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CSDN學院課程地址
- RxJava2從入門到精通-初級篇:edu.csdn.net/course/deta…
- RxJava2從入門到精通-中級篇:edu.csdn.net/course/deta…
- RxJava2從入門到精通-進階篇:edu.csdn.net/course/deta…
- RxJava2從入門到精通-原始碼分析篇:edu.csdn.net/course/deta…
10. RxJava原始碼分析
RxJava原始碼分析最主要的點在於
- RxJava是如何從事件流的傳送方傳送到事件流的接收方的
- RxJava是如何對操作符進行封裝和操作的
- RxJava是如何隨意切換執行緒的
在分析的過程中,部分原始碼分析我們會通過手寫RxJava的部分程式碼進行分析,當然也會結合實際RxJava的程式碼進行分析。其中,手寫RxJava的原因是為了簡化原始碼,讓讀者方便閱讀到主要程式碼,更快的看懂RxJava的實現思路。在閱讀原始碼之前,我們需要對RxJava的大體概念進行簡單的梳理
- 發射器:Emitter,發射資料的物件
- 被觀察者:Observable,被觀察的物件
- 觀察者:Observer,觀察的物件
- 被觀察者被訂閱時:ObservableOnSubscribe,被訂閱時的回撥,同時建立出發射器
- 釋放者:Disposable,釋放RxJava的物件
RxJava的分析三步驟
- 建立:被觀察者建立的過程
- 訂閱:被觀察者訂閱觀察者的過程
- 發射:發射器發射的過程
RxJava原理圖解
- 第一排表示各個物件的建立關係,A->B->C->D
- 第二排表示各個物件的訂閱關係,D->C->B->A
- 第三排表示各個物件的發射關係,A->B->C->D
10.1 RxJava的事件發射原理
知識點:
- 理解發射資料的過程
- 理解接收資料的過程
以下是手寫RxJava的程式碼
Observable.create(new ObservableOnSubscribe<String>() {
@Override
public void subscribe(Emitter<String> emitter) {
emitter.onNext("Hello RxJava");
emitter.onError();
emitter.onNext("Hello RxJava");
}
}).subscribe(new Observabler<String>() {
@Override
public void onSubscribe() {
}
@Override
public void onNext(String string) {
System.out.println("onNext=" + string);
}
@Override
public void onError() {
System.out.println("onError");
}
@Override
public void onComplete() {
}
});
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輸出結果:在輸出onError後,就不會繼續收到新的事件流,表示事件已經被釋放了
onNext=Hello RxJava
onError
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1、定義介面
發射器
public interface Emitter<T> {
void onNext(T t);
void onError();
}
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觀察者
public interface Observer<T> {
void onSubscribe();
void onNext(T t);
void onError();
void onComplete();
}
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被觀察者被訂閱時
public interface ObservableOnSubscribe<T> {
void subscribe(Emitter<T> emitter);
}
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2、實現被觀察者
被觀察者Observable負責建立、訂閱,發射由發射器負責
- 建立:建立的過程只是將傳遞進來的引數交給新的ObservableCreate進行管理
- 訂閱:訂閱的過程只是實現建立出來的ObservableCreate的subscribeActual方法
public abstract class Observable<T> {
public static <T> ObservableCreate create(ObservableOnSubscribe<T> observableOnSubscribe) {
return new ObservableCreate<T>(observableOnSubscribe);
}
public void subscribe(Observer<T> observer) {
subscribeActual(observer);
}
public abstract void subscribeActual(Observer<T> observer);
}
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3、ObservableCreate
ObservableCreate繼承自Observable,由於Observable.create返回當前ObservableCreate,所以在subscribe的時候,走的是這裡的subscribeActual,subscribeActual中會去建立發射器,並給發射器傳遞進去observer
public class ObservableCreate<T> extends Observable{
private ObservableOnSubscribe source;
public ObservableCreate(ObservableOnSubscribe observableOnSubscribe) {
this.source = observableOnSubscribe;
}
@Override
public void subscribeActual(Observer observer) {
//固定的三步曲分析法(個人建立,基本都是這個步驟)
//1、建立發射器
EmitterCreate<T> emitterCreate = new EmitterCreate<>(observer);
//2、回撥observer的onSubscribe
observer.onSubscribe();
//3、回撥上一個的subscribe
source.subscribe(emitterCreate);
}
}
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4、EmitterCreate
傳遞進來的observer即是我們最開始訂閱時候new出來的,此時發射資料,就會去呼叫Observer的onNext方法,這樣資料就從發射器中傳遞到觀察者中了。DisposableHelper在後面會講到,這裡只是用作判斷是否被釋放的一個工具類
public class EmitterCreate<T>
extends AtomicReference<Disposable>
implements Emitter<T>, Disposable {
private Observer<T> observer;
public EmitterCreate(Observer<T> observer) {
this.observer = observer;
}
@Override
public void onNext(T t) {
if (!isDisposed()) {
observer.onNext(t);
}
}
@Override
public void onError() {
if (!isDisposed()) {
try {
observer.onError();
} finally {
dispose();
}
}
}
@Override
public void dispose() {
DisposableHelper.dispose(this);
}
@Override
public boolean isDisposed() {
return DisposableHelper.isDisposed(get());
}
}
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以下是RxJava原始碼
1、Observable.create
public static <T> Observable<T> create(ObservableOnSubscribe<T> source) {
ObjectHelper.requireNonNull(source, "source is null");//判空
return RxJavaPlugins.onAssembly(new ObservableCreate<T>(source));//返回自身
}
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RxJavaPlugins.onAssembly只是對傳遞進來的引數做判斷處理,最終還是返回ObservableCreate,有關RxJavaPlugins的東西最終都是返回自身,RxJavaPlugins後面分析會說到,這裡只需要知道他是返回引數本身即可
2、Observable.subscribe
public final void subscribe(Observer<? super T> observer) {
ObjectHelper.requireNonNull(observer, "observer is null");//判空
try {
observer = RxJavaPlugins.onSubscribe(this, observer);//返回自身
ObjectHelper.requireNonNull(observer, "Plugin returned null Observer");
subscribeActual(observer);//回撥ObservableCreate的subscribeActual
} catch (NullPointerException e) { // NOPMD
throw e;
} catch (Throwable e) {
......
