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tornado.gen 源代码

"""``tornado.gen`` is a generator-based interface to make it easier to
work in an asynchronous environment.  Code using the ``gen`` module
is technically asynchronous, but it is written as a single generator
instead of a collection of separate functions.

For example, the following asynchronous handler:

.. testcode::

    class AsyncHandler(RequestHandler):
        def get(self):
            http_client = AsyncHTTPClient()

        def on_fetch(self, response):

.. testoutput::

could be written with ``gen`` as:

.. testcode::

    class GenAsyncHandler(RequestHandler):
        def get(self):
            http_client = AsyncHTTPClient()
            response = yield http_client.fetch("")

.. testoutput::

Most asynchronous functions in Tornado return a `.Future`;
yielding this object returns its `~.Future.result`.

You can also yield a list or dict of ``Futures``, which will be
started at the same time and run in parallel; a list or dict of results will
be returned when they are all finished:

.. testcode::

    def get(self):
        http_client = AsyncHTTPClient()
        response1, response2 = yield [http_client.fetch(url1),
        response_dict = yield dict(response3=http_client.fetch(url3),
        response3 = response_dict['response3']
        response4 = response_dict['response4']

.. testoutput::

If the `~functools.singledispatch` library is available (standard in
Python 3.4, available via the `singledispatch
<>`_ package on older
versions), additional types of objects may be yielded. Tornado includes
support for ``asyncio.Future`` and Twisted's ``Deferred`` class when
``tornado.platform.asyncio`` and ``tornado.platform.twisted`` are imported.
See the `convert_yielded` function to extend this mechanism.

.. versionchanged:: 3.2
   Dict support added.

.. versionchanged:: 4.1
   Support added for yielding ``asyncio`` Futures and Twisted Deferreds
   via ``singledispatch``.

from __future__ import absolute_import, division, print_function, with_statement

import collections
import functools
import itertools
import os
import sys
import textwrap
import types

from tornado.concurrent import Future, TracebackFuture, is_future, chain_future
from tornado.ioloop import IOLoop
from tornado.log import app_log
from tornado import stack_context
from tornado.util import PY3, raise_exc_info

        # py34+
        from functools import singledispatch  # type: ignore
    except ImportError:
        from singledispatch import singledispatch  # backport
except ImportError:
    # In most cases, singledispatch is required (to avoid
    # difficult-to-diagnose problems in which the functionality
    # available differs depending on which invisble packages are
    # installed). However, in Google App Engine third-party
    # dependencies are more trouble so we allow this module to be
    # imported without it.
    if 'APPENGINE_RUNTIME' not in os.environ:
    singledispatch = None

        # py35+
        from import Generator as GeneratorType  # type: ignore
    except ImportError:
        from backports_abc import Generator as GeneratorType  # type: ignore

        # py35+
        from inspect import isawaitable  # type: ignore
    except ImportError:
        from backports_abc import isawaitable
except ImportError:
    if 'APPENGINE_RUNTIME' not in os.environ:
    from types import GeneratorType

    def isawaitable(x):  # type: ignore
        return False

if PY3:
    import builtins
    import __builtin__ as builtins

class KeyReuseError(Exception):

class UnknownKeyError(Exception):

class LeakedCallbackError(Exception):

class BadYieldError(Exception):

class ReturnValueIgnoredError(Exception):

