I want to start a new Process (Pricefeed) from my Executor class and then have the Executor class keep running in its own event loop (the shoot method). In my current attempt, the asyncio loop gets blocked on the line p.join(). However, without that line, my code just exits. How do I do this properly?
Note: fh.run() blocks as well.
import asyncio
from multiprocessing import Process, Queue
from cryptofeed import FeedHandler
from cryptofeed.defines import L2_BOOK
from cryptofeed.exchanges.ftx import FTX
class Pricefeed(Process):
def __init__(self, queue: Queue):
super().__init__()
self.coin_symbol = 'SOL-USD'
self.fut_symbol = 'SOL-USD-PERP'
self.queue = queue
async def _book_update(self, feed, symbol, book, timestamp, receipt_timestamp):
self.queue.put(book)
def run(self):
fh = FeedHandler()
fh.add_feed(FTX(symbols=[self.fut_symbol, self.coin_symbol], channels=[L2_BOOK],
callbacks={L2_BOOK: self._book_update}))
fh.run()
class Executor:
def __init__(self):
self.q = Queue()
async def shoot(self):
print('in shoot')
for i in range(5):
msg = self.q.get()
print(msg)
await asyncio.sleep(1) # do some stuff
async def run(self):
asyncio.create_task(self.shoot())
p = Pricefeed(self.q)
p.start()
p.join()
async def main():
g = Executor()
await g.run()
if __name__ == '__main__':
asyncio.run(main())
Since you're using a queue to communicate this is a somewhat tricky problem. To answer your first question as to why removing join makes the program work, join blocks until the process finishes. In asyncio you can't do anything blocking in a function marked async or it will freeze the event loop. To do this properly you'll need to run your process with the asyncio event loop's run_in_executor method which will run things in a process pool and return an awaitable that is compatible with the asyncio event loop.
Secondly, you'll need to use a multiprocessing Manager which creates shared state that can be used by multiple processes to properly share your queue. Managers directly support creation of a shared queue. Using these two bits of knowledge you can adapt your code to something like the following which works:
import asyncio
import functools
import time
from multiprocessing import Manager
from concurrent.futures import ProcessPoolExecutor
def run_pricefeed(queue):
i = 0
while True: #simulate putting an item on the queue every 250ms
queue.put(f'test-{i}')
i += 1
time.sleep(.25)
class Executor:
async def shoot(self, queue):
print('in shoot')
for i in range(5):
while not queue.empty():
msg = queue.get(block=False)
print(msg)
await asyncio.sleep(1) # do some stuff
async def run(self):
with ProcessPoolExecutor() as pool:
with Manager() as manager:
queue = manager.Queue()
asyncio.create_task(self.shoot(queue))
await asyncio.get_running_loop().run_in_executor(pool, functools.partial(run_pricefeed, queue))
async def main():
g = Executor()
await g.run()
if __name__ == '__main__':
asyncio.run(main())
This code has a drawback in that you need to empty the queue in a non-blocking fashing from your asyncio process and wait for a while for new items to come in before emptying it again, effectively implementing a polling mechanism. If you don't wait after emptying, you'll wind up with blocking code and you will freeze the event loop again. This isn't as good as just waiting for the queue to have an item in it by blocking, but may suit your needs. If possible, I would avoid asyncio here and use multiprocessing entirely, for example, by implementing queue processing as a separate process.
Related
I am prototyping a FastAPI app with an endpoint that will launch long-running process using subprocess module. The obvious solution is to use concurrent.futures and ProcessPoolExecutor, however I am unable to get the behavior I want. Code sample:
import asyncio
from concurrent.futures import ProcessPoolExecutor
import subprocess as sb
import time
import random
pool = ProcessPoolExecutor(5)
def long_task(s):
print("started")
time.sleep(random.randrange(5, 15))
sb.check_output(["touch", str(s)])
print("done")
async def async_task():
loop = asyncio.get_event_loop()
print("started")
tasks = [loop.run_in_executor(pool, long_task, i) for i in range(10)]
while True:
print("in async task")
done, _ = await asyncio.wait(tasks, timeout=1)
for task in done:
await task
await asyncio.sleep(1)
def main():
loop = asyncio.get_event_loop()
loop.run_until_complete(async_task())
if __name__ == "__main__":
main()
This sample works fine, on the surface, but spawned processes do not get stopped after execution completes - I see all of python processes in ps aux | grep python. Shouldn't awaiting completed task stop it? In the end I do not care much about the result of the execution, it just should happen in the background and exit cleanly - without any hanging processes.
You must close the ProcessPool when you are done using it, either by explicitly calling its shutdown() method, or using it in a ContextManager. I used the ContextManager approach.
I don't know what subprocess.check_output does, so I commented it out.
I also replaced your infinite loop with a single call to asyncio.gather, which will yield until the Executor is finished.
