Reactive Android Java programming

Introduction

Ever notice how Android methods often come in pairs? For every onCreate(), there is an onDestroy(), for every onStart(), there is an onStop(). The Android SDK commonly asks clients to register callbacks or extend base classes that override pairs of methods that correspond to reversible changes in state.

State is often expressed in Java code as mutable variables. A state changes when you assign a new value to the variable. If a variable can be one value at some points and another value at other points, that means there are two states that the variable can have. Everything that interacts with that variable needs to work correctly for each state the variable can be in. For example, if an instance variable is null in a class's constructor, and set to a value by some method in that class, then every method that tries to call a method on that variable needs to check whether the value of the variable is null before handling it, because there is no guarantee which state the variable is in. You will see a lot of code that looks like this when using this pattern for representing state:

if (mFoo != null) {
    mFoo.doSomething();
}

Additionally, mutator methods may need to check the state at runtime. For example, lazy initialization often looks like this:

if (mFoo == null) {
    mFoo = new Foo(...);
}

This is not bad in and of itself, if the states are well-defined and it's easy to reason about the set of possible states by looking at the code. However, it very, very quickly becomes difficult to reason about states when there are any of the following:

  • Multiple methods that can mutate state. For example, a hypothetical Connection class that reads and writes data over a socket might disconnect on a socket error from any read() or write() call. That means that before any read() or write() call, the state must be checked. (Real Java objects will often use Exceptions to short-circuit code blocks that enter an exceptional state).
  • Methods that throw a runtime error or have undefined behavior when in a certain state. For example, a class with an initialize() method may have methods that should only be called after initialize(), but the compiler will not be able to check whether initialize() has been called. This includes every method that has an assert statement on a mutable instance variable.
  • Multiple states that interact with each other. The number of states that independently-mutable variables can take is the product of the number of states of each of the variables. Often, variables are not strictly independent (e.g. the only method that mutates a certain variable also mutates another), so some states might be unreachable. However, it‘s not possible for the compiler to tell you which states are reachable when you’re using mutable instance variables, so you have to figure that out yourself! This makes it hard to exhaustively come up with unittest cases.

Motivating Example

Consider this seemingly-simple task: you have two variables, mA and mB, each of which could be either null or some real value of types A and B, respectively. Furthermore, you want to initialize a new variable, mC of type C, when the values of mA and mB are non-null, perhaps because the C constructor takes an A and a B. Finally, if mA or mB becomes null again after creating mC, reset mC to null. Also, you need to invoke a close() method on mC whenever mC is reset. And if mA or mB changes while mC exists, you need to call mC.close() and re-create mC with the new mA and mB.

class MyClass {
    private A mA = null;
    private B mB = null;
    private C mC = null;

    public void setA(A a) {
        mA = a;
        recalculateC();
    }

    public void setB(B b) {
        mB = b;
        recalculateC();
    }

    private void recalculateC() {
        // This method is always called when A or B changes, so if C exists, it
        // must first be reset.
        if (mC != null) {
            mC.close();
            mC = null;
        }
        if (mA != null && mB != null) {
            mC = new C(mA, mB);
        }
    }
}

This may be fine on its own. But chances are, you will want to do something with mC outside these methods. Every read will have to null-check, there's an undocumented but critical requirement that every write to mA and mB is done through setA() and setB(), and that recalculateC() is only called when mA or mB is mutating, or else it will implicitly close.

These undocumented dependencies can only be protected against regression by testing. The compiler will not tell you if you made a mistake, so there must be unittests covering every possible state change. And in this case, we have two variables, each with two states that each have two possible state transitions, so 8 test cases are needed to cover everything. And this is the simplest case of composing two independent nullable mutable variables.

Meanwhile, if you use the Observables framework:


class MyClass { private final Controller<A> mA = new Controller<>(); private final Controller<B> mb = new Controller<>(); { mA.and(mB).watch(ScopeFactories.both(C::new)); } public void setA(A a) { mA.set(a); } public void setB(B b) { mB.set(b); } }

In the instance initializer, we set up a simple state machine with two Controllers, which correspond to the mutable instance variables from the previous example, and an event that observes the state of the Controllers and invokes some logic on certain state changes.

The and() call composes the mA and mB, returning a new Observable that is only activated when both sources are activated, and then deactivated if either source is deactivated. mA and mB are activated or deactivated by set() and reset() calls, respectively. The set() method deactivates the state if the argument is null (the reset() method can also be used to deactivate the state).

