)) _
) As IDisposable
On each scheduled invocation, simply call enumerator.MoveNext(), and call OnNext(enumerator.Current), and finally OnCompleted when MoveNext() returns false. This is pretty much the bare-bones way of doing it.
An alternative was to express your requirement is to restate it as "for a sequence, have a minimum interval between each value".
See this answer. The test case resembles your original question.
You could always do this very simple approach:
dim e = Enumerable.Range(0, 1024)
dim o = e.ToObservable().Do(Sub (x) Thread.Sleep(1000))
When you subscribe to o the values take a second to be produced.
I can only assume that you are using Range to dumb down your question.
Do you want every value that the Enumerable pushes to be delayed by a second?
var e = Enumerable.Range(0, 10);
var o = Observable.Interval(TimeSpan.FromSeconds(1))
.Zip(e, (_,i)=>i);
Or do you want only the last value of the Enumerable at each second to be pushed. i.e. reading from Enumerable that is evaluating as you enumerate it (perhaps some IO). In which case CombineLatest is more useful than Zip.
Or perhaps you just want to get a value every second, in which case just use the Observable.Interval method
var o = Observable.Interval(TimeSpan.FromSeconds(1));
If you explain your problem space then the community will be able to better help you.
Lee
*Excuse the C# answer, but I dont know what the equivalent VB.NET code would be.

Aggregate PropertyChanged events from the collection into one IObservable<EventPattern<PropertyChangedEventArgs>>

I have collection of INotifyPropertyChanged objects and would like to stream all PropertyChanged events into a single observable sequence for further processing.
Here is a code
IObservable<EventPattern<PropertyChangedEventArgs>> _allEvents = null;
// Items contains collection of item, which implements INotifyPropertyChanged
foreach (var item in Items)
{
var seq = Observable.FromEventPattern<PropertyChangedEventArgs>(item, "PropertyChanged");
if (_allEvents == null)
_allEvents = seq;
else
_allEvents.Merge(seq);
}
// subscribe to the aggregated observable sequence
if (_allEvents != null)
_allEvents.Subscribe(evt => Trace.WriteLine(" Property Changed -> " + evt.EventArgs.PropertyName));
A single Subscribe doesn't work here for some reason in the aggregated sequence.
Looks like I aggregated (using Reactive Extensions's Merge function) incorrectly. But, subscribe inside the loop works perfectly.
Can anybody assist me here, how to aggregate a many event streams into one with reactive extensions?
Thanks
Try this:
var _allEvents = Observable
.Merge(Items
.Select(item => Observable
.FromEventPattern<PropertyChangedEventArgs>(item, "PropertyChanged")));
_allEvents.Subscribe(evt => Trace.WriteLine(" Property Changed -> " + evt.EventArgs.PropertyName));
The reason your approach doesn't work is that you were calling IObservable<T> Observable.Merge<T>(this IObservable<T> first, IObservable<T> second). The return type of this is a resulting observable. I think you might have been thinking that Merge modified the Observable, but you can think of Observables as immutable (sort of). The way to get your approach to work would have been:
_allEvents = _allEvents.Merge(seq);
But... yuck. Don't do that.

