如何等待RxPy并行线程完成

时间:2017-05-15 21:33:03

标签: python multithreading python-multithreading reactivex rx-py

基于此excellent SO answer我可以在RxPy中同时处理多个任务,我的问题是你如何等待它们全部完成?我知道使用线程我可以做.join()但是Rx Scheduler似乎没有任何这样的选项。 .to_blocking()也没有帮助,MainThread在所有通知都被触发并且已经调用完整的处理程序之前完成。这是一个例子:

from __future__ import print_function
import os, sys
import time
import random
from rx import Observable
from rx.core import Scheduler
from threading import current_thread

def printthread(val):
    print("{}, thread: {}".format(val, current_thread().name))

def intense_calculation(value):
    printthread("calc {}".format(value))
    time.sleep(random.randint(5, 20) * .1)
    return value

if __name__ == "__main__":
    Observable.range(1, 3) \
        .select_many(lambda i: Observable.start(lambda: intense_calculation(i), scheduler=Scheduler.timeout)) \
        .observe_on(Scheduler.event_loop) \
        .subscribe(
            on_next=lambda x: printthread("on_next: {}".format(x)),
            on_completed=lambda: printthread("on_completed"),
            on_error=lambda err: printthread("on_error: {}".format(err)))

    printthread("\nAll done")
    # time.sleep(2)

预期输出

calc 1, thread: Thread-1
calc 2, thread: Thread-2
calc 3, thread: Thread-3

on_next: 2, thread: Thread-4
on_next: 3, thread: Thread-4
on_next: 1, thread: Thread-4
on_completed, thread: Thread-4
All done, thread: MainThread

实际输出

calc 1, thread: Thread-1
calc 2, thread: Thread-2
calc 3, thread: Thread-3

All done, thread: MainThread

如果我取消注释睡眠呼叫

,则为实际输出
calc 1, thread: Thread-1
calc 2, thread: Thread-2
calc 3, thread: Thread-3

All done, thread: MainThread
on_next: 2, thread: Thread-4
on_next: 3, thread: Thread-4
on_next: 1, thread: Thread-4
on_completed, thread: Thread-4

2 个答案:

答案 0 :(得分:3)

在此处发布完整解决方案:

from __future__ import print_function
import os, sys
import time
import random
from rx import Observable
from rx.core import Scheduler
from threading import current_thread
from rx.concurrency import ThreadPoolScheduler

def printthread(val):
    print("{}, thread: {}".format(val, current_thread().name))

def intense_calculation(value):
    printthread("calc {}".format(value))
    time.sleep(random.randint(5, 20) * .1)
    return value

if __name__ == "__main__":
    scheduler = ThreadPoolScheduler(4)

    Observable.range(1, 3) \
        .select_many(lambda i: Observable.start(lambda: intense_calculation(i), scheduler=scheduler)) \
        .observe_on(Scheduler.event_loop) \
        .subscribe(
            on_next=lambda x: printthread("on_next: {}".format(x)),
            on_completed=lambda: printthread("on_completed"),
            on_error=lambda err: printthread("on_error: {}".format(err)))

    printthread("\nAll done")
    scheduler.executor.shutdown()
    # time.sleep(2)

答案 1 :(得分:1)

对于ThreadPoolScheduler,您可以:

  1. scheduler = ThreadPoolScheduler(pool_size)
  2. 并行通话。
  3. scheduler.executor.shutdown()
  4. 然后,一旦完成所有结果,您就可以获得所有结果。