kotlin的协程封装了线程的API，这个线程框架可以让我们很方便得编写异步代码。
虽然协程已经很方便了，但是如果再配合Google提供的架构组件的KTX扩展一起使用，那就更方便了。
//将 Kotlin 协程与架构组件一起使用
//ViewModelScope
implementation 'androidx.lifecycle:lifecycle-viewmodel-ktx:2.3.1'
//LifecycleScope
implementation 'androidx.lifecycle:lifecycle-runtime-ktx:2.2.0'
//liveData
implementation 'androidx.lifecycle:lifecycle-livedata-ktx:2.2.0'在使用ViewModelScope之前，先来回顾一下以前在ViewModel中使用协程的方式。自己管理CoroutineScope，在不需要的时候（一般是在onCleared()）进行取消。否则，可能造成资源浪费、内存泄露等问题。
class JetpackCoroutineViewModel : ViewModel() {
//在这个ViewModel中使用协程时,需要使用这个job来方便控制取消
private val viewModelJob = SupervisorJob()
//指定协程在哪里执行,并且可以由viewModelJob很方便地取消uiScope
private val uiScope = CoroutineScope(Dispatchers.Main + viewModelJob)
fun launchDataByOldWay() {
uiScope.launch {
//在后台执行
val result = getNetData()
//修改UI
log(result)
}
}
override fun onCleared() {
super.onCleared()
viewModelJob.cancel()
}
//将耗时任务切到IO线程去执行
private suspend fun getNetData() = withContext(Dispatchers.IO) {
//模拟网络耗时
delay(1000)
//模拟返回结果
"{}"
}
}看起来有很多的样板代码，而且在不需要的时候取消协程很容易忘。
正是在这种情况下，Google为我们创造了ViewModelScope，它通过向ViewModel类添加扩展属性来方便我们使用协程，而且在ViewModel被销毁时会自动取消其子协程。
class JetpackCoroutineViewModel : ViewModel() {
fun launchData() {
viewModelScope.launch {
//在后台执行
val result = getNetData()
//修改UI
log(result)
}
}
//将耗时任务切到IO线程去执行
private suspend fun getNetData() = withContext(Dispatchers.IO) {
//模拟网络耗时
delay(1000)
//模拟返回结果
"{}"
}
}所有CoroutineScope的初始化和取消都已经为我们完成了，只需要在代码里面使用viewModelScope即可开启一个新协程，而且还不用担心忘记取消的问题。
下面我们来看看Google是怎么实现的。
点进去看看源码，知根知底，万一后面遇到什么奇怪的bug，在知道原理的情况下，才能更快的想到解决办法。
private const val JOB_KEY = "androidx.lifecycle.ViewModelCoroutineScope.JOB_KEY"
/**
* [CoroutineScope] tied to this [ViewModel].
* This scope will be canceled when ViewModel will be cleared, i.e [ViewModel.onCleared] is called
*
* This scope is bound to
* [Dispatchers.Main.immediate][kotlinx.coroutines.MainCoroutineDispatcher.immediate]
*/
public val ViewModel.viewModelScope: CoroutineScope
get() {
//先从缓存中取值，有就直接返回
val scope: CoroutineScope? = this.getTag(JOB_KEY)
if (scope != null) {
return scope
}
//没有缓存就新建一个CloseableCoroutineScope
return setTagIfAbsent(
JOB_KEY,
CloseableCoroutineScope(SupervisorJob() + Dispatchers.Main.immediate)
)
}
internal class CloseableCoroutineScope(context: CoroutineContext) : Closeable, CoroutineScope {
override val coroutineContext: CoroutineContext = context
override fun close() {
coroutineContext.cancel()
}
}源码中首先是介绍了viewModelScope是什么，它其实是一个ViewModel的扩展属性，它的实际类型是CloseableCoroutineScope。这名字看起来就是一个可以取消的协程，果不其然，它实现了Closeable并在close方法中进行了取消。
每次在使用viewModelScope的时候，会先从缓存中取，如果没有才去新建一个CloseableCoroutineScope。需要注意的是，CloseableCoroutineScope的执行是在主线程中执行的。
我们现在需要知道的是缓存是怎么存储和取出的。
//ViewModel.java
// Can't use ConcurrentHashMap, because it can lose values on old apis (see b/37042460)
@Nullable
private final Map<String, Object> mBagOfTags = new HashMap<>();
/**
* Returns the tag associated with this viewmodel and the specified key.
