共计 6436 个字符，预计需要花费 17 分钟才能阅读完成。
本文探讨 tornado 的协程实现原理，简略做了一份笔记。
首先看一段最常见的 tornado web 代码：
import tornado
import tornado.web
import tornado.gen
from tornado.gen import coroutine
from tornado.httpclient import AsyncHTTPClient
class GenHandler(tornado.web.RequestHandler):
@coroutine
def get(self):
url = 'http://www.baidu.com'
http_client = AsyncHTTPClient()
response = yield http_client.fetch(url)
yield tornado.gen.sleep(5)
self.write(response.body)
class MainHanler(tornado.web.RequestHandler):
def get(self):
self.write('root')
if __name__ == "__main__":
application = tornado.web.Application([(r"/", MainHanler),
(r"/gen_async/", GenHandler),
], autoreload=True)
application.listen(8888)
tornado.ioloop.IOLoop.current().start() 其中最初一行代码 tornado.ioloop.IOLoop.current().start() 启动服务。带着几个问题往下看：
- 晓得 yield 能够暂存执行状态，等「适合的机会」从新复原执行，那么保留的状态到哪去了？
- 上一个问题中「适合的机会」是到底是什么时候？
- 持续接上一个问题，具体是怎么复原执行的？
IOLoop 类相当于是对多路复用的封装，起到事件循环的作用，调度整个协程执行过程。
查看 IOLoop 的源码，能够看到 IOLoop 继承自 Configurable，PollIOLoop 又继承自 IOLoop。当 IOLoop 启动时，会确定应用哪一种多路复用形式，epoll、kqueue 还是 select？
# IOLoop 类
# IOLoop 中的 configurable_default 办法是重写 Configurable 的
# 这里会确定应用哪种多路复用形式
@classmethod
def configurable_default(cls):
if hasattr(select, "epoll"):
from tornado.platform.epoll import EPollIOLoop
return EPollIOLoop
if hasattr(select, "kqueue"):
# Python 2.6+ on BSD or Mac
from tornado.platform.kqueue import KQueueIOLoop
return KQueueIOLoop
from tornado.platform.select import SelectIOLoop
return SelectIOLoop# PollIOLoop 类
def initialize(self, impl, time_func=None, **kwargs):
super(PollIOLoop, self).initialize(**kwargs)
self._impl = impl
if hasattr(self._impl, 'fileno'):
set_close_exec(self._impl.fileno())
self.time_func = time_func or time.time
self._handlers = {}
self._events = {}
self._callbacks = []
self._callback_lock = threading.Lock()
self._timeouts = []
self._cancellations = 0
self._running = False
self._stopped = False
self._closing = False
self._thread_ident = None
self._blocking_signal_threshold = None
self._timeout_counter = itertools.count()
# Create a pipe that we send bogus data to when we want to wake
# the I/O loop when it is idle
self._waker = Waker()
self.add_handler(self._waker.fileno(),
lambda fd, events: self._waker.consume(),
self.READ)
def add_handler(self, fd, handler, events):
fd, obj = self.split_fd(fd)
self._handlers[fd] = (obj, stack_context.wrap(handler))
self._impl.register(fd, events | self.ERROR)
def update_handler(self, fd, events):
fd, obj = self.split_fd(fd)
self._impl.modify(fd, events | self.ERROR)
def remove_handler(self, fd):
fd, obj = self.split_fd(fd)
self._handlers.pop(fd, None)
self._events.pop(fd, None)
try:
self._impl.unregister(fd)
except Exception:
gen_log.debug("Error deleting fd from IOLoop", exc_info=True)PollIOLoop 中 initalize 办法中调用 add_handler 办法，注册对应事件的处理函数，如 socket 可读时，回调哪个函数去解决。
IOLoop 和协程之间的信使：Future
class Future(object):
def __init__(self):
self._result = None
self._exc_info = None
self._callbacks = []
self.running = True
def set_result(self, result):
...
def set_exc_info(self, exce_info):
...
def result(self):
...
