There is a global list to store data. Different async functions maybe add or remove value from it.
Example:
a = [] # List[Connection]
async def foo():
for v in a:
await v.send('msg')
async def bar():
await SomeAsyncFunc()
a.pop(0)
Both foo and bar will give up the control to let other coroutines run, so in foo, it is not safe to remove value from the list.
The following example shows how to use the lock for this:
Create a connection manager:
import asyncio
class ConnectionsManager:
def __init__(self, timeout=5):
self.timeout = timeout
self._lock = asyncio.Lock()
self._connections = []
async def __aenter__(self):
await asyncio.wait_for(self._lock.acquire(), timeout=self.timeout)
return self._connections
async def __aexit__(self, *exc):
self._lock.release()
The timeout is a security measure to break bugs with circular waits.
The manager can be used as follows:
async def foo():
for _ in range(10):
async with cm as connections:
# do stuff with connection
await asyncio.sleep(0.25)
connections.append('foo')
async def bar():
for _ in range(5):
async with cm as connections:
# do stuff with connection
await asyncio.sleep(0.5)
if len(connections) > 1:
connections.pop()
else:
connections.append('bar')
cm = ConnectionsManager()
t1 = asyncio.create_task(foo())
t2 = asyncio.create_task(bar())
await t1
await t2
async with cm as connections:
print(connections)
Note, that you could also be more explicit with connections here:
async def foo(cm):
...
async def bar(cm):
...
Just to make a comment why being explicit is so beneficial in contrast to globals. At some point you may need to write unit tests for your code, where you will need to specify all inputs to your functions/methods. Forgetting conditions on implicit inputs to your function (used globals) can easily result in untested states. For example your bar coroutine expects an element in the list a and will break if it is empty. Most of the time it might do the right thing, but one day in production...
I am connecting to aioredis from __init__ (I do not want to move it out since this means I have to some extra major changes). How can I wait for aioredis connection task in below __init__ example code and have it print self.sub and self.pub object? Currently it gives an error saying
abc.py:42> exception=AttributeError("'S' object has no attribute
'pub'")
I do see redis connections created and coro create_connetion done.
Is there a way to call blocking asyncio calls from __init__. If I replace asyncio.wait with asyncio.run_until_complete I get an error that roughly says
loop is already running.
asyncio.gather is
import sys, json
from addict import Dict
import asyncio
import aioredis
class S():
def __init__(self, opts):
print(asyncio.Task.all_tasks())
task = asyncio.wait(asyncio.create_task(self.create_connection()), return_when="ALL_COMPLETED")
print(asyncio.Task.all_tasks())
print(task)
print(self.pub, self.sub)
async def receive_message(self, channel):
while await channel.wait_message():
message = await channel.get_json()
await asyncio.create_task(self.callback_loop(Dict(json.loads(message))))
async def run_s(self):
asyncio.create_task(self.listen())
async def callback_loop(msg):
print(msg)
self.callback_loop = callback_loop
async def create_connection(self):
self.pub = await aioredis.create_redis("redis://c8:7070/0", password="abc")
self.sub = await aioredis.create_redis("redis://c8:7070/0", password="abc")
self.db = await aioredis.create_redis("redis://c8:7070/0", password="abc")
self.listener = await self.sub.subscribe(f"abc")
async def listen(self):
self.tsk = asyncio.ensure_future(self.receive_message(self.listener[0]))
await self.tsk
async def periodic(): #test function to show current tasks
number = 5
while True:
await asyncio.sleep(number)
print(asyncio.Task.all_tasks())
async def main(opts):
loop.create_task(periodic())
s = S(opts)
print(s.pub, s.sub)
loop.create_task(s.run_s())
if __name__ == "__main__":
loop = asyncio.get_event_loop()
main_task = loop.create_task(main(sys.argv[1:]))
loop.run_forever() #I DONT WANT TO MOVE THIS UNLESS IT IS NECESSARY
I think what you want to do is to make sure the function create_connections runs to completion BEFORE the S constructor. A way to do that is to rearrange your code a little bit. Move the create_connections function outside the class:
async def create_connection():
pub = await aioredis.create_redis("redis://c8:7070/0", password="abc")
sub = await aioredis.create_redis("redis://c8:7070/0", password="abc")
db = await aioredis.create_redis("redis://c8:7070/0", password="abc")
listener = await self.sub.subscribe(f"abc")
return pub, sub, db, listener
Now await that function before constructing S. So your main function becomes:
async def main(opts):
loop.create_task(periodic())
x = await create_connections()
s = S(opts, x) # pass the result of create_connections to S
print(s.pub, s.sub)
loop.create_task(s.run_s())
Now modify the S constructor to receive the objects created:
def __init__(self, opts, x):
self.pub, self.sub, self.db, self.listener = x
I'm not sure what you're trying to do with the return_when argument and the call to asyncio.wait. The create_connections function doesn't launch a set of parallel tasks, but rather awaits each of the calls before moving on to the next one. Perhaps you could improve performance by running the four calls in parallel but that's a different question.
