python中的asyncio模块
asyncio异步IO,能够异步网络操作,并发,协程1、asyncio的关键字说明
2、定义一个协程# -*-coding:utf-8 -*- import asyncio async def func(): print("waiting----func------") #这里是一个协程对象,这个时候func()函数并没有执行 coroutine = func() print("coroutine",coroutine) #创建一个循环时间loop loop = asyncio.get_event_loop() #将协程加入到事件循环loop loop.run_until_complete(coroutine) loop.close() #输出: coroutine <coroutine object func at 0x02D10AE0> waiting----func------ 协程并发# -*-coding:utf-8 -*- import asyncio #定义一个协程比普通的函数多了async关键字 async def a(): print("waiting ----a-----") #在协程中挂起(释放控制权),await后面接的方法必须是awaitable的 await asyncio.sleep(0) print("ending ------a---------") async def b(): print("In b") async def main(): #并发运行任务,另一种写法:asyncio.wait([a(),b()],) await asyncio.gather(a(),b()) if __name__ == "__main__": """python3.6 loop = asyncio.get_event_loop() loop.run_until_complete(main()) loop.close()""" #启动循环事件,python3.7新写法 asyncio.run(main()) #输出: #waiting ----a----- #In b #ending ------a--------- 创建一个task协程对象不能直接运行,在注册事件循环的时候,其实是run_until_complete方法将协程包装成为了一个任务(task)对象,task对象是Future类的子类保存了协程运行后的状态,用于未来获取协程的结果 # -*-coding:utf-8 -*- import asyncio import time now = lambda :time.time() async def do_some_work(x): print("waiting:",x) start = now() coroutine = do_some_work(2) loop = asyncio.get_event_loop() #创建task task = loop.create_task(coroutine) print("task",task) loop.run_until_complete(task) print("task--",task) print("Time:",now()-start) #输出 task <Task pending coro=<do_some_work() running at D:/soft_install/python3/python3.7/StudyHard/OneDay/CheckCrawl/asyn.py:5>> waiting: 2 task-- <Task finished coro=<do_some_work() done,defined at D:/soft_install/python3/python3.7/StudyHard/OneDay/CheckCrawl/asyn.py:5> result=None> Time: 0.0 由输出可以看出创建task后,在task加入事件循环之前为pending状态,当完成后,状态为finished 关于上面通过loop.create_task(coroutine)创建task,同样的可以通过 asyncio.ensure_future(coroutine)创建task 绑定回调绑定回调,在task执行完成的时候可以获取执行的结果,回调的最后一个参数是future对象,通过该对象可以获取协程的返回值 # -*-coding:utf-8 -*- import asyncio import time now = lambda :time.time() async def do_some_work(x): print("waiting:",x) return "Done after {}s".format(x) def callback(future): print("callback:",future.result()) start = now() coroutine = do_some_work(2) loop = asyncio.get_event_loop() #创建task task = asyncio.ensure_future(coroutine) print("task:",task) task.add_done_callback(callback) print("task_add_callback:",task) loop.run_until_complete(task) print("Time:",now()-start) #输出 task: <Task pending coro=<do_some_work() running at D:/soft_install/python3/python3.7/StudyHard/OneDay/CheckCrawl/asyn.py:5>> task_add_callback: <Task pending coro=<do_some_work() running at D:/soft_install/python3/python3.7/StudyHard/OneDay/CheckCrawl/asyn.py:5> cb=[callback() at D:/soft_install/python3/python3.7/StudyHard/OneDay/CheckCrawl/asyn.py:9]> waiting: 2 callback: Done after 2s Time: 0.0 通过add_done_callback方法给task任务添加回调函数,当task(也可以说是coroutine)执行完成的时候,就会调用回调函数。并通过参数future获取协程执行的结果。这里我们创建 的task和回调里的future对象实际上是同一个对象 来自:1、https://www.jianshu.com/p/2eaf07770e79 (编辑:李大同) 【声明】本站内容均来自网络,其相关言论仅代表作者个人观点,不代表本站立场。若无意侵犯到您的权利,请及时与联系站长删除相关内容! |