mirror of
https://github.com/janeczku/calibre-web
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562 lines
19 KiB
Python
562 lines
19 KiB
Python
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"""``tornado.gen`` is a generator-based interface to make it easier to
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work in an asynchronous environment. Code using the ``gen`` module
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is technically asynchronous, but it is written as a single generator
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instead of a collection of separate functions.
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For example, the following asynchronous handler::
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class AsyncHandler(RequestHandler):
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@asynchronous
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def get(self):
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http_client = AsyncHTTPClient()
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http_client.fetch("http://example.com",
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callback=self.on_fetch)
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def on_fetch(self, response):
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do_something_with_response(response)
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self.render("template.html")
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could be written with ``gen`` as::
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class GenAsyncHandler(RequestHandler):
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@gen.coroutine
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def get(self):
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http_client = AsyncHTTPClient()
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response = yield http_client.fetch("http://example.com")
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do_something_with_response(response)
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self.render("template.html")
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Most asynchronous functions in Tornado return a `.Future`;
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yielding this object returns its `~.Future.result`.
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For functions that do not return ``Futures``, `Task` works with any
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function that takes a ``callback`` keyword argument (most Tornado functions
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can be used in either style, although the ``Future`` style is preferred
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since it is both shorter and provides better exception handling)::
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@gen.coroutine
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def get(self):
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yield gen.Task(AsyncHTTPClient().fetch, "http://example.com")
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You can also yield a list of ``Futures`` and/or ``Tasks``, which will be
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started at the same time and run in parallel; a list of results will
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be returned when they are all finished::
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@gen.coroutine
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def get(self):
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http_client = AsyncHTTPClient()
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response1, response2 = yield [http_client.fetch(url1),
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http_client.fetch(url2)]
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For more complicated interfaces, `Task` can be split into two parts:
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`Callback` and `Wait`::
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class GenAsyncHandler2(RequestHandler):
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@asynchronous
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@gen.coroutine
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def get(self):
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http_client = AsyncHTTPClient()
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http_client.fetch("http://example.com",
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callback=(yield gen.Callback("key"))
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response = yield gen.Wait("key")
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do_something_with_response(response)
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self.render("template.html")
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The ``key`` argument to `Callback` and `Wait` allows for multiple
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asynchronous operations to be started at different times and proceed
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in parallel: yield several callbacks with different keys, then wait
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for them once all the async operations have started.
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The result of a `Wait` or `Task` yield expression depends on how the callback
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was run. If it was called with no arguments, the result is ``None``. If
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it was called with one argument, the result is that argument. If it was
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called with more than one argument or any keyword arguments, the result
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is an `Arguments` object, which is a named tuple ``(args, kwargs)``.
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"""
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from __future__ import absolute_import, division, print_function, with_statement
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import collections
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import functools
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import itertools
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import sys
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import types
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from tornado.concurrent import Future, TracebackFuture
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from tornado.ioloop import IOLoop
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from tornado.stack_context import ExceptionStackContext, wrap
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class KeyReuseError(Exception):
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pass
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class UnknownKeyError(Exception):
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pass
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class LeakedCallbackError(Exception):
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pass
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class BadYieldError(Exception):
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pass
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class ReturnValueIgnoredError(Exception):
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pass
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def engine(func):
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"""Callback-oriented decorator for asynchronous generators.
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This is an older interface; for new code that does not need to be
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compatible with versions of Tornado older than 3.0 the
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`coroutine` decorator is recommended instead.
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This decorator is similar to `coroutine`, except it does not
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return a `.Future` and the ``callback`` argument is not treated
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specially.
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In most cases, functions decorated with `engine` should take
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a ``callback`` argument and invoke it with their result when
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they are finished. One notable exception is the
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`~tornado.web.RequestHandler` :ref:`HTTP verb methods <verbs>`,
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which use ``self.finish()`` in place of a callback argument.
