Cancelling an input after a specified time limit with Python-Asyncio - python-3.x

Hello there i am trying to use Async to take an input if given and continue if its not given cancel the task and use the default input.
state = 'routine'
async def start():
while True:
state = input('Enter state')
print(state)
async def main():
task = asyncio.Task(start())
await asyncio.sleep(5)
task.cancel()
print(state)
with suppress(asyncio.CancelledError):
await task
There is an infinite loop, user is given 5 seconds to provide an input and if user has not given any input use the default one (state).It's stuck on taking input.

input is a blocking function, so it must not be called from a coroutine. A hint that your start coroutine is not correctly written is that it doesn't await anything. Take a look at aioconsole for an async equivalent of input and others.
Also, create tasks using asyncio.create_task (or loop.create_task prior to Python 3.7), not by calling the Task constructor directly.

Related

Asyncio wait_for one function to end, or for another

My code has 2 functions:
async def blabla():
sleep(5)
And
async def blublu():
sleep(2)
asyncio.wait_for as I know can wait for one function like this:
asyncio.wait_for(blublu(), timeout=6) or asyncio.wait_for(blublu(), timeout=6)
What I wan't to do, is to make asyncio wait for both of them, and if one of them ends faster, proceed without waiting for the second one.
Is it possible to make so?
Edit: timeout is needed
Use asyncio.wait with the return_when kwarg:
# directly passing coroutine objects in `asyncio.wait`
# is deprecated since py 3.8+, wrapping into a task
blabla_task = asyncio.create_task(blabla())
blublu_task = asyncio.create_task(blublu())
done, pending = await asyncio.wait(
{blabla_task, blublu_task},
return_when=asyncio.FIRST_COMPLETED
)
# do something with the `done` set

Starvation in `asyncio` loop

I have a system where two "processes" A and B run on the same asyncio event loop.
I notice that the order of the initiation of processes matters - i.e. if I start process B first then process B runs all the time, while it seems that A is being "starved" of resources vise-a-versa.
In my experience, the only reason this might happen is due to a mutex which is not being released by B, but in the following toy example it happens without any mutexs being used:
import asyncio
async def A():
while True:
print('A')
await asyncio.sleep(2)
async def B():
while True:
print('B')
await asyncio.sleep(8)
async def main():
await B()
await A()
if __name__ == '__main__':
loop = asyncio.get_event_loop()
loop.run_until_complete(main())
Is in python the processes do not perform context-switch automatically? If not - how can I make both processes participate, each one in the time the other one is idle (i.e., sleeping)?
TLDR: Coroutines merely enable concurrency, they do not automatically trigger concurrency. Explicitly launch separate tasks, e.g. via create_task or gather, to run the coroutines concurrently.
async def main():
await asyncio.gather(B(), A())
Concurrency in asyncio is handled via Tasks – a close equivalent to Threads – which merely consist of coroutines/awaitables – like Threads consist of functions/callables. In general, a coroutine/awaitable itself does not equate to a separate task.
Using await X() means "start X and wait for it to complete". When using several such constructs in sequence:
async def main():
await B()
await A()
this means launching B first, and only launching A after B has completed: while async def and await allows for concurrency towards other tasks, B and A are run sequentially with respect to each other in a single task.
The simplest means to add concurrency is to explicitly create a task:
async def main():
# execute B in a new task
b_task = asyncio.create_task(B())
# execute A in the current task
await A()
await b_task
Note how B is offloaded to a new task, while one can still do a final await A() to re-use the current task.
Most async frameworks ship with high-level helpers for common concurrency scenarios. In this case, asyncio.gather is appropriate to launch several tasks at once:
async def main():
# execute B and A in new tasks
await asyncio.gather(B(), A())

asyncio wait on multiple tasks with timeout and cancellation

I have some code that runs multiple tasks in a loop like this:
done, running = await asyncio.wait(running, timeout=timeout_seconds,
return_when=asyncio.FIRST_COMPLETED)
I need to be able to determine which of these timed out. According to the documentation:
Note that this function does not raise asyncio.TimeoutError. Futures or Tasks that aren’t done when the timeout occurs are simply returned in the second set.
I could use wait_for() instead, but that function only accepts a single awaitable, whereas I need to specify multiple. Is there any way to determine which one from the set of awaitables I passed to wait() was responsible for the timeout?
Alternatively, is there a way to use wait_for() with multiple awaitables?
Your can try that tricks, probably it is not good solution:
import asyncio
async def foo():
return 42
async def need_some_sleep():
await asyncio.sleep(1000)
return 42
async def coro_wrapper(coro):
result = await asyncio.wait_for(coro(), timeout=10)
return result
loop = asyncio.get_event_loop()
done, running = loop.run_until_complete(asyncio.wait(
[coro_wrapper(foo), coro_wrapper(need_some_sleep)],
return_when=asyncio.FIRST_COMPLETED
)
)
for item in done:
print(item.result())
print(done, running)
Here is how I do it:
done, pending = await asyncio.wait({
asyncio.create_task(task, name=index)
for index, task in enumerate([
my_coroutine(),
my_coroutine(),
my_coroutine(),
])
},
return_when=asyncio.FIRST_COMPLETED
)
num = next(t.get_name() for t in done)
if num == 2:
pass
Use enumerate to name the tasks as they are created.