*/
@SuppressWarnings({"TypeParameterUnusedInFormals", "unchecked"})
<T> T getTag(String key) {
if (mBagOfTags == null) {
return null;
}
synchronized (mBagOfTags) {
return (T) mBagOfTags.get(key);
}
}
/**
* Sets a tag associated with this viewmodel and a key.
* If the given {@code newValue} is {@link Closeable},
* it will be closed once {@link #clear()}.
* <p>
* If a value was already set for the given key, this calls do nothing and
* returns currently associated value, the given {@code newValue} would be ignored
* <p>
* If the ViewModel was already cleared then close() would be called on the returned object if
* it implements {@link Closeable}. The same object may receive multiple close calls, so method
* should be idempotent.
*/
@SuppressWarnings("unchecked")
<T> T setTagIfAbsent(String key, T newValue) {
T previous;
synchronized (mBagOfTags) {
previous = (T) mBagOfTags.get(key);
if (previous == null) {
mBagOfTags.put(key, newValue);
}
}
T result = previous == null ? newValue : previous;
if (mCleared) {
// It is possible that we'll call close() multiple times on the same object, but
// Closeable interface requires close method to be idempotent:
// "if the stream is already closed then invoking this method has no effect." (c)
closeWithRuntimeException(result);
}
return result;
}现在我们知道了，原来是存在了ViewModel的mBagOfTags中，它是一个HashMap。
知道了怎么存的，那么它是在什么时候用的呢？
@MainThread
final void clear() {
mCleared = true;
// Since clear() is final, this method is still called on mock objects
// and in those cases, mBagOfTags is null. It'll always be empty though
// because setTagIfAbsent and getTag are not final so we can skip
// clearing it
if (mBagOfTags != null) {
synchronized (mBagOfTags) {
for (Object value : mBagOfTags.values()) {
// see comment for the similar call in setTagIfAbsent
closeWithRuntimeException(value);
}
}
}
onCleared();
}
private static void closeWithRuntimeException(Object obj) {
if (obj instanceof Closeable) {
try {
((Closeable) obj).close();
} catch (IOException e) {
throw new RuntimeException(e);
}
}
}我在ViewModel中搜索了一下mBagOfTags，发现有一个clear方法，在里面将mBagOfTags遍历一遍，然后将所有value是Closeable的全部close。在上面的源码中，第一次使用viewModelScope的时候，会创建一个CloseableCoroutineScope，它实现了Closeable接口，并实现了close方法，刚好用来做取消操作。
看到这里，我们知道了：viewModelScope构建的协程是在ViewModel的clear方法回调时取消协程的。
而且，clear方法里面居然还有我们熟悉的onCleared方法调用。而onCleared我们知道是干什么的，当这个ViewModel不再使用时会回调这个方法，一般我们需要在此方法中做一些收尾工作，如取消观察者订阅、关闭资源之类的。
那么，大胆猜测一下，这个clear()方法应该也是在ViewModel要结束生命的时候调用的。
搜索了一下，发现clear方法是在ViewModelStore里面调用的。
public class ViewModelStore {
private final HashMap<String, ViewModel> mMap = new HashMap<>();
final void put(String key, ViewModel viewModel) {
ViewModel oldViewModel = mMap.put(key, viewModel);
if (oldViewModel != null) {
oldViewModel.onCleared();
}
}
final ViewModel get(String key) {
return mMap.get(key);
}
Set<String> keys() {
return new HashSet<>(mMap.keySet());
}
/**
* Clears internal storage and notifies ViewModels that they are no longer used.
