| name | r3-reactive-extensions |
| description | Build reactive/event-driven C# with R3 (Cysharp's modern reimplementation of Reactive Extensions). Covers the Observable<T>/Observer<T> model, the OnErrorResume error contract, async dispatch with AwaitOperation, Task/IAsyncEnumerable integration, TimeProvider/FrameProvider scheduling, the concurrency contract, and how R3 differs from System.Reactive (Rx.NET). |
| invocable | false |
R3: Modern Reactive Extensions for .NET
R3 is Cysharp's ground-up reimplementation of Reactive
Extensions — "the new future of dotnet/reactive and UniRx." It keeps the LINQ-over-events
programming model but rebuilds the core types, error contract, and scheduler to fix
long-standing problems in System.Reactive (Rx.NET). Use this skill when composing event
streams, UI input, timers, or push-based pipelines in C#.
Canonical sources (link to these from code and docs):
When to Use This Skill
Use this skill when:
- Composing events over time — UI input, sensor/feed updates, websocket messages, domain events
- You need operators like debounce, throttle, merge, combine-latest, distinct-until-changed
- Building MVVM state with
ReactiveProperty / BindableReactiveProperty
- Bridging push-based streams with
Task / async and IAsyncEnumerable
- Migrating from
System.Reactive, UniRx, or IObservable<T> code
- You hit Rx pain points: subscriptions dying on exceptions, scheduler overhead, or leak hunting
Not the right tool for: request/response I/O (use async/await), bounded producer/consumer
with backpressure (use System.Threading.Channels), or server-side stream processing with
batching/backpressure (use Akka.NET Streams). R3, like all Rx, is push-based with no
backpressure. See the csharp-concurrency-patterns skill for choosing between these.
Reference Files
- rx-net-differences.md: Every meaningful difference vs System.Reactive (Rx.NET) — the new core types, the error model, operator renames, dropped APIs, the scheduler swap, and a migration checklist.
- async-and-integration-patterns.md: Common patterns — async dispatch with
AwaitOperation, Task integration, IAsyncEnumerable round-tripping, ReactiveProperty/MVVM, subjects, and subscription lifecycle.
- scheduling-and-concurrency.md: How R3 handles concurrent updates (the threading contract,
Synchronize, ObserveOn), TimeProvider vs FrameProvider, when each is necessary, and deterministic testing with fake providers.
Everything in this skill was validated empirically against R3 1.3.1. Captured output
appears in the reference files as evidence.
Why R3 Exists (the "why use it")
The author (neuecc)
built R3 to fix concrete defects in System.Reactive:
- Exceptions silently kill subscriptions. In Rx, one exception in the pipeline calls
OnError and unsubscribes forever — "a billion-dollar mistake" for long-lived event
streams (a single bad UI event tears down the whole subscription). R3 routes errors to
OnErrorResume and keeps the subscription alive by default.
IScheduler is heavy and confusing. ImmediateScheduler/Merge were measured causing
real server memory/CPU bloat. R3 deletes IScheduler and uses .NET 8's TimeProvider
(wall-clock) plus a new FrameProvider (frame-clock).
- Subscription leaks are hard to find. R3 makes every
Observable<T> an abstract class so
all subscriptions funnel through one place, enabling ObservableTracker to list every live
subscription with stack traces.
- Rx and async were awkwardly fused. R3 treats Rx as event-first and adds explicit
bridges (
AwaitOperation, FromAsync, ToAsyncEnumerable) instead of pretending events
are pull-based sequences.
- One library, every UI. A platform-neutral core plus thin provider packages for Unity,
Godot, WPF, WinForms, Avalonia, WinUI3, MAUI, Stride, MonoGame, and Blazor.
Install
dotnet add package R3
using R3;
The Mental Model
R3 replaces Rx's interfaces with abstract classes, and replaces Rx's two-method error
contract with a single completion that carries a result.
public abstract class Observable<T>
{
public IDisposable Subscribe(Observer<T> observer);
protected abstract IDisposable SubscribeCore(Observer<T> observer);
}
public abstract class Observer<T> : IDisposable
{
public void OnNext(T value);
public void OnErrorResume(Exception error);
public void OnCompleted(Result result);
}
The grammar is (OnNext | OnErrorResume)* OnCompleted(Result)?. Note the difference from Rx's
OnNext* (OnError | OnCompleted)?: errors and termination are decoupled. An error is just a
notification; only OnCompleted ends the stream, and it carries a Result that is either
Result.Success or Result.Failure(exception).
Quick start
using R3;
var subscription = Observable
.EveryValueChanged(model, m => m.SearchText)
.Debounce(TimeSpan.FromMilliseconds(300))
.DistinctUntilChanged()
.SubscribeAwait(async (text, ct) =>
{
var results = await _api.SearchAsync(text, ct);
Render(results);
}, AwaitOperation.Switch);
subscription.Dispose();
Core Behavior, Verified
Errors do not terminate by default
var subject = new Subject<int>();
subject.Select(x => 100 / x).Subscribe(
onNext: x => Console.WriteLine($"next {x}"),
onErrorResume: e => Console.WriteLine($"errorResume {e.GetType().Name}"),
onCompleted: (Result r) => Console.WriteLine($"completed IsSuccess={r.IsSuccess}"));
subject.OnNext(2);
subject.OnNext(0);
subject.OnNext(5);
subject.OnCompleted();
This is the single biggest behavioral change from Rx. To opt back into classic "an error
terminates the sequence" behavior, insert .OnErrorResumeAsFailure() — the error then flows to
OnCompleted(Result.Failure(e)) and downstream OnNexts stop. Recover with Catch. Full
captured runs and the (deliberately absent) Retry story are in
rx-net-differences.md.