I'm on Windows, so to observe the creation/deletion of Processes I watched the Windows Task Manager. The program creates 5 subprocesses and closes them again when the ProcessPool context manager exits.
import asyncio
from concurrent.futures import ProcessPoolExecutor
# import subprocess as sb
import time
import random
def long_task(s):
print("started")
time.sleep(random.randrange(5, 15))
# sb.check_output(["touch", str(s)])
print("done", s)
async def async_task():
loop = asyncio.get_event_loop()
print("started")
with ProcessPoolExecutor(5) as pool:
tasks = [loop.run_in_executor(pool, long_task, i) for i in range(10)]
await asyncio.gather(*tasks)
print("Completely done")
def main():
asyncio.run(async_task())
if __name__ == "__main__":
main()
I would like to combine asyncio and multiprocessing as I have a task where a part is io-bound and another is cpu-bound. I first tried to use loop.run_in_executor(), but I couldn't get it to work probably. Instead I went with creating two processes where one uses asyncio and the other doesn't.
The code is such that I have a class with some non-blocking functions and one blocking. I have an asyncio.Queue to pass information between the non-blocking parts and a multiprocessing.Queue to pass information between the non-blocking and the blocking functions.
import multiprocessing as mp
from concurrent.futures import ProcessPoolExecutor
import asyncio
import time
class TestClass:
def __init__(self):
m = mp.Manager()
self.blocking_queue = m.Queue()
async def run(self):
loop = asyncio.get_event_loop()
self.non_blocking_queue = asyncio.Queue() # asyncio Queue must be declared within event loop
task1 = loop.create_task(self.non_blocking1())
task2 = loop.create_task(self.non_blocking2())
task3 = loop.create_task(self.print_msgs())
await asyncio.gather(task1, task2)
task3.cancel()
def blocking(self):
i = 0
while i < 5:
time.sleep(0.6)
i += 1
print("Blocking ", i)
line = self.blocking_queue.get()
print("Blocking: ", line)
print("blocking done")
async def non_blocking1(self):
for i in range(5):
await self.non_blocking_queue.put("Hello")
await asyncio.sleep(0.4)
async def non_blocking2(self):
for i in range(5):
await self.non_blocking_queue.put("World")
await asyncio.sleep(0.5)
async def print_msgs(self):
while True:
line = await self.non_blocking_queue.get()
self.blocking_queue.put(line)
print(line)
test_class = TestClass()
with ProcessPoolExecutor() as pool:
pool.submit(test_class.blocking)
pool.submit(asyncio.run(test_class.run()))
print("done")
About half the times I run this, it works fine and prints out the text in the blocking and the non-blocking queues. The other half it only prints out the results of the non-blocking queue. It looks like the blocking process isn't started at all. It is not consequent every other time. It might work five times in a row and then not work five times in row.
What might cause such a problem? Which better way can I do this, using both multiprocessing and asyncio?
running the async task "inside" the other process works for me, e.g.:
def runfn(fn):
return asyncio.run(fn())
with ProcessPoolExecutor() as pool:
pool.submit(test_class.blocking)
pool.submit(runfn, test_class.run)
presumably there's some state inside asyncio/the task that needs to be consistent or gets broken when running in another process
I have a program with one main thread where I spawn a second thread that uses asyncio. Are there any tools provided to synchronize these two threads? If everything was asyncio, I could do it with its synchronization primitives, eg:
import asyncio
async def taskA(lst, evt):
print(f'Appending 1')
lst.append(1)
evt.set()
async def taskB(lst, evt):
await evt.wait()
print('Retrieved:', lst.pop())
lst = []
evt = asyncio.Event()
asyncio.get_event_loop().run_until_complete(asyncio.gather(
taskA(lst, evt),
taskB(lst, evt),
))
However, this does not work with multiple threads. If I just use a threading.Event then it will block the asyncio thread. I figured out I could defer the wait to an executor:
import asyncio
import threading
def taskA(lst, evt):
print(f'Appending 1')
lst.append(1)
evt.set()
async def taskB(lst, evt):
asyncio.get_event_loop().run_in_executor(None, evt.wait)
print('Retrieved:', lst.pop())
def targetA(lst, evt):
taskA(lst, evt)
def targetB(lst, evt):
asyncio.set_event_loop(asyncio.new_event_loop())
asyncio.get_event_loop().run_until_complete(taskB(lst, evt))
lst = []
evt = threading.Event()
threadA = threading.Thread(target=targetA, args=(lst, evt))
threadB = threading.Thread(target=targetB, args=(lst, evt))
threadA.start()
threadB.start()
threadA.join()
threadB.join()
However, having an executor thread only to wait for a mutex seems unnatural. Is this the way this is supposed to be done? Or is there any other way to wait for synchronization between OS threads asynchronously?
A simple way to synchronize an asyncio coroutine with an event coming from another thread is to await an asyncio.Event in taskB, and set it from taskA using loop.call_soon_threadsafe.