[文档]class TimeoutError(Exception): """Exception raised by ``with_timeout``."""
def _value_from_stopiteration(e): try: # StopIteration has a value attribute beginning in py33. # So does our Return class. return e.value except AttributeError: pass try: # Cython backports coroutine functionality by putting the value in # e.args[0]. return e.args[0] except (AttributeError, IndexError): return None
[文档]def engine(func): """Callback-oriented decorator for asynchronous generators. This is an older interface; for new code that does not need to be compatible with versions of Tornado older than 3.0 the `coroutine` decorator is recommended instead. This decorator is similar to `coroutine`, except it does not return a `.Future` and the ``callback`` argument is not treated specially. In most cases, functions decorated with `engine` should take a ``callback`` argument and invoke it with their result when they are finished. One notable exception is the `~tornado.web.RequestHandler` :ref:`HTTP verb methods <verbs>`, which use ``self.finish()`` in place of a callback argument. """ func = _make_coroutine_wrapper(func, replace_callback=False) @functools.wraps(func) def wrapper(*args, **kwargs): future = func(*args, **kwargs) def final_callback(future): if future.result() is not None: raise ReturnValueIgnoredError( "@gen.engine functions cannot return values: %r" % (future.result(),)) # The engine interface doesn't give us any way to return # errors but to raise them into the stack context. # Save the stack context here to use when the Future has resolved. future.add_done_callback(stack_context.wrap(final_callback)) return wrapper
[文档]def coroutine(func, replace_callback=True): """Decorator for asynchronous generators. Any generator that yields objects from this module must be wrapped in either this decorator or `engine`. Coroutines may "return" by raising the special exception `Return(value) <Return>`. In Python 3.3+, it is also possible for the function to simply use the ``return value`` statement (prior to Python 3.3 generators were not allowed to also return values). In all versions of Python a coroutine that simply wishes to exit early may use the ``return`` statement without a value. Functions with this decorator return a `.Future`. Additionally, they may be called with a ``callback`` keyword argument, which will be invoked with the future's result when it resolves. If the coroutine fails, the callback will not be run and an exception will be raised into the surrounding `.StackContext`. The ``callback`` argument is not visible inside the decorated function; it is handled by the decorator itself. From the caller's perspective, ``@gen.coroutine`` is similar to the combination of ``@return_future`` and ``@gen.engine``. .. warning:: When exceptions occur inside a coroutine, the exception information will be stored in the `.Future` object. You must examine the result of the `.Future` object, or the exception may go unnoticed by your code. This means yielding the function if called from another coroutine, using something like `.IOLoop.run_sync` for top-level calls, or passing the `.Future` to `.IOLoop.add_future`. """ return _make_coroutine_wrapper(func, replace_callback=True)
def _make_coroutine_wrapper(func, replace_callback): """The inner workings of ``@gen.coroutine`` and ``@gen.engine``. The two decorators differ in their treatment of the ``callback`` argument, so we cannot simply implement ``@engine`` in terms of ``@coroutine``. """ # On Python 3.5, set the coroutine flag on our generator, to allow it # to be used with 'await'. if hasattr(types, 'coroutine'): func = types.coroutine(func) @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 = _value_from_stopiteration(e) except Exception: future.set_exc_info(sys.exc_info()) return future else: if isinstance(result, GeneratorType): # Inline the first iteration of This lets us # avoid the cost of creating a Runner when the coroutine # never actually yields, which in turn allows us to # use "optional" coroutines in critical path code without # performance penalty for the synchronous case. 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(_value_from_stopiteration(e)) except Exception: future.set_exc_info(sys.exc_info()) else: Runner(result, future, yielded) try: return future finally: # Subtle memory optimization: if next() raised an exception, # the future's exc_info contains a traceback which # includes this stack frame. This creates a cycle, # which will be collected at the next full GC but has # been shown to greatly increase memory usage of # benchmarks (relative to the refcount-based scheme # used in the absence of cycles). We can avoid the # cycle by clearing the local variable after we return it. future = None future.set_result(result) return future return wrapper