throw npe;
}
}
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observable.subscribe和我們手寫程式碼一樣,最終呼叫的是ObservableCreate的subscribeActual方法
3、ObservableCreate
public final class ObservableCreate<T> extends Observable<T> {
final ObservableOnSubscribe<T> source;
public ObservableCreate(ObservableOnSubscribe<T> source) {
this.source = source;
}
@Override
protected void subscribeActual(Observer<? super T> observer) {
//1、建立發射器
CreateEmitter<T> parent = new CreateEmitter<T>(observer);
//2、回撥observer的onSubscribe
observer.onSubscribe(parent);
try {
//3、回撥ObservableOnSubscribe的subscribe
source.subscribe(parent);
} catch (Throwable ex) {
Exceptions.throwIfFatal(ex);
parent.onError(ex);
}
}
static final class CreateEmitter<T>
extends AtomicReference<Disposable>
implements ObservableEmitter<T>, Disposable {
private static final long serialVersionUID = -3434801548987643227L;
final Observer<? super T> observer;
CreateEmitter(Observer<? super T> observer) {
this.observer = observer;
}
@Override
public void onNext(T t) {
if (t == null) {
onError(new NullPointerException("onNext called with null. Null values are generally not allowed in 2.x operators and sources."));
return;
}
if (!isDisposed()) {
observer.onNext(t);
}
}
@Override
public void onError(Throwable t) {
if (!tryOnError(t)) {
RxJavaPlugins.onError(t);
}
}
@Override
public boolean tryOnError(Throwable t) {
if (t == null) {
t = new NullPointerException("onError called with null. Null values are generally not allowed in 2.x operators and sources.");
}
if (!isDisposed()) {
try {
observer.onError(t);
} finally {
dispose();
}
return true;
}
return false;
}
@Override
public void onComplete() {
if (!isDisposed()) {
try {
observer.onComplete();
} finally {
dispose();
}
}
}
@Override
public void setDisposable(Disposable d) {
DisposableHelper.set(this, d);
}
@Override
public void setCancellable(Cancellable c) {
setDisposable(new CancellableDisposable(c));
}
@Override
public ObservableEmitter<T> serialize() {
return new SerializedEmitter<T>(this);
}
@Override
public void dispose() {
DisposableHelper.dispose(this);
}
@Override
public boolean isDisposed() {
return DisposableHelper.isDisposed(get());
}
}
}
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ObservableCreate和我們手寫程式碼一樣,建立發射器,並在發射器中做發射資料等操作
小結
如圖所示
10.2 RxJava的事件釋放原理
知識點:
- 理解釋放事件的原理
有關RxJava的釋放原理是基於Observable
可以返回Disposable
物件,只有呼叫dispose()
才能釋放事件,通過上面的例子,我們知道在發射器裡面有isDisposed()
和dispose()
操作,在發射完onError
事件的情況下,我們會將事件釋放,所以在finally會做釋放操作,防止後面的事件再次發射
以下是手寫RxJava的程式碼
public class EmitterCreate<T>
extends AtomicReference<Disposable>
implements Emitter<T>, Disposable {
private Observer<T> observer;
public EmitterCreate(Observer<T> observer) {
this.observer = observer;
}
@Override
public void onNext(T t) {
if (!isDisposed()) {
observer.onNext(t);
}
}
@Override
public void onError() {
if (!isDisposed()) {
try {
observer.onError();
} finally {
dispose();
}
}
}
@Override
public void dispose() {
DisposableHelper.dispose(this);
}
@Override
public boolean isDisposed() {
return DisposableHelper.isDisposed(get());
}
}
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以下是RxJava原始碼
@Override
public void dispose() {
DisposableHelper.dispose(this);
}
@Override
public boolean isDisposed() {
return DisposableHelper.isDisposed(get());
}
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可以發現事件的釋放都是通過DisposableHelper
去觸發的,不管是手寫RxJava還是原始碼,釋放RxJava都是通過DisposableHelper
進行釋放,具體看DisposableHelper
。在我們的演示程式中,我們通過發射onNext->onError->onNext
的過程,去挖掘事件是怎麼被釋放掉的
public enum DisposableHelper implements Disposable {
DISPOSED
;
public static boolean isDisposed(Disposable d) {
return d == DISPOSED;
}
public static boolean dispose(AtomicReference<Disposable> field) {
Disposable current = field.get();//獲取引數的Disposable物件
Disposable d = DISPOSED;//宣告一個已經釋放的Disposable物件
if (current != d) {//如果當前未被釋放
current = field.getAndSet(d);//則將當前的Disposable賦值成已經釋放過的Disposable物件
if (current != d) {//如果當前還未被釋放
if (current != null) {//且不為空
current.dispose();//則釋放當前Disposable物件
}
return true;
}
}
return false;
}
}
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在事件釋放的過程中,EmitterCreate
本身是個AtomicReference<Disposable>
,程式碼通過get()
去獲取Disposable
物件,其中程式碼會通過雙層判斷去做釋放,防止在多執行緒的時候出現搶奪的情況
- onNext:第一次發射資料時,
get()
會獲取一個null物件,所以不符合d == DISPOSED
- onEroor:這時候會呼叫
dispose()
去比較當前和釋放過的物件,如果不等於,則將當前的物件設定為釋放過的值 - onNext:第二次發射資料時,
get()
會獲取一個已經釋放過的物件,這個時候符合d == DISPOSED
其實這裡的操作如同設定一個Flag,但由於Disposable
是物件的形式,且需要保證原子性,AtomicReference
型別是個最佳選擇,能保證物件的原子性
10.3 RxJava的背壓原理
知識點:
- 理解背壓實現的本質
- 理解背壓資料項丟棄的本質
背壓原理有一部分和RxJava事件發射原理相似,其背壓的過程就是在不同策略的發射器去處理當前的資料項而已。在分析背壓策略的時候,我們都知道背壓是需要手動進行請求才可以將資料發射到觀察者中,所以我們會呼叫s.request(Long.MAX_VALUE)
讓觀察者能接收到資料。有些人就會有疑問,為什麼有些人平時用背壓的時候,不需要去呼叫request()
就能接收到資料,原因是有些背壓已經在內部預設呼叫了s.request(Long.MAX_VALUE)
,所以這裡是不用多想的,是一定要呼叫s.request(Long.MAX_VALUE)
才能收到資料的。由於不同背壓的策略的原理大同小異,主要以Drop策略去分析背壓的原理
public static void drop(View view) {
Flowable.create(new FlowableOnSubscribe<Integer>() {
@Override
public void subscribe(FlowableEmitter<Integer> emitter) throws Exception {
for (int i = 0; i < 1000; i++) {
emitter.onNext(i);
}
}
}, BackpressureStrategy.DROP)
.subscribeOn(Schedulers.io())
.observeOn(AndroidSchedulers.mainThread())
.subscribe(new FlowableSubscriber<Integer>() {
@Override
public void onSubscribe(Subscription s) {
s.request(Long.MAX_VALUE);
}
@Override
public void onNext(Integer integer) {
Log.e("TAG", "onNext=" + integer);
}
@Override
public void onError(Throwable t) {
t.printStackTrace();
}
@Override
public void onComplete() {
}
});
}
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以下是RxJava原始碼
1、Flowable.create
public static <T> Flowable<T> create(FlowableOnSubscribe<T> source, BackpressureStrategy mode) {
ObjectHelper.requireNonNull(source, "source is null");//判空
ObjectHelper.requireNonNull(mode, "mode is null");//判空
return RxJavaPlugins.onAssembly(new FlowableCreate<T>(source, mode));//返回自身
}
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Flowable.create跟我們前面是一樣的,最後還是會交給新物件FlowableCreate去處理
2、Flowable.subscribe
public final void subscribe(FlowableSubscriber<? super T> s) {
ObjectHelper.requireNonNull(s, "s is null");
try {
Subscriber<? super T> z = RxJavaPlugins.onSubscribe(this, s);
ObjectHelper.requireNonNull(z, "Plugin returned null Subscriber");
subscribeActual(z);
} catch (NullPointerException e) { // NOPMD
throw e;
} catch (Throwable e) {
......
