Asynchronous Python explained (as simple as possible)

# - Simple examples showing asynchronous workflow in Python -

#****** 1. asyncio approach (Python>=3.4) ******
# Pros: It's the closest one to JavaScript's async/await, so it's expected to be fully optimized.
# Cons: Limited Python version support, spanning from still recent one. I wouldn't recommend it anyways since LTS isn't yet reached for it, so beware - it can be buggy sometimes.

import asyncio
@asyncio.coroutine
def test_sleep(): # for Python>=3.5 can use "async def" without decorator above
    print("before")
    yield from asyncio.sleep(2) # for Python>=3.5 can use "await" instead
    print("after")

@asyncio.coroutine
def main():
    task = asyncio.create_task(test_sleep())
    yield from asyncio.sleep(1)
    print(1)
    yield from task

asyncio.get_event_loop().run_until_complete(main()) # for Python>=3.6 can use this instead: asyncio.run(main())

#****** 2. Threading approach ******
# Pros: Long-term support, should work on all Python interpreters and versions in all environments.
# Cons: It's overhead to do this for simple routines like below.

from threading import Thread
from time import sleep
def test_sleep():
    print("before") # for Python 2 it's without parenthesis
    sleep(2)
    print("after")

thread = Thread(target=test_sleep)
thread.start()
sleep(1)
print(1)
thread.join()
#EOF