To be able to pass values and exceptions between the two, you can use futures; however then you are inventing much of run_in_executor. If the only job of taskA is to take tasks off a queue, you might as well make a single-worker "pool" and use it as your worker thread. Then you can use run_in_executor as intended:
worker = concurrent.futures.ThreadPoolExecutor(max_workers=1)
async def taskB(lst):
loop = asyncio.get_event_loop()
# or result = await ..., if taskA has a useful return value
# This will also propagate exceptions raised by taskA
await loop.run_in_executor(worker, taskA, lst)
print('Retrieved:', lst.pop())
The semantics are the same as in your version with an explicit queue - the queue is still there, it's just inside the ThreadPoolExecutor.
I'm trying to combine multiprocessing with asyncio. The program has two main components - one which streams/generates content, and another that consumes it.
What I want to do is to create multiple processes in order to exploit multiple CPU cores - one for the stream listener/generator, another for the consumer, and a simple one to shut down everything when the consumer has stopped.
My approach so far has been to create the processes, and start them. Each such process creates an async task. Once all processes have started, I run the asyncio tasks. What I have so far (stripped down) is:
def consume_task(loop, consumer):
loop.create_task(consume_queue(consumer))
def stream_task(loop, listener, consumer):
loop.create_task(create_stream(listener, consumer))
def shutdown_task(loop, listener):
loop.create_task(shutdown(consumer))
async def shutdown(consumer):
print("Shutdown task created")
while not consumer.is_stopped():
print("No activity")
await asyncio.sleep(5)
print("Shutdown initiated")
loop.stop()
async def create_stream(listener, consumer):
stream = Stream(auth, listener)
print("Stream created")
stream.filter(track=KEYWORDS, is_async=True)
await asyncio.sleep(EVENT_DURATION)
print("Stream finished")
consumer.stop()
async def consume_queue(consumer):
await consumer.run()
loop = asyncio.get_event_loop()
p_stream = Process(target=stream_task, args=(loop, listener, consumer, ))
p_consumer = Process(target=consume_task, args=(loop, consumer, ))
p_shutdown = Process(target=shutdown_task, args=(loop, consumer, ))
p_stream.start()
p_consumer.start()
p_shutdown.start()
loop.run_forever()
loop.close()
The problem is that everything hangs (or does it block?) - no tasks are actually running. My solution was to change the first three functions to:
def consume_task(loop, consumer):
loop.create_task(consume_queue(consumer))
loop.run_forever()
def stream_task(loop, listener, consumer):
loop.create_task(create_stream(listener, consumer))
loop.run_forever()
def shutdown_task(loop, listener):
loop.create_task(shutdown(consumer))
loop.run_forever()
This does actually run. However, the consumer and the listener objects are not able to communicate. As a simple example, when the create_stream function calls consumer.stop(), the consumer does not stop. Even when I change a consumer class variable, the changes are not made - case in point, the shared queue remains empty. This is how I am creating the instances:
queue = Queue()
consumer = PrintConsumer(queue)
listener = QueuedListener(queue, max_time=EVENT_DURATION)
Please note that if I do not use processes, but only asyncio tasks, everything works as expected, so I do not think it's a reference issue:
loop = asyncio.get_event_loop()
stream_task(loop, listener, consumer)
consume_task(loop, consumer)
shutdown_task(loop, listener)
loop.run_forever()
loop.close()
Is it because they are running on different processes? How should I go about fixing this issue please?
Found the problem! Multi-processing creates copies of instances. The solution is to create a Manager, which shares the instances itself.
EDIT [11/2/2020]:
import asyncio
from multiprocessing import Process, Manager
"""
These two functions will be created as separate processes.
"""
def task1(loop, shared_list):
output = loop.run_until_complete(asyncio.gather(async1(shared_list)))
def task2(loop, shared_list):
output = loop.run_until_complete(asyncio.gather(async2(shared_list)))
"""
These two functions will be called (in different processes) asynchronously.
"""
async def async1(shared_list):
pass
async def async2(shared_list):
pass
"""
Create the manager and start it up.
From this manager, also create a list that is shared by functions in different threads.
"""
manager = Manager()
manager.start()
shared_list = manager.list()
loop = asyncio.get_event_loop() # the event loop
"""
Create two processes.
"""
process1 = Process(target=task1, args=(loop, shared_list, ))
process2 = Process(target=task2, args=(loop, shared_list, ))
"""
Start the two processes and wait for them to finish.
"""
process1.start()
process2.start()
output1 = process1.join()
output2 = process2.join()
"""
Clean up
"""
loop.close()
manager.shutdown()
It seems asyncio.Queue only can be pushed by the same thread reading it? For instance:
import asyncio
from threading import Thread
import time
q = asyncio.Queue()
def produce():
for i in range(100):
q.put_nowait(i)
time.sleep(0.1)
async def consume():
while True:
i = await q.get()
print('consumed', i)
Thread(target=produce).start()
asyncio.get_event_loop().run_until_complete(consume())
only prints
consumed 0
and then hangs. What am I missing?
You can't call asyncio methods from another thread directly.
Either use loop.call_soon_threadsafe:
loop.call_soon_threadsafe(q.put_nowait, i)
Or asyncio.run_coroutine_threadsafe:
future = asyncio.run_coroutine_threadsafe(q.put(i), loop)
where loop is the loop returned by asyncio.get_event_loop() in your main thread.