throw npe;
}
}
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Flowable.subscribe跟我們前面是一樣的,最終呼叫的是FlowableCreate的subscribeActual方法
3、FlowableCreate.subscribeActual
public final class FlowableCreate<T> extends Flowable<T> {
final FlowableOnSubscribe<T> source;
final BackpressureStrategy backpressure;
public FlowableCreate(FlowableOnSubscribe<T> source, BackpressureStrategy backpressure) {
this.source = source;
this.backpressure = backpressure;
}
@Override
public void subscribeActual(Subscriber<? super T> t) {
//使用三步曲分析法
BaseEmitter<T> emitter;
switch (backpressure) {
case MISSING: {
emitter = new MissingEmitter<T>(t);
break;
}
case ERROR: {
emitter = new ErrorAsyncEmitter<T>(t);
break;
}
case DROP: {
emitter = new DropAsyncEmitter<T>(t);
break;
}
case LATEST: {
emitter = new LatestAsyncEmitter<T>(t);
break;
}
default: {
emitter = new BufferAsyncEmitter<T>(t, bufferSize());
break;
}
}
t.onSubscribe(emitter);
try {
source.subscribe(emitter);
} catch (Throwable ex) {
Exceptions.throwIfFatal(ex);
emitter.onError(ex);
}
}
}
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subscribeActual會根據不同的策略生成不同的發射器,具體的所有策略邏輯都在發射器中體現的
4、DropAsyncEmitter
static final class DropAsyncEmitter<T> extends NoOverflowBaseAsyncEmitter<T> {
private static final long serialVersionUID = 8360058422307496563L;
DropAsyncEmitter(Subscriber<? super T> actual) {
super(actual);
}
@Override
void onOverflow() {
// nothing to do
}
}
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DropAsyncEmitter其實沒做什麼事情,主要都在其父類中實現了,onOverflow的回撥錶示事件流溢位的時候的處理,很明顯Drop策略就把溢位的資料項直接不做處理,意思就是拋棄掉這個資料項了
static final class ErrorAsyncEmitter<T> extends NoOverflowBaseAsyncEmitter<T> {
private static final long serialVersionUID = 338953216916120960L;
ErrorAsyncEmitter(Subscriber<? super T> actual) {
super(actual);
}
@Override
void onOverflow() {
onError(new MissingBackpressureException("create: could not emit value due to lack of requests"));
}
}
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再看看Error策略,溢位之後就會丟擲溢位的異常,其他策略也類似分析,具體父類是如何處理溢位函式的呢
5、NoOverflowBaseAsyncEmitter
abstract static class NoOverflowBaseAsyncEmitter<T> extends BaseEmitter<T> {
private static final long serialVersionUID = 4127754106204442833L;
NoOverflowBaseAsyncEmitter(Subscriber<? super T> actual) {
super(actual);
}
@Override
public final void onNext(T t) {
if (isCancelled()) {
return;
}
if (t == null) {
onError(new NullPointerException("onNext called with null. Null values are generally not allowed in 2.x operators and sources."));
return;
}
//這裡暫時將get()函式當作是類似於List這種的容器,儲存的是當前需要處理的資料項
if (get() != 0) { //從資料項容器中取值,如果當前有資料項需要處理
actual.onNext(t); //發射資料項
BackpressureHelper.produced(this, 1); //對當前存在需要處理的資料項進行-1操作
} else {
onOverflow(); //從資料項容器中取值,如果當前沒有資料項需要處理,則回撥溢位函式
}
}
abstract void onOverflow();
}
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NoOverflowBaseAsyncEmitter在發射資料項的時候,會去BaseEmitter中的資料項容器去取出資料項,如果存在則處理,不存在則表示溢位,回撥溢位函式,那麼具體的資料項容器時候怎麼儲存需要處理的資料項的呢
6、BaseEmitter
abstract static class BaseEmitter<T>
extends AtomicLong
implements FlowableEmitter<T>, Subscription {
private static final long serialVersionUID = 7326289992464377023L;
final Subscriber<? super T> actual;
final SequentialDisposable serial;
BaseEmitter(Subscriber<? super T> actual) {
this.actual = actual;
this.serial = new SequentialDisposable();
}
@Override
public void onComplete() {
complete();
}
protected void complete() {
if (isCancelled()) {
return;
}
try {
actual.onComplete();
} finally {
serial.dispose();
}
}
@Override
public final void onError(Throwable e) {
if (!tryOnError(e)) {
RxJavaPlugins.onError(e);
}
}
@Override
public final void request(long n) {
if (SubscriptionHelper.validate(n)) {
BackpressureHelper.add(this, n);
}
}
}
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BaseEmitter就是一個AtomicLong,如果沒學過AtomicLong的話,可以簡單理解為一個計數器,get()就是獲取當前的Long值,只要不等於0就表示有值。主要還是在request()
,request()
表示此時需要處理的資料項。結合上面NoOverflowBaseAsyncEmitter的中的BackpressureHelper.produced(this, 1)
和當前BaseEmitter中的BackpressureHelper.add(this, n)
,可得資料項的容器完全都是由BackpressureHelper去控制,我們只需要對BackpressureHelper的儲存和獲取做分析,就可以知道當前是否有資料項需要處理
7、BackpressureHelper
public final class BackpressureHelper {
public static long add(AtomicLong requested, long n) {
for (;;) {
long r = requested.get(); //獲取當前資料項
if (r == Long.MAX_VALUE) {
return Long.MAX_VALUE;
}
long u = addCap(r, n);//當前資料項 + 新增的資料項
