先来看个例子,本身实现的模拟耗时操做express
例1api
import types import select import time import socket import functools class Future: def __init__(self, *, loop=None): self._result = None self._callbacks = [] self._loop = loop def set_result(self, result): self._result = result callbacks = self._callbacks[:] self._callbacks = [] for callback in callbacks: loop._ready.append(callback) def add_callback(self, callback): self._callbacks.append(callback) def __iter__(self): print('enter Future ...') print('foo 挂起在yield处 ') yield self print('foo 恢复执行') print('exit Future ...') return 'future' __await__ = __iter__ class Task: def __init__(self, cor, *, loop=None): self.cor = cor self._loop = loop def _step(self): cor = self.cor try: result = cor.send(None) # 1. cor 协程执行完毕时,会抛出StopIteration,说明cor执行完毕了,这是关闭loop except StopIteration as e: self._loop.close() # 2. 有异常时 except Exception as e: """处理异常逻辑""" # 3. result为Future对象时 else: if isinstance(result, Future): result.add_callback(self._wakeup) def _wakeup(self): self._step() class Loop: def __init__(self): self._stop = False self._ready = [] self._scheduled = [] self._time = lambda: time.time() sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM) sock.setblocking(False) self._select = functools.partial(select.select, [sock], [], []) def create_task(self, cor): task = Task(cor, loop=self) self._ready.append(task._step) return task def call_later(self, delay, callback, *args): callback._when = delay self._scheduled.append((callback, *args)) def run_until_complete(self, task): assert isinstance(task, Task) timeout = None while not self._stop: if self._ready: timeout = 0 if self._scheduled: callback, *args = self._scheduled.pop() timeout = callback._when self._ready.append(functools.partial(callback, *args)) # 经过select(timeout)来控制阻塞时间 self._select(timeout) n = len(self._ready) for i in range(n): step = self._ready.pop() step() def close(self): self._stop = True @types.coroutine def _sleep(): yield # 本身实现一个sleep协程 async def sleep(s, result=None): if s <= 0: await _sleep() return result else: future = Future(loop=loop) future._loop.call_later(s, callback, future) await future return result # 延迟回调函数 def callback(future): # 时间到了就回调此函数 future.set_result(None) async def foo(): print(f'enter foo at {time.strftime("%Y-%m-%d %H:%M:%S")}') await sleep(3) print(f'exit foo at {time.strftime("%Y-%m-%d %H:%M:%S")}') if __name__ == '__main__': f = foo() loop = Loop() task = loop.create_task(f) loop.run_until_complete(task)
执行结果:app
enter foo at 2019-07-08 21:09:43 enter Future ... foo 挂起在yield处 foo 恢复执行 exit Future ... exit foo at 2019-07-08 21:09:46
在上一篇文章经过Loop, Task, Future三个类基本上实现了对协程的调度,在此基础上作了一些修改实现了对协程中耗时操做的模拟。less
首先咱们分析一下async def foo协程中的await sleep(3),这里其实会进入到sleep中 await future这里,再进入到future对象的__await__方法中的yield self,foo协程此时被挂起,上一篇文章中咱们分析知道,最终foo仍是被这个future对象给分红了part1和part2两部分逻辑。socket
- foo print('enter foo at ...') - sleep - future print('enter Future ...') # 以上是第一次f.send(None)执行的逻辑,命名为part1 - future yield self --------------------------------------------------------------- - print('exit Future ...') #如下是第二次f.send(None)执行的逻辑,命名为part2 - sleep - foo print('exit foo at ...')
