Imagine that I have a main program which starts many async activities which all wait on queues to do jobs, and then on ctrl-C properly closes them all down: it might look something like this:
async def run_act1_forever():
# this is the async queue loop
while True:
job = await inputQueue1.get()
# do something with this incoming job
def run_activity_1(loop):
# run the async queue loop as a task
coro = loop.create_task(run_act1_forever())
return coro
def mainprogram():
loop = asyncio.get_event_loop()
act1 = run_activity_1(loop)
# also start act2, act3, etc here
try:
loop.run_forever()
except KeyboardInterrupt:
pass
finally:
act1.cancel()
# also act2.cancel(), act3.cancel(), etc
loop.close()
This all works fine. However, starting up activity 1 is actually more complex than this; it happens in three parts. Part 1 is to wait on the queue until a particular job comes in, one time; part 2 is a synchronous part which has to run in a thread with run_in_executor, one time, and then part 3 is the endless waiting on the queue for jobs as above. How do I structure this? My initial thought was:
async def run_act1_forever():
# this is the async queue loop
while True:
job = await inputQueue1.get()
# do something with this incoming job
async def run_act1_step1():
while True:
job = await inputQueue1.get()
# good, we have handled that first task; we're done
break
def run_act1_step2():
# note: this is sync, not async, so it's in a thread
# do whatever, here, and then exit when done
time.sleep(5)
def run_activity_1(loop):
# run step 1 as a task
step1 = loop.create_task(run_act1_step1())
# ERROR! See below
# now run the sync step 2 in a thread
self.loop.run_in_executor(None, run_act1_step2())
# finally, run the async queue loop as a task
coro = loop.create_task(run_act1_forever())
return coro
def mainprogram():
loop = asyncio.get_event_loop()
act1 = run_activity_1(loop)
# also start act2, act3, etc here
try:
loop.run_forever()
except KeyboardInterrupt:
pass
finally:
act1.cancel()
# also act2.cancel(), act3.cancel(), etc
loop.close()
but this does not work, because at the point where we say "ERROR!", we need to await the step1 task and we never do. We can't await it, because run_activity_1 is not an async function. So... what should I do here?
I thought about getting the Future back from calling run_act1_step1() and then using future.add_done_callback to handle running steps 2 and 3. However, if I do that, then run_activity_1() can't return the future generated by run_act1_forever(), which means that mainprogram() can't cancel that run_act1_forever() task.
I thought of generating an "empty" Future in run_activity_1() and returning that, and then making that empty Future "chain" to the Future returned by run_act1_forever(). But Python asyncio doesn't support chaining Futures.
You say that things are difficult because run_activity_1 is not an async function, but don't really detail why it can't be async.
async def run_activity_1(loop):
await run_act1_step1()
await loop.run_in_executor(None, run_act1_step2)
await run_act1_forever()
The returned coroutine won't be the same as the one returned by run_act1_forever(), but cancellation should propagate if you've got as far as executing that step.
With this change, run_activity_1 is no longer returning a task, so the invocation inside mainprogram would need to change to:
act1 = loop.create_task(run_activity_1(loop))
I think you were on the right track when you said, "I thought about getting the Future back from calling run_act1_step1() and then using future.add_done_callback to handle running steps 2 and 3." That's the logical way to structure this application. You have to manage the various returned objects correctly, but a small class solves this problem.
Here is a program similar to your second code snippet. It runs (tested with Python3.10) and handles Ctrl-C gracefully.
Python3.10 issues a deprecation warning when the function asyncio.get_event_loop() is called without a running loop, so I avoided doing that.
Activities.run() creates task1, then attaches a done_callback that starts task2 and the rest of the activities. The Activities object keeps track of task1 and task2 so they can be cancelled. The main program keeps a reference to Activities, and calls cancel_gracefully() to do the right thing, depending on how far the script progressed through the sequence of start-up activities.
Some care needs to be taken to catch the CancelledExceptions; otherwise stuff gets printed on the console when the program terminates.
The important difference between this program and your second code snippet is that this program immediately stores task1 and task2 in variables so they can be accessed later. Therefore they can be cancelled any time after their creation. The done_callback trick is used to launch all the steps in the proper order.
