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calibre-web/lib/tornado/gen.py

562 lines
19 KiB
Python

"""``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`.
For functions that do not return ``Futures``, `Task` works with any
function that takes a ``callback`` keyword argument (most Tornado functions
can be used in either style, although the ``Future`` style is preferred
since it is both shorter and provides better exception handling)::
@gen.coroutine
def get(self):
yield gen.Task(AsyncHTTPClient().fetch, "http://example.com")
You can also yield a list of ``Futures`` and/or ``Tasks``, which will be
started at the same time and run in parallel; a list 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)]
For more complicated interfaces, `Task` can be split into two parts:
`Callback` and `Wait`::
class GenAsyncHandler2(RequestHandler):
@asynchronous
@gen.coroutine
def get(self):
http_client = AsyncHTTPClient()
http_client.fetch("http://example.com",
callback=(yield gen.Callback("key"))
response = yield gen.Wait("key")
do_something_with_response(response)
self.render("template.html")
The ``key`` argument to `Callback` and `Wait` allows for multiple
asynchronous operations to be started at different times and proceed
in parallel: yield several callbacks with different keys, then wait
for them once all the async operations have started.
The result of a `Wait` or `Task` yield expression depends on how the callback
was run. If it was called with no arguments, the result is ``None``. If
it was called with one argument, the result is that argument. If it was
called with more than one argument or any keyword arguments, the result
is an `Arguments` object, which is a named tuple ``(args, kwargs)``.
"""
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
from tornado.ioloop import IOLoop
from tornado.stack_context import ExceptionStackContext, wrap
class KeyReuseError(Exception):
pass
class UnknownKeyError(Exception):
pass
class LeakedCallbackError(Exception):
pass
class BadYieldError(Exception):
pass
class ReturnValueIgnoredError(Exception):
pass
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.
"""
@functools.wraps(func)
def wrapper(*args, **kwargs):
runner = None
def handle_exception(typ, value, tb):
# if the function throws an exception before its first "yield"
# (or is not a generator at all), the Runner won't exist yet.
# However, in that case we haven't reached anything asynchronous
# yet, so we can just let the exception propagate.
if runner is not None:
return runner.handle_exception(typ, value, tb)
return False
with ExceptionStackContext(handle_exception) as deactivate:
try:
result = func(*args, **kwargs)
except (Return, StopIteration) as e:
result = getattr(e, 'value', None)
else:
if isinstance(result, types.GeneratorType):
def final_callback(value):
if value is not None:
raise ReturnValueIgnoredError(
"@gen.engine functions cannot return values: "
"%r" % (value,))
assert value is None
deactivate()
runner = Runner(result, final_callback)
runner.run()
return
if result is not None:
raise ReturnValueIgnoredError(
"@gen.engine functions cannot return values: %r" %
(result,))
deactivate()
# no yield, so we're done
return wrapper
def coroutine(func):
"""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``.
"""
@functools.wraps(func)
def wrapper(*args, **kwargs):
runner = None
future = TracebackFuture()
if 'callback' in kwargs:
callback = kwargs.pop('callback')
IOLoop.current().add_future(
future, lambda future: callback(future.result()))
def handle_exception(typ, value, tb):
try:
if runner is not None and runner.handle_exception(typ, value, tb):
return True
except Exception:
typ, value, tb = sys.exc_info()
future.set_exc_info((typ, value, tb))
return True
with ExceptionStackContext(handle_exception) as deactivate:
try:
result = func(*args, **kwargs)
except (Return, StopIteration) as e:
result = getattr(e, 'value', None)
except Exception:
deactivate()
future.set_exc_info(sys.exc_info())
return future
else:
if isinstance(result, types.GeneratorType):
def final_callback(value):
deactivate()
future.set_result(value)
runner = Runner(result, final_callback)
runner.run()
return future
deactivate()
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.
Applications do not normally need to use this class, but it may be
subclassed to provide additional yielding behavior.
"""
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`.
"""
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`."""
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.
"""
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]
class Task(YieldPoint):
"""Runs a single asynchronous operation.
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.
A `Task` is equivalent to a `Callback`/`Wait` pair (with a unique
key generated automatically)::
result = yield gen.Task(func, args)
func(args, callback=(yield gen.Callback(key)))
result = yield gen.Wait(key)
"""
def __init__(self, func, *args, **kwargs):
assert "callback" not in kwargs
self.args = args
self.kwargs = kwargs
self.func = func
def start(self, runner):
self.runner = runner
self.key = object()
runner.register_callback(self.key)
self.kwargs["callback"] = runner.result_callback(self.key)
self.func(*self.args, **self.kwargs)
def is_ready(self):
return self.runner.is_ready(self.key)
def get_result(self):
return self.runner.pop_result(self.key)
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):
self.runner = runner
self.key = object()
runner.register_callback(self.key)
self.io_loop.add_future(self.future, runner.result_callback(self.key))
def is_ready(self):
return self.runner.is_ready(self.key)
def get_result(self):
return self.runner.pop_result(self.key).result()
class Multi(YieldPoint):
"""Runs multiple asynchronous operations in parallel.
Takes a list of ``Tasks`` or other ``YieldPoints`` 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``.
"""
def __init__(self, children):
self.children = []
for i in children:
if isinstance(i, Future):
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):
return [i.get_result() for i in self.children]
class _NullYieldPoint(YieldPoint):
def start(self, runner):
pass
def is_ready(self):
return True
def get_result(self):
return None
_null_yield_point = _NullYieldPoint()
class Runner(object):
"""Internal implementation of `tornado.gen.engine`.
Maintains information about pending callbacks and their results.
``final_callback`` is run after the generator exits.
"""
def __init__(self, gen, final_callback):
self.gen = gen
self.final_callback = final_callback
self.yield_point = _null_yield_point
self.pending_callbacks = set()
self.results = {}
self.running = False
self.finished = False
self.exc_info = None
self.had_exception = False
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'])