Android RxJava 3.x 使用总结
转载请标明出处：http://blog.csdn.net/zhaoyanjun6/article/details/106720158
本文出自【赵彦军的博客】
文章目录
- 依赖接入
- Flowable
- Single
- Maybe
- BackpressureStrategy
- 线程切换
- concat
- 例子1
依赖接入
implementation 'io.reactivex.rxjava3:rxandroid:3.0.0'
implementation "io.reactivex.rxjava3:rxjava:3.0.4"
Flowable
//java 方式
Flowable.just(1)
.subscribe(new Consumer<Integer>() {
@Override
public void accept(Integer integer) throws Throwable {
}
}, new Consumer<Throwable>() {
@Override
public void accept(Throwable throwable) throws Throwable {
}
});
//或者用 Lambda 简写
Flowable.just(1)
.subscribe( it -> {
}, throwable -> {
});
range 一组序列数据
Flowable.range(0, 4)
.subscribe(it -> {
//结果 0 1 2 3
}, throwable -> {
});
Single
Single只发射单个数据或错误事件，即使发射多个数据，后面发射的数据也不会处理。
只有 onSuccess 和 onError事件，没有 onNext 、onComplete事件。
SingleEmitter
public interface SingleEmitter<@NonNull T> {
void onSuccess(@NonNull T t);
void onError(@NonNull Throwable t);
void setDisposable(@Nullable Disposable d);
void setCancellable(@Nullable Cancellable c);
boolean isDisposed();
boolean tryOnError(@NonNull Throwable t);
}
示例1
Single.create(new SingleOnSubscribe<Integer>() {
@Override
public void subscribe(@NonNull SingleEmitter<Integer> emitter) throws Throwable {
emitter.onSuccess(1);
}
})
.subscribe(integer -> {
}, throwable -> {
});
示例2
Single.just(1)
.subscribe(integer -> {
}, throwable -> {
});
Maybe
Maybe 是 RxJava2.x 之后才有的新类型，可以看成是Single和Completable的结合。
Maybe 也只能发射单个事件或错误事件，即使发射多个数据，后面发射的数据也不会处理。
只有 onSuccess 、 onError 、onComplete事件，没有 onNext 事件。
public interface MaybeEmitter<@NonNull T> {
void onSuccess(@NonNull T t);
void onError(@NonNull Throwable t);
void onComplete();
void setDisposable(@Nullable Disposable d);
void setCancellable(@Nullable Cancellable c);
boolean isDisposed();
boolean tryOnError(@NonNull Throwable t);
}
实例1
Maybe.create(new MaybeOnSubscribe<Integer>() {
@Override
public void subscribe(@NonNull MaybeEmitter<Integer> emitter) throws Throwable {
emitter.onSuccess(1);
emitter.onComplete();
}
})
.subscribe(integer -> {
}, throwable -> {
});
实例2
Maybe.just(1)
.subscribe(integer -> {
}, throwable -> {
});
BackpressureStrategy
背压策略
public enum BackpressureStrategy {
/**
* The {@code onNext} events are written without any buffering or dropping.
* Downstream has to deal with any overflow.
* Useful when one applies one of the custom-parameter onBackpressureXXX operators.
*/
MISSING,
/**
* Signals a {@link io.reactivex.rxjava3.exceptions.MissingBackpressureException MissingBackpressureException}
* in case the downstream can't keep up.
*/
ERROR,
/**
* Buffers all {@code onNext} values until the downstream consumes it.
*/
BUFFER,
/**
* Drops the most recent {@code onNext} value if the downstream can't keep up.
*/
DROP,
/**
* Keeps only the latest {@code onNext} value, overwriting any previous value if the
* downstream can't keep up.
