RxPy: How to create hot observable from external callback and subscribe multiple asynchronous processes?
我有一个外部服务(ExternalDummyService)，在其中注册了回调。我想从该回调中创建一个可观察对象，并订阅多个异步进程。
pyfiddle中的完整代码：https://pyfiddle.io/fiddle/da1e1d53-2e34-4742-a0b9-07838f2c13df
*请注意，在pyfiddle版本中，"睡眠"被替换为" for range(10000)中的i：foo = i"，因为睡眠无法正常工作。
主要代码是这样的：
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 | thread = ExternalDummyService() external_obs = thread.subject.publish() external_obs.subscribe(slow_process) external_obs.subscribe(fast_process) external_obs.connect() thread.start() class ExternalDummyService(Thread): def __init__(self): self.subject = Subject() def run(self): for i in range(5): dummy_msg = { ... } self.subject.on_next(dummy_msg) def fast_process(msg): print("FAST {0} {1}".format(msg["counter"], 1000*(time() - msg["timestamp"]))) sleep(0.1) def slow_process(msg): print("SLOW {0} {1}".format(msg["counter"], 1000*(time() - msg["timestamp"]))) sleep(1) |
我得到的输出是这个，两个进程都同步运行，并且在两个进程都完成每次执行之前，ExternalDummyService不会发出新值：
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 | emitting 0 STARTED SLOW 0 1.0008811950683594 FAST 0 2.0122528076171875 emitting 1 SLOW 1 1.5070438385009766 FAST 1 1.5070438385009766 emitting 2 SLOW 2 0.5052089691162109 FAST 2 0.9891986846923828 emitting 3 SLOW 3 1.0006427764892578 FAST 3 1.0006427764892578 emitting 4 SLOW 4 1.0013580322265625 FAST 4 1.0013580322265625 FINISHED |
我想得到这样的东西，服务发出消息而无需等待进程运行和异步运行：
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 | STARTED emitting 0 emitting 1 emitting 2 FAST 0 2.0122528076171875 FAST 1 1.5070438385009766 emitting 3 SLOW 0 1.0008811950683594 FAST 2 0.9891986846923828 emitting 4 FAST 3 1.0006427764892578 SLOW 1 1.5070438385009766 FAST 4 1.0013580322265625 SLOW 2 0.5052089691162109 SLOW 3 1.0006427764892578 SLOW 4 1.0013580322265625 FINISHED |
我尝试使用share()，ThreadPoolScheduler和其他我没有想法的东西在做事情。
谢谢！
使用以下问题的答案：具有多个订阅者和事件的RxJava并发
...通过以下代码，我已经达到了预期的结果：
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 | optimal_thread_count = cpu_count() pool_scheduler = ThreadPoolScheduler(optimal_thread_count) thread = ExternalDummyService() external_obs = thread.subject.publish() external_obs \\ .flat_map(lambda msg: Observable.just(msg).subscribe_on(pool_scheduler)) \\ .subscribe(fast_process) external_obs \\ .flat_map(lambda msg: Observable.just(msg).subscribe_on(pool_scheduler)) \\ .subscribe(slow_process) external_obs.connect() thread.start() |
完整版本：https：//pyfiddle.io/fiddle/20f8871c-48d6-4d6b-b1a4-fdd0a4aa6f95/？m =保存的小提琴
输出为：
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | emitting 0 emitting 1 emitting 2 emitting 3 emitting 4 FAST 0 52.629709243774414 FAST 1 51.12814903259277 FAST 2 100.2051830291748 FAST 3 151.2434482574463 SLOW 0 503.0245780944824 SLOW 1 502.0263195037842 FAST 4 548.7725734710693 SLOW 2 551.4400005340576 SLOW 3 652.1098613739014 SLOW 4 1000.3445148468018 |
请随时提出任何改进建议。