The watch() call makes it so that when the composed Observable formed by mA.and(mB) is activated, a new C object will be created. When deactivated, that C object's close() method will be called.

This really does cover all the cases we need. If multiple set*() calls are made, an implicit reset() call will be made to the relevant Controller and the C object associated with the first scope will be close()d.

What‘s better about this? First, notice we **don’t need mutable variables**. Both Controller objects are final, and are never null. We don't at any point need to know what state the object is in inside any method implementations; the Controllers and the pipeline set up by the and() and watch() calls handle that for you.

Second, notice how the concerns of mutating and reacting to state are cleanly separated. The mutator methods setA() and setB() are concerned only with their respective Controllers, and the lifetime of the C object is managed in one place in the instance initializer.

Finally, the relationship between the A, B, and C objects is self-documenting. In the first approach with mutable variables, to understand that the lifetime of C is associated with the intersection of the lifetimes of A and B, one has to examine both setters and trace through recalculateC() from the perspective of both of its call sites. In the second approach, using Controllers, the relationship between A, B, and C is expressed holistically in one line.

Observables and Scopes

Think of an Observable as an encapsulation of a nullable, mutable variable, with one very important feature: the ability to register observers that will be notified when changes take place. The Observable API alone does not expose any state mutators, but it provides ways to register events that will be invoked when state changes.

An Observable has two states: activated and deactivated. There are two transitions between states: activation occurs when transitioning from deactivated to activated, and deactivation occurs when transitioning from activated to deactivated.

An activation is similar to setting a nullable, mutable variable that was null to a non-null value. A deactivation, likewise, is similar to setting a nullable, mutable variable that had a non-null value to null. The non-null value that an activation is associated with is called activation data.

To register events that should be invoked on these state transitions, we utilize scopes. When an Observable is activated, an observing scope is created, and when the Observable is deactivated, that scope is close()d.

The only requirement of a scope is that it implements Scope, which has a single close() method. (Scope extends java.lang.AutoCloseable, but does not throw checked exceptions. This means it can be used in try-with-resources statements.) The side-effects of activation are in the scope's constructor (or a ScopeFactory‘s create() method), and the side-effects of deactivation are in the scope’s close() method. This pairing of constructors with a close() is inspired by RAII in C++, and allows the activation data injected into the scope to be expressed as an immutable variable.

Registering scopes with Observables

To register scopes to track the state of an Observable, we call watch() on the Observable. The watch() method takes a single argument, a ScopeFactory, which has a create() method that returns a Scope. The ScopeFactory's create() method is called when the Observable activates, and the resulting Scope's close() method is called when the Observable deactivates.

Lambda syntax can be used to easily construct ScopeFactory objects without much boilerplate. For instance, if we want to simply log the transitions of an Observable, we might do it like this:

void logStateTransitions(Observable<?> observable) {
    observable.watch(() -> {
        Log.d(TAG, "activated");
        return () -> Log.d(TAG, "deactivated");
    });
};

This is equivalent to the following, much more verbose version:

void logStateTransitions(Observable<?> observable) {
    observable.watch(new VoidScopeFactory() {
        @Override
        public Scope create() {
            Log.d(TAG, "activated");
            return new Scope() {
                @Override
                public void close() {
                    Log.d(TAG, "deactivated");
                }
            };
        }
    });
}

As you can see, the version that uses lambdas is much more readable, as long as you understand what a ScopeFactory is.

Either way, when logStateTransitions() is called on an Observable, "activated" will be printed to the log when that Observable is activated, and "deactivated" will be printed to the log when that Observable is deactivated.

There are actually two types of ScopeFactory. VoidScopeFactory, as seen above, does not care about the activation data, and so its create() method takes no arguments. A normal ScopeFactory actually takes a single parameter to its create() method, so that the behavior of the scope can depend on what data the Observable is activated with.

Say we have an Observable<String> and we want to log the data it is activated with:

void logStateTransitionsWithData(Observable<String> observable) {
    observable.watch((String s) -> {
        Log.d(TAG, "activated with data: " + s);
        return () -> Log.d(TAG, "deactivated");
    });
}

Mutating state with Controllers

The Observable interface does not provide any way to directly change the state of the Observable. However, the Controller object, which implements Observable, exposes two methods to do just that: set() and reset().