if (requested.compareAndSet(r, u)) { //設定最新的資料項
return r;
}
}
}
public static long addCap(long a, long b) {
long u = a + b;
if (u < 0L) {
return Long.MAX_VALUE;
}
return u;
}
public static long produced(AtomicLong requested, long n) {
for (;;) {
long current = requested.get(); //獲取當前資料項
if (current == Long.MAX_VALUE) {
return Long.MAX_VALUE;
}
long update = current - n; //當前資料項 - 需要發射的資料項(從原始碼上,n為1)
if (update < 0L) { //不能為負數
RxJavaPlugins.onError(new IllegalStateException("More produced than requested: " + update));
update = 0L;
}
if (requested.compareAndSet(current, update)) { //設定最新的資料項
return update;
}
}
}
}
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BackpressureHelper就是利用AtomicLong的原子性就行簡單的計數器操作而已,並沒有什麼複雜的操作。至此,我們就知道背壓的原理原來就是利用AtomicLong計數器和生產消費的模式去決定是否發射當前的資料項而已
10.4 RxJava的常用操作符原理
知識點:
- 理解map操作符的原理
RxJava常用操作符的代表就是map,分析map原始碼後,其他的操作符的思想是一樣的,只不過是實現邏輯不一致而已。下面我們通過分析map的主要流程去分析map是如何轉換字串的,從上面我們知道Observable的建立、訂閱、發射的過程,這次對於重複的內容就不再繼續分析,主要是分析中間map是如何回撥apply()
去將資料項轉換成字串的
public void map() {
//建立被觀察者
Observable
.create(new ObservableOnSubscribe<String>() {
@Override
//預設在主執行緒裡執行該方法
public void subscribe(@NonNull ObservableEmitter<String> e) throws Exception {
e.onNext("俊俊俊很帥");
e.onNext("你值得擁有");
e.onNext("取消關注");
e.onNext("但還是要保持微笑");
e.onComplete();
}
})
.map(new Function<String, String>() {
@Override
public String apply(String s) throws Exception {
return "Hello";
}
})
//建立觀察者並訂閱
.subscribe(new Observer<String>() {
@Override
public void onSubscribe(Disposable d) {
if (!d.isDisposed()) {
d.dispose();
}
}
@Override
public void onNext(String s) {
System.out.println("onNext=" + s);
}
@Override
public void onError(Throwable e) {
System.out.println("onNext=" + e.getMessage());
}
@Override
public void onComplete() {
}
});
}
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以下是RxJava原始碼
1、Observable.map
public static <T> Observable<T> create(ObservableOnSubscribe<T> source) {
ObjectHelper.requireNonNull(source, "source is null");
return RxJavaPlugins.onAssembly(new ObservableCreate<T>(source));
}
public final <R> Observable<R> map(Function<? super T, ? extends R> mapper) {
ObjectHelper.requireNonNull(mapper, "mapper is null");
return RxJavaPlugins.onAssembly(new ObservableMap<T, R>(this, mapper));
}
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從create到map的過程中,create的時候,當前的Observable已經被轉換成ObservableCreate
,再次map的時候,
當前的Observable已經被轉換成ObservableMap
,而且在ObservableMap
中傳遞的引數包含this
,所以當前ObservableMap
中是巢狀著ObservableCreate
2、Observable.subscribe
由於當前的Observable是ObservableMap
,所以Observable.subscribe會回撥ObservableMap
中的subscribeActual
public final class ObservableMap<T, U> extends AbstractObservableWithUpstream<T, U> {
final Function<? super T, ? extends U> function;
public ObservableMap(ObservableSource<T> source, Function<? super T, ? extends U> function) {
super(source);
this.function = function;
}
@Override
public void subscribeActual(Observer<? super U> t) {
source.subscribe(new MapObserver<T, U>(t, function));//source是傳遞進來的ObservableCreate
}
}
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ObservableMap
中的subscribeActual
,會去呼叫ObservableCreate
的subscribe
方法,最後還是會去回撥
ObservableCreate
的subscribeActual
,不過這裡在回撥的過程中增加了一個引數MapObserver
,這個引數只有在ObservableCreate
發射器發射的時候才會被呼叫
3、ObservableCreate.subscribeActual
@Override
protected void subscribeActual(Observer<? super T> observer) {
CreateEmitter<T> parent = new CreateEmitter<T>(observer);
observer.onSubscribe(parent);
try {
source.subscribe(parent);
} catch (Throwable ex) {
Exceptions.throwIfFatal(ex);
parent.onError(ex);
}
}
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在ObservableCreate.subscribeActual
中,會接收一個Observer
的引數,這個時候的Observer
的引數是從ObservableMap
中傳遞過來的MapObserver
,當CreateEmitter
發射onNext
的時候,就會在當前的MapObserver
物件onNext
進行處理
4、MapObserver.onNext
static final class MapObserver<T, U> extends BasicFuseableObserver<T, U> {
final Function<? super T, ? extends U> mapper;
MapObserver(Observer<? super U> actual, Function<? super T, ? extends U> mapper) {
super(actual);
this.mapper = mapper;
}
@Override
public void onNext(T t) {
if (done) {
return;
}
if (sourceMode != NONE) {
actual.onNext(null);
return;
}
U v;
try {
v = ObjectHelper.requireNonNull(mapper.apply(t), "The mapper function returned a null value.");
} catch (Throwable ex) {
fail(ex);
return;
}
actual.onNext(v);
}
......
