Testing Rx
Modern quality assurance standards demand comprehensive automated testing that can help evaluate and prevent bugs. It is good practice to have a suite of tests that verify correct behaviour and to run this as part of the build process to detect regressions early.
The System.Reactive source code includes a comprehensive tests suite. Testing Rx-based code presents some challenges, especially when time-sensitive operators are involved. Rx.NET's test suite includes many tests designed to exercise awkward edge cases to ensure predictable behaviour under load. This is only possible because Rx.NET was designed to be testable.
In this chapter, we'll show how you can take advantage of Rx's testability in your own code.
Virtual Time
It's common to deal with timing in Rx. As you've seen, it offers several operators that take time into account, and this presents a challenge. We don't want to introduce slow tests, because that can make test suites take too long to execute, but how might we test an application that waits for the user to stop typing for half a second before submitting a query? Non-deterministic tests can also be a problem: when there are race conditions it can be very hard to recreate these reliably.
The Scheduling and Threading chapter described how schedulers use a virtualized representation of time. This is critical for enabling tests to validate time-related behaviour. It lets us control Rx's perception of the progression of time, enabling us to write tests that logically take seconds, but which execute in microseconds.
Consider this example, where we create a sequence that publishes values every second for five seconds.
IObservable<long> interval = Observable
.Interval(TimeSpan.FromSeconds(1))
.Take(5);
A naive a test to ensure that this produces five values at one second intervals would take five seconds to run. That would be no good; we want hundreds if not thousands of tests to run in five seconds. Another very common requirement is to test a timeout. Here, we try to test a timeout of one minute.
var never = Observable.Never<int>();
var exceptionThrown = false;
never.Timeout(TimeSpan.FromMinutes(1))
.Subscribe(
i => Console.WriteLine("This will never run."),
ex => exceptionThrown = true);
Assert.IsTrue(exceptionThrown);
It looks like we would have no choice but to make our test wait for a minute before running that assert. In practice, we'd want to wait a little over a minute, because if the computer running the test is busy, it might trigger the timeout bit later than we've asked. This kind of scenario is notorious for causing tests to fail occasionally even when there's no real problem in the code being tested.
Nobody wants slow, inconsistent tests. So let's look at how Rx helps us to avoid these problems.
TestScheduler
The Scheduling and Threading chapter explained that schedulers determine when and how to execute code, and that they keep track of time. Most of the schedulers we looked at in that chapter addressed various threading concerns, and when it came to timing, they all attempted to run work at the time requested. But Rx provides TestScheduler, which handles time completely differently. It takes advantage of the fact that schedulers control all time-related behaviour to allow us to emulate and control time.
Note: TestScheduler is not in the main System.Reactive package. You will need to add a reference to Microsoft.Reactive.Testing to use it.
Any scheduler maintains a queue of actions to be executed. Each action is assigned a point in time when it should be executed. (Sometimes that time is "as soon as possible" but time-based operators will often schedule work to run at some specific time in the future.) If we use the TestScheduler it will effectively act as though time stands still until we tell it we want time to move on.
In this example, we schedule a task to be run immediately by using the simplest Schedule overload. Even though this effectively asks for the work to be run as soon as possible, the TestScheduler always waits for us to tell it we're ready before processing newly queued work. We advance the virtual clock forward by one tick, at which point it will execute that queued work. (It runs all newly-queued "as soon as possible" work any time we advance the virtual time. If we advance the time far enough to mean that work that was previously logically in the future is now runnable, it runs that too.)
var scheduler = new TestScheduler();
var wasExecuted = false;
scheduler.Schedule(() => wasExecuted = true);
Assert.IsFalse(wasExecuted);
scheduler.AdvanceBy(1); // execute 1 tick of queued actions
Assert.IsTrue(wasExecuted);
The TestScheduler implements the IScheduler interface and also defines methods allowing us to control and monitor virtual time. This shows these additional methods:
public class TestScheduler : // ...
{
public bool IsEnabled { get; private set; }
public TAbsolute Clock { get; protected set; }
public void Start()
public void Stop()
public void AdvanceTo(long time)
public void AdvanceBy(long time)
...