I need to suspend a coroutine until a condition is met. Currently, I have:
class Awaiter:
def __init__(self):
self.ready = False
def __await__(self):
while not self.ready:
yield
And the caller code:
await awaiter
This works, but it requires boilerplate code. Is it necessary boilerplate or is there a special syntax to await on a predicate, such as:
await condition
which would yield until condition is false?
At the asyncio package there is a builtin Condition object that you can use.
An asyncio condition primitive can be used by a task to wait for some event to happen and then get exclusive access to a shared resource.
How to use the condition (from the same source):
cond = asyncio.Condition()
# The preferred way to use a Condition is an async with statement
async with cond:
await cond.wait()
# It can also be used as follow
await cond.acquire()
try:
await cond.wait()
finally:
cond.release()
A code example:
import asyncio
cond = asyncio.Condition()
async def func1():
async with cond:
print('It\'s look like I will need to wait')
await cond.wait()
print('Now it\'s my turn')
async def func2():
async with cond:
print('Notifying....')
cond.notify()
print('Let me finish first')
# Main function
async def main(loop):
t1 = loop.create_task(func1())
t2 = loop.create_task(func2())
await asyncio.wait([t1, t2])
if __name__ == '__main__':
l = asyncio.get_event_loop()
l.run_until_complete(main(l))
l.close()
This will results with:
It's look like I will need to wait
Notifying....
Let me finish first
Now it's my turn
An alternative way is to use the asyncio.Event.
import asyncio
event = asyncio.Event()
async def func1():
print('It\'s look like I will need to wait')
await event.wait()
print('Now it\'s my turn')
async def func2():
print('Notifying....')
event.set()
print('Let me finish first')
It will have the same results as the Condition code example.
Is it possible to run an async while loop independently of another one?
Instead of the actual code I isolated the issue I am having in the following example code
import asyncio, time
class Time:
def __init__(self):
self.start_time = 0
async def dates(self):
while True:
t = time.time()
if self.start_time == 0:
self.start_time = t
yield t
await asyncio.sleep(1)
async def printer(self):
while True:
print('looping') # always called
await asyncio.sleep(self.interval)
async def init(self):
async for i in self.dates():
if i == self.start_time:
self.interval = 3
await self.printer()
print(i) # Never Called
loop = asyncio.get_event_loop()
t = Time()
loop.run_until_complete(t.init())
Is there a way to have the print function run independently so print(i) gets called each time?
What it should do is print(i) each second and every 3 seconds call self.printer(i)
Essentially self.printer is a separate task that does not need to be called very often, only every x seconds(in this case 3).