Async dispatch is explicit
R3's async operators (SubscribeAwait, SelectAwait, WhereAwait, …) take an AwaitOperation
that decides what happens when values arrive faster than the async work completes:
AwaitOperation | Overlap behavior | Typical use |
|---|
Sequential (default) | Queue values, run one at a time | Ordered processing |
Drop | Ignore new values while one is running | Debounced submit / cooldown |
Switch | Cancel the running one, start the new | Search-as-you-type, latest-wins |
Parallel | Run all concurrently | Independent fan-out |
SequentialParallel | Run concurrently, emit results in order | Parallel map, ordered output |
ThrottleFirstLast | Run first + last of a burst | Leading/trailing sampling |
These were verified to behave exactly as described (including Switch cancelling the superseded
operation's CancellationToken). See async-and-integration-patterns.md.
Task and IAsyncEnumerable bridges
await Observable.FromAsync(async ct => await LoadAsync(ct)).FirstAsync();
List<int> all = await source.ToListAsync();
int last = await source.LastAsync();
await asyncEnumerable.ToObservable().ForEachAsync(Handle);
await foreach (var x in source.ToAsyncEnumerable()) { }
All verified working. Details and the full terminal-operator list are in
async-and-integration-patterns.md.
How R3 Handles Concurrent Updates
R3 does not serialize concurrent producers. Like Rx, it assumes the Rx grammar: OnNext
must not be called concurrently or re-entrantly from multiple threads. Operators (Where,
Select, Subject, …) are not internally locked. Pushing OnNext from many threads at once
into a stateful downstream corrupts state — in testing, 20,000 concurrent OnNext calls into
a List<T> subscriber lost ~half the items and threw inside the operator chain.
The fix is to make the boundary explicit:
subject.Synchronize()
.Where(x => x.IsValid)
.Subscribe(Handle);
source.ObserveOnThreadPool().Subscribe(Handle);
var counter = new SynchronizedReactiveProperty<int>(0);
Practical rule: if more than one thread can publish into a stream, put Synchronize() (or an
ObserveOn*) immediately after the source, or use SynchronizedReactiveProperty. Full race
reproductions and outputs are in scheduling-and-concurrency.md.
Time vs Frames: TimeProvider and FrameProvider
R3 has two notions of "when," and both are abstractions you can fake in tests:
TimeProvider (the .NET 8 BCL type) = wall-clock time. Used by Delay, Debounce,
Interval, Timer, Timeout. This is what server/business code uses.
FrameProvider (R3-specific) = a frame clock. Used by EveryUpdate, DelayFrame(n),
IntervalFrame(n), etc.
When is a FrameProvider necessary? Whenever "progress" is measured in render/update ticks
instead of elapsed time:
- Game engines (Unity, Godot, Stride, MonoGame) — logic ticks with the engine's update loop,
so it respects pause and time-scale and stays in lockstep with rendering.
- UI render loops (WPF/Avalonia/WinUI composition frames) — react per frame.
- Deterministic tests —
FakeFrameProvider.Advance(n) drives frames with zero real time,
exactly as FakeTimeProvider.Advance(timeSpan) drives the clock.
Plain server/business code virtually never needs FrameProvider — that's TimeProvider
territory. Both fakes make time-dependent pipelines fully deterministic; examples in
scheduling-and-concurrency.md.
Best Practices Summary
DO
- Treat
OnErrorResume as the default: design streams that survive individual bad events.
- Add
.OnErrorResumeAsFailure() when you genuinely want an error to terminate the stream.
- Choose an
AwaitOperation deliberately for every async operator (Switch for latest-wins,
Sequential for ordering, Drop for cooldowns).
- Put
Synchronize() / ObserveOn* after any source that multiple threads publish into.
- Pass a
TimeProvider to time operators and a FrameProvider to frame operators so tests can
use FakeTimeProvider / FakeFrameProvider.
- Manage lifetime: route subscriptions into a
DisposableBag, CompositeDisposable, or
.AddTo(cancellationToken); turn on ObservableTracker in dev to catch leaks.
- Use
ReactiveProperty for de-duplicated observable state; BindableReactiveProperty for
XAML-bound state.
DON'T
- Don't assume an exception ends the stream (that's Rx, not R3).
- Don't reach for Rx names that R3 renamed: it's
Debounce (not Throttle), ThrottleLast
(not Sample), Chunk (not Buffer). Retry, GroupBy, Finally, and plain Buffer are
absent in 1.3.1 — see the differences file for replacements.
- Don't call
OnNext concurrently/re-entrantly from multiple threads without Synchronize().
- Don't use R3 for backpressured throughput pipelines — use Channels or Akka.NET Streams.
- Don't block on terminal operators (
.Result/.Wait()); they return Task<T> — await them.
Additional Resources