}
TestScheduler works in the same units as TimeSpan.Ticks. If you want to move time forward by 1 second, you can call scheduler.AdvanceBy(TimeSpan.FromSeconds(1).Ticks). One tick corresponds to 100ns, so 1 second is 10,000,000 ticks.
AdvanceTo
The AdvanceTo(long) method sets the virtual time to the specified number of ticks. This will execute all the actions that have been scheduled up to that absolute time specified. The TestScheduler uses ticks as its measurement of time. In this example, we schedule actions to be invoked now, in 10 ticks, and in 20 ticks (1 and 2 microseconds respectively).
var scheduler = new TestScheduler();
scheduler.Schedule(() => Console.WriteLine("A")); // Schedule immediately
scheduler.Schedule(TimeSpan.FromTicks(10), () => Console.WriteLine("B"));
scheduler.Schedule(TimeSpan.FromTicks(20), () => Console.WriteLine("C"));
Console.WriteLine("scheduler.AdvanceTo(1);");
scheduler.AdvanceTo(1);
Console.WriteLine("scheduler.AdvanceTo(10);");
scheduler.AdvanceTo(10);
Console.WriteLine("scheduler.AdvanceTo(15);");
scheduler.AdvanceTo(15);
Console.WriteLine("scheduler.AdvanceTo(20);");
scheduler.AdvanceTo(20);
Output:
scheduler.AdvanceTo(1);
A
scheduler.AdvanceTo(10);
B
scheduler.AdvanceTo(15);
scheduler.AdvanceTo(20);
C
Note that nothing happened when we advanced to 15 ticks. All work scheduled before 15 ticks had been performed and we had not advanced far enough yet to get to the next scheduled action.
AdvanceBy
The AdvanceBy(long) method allows us to move the clock forward by some amount of time. Unlike AdvanceTo, the argument here is relative to the current virtual time. Again, the measurements are in ticks. We can take the last example and modify it to use AdvanceBy(long).
var scheduler = new TestScheduler();
scheduler.Schedule(() => Console.WriteLine("A")); // Schedule immediately
scheduler.Schedule(TimeSpan.FromTicks(10), () => Console.WriteLine("B"));
scheduler.Schedule(TimeSpan.FromTicks(20), () => Console.WriteLine("C"));
Console.WriteLine("scheduler.AdvanceBy(1);");
scheduler.AdvanceBy(1);
Console.WriteLine("scheduler.AdvanceBy(9);");
scheduler.AdvanceBy(9);
Console.WriteLine("scheduler.AdvanceBy(5);");
scheduler.AdvanceBy(5);
Console.WriteLine("scheduler.AdvanceBy(5);");
scheduler.AdvanceBy(5);
Output:
scheduler.AdvanceBy(1);
A
scheduler.AdvanceBy(9);
B
scheduler.AdvanceBy(5);
scheduler.AdvanceBy(5);
C
Start
The TestScheduler's Start() method runs everything that has been scheduled, advancing virtual time as necessary for work items that were queued for a specific time. We take the same example again and swap out the AdvanceBy(long) calls for a single Start() call.
var scheduler = new TestScheduler();
scheduler.Schedule(() => Console.WriteLine("A")); // Schedule immediately
scheduler.Schedule(TimeSpan.FromTicks(10), () => Console.WriteLine("B"));
scheduler.Schedule(TimeSpan.FromTicks(20), () => Console.WriteLine("C"));
Console.WriteLine("scheduler.Start();");
scheduler.Start();
Console.WriteLine("scheduler.Clock:{0}", scheduler.Clock);
Output:
scheduler.Start();
A
B
C
scheduler.Clock:20
Note that once all of the scheduled actions have been executed, the virtual clock matches our last scheduled item (20 ticks).
