I need to run a program about 500 times with different inputs.
I'd like to use asyncio.create_subprocess_exec and want to limit the number of processes running at the same time so as not to clog up the machine.
Is there a way to set the concurrency level? For example, I'd expect something like AbstractEventLoop.set_max_tasks.
As suggested by #AndrewSvetlov, you can use an asyncio.Semaphore to enforce the limit:
async def run_program(input):
p = await asyncio.create_subprocess_exec(...)
# ... communicate with the process ...
p.terminate()
return something_useful
async def run_throttled(input, sem):
async with sem:
result = await run_program(input)
return result
LIMIT = 10
async def many_programs(inputs):
sem = asyncio.Semaphore(LIMIT)
results = await asyncio.gather(
*[run_throttled(input, sem) for input in inputs])
# ...
Related
I am planning to have an asyncio Queue based producer-consumer implementation for a processing of realtime data where sending out data in correct time order is vital. So here is the code snippet of it :
async def produce(Q, n_jobs):
for i in range(n_jobs):
print(f"Producing :{i}")
await Q.put(i)
async def consume(Q):
while True:
n = await Q.get()
print(f"Consumed :{n}")
x = do_sometask_and_return_the_result(n)
print(f"Finished :{n} and Result: {x}")
async def main(loop):
Q = asyncio.Queue(loop=loop, maxsize=3)
await asyncio.wait([produce(Q, 10), consume(Q), consume(Q), consume(Q)])
print("Done")
Here the producer produces data and puts it into the asyncio Queue. I have multiple consumers to consume and process the data. While seeing the outputs, the order is maintained while printing "Consumed :{n}" (as in 1,2,3,4... and so on) , this is completely fine. but, since the function do_sometask_and_return_the_result(n) takes variable time to return the result, the order is not maintained in the next print of n "Finished :{n}" (as in 2,1,4,3,5,...).
Is there any way to synchronize this data as I need to maintain the order of printing the results? I want to see 1,2,3,4,.. sequential prints for 'n' even after do_sometask_and_return_the_result(n).
You could use a priority queue system (using the python heapq library) to reorder your jobs after they are complete. Something like this.
# add these variables at class/global scope
priority_queue = []
current_job_id = 1
job_id_dict = {}
async def produce(Q, n_jobs):
# same as above
async def consume(Q):
while True:
n = await Q.get()
print(f"Consumed :{n}")
x = do_sometask_and_return_the_result(n)
await process_result(n, x)
async def process_result(n, x):
heappush(priority_queue, n)
job_id_dict[n] = x
while current_job_id == priority_queue[0]:
job_id = heappop(priority_queue)
print(f"Finished :{job_id} and Result: {job_id_dict[job_id]}")
current_job_id += 1
async def main(loop):
Q = asyncio.Queue(loop=loop, maxsize=3)
await asyncio.wait([produce(Q, 10), consume(Q), consume(Q), consume(Q)])
print("Done")
For more information on the heapq module: https://docs.python.org/3/library/heapq.html
I would like to stop a python asyncio task from another task and start it again when some condition in the second task happen.
Please note, than I don't want to cancel the coroutine of the first task (the state of that coroutine when it stopped should be available). Also, I don't care about the exact state the first task is in, I just want the event loop stop running the first task until told otherwise from the second.
I hope this example code helps understanding the problem:
import asyncio
async def coroutine1():
i = 0
while(True):
i += 1
print("coroutine1: " + str(i) )
await asyncio.sleep(1)
async def coroutine2(task1):
i = 0
while(True):
i += 1
if (i > 3) and (i<10):
pass #TODO: stop task1 here
else:
pass #TODO: Maybe check if task1 is running
#and start task1 again if it's not?
print("coroutine2: " + str(i) )
await asyncio.sleep(1)
async def main_coroutine():
loop = asyncio.get_event_loop()
task1 = loop.create_task(coroutine1())
task2 = loop.create_task(coroutine2(task1))
done, pending = await asyncio.wait(
[task1, task2]
, return_when=asyncio.FIRST_COMPLETED,)
loop = asyncio.get_event_loop()
loop.run_until_complete(main_coroutine())
loop.close()
I would like to stop a python asyncio task from another task and start it again when some condition in the second task happen.