Handling errors in an observable sequence using Rx

Is there a way to have an observable sequence to resume execution with the next element in the sequence if an error occurs?
From this post it looks like you need to specify a new observable sequence in Catch() to resume execution, but what if you needed to just continue processing with the next element in the sequence instead? Is there a way to achieve this?
UPDATE:
The scenario is as follows:
I have a bunch of elements that I need to process. The processing is made up of a bunch of steps. I have
decomposed the steps into tasks that I would like to compose.
I followed the guidelines for ToObservable() posted here
to convert by tasks to an observables for composition.
so basically I'm doing somethng like so -
foreach(element in collection)
{
var result = from aResult in DoAAsync(element).ToObservable()
from bResult in DoBAsync(aResult).ToObservable()
from cResult in DoCAsync(bResult).ToObservable()
select cResult;
result.subscribe( register on next and error handlers here)
}
or I could something like this:
var result =
from element in collection.ToObservable()
from aResult in DoAAsync(element).ToObservable()
from bResult in DoBAsync(aResult).ToObservable()
from cResult in DoCAsync(bResult).ToObservable()
select cResult;
What is the best way here to continue processing other elements even if let's say the processing of
one of the elements throws an exception. I would like to be able to log the error and move on ideally.
Both James & Richard made some good points, but I don't think they have given you the best method for solving your problem.
James suggested using .Catch(Observable.Never<Unit>()). He was wrong when he said that "will ... allow the stream to continue" because once you hit an exception the stream must end - that is what Richard pointed out when he mentioned the contract between observers and observables.
Also, using Never in this way will cause your observables to never complete.
The short answer is that .Catch(Observable.Empty<Unit>()) is the correct way to change a sequence from one that ends with an error to one that ends with completion.
You've hit on the right idea of using SelectMany to process each value of the source collection so that you can catch each exception, but you're left with a couple of issues.
You're using tasks (TPL) just to turn a function call into an observable. This forces your observable to use task pool threads which means that the SelectMany statement will likely produce values in a non-deterministic order.
Also you hide the actual calls to process your data making refactoring and maintenance harder.
I think you're better off creating an extension method that allows the exceptions to be skipped. Here it is:
public static IObservable<R> SelectAndSkipOnException<T, R>(
this IObservable<T> source, Func<T, R> selector)
{
return
source
.Select(t =>
Observable.Start(() => selector(t)).Catch(Observable.Empty<R>()))
.Merge();
}
With this method you can now simply do this:
var result =
collection.ToObservable()
.SelectAndSkipOnException(t =>
{
var a = DoA(t);
var b = DoB(a);
var c = DoC(b);
return c;
});
This code is much simpler, but it hides the exception(s). If you want to hang on to the exceptions while letting your sequence continue then you need to do some extra funkiness. Adding a couple of overloads to the Materialize extension method works to keep the errors.
public static IObservable<Notification<R>> Materialize<T, R>(
this IObservable<T> source, Func<T, R> selector)
{
return source.Select(t => Notification.CreateOnNext(t)).Materialize(selector);
}
public static IObservable<Notification<R>> Materialize<T, R>(
this IObservable<Notification<T>> source, Func<T, R> selector)
{
Func<Notification<T>, Notification<R>> f = nt =>
{
if (nt.Kind == NotificationKind.OnNext)
{
try
{
return Notification.CreateOnNext<R>(selector(nt.Value));
}
catch (Exception ex)
{
ex.Data["Value"] = nt.Value;
ex.Data["Selector"] = selector;
return Notification.CreateOnError<R>(ex);
}
}
else
{
if (nt.Kind == NotificationKind.OnError)
{
return Notification.CreateOnError<R>(nt.Exception);
}
else
{
return Notification.CreateOnCompleted<R>();
}
}
};
return source.Select(nt => f(nt));
}
These methods allow you to write this:
var result =
collection
.ToObservable()
.Materialize(t =>
{
var a = DoA(t);
var b = DoB(a);
var c = DoC(b);
return c;
})
.Do(nt =>
{
if (nt.Kind == NotificationKind.OnError)
{
/* Process the error in `nt.Exception` */
}
})
.Where(nt => nt.Kind != NotificationKind.OnError)
.Dematerialize();
You can even chain these Materialize methods and use ex.Data["Value"] & ex.Data["Selector"] to get the value and selector function that threw the error out.
I hope this helps.
The contract between IObservable and IObserver is OnNext*(OnCompelted|OnError)? which is upheld by all operators, even if not by the source.
Your only choice is to re-subscribe to the source using Retry, but if the source returns the IObservable instance for every description you won't see any new values.
Could you supply more information on your scenario? Maybe there is another way of looking at it.
Edit: Based on your updated feedback, it sounds like you just need Catch:
var result =
from element in collection.ToObservable()
from aResult in DoAAsync(element).ToObservable().Log().Catch(Observable.Empty<TA>())
from bResult in DoBAsync(aResult).ToObservable().Log().Catch(Observable.Empty<TB>())
from cResult in DoCAsync(bResult).ToObservable().Log().Catch(Observable.Empty<TC>())
select cResult;
This replaces an error with an Empty which would not trigger the next sequence (since it uses SelectMany under the hood.