#! python3.10
import asyncio
import time
async def run_act1_forever():
# this is the async queue loop
while True:
await asyncio.sleep(1.0)
# job = await inputQueue1.get()
# do something with this incoming job
print("Act1 forever")
async def run_act1_step1():
while True:
await asyncio.sleep(1.0)
# job = await inputQueue1.get()
# good, we have handled that first task; we're done
break
print("act1 step1 finished")
def run_act1_step2():
# note: this is sync, not async, so it's in a thread
# do whatever, here, and then exit when done
time.sleep(5)
print("Step2 finished")
class Activities:
def __init__(self, loop):
self.loop = loop
self.task1: asyncio.Task = None
self.task2: asyncio.Task = None
def run(self):
# run step 1 as a task
self.task1 = self.loop.create_task(run_act1_step1())
self.task1.add_done_callback(self.run2)
# also start act2, act3, etc here
def run2(self, fut):
try:
if fut.exception() is not None: # do nothing if task1 failed
return
except asyncio.CancelledError: # or if it was cancelled
return
# now run the sync step 2 in a thread
self.loop.run_in_executor(None, run_act1_step2)
# finally, run the async queue loop as a task
self.task2 = self.loop.create_task(run_act1_forever())
async def cancel_gracefully(self):
if self.task2 is not None:
# in this case, task1 has already finished without error
self.task2.cancel()
try:
await self.task2
except asyncio.CancelledError:
pass
elif self.task1 is not None:
self.task1.cancel()
try:
await self.task1
except asyncio.CancelledError:
pass
# also act2.cancel(), act3.cancel(), etc
def mainprogram():
loop = asyncio.new_event_loop()
asyncio.set_event_loop(loop)
acts = Activities(loop)
loop.call_soon(acts.run)
try:
loop.run_forever()
except KeyboardInterrupt:
pass
loop.run_until_complete(acts.cancel_gracefully())
if __name__ == "__main__":
mainprogram()
You can do this with a combination of threading events and asyncio events. You'll need two events, one to signal the first item has arrived. The thread will wait on this event, so it needs to be a threading Event. You'll also need one to signal the thread is finished. Your run_act1_forever coroutine will await this, so it will need to be an asyncio Event. You can then return the task for run_act1_forever normally and cancel it as you need.
Note that when setting the asyncio event from the separate thread you'll need to use loop.call_soon_threadsafe as asyncio Events are not thread safe.
import asyncio
import time
import threading
import functools
from asyncio import Queue, AbstractEventLoop
async def run_act1_forever(inputQueue1: Queue,
thread_done_event: asyncio.Event):
await thread_done_event.wait()
print('running forever')
while True:
job = await inputQueue1.get()
async def run_act1_step1(inputQueue1: Queue,
first_item_event: threading.Event):
print('Waiting for queue item')
job = await inputQueue1.get()
print('Setting event')
first_item_event.set()
def run_act1_step2(loop: AbstractEventLoop,
first_item_event: threading.Event,
thread_done_event: asyncio.Event):
print('Waiting for event...')
first_item_event.wait()
print('Got event, processing...')
time.sleep(5)
loop.call_soon_threadsafe(thread_done_event.set)
def run_activity_1(loop):
inputQueue1 = asyncio.Queue(loop=loop)
first_item_event = threading.Event()
thread_done_event = asyncio.Event(loop=loop)
loop.create_task(run_act1_step1(inputQueue1, first_item_event))
inputQueue1.put_nowait('First item to test the code')
loop.run_in_executor(None, functools.partial(run_act1_step2,
loop,
first_item_event,
thread_done_event))
return loop.create_task(run_act1_forever(inputQueue1, thread_done_event))
def mainprogram():
loop = asyncio.new_event_loop()
act1 = run_activity_1(loop)
# also start act2, act3, etc here
try:
loop.run_forever()
except KeyboardInterrupt:
pass
finally:
act1.cancel()
# also act2.cancel(), act3.cancel(), etc
loop.close()
mainprogram()
Why FastAPI doesn't complain about the following task
app.state["my_task"] = asyncio.create_task(my_task())
not being awaited in any part of the code?
app is an instance of FastAPI() whereas app.state a simple dictionary.
I can even app.state["my_task"].cancel() in a shutdown callback.
From the asyncio docs:
When a coroutine function is called, but not awaited (e.g. coro() instead of await coro()) or the coroutine is not scheduled with asyncio.create_task(), asyncio will emit a RuntimeWarning
Thus, it is expected that, when using create_task(), no warning is emmited. This is no exclusive behavior to FastAPI. You can check it in the minimal snippet below:
import asyncio
async def task():
print("foobar")
async def main():
# task() # Emits a RuntimeWarning
# await task() # Does not emmit
x = asyncio.create_task(task()) # Doesn't either
loop = asyncio.get_event_loop()
loop.run_until_complete(main())
Edit PS: Calling the coroutine function as-is does not schedule the underlying task (and returns a coroutine object), while calling create_task() does (and returns a Task object). For more info, again, check the asyncio docs.