I assume you control the task creation, but don't want to touch the implementation of the coroutine. In your case, you control coroutine2 and main_coroutine, but not the insides of coroutine1.
In that case you can wrap the coroutine in a an __await__ that, instead of the normal yield from loop, checkes your stopped flag and waits for a future that tells it when to resume.
class Stoppable:
def __init__(self, coro):
self._coro_iter = coro.__await__()
self._stopped = None
def __await__(self):
while True:
while self._stopped:
print('awaiting stopped')
yield from self._stopped.__await__()
try:
v = next(self._coro_iter)
except StopIteration as e:
return v
yield v
def stop(self):
loop = asyncio.get_event_loop()
self._stopped = loop.create_future()
def start(self):
if self._stopped is not None:
self._stopped.set_result(None)
self._stopped = None
You can use the wrapper to modify coroutine2 to stop and resume the execution of coroutine1 at will:
async def coroutine2(s):
i = 0
while True:
i += 1
if i == 3:
print('stopping coroutine1')
s.stop()
elif i == 10:
print('restarting coroutine1')
s.start()
print("coroutine2: " + str(i) )
await asyncio.sleep(1)
async def main_coroutine():
loop = asyncio.get_event_loop()
s = Stoppable(coroutine1())
fut1 = asyncio.ensure_future(s)
task2 = loop.create_task(coroutine2(s))
done, pending = await asyncio.wait(
[fut1, task2], return_when=asyncio.FIRST_COMPLETED)
The way wrapper works is by unrolling the loop inherent in yield from. For example, to just delegate __await__ to another coroutine, one would write:
def __await__(self):
yield from self._coro_iter
Written like this, you can't implement stopping because the yield from contains an implicit loop that yields all the values produced by the underlying iterator - something like:
def __await__(self):
while True:
try:
v = next(self._coro_iter)
except StopIteration as e:
return e.value
yield v
Taken like this, it is easy enough to add an if that checks for _stopped at each iteration pass, meaning each time we're resumed by the event loop. The remaining hurdle is that one cannot just busy-loop until _stopped is rescinded - we must yield something else to allow the event loop to resume running other coroutines. Fortunately that is easily achieved by making _stopped a future, and yielding from the future. When the future's result is set, we will be automatically resumed and continue executing the wrapped coroutine.
It seems it can't be done.
It's possible to cancel an ongoing task with task1.cancel() and it's possible to create a new task with asyncio.get_event_loop().create_task(newTask).
It's also possible to get the coroutine of a running task with task1._coro but if we try to create a task again with a previously scheduled coroutine we will get a RuntimeError exception. This the discussion where they decided it: https://bugs.python.org/issue25887
Finally, a possible way of accomplishing the desire effect is using a asyncio.Queue object:
import asyncio
async def coroutine1(stop_queue):
i = 0
while(True):
if stop_queue.empty(): #if the queue is empty keep working.
i += 1
print("coroutine1: " + str(i) )
await asyncio.sleep(1)
async def coroutine2(stop_queue):
i = 0
while(True):
i += 1
if i == 3:
await stop_queue.put("whatever..") #put something in the queue
if i == 11:
await stop_queue.get() #take something from the queue
print("coroutine2: " + str(i) )
await asyncio.sleep(1)
async def main_coroutine():
stop_queue = asyncio.Queue()
done, pending = await asyncio.wait(
[coroutine1(stop_queue), coroutine2(stop_queue)]
, return_when=asyncio.ALL_COMPLETED,)
loop = asyncio.get_event_loop()
loop.run_until_complete(main_coroutine())
loop.close()
I have been trying all kinds of things to be able to use an asyncio loop inside another asyncio loop. Most of the time my test just end in errors, such as:
RuntimeError: This event loop is already running
My example code below is just the base test I started with, so you can see the basics of what I am trying to do. I tried so many things after this test, it was just too confusing, so I figured I should keep it simple when asking for help. If anyone can point me in the right direction, that would be great. Thank you for your time!