*/
LATEST
}
- MISSING 策略则表示通过 Create 方法创建的 Flowable 没有指定背压策略，不会对通过 OnNext 发射的数据做缓存或丢弃处理，需要下游通过背压操作符
- BUFFER 策略则在还有数据未下发完成时就算上游调用onComplete或onError也会等待数据下发完成
- LATEST 策略则当产生背压时仅会缓存最新的数据
- DROP 策略为背压时丢弃背压数据
- ERROR 策略是背压时抛出异常调用onError
Flowable.create(new FlowableOnSubscribe<Long>() {
@Override
public void subscribe(@NonNull FlowableEmitter<Long> emitter) throws Throwable {
emitter.onNext(1L);
emitter.onNext(2L);
emitter.onComplete();
}
}, BackpressureStrategy.DROP)
.subscribeOn(Schedulers.io())
.observeOn(AndroidSchedulers.mainThread())
.subscribe(it -> {
}, throwable -> {
});
线程切换
RxUtil
package com.example.stream
import io.reactivex.rxjava3.android.schedulers.AndroidSchedulers
import io.reactivex.rxjava3.core.FlowableTransformer
import io.reactivex.rxjava3.core.MaybeTransformer
import io.reactivex.rxjava3.core.ObservableTransformer
import io.reactivex.rxjava3.core.SingleTransformer
import io.reactivex.rxjava3.schedulers.Schedulers
/**
* @author yanjun.zhao
* @time 2020/6/12 8:39 PM
* @desc
*/
object RxUtil {
/**
* 线程切换
*/
fun <T> maybeToMain(): MaybeTransformer<T, T> {
return MaybeTransformer { upstream ->
upstream.subscribeOn(Schedulers.io())
.observeOn(AndroidSchedulers.mainThread())
}
}
/**
* 线程切换
*/
fun <T> singleToMain(): SingleTransformer<T, T> {
return SingleTransformer { upstream ->
upstream.subscribeOn(Schedulers.io())
.observeOn(AndroidSchedulers.mainThread())
}
}
/**
* 线程切换
*/
fun <T> flowableToMain(): FlowableTransformer<T, T> {
return FlowableTransformer { upstream ->
upstream.subscribeOn(Schedulers.io())
.observeOn(AndroidSchedulers.mainThread())
}
}
fun <T> observableToMain(): ObservableTransformer<T, T> {
return ObservableTransformer { upstream ->
upstream.subscribeOn(Schedulers.io())
.observeOn(AndroidSchedulers.mainThread())
}
}
}
具体实现
package com.example.stream
import android.os.Bundle
import androidx.appcompat.app.AppCompatActivity
import io.reactivex.rxjava3.core.Flowable
import io.reactivex.rxjava3.core.Maybe
import io.reactivex.rxjava3.core.Observable
import io.reactivex.rxjava3.core.Single
class MainActivity : AppCompatActivity() {
override fun onCreate(savedInstanceState: Bundle?) {
super.onCreate(savedInstanceState)
setContentView(R.layout.activity_main)
Single.just(1)
.map {
//运行在子线程
it
}
.compose(RxUtil.singleToMain()) //线程转换
.subscribe(
{
//运行在主线程
},
{
it.printStackTrace()
}
)
Maybe.just(1)
.map {
//运行在子线程
it
}
.compose(RxUtil.maybeToMain()) //线程转换
.subscribe(
{
//运行在主线程
},
{
it.printStackTrace()
}
)
Flowable.just(1)
.map {
//运行在子线程
it
}
.compose(RxUtil.flowableToMain()) //线程转换
.subscribe(
{
//运行在主线程
},
{
it.printStackTrace()
}
)
Observable.just(1)
.map {
//运行在子线程
it
}
.compose(RxUtil.observableToMain()) //线程转换
.subscribe(
{ it ->
//运行在主线程
},
{
it.printStackTrace()
}
)
}
}
concat
Concat操作符连接多个Observable的输出，就好像它们是一个Observable，第一个Observable发射的所有数据在第二个Observable发射的任何数据前面，以此类推。
直到前面一个Observable终止，Concat才会订阅额外的一个Observable。注意：因此，如果你尝试连接一个"热"Observable（这种Observable在创建后立即开始发射数据，即使没有订阅者），Concat将不会看到也不会发射它之前发射的任何数据。
例子1
private var ob1 = Observable.create<String> {
Log.d("concat-数据源1", " ${Thread.currentThread().name} ")
it.onNext("a1")
it.onComplete()
}
private var ob2 = Observable.create<String> {
Log.d("concat-数据源2", " ${Thread.currentThread().name} ")
it.onNext("a2")
it.onComplete()
}
private var ob3 = Observable.create<String> {
Log.d("concat-数据源3", " ${Thread.currentThread().name} ")
it.onNext("a3")
it.onComplete()
}
Observable.concat<String>(ob1, ob2, ob3)
.subscribeOn(Schedulers.io())
.subscribe{
Log.d("concat-结果", " ${Thread.currentThread().name} " + it)
}
结果是：
concat-数据源1: RxCachedThreadScheduler-1
concat-结果: RxCachedThreadScheduler-1
concat-数据源2: RxCachedThreadScheduler-1
concat-结果: RxCachedThreadScheduler-1
concat-数据源3: RxCachedThreadScheduler-1
concat-结果: RxCachedThreadScheduler-1
结果分析：
- concat 输出结果是有序的
- concat 会使三个数据源都会执行
那么如果我要实现哪个数据源有数据，我就用哪个数据，一旦获取到想要的数据，后续数据源不再执行。其实很简单，用 firstElement() ，这个需求有点像图片加载流程 先从内存取，内存没有从本地文件取，本都文件没有就请求服务器。一旦哪个环节获取到了数据，立刻停止后面的流程
Observable.concat<String>(ob1, ob2, ob3)
.firstElement()
.subscribeOn(Schedulers.io())
.subscribe {
Log.d("concat-结果", " ${Thread.currentThread().name} ")
}
}
运行结果为：
concat-数据源1: RxCachedThreadScheduler-1
concat-结果: RxCachedThreadScheduler-1