We further extend our example by scheduling a new action to happen after Start() has already been called.
var scheduler = new TestScheduler();
scheduler.Schedule(() => Console.WriteLine("A"));
scheduler.Schedule(TimeSpan.FromTicks(10), () => Console.WriteLine("B"));
scheduler.Schedule(TimeSpan.FromTicks(20), () => Console.WriteLine("C"));
Console.WriteLine("scheduler.Start();");
scheduler.Start();
Console.WriteLine("scheduler.Clock:{0}", scheduler.Clock);
scheduler.Schedule(() => Console.WriteLine("D"));
Output:
scheduler.Start();
A
B
C
scheduler.Clock:20
Note that the output is exactly the same; If we want our fourth action to be executed, we will have to call Start() (or AdvanceTo or AdvanceBy) again.
Stop
There is a Stop() method whose name seems to imply some symmetry with Start(). This sets the scheduler's IsEnabled property to false, and if Start is currently running, this means that it will stop inspecting the queue for further work, and will return as soon as the work item currently being processed completes.
In this example, we show how you could use Stop() to pause processing of scheduled actions.
var scheduler = new TestScheduler();
scheduler.Schedule(() => Console.WriteLine("A"));
scheduler.Schedule(TimeSpan.FromTicks(10), () => Console.WriteLine("B"));
scheduler.Schedule(TimeSpan.FromTicks(15), scheduler.Stop);
scheduler.Schedule(TimeSpan.FromTicks(20), () => Console.WriteLine("C"));
Console.WriteLine("scheduler.Start();");
scheduler.Start();
Console.WriteLine("scheduler.Clock:{0}", scheduler.Clock);
Output:
scheduler.Start();
A
B
scheduler.Clock:15
Note that "C" never gets printed as we stop the clock at 15 ticks.
Since Start automatically stops when it has drained the work queue, you're under no obligation to call Stop. It's there only if you want to call Start but then pause processing part way through the test.
Schedule collision
When scheduling actions, it is possible and even likely that many actions will be scheduled for the same point in time. This most commonly would occur when scheduling multiple actions for now. It could also happen that there are multiple actions scheduled for the same point in the future. The TestScheduler has a simple way to deal with this. When actions are scheduled, they are marked with the clock time they are scheduled for. If multiple items are scheduled for the same point in time, they are queued in order that they were scheduled; when the clock advances, all items for that point in time are executed in the order that they were scheduled.
var scheduler = new TestScheduler();
scheduler.Schedule(TimeSpan.FromTicks(10), () => Console.WriteLine("A"));
scheduler.Schedule(TimeSpan.FromTicks(10), () => Console.WriteLine("B"));
scheduler.Schedule(TimeSpan.FromTicks(10), () => Console.WriteLine("C"));
Console.WriteLine("scheduler.Start();");
scheduler.Start();
Console.WriteLine("scheduler.Clock:{0}", scheduler.Clock);
Output:
scheduler.AdvanceTo(10);
A
B
C
scheduler.Clock:10
Note that the virtual clock is at 10 ticks, the time we advanced to.
Testing Rx code
Now that we have learnt a little bit about the TestScheduler, let's look at how we could use it to test our two initial code snippets that use Interval and Timeout. We want to execute tests as fast as possible but still maintain the semantics of time. In this example we generate our five values one second apart but pass in our TestScheduler to the Interval method to use instead of the default scheduler.
[TestMethod]
public void Testing_with_test_scheduler()
{
var expectedValues = new long[] {0, 1, 2, 3, 4};
var actualValues = new List<long>();
var scheduler = new TestScheduler();
var interval = Observable.Interval(TimeSpan.FromSeconds(1), scheduler).Take(5);
interval.Subscribe(actualValues.Add);
scheduler.Start();
CollectionAssert.AreEqual(expectedValues, actualValues);
// Executes in less than 0.01s "on my machine"
}
While this is mildly interesting, what I think is more important is how we would test a real piece of code. Imagine, if you will, a ViewModel that subscribes to a stream of prices. As prices are published, it adds them to a collection. Assuming this is a WPF implementation, we take the liberty of enforcing that the subscription be done on the ThreadPool and the observing is executed on the Dispatcher.
public class MyViewModel : IMyViewModel
{
private readonly IMyModel _myModel;
private readonly ObservableCollection<decimal> _prices;
public MyViewModel(IMyModel myModel)
{
_myModel = myModel;
_prices = new ObservableCollection<decimal>();
}
public void Show(string symbol)
{
// TODO: resource mgt, exception handling etc...
