How to use async/await in python 3.5+

Question

I was trying to explain an example of async programming in python but I failed. Here is my code.

import asyncio
import time

async def asyncfoo(t):
    time.sleep(t)
    print("asyncFoo")


loop = asyncio.get_event_loop()
loop.run_until_complete(asyncfoo(10)) # I think Here is the problem
print("Foo")
loop.close()

My expectation is that I would see:

Foo
asyncFoo

With a wait of 10s before asyncFoo was displayed.

But instead I got nothing for 10s, and then they both displayed.

What am I doing wrong, and how can I explain it?

I don't think it is fair to put this question on hold. He clearly says he wants to "Foo" to be printed before "asyncFoo". — Eddie
– Eddie, Commented Dec 22, 2016 at 13:01
FWIW, time.sleep is also blocking. Async is useful for resuming execution while waiting for IO, not blocking the thread. — Wayne Werner
– Wayne Werner, Commented Dec 22, 2016 at 13:01
You might wanna use asyncio.sleep(10) instead. Also please note loop.run_until_complete is a blocking one, so you might wanna have two async functions, one for the "slow foo" and one for the "fast foo". I wanted to post a complete answer but unfortunately somebody has put this question on hold. — Eddie
– Eddie, Commented Dec 22, 2016 at 13:06

Udi · Accepted Answer · 2016-12-22 19:41:01Z

11

run_until_complete will block until asyncfoo is done. Instead, you would need two coroutines executed in the loop. Use asyncio.gather to easily start more than one coroutine with run_until_complete.

Here is a an example:

import asyncio


async def async_foo():
    print("asyncFoo1")
    await asyncio.sleep(3)
    print("asyncFoo2")


async def async_bar():
    print("asyncBar1")
    await asyncio.sleep(1)
    print("asyncBar2")


loop = asyncio.get_event_loop()
loop.run_until_complete(asyncio.gather(async_foo(), async_bar()))
loop.close()

answered Dec 22, 2016 at 19:41

Udi

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Comments

songololo · Accepted Answer · 2017-01-05 23:31:35Z

2

Your expectation would work in contexts where you run your coroutine as a Task independent of the flow of the code. Another situation where it would work is if you are running multiple coroutines side-by-side, in which case the event-loop will juggle the code execution from await to await statement.

Within the context of your example, you can achieve your anticipated behaviour by wrapping your coroutine in a Task object, which will continue-on in the background without holding up the remainder of the code in the code-block from whence it is called.

For example.

import asyncio

async def asyncfoo(t):
    await asyncio.sleep(t)
    print("asyncFoo")

async def my_app(t):
    my_task = asyncio.ensure_future(asyncfoo(t))
    print("Foo")
    await asyncio.wait([my_task])

loop = asyncio.get_event_loop()
loop.run_until_complete(my_app(10))
loop.close()

Note that you should use asyncio.sleep() instead of the time module.

edited Jan 5, 2017 at 23:31

answered Dec 22, 2016 at 17:02

songololo

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3 Comments

Rahul Over a year ago

it prints foo but fails to print asyncfoo.

songololo Over a year ago

The event loop is exiting before the task completes. One way to keep the event loop open is to use loop.run_forever(), another way is to assign the task to a variable, e.g. my_task_var and then wait for the task to finish using await asyncio.wait(my_task_var). In this case, await the task variable at a location that doesn't block your code execution, e.g. Place it after the print("Foo") statement.

songololo Over a year ago

@Scripting.FileSystemObject updated answer with version that now works and exits automatically. (Have been away from a computer for a few weeks...)

Matthew Wilcoxson · Accepted Answer · 2016-12-22 12:29:23Z

-1

run_until_complete is blocking. So, even if it'll happen in 10 seconds, it will wait for it. After it's completed, the other print occurs.

You should launch your loop.run_until_complete(asyncfoo(10)) in a thread or a subprocess if you want the "Foo" to be print before.

edited Dec 22, 2016 at 12:29

Matthew Wilcoxson

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answered Dec 22, 2016 at 12:26

iFlo

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2 Comments

Rahul Over a year ago

I see little gain with more complexity of using async with python. Why can't it be as simple as in node?

Udi Over a year ago

Running async and a thread/subprocess misses the point in this example.

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