Remember that Controllers are basically nullable, mutable variables that let you register callbacks, through the Observable interface, that are run when the variable changes.

With this in mind, the set() method on Controller is like setting a mutable variable to a value. The reset() method is like setting the mutable variable to null. Any nullable mutable variable can be replaced by a Controller.

Here are some guarantees that Controllers provide:

  • Start out in the deactivated state.
  • If the parameter of set() is non-null, it enters the activated state.
  • If the parameter of set() is null, it enters the deactivated state.
  • If in the activated state, reset() and set(null) enter the deactivated state.
  • If already in the deactivated state, reset() and set(null) do nothing.
  • If in the activated state with data data1, set(data2) no-ops if data1.equals(data2).
  • If in the activated state, and the new data is not equal() to the current data, set() implicitly deactivates and reactivates with the new data.

As corollaries, any registered ScopeFactory objects will:

  • have their create() methods invoked exactly once for each non-null set() call
  • have their resulting Scopes close()d exactly once when reset() or set() to null
  • always clean up scopes from previous activations when new activations occur

This means this:

void helloGoodbye(Controller<String> message) {
    message.set("hello");
    message.set("goodbye");
    message.set(null);
}

has the same behavior as this:

void helloGoodbye(Controller<String> message) {
    message.set("hello");
    message.reset();
    message.set("goodbye");
    message.reset();
}

Essentially, a Controller adapts two states with two possible actions each:

  • deactivated: set, reset
  • activated: set, reset

into a well-defined state machine with two states and two transitions:

  • deactivated: set
  • activated: reset

... by dropping redundant reset() calls and inserting implicit reset() calls between contiguous set() calls. This cuts the number of state transitions you need to worry about in half!

Since Controllers implement Observable, you can register ScopeFactory objects with watch() the same way as in the previous section, or inject a Controller into any method that takes an Observable of the same parametric type.

Observables without data

The state of a Controller<T> is isomorphic to that of a nullable T variable for all types T. But there are many cases where what we really want is a representation of a boolean state: on or off, active or inactive, and don't need any activation data.

For these cases, the org.chromium.chromecast.base.Unit class is used to denote the fact that there is no data associated with the controller. The Unit type is inspired by the type of the same name in many functional programming languages, and represents a type with only one possible instance (aka Singleton).

To make a controller without data, you can therefore use Controller<Unit>. Since Unit means “no data,” and there's only one way to get a Unit instance (through the Unit.unit() method), this maps correctly to the concept of a mutable boolean value.

Note that because the instance of Unit equals itself, calling set() on a Controller<Unit> when it is already activated will no-op, making the behavior of set(Unit.unit()) and reset() symmetric.

Example:

{
    Controller<Unit> onOrOff = new Controller<>();
    onOrOff.watch(() -> {
        Log.d(TAG, "on");
        return () -> Log.d(TAG, "off");
    });
    onOrOff.set(Unit.unit()); // Turns on.
    onOrOff.set(Unit.unit()); // Does nothing because it's already on.
    onOrOff.reset(); // Turns off.
    onOrOff.reset(); // Does nothing because it's already off.
}

Composing Observables with and()

In the motivating example, we wanted to invoke a callback once two independent states have been activated.

If there are two independent states, there are four possible combinations of states. Given two independent states, A and B, there are four states in the time-independent product state space:

  • neither
  • just A
  • just B
  • A and B

...and eight transitions:

  • neither <-> just A
  • neither <-> just B
  • just A <-> A and B
  • just B <-> A and B

The Observable interface gives us a convenient way to get the (A and B) state with a simple call:

public void logWhenBoth(Observable<A> observableA, Observable<B> observableB) {
    observableA.and(observableB).watch(...);
}

The and() method takes the calling Observable and the given other Observable and returns a new Observable that is only activated when both input Observables are activated.

One way to think about it is that the and() call collapses the three states (neither), (just A), and (just B) into one deactivated state, and treats the state both as activated. For observers of the and()-composition of states, one needs only worry about the two states, deactivated and activated, same as with any other observer.

So how do we get the data in the watch() call? Let's say we want to log when both Observables are activated:

public void logWhenBoth(Observable<A> observableA, Observable<B> observableB) {
    observableA.and(observableB).watch((Both<A, B> data) -> {
        A a = data.first;
        B b = data.second;
        Log.d(TAG, "both activated: a=" + a + ", b=" + b);
        return () -> Log.d(TAG, "deactivated");
    });
}

The type of the activation data for an and()-composed Observable is Both. The Both type has two generic parameters, and first and second public fields to access the data it encapsulates. It is essentially a trick to box multiple values into a single object, so we only ever need ScopeFactory interfaces that take a single argument.