I'm trying to expose an event-based communication as a coroutine. Here is an example:
class Terminal:
async def start(self):
loop = asyncio.get_running_loop()
future = loop.create_future()
t = threading.Thread(target=self.run_cmd, args=future)
t.start()
return await future
def run_cmd(self, future):
time.sleep(3) # imitating doing something
future.set_result(1)
But when I run it like this:
async def main():
t = Terminal()
result = await t.start()
print(result)
asyncio.run(main())
I get the following error: RuntimeError: await wasn't used with future
Is it possible to achieve the desired behavior?
There are two issues with your code. One is that the args argument to the Thread constructor requires a sequence or iterable, so you need to write wrap the argument in a container, e.g. args=(future,). Since future is iterable (for technical reasons unrelated to this use case), args=future is not immediately rejected, but leads to the misleading error later down the line.
The other issue is that asyncio objects aren't thread-safe, so you cannot just call future.set_result from another thread. This causes the test program to hang even after fixing the first issue. The correct way to resolve the future from another thread is through the call_soon_threadsafe method on the event loop:
class Terminal:
async def start(self):
loop = asyncio.get_running_loop()
future = loop.create_future()
t = threading.Thread(target=self.run_cmd, args=(loop, future,))
t.start()
return await future
def run_cmd(self, loop, future):
time.sleep(3)
loop.call_soon_threadsafe(future.set_result, 1)
If your thread is really just calling a blocking function whose result you're interested in, consider using run_in_executor instead of manually spawning threads:
class Terminal:
async def start(self):
loop = asyncio.get_running_loop()
return await loop.run_in_executor(None, self.run_cmd)
# Executed in a different thread; `run_in_executor` submits the
# callable to a thread pool, suspends the awaiting coroutine until
# it's done, and transfers the result/exception back to asyncio.
def run_cmd(self):
time.sleep(3)
return 1
I am confused from different thread posted in different time for this topic.
Is this feature of Asyncio available with latest version(As of Dec 2019) of cx_Oracle?
I am using below code snippets which is working but not sure if this is perfect way to do async call for Oracle? Any pointer will be helpful.
import asyncio
async def sqlalchemyoracle_fetch():
conn_start_time = time()
oracle_tns_conn = 'oracle+cx_oracle://{username}:{password}#{tnsname}'
engine = create_engine(
oracle_tns_conn.format(
username=USERNAME,
password=PWD,
tnsname=TNS,
),
pool_recycle=50,
)
for x in test:
pd.read_sql(query_randomizer(x), engine)
!calling custom query_randomizer function which will execute oracle queries from the parameters passed through test which is a list
async def main():
tasks = [sqlalchemyoracle_asyncfetch()]
return await asyncio.gather(*tasks)
if __name__ == "__main__":
result = await main()
I use the cx_Oracle library but not SQLAlchemy. As of v8.2, asyncio is not supported.
This issue tracks and confirms it - https://github.com/oracle/python-cx_Oracle/issues/178.
And no, your code block does not run asynchronously, although defined using async def there is no statement in the code block that is asynchronous. To be asynchronous, your async function either needs to await another async function (that already supports async operations) or use yield to indicate a possible context switch. None of these happens in your code block.
You can try the following package which states to have implemented async support for cx_Oracle. https://pypi.org/project/cx-Oracle-async/
I have a function similar to the following:
def wrapper(fn, client):
async def helper(*args, **kwargs):
id_ = fn(*args, **kwargs)
while True:
await asyncio.sleep(60)
status = client.get_status(id_)
if status == 'OK':
break
return status
return helper
Basically it takes a function, which launches a compute job somewhere. The coroutine then asks the status of this compute job every 60 seconds and if the status is OK then it breaks from the infinite loop.
To test it I am using:
classs Test_wrapper(unittest.TestCase):
def test_wrapper(self):
client = get_client()
aio_fn = wraper(fn, client)
coro = aio_fn(arg1, arg2, arg3=arg3, arg4=arg4)
loop = asyncio.get_event_loop()
loop.run_until_complete(coro)
loop.close()
I have also tested variations of the alternatives shown in this answer by I do not get it to work. I have run the wraper outside pytest and it works.
I have tested this wrapper running the code it is suppose to run, but the tests keep failing. Do you have any clue?
No error message or exeption is displayed when it fails, it only says that it fails.