Using asyncio for concurrency

Concurrency and parallelism have always been confusing concepts . Concurrency usually means that multiple tasks need to be performed at the same time , In parallel, multiple tasks are executed at the same time .

asyncio Implement concurrency , It's going to take more than one process to complete the task , Whenever there's a task jam, it's await, And then the other coroners continue to work . Create a list of multiple collaborations , Then register these processes in the time cycle .

One 、asyncio Implement concurrency

import asyncio
import time
now  = lambda:time.time()
def events_demo():

async def do_some_work(x):
	print('Waiting:',x)
	await asyncio.sleep(x)
	return 'Done after {}s'.format(x)
start = now()

# Create multiple collaboration objects 
coroutine1=do_some_work(1)
coroutine1=do_some_work(2)
coroutine1=do_some_work(4)

# Create a task list 
tasks=[
	asyncio.ensure_future(coroutine1),
	asyncio.ensure_future(coroutine2),
	asyncio.ensure_future(coroutine3)
]
# Register the task list into the event loop 
loop=asyncio.get_event_loop()
loop.run_until_complete(asyncio.wait(tasks))

# Get the returned result 
for task in tasks:
	print('Task ret:',task.result())

print('TIME:',now()-start)

Two 、 Summary of the experiment

Running result display , In parallel, it should be 1+2+4=7 second ; Execute each task concurrently do_some_work, The first time it took was 1 second , It takes time to execute other cooperation processes , The second time is 2 second , It takes time to execute other cooperation processes , And so on . In case of time-consuming blocking, other processes are performed , The longest time is 4 second , Three tasks 4 Seconds to complete .