In JavaScript the solution is to do something like so
setInterval(printer, 3000);
EDIT: Ideally self.printer would also be able to be canceled / stopped if a condition or stopping function is called
The asyncio equivalent of JavaScript's setTimeout would be asyncio.ensure_future:
import asyncio
async def looper():
for i in range(1_000_000_000):
print(f'Printing {i}')
await asyncio.sleep(0.5)
async def main():
print('Starting')
future = asyncio.ensure_future(looper())
print('Waiting for a few seconds')
await asyncio.sleep(4)
print('Cancelling')
future.cancel()
print('Waiting again for a few seconds')
await asyncio.sleep(2)
print('Done')
if __name__ == '__main__':
asyncio.get_event_loop().run_until_complete(main())
You'd want to register your self.printer() coroutine as a separate task; pass it to asyncio.ensure_future() rather than await on it directly:
asyncio.ensure_future(self.printer())
By passing the coroutine to asyncio.ensure_future(), you put it on the list of events that the loop switches between as each awaits on further work to be completed.
With that change, your test code outputs:
1516819094.278697
looping
1516819095.283424
1516819096.283742
looping
1516819097.284152
# ... etc.
Tasks are the asyncio equivalent of threads in a multithreading scenario.
I'm migrating from tornado to asyncio, and I can't find the asyncio equivalent of tornado's PeriodicCallback. (A PeriodicCallback takes two arguments: the function to run and the number of milliseconds between calls.)
Is there such an equivalent in asyncio?
If not, what would be the cleanest way to implement this without running the risk of getting a RecursionError after a while?
For Python versions below 3.5:
import asyncio
#asyncio.coroutine
def periodic():
while True:
print('periodic')
yield from asyncio.sleep(1)
def stop():
task.cancel()
loop = asyncio.get_event_loop()
loop.call_later(5, stop)
task = loop.create_task(periodic())
try:
loop.run_until_complete(task)
except asyncio.CancelledError:
pass
For Python 3.5 and above:
import asyncio
async def periodic():
while True:
print('periodic')
await asyncio.sleep(1)
def stop():
task.cancel()
loop = asyncio.get_event_loop()
loop.call_later(5, stop)
task = loop.create_task(periodic())
try:
loop.run_until_complete(task)
except asyncio.CancelledError:
pass
When you feel that something should happen "in background" of your asyncio program, asyncio.Task might be good way to do it. You can read this post to see how to work with tasks.
Here's possible implementation of class that executes some function periodically:
import asyncio
from contextlib import suppress
class Periodic:
def __init__(self, func, time):
self.func = func
self.time = time
self.is_started = False
self._task = None
async def start(self):
if not self.is_started:
self.is_started = True
# Start task to call func periodically:
self._task = asyncio.ensure_future(self._run())
async def stop(self):
if self.is_started:
self.is_started = False
# Stop task and await it stopped:
self._task.cancel()
with suppress(asyncio.CancelledError):
await self._task
async def _run(self):
while True:
await asyncio.sleep(self.time)
self.func()
Let's test it:
async def main():
p = Periodic(lambda: print('test'), 1)
try:
print('Start')
await p.start()
await asyncio.sleep(3.1)
print('Stop')
await p.stop()
await asyncio.sleep(3.1)
print('Start')
await p.start()
await asyncio.sleep(3.1)
finally:
await p.stop() # we should stop task finally
if __name__ == '__main__':
loop = asyncio.get_event_loop()
loop.run_until_complete(main())
Output:
Start
test
test
test
Stop
Start
test
test
test
[Finished in 9.5s]
As you see on start we just start task that calls some functions and sleeps some time in endless loop. On stop we just cancel that task. Note, that task should be stopped at the moment program finished.
One more important thing that your callback shouldn't take much time to be executed (or it'll freeze your event loop). If you're planning to call some long-running func, you possibly would need to run it in executor.
A variant that may be helpful: if you want your recurring call to happen every n seconds instead of n seconds between the end of the last execution and the beginning of the next, and you don't want calls to overlap in time, the following is simpler:
async def repeat(interval, func, *args, **kwargs):
"""Run func every interval seconds.
If func has not finished before *interval*, will run again
immediately when the previous iteration finished.
