I am trying to properly understand and implement two concurrently running Task
objects using Python 3's relatively new asyncio
module.
In a nutshell, asyncio seems designed to handle asynchronous processes and concurrent Task
execution over an event loop. It promotes the use of await
(applied in async functions) as a callback-free way to wait for and use a result, without blocking the event loop. (Futures and callbacks are still a viable alternative.)
It also provides the asyncio.Task()
class, a specialized subclass of Future
designed to wrap coroutines. Preferably invoked by using the asyncio.ensure_future()
method. The intended use of asyncio tasks is to allow independently running tasks to run 'concurrently' with other tasks within the same event loop. My understanding is that Tasks
are connected to the event loop which then automatically keeps driving the coroutine between await
statements.
I like the idea of being able to use concurrent Tasks without needing to use one of the Executor
classes, but I haven't found much elaboration on implementation.
This is how I'm currently doing it:
import asyncio
print('running async test')
async def say_boo():
i = 0
while True:
await asyncio.sleep(0)
print('...boo {0}'.format(i))
i += 1
async def say_baa():
i = 0
while True:
await asyncio.sleep(0)
print('...baa {0}'.format(i))
i += 1
# wrap in Task object
# -> automatically attaches to event loop and executes
boo = asyncio.ensure_future(say_boo())
baa = asyncio.ensure_future(say_baa())
loop = asyncio.get_event_loop()
loop.run_forever()
In the case of trying to concurrently run two looping Tasks, I've noticed that unless the Task has an internal await
expression, it will get stuck in the while
loop, effectively blocking other tasks from running (much like a normal while
loop). However, as soon the Tasks have to (a)wait, they seem to run concurrently without an issue.
Thus, the await
statements seem to provide the event loop with a foothold for switching back and forth between the tasks, giving the effect of concurrency.
Example output with internal await
:
running async test
...boo 0
...baa 0
...boo 1
...baa 1
...boo 2
...baa 2
Example output without internal await
:
...boo 0
...boo 1
...boo 2
...boo 3
...boo 4
Does this implementation pass for a 'proper' example of concurrent looping Tasks in asyncio
?
Is it correct that the only way this works is for a Task
to provide a blocking point (await
expression) in order for the event loop to juggle multiple tasks?
Yes, any coroutine that's running inside your event loop will block other coroutines and tasks from running, unless it
yield from
or await
(if using Python 3.5+).This is because asyncio
is single-threaded; the only way for the event loop to run is for no other coroutine to be actively executing. Using yield from
/await
suspends the coroutine temporarily, giving the event loop a chance to work.
Your example code is fine, but in many cases, you probably wouldn't want long-running code that isn't doing asynchronous I/O running inside the event loop to begin with. In those cases, it often makes more sense to use asyncio.loop.run_in_executor
to run the code in a background thread or process. ProcessPoolExecutor
would be the better choice if your task is CPU-bound, ThreadPoolExecutor
would be used if you need to do some I/O that isn't asyncio
-friendly.
Your two loops, for example, are completely CPU-bound and don't share any state, so the best performance would come from using ProcessPoolExecutor
to run each loop in parallel across CPUs:
import asyncio
from concurrent.futures import ProcessPoolExecutor
print('running async test')
def say_boo():
i = 0
while True:
print('...boo {0}'.format(i))
i += 1
def say_baa():
i = 0
while True:
print('...baa {0}'.format(i))
i += 1
if __name__ == "__main__":
executor = ProcessPoolExecutor(2)
loop = asyncio.get_event_loop()
boo = asyncio.create_task(loop.run_in_executor(executor, say_boo))
baa = asyncio.create_task(loop.run_in_executor(executor, say_baa))
loop.run_forever()