Simplest async/await example possible in Python

is it possible to give a simple example showing how async / await works, by using only these two keywords + asyncio.get_event_loop() + run_until_complete + other Python code but no other asyncio functions?

This way it's possible to write code that works:

import asyncio


async def main():
    print('done!')


if __name__ ==  '__main__':
    loop = asyncio.get_event_loop()
    loop.run_until_complete(main())

But this way it's impossible to demonstrate why you need asyncio.

By the way, why do you need asyncio, not just plain code? Answer is - asyncio allows you to get performance benefit when you parallelize I/O blocking operations (like reading/writing to network). And to write useful example you need to use async implementation of those operations.

Please read this answer for more detailed explanation.

Upd:

ok, here's example that uses asyncio.sleep to imitate I/O blocking operation and asyncio.gather that shows how you can run multiple blocking operations concurrently:

import asyncio


async def io_related(name):
    print(f'{name} started')
    await asyncio.sleep(1)
    print(f'{name} finished')


async def main():
    await asyncio.gather(
        io_related('first'),
        io_related('second'),
    )  # 1s + 1s = over 1s


if __name__ ==  '__main__':
    loop = asyncio.get_event_loop()
    loop.run_until_complete(main())

Output:

first started
second started
first finished
second finished
[Finished in 1.2s]

Note how both io_related started then, after only one second, both done.

To answer your questions, I will provide 3 different solutions to the same problem.

Case 1: just normal Python

import time

def sleep():
    print(f'Time: {time.time() - start:.2f}')
    time.sleep(1)

def sum(name, numbers):
    total = 0
    for number in numbers:
        print(f'Task {name}: Computing {total}+{number}')
        sleep()
        total += number
    print(f'Task {name}: Sum = {total}\n')

start = time.time()
tasks = [
    sum("A", [1, 2]),
    sum("B", [1, 2, 3]),
]
end = time.time()
print(f'Time: {end-start:.2f} sec')

output:

Task A: Computing 0+1
Time: 0.00
Task A: Computing 1+2
Time: 1.00
Task A: Sum = 3

Task B: Computing 0+1
Time: 2.01
Task B: Computing 1+2
Time: 3.01
Task B: Computing 3+3
Time: 4.01
Task B: Sum = 6

Time: 5.02 sec

Case 2: async/await done wrong

import asyncio
import time

async def sleep():
    print(f'Time: {time.time() - start:.2f}')
    time.sleep(1)

async def sum(name, numbers):
    total = 0
    for number in numbers:
        print(f'Task {name}: Computing {total}+{number}')
        await sleep()
        total += number
    print(f'Task {name}: Sum = {total}\n')

start = time.time()

loop = asyncio.get_event_loop()
tasks = [
    loop.create_task(sum("A", [1, 2])),
    loop.create_task(sum("B", [1, 2, 3])),
]
loop.run_until_complete(asyncio.wait(tasks))
loop.close()

end = time.time()
print(f'Time: {end-start:.2f} sec')

output:

Task A: Computing 0+1
Time: 0.00
Task A: Computing 1+2
Time: 1.00
Task A: Sum = 3

Task B: Computing 0+1
Time: 2.01
Task B: Computing 1+2
Time: 3.01
Task B: Computing 3+3
Time: 4.01
Task B: Sum = 6

Time: 5.01 sec

Case 3: async/await done right

Same as case 2 except the sleep function:

async def sleep():
    print(f'Time: {time.time() - start:.2f}')
    await asyncio.sleep(1)

output:

Task A: Computing 0+1
Time: 0.00
Task B: Computing 0+1
Time: 0.00
Task A: Computing 1+2
Time: 1.00
Task B: Computing 1+2
Time: 1.00
Task A: Sum = 3

Task B: Computing 3+3
Time: 2.00
Task B: Sum = 6

Time: 3.01 sec

Case 1 and case 2 give the same 5 seconds, whereas case 3 just 3 seconds. So the async/await done right is faster.

The reason for the difference is within the implementation of sleep function.

# case 1
def sleep():
    ...
    time.sleep(1)

# case 2
async def sleep():
    ...
    time.sleep(1)

# case 3
async def sleep():
    ...
    await asyncio.sleep(1)

In case 1 and case 2, they are the "same": they "sleep" without allowing others to use the resources. Whereas in case 3, it allows access to the resources when it is asleep.

In case 2, we added async to the normal function. However the event loop will run it without interruption. Why? Because we didn't say where the loop is allowed to interrupt your function to run another task.

In case 3, we told the event loop exactly where to interrupt the function to run another task. Where exactly? Right here!

await asyncio.sleep(1)

More on this read here

Update 02/May/2020

Consider reading

• A Hitchhikers Guide to Asynchronous Programming
• Asyncio Futures and Coroutines