_myModel.PriceStream(symbol)
.SubscribeOn(Scheduler.ThreadPool)
.ObserveOn(Scheduler.Dispatcher)
.Timeout(TimeSpan.FromSeconds(10), Scheduler.ThreadPool)
.Subscribe(
Prices.Add,
ex=>
{
if(ex is TimeoutException)
IsConnected = false;
});
IsConnected = true;
}
public ObservableCollection<decimal> Prices
{
get { return _prices; }
}
public bool IsConnected { get; private set; }
}
Injecting scheduler dependencies
While the snippet of code above may do what we want it to, it will be hard to test as it is accessing the schedulers via static properties. You will need some way of enabling tests to supply different schedulers during testing. In this example, we're going to define an interface for this purpose:
public interface ISchedulerProvider
{
IScheduler CurrentThread { get; }
IScheduler Dispatcher { get; }
IScheduler Immediate { get; }
IScheduler NewThread { get; }
IScheduler ThreadPool { get; }
IScheduler TaskPool { get; }
}
The default implementation that we would run in production is implemented as follows:
public sealed class SchedulerProvider : ISchedulerProvider
{
public IScheduler CurrentThread => Scheduler.CurrentThread;
public IScheduler Dispatcher => DispatcherScheduler.Instance;
public IScheduler Immediate => Scheduler.Immediate;
public IScheduler NewThread => Scheduler.NewThread;
public IScheduler ThreadPool => Scheduler.ThreadPool;
public IScheduler TaskPool => Scheduler.TaskPool;
}
We can substitute implementations of ISchedulerProvider to help with testing. For example:
public sealed class TestSchedulers : ISchedulerProvider
{
// Schedulers available as TestScheduler type
public TestScheduler CurrentThread { get; } = new TestScheduler();
public TestScheduler Dispatcher { get; } = new TestScheduler();
public TestScheduler Immediate { get; } = new TestScheduler();
public TestScheduler NewThread { get; } = new TestScheduler();
public TestScheduler ThreadPool { get; } = new TestScheduler();
// ISchedulerService needs us to return IScheduler, but we want the properties
// to return TestScheduler for the convenience of test code, so we provide
// explicit implementations of all the properties to match ISchedulerService.
IScheduler ISchedulerProvider.CurrentThread => CurrentThread;
IScheduler ISchedulerProvider.Dispatcher => Dispatcher;
IScheduler ISchedulerProvider.Immediate => Immediate;
IScheduler ISchedulerProvider.NewThread => NewThread;
IScheduler ISchedulerProvider.ThreadPool => ThreadPool;
}
Note that ISchedulerProvider is implemented explicitly because that interface requires each property to return an IScheduler, but our tests will need to access the TestScheduler instances directly. I can now write some tests for my ViewModel. Below, we test a modified version of the MyViewModel class that takes an ISchedulerProvider and uses that instead of the static schedulers from the Scheduler class. We also use the popular Moq framework to provide a suitable fake implementation of our model.