def exc_info(self):
...
def add_done_callback(self, callback):
self._callbacks.append(callback)Future 对象起到“占位符”的作用，协程的执行后果会通过 set_result 形式写入其中，并调用通过 add_done_callback 设置的回调。
复原唤醒协程的 Runner
class Runner(object):
def __init__(self, gen, result_future, first_yielded):
self.gen = gen
self.result_future = result_future
self.future = _null_future
self.yield_point = None
self.pending_callbacks = None
self.results = None
self.running = False
self.finished = False
self.had_exception = False
self.io_loop = IOLoop.current()
self.stack_context_deactivate = None
# 下面一堆不须要看的初始化
if self.handle_yield(first_yielded):
gen = result_future = first_yielded = None
self.run()
def handle_yield(self, yielded):
self.future = convert_yielded(yielded)
if self.future is moment:
self.io_loop.add_callback(self.run)
return False
elif not self.future.done():
def inner(f):
# Break a reference cycle to speed GC.
f = None
self.run()
self.io_loop.add_future(self.future, inner)
return False
return True
def run(self):
if self.running or self.finished:
return
try:
self.running = True
while True:
future = self.future
if not future.done():
return
self.future = None
try:
orig_stack_contexts = stack_context._state.contexts
exc_info = None
try:
value = future.result()
except Exception:
self.had_exception = True
exc_info = sys.exc_info()
future = None
yielded = self.gen.send(value)
except (StopIteration, Return) as e:
self.finished = True
self.future = _null_future
if self.pending_callbacks and not self.had_exception:
raise LeakedCallbackError(
"finished without waiting for callbacks %r" %
self.pending_callbacks)
future_set_result_unless_cancelled(self.result_future,
_value_from_stopiteration(e))
self.result_future = None
self._deactivate_stack_context()
return
except Exception:
# 一些完结操作
return
if not self.handle_yield(yielded):
return
yielded = None
finally:
self.running = False 协程每生成一个 Future，都会生成对应的一个 Runner，并将 Future 初始化注入都其中。Runner 的 run 办法中，通过 self.gen.send(Future) 来启动 Future，当 Future 实现时，将其设置成 done，并回调其预设的 callback。
答复第一个问题：协程的状态保留到哪去了：
IOLoop 中通过 add_future 调用实现类 PollIOLoop 中的 add_callback 办法，其中通过 functools 生成偏函数，放入 _callbacks 列表，期待被回调执行。
# IOLoop 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))
# PollIOLoop 的 add_callback
def add_callback(self, callback, *args, **kwargs):
if thread.get_ident() != self._thread_ident:
with self._callback_lock:
if self._closing:
return
list_empty = not self._callbacks
self._callbacks.append(functools.partial(stack_context.wrap(callback), *args, **kwargs))
if list_empty:
self._waker.wake()
else:
if self._closing:
return
self._callbacks.append(functools.partial(stack_context.wrap(callback), *args, **kwargs))第二个问题：「适合的机会」是什么？
IOLoop 实际上就是对多路复用的封装，当底层 epoll_wait 事件产生时，即会告诉 IOLoop 主线程。
这一段是 IOLoop 中期待多路复用的事件，以及处理事件。
try:
# 期待事件
event_pairs = self._impl.poll(poll_timeout)
except Exception as e:
print("wait fail")
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)
# 处理事件
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第三个问题：具体是怎么复原的。
Runner 通过一直 check Future 的状态，最初调用 callback 来返回后果。
总结
首先 tornado 对多路复用零碎调用做了封装，来实现非阻塞 web 服务。
其次 tornado 通过 yield+Future+Runner 实现了生成 Future，Runner 监控后果，回调 callback 来实现协程的执行。
参考：
http://www.nodekey.com/tornado-yi-bu-yuan-ma-jie-xi/
https://blog.csdn.net/wyx819/article/details/45420017
https://yangyaq.github.io/2019/03/06/tornado 的事件循环机制 /
本文由 mdnice 多平台公布
正文完