*/
public final void clear() {
for (ViewModel vm : mMap.values()) {
vm.clear();
}
mMap.clear();
}
}ViewModelStore是一个容器，用于盛放ViewModel。在ViewModelStore的clear方法中调用了该ViewModelStore中所有ViewModel的clear方法。那么ViewModelStore的clear是在哪里调用的？我跟着追踪，发现是在ComponentActivity的构造方法中。
public ComponentActivity() {
Lifecycle lifecycle = getLifecycle();
getLifecycle().addObserver(new LifecycleEventObserver() {
@Override
public void onStateChanged(@NonNull LifecycleOwner source,
@NonNull Lifecycle.Event event) {
if (event == Lifecycle.Event.ON_DESTROY) {
if (!isChangingConfigurations()) {
getViewModelStore().clear();
}
}
}
});
}在Activity的生命周期走到onDestroy的时候调用ViewModelStore的clear做收尾工作。但是，注意一下，这个调用有个前提，此次走onDestroy不是因为配置更改才会去调用clear方法。
好的，到此为止，咱们理通了viewModelScope的协程是怎么做到自动取消的（ViewModel的mBagOfTags），以及是在什么时候进行取消的（ViewModel的clear()时）。
对于Lifecycle，Google贴心地提供了LifecycleScope，我们可以直接通过launch来创建Coroutine。
举个简单例子，比如在Activity的onCreate里面,每隔100毫秒更新一下TextView的文字。
lifecycleScope.launch {
repeat(100000) {
delay(100)
tvText.text = "$it"
}
}因为LifeCycle是可以感知组件的生命周期的，所以Activity一旦onDestroy了，相应的上面这个lifecycleScope。launch闭包的调用也会取消。
另外，lifecycleScope还贴心地提供了launchWhenCreated、launchWhenStarted、launchWhenResumed方法，这些方法的闭包里面有协程的作用域，它们分别是在CREATED、STARTED、RESUMED时被执行。
//方式1
lifecycleScope.launchWhenStarted {
repeat(100000) {
delay(100)
tvText.text = "$it"
}
}
//方式2
lifecycleScope.launch {
whenStarted {
repeat(100000) {
delay(100)
tvText.text = "$it"
}
}
}不管是直接调用launchWhenStarted还是在launch中调用whenStarted都能达到同样的效果。
先来看下lifecycleScope.launch是怎么做到的
/**
* [CoroutineScope] tied to this [LifecycleOwner]'s [Lifecycle].
*
* This scope will be cancelled when the [Lifecycle] is destroyed.
*
* This scope is bound to
* [Dispatchers.Main.immediate][kotlinx.coroutines.MainCoroutineDispatcher.immediate].
*/
val LifecycleOwner.lifecycleScope: LifecycleCoroutineScope
get() = lifecycle.coroutineScope好家伙，又是扩展属性。这次扩展的是LifecycleOwner，返回了一个LifecycleCoroutineScope。每次在get的时候，是返回的lifecycle.coroutineScope，看看这个是啥。
/**
* [CoroutineScope] tied to this [Lifecycle].
*
* This scope will be cancelled when the [Lifecycle] is destroyed.
*
* This scope is bound to
* [Dispatchers.Main.immediate][kotlinx.coroutines.MainCoroutineDispatcher.immediate]
*/
val Lifecycle.coroutineScope: LifecycleCoroutineScope
get() {
while (true) {
val existing = mInternalScopeRef.get() as LifecycleCoroutineScopeImpl?