[TestInitialize]
public void SetUp()
{
_myModelMock = new Mock<IMyModel>();
_schedulerProvider = new TestSchedulers();
_viewModel = new MyViewModel(_myModelMock.Object, _schedulerProvider);
}
[TestMethod]
public void Should_add_to_Prices_when_Model_publishes_price()
{
decimal expected = 1.23m;
var priceStream = new Subject<decimal>();
_myModelMock.Setup(svc => svc.PriceStream(It.IsAny<string>())).Returns(priceStream);
_viewModel.Show("SomeSymbol");
// Schedule the OnNext
_schedulerProvider.ThreadPool.Schedule(() => priceStream.OnNext(expected));
Assert.AreEqual(0, _viewModel.Prices.Count);
// Execute the OnNext action
_schedulerProvider.ThreadPool.AdvanceBy(1);
Assert.AreEqual(0, _viewModel.Prices.Count);
// Execute the OnNext handler
_schedulerProvider.Dispatcher.AdvanceBy(1);
Assert.AreEqual(1, _viewModel.Prices.Count);
Assert.AreEqual(expected, _viewModel.Prices.First());
}
[TestMethod]
public void Should_disconnect_if_no_prices_for_10_seconds()
{
var timeoutPeriod = TimeSpan.FromSeconds(10);
var priceStream = Observable.Never<decimal>();
_myModelMock.Setup(svc => svc.PriceStream(It.IsAny<string>())).Returns(priceStream);
_viewModel.Show("SomeSymbol");
_schedulerProvider.ThreadPool.AdvanceBy(timeoutPeriod.Ticks - 1);
Assert.IsTrue(_viewModel.IsConnected);
_schedulerProvider.ThreadPool.AdvanceBy(timeoutPeriod.Ticks);
Assert.IsFalse(_viewModel.IsConnected);
}
Output:
2 passed, 0 failed, 0 skipped, took 0.41 seconds (MSTest 10.0).
These two tests ensure five things:
- That the
Priceproperty has prices added to it as the model produces them - That the sequence is subscribed to on the ThreadPool
- That the
Priceproperty is updated on the Dispatcher i.e. the sequence is observed on the Dispatcher - That a timeout of 10 seconds between prices will set the ViewModel to disconnected
- The tests run fast.
While the time to run the tests is not that impressive, most of that time seems to be spent warming up my test harness. Moreover, increasing the test count to 10 only adds 0.03seconds. In general, a modern CPU should be able to execute thousands of unit tests per second.
In the first test, we can see that only once both the ThreadPool and the Dispatcher schedulers have been run will we get a result. In the second test, it helps to verify that the timeout is not less than 10 seconds.
In some scenarios, you are not interested in the scheduler and you want to be focusing your tests on other functionality. If this is the case, then you may want to create another test implementation of the ISchedulerProvider that returns the ImmediateScheduler for all of its members. That can help reduce the noise in your tests.
public sealed class ImmediateSchedulers : ISchedulerService
{
public IScheduler CurrentThread => Scheduler.Immediate;
public IScheduler Dispatcher => Scheduler.Immediate;
public IScheduler Immediate => Scheduler.Immediate;
public IScheduler NewThread => Scheduler.Immediate;
public IScheduler ThreadPool => Scheduler.Immediate;
}
Advanced features - ITestableObserver
The TestScheduler provides further advanced features. These can be useful when parts of your test setup need to run at particular virtual times.
Start(Func<IObservable<T>>)
There are three overloads to Start, which are used to start an observable sequence at a given time, record the notifications it makes and dispose of the subscription at a given time. This can be confusing at first, as the parameterless overload of Start is quite unrelated. These three overloads return an ITestableObserver<T> which allows you to record the notifications from an observable sequence, much like the Materialize method we saw in the Transformation chapter.
public interface ITestableObserver<T> : IObserver<T>
{
// Gets recorded notifications received by the observer.
IList<Recorded<Notification<T>>> Messages { get; }
}
While there are three overloads, we will look at the most specific one first. This overload takes four parameters:
- an observable sequence factory delegate
- the point in time to invoke the factory
- the point in time to subscribe to the observable sequence returned from the factory
- the point in time to dispose of the subscription
The time for the last three parameters is measured in ticks, as per the rest of the TestScheduler members.
public ITestableObserver<T> Start<T>(
Func<IObservable<T>> create,
long created,
long subscribed,
long disposed)
{...}
We could use this method to test the Observable.Interval factory method. Here, we create an observable sequence that spawns a value every second for 4 seconds. We use the TestScheduler.Start method to create and subscribe to it immediately (by passing 0 for the second and third parameters). We dispose of our subscription after 5 seconds. Once the Start method has run, we output what we have recorded.