Since the and() method returns an Observable, the result can itself call and(), whose result can itself call and(), ad infinitum:

    observableA.and(observableB).and(observableC).and(observableD)...

But beware, as the associated type of the Observable gets uglier and uglier:

    a.and(b).and(c).and(d).watch((Both<Both<Both<A, B>, C>, D> data) -> {
        A aData = data.first.first.first;
        B bData = data.first.first.second;
        C cData = data.first.second;
        D dData = data.second;
        Log.d(TAG, "a=%s, b=%s, c=%s, d=%s", aData, bData, cData, dData);
        return () -> Log.d(TAG, "exit");
    });

One one hand, it's kind of neat that you can do that at all. But it does come at a cost to readability. The compiler can catch you if you mess up the first.first.second chains if the types are different, but it is regrettable that this much work is required to read the compound data. Some methods for alleviating this are described below.

Imposing order dependency with andThen()

Every composition of states up to this point has been time-independent. For example, stateA.and(stateB) doesn't care if stateA or stateB was activated first, so it can be activated by either activating stateA and then stateB, or by activating stateB and then stateA.

This means the state (A and B), extracted by the and() method on Observable, is too ambiguous for knowing the order of activation. We must partition the state (A and B) into (A and then B) and (B and then A). The time-dependent state space for two Observables looks like this, with five states:

  • neither
  • just A
  • just B
  • A and then B
  • B and then A

...and ten transitions:

  • neither <-> just A
  • neither <-> just B
  • just A <--> A and then B
  • just B <--> B and then A
  • A and then B --> just B
  • B and then A --> just A

Calling stateA.andThen(stateB) returns an Observable representing the (A and then B) state from above. The resulting Observable will only activate on the transition between (just A) and (A and then B), and will not activate on the transition between (just B) and (B and then A).

Observers as Scopes

Sometimes you might want to only watch() an Observable for a limited time, for instance, until some other Observable is activated. So how do you remove an observer?

The watch() method actually returns a Scope, which, when close()d, will unregister the ScopeFactory registered in the watch() call. To watch() for a limited time, simply store the Scope somewhere, and call close() on it when you're done.

    private final Observable<String> mMessages = ...;
    private final List<String> mLog = ...;
    private Scope mObserver = null;

    public void startRecording() {
        if (mObserver != null) stopRecording();
        mObserver = mMessages.watch(ScopeFactories.onEnter(mLog::add));
    }

    public void stopRecording() {
        if (mObserver == null) return;
        mObserver.close();
    }

... wait a minute, are those null-checks? And a mutable variable? I thought this framework was supposed to get rid of those!

... hold on, mObserver is a Scope... that means we can use it in another watch() call!

    private final Observable<String> mMessages = ...;
    private final List<String> mLog = ...;
    private final Controller<Unit> mRecordingState = ...;

    {
        // When mRecordingState is activated, a ScopeFactory is registered to
        // watch mMessages.
        mRecordingState.watch(() -> {
            // When mRecordingState is deactivated, the Scope representing the
            // fact that we are watching mMessages is closed, so new messages
            // will stop being added to the log.
            return mMessages.watch(ScopeFactories.onEnter(mLog::add));
        });
    }

    public void startRecording() {
        mRecordingState.set(Unit.unit());
    }

    public void stopRecording() {
        mRecordingState.reset();
    }

Now we have removed the mutable variable and delegated all management of state to Observables.

But wait, we could have done the same thing with and():

    {
        mRecordingState.and(mMessages).watch(ScopeFactories.onEnter(
                (Both<Unit, String> data) -> mLog.add(data.second)));
    }

But here we can see the drawbacks of that approach. We need to deconstruct the Both object. Though the below section shows a way to circumvent that when only using a single and() call, it gets much harder to work with longer chains of and()-composed Observables.