if (existing != null) {
return existing
}
val newScope = LifecycleCoroutineScopeImpl(
this,
SupervisorJob() + Dispatchers.Main.immediate
)
if (mInternalScopeRef.compareAndSet(null, newScope)) {
newScope.register()
return newScope
}
}
}Lifecycle的coroutineScope也是扩展属性，它是一个LifecycleCoroutineScope。从注释可以看到，在Lifecycle被销毁之后，这个协程会跟着取消。这里首先会从mInternalScopeRef中取之前存入的缓存，如果没有再生成一个LifecycleCoroutineScopeImpl放进去，并调用LifecycleCoroutineScopeImpl的register函数。这里的mInternalScopeRef是Lifecycle类里面的一个属性： AtomicReference<Object> mInternalScopeRef = new AtomicReference<>(); （AtomicReference可以让一个对象保证原子性）。这里使用AtomicReference当然是为了线程安全。
既然生成的是LifecycleCoroutineScopeImpl，那么就先来看看这个东西是什么
internal class LifecycleCoroutineScopeImpl(
override val lifecycle: Lifecycle,
override val coroutineContext: CoroutineContext
) : LifecycleCoroutineScope(), LifecycleEventObserver {
init {
// in case we are initialized on a non-main thread, make a best effort check before
// we return the scope. This is not sync but if developer is launching on a non-main
// dispatcher, they cannot be 100% sure anyways.
if (lifecycle.currentState == Lifecycle.State.DESTROYED) {
coroutineContext.cancel()
}
}
fun register() {
//启了个协程，当前Lifecycle的state大于等于INITIALIZED，就注册一下Lifecycle的观察者，观察生命周期
launch(Dispatchers.Main.immediate) {
if (lifecycle.currentState >= Lifecycle.State.INITIALIZED) {
lifecycle.addObserver(this@LifecycleCoroutineScopeImpl)
} else {
coroutineContext.cancel()
}
}
}
override fun onStateChanged(source: LifecycleOwner, event: Lifecycle.Event) {
//观察到当前生命周期小于等于DESTROYED，那么就移除当前这个观察者并且取消协程
if (lifecycle.currentState <= Lifecycle.State.DESTROYED) {
lifecycle.removeObserver(this)
coroutineContext.cancel()
}
}
}在上面的代码中，有2个重要的函数：register和onStateChanged。register函数是在初始化LifecycleCoroutineScopeImpl的时候调用的，先在register函数中添加一个观察者用于观察生命周期的变化，然后在onStateChanged函数中判断生命周期到DESTROYED时就移除观察者并且取消协程。
有个小细节，为啥register函数中能直接启协程？是因为LifecycleCoroutineScopeImpl继承了LifecycleCoroutineScope,，而LifecycleCoroutineScope实现了CoroutineScope接口(其实是在LifecycleCoroutineScopeImpl中实现的)。
public abstract class LifecycleCoroutineScope internal constructor() : CoroutineScope {
internal abstract val lifecycle: Lifecycle
......
}现在我们流程理清楚了，lifecycleScope使用时会构建一个协程，同时会观察组件的生命周期，在适当的时机（DESTROYED）取消协程。
在上面的实例我们见过一段代码：
//方式1
lifecycleScope.launchWhenStarted {
repeat(100000) {
delay(100)
tvText.text = "$it"
}
}
//方式2
lifecycleScope.launch {
whenStarted {
repeat(100000) {
delay(100)
tvText.text = "$it"
}
}
}可以直接通过lifecycleScope提供的launchWhenCreated、launchWhenStarted、launchWhenResumed在相应的生命周期时执行协程。
点进去看一下
abstract class LifecycleCoroutineScope internal constructor() : CoroutineScope {
internal abstract val lifecycle: Lifecycle
/**
* Launches and runs the given block when the [Lifecycle] controlling this
* [LifecycleCoroutineScope] is at least in [Lifecycle.State.CREATED] state.
*
* The returned [Job] will be cancelled when the [Lifecycle] is destroyed.
* @see Lifecycle.whenCreated
* @see Lifecycle.coroutineScope
*/
fun launchWhenCreated(block: suspend CoroutineScope.() -> Unit): Job = launch {
lifecycle.whenCreated(block)
}
/**
* Launches and runs the given block when the [Lifecycle] controlling this
* [LifecycleCoroutineScope] is at least in [Lifecycle.State.STARTED] state.
*
* The returned [Job] will be cancelled when the [Lifecycle] is destroyed.