import asyncio
async def fetch(data):
message = 'Hey {}!'.format(data)
other_data = ['image_a.com', 'image_b.com', 'image_c.com']
images = sub_run(other_data)
return {'message' : message, 'images' : images}
async def bound(sem, data):
async with sem:
r = await fetch(data)
return r
async def build(dataset):
tasks = []
sem = asyncio.Semaphore(400)
for data in dataset:
task = asyncio.ensure_future(bound(sem, data))
tasks.append(task)
r = await asyncio.gather(*tasks)
return r
def run(dataset):
loop = asyncio.get_event_loop()
future = asyncio.ensure_future(build(dataset))
responses = loop.run_until_complete(future)
loop.close()
return responses
async def sub_fetch(data):
image = 'https://{}'.format(data)
return image
async def sub_bound(sem, data):
async with sem:
r = await sub_fetch(data)
return r
async def sub_build(dataset):
tasks = []
sem = asyncio.Semaphore(400)
for data in dataset:
task = asyncio.ensure_future(sub_bound(sem, data))
tasks.append(task)
r = await asyncio.gather(*tasks)
return r
def sub_run(dataset):
loop = asyncio.get_event_loop()
future = asyncio.ensure_future(sub_build(dataset))
responses = loop.run_until_complete(future)
loop.close()
return responses
if __name__ == '__main__':
dataset = ['Joe', 'Bob', 'Zoe', 'Howard']
responses = run(dataset)
print (responses)
Running loop.run_until_compete inside a running event loop would block the outer loop, thus defeating the purpose of using asyncio. Because of that, asyncio event loops aren't recursive, and one shouldn't need to run them recursively. Instead of creating an inner event loop, await a task on the existing one.
In your case, remove sub_run and simply replace its usage:
images = sub_run(other_data)
with:
images = await sub_build(other_data)
And it will work just fine, running the sub-coroutines and not continuing with the outer coroutine until the inner one is complete, as you likely intended from the sync code.
I have 2 functions: The first one, def_a, is an asynchronous function and the second one is def_b which is a regular function and called with the result of def_a as a callback with the add_done_callback function.
My code looks like this:
import asyncio
def def_b(result):
next_number = result.result()
# some work on the next_number
print(next_number + 1)
async def def_a(number):
await some_async_work(number)
return number + 1
loop = asyncio.get_event_loop()
task = asyncio.ensure_future(def_a(1))
task.add_done_callback(def_b)
response = loop.run_until_complete(task)
loop.close()
And it's work perfectly.
The problem began when also the second function, def_b, became asynchronous. Now it looks like this:
async def def_b(result):
next_number = result.result()
# some asynchronous work on the next_number
print(next_number + 1)
But now I can not provide it to the add_done_callback function, because it's not a regular function.
My question is- Is it possible and how can I provide def_b to the add_done_callback function if def_b is asynchronous?
add_done_callback is considered a "low level" interface. When working with coroutines, you can chain them in many ways, for example:
import asyncio
async def my_callback(result):
print("my_callback got:", result)
return "My return value is ignored"
async def coro(number):
await asyncio.sleep(number)
return number + 1
async def add_success_callback(fut, callback):
result = await fut
await callback(result)
return result
loop = asyncio.get_event_loop()
task = asyncio.ensure_future(coro(1))
task = add_success_callback(task, my_callback)
response = loop.run_until_complete(task)
print("response:", response)
loop.close()
Keep in mind add_done_callback will still call the callback if your future raises an exception (but calling result.result() will raise it).