Recall that deconstructing larger Both trees is ugly:

    stateA.and(stateB).and(stateC).and(stateD).watch(data -> {
        A a = data.first.first.first;
        B b = data.first.first.second;
        C c = data.first.second;
        D d = data.second;
        ...
    });

If we only care about registering a Scope for when all four Observables are activated, then we can use nested watch() calls instead:

    stateA.watch(a -> stateB.watch(b -> stateC.watch(c -> stateD.watch(d -> {
        ...
    }))));

This is called watch-currying, and is a useful alternative to and() calls when registering ScopeFactory objects for the intersection of many Observables.

To show why this works, let's simplify to just this:

   stateA.watch(a -> stateB.watch(b -> ...));

If stateA is activated first, then the a -> stateB.watch(b -> ...) lambda, which is a ScopeFactory, will start watching stateB. If stateB is then activated, then the b -> ... lambda will execute. If stateB is then deactivated, then the Scope created by that lambda will close(), or if stateA is deactivated first, then the watch() Scope that watches stateA will close().

The imporant fact that makes this work is that a watch() Scope that is activated is implicitly deactivated when closed. In other words, if stateA and stateB are activated, and then stateA deactivates, the fact that the watch() Scope inside stateA's watch() call is closed implies that stateB's exit handler is called.

The fact that unregistering activated ScopeFactories implicitly closes their Scopes means that Scopes will clean up after themselves. Keep in mind, this means that if the exit handler of a Scope is called, it could mean either that the Observable that it is observing deactivated, or that the ScopeFactory that created the Scope was unregistered from the Observable (by calling the watch-scope's close() method).

It is still preferable to use and(), because that's easier to read, but if an and()-chain becomes too clunky, and just needs to register a callback rather than return an Observable, you can use watch-currying to avoid deconstructing nasty Both objects.

Increase readability for ScopeFactories with wrapper methods

The ScopeFactories class contains several helper methods to increase the fluency and readability of common cases that ScopeFactory objects might be used for.

Use onEnter() and onExit() to observe only one kind of transition

Every ScopeFactory returns a Scope, but sometimes clients do not care about when the state deactivates, only when it activates. It's possible to create a ScopeFactory with lambda syntax to do the job like this:

{
    observable.watch((String data) -> {
        Log.d(TAG, "activated: data=" + data);
        return () -> {};
    });
}

The return () -> {}; statement in the lambda corresponds to having no side-effects to handle the destructor, but this is not very readable.

To make intentions clearer, the onEnter() method can wrap any Runnable or Consumer of the activation data's type:

{
    // Without data.
    observable.watch(ScopeFactories.onEnter(() -> Log.d(TAG, "activated")));
    // With data.
    observable.watch(ScopeFactories.onEnter((String data) -> {
        Log.d(TAG, "activated: data=" + data);
    }));
}

Likewise, onExit() is used the same way to transform any Runnable or Consumer of the activation data's type into a ScopeFactory that only has side effects when the state is deactivated.

Deconstructing Both objects

When you use the and() method on Observable to create an Observable<Both>, recall that the ScopeFactory passed to watch() must look like this:

{
    observableA.and(observableB).watch((Both<A, B> data) -> {
        A a = data.first;
        B b = data.second;
        Log.d(TAG, "on enter: a = " + a + "; b = " + b);
        return () -> Log.d(TAG, "on exit: a = " + a + "; b = " + b);
    });
}

ScopeFactories provides a helper method to turn any function that takes two arguments and returns a Scope into a ScopeFactory<Both>, which deconstructs the Both object for you and passes the constituent parts into the function.

Using ScopeFactories.both(), we can rewrite the above like this:

{
    observableA.and(observableB).watch(ScopeFactories.both((A a, B b) -> {
        Log.d(TAG, "on enter: a = " + a + "; b = " + b);
        return () -> Log.d(TAG, "on exit: a = " + a + "; b = " + b);
    }));
}

The onEnter() and onExit() helpers can also take a consumer of two arguments and return an appropriate ScopeFactory<Both>:

{
    Observable<Both<A, B>> both = observableA.and(observableB);
    both.watch(ScopeFactories.onEnter((A a, B b) -> {
        Log.d(TAG, "on enter: a = " + a + "; b = " + b);
    }));
    both.watch(ScopeFactories.onExit((A a, B b) -> {
        Log.d(TAG, "on exit: a = " + a + "; b = " + b);
    }));
}

Data flow

There are numerous instances where one may want to take the activation data of some Observable and use it to set the state of a Controller, and reset that Controller when the Observable is deactivated. A shortcut to doing this without having to instantiate any Controller is provided with the map() method in the Observable interface.