}
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onNext
主要做了兩個事情,一個是mapper.apply(t)
,這個就是map
操作符所實現的方法,這裡就將原來的值轉換成新的值,一個是actual.onNext(v)
,將轉換出來的新值v
繼續onNext
出去,這裡的actual
就是在建構函式中傳遞進來的ObservableCreate
,這裡就已經將資料項經過map的操作符後繼續執行後面正常的發射流程
小結
如圖所示
10.5 RxJava的執行緒切換原理
知識點:
- 理解在工作執行緒上為什麼能執行耗時操作
- 理解在UI執行緒為什麼能執行更新UI的操作
沿用上面的例子,線上程切換的過程中,無非就是相當於不同的操作符繼續運算元據項而已,根本的實現思路和map等操作符是一樣的,也是通過巢狀Observable的過程來執行的,只不過是執行緒切換的操作符內部實現的邏輯有區別而已。通過我們以往的思路去想,這兩個知識點無非就是啟動執行緒池去執行耗時任務,而UI執行緒則是交給Handler去處理,RxJava執行緒切換的原理就是這樣的
Observable
.create(new ObservableOnSubscribe<String>() {
@Override
//預設在主執行緒裡執行該方法
public void subscribe(@NonNull ObservableEmitter<String> e) throws Exception {
e.onNext("俊俊俊很帥");
e.onNext("你值得擁有");
e.onNext("取消關注");
e.onNext("但還是要保持微笑");
e.onComplete();
}
})
.map(new Function<String, String>() {
@Override
public String apply(String s) throws Exception {
return "Hello";
}
})
//將被觀察者切換到子執行緒
.subscribeOn(Schedulers.io())
//將觀察者切換到主執行緒 需要在Android環境下執行
.observeOn(AndroidSchedulers.mainThread())
//建立觀察者並訂閱
.subscribe(new Observer<String>() {
@Override
public void onSubscribe(Disposable d) {
if (!d.isDisposed()) {
d.dispose();
}
}
@Override
public void onNext(String s) {
System.out.println("onNext=" + s);
}
@Override
public void onError(Throwable e) {
System.out.println("onNext=" + e.getMessage());
}
@Override
public void onComplete() {
}
});
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基礎概念:
- Schedulers:排程器的管理者。管理著多種不同種類的Scheduler
- Scheduler:排程器。負責執行緒Worker的建立
createWorker()
,排程Worker的執行schedule()
- Worker:抽象的工作執行緒。被執行緒排程器管理,負責執行緒的建立和執行
在原始碼中,我們需要先熟悉這三者之間的關係到底是如何運作的
以下是RxJava原始碼
1、observeOn()
@CheckReturnValue
@SchedulerSupport("custom")
public final Observable<T> observeOn(Scheduler scheduler) {
return this.observeOn(scheduler, false, bufferSize());
}
@CheckReturnValue
@SchedulerSupport("custom")
public final Observable<T> observeOn(Scheduler scheduler, boolean delayError, int bufferSize) {
ObjectHelper.requireNonNull(scheduler, "scheduler is null");
ObjectHelper.verifyPositive(bufferSize, "bufferSize");
return RxJavaPlugins.onAssembly(new ObservableObserveOn(this, scheduler, delayError, bufferSize));
}
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當前的Observable已經被轉換成ObservableObserveOn
public final class ObservableObserveOn<T> extends AbstractObservableWithUpstream<T, T> {
final Scheduler scheduler;
final boolean delayError;
final int bufferSize;
public ObservableObserveOn(ObservableSource<T> source, Scheduler scheduler, boolean delayError, int bufferSize) {
super(source);
this.scheduler = scheduler;
this.delayError = delayError;
this.bufferSize = bufferSize;
}
protected void subscribeActual(Observer<? super T> observer) {
if (this.scheduler instanceof TrampolineScheduler) {
this.source.subscribe(observer);
} else {
//1、建立工作執行緒
Worker w = this.scheduler.createWorker();
//2、訂閱之後,在發射的過程中
this.source.subscribe(new ObservableObserveOn.ObserveOnObserver(observer, w, this.delayError, this.bufferSize));
}
}
static final class ObserveOnObserver<T> extends BasicIntQueueDisposable<T> implements Observer<T>, Runnable {
private static final long serialVersionUID = 6576896619930983584L;
final Observer<? super T> actual;
final Worker worker;
final boolean delayError;
final int bufferSize;
SimpleQueue<T> queue;
public void onNext(T t) {
if (!this.done) {
if (this.sourceMode != 2) {
this.queue.offer(t);
}
//3、在OnNext中執行
this.schedule();
}
}
void schedule() {
if (this.getAndIncrement() == 0) {
//4、執行工作執行緒
this.worker.schedule(this);
}
}
}
}
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其三者的關係簡單的說就是在每次訂閱的時候,都會去建立出對應的工作執行緒,這個工作執行緒取決於你傳遞的引數是哪個Worker,在發射器發射的過程中,這個工作執行緒總會去執行它的回撥schedule
,其實大部分的操作就是在schedule
裡面執行執行緒。搞懂了三者的關係之後,分析執行緒切換就簡單多了,就相當於工廠一樣,給個具體的任務給到具體的工人去執行,很像工廠的流水線,我們已經確定下來了流水線的流程了,這個時候我們就需要去關心引數具體是什麼東西了。在閱讀subscribeOn、observeOn前,我們先看看這兩個方法中的引數都是什麼
1、Schedulers.io()
public final class Schedulers {
@NonNull
static final Scheduler IO;
static {
SINGLE = RxJavaPlugins.initSingleScheduler(new SingleTask());
COMPUTATION = RxJavaPlugins.initComputationScheduler(new ComputationTask());
//1、在初始化的時候就構建出了IOTask,initIoScheduler會去執行IOTask的call方法
IO = RxJavaPlugins.initIoScheduler(new IOTask());
TRAMPOLINE = TrampolineScheduler.instance();
NEW_THREAD = RxJavaPlugins.initNewThreadScheduler(new NewThreadTask());
}
static final class IOTask implements Callable<Scheduler> {
@Override
public Scheduler call() throws Exception {
//2、IOTask的call方法會去獲取IoHolder的值
return IoHolder.DEFAULT;
}
}
static final class IoHolder {
//3、建立IoScheduler
static final Scheduler DEFAULT = new IoScheduler();
}
public static Scheduler io() {
//Schedulers.io():它會去獲取前面3步建立出來的IoScheduler物件
return RxJavaPlugins.onIoScheduler(IO); //返回IO自身
}
}
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其正在實現在IoScheduler,其表示管理Io執行緒的管理者
public final class IoScheduler extends Scheduler {
final AtomicReference<CachedWorkerPool> pool;
static final CachedWorkerPool NONE;
static {
......
//1、建立CachedWorkerPool
NONE = new CachedWorkerPool(0, null, WORKER_THREAD_FACTORY);
}
static final class CachedWorkerPool implements Runnable {
......
private final ScheduledExecutorService evictorService;
private final Future<?> evictorTask;
CachedWorkerPool(long keepAliveTime, TimeUnit unit, ThreadFactory threadFactory) {
......