*args and **kwargs are passed as the arguments to func.
"""
while True:
await asyncio.gather(
func(*args, **kwargs),
asyncio.sleep(interval),
)
And an example of using it to run a couple tasks in the background:
async def f():
await asyncio.sleep(1)
print('Hello')
async def g():
await asyncio.sleep(0.5)
print('Goodbye')
async def main():
t1 = asyncio.ensure_future(repeat(3, f))
t2 = asyncio.ensure_future(repeat(2, g))
await t1
await t2
loop = asyncio.get_event_loop()
loop.run_until_complete(main())
There is no built-in support for periodic calls, no.
Just create your own scheduler loop that sleeps and executes any tasks scheduled:
import math, time
async def scheduler():
while True:
# sleep until the next whole second
now = time.time()
await asyncio.sleep(math.ceil(now) - now)
# execute any scheduled tasks
async for task in scheduled_tasks(time.time()):
await task()
The scheduled_tasks() iterator should produce tasks that are ready to be run at the given time. Note that producing the schedule and kicking off all the tasks could in theory take longer than 1 second; the idea here is that the scheduler yields all tasks that should have started since the last check.
Alternative version with decorator for python 3.7
import asyncio
import time
def periodic(period):
def scheduler(fcn):
async def wrapper(*args, **kwargs):
while True:
asyncio.create_task(fcn(*args, **kwargs))
await asyncio.sleep(period)
return wrapper
return scheduler
#periodic(2)
async def do_something(*args, **kwargs):
await asyncio.sleep(5) # Do some heavy calculation
print(time.time())
if __name__ == '__main__':
asyncio.run(do_something('Maluzinha do papai!', secret=42))
Based on #A. Jesse Jiryu Davis answer (with #Torkel Bjørnson-Langen and #ReWrite comments) this is an improvement which avoids drift.
import time
import asyncio
#asyncio.coroutine
def periodic(period):
def g_tick():
t = time.time()
count = 0
while True:
count += 1
yield max(t + count * period - time.time(), 0)
g = g_tick()
while True:
print('periodic', time.time())
yield from asyncio.sleep(next(g))
loop = asyncio.get_event_loop()
task = loop.create_task(periodic(1))
loop.call_later(5, task.cancel)
try:
loop.run_until_complete(task)
except asyncio.CancelledError:
pass
This solution uses the decoration concept from Fernando José Esteves de Souza, the drifting workaround from Wojciech Migda and a superclass in order to generate most elegant code as possible to deal with asynchronous periodic functions.
Without threading.Thread
The solution is comprised of the following files:
periodic_async_thread.py with the base class for you to subclass
a_periodic_thread.py with an example subclass
run_me.py with an example instantiation and run
The PeriodicAsyncThread class in the file periodic_async_thread.py:
import time
import asyncio
import abc
class PeriodicAsyncThread:
def __init__(self, period):
self.period = period
def periodic(self):
def scheduler(fcn):
async def wrapper(*args, **kwargs):
def g_tick():
t = time.time()
count = 0
while True:
count += 1
yield max(t + count * self.period - time.time(), 0)
g = g_tick()
while True:
# print('periodic', time.time())
asyncio.create_task(fcn(*args, **kwargs))
await asyncio.sleep(next(g))
return wrapper
return scheduler
#abc.abstractmethod
async def run(self, *args, **kwargs):
return
def start(self):
asyncio.run(self.run())
An example of a simple subclass APeriodicThread in the file a_periodic_thread.py:
from periodic_async_thread import PeriodicAsyncThread
import time
import asyncio
class APeriodicThread(PeriodicAsyncThread):
def __init__(self, period):
super().__init__(period)
self.run = self.periodic()(self.run)
async def run(self, *args, **kwargs):
await asyncio.sleep(2)
print(time.time())
Instantiating and running the example class in the file run_me.py:
from a_periodic_thread import APeriodicThread
apt = APeriodicThread(2)
apt.start()
This code represents an elegant solution that also mitigates the time drift problem of other solutions. The output is similar to:
1642711285.3898764
1642711287.390698
1642711289.3924973
1642711291.3920736
With threading.Thread
The solution is comprised of the following files:
async_thread.py with the canopy asynchronous thread class.
