Hey there! So you want to know how LiveData in Android can handle updating a bunch of observers, like 100 of them, all at once? That’s super cool! Let’s break it down together in a fun and easy way. Ready? Let’s dive in!

What is LiveData?

First things first, LiveData is like a VIP backstage pass for your data. It’s an observable data holder class in Android that’s smart enough to know the lifecycle of your app components like activities and fragments. This means your UI only gets updates when it’s safe to do so. How awesome is that?

Design Pattern Behind LiveData

LiveData uses the Observer Pattern. Imagine you have a rockstar (your data) and a bunch of fans (the observers). When the rockstar releases a new song (data changes), all the fans get notified. This pattern makes sure everyone stays in the loop without you having to manage it manually.

How LiveData Works Internally

Let’s break down how LiveData keeps everything in sync, even if you have 100 fans… I mean, observers.

1. LiveData Initialization

When you create a LiveData object, it’s like setting up a new fan club with no members yet and no content.

val liveData = MutableLiveData<String>()

2. Adding Observers

Observers join the fan club using the observe method. Each observer is linked to a lifecycle, ensuring they only get updates when they’re active (like when your activity or fragment is visible).

liveData.observe(this, Observer { data ->
    // Update the UI with new data
})

Internally, when you add an observer, LiveData:

• Connects to Lifecycle: Hooks up the observer to the lifecycle of the activity or fragment.
• Wraps the Observer: Puts the observer in an ObserverWrapper to keep track of its state.

3. Storing Observers

LiveData keeps a list of observers using a special data structure called SafeIterableMap. Think of it as a super-organized guest list that’s safe to use with multiple threads, making sure no one gets left out or added twice.

private final SafeIterableMap<Observer<T>, ObserverWrapper> mObservers = new SafeIterableMap<>();

4. Updating Observers

When you update LiveData’s value using setValue or postValue, it’s like the rockstar releasing a new hit. LiveData goes through all its active fans and notifies them of the new song.

liveData.value = "New Hit Song"

Here’s what happens backstage:

1. Flag the Change: LiveData marks its data as changed and gets ready to notify the fans.
2. Notify Observers: It iterates through all active observers and calls their onChanged method, making sure everyone gets the new data.

Here’s a simplified version of what’s happening behind the curtain:

private void dispatchingValue(@Nullable ObserverWrapper initiator) {
    mDispatchingValue = true;
    do {
        mDispatchInvalidated = false;
        if (initiator != null) {
            considerNotify(initiator);
            initiator = null;
        } else {
            for (Iterator<Map.Entry<Observer<T>, ObserverWrapper>> iterator =
                    mObservers.iteratorWithAdditions(); iterator.hasNext();) {
                considerNotify(iterator.next().getValue());
                if (mDispatchInvalidated) {
                    break;
                }
            }
        }
    } while (mDispatchInvalidated);
    mDispatchingValue = false;
}

5. Threading and Concurrency

LiveData makes sure updates happen on the main thread. If you call postValue from a background thread, LiveData uses a handler to post the update to the main thread. It’s like making sure the rockstar only performs on the main stage.

private static final Object NOT_SET = new Object();
private final Object mDataLock = new Object();
private final Runnable mPostValueRunnable = new Runnable() {
    @Override
    public void run() {
        synchronized (mDataLock) {
            Object newValue = mPendingData;
            mPendingData = NOT_SET;
        }
        setValue((T) newValue);
    }
};

@MainThread
public void setValue(T value) {
    assertMainThread("setValue");
    mVersion++;
    mData = value;
    dispatchingValue(null);
}

public void postValue(T value) {
    boolean postTask;
    synchronized (mDataLock) {
        postTask = mPendingData == NOT_SET;
        mPendingData = value;
    }
    if (!postTask) {
        return;
    }
    ArchTaskExecutor.getInstance().postToMainThread(mPostValueRunnable);
}

This ensures thread safety and that the UI updates happen smoothly.

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Example: Updating 100 Observers

Imagine you have 100 fragments observing the same LiveData. When the LiveData value changes, all these fragments need to be notified and update their UI.

Here’s how it works:

1. Define LiveData in ViewModel:

class MyViewModel : ViewModel() {
    val liveData = MutableLiveData<String>()
}

2. Observers in Fragments:

class MyFragment : Fragment() {
    private lateinit var viewModel: MyViewModel

    override fun onCreateView(
        inflater: LayoutInflater, container: ViewGroup?,
        savedInstanceState: Bundle?
    ): View? {
        viewModel = ViewModelProvider(this).get(MyViewModel::class.java)
        viewModel.liveData.observe(viewLifecycleOwner, Observer { data ->
            // Update UI with new data
        })
        return inflater.inflate(R.layout.fragment_my, container, false)
    }
}

3. Updating LiveData:

viewModel.liveData.value = "Hello, 100 Fans!"f

When liveData.value is updated, LiveData goes through its list of 100 observers and calls their onChanged method, updating all of them efficiently and correctly.

Wrapping Up

So, that’s how LiveData works its magic to update all observers, even if you have 100 of them! It uses the Observer Pattern, keeps track of observers in a safe and efficient way, and ensures updates happen on the main thread. This design makes LiveData a rockstar for managing UI updates in Android apps.

Hope this makes things clear! If you have more questions or need further clarification, just let me know. Happy coding! 😊

This article is previously published on proandroiddev.com