Future<?> task = null;
if (unit != null) {
evictor = Executors.newScheduledThreadPool(1, EVICTOR_THREAD_FACTORY);
task = evictor.scheduleWithFixedDelay(this, this.keepAliveTime, this.keepAliveTime, TimeUnit.NANOSECONDS);
}
evictorService = evictor;
evictorTask = task;
}
}
@NonNull
@Override
public Worker createWorker() {
//2、建立具體的執行緒
return new EventLoopWorker(pool.get());
}
static final class EventLoopWorker extends Scheduler.Worker {
private final CompositeDisposable tasks;
private final CachedWorkerPool pool;
private final ThreadWorker threadWorker;
final AtomicBoolean once = new AtomicBoolean();
EventLoopWorker(CachedWorkerPool pool) {
this.pool = pool;
this.tasks = new CompositeDisposable();
this.threadWorker = pool.get();
}
@NonNull
@Override
public Disposable schedule(@NonNull Runnable action, long delayTime, @NonNull TimeUnit unit) {
if (tasks.isDisposed()) {
// don't schedule, we are unsubscribed
return EmptyDisposable.INSTANCE;
}
//3、最終會去呼叫ThreadWorker的scheduleActual
return threadWorker.scheduleActual(action, delayTime, unit, tasks);
}
}
//4、由於ThreadWorker沒有scheduleActual,在父類中找NewThreadWorker
static final class ThreadWorker extends NewThreadWorker {
private long expirationTime;
ThreadWorker(ThreadFactory threadFactory) {
super(threadFactory);
this.expirationTime = 0L;
}
public long getExpirationTime() {
return expirationTime;
}
public void setExpirationTime(long expirationTime) {
this.expirationTime = expirationTime;
}
}
}
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NewThreadWorker,最終還是呼叫executor.submit()
或executor.schedule()
@NonNull
public ScheduledRunnable scheduleActual(final Runnable run, long delayTime, @NonNull TimeUnit unit, @Nullable DisposableContainer parent) {
Runnable decoratedRun = RxJavaPlugins.onSchedule(run);
ScheduledRunnable sr = new ScheduledRunnable(decoratedRun, parent);
if (parent != null) {
if (!parent.add(sr)) {
return sr;
}
}
Future<?> f;
try {
if (delayTime <= 0) {
f = executor.submit((Callable<Object>)sr);
} else {
f = executor.schedule((Callable<Object>)sr, delayTime, unit);
}
sr.setFuture(f);
} catch (RejectedExecutionException ex) {
if (parent != null) {
parent.remove(sr);
}
RxJavaPlugins.onError(ex);
}
return sr;
}
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2、AndroidSchedulers.mainThread()
public final class AndroidSchedulers {
private static final class MainHolder {
static final Scheduler DEFAULT = new HandlerScheduler(new Handler(Looper.getMainLooper()));
}
private static final Scheduler MAIN_THREAD = RxAndroidPlugins.initMainThreadScheduler(
new Callable<Scheduler>() {
@Override public Scheduler call() throws Exception {
return MainHolder.DEFAULT;
}
});
/** A {@link Scheduler} which executes actions on the Android main thread. */
public static Scheduler mainThread() {
return RxAndroidPlugins.onMainThreadScheduler(MAIN_THREAD);
}
}
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返回一個HandlerScheduler,建立單例模式的主執行緒Handler
final class HandlerScheduler extends Scheduler {
private final Handler handler;
HandlerScheduler(Handler handler) {
this.handler = handler;
}
public Disposable scheduleDirect(Runnable run, long delay, TimeUnit unit) {
if (run == null) {
throw new NullPointerException("run == null");
} else if (unit == null) {
throw new NullPointerException("unit == null");
} else {
run = RxJavaPlugins.onSchedule(run);
HandlerScheduler.ScheduledRunnable scheduled = new HandlerScheduler.ScheduledRunnable(this.handler, run);
this.handler.postDelayed(scheduled, unit.toMillis(delay));
return scheduled;
}
}
public Worker createWorker() {
//建立具體工作執行緒
return new HandlerScheduler.HandlerWorker(this.handler);
}
......
}
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就好像我們上面分析的三者關係一樣,Schedule最終還是會管理著具體的工作執行緒
private static final class HandlerWorker extends Worker {
private final Handler handler;
private volatile boolean disposed;
HandlerWorker(Handler handler) {
this.handler = handler;
}
@Override
public Disposable schedule(Runnable run, long delay, TimeUnit unit) {
if (run == null) throw new NullPointerException("run == null");
if (unit == null) throw new NullPointerException("unit == null");
if (disposed) {
return Disposables.disposed();
}
run = RxJavaPlugins.onSchedule(run);
//包裝新的Runnable交給Handler
ScheduledRunnable scheduled = new ScheduledRunnable(handler, run);
Message message = Message.obtain(handler, scheduled);
message.obj = this; // Used as token for batch disposal of this worker's runnables.
handler.sendMessageDelayed(message, unit.toMillis(delay));
// Re-check disposed state for removing in case we were racing a call to dispose().
if (disposed) {
handler.removeCallbacks(scheduled);
return Disposables.disposed();
}
return scheduled;
}
@Override
public void dispose() {
disposed = true;
handler.removeCallbacksAndMessages(this /* token */);
}
@Override
public boolean isDisposed() {
return disposed;
}
}
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3、subscribeOn()
理解完引數後,回到我們的分析重點
public final Observable<T> subscribeOn(Scheduler scheduler) {
ObjectHelper.requireNonNull(scheduler, "scheduler is null");
return RxJavaPlugins.onAssembly(new ObservableSubscribeOn<T>(this, scheduler));
}
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subscribeOn就如同普通操作符一樣,包裝一層ObservableSubscribeOn
,在subscribe的時候真正走的還是subscribeActual
public final class ObservableSubscribeOn<T> extends AbstractObservableWithUpstream<T, T> {
@Override
public void subscribeActual(final Observer<? super T> s) {
//使用三步曲分析法
final SubscribeOnObserver<T> parent = new SubscribeOnObserver<T>(s);
s.onSubscribe(parent);
//3、將第三步的內容放到執行緒中去執行
parent.setDisposable(scheduler.scheduleDirect(new SubscribeTask(parent)));
}
final class SubscribeTask implements Runnable {
private final SubscribeOnObserver<T> parent;
SubscribeTask(SubscribeOnObserver<T> parent) {
this.parent = parent;
}
@Override
public void run() {
//3、回撥ObservableOnSubscribe的subscribe
source.subscribe(parent);
}
}
}
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scheduler.scheduleDirect
中會去執行Scheduler裡的方法,這裡的scheduler就是IoScheduler
@NonNull
public Disposable scheduleDirect(@NonNull Runnable run) {
return scheduleDirect(run, 0L, TimeUnit.NANOSECONDS);
}
@NonNull
public Disposable scheduleDirect(@NonNull Runnable run, long delay, @NonNull TimeUnit unit) {
final Worker w = createWorker();
final Runnable decoratedRun = RxJavaPlugins.onSchedule(run);
DisposeTask task = new DisposeTask(decoratedRun, w);
w.schedule(task, delay, unit);
return task;
}
