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SickRage/tornado/gen.py

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"""``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::
class AsyncHandler(RequestHandler):
@asynchronous
def get(self):
http_client = AsyncHTTPClient()
http_client.fetch("http://example.com",
callback=self.on_fetch)
def on_fetch(self, response):
do_something_with_response(response)
self.render("template.html")
could be written with ``gen`` as::
class GenAsyncHandler(RequestHandler):
@gen.coroutine
def get(self):
http_client = AsyncHTTPClient()
response = yield http_client.fetch("http://example.com")
do_something_with_response(response)
self.render("template.html")
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::
@gen.coroutine
def get(self):
http_client = AsyncHTTPClient()
response1, response2 = yield [http_client.fetch(url1),
http_client.fetch(url2)]
response_dict = yield dict(response3=http_client.fetch(url3),
response4=http_client.fetch(url4))
response3 = response_dict['response3']
response4 = response_dict['response4']
.. versionchanged:: 3.2
Dict support added.
"""
from __future__ import absolute_import, division, print_function, with_statement
import collections
import functools
import itertools
import sys
import types
from tornado.concurrent import Future, TracebackFuture, is_future, chain_future
from tornado.ioloop import IOLoop
from tornado import stack_context
class KeyReuseError(Exception):
pass
class UnknownKeyError(Exception):
pass
class LeakedCallbackError(Exception):
pass
class BadYieldError(Exception):
pass
class ReturnValueIgnoredError(Exception):
pass
class TimeoutError(Exception):
"""Exception raised by ``with_timeout``."""
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
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``.
"""
@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):
# Inline the first iteration of Runner.run. 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(getattr(e, 'value', None))
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
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
class YieldPoint(object):
"""Base class for objects that may be yielded from the generator.
.. deprecated:: 4.0
Use `Futures <.Future>` instead.
"""
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()
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()
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()
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)
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)
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]
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):
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 = 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
class Multi(YieldPoint):
"""Runs multiple asynchronous operations in parallel.
Takes a list of ``YieldPoints`` or ``Futures`` and returns a list of
their responses. It is not necessary to call `Multi` explicitly,
since the engine will do so automatically when the generator yields
a list of ``YieldPoints`` or a mixture of ``YieldPoints`` and ``Futures``.
Instead of a list, the argument may also be a dictionary whose values are
Futures, in which case a parallel dictionary is returned mapping the same
keys to their results.
"""
def __init__(self, children):
self.keys = None
if isinstance(children, dict):
self.keys = list(children.keys())
children = children.values()
self.children = []
for i in children:
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)
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 = (i.get_result() for i in self.children)
if self.keys is not None:
return dict(zip(self.keys, result))
else:
return list(result)
def multi_future(children):
"""Wait for multiple asynchronous futures in parallel.
Takes a list of ``Futures`` (but *not* other ``YieldPoints``) and returns
a new Future that resolves when all the other Futures are done.
If all the ``Futures`` succeeded, the returned Future's result is a list
of their results. If any failed, the returned Future raises the exception
of the first one to fail.
Instead of a list, the argument may also be a dictionary whose values are
Futures, in which case a parallel dictionary is returned mapping the same
keys to their results.
It is not necessary to call `multi_future` explcitly, since the engine will
do so automatically when the generator yields a list of `Futures`.
This function is faster than the `Multi` `YieldPoint` because it does not
require the creation of a stack context.
.. versionadded:: 4.0
"""
if isinstance(children, dict):
keys = list(children.keys())
children = children.values()
else:
keys = None
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:
try:
result_list = [i.result() for i in children]
except Exception:
future.set_exc_info(sys.exc_info())
else:
if keys is not None:
future.set_result(dict(zip(keys, result_list)))
else:
future.set_result(result_list)
for f in children:
f.add_done_callback(callback)
return future
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.
"""
if is_future(x):
return x
else:
fut = Future()
fut.set_result(x)
return fut
def with_timeout(timeout, future, io_loop=None):
"""Wraps a `.Future` 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`)
Currently only supports Futures, not other `YieldPoint` classes.
.. versionadded:: 4.0
"""
# TODO: allow yield points in addition to futures?
# 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.
result = Future()
chain_future(future, result)
if io_loop is None:
io_loop = IOLoop.current()
timeout_handle = io_loop.add_timeout(
timeout,
lambda: result.set_exception(TimeoutError("Timeout")))
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
_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):
self.run()
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
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:
future = self.future
if not future.done():
return
self.future = None
try:
orig_stack_contexts = stack_context._state.contexts
try:
value = future.result()
except Exception:
self.had_exception = True
yielded = self.gen.throw(*sys.exc_info())
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(getattr(e, 'value', None))
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):
if isinstance(yielded, list):
if all(is_future(f) for f in yielded):
yielded = multi_future(yielded)
else:
yielded = Multi(yielded)
elif isinstance(yielded, dict):
if all(is_future(f) for f in yielded.values()):
yielded = multi_future(yielded)
else:
yielded = Multi(yielded)
if isinstance(yielded, YieldPoint):
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.run()
self.io_loop.add_callback(cb)
return False
else:
start_yield_point()
elif is_future(yielded):
self.future = yielded
if not self.future.done() or self.future is moment:
self.io_loop.add_future(
self.future, lambda f: self.run())
return False
else:
self.future = TracebackFuture()
self.future.set_exception(BadYieldError(
"yielded unknown object %r" % (yielded,)))
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))
self.run()
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