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"""
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@functools.wraps(func)
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def wrapper(*args, **kwargs):
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runner = None
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def handle_exception(typ, value, tb):
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# if the function throws an exception before its first "yield"
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# (or is not a generator at all), the Runner won't exist yet.
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# However, in that case we haven't reached anything asynchronous
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# yet, so we can just let the exception propagate.
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if runner is not None:
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return runner.handle_exception(typ, value, tb)
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return False
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with ExceptionStackContext(handle_exception) as deactivate:
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try:
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result = func(*args, **kwargs)
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except (Return, StopIteration) as e:
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result = getattr(e, 'value', None)
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else:
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if isinstance(result, types.GeneratorType):
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def final_callback(value):
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if value is not None:
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raise ReturnValueIgnoredError(
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"@gen.engine functions cannot return values: "
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"%r" % (value,))
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assert value is None
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deactivate()
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runner = Runner(result, final_callback)
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runner.run()
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return
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if result is not None:
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raise ReturnValueIgnoredError(
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"@gen.engine functions cannot return values: %r" %
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(result,))
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deactivate()
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# no yield, so we're done
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return wrapper
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def coroutine(func):
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"""Decorator for asynchronous generators.
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Any generator that yields objects from this module must be wrapped
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in either this decorator or `engine`.
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Coroutines may "return" by raising the special exception
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`Return(value) <Return>`. In Python 3.3+, it is also possible for
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the function to simply use the ``return value`` statement (prior to
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Python 3.3 generators were not allowed to also return values).
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In all versions of Python a coroutine that simply wishes to exit
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early may use the ``return`` statement without a value.
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Functions with this decorator return a `.Future`. Additionally,
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they may be called with a ``callback`` keyword argument, which
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will be invoked with the future's result when it resolves. If the
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coroutine fails, the callback will not be run and an exception
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will be raised into the surrounding `.StackContext`. The
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``callback`` argument is not visible inside the decorated
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function; it is handled by the decorator itself.
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From the caller's perspective, ``@gen.coroutine`` is similar to
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the combination of ``@return_future`` and ``@gen.engine``.
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"""
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@functools.wraps(func)
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def wrapper(*args, **kwargs):
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runner = None
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future = TracebackFuture()
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if 'callback' in kwargs:
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callback = kwargs.pop('callback')
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IOLoop.current().add_future(
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future, lambda future: callback(future.result()))
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def handle_exception(typ, value, tb):
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try:
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if runner is not None and runner.handle_exception(typ, value, tb):
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return True
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except Exception:
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typ, value, tb = sys.exc_info()
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future.set_exc_info((typ, value, tb))
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return True
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with ExceptionStackContext(handle_exception) as deactivate:
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try:
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result = func(*args, **kwargs)
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except (Return, StopIteration) as e:
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result = getattr(e, 'value', None)
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except Exception:
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deactivate()
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future.set_exc_info(sys.exc_info())
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return future
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else:
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if isinstance(result, types.GeneratorType):
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def final_callback(value):
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deactivate()
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future.set_result(value)
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runner = Runner(result, final_callback)
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runner.run()
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return future
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deactivate()
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future.set_result(result)
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return future
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return wrapper
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class Return(Exception):
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"""Special exception to return a value from a `coroutine`.
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If this exception is raised, its value argument is used as the
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result of the coroutine::
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@gen.coroutine
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def fetch_json(url):
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response = yield AsyncHTTPClient().fetch(url)
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raise gen.Return(json_decode(response.body))
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In Python 3.3, this exception is no longer necessary: the ``return``
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statement can be used directly to return a value (previously
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``yield`` and ``return`` with a value could not be combined in the
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same function).
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By analogy with the return statement, the value argument is optional,
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but it is never necessary to ``raise gen.Return()``. The ``return``
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statement can be used with no arguments instead.
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"""
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def __init__(self, value=None):
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super(Return, self).__init__()
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self.value = value
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class YieldPoint(object):
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"""Base class for objects that may be yielded from the generator.