[文档]class Return(Exception): """Special exception to return a value from a `coroutine`. If this exception is raised, its value argument is used as the result of the coroutine:: @gen.coroutine def fetch_json(url): response = yield AsyncHTTPClient().fetch(url) raise gen.Return(json_decode(response.body)) In Python 3.3, this exception is no longer necessary: the ``return`` statement can be used directly to return a value (previously ``yield`` and ``return`` with a value could not be combined in the same function). By analogy with the return statement, the value argument is optional, but it is never necessary to ``raise gen.Return()``. The ``return`` statement can be used with no arguments instead. """ def __init__(self, value=None): super(Return, self).__init__() self.value = value # Cython recognizes subclasses of StopIteration with a .args tuple. self.args = (value,)
[文档]class WaitIterator(object): """Provides an iterator to yield the results of futures as they finish. Yielding a set of futures like this: ``results = yield [future1, future2]`` pauses the coroutine until both ``future1`` and ``future2`` return, and then restarts the coroutine with the results of both futures. If either future is an exception, the expression will raise that exception and all the results will be lost. If you need to get the result of each future as soon as possible, or if you need the result of some futures even if others produce errors, you can use ``WaitIterator``:: wait_iterator = gen.WaitIterator(future1, future2) while not wait_iterator.done(): try: result = yield except Exception as e: print("Error {} from {}".format(e, wait_iterator.current_future)) else: print("Result {} received from {} at {}".format( result, wait_iterator.current_future, wait_iterator.current_index)) Because results are returned as soon as they are available the output from the iterator *will not be in the same order as the input arguments*. If you need to know which future produced the current result, you can use the attributes ``WaitIterator.current_future``, or ``WaitIterator.current_index`` to get the index of the future from the input list. (if keyword arguments were used in the construction of the `WaitIterator`, ``current_index`` will use the corresponding keyword). On Python 3.5, `WaitIterator` implements the async iterator protocol, so it can be used with the ``async for`` statement (note that in this version the entire iteration is aborted if any value raises an exception, while the previous example can continue past individual errors):: async for result in gen.WaitIterator(future1, future2): print("Result {} received from {} at {}".format( result, wait_iterator.current_future, wait_iterator.current_index)) .. versionadded:: 4.1 .. versionchanged:: 4.3 Added ``async for`` support in Python 3.5. """ def __init__(self, *args, **kwargs): if args and kwargs: raise ValueError( "You must provide args or kwargs, not both") if kwargs: self._unfinished = dict((f, k) for (k, f) in kwargs.items()) futures = list(kwargs.values()) else: self._unfinished = dict((f, i) for (i, f) in enumerate(args)) futures = args self._finished = collections.deque() self.current_index = self.current_future = None self._running_future = None for future in futures: future.add_done_callback(self._done_callback)
[文档] def done(self): """Returns True if this iterator has no more results.""" if self._finished or self._unfinished: return False # Clear the 'current' values when iteration is done. self.current_index = self.current_future = None return True
[文档] def next(self): """Returns a `.Future` that will yield the next available result. Note that this `.Future` will not be the same object as any of the inputs. """ self._running_future = TracebackFuture() if self._finished: self._return_result(self._finished.popleft()) return self._running_future
def _done_callback(self, done): if self._running_future and not self._running_future.done(): self._return_result(done) else: self._finished.append(done) def _return_result(self, done): """Called set the returned future's state that of the future we yielded, and set the current future for the iterator. """ chain_future(done, self._running_future) self.current_future = done self.current_index = self._unfinished.pop(done) @coroutine def __aiter__(self): raise Return(self) def __anext__(self): if self.done(): # Lookup by name to silence pyflakes on older versions. raise getattr(builtins, 'StopAsyncIteration')() return
[文档]class YieldPoint(object): """Base class for objects that may be yielded from the generator. .. deprecated:: 4.0 Use `Futures <.Future>` instead. """
[文档] def start(self, runner): """Called by the runner after the generator has yielded. No other methods will be called on this object before ``start``. """ raise NotImplementedError()
[文档] def is_ready(self): """Called by the runner to determine whether to resume the generator. Returns a boolean; may be called more than once. """ raise NotImplementedError()
[文档] def get_result(self): """Returns the value to use as the result of the yield expression. This method will only be called once, and only after `is_ready` has returned true. """ raise NotImplementedError()
