VB.net 2010 视频教程 VB.net 2010 视频教程 python基础视频教程
SQL Server 2008 视频教程 c#入门经典教程 Visual Basic从门到精通视频教程
当前位置:
首页 > 编程开发 > python教程 >

  • python基础教程之Python3标准库：asyncio异步I/O、事件循环和并发工具(7)

本站最新发布   Python从入门到精通|Python基础教程
试听地址  https://www.xin3721.com/eschool/pythonxin3721/


  •  
  • async def main(loop):
  • # Create a shared event
  • event = asyncio.Event()
  • print('event start state: {}'.format(event.is_set()))
  •  
  • loop.call_later(
  • 0.1, functools.partial(set_event, event)
  • )
  •  
  • await asyncio.wait([coro1(event), coro2(event)])
  • print('event end state: {}'.format(event.is_set()))
  •  
  • event_loop = asyncio.get_event_loop()
  • try:
  • event_loop.run_until_complete(main(event_loop))
  • finally:
  • event_loop.close()

    • 与Lock一样，coro1()和coro2()会等待设置事件。区别是一旦事件状态改变，它们便可以立即启动，并且它们不需要得到事件对象上的唯一的锁。

    1.7.3 条件

    Condition的做法与Event类似，只不过不是通知所有等待的协程，被唤醒的等待协程的数目由notify()的一个参数控制。 

    

      

    1. 
import asyncio
      2. 

    2. 
 
      3. 

    3. 
async def consumer(condition, n):
      4. 

    4. 
async with condition:
      5. 

    5. 
print('consumer {} is waiting'.format(n))
      6. 

    6. 
await condition.wait()
      7. 

    7. 
print('consumer {} triggered'.format(n))
      8. 

    8. 
print('ending consumer {}'.format(n))
      9. 

    9. 
 
      10. 

    10. 
async def manipulate_condition(condition):
      11. 

    11. 
print('starting manipulate_condition')
      12. 

    12. 
 
      13. 

    13. 
# pause to let consumers start
      14. 

    14. 
await asyncio.sleep(0.1)
      15. 

    15. 
 
      16. 

    16. 
for i in range(1, 3):
      17. 

    17. 
async with condition:
      18. 

    18. 
print('notifying {} consumers'.format(i))
      19. 

    19. 
condition.notify(n=i)
      20. 

    20. 
await asyncio.sleep(0.1)
      21. 

    21. 
 
      22. 

    22. 
async with condition:
      23. 

    23. 
print('notifying remaining consumers')
      24. 

    24. 
condition.notify_all()
      25. 

    25. 
 
      26. 

    26. 
print('ending manipulate_condition')
      27. 

    27. 
 
      28. 

    28. 
async def main(loop):
      29. 

    29. 
# Create a condition
      30. 

    30. 
condition = asyncio.Condition()
      31. 

    31. 
 
      32. 

    32. 
# Set up tasks watching the condition
      33. 

    33. 
consumers = [
      34. 

    34. 
consumer(condition, i)
      35. 

    35. 
for i in range(5)
      36. 

    36. 
]
      37. 

    37. 
 
      38. 

    38. 
# Schedule a task to manipulate the condition variable
      39. 

    39. 
loop.create_task(manipulate_condition(condition))
      40. 

    40. 
 
      41. 

    41. 
# Wait for the consumers to be done
      42. 

    42. 
await asyncio.wait(consumers)
      43. 

    43. 
 
      44. 

    44. 
event_loop = asyncio.get_event_loop()
      45. 

    45. 
try:
      46. 

    46. 
result = event_loop.run_until_complete(main(event_loop))
      47. 

    47. 
finally:
      48. 

    48. 
event_loop.close()
      49. 

    

    

    
这个例子启动Condition的5个消费者。它们分别使用wait()方法来等待通知让它继续。manipulate_condition()通知一个消费者，再通知两个消费者，然后通知所有其余的消费者。
    

    

    

    
1.7.4 队列
    

    
asyncio.Queue为协程提供了一个先进先出的数据结构，这与线程的queue.Queue或进程的multiprocessing.Queue很类似。
    

    

    

      

    1. 
import asyncio
      2. 

    2. 
 
      3. 

    3. 
async def consumer(n, q):
      4. 

    4. 
print('consumer {}: starting'.format(n))
      5. 

    5. 
while True:
      6. 

    6. 
print('consumer {}: waiting for item'.format(n))
      7. 

    7. 
item = await q.get()
      8. 

    8. 
print('consumer {}: has item {}'.format(n, item))
      9. 

    9. 
if item is None:
      10. 

    10. 
# None is the signal to stop.
      11. 

    11. 
q.task_done()
      12. 

    12. 
break
      13. 

    13. 
else:
      14. 

    14. 
await asyncio.sleep(0.01 * item)
      15. 

    15. 
q.task_done()
      16. 

    16. 
print('consumer {}: ending'.format(n))
      17. 

    17. 
 
      18. 

    18. 
async def producer(q, num_workers):
      19. 

    19. 
print('producer: starting')
      20. 

    20. 
# Add some numbers to the queue to simulate jobs
      21. 

    21. 
for i in range(num_workers * 3):
      22. 

    22. 
await q.put(i)
      23. 

    23. 
print('producer: added task {} to the queue'.format

    

    


    

    


    

    

    相关教程