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Applications do not normally need to use this class, but it may be
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subclassed to provide additional yielding behavior.
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"""
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def start(self, runner):
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"""Called by the runner after the generator has yielded.
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No other methods will be called on this object before ``start``.
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"""
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raise NotImplementedError()
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def is_ready(self):
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"""Called by the runner to determine whether to resume the generator.
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Returns a boolean; may be called more than once.
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"""
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raise NotImplementedError()
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def get_result(self):
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"""Returns the value to use as the result of the yield expression.
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This method will only be called once, and only after `is_ready`
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has returned true.
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"""
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raise NotImplementedError()
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class Callback(YieldPoint):
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"""Returns a callable object that will allow a matching `Wait` to proceed.
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The key may be any value suitable for use as a dictionary key, and is
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used to match ``Callbacks`` to their corresponding ``Waits``. The key
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must be unique among outstanding callbacks within a single run of the
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generator function, but may be reused across different runs of the same
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function (so constants generally work fine).
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The callback may be called with zero or one arguments; if an argument
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is given it will be returned by `Wait`.
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"""
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def __init__(self, key):
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self.key = key
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def start(self, runner):
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self.runner = runner
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runner.register_callback(self.key)
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def is_ready(self):
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return True
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def get_result(self):
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return self.runner.result_callback(self.key)
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class Wait(YieldPoint):
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"""Returns the argument passed to the result of a previous `Callback`."""
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def __init__(self, key):
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self.key = key
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def start(self, runner):
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self.runner = runner
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def is_ready(self):
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return self.runner.is_ready(self.key)
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def get_result(self):
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return self.runner.pop_result(self.key)
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class WaitAll(YieldPoint):
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"""Returns the results of multiple previous `Callbacks <Callback>`.
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The argument is a sequence of `Callback` keys, and the result is
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a list of results in the same order.
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`WaitAll` is equivalent to yielding a list of `Wait` objects.
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"""
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def __init__(self, keys):
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self.keys = keys
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def start(self, runner):
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self.runner = runner
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def is_ready(self):
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return all(self.runner.is_ready(key) for key in self.keys)
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def get_result(self):
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return [self.runner.pop_result(key) for key in self.keys]
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class Task(YieldPoint):
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"""Runs a single asynchronous operation.
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Takes a function (and optional additional arguments) and runs it with
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those arguments plus a ``callback`` keyword argument. The argument passed
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to the callback is returned as the result of the yield expression.
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A `Task` is equivalent to a `Callback`/`Wait` pair (with a unique
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key generated automatically)::
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result = yield gen.Task(func, args)
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func(args, callback=(yield gen.Callback(key)))
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result = yield gen.Wait(key)
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"""
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def __init__(self, func, *args, **kwargs):
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assert "callback" not in kwargs
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self.args = args
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self.kwargs = kwargs
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self.func = func
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def start(self, runner):
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self.runner = runner
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self.key = object()
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runner.register_callback(self.key)
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self.kwargs["callback"] = runner.result_callback(self.key)
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self.func(*self.args, **self.kwargs)
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def is_ready(self):
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return self.runner.is_ready(self.key)
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def get_result(self):
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return self.runner.pop_result(self.key)
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class YieldFuture(YieldPoint):
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def __init__(self, future, io_loop=None):
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self.future = future
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self.io_loop = io_loop or IOLoop.current()
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def start(self, runner):
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self.runner = runner
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self.key = object()
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runner.register_callback(self.key)
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self.io_loop.add_future(self.future, runner.result_callback(self.key))
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def is_ready(self):
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return self.runner.is_ready(self.key)
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def get_result(self):
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return self.runner.pop_result(self.key).result()
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class Multi(YieldPoint):
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"""Runs multiple asynchronous operations in parallel.
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Takes a list of ``Tasks`` or other ``YieldPoints`` and returns a list of
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their responses. It is not necessary to call `Multi` explicitly,
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since the engine will do so automatically when the generator yields
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a list of ``YieldPoints``.