[文档]class Callback(YieldPoint): """Returns a callable object that will allow a matching `Wait` to proceed. The key may be any value suitable for use as a dictionary key, and is used to match ``Callbacks`` to their corresponding ``Waits``. The key must be unique among outstanding callbacks within a single run of the generator function, but may be reused across different runs of the same function (so constants generally work fine). The callback may be called with zero or one arguments; if an argument is given it will be returned by `Wait`. .. deprecated:: 4.0 Use `Futures <.Future>` instead. """ def __init__(self, key): self.key = key def start(self, runner): self.runner = runner runner.register_callback(self.key) def is_ready(self): return True def get_result(self): return self.runner.result_callback(self.key)
[文档]class Wait(YieldPoint): """Returns the argument passed to the result of a previous `Callback`. .. deprecated:: 4.0 Use `Futures <.Future>` instead. """ def __init__(self, key): self.key = key def start(self, runner): self.runner = runner def is_ready(self): return self.runner.is_ready(self.key) def get_result(self): return self.runner.pop_result(self.key)
[文档]class WaitAll(YieldPoint): """Returns the results of multiple previous `Callbacks <Callback>`. The argument is a sequence of `Callback` keys, and the result is a list of results in the same order. `WaitAll` is equivalent to yielding a list of `Wait` objects. .. deprecated:: 4.0 Use `Futures <.Future>` instead. """ def __init__(self, keys): self.keys = keys def start(self, runner): self.runner = runner def is_ready(self): return all(self.runner.is_ready(key) for key in self.keys) def get_result(self): return [self.runner.pop_result(key) for key in self.keys]
[文档]def Task(func, *args, **kwargs): """Adapts a callback-based asynchronous function for use in coroutines. Takes a function (and optional additional arguments) and runs it with those arguments plus a ``callback`` keyword argument. The argument passed to the callback is returned as the result of the yield expression. .. versionchanged:: 4.0 ``gen.Task`` is now a function that returns a `.Future`, instead of a subclass of `YieldPoint`. It still behaves the same way when yielded. """ future = Future() def handle_exception(typ, value, tb): if future.done(): return False future.set_exc_info((typ, value, tb)) return True def set_result(result): if future.done(): return future.set_result(result) with stack_context.ExceptionStackContext(handle_exception): func(*args, callback=_argument_adapter(set_result), **kwargs) return future
class YieldFuture(YieldPoint): def __init__(self, future, io_loop=None): """Adapts a `.Future` to the `YieldPoint` interface. .. versionchanged:: 4.1 The ``io_loop`` argument is deprecated. """ self.future = future self.io_loop = io_loop or IOLoop.current() def start(self, runner): if not self.future.done(): self.runner = runner self.key = object() runner.register_callback(self.key) self.io_loop.add_future(self.future, runner.result_callback(self.key)) else: self.runner = None self.result_fn = self.future.result def is_ready(self): if self.runner is not None: return self.runner.is_ready(self.key) else: return True def get_result(self): if self.runner is not None: return self.runner.pop_result(self.key).result() else: return self.result_fn() def _contains_yieldpoint(children): """Returns True if ``children`` contains any YieldPoints. ``children`` may be a dict or a list, as used by `MultiYieldPoint` and `multi_future`. """ if isinstance(children, dict): return any(isinstance(i, YieldPoint) for i in children.values()) if isinstance(children, list): return any(isinstance(i, YieldPoint) for i in children) return False
[文档]def multi(children, quiet_exceptions=()): """Runs multiple asynchronous operations in parallel. ``children`` may either be a list or a dict whose values are yieldable objects. ``multi()`` returns a new yieldable object that resolves to a parallel structure containing their results. If ``children`` is a list, the result is a list of results in the same order; if it is a dict, the result is a dict with the same keys. That is, ``results = yield multi(list_of_futures)`` is equivalent to:: results = [] for future in list_of_futures: results.append(yield future) If any children raise exceptions, ``multi()`` will raise the first one. All others will be logged, unless they are of types contained in the ``quiet_exceptions`` argument. If any of the inputs are `YieldPoints <YieldPoint>`, the returned yieldable object is a `YieldPoint`. Otherwise, returns a `.Future`. This means that the result of `multi` can be used in a native coroutine if and only if all of its children can be. In a ``yield``-based coroutine, it is not normally necessary to call this function directly, since the coroutine runner will do it automatically when a list or dict is yielded. However, it is necessary in ``await``-based coroutines, or to pass the ``quiet_exceptions`` argument. This function is available under the names ``multi()`` and ``Multi()`` for historical reasons. .. versionchanged:: 4.2 If multiple yieldables fail, any exceptions after the first (which is raised) will be logged. Added the ``quiet_exceptions`` argument to suppress this logging for selected exception types. .. versionchanged:: 4.3 Replaced the class ``Multi`` and the function ``multi_future`` with a unified function ``multi``. Added support for yieldables other than `YieldPoint` and `.Future`. """ if _contains_yieldpoint(children): return MultiYieldPoint(children, quiet_exceptions=quiet_exceptions) else: return multi_future(children, quiet_exceptions=quiet_exceptions)