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回撥IoScheduler的createWorker()
並執行w.schedule()
小結
如圖所示
10.6 RxJava的自定義Operator原理
知識點:
- 自定義Operator是如何實現的
在講解之前,讓我們先回味下自定義Operator
public class CustomOperator implements ObservableOperator<String, List<String>> {
@Override
public Observer<? super List<String>> apply(final Observer<? super String> observer) throws Exception {
return new Observer<List<String>>() {
@Override
public void onSubscribe(Disposable d) {
observer.onSubscribe(d);
}
@Override
public void onNext(List<String> strings) {
observer.onNext(strings.toString());
}
@Override
public void onError(Throwable e) {
observer.onError(e);
}
@Override
public void onComplete() {
observer.onComplete();
}
};
}
}
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Observable.create(new ObservableOnSubscribe<List<String>>() {
@Override
public void subscribe(@NonNull ObservableEmitter<List<String>> e) throws Exception {
}
}).lift(new CustomOperator())
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自定義Operator如同普通的操作符原理差不多,用的是lift
的操作符,只不過在lift
裡面將邏輯的執行回撥到自定義的Operator的apply()
以下是RxJava原始碼
1、Observable.lift
public final <R> Observable<R> lift(ObservableOperator<? extends R, ? super T> lifter) {
ObjectHelper.requireNonNull(lifter, "onLift is null");
return RxJavaPlugins.onAssembly(new ObservableLift<R, T>(this, lifter));
}
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2、ObservableLift.subscribeActual
public final class ObservableLift<R, T> extends AbstractObservableWithUpstream<T, R> {
/** The actual operator. */
final ObservableOperator<? extends R, ? super T> operator;
public ObservableLift(ObservableSource<T> source, ObservableOperator<? extends R, ? super T> operator) {
super(source);
this.operator = operator;
}
@Override
public void subscribeActual(Observer<? super R> s) {
Observer<? super T> observer;
try {
observer = ObjectHelper.requireNonNull(operator.apply(s), "Operator " + operator + " returned a null Observer");
} catch (NullPointerException e) { // NOPMD
throw e;
} catch (Throwable e) {
Exceptions.throwIfFatal(e);
// can't call onError because no way to know if a Disposable has been set or not
// can't call onSubscribe because the call might have set a Disposable already
RxJavaPlugins.onError(e);
NullPointerException npe = new NullPointerException("Actually not, but can't throw other exceptions due to RS");
npe.initCause(e);
throw npe;
}
source.subscribe(observer);
}
}
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可以看到程式碼非常快的就將傳遞進來的引數operator
執行apply()
10.7 RxJava的自定義Transformer原理
知識點:
- 自定義Transformer是如何實現的
在講解之前,讓我們先回味下自定義Transformer
public class NetWorkTransformer implements ObservableTransformer {
@Override
public ObservableSource apply(Observable upstream) {
return upstream.subscribeOn(Schedulers.io()).observeOn(AndroidSchedulers.mainThread());
}
}
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Observable.create(new ObservableOnSubscribe<Integer>() {
@Override
public void subscribe(ObservableEmitter<Integer> emitter) throws Exception {
}
}).compose(new CustomTransformer())
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自定義Transformer如同普通的操作符原理差不多,用的是compose
的操作符,只不過在compose
裡面將邏輯的執行回撥到自定義的Transformer的apply()
以下是RxJava原始碼
1、Observable.compose
public final <R> Observable<R> compose(ObservableTransformer<? super T, ? extends R> composer) {
return wrap(((ObservableTransformer<T, R>) ObjectHelper.requireNonNull(composer, "composer is null")).apply(this));
}
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可以看到程式碼非常快的就將傳遞進來的引數composer
執行apply()
,這裡的wrap()
只是將程式碼裹了一層,如果你想簡單的理解的話,可以理解為作者的強迫症犯了,只是為了讓所有程式碼看起來都比較規範,不然這裡實在和其他操作符的實現不一樣,我們可以追進去wrap()
public static <T> Observable<T> wrap(ObservableSource<T> source) {
ObjectHelper.requireNonNull(source, "source is null");
if (source instanceof Observable) {
return RxJavaPlugins.onAssembly((Observable<T>)source);
}
return RxJavaPlugins.onAssembly(new ObservableFromUnsafeSource<T>(source));
}
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wrap()
其實是對composer
操作符做了Hook,因為所有操作符都會被RxJava去Hook住,這裡會在下面講到自定義Plugin原理的時候就明白了
10.8 RxJava的自定義Plugin原理
知識點:
- 自定義Plugin是如何實現AOP的
在講解之前,讓我們先回味下自定義Plugin
public class CustomObservableAssembly implements Function<Observable, Observable> {
@Override
public Observable apply(Observable observable) throws Exception {
System.out.println("CustomObservableAssembly observable.toString:" + observable.toString());
return observable;
}
}
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RxJavaPlugins.setOnObservableAssembly(new CustomObservableAssembly());
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在自定義Plugin中,類似於Android的術語Hook,但在這裡並不是真正的Hook,而是作者在寫RxJava的時候去限定一套規範,讓後面的所有操作符或其他操作等,都可以實現Hook的原理
以下是RxJava原始碼
1、RxJavaPlugins.setOnObservableAssembly
public static void setOnObservableAssembly(@Nullable Function<? super Observable, ? extends Observable> onObservableAssembly) {
if (lockdown) {
throw new IllegalStateException("Plugins can't be changed anymore");
}
RxJavaPlugins.onObservableAssembly = onObservableAssembly;
}
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RxJavaPlugins.setOnObservableAssembly
只是對成員變數設定了自定義的值,這個時候onObservableAssembly
就有了值,預設是為null的。設定完值就表示已經Hook成功了,當操作符執行的時候,是如何回撥我們Hook的函式的
2、Observable.create
public static <T> Observable<T> create(ObservableOnSubscribe<T> source) {
ObjectHelper.requireNonNull(source, "source is null");
return RxJavaPlugins.onAssembly(new ObservableCreate<T>(source));
}
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create相當於一個操作符,在每個操作符的裡面都會去執行一段RxJavaPlugins.onAssembly
,這裡就是RxJava規定的規範,一開始我們只是說返回自身,但是有了Hook之後,就會回撥Hook函式,返回已經經過二次加工的自身
3、RxJavaPlugins.onAssembly
public static <T> Observable<T> onAssembly(@NonNull Observable<T> source) {
Function<? super Observable, ? extends Observable> f = onObservableAssembly;
if (f != null) {
return apply(f, source);
}
return source;
}
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由於我們已經設定了新值,這裡的onObservableAssembly
就不為null,不為null則執行apply()
,apply()
就是我們Hook傳進去引數的回撥方法
10.9 美團WhiteBoard
美團的WhiteBoard其實是取自美團的開源框架Shield——開源的移動端頁面模組化開發框架
中的程式碼,其主要作用是應用RxJava的Subject搭起元件間通訊的橋樑。實質上在WhiteBoard中,是將所有的元件的資料和Subject通訊的橋樑儲存起來,通過key作為元件的唯一標誌。不過比較可惜的是WhiteBoard使用的是RxJava1,不過關係不大,只要讀懂裡面的原始碼即可
1、WhiteBoard的初始化
初始化放在Activity/Fragment介面中,相當於通訊的橋樑,每個介面中僅有一個WhiteBoard的例項,並由所有元件共用
public abstract class ShieldFragment extends Fragment implements AgentCellBridgeInterface, DriverInterface {
static final String TAG = ShieldFragment.class.getSimpleName();
......
