如何使用 asyncio 定期执行函数?

How can I periodically execute a function with asyncio?

我正在从 tornado 迁移到 asyncio,但找不到与 tornadoPeriodicCallback 等效的 asyncio。 (A PeriodicCallback 有两个参数:运行 的函数和调用之间的毫秒数。)

没有对定期调用的内置支持,没有。

只需创建您自己的调度程序循环即可休眠并执行任何已安排的任务:

import math, time

async def scheduler():
    while True:
        # sleep until the next whole second
        now = time.time()
        await asyncio.sleep(math.ceil(now) - now)
       
        # execute any scheduled tasks
        async for task in scheduled_tasks(time.time()):
            await task()

scheduled_tasks() 迭代器应生成在给定时间准备好 运行 的任务。请注意,生成时间表并启动所有任务理论上可能需要超过 1 秒的时间;这里的想法是调度程序产生自上次检查以来应该开始的所有任务。

对于低于 3.5 的 Python 版本:

import asyncio

@asyncio.coroutine
def periodic():
    while True:
        print('periodic')
        yield from asyncio.sleep(1)

def stop():
    task.cancel()

loop = asyncio.get_event_loop()
loop.call_later(5, stop)
task = loop.create_task(periodic())

try:
    loop.run_until_complete(task)
except asyncio.CancelledError:
    pass

对于 Python 3.5 及更高版本:

import asyncio

async def periodic():
    while True:
        print('periodic')
        await asyncio.sleep(1)

def stop():
    task.cancel()

loop = asyncio.get_event_loop()
loop.call_later(5, stop)
task = loop.create_task(periodic())

try:
    loop.run_until_complete(task)
except asyncio.CancelledError:
    pass

当您觉得您的 asyncio 程序 "in background" 应该发生某些事情时,asyncio.Task 可能是实现它的好方法。您可以阅读 了解如何处理任务。

下面是 class 的可能实现,它会周期性地执行一些函数:

import asyncio
from contextlib import suppress


class Periodic:
    def __init__(self, func, time):
        self.func = func
        self.time = time
        self.is_started = False
        self._task = None

    async def start(self):
        if not self.is_started:
            self.is_started = True
            # Start task to call func periodically:
            self._task = asyncio.ensure_future(self._run())

    async def stop(self):
        if self.is_started:
            self.is_started = False
            # Stop task and await it stopped:
            self._task.cancel()
            with suppress(asyncio.CancelledError):
                await self._task

    async def _run(self):
        while True:
            await asyncio.sleep(self.time)
            self.func()

我们来测试一下:

async def main():
    p = Periodic(lambda: print('test'), 1)
    try:
        print('Start')
        await p.start()
        await asyncio.sleep(3.1)

        print('Stop')
        await p.stop()
        await asyncio.sleep(3.1)

        print('Start')
        await p.start()
        await asyncio.sleep(3.1)
    finally:
        await p.stop()  # we should stop task finally


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

输出:

Start
test
test
test

Stop

Start
test
test
test

[Finished in 9.5s]

正如您在 start 上看到的那样,我们只是开始调用一些函数并在无限循环中休眠一段时间的任务。在 stop 我们只是取消了那个任务。请注意,该任务应在程序完成时停止。

更重要的一点是您的回调不应花费太多时间来执行(否则它会冻结您的事件循环)。如果你打算调用一些 long-运行 func,你可能需要 .

基于 (@Torkel Bjørnson-Langen 和@ReWrite 评论)这是一项避免漂移的改进。

import time
import asyncio

@asyncio.coroutine
def periodic(period):
    def g_tick():
        t = time.time()
        count = 0
        while True:
            count += 1
            yield max(t + count * period - time.time(), 0)
    g = g_tick()

    while True:
        print('periodic', time.time())
        yield from asyncio.sleep(next(g))

loop = asyncio.get_event_loop()
task = loop.create_task(periodic(1))
loop.call_later(5, task.cancel)

try:
    loop.run_until_complete(task)
except asyncio.CancelledError:
    pass

带有装饰器的替代版本 python 3.7

import asyncio
import time


def periodic(period):
    def scheduler(fcn):

        async def wrapper(*args, **kwargs):

            while True:
                asyncio.create_task(fcn(*args, **kwargs))
                await asyncio.sleep(period)

        return wrapper

    return scheduler


@periodic(2)
async def do_something(*args, **kwargs):
    await asyncio.sleep(5)  # Do some heavy calculation
    print(time.time())


if __name__ == '__main__':
    asyncio.run(do_something('Maluzinha do papai!', secret=42))

一个可能有用的变体:如果您希望在上次执行结束和下一次执行开始之间每隔 n 秒而不是 n 秒进行一次重复调用,并且您不希望调用重叠及时,以下更简单:

async def repeat(interval, func, *args, **kwargs):
    """Run func every interval seconds.

    If func has not finished before *interval*, will run again
    immediately when the previous iteration finished.