For example, we might have an Activity that overrides onNewIntent(), and extracts some data from the Intent it receives. We might want to register observers on the extracted data rather than the Intent itself, as some work needs to be done to unparcel the data we care about from the Intent.

public class MyActivity extends Activity {
    private final Controller<Intent> mIntentState = new Controller<>();

    {
        Observable<Uri> uriState = mIntentState.map(Intent::getData);
        Observable<String> instanceIdState = uriState.map(Uri::getPath);
        ...
    }

    public void onCreate() {
        super.onCreate();
        mIntentState.set(getIntent());
    }

    public void onNewIntent(Intent intent) {
        super.onNewIntent(intent);
        mIntentState.set(intent);
    }
}

The map() method takes any function on the Observable's activation data and creates a new Observable of the result of that function applied to the original Observable's activation data. So the activation lifetime of uriState and instanceIdState are the same as mIntentState in this example.

The instance initializer can then call watch() on uriState or instanceIdState to register callbacks for when we get a new URI or instance ID, and the process of extracting the URI from the Intent and the instance ID from the Uri is delegated to methods with no side-effects.

Handling null

If a function provided to a map() method returns null, then the resulting Observable will be put in a deactivated state, even if the source Observable is activated. This can be used to filter invalid data from Observables in the pipeline:

{
    mIntentState.map(Intent::getExtras)
            .map((Bundle bundle) -> bundle.getString(INTENT_EXTRA_FOO))
            .watch((String foo) -> ...);
}

The bundle.getString() call might return null if the source Intent does not have the correct extra data field set. When this happens, the resulting Observable simply does not activate, so the ScopeFactory registered in the watch() call does not need to worry that foo might be null.

Filtering data

One may wish to construct an Observable that is only activated if some predicate on some other Observable's activation data is true. This is easily done using the filter() method on Observable.

This example will only log "Got FOO intent" if mIntentState was set() with an Intent with action "org.my.app.action.FOO":

{
    String ACTION_FOO = "org.my.app.action.FOO";
    mIntentState.map(Intent::getAction)
            .filter(ACTION_FOO::equals)
            .watch(ScopeFactories.onEnter(() -> {
                Log.d(TAG, "Got FOO intent");
            }));
}

Since Observable<T>#filter() takes any Predicate<T>, which is a functional interface whose method takes a T and returns a boolean, the parameter can be an instance of a class that implements Predicate<T>:

    class InRangePredicate implements Predicate<Integer> {
        private final int mMin;
        private final int mMax;

        private InRangePredicate(int min, int max) {
            mMin = min;
            mMax = max;
        }

        @Override
        public boolean test(Integer value) {
            return mMin <= value && value <= mMax;
        }
    }

    InRangePredicate inRange(int min, int max) {
        return new InRangePredicate(min, max);
    }

    Controller<Integer> hasIntState = new Controller<>();
    Observable<Integer> hasValidIntState = hasIntState.filter(inRange(0, 10));
}

... or a method reference for a method that takes the activation data and returns a boolean:

    class Util {
        static boolean inRange(int i) {
            return 0 <= i && i <= 10;
        }
    }
    Controller<Integer> hasIntState = new Controller<>();
    Observable<Integer> hasValidIntState = hasIntState.filter(Util::inRange);

... or a lambda that takes the activation data and returns a boolean:

    Controller<Integer> hasIntState = new Controller<>();
    Observable<Integer> hasValidIntState =
            hasIntState.filter(i -> 0 <= i && i <= 10);

Tips and best practices

Construct the pipeline before modifying it

Consider this code:

    Controller<String> c = new Controller<>();
    c.set("hi");
    c.reset();
    c.watch(ScopeFactories.onEnter(s -> Log.d(TAG, s)));

Will the callback registered in the watch() call get fired? It turns out that it will not, since c is deactivated when watch() is made. But if the watch() call is made before the set() call, then the callback is fired.