This only works for one future job, if you have multiple async jobs, they will blocks each other, a better way is using asyncio.as_completed() to iterate future list:
import asyncio
async def __after_done_callback(future_result):
# await for something...
pass
async def __future_job(number):
await some_async_work(number)
return number + 1
loop = asyncio.get_event_loop()
tasks = [asyncio.ensure_future(__future_job(x)) for x in range(100)] # create 100 future jobs
for f in asyncio.as_completed(tasks):
result = await f
await __after_done_callback(result)
loop.close()
You can try the aiodag library. It's a very lightweight wrapper around asyncio that abstracts away some of the async plumbing that you usually have to think about. From this example you won't be able to tell that things are running asynchronously since it's just 1 task that depends on another, but it is all running async.
import asyncio
from aiodag import task
#task
async def def_b(result):
# some asynchronous work on the next_number
print(result + 1)
#task
async def def_a(number):
await asyncio.sleep(number)
return number + 1
async def main():
a = def_a(1)
b = def_b(a) # this makes task b depend on task a
return await b
loop = asyncio.get_event_loop()
asyncio.set_event_loop(loop)
response = loop.run_until_complete(main())
I have a program with one producer and two slow consumers and I'd like to rewrite it with coroutines in such way that each consumer will handle only last value (i.e. skip new values generated during processing the old ones) produced for it (I used threads and threading.Queue() but with it blocks on put(), cause the queue will be full most of the time).
After reading answer to this question I decided to use asyncio.Event and asyncio.Queue. I wrote this prototype program:
import asyncio
async def l(event, q):
h = 1
while True:
# ready
event.set()
# get value to process
a = await q.get()
# process it
print(a * h)
h *= 2
async def m(event, q):
i = 1
while True:
# pass element to consumer, when it's ready
if event.is_set():
await q.put(i)
event.clear()
# produce value
i += 1
el = asyncio.get_event_loop()
ev = asyncio.Event()
qu = asyncio.Queue(2)
tasks = [
asyncio.ensure_future(l(ev, qu)),
asyncio.ensure_future(m(ev, qu))
]
el.run_until_complete(asyncio.gather(*tasks))
el.close()
and I have noticed that l coroutine blocks on q.get() line and doesn't print anything.
It works as I expect after adding asyncio.sleep() in both (I get 1,11,21,...):
import asyncio
import time
async def l(event, q):
h = 1
a = 1
event.set()
while True:
# await asyncio.sleep(1)
a = await q.get()
# process it
await asyncio.sleep(1)
print(a * h)
event.set()
async def m(event, q):
i = 1
while True:
# pass element to consumer, when it's ready
if event.is_set():
await q.put(i)
event.clear()
await asyncio.sleep(0.1)
# produce value
i += 1
el = asyncio.get_event_loop()
ev = asyncio.Event()
qu = asyncio.Queue(2)
tasks = [
asyncio.ensure_future(l(ev, qu)),
asyncio.ensure_future(m(ev, qu))
]
el.run_until_complete(asyncio.gather(*tasks))
el.close()
...but I'm looking for solution without it.
Why is it so? How can I fix it? I think I cannot call await l() from m as both of them have states (in original program the first draws solution with PyGame and the second plots results).
The code is not working as expected as the task running the m function is never stopped. The task will continue increment i in the case that event.is_set() == False. Because this task is never suspended, the task running function l will never be called. Therefore, you need a way to suspend the task running function m. One way of suspending is awaiting another coroutine, that is the reason why a asyncio.sleep works as expected.
I think the following code will work as you expect. The LeakyQueue will ensure that only the last value from the producer will be processed by the consumer. As the complexity is very symmetric, the consumer will consume all values produced by the producer. If you increase the delay argument, you can simulate that the consumer only processes the last value created by the producer.
import asyncio
class LeakyQueue(asyncio.Queue):
async def put(self, item):
if self.full():
await self.get()
await super().put(item)
async def consumer(queue, delay=0):
h = 1
while True:
a = await queue.get()
if delay:
await asyncio.sleep(delay)
print ('consumer', a)
h += 2
async def producer(queue):
i = 1
while True:
await asyncio.ensure_future(queue.put(i))
print ('producer', i)
i += 1
loop = asyncio.get_event_loop()
queue = LeakyQueue(maxsize=1)
tasks = [
asyncio.ensure_future(consumer(queue, 0)),
asyncio.ensure_future(producer(queue))
]
loop.run_until_complete(asyncio.gather(*tasks))