* @see Lifecycle.whenStarted
* @see Lifecycle.coroutineScope
*/
fun launchWhenStarted(block: suspend CoroutineScope.() -> Unit): Job = launch {
lifecycle.whenStarted(block)
}
/**
* Launches and runs the given block when the [Lifecycle] controlling this
* [LifecycleCoroutineScope] is at least in [Lifecycle.State.RESUMED] state.
*
* The returned [Job] will be cancelled when the [Lifecycle] is destroyed.
* @see Lifecycle.whenResumed
* @see Lifecycle.coroutineScope
*/
fun launchWhenResumed(block: suspend CoroutineScope.() -> Unit): Job = launch {
lifecycle.whenResumed(block)
}
}原来这些函数就是LifecycleOwner的扩展属性lifecycleScope所返回的LifecycleCoroutineScope类里面的函数。这几个函数里面啥也没干，直接调用了lifecycle对应的函数
/**
* Runs the given block when the [Lifecycle] is at least in [Lifecycle.State.CREATED] state.
*
* @see Lifecycle.whenStateAtLeast for details
*/
suspend fun <T> Lifecycle.whenCreated(block: suspend CoroutineScope.() -> T): T {
return whenStateAtLeast(Lifecycle.State.CREATED, block)
}
/**
* Runs the given block when the [Lifecycle] is at least in [Lifecycle.State.STARTED] state.
*
* @see Lifecycle.whenStateAtLeast for details
*/
suspend fun <T> Lifecycle.whenStarted(block: suspend CoroutineScope.() -> T): T {
return whenStateAtLeast(Lifecycle.State.STARTED, block)
}
/**
* Runs the given block when the [Lifecycle] is at least in [Lifecycle.State.RESUMED] state.
*
* @see Lifecycle.whenStateAtLeast for details
*/
suspend fun <T> Lifecycle.whenResumed(block: suspend CoroutineScope.() -> T): T {
return whenStateAtLeast(Lifecycle.State.RESUMED, block)
}这几个函数原来是suspend函数，并且是扩展Lifecycle的函数。它们最终都调用到了whenStateAtLeast函数，并传入了执行协程的最小的生命周期状态标志（minState）。
suspend fun <T> Lifecycle.whenStateAtLeast(
minState: Lifecycle.State,
block: suspend CoroutineScope.() -> T
) = withContext(Dispatchers.Main.immediate) {
val job = coroutineContext[Job] ?: error("when[State] methods should have a parent job")
val dispatcher = PausingDispatcher()
val controller =
LifecycleController(this@whenStateAtLeast, minState, dispatcher.dispatchQueue, job)
try {
//执行协程
withContext(dispatcher, block)
} finally {
//收尾工作 移除生命周期观察
controller.finish()
}
}
@MainThread
internal class LifecycleController(
private val lifecycle: Lifecycle,
private val minState: Lifecycle.State,
private val dispatchQueue: DispatchQueue,
parentJob: Job
) {
private val observer = LifecycleEventObserver { source, _ ->
if (source.lifecycle.currentState == Lifecycle.State.DESTROYED) {
//DESTROYED->取消协程
handleDestroy(parentJob)
} else if (source.lifecycle.currentState < minState) {
dispatchQueue.pause()
} else {
//执行
dispatchQueue.resume()
}
}
init {
// If Lifecycle is already destroyed (e.g. developer leaked the lifecycle), we won't get
// an event callback so we need to check for it before registering
// see: b/128749497 for details.
if (lifecycle.currentState == Lifecycle.State.DESTROYED) {
handleDestroy(parentJob)
} else {
//观察生命周期变化
lifecycle.addObserver(observer)
}
}
@Suppress("NOTHING_TO_INLINE") // avoid unnecessary method
private inline fun handleDestroy(parentJob: Job) {
parentJob.cancel()
finish()
}
/**
* Removes the observer and also marks the [DispatchQueue] as finished so that any remaining
* runnables can be executed.