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"""
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def __init__(self, children):
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self.children = []
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for i in children:
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if isinstance(i, Future):
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i = YieldFuture(i)
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self.children.append(i)
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assert all(isinstance(i, YieldPoint) for i in self.children)
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self.unfinished_children = set(self.children)
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def start(self, runner):
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for i in self.children:
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i.start(runner)
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def is_ready(self):
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finished = list(itertools.takewhile(
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lambda i: i.is_ready(), self.unfinished_children))
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self.unfinished_children.difference_update(finished)
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return not self.unfinished_children
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def get_result(self):
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return [i.get_result() for i in self.children]
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class _NullYieldPoint(YieldPoint):
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def start(self, runner):
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pass
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def is_ready(self):
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return True
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def get_result(self):
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return None
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_null_yield_point = _NullYieldPoint()
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class Runner(object):
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"""Internal implementation of `tornado.gen.engine`.
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Maintains information about pending callbacks and their results.
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``final_callback`` is run after the generator exits.
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"""
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def __init__(self, gen, final_callback):
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self.gen = gen
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self.final_callback = final_callback
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self.yield_point = _null_yield_point
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self.pending_callbacks = set()
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self.results = {}
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self.running = False
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self.finished = False
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self.exc_info = None
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self.had_exception = False
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def register_callback(self, key):
|
||
|
"""Adds ``key`` to the list of callbacks."""
|
||
|
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 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
|
||
|
self.run()
|
||
|
|
||
|
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:
|
||
|
if self.exc_info is None:
|
||
|
try:
|
||
|
if not self.yield_point.is_ready():
|
||
|
return
|
||
|
next = self.yield_point.get_result()
|
||
|
self.yield_point = None
|
||
|
except Exception:
|
||
|
self.exc_info = sys.exc_info()
|
||
|
try:
|
||
|
if self.exc_info is not None:
|
||
|
self.had_exception = True
|
||
|
exc_info = self.exc_info
|
||
|
self.exc_info = None
|
||
|
yielded = self.gen.throw(*exc_info)
|
||
|
else:
|
||
|
yielded = self.gen.send(next)
|
||
|
except (StopIteration, Return) as e:
|
||
|
self.finished = True
|
||
|
self.yield_point = _null_yield_point
|
||
|
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.final_callback(getattr(e, 'value', None))
|
||
|
self.final_callback = None
|
||
|
return
|
||
|
except Exception:
|
||
|
self.finished = True
|
||
|
self.yield_point = _null_yield_point
|
||
|
raise
|
||
|
if isinstance(yielded, list):
|
||
|
yielded = Multi(yielded)
|
||
|
elif isinstance(yielded, Future):
|
||
|
yielded = YieldFuture(yielded)
|
||
|
if isinstance(yielded, YieldPoint):
|
||
|
self.yield_point = yielded
|
||
|
try:
|
||
|
self.yield_point.start(self)
|
||
|
except Exception:
|
||
|
self.exc_info = sys.exc_info()
|
||
|
else:
|
||
|
self.exc_info = (BadYieldError(
|
||
|
"yielded unknown object %r" % (yielded,)),)
|
||
|
finally:
|
||
|
self.running = False
|
||
|
|
||
|
def result_callback(self, key):
|
||
|
def inner(*args, **kwargs):
|
||
|
if kwargs or len(args) > 1:
|
||
|
result = Arguments(args, kwargs)
|
||
|
elif args:
|
||
|
result = args[0]
|
||
|
else:
|
||
|
result = None
|
||
|
self.set_result(key, result)
|
||
|
return wrap(inner)
|
||
|
|
||
|
def handle_exception(self, typ, value, tb):
|
||
|
if not self.running and not self.finished:
|
||
|
self.exc_info = (typ, value, tb)
|
||
|
self.run()
|
||
|
return True
|
||
|
else:
|
||
|
return False
|
||
|
|
||
|
Arguments = collections.namedtuple('Arguments', ['args', 'kwargs'])
|