part1 在 loop 循环的开始就执行了,返回一个 future 对象,把 part2 注册到 future 中,而后挂起了,下半部分 part2 在何时执行呢?由于在 sleep 中咱们经过注册了一个3秒以后执行的回调函数 callback 到 loop 对象中,loop 对象在执行完 part1 后,会在下一轮的循环中执行 callback 回调函数,因为 loop._scheduled 不为空,timeout 被赋值成3,所以 select(3) 阻塞3秒后就继续往下执行。也就是说 callback 函数的执行时机就是在 select(3) 阻塞3秒后执行,callback 回调函数中又会调用 future.set_result() ,在 set_result 中会把 part2 注册到 loop 中,因此最终又在 loop 的下一轮循环中调用 part2 的逻辑,回到上次 foo 挂起的地方,继续 foo 的流程,直到协程退出。async
其实所谓的模拟耗时3秒,其实就是在执行完part1后经过 select 函数阻塞3秒,而后再次执行 part2 ,这样就实现了所谓的等待3秒的操做。函数
要实现这个sleep协程的耗时模拟,主要是有2个关键点:oop
1.经过 select(timeout) 的 timeout来控制 select 函数的阻塞时间。ui
timeout=None 一直阻塞,直到有真实的IO事件到来,如socket的可读可写事件 timeout=0 不管此时是否有IO事件到来,都立马返回 timeout=n 阻塞n秒,在这n秒内,只要有IO事件到来,就立马返回,不然阻塞n秒才返回
2.当延迟时间到来时,经过 callback 函数中调用 future.set_result() 方法,来驱动 part2 的执行。debug
了解到这里以后,咱们再来看一下 asyncio 的源码
Loop类
class BaseEventLoop(events.AbstractEventLoop): ... def __init__(self): ... # 用来保存包裹task.step方法的handle对象的对端队列 self._ready = collections.deque() # 用来保存包裹延迟回调函数的handle对象的二叉堆,是一个最小二叉堆 self._scheduled = [] ... def create_task(self, coro): """Schedule a coroutine object. Return a task object. """ self._check_closed() # self._task_factory 默认是None if self._task_factory is None: # 建立一个task对象 task = tasks.Task(coro, loop=self) if task._source_traceback: del task._source_traceback[-1] else: task = self._task_factory(self, coro) # 返回这个task对象 return task def call_soon(self, callback, *args): self._check_closed() if self._debug: self._check_thread() self._check_callback(callback, 'call_soon') # 关键代码callback就是task._step方法,args是task._step的参数 handle = self._call_soon(callback, args) if handle._source_traceback: del handle._source_traceback[-1] return handle def _call_soon(self, callback, args): # 1 handle是一个包裹了task._step方法和args参数的对象 handle = events.Handle(callback, args, self) if handle._source_traceback: del handle._source_traceback[-1] # 2 关键代码,把handle添加到列表self._ready中 self._ready.append(handle) return handle def run_until_complete(self, future): ... # future就是task对象,下面2句是为了确保future是一个Future类实例对象 new_task = not futures.isfuture(future) future = tasks.ensure_future(future, loop=self) if new_task: # An exception is raised if the future didn't complete, so there # is no need to log the "destroy pending task" message future._log_destroy_pending = False # 添加回调方法_run_until_complete_cb到当前的task对象的callbacks列表中,_run_until_complete_cb就是最后 # 把loop的_stop属性设置为ture的,用来结束loop循环的 future.add_done_callback(_run_until_complete_cb) try: # 开启无线循环 self.run_forever() except: ... raise finally: ... # 执行完毕返回cor的返回值 return future.result() def run_forever(self): ... try: events._set_running_loop(self) while True: # 每次运行一次循环,判断下_stopping是否为true,也就是是否结束循环 self._run_once() if self._stopping: break finally: ... def _run_once(self): # loop的_scheduled是一个最小二叉堆,用来存放延迟执行的回调函数,根据延迟的大小,把这些回调函数构成一个最小堆,而后再每次从对顶弹出延迟最小的回调函数放入_ready双端队列中, # loop的_ready是双端队列,全部注册到loop的回调函数,最终是要放入到这个队列中,依次取出而后执行的 # 1. self._scheduled是否为空 sched_count = len(self._scheduled) if (sched_count > _MIN_SCHEDULED_TIMER_HANDLES and self._timer_cancelled_count / sched_count > _MIN_CANCELLED_TIMER_HANDLES_FRACTION): # Remove delayed calls that were cancelled if their number # is too high new_scheduled = [] for handle in self._scheduled: if handle._cancelled: handle._scheduled = False else: new_scheduled.append(handle) heapq.heapify(new_scheduled) self._scheduled = new_scheduled self._timer_cancelled_count = 0 else: # Remove delayed calls that were cancelled from head of queue. while self._scheduled and self._scheduled[0]._cancelled: self._timer_cancelled_count -= 1 handle = heapq.heappop(self._scheduled) handle._scheduled = False # 2. 