var scheduler = new TestScheduler();
var source = Observable.Interval(TimeSpan.FromSeconds(1), scheduler)
.Take(4);
var testObserver = scheduler.Start(
() => source,
0,
0,
TimeSpan.FromSeconds(5).Ticks);
Console.WriteLine("Time is {0} ticks", scheduler.Clock);
Console.WriteLine("Received {0} notifications", testObserver.Messages.Count);
foreach (Recorded<Notification<long>> message in testObserver.Messages)
{
Console.WriteLine("{0} @ {1}", message.Value, message.Time);
}
Output:
Time is 50000000 ticks
Received 5 notifications
OnNext(0) @ 10000001
OnNext(1) @ 20000001
OnNext(2) @ 30000001
OnNext(3) @ 40000001
OnCompleted() @ 40000001
Note that the ITestObserver<T> records OnNext and OnCompleted notifications. If the sequence was to terminate in error, the ITestObserver<T> would record the OnError notification instead.
We can play with the input variables to see the impact it makes. We know that the Observable.Interval method is a Cold Observable, so the virtual time of the creation is not relevant. Changing the virtual time of the subscription can change our results. If we change it to 2 seconds, we will notice that if we leave the disposal time at 5 seconds, we will miss some messages.
var testObserver = scheduler.Start(
() => Observable.Interval(TimeSpan.FromSeconds(1), scheduler).Take(4),
0,
TimeSpan.FromSeconds(2).Ticks,
TimeSpan.FromSeconds(5).Ticks);
Output:
Time is 50000000 ticks
Received 2 notifications
OnNext(0) @ 30000000
OnNext(1) @ 40000000
We start the subscription at 2 seconds; the Interval produces values after each second (i.e. second 3 and 4), and we dispose on second 5. So we miss the other two OnNext messages as well as the OnCompleted message.
There are two other overloads to this TestScheduler.Start method.
public ITestableObserver<T> Start<T>(Func<IObservable<T>> create, long disposed)
{
if (create == null)
{
throw new ArgumentNullException("create");
}
else
{
return this.Start<T>(create, 100L, 200L, disposed);
}
}
public ITestableObserver<T> Start<T>(Func<IObservable<T>> create)
{
if (create == null)
{
throw new ArgumentNullException("create");
}
else
{
return this.Start<T>(create, 100L, 200L, 1000L);
}
}
As you can see, these overloads just call through to the variant we have been looking at, but passing some default values. These default values provide short gaps before creation and between creation and subscription, giving enough space to configure other things to happen between them. And then the disposal happens a bit later, allowing a little longer for the thing to run. There's nothing particularly magical about these default values, but if you value a lack of clutter over it being completely obvious what happens when, and are happy to rely on the invisible effects of convention, then you might prefer this. The Rx source code itself contains thousands of tests, and a very large number of them use the simplest Start overload, and developers working in the code base day in, day out soon get used to the idea that creation occurs at time 100, and subscription at time 200, and that you test everything you need to before 1000.
CreateColdObservable
Just as we can record an observable sequence, we can also use CreateColdObservable to play back a set of Recorded<Notification<int>>. The signature for CreateColdObservable simply takes a params array of recorded notifications.
// Creates a cold observable from an array of notifications.
// Returns a cold observable exhibiting the specified message behavior.
public ITestableObservable<T> CreateColdObservable<T>(
params Recorded<Notification<T>>[] messages)
{...}
The CreateColdObservable returns an ITestableObservable<T>. This interface extends IObservable<T> by exposing the list of "subscriptions" and the list of messages it will produce.
public interface ITestableObservable<T> : IObservable<T>
{
// Gets the subscriptions to the observable.
IList<Subscription> Subscriptions { get; }
// Gets the recorded notifications sent by the observable.
