Tornado 源码阅读：初步认识

来源：国夫君 segmentfault.com/a/1190000002971992

ioloop

`ioloop`是`tornado`的核心模块,也是个调度模块,各种异步事件都是由他调度的,所以必须弄清他的执行逻辑

源码分析

而`ioloop`的核心部分则是 `while True`这个循环内部的逻辑,贴上他的代码下

def start(self): if self._running: raise RuntimeError("IOLoop is already running") self._setup_logging() if self._stopped: self._stopped = False return old_current = getattr(IOLoop._current, "instance", None) IOLoop._current.instance = self self._thread_ident = thread.get_ident() self._running = True old_wakeup_fd = None if hasattr(signal, 'set_wakeup_fd') and os.name == 'posix': try: old_wakeup_fd = signal.set_wakeup_fd(self._waker.write_fileno()) if old_wakeup_fd != -1: signal.set_wakeup_fd(old_wakeup_fd) old_wakeup_fd = None except ValueError: old_wakeup_fd = None try: while True: with self._callback_lock: callbacks = self._callbacks self._callbacks = [] due_timeouts = [] if self._timeouts: now = self.time() while self._timeouts: if self._timeouts[0].callback is None: heapq.heappop(self._timeouts) self._cancellations -= 1 elif self._timeouts[0].deadline <= now: due_timeouts.append(heapq.heappop(self._timeouts)) else: break if (self._cancellations > 512 and self._cancellations > (len(self._timeouts) >> 1)): self._cancellations = 0 self._timeouts = [x for x in self._timeouts if x.callback is not None] heapq.heapify(self._timeouts) for callback in callbacks: self._run_callback(callback) for timeout in due_timeouts: if timeout.callback is not None: self._run_callback(timeout.callback) callbacks = callback = due_timeouts = timeout = None if self._callbacks: poll_timeout = 0.0 elif self._timeouts: poll_timeout = self._timeouts[0].deadline - self.time() poll_timeout = max(0, min(poll_timeout, _POLL_TIMEOUT)) else: poll_timeout = _POLL_TIMEOUT if not self._running: break if self._blocking_signal_threshold is not None: signal.setitimer(signal.ITIMER_REAL, 0, 0) try: event_pairs = self._impl.poll(poll_timeout) except Exception as e: if errno_from_exception(e) == errno.EINTR: continue else: raise if self._blocking_signal_threshold is not None: signal.setitimer(signal.ITIMER_REAL, self._blocking_signal_threshold, 0) self._events.update(event_pairs) while self._events: fd, events = self._events.popitem() try: fd_obj, handler_func = self._handlers[fd] handler_func(fd_obj, events) except (OSError, IOError) as e: if errno_from_exception(e) == errno.EPIPE: pass else: self.handle_callback_exception(self._handlers.get(fd)) except Exception: self.handle_callback_exception(self._handlers.get(fd)) fd_obj = handler_func = None finally: self._stopped = False if self._blocking_signal_threshold is not None: signal.setitimer(signal.ITIMER_REAL, 0, 0) IOLoop._current.instance = old_current if old_wakeup_fd is not None: signal.set_wakeup_fd(old_wakeup_fd)

除去注释,代码其实没多少行. 由while 内部代码可以看出ioloop主要由三部分组成:

1.回调 callbacks

他是ioloop回调的基础部分,通过IOLoop.instance().add_callback()添加到self._callbacks，他们将在每一次loop中被运行.

主要用途是将逻辑分块,在适合时机将包装好的callback添加到self._callbacks让其执行.

例如ioloop中的add_future

def add_future(self, future, callback): """Schedules a callback on the ``IOLoop`` when the given `.Future` is finished. The callback is invoked with one argument, the `.Future`. """ assert is_future(future) callback = stack_context.wrap(callback) future.add_done_callback( lambda future: self.add_callback(callback, future))

future对象得到result的时候会调用future.add_done_callback添加的callback,再将其转至ioloop执行

2.定时器 due_timeouts

这是定时器,在指定的事件执行callback.