protected WhiteBoard whiteBoard;
public ShieldFragment() {
this.whiteBoard = new WhiteBoard();//初始化
}
@Override
public void onCreate(Bundle savedInstanceState) {
super.onCreate(savedInstanceState);
......
whiteBoard.onCreate(savedInstanceState);//對應生命週期
}
@Override
public void onDestroy() {
super.onDestroy();
......
whiteBoard.onDestory();//對應生命週期
}
@Override
public void onSaveInstanceState(Bundle outState) {
super.onSaveInstanceState(outState);
......
whiteBoard.onSaveInstanceState(outState);//對應生命週期
}
@Override
public WhiteBoard getWhiteBoard() {
return whiteBoard;//獲取例項
}
}
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2、WhiteBoard監聽通知
元件只監聽某個key的事件,有通知的時候就能收到
public class MixCellAgent extends LightAgent {
private MixCell mixCell;
private Subscription loadingSubscription;
private Subscription emptySubscription;
public MixCellAgent(Fragment fragment, DriverInterface bridge, PageContainerInterface pageContainer) {
super(fragment, bridge, pageContainer);
}
@Override
public void onCreate(Bundle savedInstanceState) {
super.onCreate(savedInstanceState);
mixCell = new MixCell(getContext(), this);
loadingSubscription = getWhiteBoard().getObservable(MixLoadingAgent.KEY_LOADING).filter(new Func1() {
@Override
public Object call(Object o) {
return o instanceof Boolean && ((Boolean) o);
}
}).subscribe(new Action1() {
@Override
public void call(Object o) {
loading();
}
});
emptySubscription = getWhiteBoard().getObservable(MixLoadingAgent.KEY_EMPTY).filter(new Func1<Object, Boolean>() {
@Override
public Boolean call(Object o) {
return o instanceof Boolean && ((Boolean) o);
}
}).subscribe(new Action1() {
@Override
public void call(Object o) {
mixCell.onEmpty();
}
});
......
}
@Override
public void onDestroy() {
if (loadingSubscription != null) {
loadingSubscription.unsubscribe();
loadingSubscription = null;
}
if (emptySubscription != null) {
emptySubscription.unsubscribe();
}
......
}
}
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3、WhiteBoard的傳送通知
WhiteBoard傳送通知就是呼叫WhiteBoard提供的所有put方法,具體是如何收到訊息的,還需要通過WhiteBoard的原始碼看下
public class MixLoadingAgent extends LightAgent implements MixLoadingCell.MixLoadingListener {
public static final String KEY_LOADING = "loading";
public static final String KEY_EMPTY = "empty";
public static final String KEY_FAILED = "failed";
public static final String KEY_MORE = "more";
public static final String KEY_DONE = "done";
private MixLoadingCell mixLoadingCell;
public MixLoadingAgent(Fragment fragment, DriverInterface bridge, PageContainerInterface pageContainer) {
super(fragment, bridge, pageContainer);
mixLoadingCell = new MixLoadingCell(getContext());
mixLoadingCell.setOnMixLoadingListener(this);
}
@Override
public SectionCellInterface getSectionCellInterface() {
return mixLoadingCell;
}
@Override
public void onLoading() {
getWhiteBoard().putBoolean(KEY_LOADING, true);
}
@Override
public void onEmpty() {
getWhiteBoard().putBoolean(KEY_EMPTY, true);
}
@Override
public void onFailed() {
getWhiteBoard().putBoolean(KEY_FAILED, true);
}
@Override
public void onMore() {
getWhiteBoard().putBoolean(KEY_MORE, true);
}
@Override
public void onDone() {
getWhiteBoard().putBoolean(KEY_DONE, true);
}
}
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4、WhiteBoard的原理
最後只需要獲取例項後傳送通知即可,getWhiteBoard().putBoolean(key)
。WhiteBoard原理是隻要還是Subject的橋樑的作用
public class WhiteBoard {
public static final String WHITE_BOARD_DATA_KEY = "White_Board_Data";
protected Bundle mData;//儲存所有元件的資料
protected HashMap<String, Subject> subjectMap;//儲存所有元件的通訊橋樑
public WhiteBoard() {
this(null);
}
public WhiteBoard(Bundle data) {
mData = data;
if (mData == null) {
mData = new Bundle();//初始化
}
subjectMap = new HashMap<>();//初始化
}
public void onCreate(Bundle savedInstanceState) {
if (savedInstanceState != null) {
mData = savedInstanceState.getBundle(WHITE_BOARD_DATA_KEY);
}
if (mData == null) {
mData = new Bundle();
}
}
public void onSaveInstanceState(Bundle outState) {
if (outState != null) {
// here we must save a new copy of the mData into the outState
outState.putBundle(WHITE_BOARD_DATA_KEY, new Bundle(mData));
}
}
public void onDestory() {
subjectMap.clear();
mData.clear();
}
//通過key獲取某元件的橋樑
public Observable getObservable(final String key) {
Subject res = null;
if (subjectMap.containsKey(key)) {
res = subjectMap.get(key);
} else {
res = PublishSubject.create();
subjectMap.put(key, res);
}
if (getData(key) != null) {
return res.startWith(getData(key));//帶上已經儲存過的資料
} else {
return res;
}
}
//通過key通知某元件
protected void notifyDataChanged(String key) {
if (subjectMap.containsKey(key)) {
subjectMap.get(key).onNext(mData.get(key));
}
}
//移除元件中的資料
public void removeData(String key) {
mData.remove(key);
notifyDataChanged(key);
}
//每次put值的時候,就會去通知對應的元件
public void putBoolean(@Nullable String key, boolean value) {
mData.putBoolean(key, value);
notifyDataChanged(key);
}
public void putInt(@Nullable String key, int value) {
mData.putInt(key, value);
notifyDataChanged(key);
}
public void putString(@Nullable String key, @Nullable String value) {
mData.putString(key, value);
notifyDataChanged(key);
}
......
public double getDouble(String key) {
return mData.getDouble(key);
}
public String getString(String key, String defaultValue) {
return mData.getString(key, defaultValue);
}
......
}
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