Multi = multi
[文档]class MultiYieldPoint(YieldPoint): """Runs multiple asynchronous operations in parallel. This class is similar to `multi`, but it always creates a stack context even when no children require it. It is not compatible with native coroutines. .. versionchanged:: 4.2 If multiple ``YieldPoints`` fail, any exceptions after the first (which is raised) will be logged. Added the ``quiet_exceptions`` argument to suppress this logging for selected exception types. .. versionchanged:: 4.3 Renamed from ``Multi`` to ``MultiYieldPoint``. The name ``Multi`` remains as an alias for the equivalent `multi` function. .. deprecated:: 4.3 Use `multi` instead. """ def __init__(self, children, quiet_exceptions=()): self.keys = None if isinstance(children, dict): self.keys = list(children.keys()) children = children.values() self.children = [] for i in children: if not isinstance(i, YieldPoint): i = convert_yielded(i) if is_future(i): i = YieldFuture(i) self.children.append(i) assert all(isinstance(i, YieldPoint) for i in self.children) self.unfinished_children = set(self.children) self.quiet_exceptions = quiet_exceptions def start(self, runner): for i in self.children: i.start(runner) def is_ready(self): finished = list(itertools.takewhile( lambda i: i.is_ready(), self.unfinished_children)) self.unfinished_children.difference_update(finished) return not self.unfinished_children def get_result(self): result_list = [] exc_info = None for f in self.children: try: result_list.append(f.get_result()) except Exception as e: if exc_info is None: exc_info = sys.exc_info() else: if not isinstance(e, self.quiet_exceptions): app_log.error("Multiple exceptions in yield list", exc_info=True) if exc_info is not None: raise_exc_info(exc_info) if self.keys is not None: return dict(zip(self.keys, result_list)) else: return list(result_list)
[文档]def multi_future(children, quiet_exceptions=()): """Wait for multiple asynchronous futures in parallel. This function is similar to `multi`, but does not support `YieldPoints <YieldPoint>`. .. versionadded:: 4.0 .. versionchanged:: 4.2 If multiple ``Futures`` fail, any exceptions after the first (which is raised) will be logged. Added the ``quiet_exceptions`` argument to suppress this logging for selected exception types. .. deprecated:: 4.3 Use `multi` instead. """ if isinstance(children, dict): keys = list(children.keys()) children = children.values() else: keys = None children = list(map(convert_yielded, children)) assert all(is_future(i) for i in children) unfinished_children = set(children) future = Future() if not children: future.set_result({} if keys is not None else []) def callback(f): unfinished_children.remove(f) if not unfinished_children: result_list = [] for f in children: try: result_list.append(f.result()) except Exception as e: if future.done(): if not isinstance(e, quiet_exceptions): app_log.error("Multiple exceptions in yield list", exc_info=True) else: future.set_exc_info(sys.exc_info()) if not future.done(): if keys is not None: future.set_result(dict(zip(keys, result_list))) else: future.set_result(result_list) listening = set() for f in children: if f not in listening: listening.add(f) f.add_done_callback(callback) return future
[文档]def maybe_future(x): """Converts ``x`` into a `.Future`. If ``x`` is already a `.Future`, it is simply returned; otherwise it is wrapped in a new `.Future`. This is suitable for use as ``result = yield gen.maybe_future(f())`` when you don't know whether ``f()`` returns a `.Future` or not. .. deprecated:: 4.3 This function only handles ``Futures``, not other yieldable objects. Instead of `maybe_future`, check for the non-future result types you expect (often just ``None``), and ``yield`` anything unknown. """ if is_future(x): return x else: fut = Future() fut.set_result(x) return fut
[文档]def with_timeout(timeout, future, io_loop=None, quiet_exceptions=()): """Wraps a `.Future` (or other yieldable object) in a timeout. Raises `TimeoutError` if the input future does not complete before ``timeout``, which may be specified in any form allowed by `.IOLoop.add_timeout` (i.e. a `datetime.timedelta` or an absolute time relative to `.IOLoop.time`) If the wrapped `.Future` fails after it has timed out, the exception will be logged unless it is of a type contained in ``quiet_exceptions`` (which may be an exception type or a sequence of types). Does not support `YieldPoint` subclasses. .. versionadded:: 4.0 .. versionchanged:: 4.1 Added the ``quiet_exceptions`` argument and the logging of unhandled exceptions. .. versionchanged:: 4.4 Added support for yieldable objects other than `.Future`. """ # TODO: allow YieldPoints in addition to