*/
@MainThread
fun finish() {
//移除生命周期观察者
lifecycle.removeObserver(observer)
//标记已完成 并执行剩下的可执行的Runnable
dispatchQueue.finish()
}
}
whenStateAtLeast也是一个Lifecycle的扩展函数，核心逻辑是在LifecycleController中添加了LifecycleObserver来监听生命周期状态，通过状态来决定是暂停执行还是恢复执行，或者是取消执行。当执行完成之后，也就是finally那里，从执行LifecycleController的finish进行收尾工作：移除生命周期监听，开始执行余下的任务。
执行完成一次，就会移除生命周期观察者，相当于我们写到launchWhenResumed之类的函数里面的闭包只会被执行一次。执行完成之后，即使再经过onPause->onResume也不会再次执行。
在我们平时使用LiveData的过程中，可能会涉及到这种场景：去请求网络拿结果，然后通过LiveData将数据转出去，在Activity里面收到通知，然后更新UI。非常常见的场景，这种情况下，我们可以通过官方的liveData构造器函数来简化上面的场景代码。
val netData: LiveData<String> = liveData {
//观察的时候在生命周期内,则会马上执行
val data = getNetData()
emit(data)
}
//将耗时任务切到IO线程去执行
private suspend fun getNetData() = withContext(Dispatchers.IO) {
//模拟网络耗时
delay(5000)
//模拟返回结果
"{}"
}
在上面的例子中，getNetData()是一个suspend函数。使用LiveData构造器函数异步调用getNetData()，然后使用emit()提交结果。在Activity那边如果观察了这个netData，并且处于活动状态，那么就会收到结果。我们知道，suspend函数需要在协程作用域中调用，所以liveData的闭包里面也是有协程作用域的。
有个小细节，如果组件在观察此netData时刚好处于活动状态，那么liveData闭包里面的代码会立刻执行。
除了上面这种用法，还可以在liveData里面发出多个值。
val netData2: LiveData<String> = liveData {
delay(3000)
val source = MutableLiveData<String>().apply {
value = "11111"
}
val disposableHandle = emitSource(source)
delay(3000)
disposableHandle.dispose()
val source2 = MutableLiveData<String>().apply {
value = "22222"
}
val disposableHandle2 = emitSource(source2)
}需要注意的是，后一个调用emitSource的时候需要把前一个emitSource的返回值调用一下dispose函数，切断。
老规矩，Ctrl+鼠标左键 点进去看源码
@UseExperimental(ExperimentalTypeInference::class)
fun <T> liveData(
context: CoroutineContext = EmptyCoroutineContext,
timeoutInMs: Long = DEFAULT_TIMEOUT,
@BuilderInference block: suspend LiveDataScope<T>.() -> Unit
): LiveData<T> = CoroutineLiveData(context, timeoutInMs, block)
//咱们在liveData后面的闭包里面写的代码就是传给了这里的block，它是一个suspend函数，有LiveDataScope的上下文首先，映入眼帘的是liveData函数居然是一个全局函数，这意味着你可以在任何地方使用它，而不局限于Activity或者ViewModel里面。
其次，liveData函数返回的是一个CoroutineLiveData对象？居然返回的是一个对象，没有在这里执行任何代码。那我的代码是在哪里执行的？
这就得看CoroutineLiveData类的代码了
internal class CoroutineLiveData<T>(
context: CoroutineContext = EmptyCoroutineContext,
timeoutInMs: Long = DEFAULT_TIMEOUT,
block: Block<T>
) : MediatorLiveData<T>() {
private var blockRunner: BlockRunner<T>?
private var emittedSource: EmittedSource? = null
init {
// use an intermediate supervisor job so that if we cancel individual block runs due to losing
// observers, it won't cancel the given context as we only cancel w/ the intention of possibly
// relaunching using the same parent context.
val supervisorJob = SupervisorJob(context[Job])
// The scope for this LiveData where we launch every block Job.
// We default to Main dispatcher but developer can override it.