Sometimes this is what you want, but it's best to avoid any ambiguity like this. Generally, Observable methods like watch() should be called before any Controller methods. A couple of things that one can do to help with this:

  • Instantiate Controller objects in field initializers, not the constructor.
  • Set up the pipeline (watch(), and(), map(), etc.) in an instance initializer. This is run before anything else when creating an instance, including the constructor, and is the same regardless of which constructor is being used. This also removes the potential of accidentally depending on constructor parameters or mutable instance variables in the pipeline, which can be dangerous compared to adapting them to Observables.
  • In the instance initializer, Observables composed from other Observables can usually be local variables rather than instance variables. This prevents code outside the initializer from watch()ing these Observables after the instance has been initialized.
  • Do not call Controller mutator methods (set() or reset()) inside the instance initializer. They may be called in the constructor or any instance methods.
  • Alternatively, the concerns of creating the pipeline and adapting function calls to state changes of Controllers can be separated by using a factory function.

Manipulating state inside observers

What happens here?

    Controller<Object> c = new Controller<>();
    c.watch(() -> {
        Log.d(TAG, "enter");
        c.reset();
        return () -> Log.d(TAG, "exit");
    });
    c.set("ding");

Here, we reset() the same Controller in an activation observer for that very Controller!

This is in fact safe, though there should be few places you need to do something like this. Currently, Controllers notify all observers synchronously on the thread that set() or reset() was called in (so they are not thread safe), but if an observer calls set() or reset() again while observers are still being notified, the set() or reset() call gets queued and handled only after all observers have been notified. This allows a deterministic and unastonishing order of execution for the above example: the log will show “enter”, followed immediately by “exit”.

Note that if you set() a controller with a value that is never null inside an activation handler, you will get an infinite loop.

    Controller<Integer> c = new Controller<>();
    c.watch(ScopeFactories.onEnter(x -> c.set(x + 1))); // Danger!
    c.set(0); // Infinite loop!

Whenever the Controller is set with a value, the observing scope immediately sets it with a new value, recurring infinitely.

It‘s possible to still be safe if you can guarantee that set() isn’t called or set(null) is called in some base case for all recursive stacks of activation handlers, but if you do that, it's your job to solve the halting problem.

It is good practice to avoid calling set() or reset() on Controllers inside ScopeFactory event handlers altogether, but there are many safe ways that are useful. and()-composed Observables, for example, use Controllers under the hood to know when to notify.

Testing

One of the most important aspects of using Observables is that they are very testable. The Observable cleanly separates the concerns of mutating program state and responding to program state. Reactors, or observers, registered in watch() methods tend to be functional, i.e. with no side effects, though this isn't a strict requirement (see the above section).

If you write a class that implements Observable or returns an Observable in one of its methods, it's easy to test the events it emits by using the ReactiveRecorder test utility function. This class, which is only allowed in tests, provides a fluent interface for describing the expected output of an Observable.

To use this in your tests, add //chromecast/base:cast_base_test_utils_java to your JUnit test target's GN deps.

As an example, imagine we want to test a class called FlipFlop, which implements Observable and changes from deactivated to activated every time its flip method is called. The tests might look like this:

import org.chromium.chromecast.base.ReactiveRecorder;
... // other imports
public class FlipFlopTest {
    @Test
    public void testStartsDeactivated() {
        FlipFlop f = new FlipFlop();
        ReactiveRecorder recorder = ReactiveRecorder.record(f);
        // No events should be emitted.
        recorder.verify().end();
    }

    @Test
    public void testFlipOnceActivatesObserver() {
        FlipFlop f = new FlipFlop();
        ReactiveRecorder recorder = ReactiveRecorder.record(f);
        f.flip();
        // A single activation should have been emitted.
        recorder.verify().entered().end();
    }

    @Test
    public void testFlipTwiceActivatesThenDeactivates() {
        FlipFlop f = new FlipFlop();
        ReactiveRecorder recorder = ReactiveRecorder.record(f);
        f.flip();
        f.flip();
        // Expect an activation followed by a deactivation.
        recorder.verify().entered().exited().end();
    }
}

ReactiveRecorder's entered() and exited() methods can also take arguments to perform assertions on the activation data. ReactiveRecorder.record() can also take arbitrarily many Observable arguments and receive the events of all of the given Observables. In this case, the entered() and exited() methods have overloads that take an Observable as an argument, which can be used to assert which Observable emitted an event.

When to use Observables

Observables and Controllers are intended to succinctly adapt common Android SDK method pairs, whether they're callbacks for entering and exiting a state, or mutators to perform state changes, into a common pattern that better separates concerns and is composable.

Replace mutable, nullable variables

Every mutable, nullable variable is a variable that you constantly have to null-check before using. A Controller can be used to refactor these variables into a final Controller.