periodic_async_thread.py with the base class for you to subclass
a_periodic_thread.py with an example subclass
run_me.py with an example instantiation and run
The AsyncThread class in the file async_thread.py:
from threading import Thread
import asyncio
import abc
class AsyncThread(Thread):
def __init__(self, *args, **kwargs) -> None:
super().__init__(*args, **kwargs)
#abc.abstractmethod
async def async_run(self, *args, **kwargs):
pass
def run(self, *args, **kwargs):
# loop = asyncio.new_event_loop()
# asyncio.set_event_loop(loop)
# loop.run_until_complete(self.async_run(*args, **kwargs))
# loop.close()
asyncio.run(self.async_run(*args, **kwargs))
The PeriodicAsyncThread class in the file periodic_async_thread.py:
import time
import asyncio
from .async_thread import AsyncThread
class PeriodicAsyncThread(AsyncThread):
def __init__(self, period, *args, **kwargs):
self.period = period
super().__init__(*args, **kwargs)
self.async_run = self.periodic()(self.async_run)
def periodic(self):
def scheduler(fcn):
async def wrapper(*args, **kwargs):
def g_tick():
t = time.time()
count = 0
while True:
count += 1
yield max(t + count * self.period - time.time(), 0)
g = g_tick()
while True:
# print('periodic', time.time())
asyncio.create_task(fcn(*args, **kwargs))
await asyncio.sleep(next(g))
return wrapper
return scheduler
An example of a simple subclass APeriodicThread in the file a_periodic_thread.py:
import time
from threading import current_thread
from .periodic_async_thread import PeriodicAsyncThread
import asyncio
class APeriodicAsyncTHread(PeriodicAsyncThread):
async def async_run(self, *args, **kwargs):
print(f"{current_thread().name} {time.time()} Hi!")
await asyncio.sleep(1)
print(f"{current_thread().name} {time.time()} Bye!")
Instantiating and running the example class in the file run_me.py:
from .a_periodic_thread import APeriodicAsyncTHread
a = APeriodicAsyncTHread(2, name = "a periodic async thread")
a.start()
a.join()
This code represents an elegant solution that also mitigates the time drift problem of other solutions. The output is similar to:
a periodic async thread 1643726990.505269 Hi!
a periodic async thread 1643726991.5069854 Bye!
a periodic async thread 1643726992.506919 Hi!
a periodic async thread 1643726993.5089169 Bye!
a periodic async thread 1643726994.5076022 Hi!
a periodic async thread 1643726995.509422 Bye!
a periodic async thread 1643726996.5075526 Hi!
a periodic async thread 1643726997.5093904 Bye!
a periodic async thread 1643726998.5072556 Hi!
a periodic async thread 1643726999.5091035 Bye!
For multiple types of scheduling I'd recommend APSScheduler which has asyncio support.
I use it for a simple python process I can fire up using docker and just runs like a cron executing something weekly, until I kill the docker/process.
This is what I did to test my theory of periodic call backs using asyncio. I don't have experience using Tornado, so I'm not sure exactly how the periodic call backs work with it. I am used to using the after(ms, callback) method in Tkinter though, and this is what I came up with. While True: Just looks ugly to me even if it is asynchronous (more so than globals). The call_later(s, callback, *args) method uses seconds not milliseconds though.
import asyncio
my_var = 0
def update_forever(the_loop):
global my_var
print(my_var)
my_var += 1
# exit logic could be placed here
the_loop.call_later(3, update_forever, the_loop) # the method adds a delayed callback on completion
event_loop = asyncio.get_event_loop()
event_loop.call_soon(update_forever, event_loop)
event_loop.run_forever()