跟1中的callback类似,通过IOLoop.instance().add_callback在每一次循环,会计算timeouts回调列表里的事件,运行已到期的callback.

当然不是无节操的循环.

因为poll操作会阻塞到有io操作发生,所以只要计算最近的timeout, 然后用这个时间作为self._impl.poll(poll_timeout) 的 poll_timeout ,就可以达到按时运行了

但是,假设poll_timeout的时间很大时,self._impl.poll一直在堵塞中(没有io事件,但在处理某一个io事件), 那添加刚才1中的callback不是要等很久才会被运行吗? 答案当然是不会.

ioloop中有个waker对象,他是由两个fd组成,一个读一个写.

ioloop在初始化的时候把waker绑定到epoll里了,add_callback时会触发waker的读写.

这样ioloop就会在poll中被唤醒了,接着就可以及时处理timeout callback了

用这样的方式也可以自己封装一个小的定时器功能玩玩

3.io事件的event loop

处理epoll事件的功能

通过IOLoop.instance().add_handler(fd, handler, events)绑定fd event的处理事件

在httpserver.listen的代码内,

netutil.py中的netutil.py的add_accept_handler绑定accept handler处理客户端接入的逻辑

如法炮制,其他的io事件也这样绑定,业务逻辑的分块交由ioloop的callback和future处理

关于epoll的用法的内容.详情见我第一篇文章吧,哈哈

总结

ioloop由callback(业务分块), timeout callback(定时任务) io event(io传输和解析) 三块组成,互相配合完成异步的功能,构建gen,httpclient,iostream等功能。

串联大致的流程是,tornado 绑定io event,处理io传输解析,传输完成后(结合Future)回调(callback)业务处理的逻辑和一些固定操作 . 定时器则是较为独立的模块

Futrue

个人认为Future是tornado仅此ioloop重要的模块,他贯穿全文,所有异步操作都有他的身影。顾名思义,他主要是关注日后要做的事,类似jquery的Deferred吧

一般的用法是通过ioloop的add_future定义future的done callback, 当future被set_result的时候,future的done callback就会被调用. 从而完成Future的功能.

具体可以参考gen.coroutine的实现,本文后面也会讲到

他的组成不复杂,只有几个重要的方法，最重要的是 add_done_callback , set_result

tornado用Future和ioloop,yield实现了gen.coroutine

1. add_done_callback

跟ioloop的callback类似 , 存储事件完成后的callback在self._callbacks里

def add_done_callback(self, fn): if self._done: fn(self) else: self._callbacks.append(fn)

2.set_result

设置事件的结果,并运行之前存储好的callback

def set_result(self, result): self._result = result self._set_done() def _set_done(self): self._done = True for cb in self._callbacks: try: cb(self) except Exception: app_log.exception('Exception in callback %r for %r', cb, self) self._callbacks = None

为了验证之前所说的,上一段测试代码

#! /usr/bin/env python #coding=utf-8 import tornado.web import tornado.ioloop from tornado.gen import coroutine from tornado.concurrent import Future def test(): def pp(s): print s future = Future() iol = tornado.ioloop.IOLoop.instance() print 'init future %s'%future iol.add_future(future, lambda f: pp('ioloop callback after future done,future is %s'%f)) #模拟io延迟操作 iol.add_timeout(iol.time()+5,lambda:future.set_result('set future is done')) print 'init complete' tornado.ioloop.IOLoop.instance().start() if __name__ == "__main__": test()

运行结果:

gen.coroutine

接着继续延伸,看看coroutine的实现。

gen.coroutine实现的功能其实是将原来的callback的写法,用yield的写法代替. 即以yield为分界,将代码分成两部分.