other yieldables? # Tricky to do with stack_context semantics. # # It's tempting to optimize this by cancelling the input future on timeout # instead of creating a new one, but A) we can't know if we are the only # one waiting on the input future, so cancelling it might disrupt other # callers and B) concurrent futures can only be cancelled while they are # in the queue, so cancellation cannot reliably bound our waiting time. future = convert_yielded(future) result = Future() chain_future(future, result) if io_loop is None: io_loop = IOLoop.current() def error_callback(future): try: future.result() except Exception as e: if not isinstance(e, quiet_exceptions): app_log.error("Exception in Future %r after timeout", future, exc_info=True) def timeout_callback(): result.set_exception(TimeoutError("Timeout")) # In case the wrapped future goes on to fail, log it. future.add_done_callback(error_callback) timeout_handle = io_loop.add_timeout( timeout, timeout_callback) if isinstance(future, Future): # We know this future will resolve on the IOLoop, so we don't # need the extra thread-safety of IOLoop.add_future (and we also # don't care about StackContext here. future.add_done_callback( lambda future: io_loop.remove_timeout(timeout_handle)) else: # concurrent.futures.Futures may resolve on any thread, so we # need to route them back to the IOLoop. io_loop.add_future( future, lambda future: io_loop.remove_timeout(timeout_handle)) return result
[文档]def sleep(duration): """Return a `.Future` that resolves after the given number of seconds. When used with ``yield`` in a coroutine, this is a non-blocking analogue to `time.sleep` (which should not be used in coroutines because it is blocking):: yield gen.sleep(0.5) Note that calling this function on its own does nothing; you must wait on the `.Future` it returns (usually by yielding it). .. versionadded:: 4.1 """ f = Future() IOLoop.current().call_later(duration, lambda: f.set_result(None)) return f
_null_future = Future() _null_future.set_result(None) moment = Future() moment.__doc__ = \ """A special object which may be yielded to allow the IOLoop to run for one iteration. This is not needed in normal use but it can be helpful in long-running coroutines that are likely to yield Futures that are ready instantly. Usage: ``yield gen.moment`` .. versionadded:: 4.0 """ moment.set_result(None) class Runner(object): """Internal implementation of `tornado.gen.engine`. Maintains information about pending callbacks and their results. The results of the generator are stored in ``result_future`` (a `.TracebackFuture`) """ 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() # For efficiency, we do not create a stack context until we # reach a YieldPoint (stack contexts are required for the historical # semantics of YieldPoints, but not for Futures). When we have # done so, this field will be set and must be called at the end # of the coroutine. self.stack_context_deactivate = None if self.handle_yield(first_yielded): def register_callback(self, key): """Adds ``key`` to the list of callbacks.""" if self.pending_callbacks is None: # Lazily initialize the old-style YieldPoint data structures. self.pending_callbacks = set() self.results = {} if key in self.pending_callbacks: raise KeyReuseError("key %r is already pending" % (key,)) self.pending_callbacks.add(key) def is_ready(self, key): """Returns true if a result is available for ``key``.""" if self.pending_callbacks is None or key not in self.pending_callbacks: raise UnknownKeyError("key %r is not pending" % (key,)) return key in self.results def set_result(self, key, result): """Sets the result for ``key`` and attempts to resume the generator.""" self.results[key] = result if self.yield_point is not None and self.yield_point.is_ready(): try: self.future.set_result(self.yield_point.get_result()) except: self.future.set_exc_info(sys.exc_info()) self.yield_point = None def pop_result(self, key): """Returns the result for ``key`` and unregisters it.""" self.pending_callbacks.remove(key) return self.results.pop(key) def run(self): """Starts or resumes the generator, running until it reaches a yield point that is not ready. """ 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() if exc_info is not None: yielded = self.gen.throw(*exc_info) exc_info = None else: yielded = self.gen.send(value) if stack_context._state.contexts is not orig_stack_contexts: self.gen.throw( stack_context.StackContextInconsistentError( 'stack_context inconsistency (probably caused ' 'by yield within a "with StackContext" block)')) except (StopIteration, Return) as e: self.finished = True self.future = _null_future if self.pending_callbacks and not self.had_exception: # If we ran cleanly without waiting on all callbacks # raise an error (really more of a warning). If we # had an exception then some callbacks may have been # orphaned, so skip the check in that case. raise LeakedCallbackError( "finished without waiting for callbacks %r" % self.pending_callbacks) self.result_future.set_result(_value_from_stopiteration(e)) self.result_future = None self._deactivate_stack_context() return except Exception: self.finished = True self.future = _null_future self.result_future.set_exc_info(sys.exc_info()) self.result_future = None self._deactivate_stack_context() return if not self.handle_yield(yielded): return finally: self.running = False def handle_yield(self, yielded): # Lists containing YieldPoints require stack contexts; # other lists are handled in convert_yielded. if _contains_yieldpoint(yielded): yielded = multi(yielded) if isinstance(yielded, YieldPoint): # YieldPoints are too closely coupled to the Runner to go # through the generic convert_yielded mechanism. self.future = TracebackFuture() def start_yield_point(): try: yielded.start(self) if yielded.is_ready(): self.future.set_result( yielded.get_result()) else: self.yield_point = yielded except Exception: self.future = TracebackFuture() self.future.set_exc_info(sys.exc_info()) if self.stack_context_deactivate is None: # Start a stack context if this is the first # YieldPoint we've seen. with stack_context.ExceptionStackContext( self.handle_exception) as deactivate: self.stack_context_deactivate = deactivate def cb(): start_yield_point() self.io_loop.add_callback(cb) return False else: start_yield_point() else: try: self.future = convert_yielded(yielded) except BadYieldError: self.future = TracebackFuture() self.future.set_exc_info(sys.exc_info()) if not self.future.done() or self.future is moment: self.io_loop.add_future( self.future, lambda f: return False return True def result_callback(self, key): return stack_context.wrap(_argument_adapter( functools.partial(self.set_result, key))) def handle_exception(self, typ, value, tb): if not self.running and not self.finished: self.future = TracebackFuture() self.future.set_exc_info((typ, value, tb)) return True else: return False def _deactivate_stack_context(self): if self.stack_context_deactivate is not None: self.stack_context_deactivate() self.stack_context_deactivate = None Arguments = collections.namedtuple('Arguments', ['args', 'kwargs']) def _argument_adapter(callback): """Returns a function that when invoked runs ``callback`` with one arg. If the function returned by this function is called with exactly one argument, that argument is passed to ``callback``. Otherwise the args tuple and kwargs dict are wrapped in an `Arguments` object. """ def wrapper(*args, **kwargs): if kwargs or len(args) > 1: callback(Arguments(args, kwargs)) elif args: callback(args[0]) else: callback(None) return wrapper # Convert Awaitables into Futures. It is unfortunately possible # to have infinite recursion here if those Awaitables assume that # we're using a different coroutine runner and yield objects # we don't understand. If that happens, the solution is to # register that runner's yieldable objects with convert_yielded. if sys.version_info >= (3, 3): exec(textwrap.dedent(""" @coroutine def _wrap_awaitable(x): if hasattr(x, '__await__'): x = x.__await__() return (yield from x) """)) else: # Py2-compatible version for use with Cython. # Copied from PEP 380. @coroutine def _wrap_awaitable(x): if hasattr(x, '__await__'): _i = x.__await__() else: _i = iter(x) try: _y = next(_i) except StopIteration as _e: _r = _value_from_stopiteration(_e) else: while 1: try: _s = yield _y except GeneratorExit as _e: try: _m = _i.close except AttributeError: pass else: _m() raise _e except BaseException as _e: _x = sys.exc_info() try: _m = _i.throw except AttributeError: raise _e else: try: _y = _m(*_x) except StopIteration as _e: _r = _value_from_stopiteration(_e) break else: try: if _s is None: _y = next(_i) else: _y = _i.send(_s) except StopIteration as _e: _r = _value_from_stopiteration(_e) break raise Return(_r)
[文档]def convert_yielded(yielded): """Convert a yielded object into a `.Future`. The default implementation accepts lists, dictionaries, and Futures. If the `~functools.singledispatch` library is available, this function may be extended to support additional types. For example:: @convert_yielded.register(asyncio.Future) def _(asyncio_future): return tornado.platform.asyncio.to_tornado_future(asyncio_future) .. versionadded:: 4.1 """ # Lists and dicts containing YieldPoints were handled earlier. if isinstance(yielded, (list, dict)): return multi(yielded) elif is_future(yielded): return yielded elif isawaitable(yielded): return _wrap_awaitable(yielded) else: raise BadYieldError("yielded unknown object %r" % (yielded,))
if singledispatch is not None: convert_yielded = singledispatch(convert_yielded) try: # If we can import t.p.asyncio, do it for its side effect # (registering asyncio.Future with convert_yielded). # It's ugly to do this here, but it prevents a cryptic # infinite recursion in _wrap_awaitable. # Note that even with this, asyncio integration is unlikely # to work unless the application also configures AsyncIOLoop, # but at least the error messages in that case are more # comprehensible than a stack overflow. import tornado.platform.asyncio except ImportError: pass else: # Reference the imported module to make pyflakes happy. tornado