Asynchronous method call in Python?

Something like:

import threading

thr = threading.Thread(target=foo, args=(), kwargs={})
thr.start() # Will run "foo"
....
thr.is_alive() # Will return whether foo is running currently
....
thr.join() # Will wait till "foo" is done

See the documentation at https://docs.python.org/library/threading.html for more details.

You can use the multiprocessing module added in Python 2.6. You can use pools of processes and then get results asynchronously with:

apply_async(func[, args[, kwds[, callback]]])

E.g.:

from multiprocessing import Pool

def f(x):
    return x*x

if __name__ == '__main__':
    pool = Pool(processes=1)              # Start a worker processes.
    result = pool.apply_async(f, [10], callback) # Evaluate "f(10)" asynchronously calling callback when finished.

This is only one alternative. This module provides lots of facilities to achieve what you want. Also it will be really easy to make a decorator from this.

It's not in the language core, but a very mature library that does what you want is Twisted. It introduces the Deferred object, which you can attach callbacks or error handlers ("errbacks") to. A Deferred is basically a "promise" that a function will have a result eventually.

Is there any reason not to use threads? You can use the threading class. Instead of finished() function use the isAlive(). The result() function could join() the thread and retrieve the result. And, if you can, override the run() and __init__ functions to call the function specified in the constructor and save the value somewhere to the instance of the class.

The native Python way for asynchronous calls in 2021 with Python 3.9 suitable also for Jupyter / Ipython Kernel

Camabeh's answer is the way to go since Python 3.3.

async def display_date(loop):
    end_time = loop.time() + 5.0
    while True:
        print(datetime.datetime.now())
        if (loop.time() + 1.0) >= end_time:
            break
        await asyncio.sleep(1)


loop = asyncio.get_event_loop()
# Blocking call which returns when the display_date() coroutine is done
loop.run_until_complete(display_date(loop))
loop.close()

This will work in Jupyter Notebook / Jupyter Lab but throw an error:

RuntimeError: This event loop is already running

Due to Ipython's usage of event loops we need something called nested asynchronous loops which is not yet implemented in Python. Luckily there is nest_asyncio to deal with the issue. All you need to do is:

!pip install nest_asyncio # use ! within Jupyter Notebook, else pip install in shell
import nest_asyncio
nest_asyncio.apply()

(Based on this thread)

Only when you call loop.close() it throws another error as it probably refers to Ipython's main loop.

RuntimeError: Cannot close a running event loop

I'll update this answer as soon as someone answered to this github issue.

The newer asyncio running method in Python 3.7 and later is using asyncio.run() instead of creating loop and calling loop.run_until_complete() as well as closing it:

import asyncio
import datetime

async def display_date(delay):
    loop = asyncio.get_running_loop()
    end_time = loop.time() + delay
    while True:
        print("Blocking...", datetime.datetime.now())
        await asyncio.sleep(1)
        if loop.time() > end_time:
            print("Done.")
            break


asyncio.run(display_date(5))

You can use process. If you want to run it forever use while (like networking) in you function:

from multiprocessing import Process
def foo():
    while 1:
        # Do something

p = Process(target = foo)
p.start()

if you just want to run it one time, do like that:

from multiprocessing import Process
def foo():
    # Do something

p = Process(target = foo)
p.start()
p.join()