给timeout赋值,self._scheduled为空,timeout就为None timeout = None # 只要self._ready和self._scheduled中有一个不为空,timeout就为0 if self._ready or self._stopping: timeout = 0 # 只要self._scheduled不为空 elif self._scheduled: # Compute the desired timeout. # 用堆顶的回调函数的延迟时间做为timeout的等待时间,也就是说用等待时间最短的回调函数的时间做为timeout的等待时间 when = self._scheduled[0]._when timeout = max(0, when - self.time()) 、 if self._debug and timeout != 0: ... # 3. 关注else分支,这是关键代码 else: # timeout=None --> 一直阻塞,只要有io事件产生,立马返回event_list事件列表,不然一直阻塞着 # timeout=0 --> 不阻塞,有io事件产生,就立马返回event_list事件列表,没有也返空列表 # timeout=2 --> 阻塞等待2s,在这2秒内只要有io事件产生,立马返回event_list事件列表,没有io事件就阻塞2s,而后返回空列表 event_list = self._selector.select(timeout) # 用来处理真正的io事件的函数 self._process_events(event_list) # Handle 'later' callbacks that are ready. end_time = self.time() + self._clock_resolution # 4. 依次取出堆顶的回调函数handle添加到_ready队列中 while self._scheduled: handle = self._scheduled[0] # 当_scheduled[]中有多个延迟回调时,经过handle._when >= end_time来阻止没有到时间的延迟函数被弹出, # 也就是说,当有n个延迟回调时,会产生n个timeout,对应n次run_once循环的调用 if handle._when >= end_time: break # 从堆中弹出堆顶最小的回调函数,放入 _ready 队列中 handle = heapq.heappop(self._scheduled) handle._scheduled = False self._ready.append(handle) # 5. 执行self._ready队列中全部的回调函数handle对象 ntodo = len(self._ready) for i in range(ntodo): handle = self._ready.popleft() if handle._cancelled: continue if self._debug: try: self._current_handle = handle t0 = self.time() handle._run() dt = self.time() - t0 if dt >= self.slow_callback_duration: logger.warning('Executing %s took %.3f seconds', _format_handle(handle), dt) finally: self._current_handle = None else: # handle._run()实际上就是执行task._step(),也就是执行cor.send(None) handle._run() handle = None # Needed to break cycles when an exception occurs.
Task类
class Task(futures.Future): ... def _step(self, exc=None): """ _step方法能够看作是task包装的coroutine对象中的代码的直到yield的前半部分逻辑 """ ... try: if exc is None: # 1.关键代码,调用协程 result = coro.send(None) else: result = coro.throw(exc) # 2. coro执行完毕会抛出StopIteration异常 except StopIteration as exc: if self._must_cancel: # Task is cancelled right before coro stops. self._must_cancel = False self.set_exception(futures.CancelledError()) else: # result为None时,调用task的callbasks列表中的回调方法,在调用loop.run_until_complite,结束loop循环 self.set_result(exc.value) except futures.CancelledError: super().cancel() # I.e., Future.cancel(self). except Exception as exc: self.set_exception(exc) except BaseException as exc: self.set_exception(exc) raise # 3. result = coro.send(None)不抛出异常,说明协程被yield挂起 else: # 4. 查看result是否含有_asyncio_future_blocking属性 blocking = getattr(result, '_asyncio_future_blocking', None) if blocking is not None: # Yielded Future must come from Future.__iter__(). if result._loop is not self._loop: self._loop.call_soon( self._step, RuntimeError( 'Task {!r} got Future {!r} attached to a ' 'different loop'.format(self, result))) elif blocking: if result is self: self._loop.call_soon( self._step, RuntimeError( 'Task cannot await on itself: {!r}'.format( self))) # 4.1. 若是result是一个future对象时,blocking会被设置成true else: result._asyncio_future_blocking = False # 把_wakeup回调函数设置到此future对象中,当此future对象调用set_result()方法时,就会调用_wakeup方法 result.add_done_callback(self._wakeup) self._fut_waiter = result if self._must_cancel: if self._fut_waiter.cancel(): self._must_cancel = False else: self._loop.call_soon( self._step, RuntimeError( 'yield was used instead of yield from ' 'in task {!r} with {!r}'.format(self, result))) # 5. 