    *args and **kwargs are passed as the arguments to func.
    """
    while True:
        await asyncio.gather(
            func(*args, **kwargs),
            asyncio.sleep(interval),
        )

还有一个使用它来 运行 在后台执行几个任务的示例:

async def f():
    await asyncio.sleep(1)
    print('Hello')


async def g():
    await asyncio.sleep(0.5)
    print('Goodbye')


async def main():
    t1 = asyncio.ensure_future(repeat(3, f))
    t2 = asyncio.ensure_future(repeat(2, g))
    await t1
    await t2

loop = asyncio.get_event_loop()
loop.run_until_complete(main())

这就是我用 asyncio 测试我的周期性回调理论所做的。我没有使用 Tornado 的经验,所以我不确定定期回调如何与它一起工作。不过,我习惯于在 Tkinter 中使用 after(ms, callback) 方法,这就是我想出的方法。 While True: 即使它是异步的(比全局更严重),我看起来也很难看。 call_later(s, callback, *args) 方法使用秒而不是毫秒。

import asyncio
my_var = 0
def update_forever(the_loop):
    global my_var
    print(my_var)
    my_var += 1 
    # exit logic could be placed here
    the_loop.call_later(3, update_forever, the_loop)  # the method adds a delayed callback on completion

event_loop = asyncio.get_event_loop()
event_loop.call_soon(update_forever, event_loop)
event_loop.run_forever()

此解决方案使用来自 Fernando José Esteves de Souza, the drifting workaround from Wojciech Migda 的装饰概念和超级class 以尽可能生成最优雅的代码来处理异步周期函数。

没有threading.Thread

解决方案由以下文件组成:

  • periodic_async_thread.py 以 class 为底子 class
  • a_periodic_thread.py 示例 subclass
  • run_me.py 示例实例化和 运行

文件中的PeriodicAsyncThread class periodic_async_thread.py:

import time
import asyncio
import abc

class PeriodicAsyncThread:
    def __init__(self, period):
        self.period = period

    def periodic(self):
        def scheduler(fcn):
            async def wrapper(*args, **kwargs):
                def g_tick():
                    t = time.time()
                    count = 0
                    while True:
                        count += 1
                        yield max(t + count * self.period - time.time(), 0)
                g = g_tick()

                while True:
                    # print('periodic', time.time())
                    asyncio.create_task(fcn(*args, **kwargs))
                    await asyncio.sleep(next(g))
            return wrapper
        return scheduler

    @abc.abstractmethod
    async def run(self, *args, **kwargs):
        return

    def start(self):
        asyncio.run(self.run())

一个简单的子示例class APeriodicThread 文件 a_periodic_thread.py:

from periodic_async_thread import PeriodicAsyncThread
import time
import asyncio

class APeriodicThread(PeriodicAsyncThread):
    def __init__(self, period):
        super().__init__(period)
        self.run = self.periodic()(self.run)
    
    async def run(self, *args, **kwargs):
        await asyncio.sleep(2)
        print(time.time())

在文件 run_me.py:

中实例化和 运行 实例 class
from a_periodic_thread import APeriodicThread
apt = APeriodicThread(2)
apt.start()

此代码代表了一种优雅的解决方案,它还减轻了其他解决方案的时间漂移​​问题。输出类似于:

1642711285.3898764
1642711287.390698
1642711289.3924973
1642711291.3920736

与threading.Thread

解决方案由以下文件组成:

  • async_thread.py 与 canopy 异步线程 class.
  • periodic_async_thread.py 以 class 为底子 class
  • a_periodic_thread.py 示例 subclass
  • run_me.py 示例实例化和 运行

文件async_thread.py中的AsyncThreadclass:

from threading import Thread
import asyncio
import abc

class AsyncThread(Thread):
    def __init__(self, *args, **kwargs) -> None:
        super().__init__(*args, **kwargs)

    @abc.abstractmethod
    async def async_run(self, *args, **kwargs):
        pass

    def run(self, *args, **kwargs):
        # loop = asyncio.new_event_loop()
        # asyncio.set_event_loop(loop)

        # loop.run_until_complete(self.async_run(*args, **kwargs))
        # loop.close()
        asyncio.run(self.async_run(*args, **kwargs))

文件中的PeriodicAsyncThread class periodic_async_thread.py:

import time
import asyncio
from .async_thread import AsyncThread

class PeriodicAsyncThread(AsyncThread):
    def __init__(self, period, *args, **kwargs):
        self.period = period
        super().__init__(*args, **kwargs)
        self.async_run = self.periodic()(self.async_run)

    def periodic(self):
        def scheduler(fcn):
            async def wrapper(*args, **kwargs):
                def g_tick():
                    t = time.time()
                    count = 0
                    while True:
                        count += 1
                        yield max(t + count * self.period - time.time(), 0)
                g = g_tick()

                while True:
                    # print('periodic', time.time())
                    asyncio.create_task(fcn(*args, **kwargs))
                    await asyncio.sleep(next(g))
            return wrapper
        return scheduler

一个简单的子示例class APeriodicThread 文件 a_periodic_thread.py:

import time
from threading import current_thread
from .periodic_async_thread import PeriodicAsyncThread
import asyncio

class APeriodicAsyncTHread(PeriodicAsyncThread):
    async def async_run(self, *args, **kwargs):
        print(f"{current_thread().name} {time.time()} Hi!")
        await asyncio.sleep(1)
        print(f"{current_thread().name} {time.time()} Bye!")

在文件 run_me.py:

中实例化和 运行 实例 class
from .a_periodic_thread import APeriodicAsyncTHread
a = APeriodicAsyncTHread(2, name = "a periodic async thread")
a.start()
a.join()

此代码代表了一种优雅的解决方案,它还减轻了其他解决方案的时间漂移​​问题。输出类似于:

a periodic async thread 1643726990.505269 Hi!
a periodic async thread 1643726991.5069854 Bye!
a periodic async thread 1643726992.506919 Hi!
a periodic async thread 1643726993.5089169 Bye!
a periodic async thread 1643726994.5076022 Hi!
a periodic async thread 1643726995.509422 Bye!
a periodic async thread 1643726996.5075526 Hi!
a periodic async thread 1643726997.5093904 Bye!
a periodic async thread 1643726998.5072556 Hi!
a periodic async thread 1643726999.5091035 Bye!

对于多种类型的调度,我推荐 APSScheduler,它支持异步。

我将它用于一个简单的 python 进程,我可以使用 docker 启动它,就像一个 cron 一样每周执行一些事情,直到我杀死 docker/process.