如:

#! /usr/bin/env python #coding=utf-8 import tornado.ioloop from tornado.gen import coroutine from tornado.httpclient import AsyncHTTPClient @coroutine def cotest(): client = AsyncHTTPClient() res = yield client.fetch("http://www.segmentfault.com/") print res if __name__ == "__main__": f = cotest() print f #这里返回了一个future哦 tornado.ioloop.IOLoop.instance().start()

运行结果:

源码分析

接下来分析下coroutine的实现

def _make_coroutine_wrapper(func, replace_callback): @functools.wraps(func) def wrapper(*args, **kwargs): future = TracebackFuture() if replace_callback and 'callback' in kwargs: callback = kwargs.pop('callback') IOLoop.current().add_future( future, lambda future: callback(future.result())) try: result = func(*args, **kwargs) except (Return, StopIteration) as e: result = getattr(e, 'value', None) except Exception: future.set_exc_info(sys.exc_info()) return future else: if isinstance(result, types.GeneratorType): try: orig_stack_contexts = stack_context._state.contexts yielded = next(result) if stack_context._state.contexts is not orig_stack_contexts: yielded = TracebackFuture() yielded.set_exception( stack_context.StackContextInconsistentError( 'stack_context inconsistency (probably caused ' 'by yield within a "with StackContext" block)')) except (StopIteration, Return) as e: future.set_result(getattr(e, 'value', None)) except Exception: future.set_exc_info(sys.exc_info()) else: Runner(result, future, yielded) try: return future finally: future = None future.set_result(result) return future return wrapper

如源码所示,func运行的结果是GeneratorType ,yielded = next(result), 运行至原函数的yield位置,返回的是原函数func内部 yield 右边返回的对象(必须是Future或Future的list)给yielded.经过Runner(result, future, yielded) 对yielded进行处理.在此就 贴出Runner的代码了.

Runner初始化过程,调用handle_yield, 查看yielded是否已done了,否则add_future运行Runner的run方法, run方法中如果yielded对象已完成,用对它的gen调用send,发送完成的结果.

所以yielded在什么地方被set_result非常重要, 当被set_result的时候,才会send结果给原func,完成整个异步操作

详情可以查看tornado 中重要的对象 iostream,源码中iostream的 _handle_connect,如此设置了连接的result.

def _handle_connect(self): err = self.socket.getsockopt(socket.SOL_SOCKET, socket.SO_ERROR) if err != 0: self.error = socket.error(err, os.strerror(err)) if self._connect_future is None: gen_log.warning("Connect error on fd %s: %s", self.socket.fileno(), errno.errorcode[err]) self.close() return if self._connect_callback is not None: callback = self._connect_callback self._connect_callback = None self._run_callback(callback) if self._connect_future is not None: future = self._connect_future self._connect_future = None future.set_result(self) self._connecting = False

最后贴上一个简单的测试代码,演示coroutine,future的用法

import tornado.ioloop from tornado.gen import coroutine from tornado.concurrent import Future @coroutine def asyn_sum(a, b): print("begin calculate:sum %d+%d"%(a,b)) future = Future() future2 = Future() iol = tornado.ioloop.IOLoop.instance() print future def callback(a, b): print("calculating the sum of %d+%d:"%(a,b)) future.set_result(a+b) iol.add_timeout(iol.time()+3,lambda f:f.set_result(None),future2) iol.add_timeout(iol.time()+3,callback, a, b) result = yield future print("after yielded") print("the %d+%d=%d"%(a, b, result)) yield future2 print 'after future2' def main(): f = asyn_sum(2,3) print '' print f tornado.ioloop.IOLoop.instance().start() if __name__ == "__main__": main()

运行结果:

为什么代码中个yield都起作用了? 因为Runner.run里,最后继续用handle_yield处理了send后返回的yielded对象,意思是func里可以有n干个yield操作

if not self.handle_yield(yielded): return

总结

至此,已完成tornado中重要的几个模块的流程,其他模块也是由此而来.写了这么多,越写越卡,就到此为止先吧。