若是result是None,则注册task._step到loop对象中去,在下一轮_run_once中被回调 elif result is None: # Bare yield relinquishes control for one event loop iteration. self._loop.call_soon(self._step) # --------下面的代码能够暂时不关注了-------- elif inspect.isgenerator(result): # Yielding a generator is just wrong. self._loop.call_soon( self._step, RuntimeError( 'yield was used instead of yield from for ' 'generator in task {!r} with {}'.format( self, result))) else: # Yielding something else is an error. self._loop.call_soon( self._step, RuntimeError( 'Task got bad yield: {!r}'.format(result))) finally: self.__class__._current_tasks.pop(self._loop) self = None # Needed to break cycles when an exception occurs. def _wakeup(self, future): try: future.result() except Exception as exc: # This may also be a cancellation. self._step(exc) else: # 这里是关键代码,上次的_step()执行到第一次碰到yield的地方挂住了,此时再次执行_step(), # 也就是再次执行 result = coro.send(None) 这句代码,也就是从上次yield的地方继续执行yield后面的逻辑 self._step() self = None # Needed to break cycles when an exception occurs.
Future类
class Future: ... def add_done_callback(self, fn, *, context=None): if self._state != _PENDING: self._loop.call_soon(fn, self, context=context) else: if context is None: context = contextvars.copy_context() self._callbacks.append((fn, context)) def set_result(self, result): if self._state != _PENDING: raise InvalidStateError('{}: {!r}'.format(self._state, self)) self._result = result self._state = _FINISHED self.__schedule_callbacks() def __iter__(self): # self.done()返回False, if not self.done(): self._asyncio_future_blocking = True # 把Future对象本身返回出去 yield self # This tells Task to wait for completion. assert self.done(), "yield from wasn't used with future" return self.result() # May raise too. if compat.PY35: __await__ = __iter__ # make compatible with 'await' expression
sleep协程
#延迟回调函数,里面调用fut.set_result def _set_result_unless_cancelled(fut, result): if fut.cancelled(): return # 关键是这一步,驱动协程从上次挂起的地方继续执行 fut.set_result(result) @types.coroutine def __sleep0(): yield async def sleep(delay, result=None, *, loop=None): """Coroutine that completes after a given time (in seconds).""" if delay <= 0: await __sleep0() return result if loop is None: loop = events.get_event_loop() # 建立一个future对象 future = loop.create_future() # 注册一个延迟回调函数到loop对象中 h = loop.call_later(delay, futures._set_result_unless_cancelled, future, result) try: return await future finally: h.cancel()
关键地方我都写了注释,若是能耐着性子细心看下来,你会发现例1中的实现,就是模仿asyncio中的这几个类去实现的。
asyncio的sleep中的延迟回调函数是_set_result_unless_cancelled与我写的callback对应,关键都是要回调future.set_result方法,这样才能驱动协程从上次挂起的地方开始继续执行。
对于使用asyncio.sleep的例子
import asyncio async def cor(): print('enter cor ...') await asyncio.sleep(2) print('exit cor ...') return 'cor' loop = asyncio.get_event_loop() task = loop.create_task(cor()) rst = loop.run_until_complete(task) print(rst)
await asyncio.sleep(2) 这句代码一样是把cor协程分为以下两个部分:
- cor print('enter cor ...') - sleep - future print('enter Future ...') # 以上是第一次cor.send(None)执行的逻辑,命名为part1 - future yield self --------------------------------------------------------------- - future print('exit Future ...') # 如下是第二次cor.send(None)执行的逻辑,命名为part2 - sleep - cor print('exit foo ...')
总之,只要有要耗时的地方,就必需要有一个 future 用来 await future,而后协程就被分红了part1和part2,part1和part2就被分别封装到了task._step和task._wakeup中,而后在loop循环中先调用part1,再经过select函数阻塞n秒以后,再执行part2,最后,协程执行完毕。