how to run gather and a coroutine task concurrently

I have approximately the following code
import asyncio
.
.
.
async def query_loop()
while connected:
result = await asyncio.gather(get_value1, get_value2, get_value3)
if True in result:
connected = False
async def main():
await query_loop()
asyncio.run(main())
The get_value - functions query a device, receive values, and publish them to a server. If no problems occur they return False, else True.
Now I need to implement, that the get_value2-function checks if it received the value 7. In this case I need the program to wait for 3 min before sending a special command to the device. But in the mean time, and also afterwards the query_loop should continue.
Has anybody an idea how to do that ?
thanks in advance!
If I understand you correctly, you want to modify get_value2 so that it reacts to a value received from device by spawning additional work in the background, i.e. do something without the loop in query_loop having to wait for that new work to finish.
You can use asyncio.create_task() to spawn a background task. In fact, you can always combine create_task() and await to runs things in the background; asyncio.gather is just a utility function that does it for you. In this case query_loop remains unchanged, and get_value2 gets modified like this:
async def get_value2():
...
value = await receive_value_from_device()
if value == 7:
# schedule send_command() to run, but don't wait for it
asyncio.create_task(special_command())
...
return False
async def special_command():
await asyncio.sleep(180)
await send_command_to_device(...)
Note that if get_value1 and others are async functions, the correct invocation of gather must call them, so it should be await asyncio.gather(get_value1(), get_value2(), get_value3()) (note the extra parentheses).

Return an asyncio callback result from task creating function

I'm trying to wrap an async function up so that I can use it without importing asyncio in certain files. The ultimate goal is to use asynchronous functions but being able to call them normally and get back the result.
How can I access the result from the callback function printing(task) and use it as the return of my make_task(x) function?
MWE:
#!/usr/bin/env python3.7
import asyncio
loop = asyncio.get_event_loop()
def make_task(x): # Can be used without asyncio
task = loop.create_task(my_async(x))
task.add_done_callback(printing)
# return to get the
def printing(task):
print('sleep done: %s' % task.done())
print('results: %s' % task.result())
return task.result() # How can i access this return?
async def my_async(x): # Handeling the actual async running
print('Starting my async')
res = await my_sleep(x)
return res # The value I want to ultimately use in the real callback
async def my_sleep(x):
print('starting sleep for %d' % x)
await asyncio.sleep(x)
return x**2
async def my_coro(*coro):
return await asyncio.gather(*coro)
val1 = make_task(4)
val2 = make_task(5)
loop.run_until_complete(my_coro(asyncio.sleep(6)))
print(val1)
print(val2)
If I understand correctly you want to use asynchronous functions but don't want to write async/await in top-level code.
If that's the case, I'm afraid it's not possible to achieve with asyncio. asyncio wants you to write async/await everywhere asynchronous stuff happens and this is intentional: forcing to explicitly mark places of possible context switch is a asyncio's way to fight concurrency-related problems (which is very hard to fight otherwise). Read this answer for more info.
If you still want to have asynchronous stuff and use it "as usual code" take a look at alternative solutions like gevent.
Instead of using a callback, you can make printing a coroutine and await the original coroutine, such as my_async. make_task can then create a task out of printing(my_async(...)), which will make the return value of printing available as the task result. In other words, to return a value out of printing, just - return it.
For example, if you define make_task and printing like this and leave the rest of the program unchanged:
def make_task(x):
task = loop.create_task(printing(my_async(x)))
return task
async def printing(coro):
coro_result = await coro
print('sleep done')
print('results: %s' % coro_result)
return coro_result
The resulting output is:
Starting my async
starting sleep for 4
Starting my async
starting sleep for 5
sleep done
results: 16
sleep done
results: 25
<Task finished coro=<printing() done, defined at result1.py:11> result=16>
<Task finished coro=<printing() done, defined at result1.py:11> result=25>

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