IList<Recorded<Notification<T>>> Messages { get; }
}
Using CreateColdObservable, we can emulate the Observable.Interval test we had earlier.
var scheduler = new TestScheduler();
var source = scheduler.CreateColdObservable(
new Recorded<Notification<long>>(10000000, Notification.CreateOnNext(0L)),
new Recorded<Notification<long>>(20000000, Notification.CreateOnNext(1L)),
new Recorded<Notification<long>>(30000000, Notification.CreateOnNext(2L)),
new Recorded<Notification<long>>(40000000, Notification.CreateOnNext(3L)),
new Recorded<Notification<long>>(40000000, Notification.CreateOnCompleted<long>())
);
var testObserver = scheduler.Start(
() => source,
0,
0,
TimeSpan.FromSeconds(5).Ticks);
Console.WriteLine("Time is {0} ticks", scheduler.Clock);
Console.WriteLine("Received {0} notifications", testObserver.Messages.Count);
foreach (Recorded<Notification<long>> message in testObserver.Messages)
{
Console.WriteLine(" {0} @ {1}", message.Value, message.Time);
}
Output:
Time is 50000000 ticks
Received 5 notifications
OnNext(0) @ 10000001
OnNext(1) @ 20000001
OnNext(2) @ 30000001
OnNext(3) @ 40000001
OnCompleted() @ 40000001
Note that our output is exactly the same as the previous example with Observable.Interval.
CreateHotObservable
We can also create hot test observable sequences using the CreateHotObservable method. It has the same parameters and return value as CreateColdObservable; the difference is that the virtual time specified for each message is now relative to when the observable was created, not when it is subscribed to as per the CreateColdObservable method.
This example is just that last "cold" sample, but creating a Hot observable instead.
var scheduler = new TestScheduler();
var source = scheduler.CreateHotObservable(
new Recorded<Notification<long>>(10000000, Notification.CreateOnNext(0L)),
// ...
Output:
Time is 50000000 ticks
Received 5 notifications
OnNext(0) @ 10000000
OnNext(1) @ 20000000
OnNext(2) @ 30000000
OnNext(3) @ 40000000
OnCompleted() @ 40000000
Note that the output is almost the same. Scheduling of the creation and subscription do not affect the Hot Observable, therefore the notifications happen 1 tick earlier than their Cold counterparts.
We can see the major difference a Hot Observable bears by changing the virtual create time and virtual subscribe time to be different values. With a Cold Observable, the virtual create time has no real impact, as subscription is what initiates any action. This means we cannot miss any early message on a Cold Observable. For Hot Observables, we can miss messages if we subscribe too late. Here, we create the Hot Observable immediately, but only subscribe to it after 1 second (thus missing the first message).
var scheduler = new TestScheduler();
var source = scheduler.CreateHotObservable(
new Recorded<Notification<long>>(10000000, Notification.CreateOnNext(0L)),
new Recorded<Notification<long>>(20000000, Notification.CreateOnNext(1L)),
new Recorded<Notification<long>>(30000000, Notification.CreateOnNext(2L)),
new Recorded<Notification<long>>(40000000, Notification.CreateOnNext(3L)),
new Recorded<Notification<long>>(40000000, Notification.CreateOnCompleted<long>())
);
var testObserver = scheduler.Start(
() => source,
0,
TimeSpan.FromSeconds(1).Ticks,
TimeSpan.FromSeconds(5).Ticks);
Console.WriteLine("Time is {0} ticks", scheduler.Clock);
Console.WriteLine("Received {0} notifications", testObserver.Messages.Count);
foreach (Recorded<Notification<long>> message in testObserver.Messages)
{
Console.WriteLine(" {0} @ {1}", message.Value, message.Time);
}
Output:
Time is 50000000 ticks
Received 4 notifications
OnNext(1) @ 20000000
OnNext(2) @ 30000000
OnNext(3) @ 40000000
OnCompleted() @ 40000000
CreateObserver
Finally, if you do not want to use the TestScheduler.Start methods, and you need more fine-grained control over your observer, you can use TestScheduler.CreateObserver(). This will return an ITestObserver that you can use to manage the subscriptions to your observable sequences with. Furthermore, you will still be exposed to the recorded messages and any subscribers.
Current industry standards demand broad coverage of automated unit tests to meet quality assurance standards. Concurrent programming, however, is often a difficult area to test well. Rx delivers a well-designed implementation of testing features, allowing deterministic and high-throughput testing. The TestScheduler provides methods to control virtual time and produce observable sequences for testing. This ability to easily and reliably test concurrent systems sets Rx apart from many other libraries.