// The supervisor job is added last to isolate block runs.
val scope = CoroutineScope(Dispatchers.Main.immediate + context + supervisorJob)
blockRunner = BlockRunner(
liveData = this,
block = block,
timeoutInMs = timeoutInMs,
scope = scope
) {
blockRunner = null
}
}
internal suspend fun emitSource(source: LiveData<T>): DisposableHandle {
clearSource()
val newSource = addDisposableSource(source)
emittedSource = newSource
return newSource
}
internal suspend fun clearSource() {
emittedSource?.disposeNow()
emittedSource = null
}
override fun onActive() {
super.onActive()
blockRunner?.maybeRun()
}
override fun onInactive() {
super.onInactive()
blockRunner?.cancel()
}
}里面代码比较少，主要就是继承了MediatorLiveData，然后在onActive的时候执行BlockRunner的maybeRun函数。BlockRunner的maybeRun里面执行的实际上就是我们在liveData里面写的代码块，而onActive方法实际上是从LiveData那里继承过来的，当有一个处于活跃状态的观察者监听LiveData时会被调用。
这就解释得通了，我上面的案例中是在Activity的onCreate（处于活跃状态）里面观察了netData，所以liveData里面的代码会被立刻执行。
//typealias 类型别名
//在下面的BlockRunner中会使用到这个，这个东西用于承载我们在liveData后面闭包里面的代码
internal typealias Block<T> = suspend LiveDataScope<T>.() -> Unit
/**
* Handles running a block at most once to completion.
*/
internal class BlockRunner<T>(
private val liveData: CoroutineLiveData<T>,
private val block: Block<T>,
private val timeoutInMs: Long,
private val scope: CoroutineScope,
private val onDone: () -> Unit
) {
@MainThread
fun maybeRun() {
...
//这里的scope是CoroutineScope(Dispatchers.Main.immediate + context + supervisorJob)
runningJob = scope.launch {
val liveDataScope = LiveDataScopeImpl(liveData, coroutineContext)
//这里的block执行的是我们在liveData里面写的代码，在执行block时将liveDataScope实例传入，liveDataScope上下文有了
block(liveDataScope)
//完成
onDone()
}
}
...
}
internal class LiveDataScopeImpl<T>(
internal var target: CoroutineLiveData<T>,
context: CoroutineContext
) : LiveDataScope<T> {
...
// use `liveData` provided context + main dispatcher to communicate with the target
// LiveData. This gives us main thread safety as well as cancellation cooperation
private val coroutineContext = context + Dispatchers.Main.immediate
//因为在执行liveData闭包的时候有LiveDataScopeImpl上下文，所以可以使用emit函数
override suspend fun emit(value: T) = withContext(coroutineContext) {
target.clearSource()
//给target这个LiveData设置value，而liveData返回的就是这个target，在组件中观察此target，就会收到这里的value数据
target.value = value
}
}
在BlockRunner的maybeRun函数的里面启了个协程，这个scope是在CoroutineLiveData里面初始化的：CoroutineScope(Dispatchers.Main.immediate + context + supervisorJob)，接着就是在这个scope里面执行我们在liveData后面闭包里面写的代码，并且有LiveDataScopeImpl的上下文。有了LiveDataScopeImpl的上下文，那么我们就可以使用LiveDataScopeImpl里面的emit方法，而emit方法其实很简单，就是将一个数据交给一个LiveData对象，而这个LiveData就是liveData{}返回的那个。此时因为LiveData的数据发生了变化，如果有组件观察了该LiveData并且该组件处于活动状态，那么该组件就会收到数据发生变化的回调。
整个过程大致流程就是在liveData{}里面构建了一个协程，返回了一个LiveData，然后我们写的闭包里面的代码实际上是在一个协程里面执行的，我们调用emit方法时就是在更新这个LiveData里面的value。既然是返回的LiveData，那么天然就与组件生命周期关联上了，只有在组件处于活动状态才能得到结果，而且也避免了一些内存泄露的问题。
不得不说，官方提供的东西就是方便，可以极大地方便我们使用协程。在使用协程且还没有与架构组件一起使用的小伙伴儿赶快用起来。美滋滋~