The important insight is that you tend to only read a variable when state changes, either after the variable itself is known to change, or when some other state changes.

First, let's consider an Activity that registers a BroadcastReceiver in onStart() and unregisters the BroadcastReceiver in onStop().

We will ignore for now that Android tries to guarantee that pathological call sequences like multiple onStart()s in a row or an onStop() before the first onStart() will not occur, because these guarantees are not known to the Java compiler and similar guarantees can't be relied on for all events.

class MyActivity extends Activity {
    private BroadcastReceiver mReceiver = null;

    @Override
    public void onStart() {
        super.onStart();
        if (mReceiver != null)
            unregisterReceiver(mReceiver);
        mReceiver = new BroadcastReceiver(...);
        registerReceiver(mReceiver);
    }

    @Override
    public void onStop() {
        if (mReceiver != null)
            unregisterReceiver(mReceiver);
        mReceiver = null;
        super.onStop();
    }
}

Without the assumption that Android will call onStart() and onStop() in reasonable orders, we need to check the state of the mReceiver variable each time before it is used. And making that assumption is prone to backfiring, as it's a recipe for NullPointerExceptions, IllegalStateExceptions, and other horrors in general practice.

Here's the refactored version that uses a Controller:

class MyActivity extends Activity {
    private final Controller<Unit> mStartedState = new Controller<>();

    {
        mStartedState.watch(() -> {
            final BroadcastReceiver receiver = new BroadcastReceiver(...);
            registerReceiver(receiver);
            return () -> unregisterReceiver(receiver);
        });
    }

    @Override
    public void onStart() {
        super.onStart();
        mStartedState.set(Unit.unit());
    }

    @Override
    public void onStop() {
        mStartedState.reset();
        super.onStop();
    }
}

The refactored version better separates concerns. BroadcastReceiver registration and unregistration is handled in a small area of the code, rather than spread throughout the class, and the BroadcastReceiver doesn't need to be stored in a mutable variable. No code outside the scope in which the BroadcastReceiver object is relevant can touch it, and the onStart() and onStop() methods have no logic except toggling the Controller that represents whether the Activity is started. Best of all, there are no null checks, and no need for any.

Asynchronous initialization

Some methods run asynchronously and take a callback that is run when the work is complete. We can set() Controllers in such callbacks to adapt this pattern to Observables, which can be used to create asynchronous initialization pipelines.

This example shows how one can link up the outputs of multiple asynchronous functions that use the callback-passing style using Controllers, and encapsulating the complicated setup into a single function that returns an Observable.

public class AsyncExample {
    private static final String TAG = "AsyncExample";

    // Adapts the callback-style asynchronous Baz function to an Observable.
    // Shows how a
    public static Observable<Baz> createBazDefault() {
        // Begin constructing a Foo.
        Controller<Foo> fooState = new Controller<>();
        // Set the fooState controller when created, reset on errors.
        Foo.createAsync(fooState::set, fooState::reset);
        // Bar requires Foo to initialize.
        Controller<Bar> barState = new Controller<>();
        fooState.watch((Foo foo) -> {
            Bar.createAsync(foo, barState::set);
            // If fooState is reset, then barState is also reset.
            return barState::reset;
        });
        // Baz requires Foo and Bar to initialize.
        Controller<Baz> bazState = new Controller<>();
        fooState.and(barState).watch(ScopeFactories.both((Foo foo, Bar bar) -> {
            Baz.createAsync(foo, bar, bazState::set);
            // If fooState or barState is reset, then bazState is also reset.
            return bazState::reset;
        }));
        return bazState;
    }

    public static void demo() {
        Observable<Baz> bazState = createBazDefault();
        bazState.watch(ScopeFactories.onEnter((Baz baz) -> {
            // This runs when the full initialization pipeline is complete.
            Log.d(TAG, "Baz created!");
        }));
    }

    public static class Foo {
        static void createAsync(Consumer<Foo> callback, Runnable onError) {...}
    }

    public static class Bar {
        static void createAsync(Foo foo, Consumer<Bar> callback) {...}
    }

    public static class Baz {
        static void createAsync(Foo foo, Bar bar, Consumer<Baz> callback) {...}
    }
}

This way, Observables can be used similarly to Promises, where a callback handling the underlying value can be registered before the underlying value is available. But unlike Promises, Observables provide a way to also handle teardowns, and to transitively tear down everything down stream when something is torn down.