Source code for tornado.ioloop

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# Copyright 2009 Facebook
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# Licensed under the Apache License, Version 2.0 (the "License"); you may
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"""An I/O event loop for non-blocking sockets.

On Python 3, `.IOLoop` is a wrapper around the `asyncio` event loop.

Typical applications will use a single `IOLoop` object, accessed via
`IOLoop.current` class method. The `IOLoop.start` method (or
equivalently, `asyncio.AbstractEventLoop.run_forever`) should usually
be called at the end of the ``main()`` function. Atypical applications
may use more than one `IOLoop`, such as one `IOLoop` per thread, or
per `unittest` case.

In addition to I/O events, the `IOLoop` can also schedule time-based
events. `IOLoop.add_timeout` is a non-blocking alternative to
`time.sleep`.

"""

import asyncio
from concurrent.futures import ThreadPoolExecutor
import datetime
import logging
import numbers
import os
import sys
import time
import math
import random

from tornado.concurrent import Future, is_future, chain_future, future_set_exc_info, future_add_done_callback  # noqa: E501
from tornado.log import app_log
from tornado.util import Configurable, TimeoutError, unicode_type, import_object


[docs]class IOLoop(Configurable): """A level-triggered I/O loop. On Python 3, `IOLoop` is a wrapper around the `asyncio` event loop. On Python 2, it uses ``epoll`` (Linux) or ``kqueue`` (BSD and Mac OS X) if they are available, or else we fall back on select(). If you are implementing a system that needs to handle thousands of simultaneous connections, you should use a system that supports either ``epoll`` or ``kqueue``. Example usage for a simple TCP server: .. testcode:: import errno import functools import socket import tornado.ioloop from tornado import gen from tornado.iostream import IOStream async def handle_connection(connection, address): stream = IOStream(connection) message = await stream.read_until_close() print("message from client:", message.decode().strip()) def connection_ready(sock, fd, events): while True: try: connection, address = sock.accept() except socket.error as e: if e.args[0] not in (errno.EWOULDBLOCK, errno.EAGAIN): raise return connection.setblocking(0) handle_connection(connection, address) if __name__ == '__main__': sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM, 0) sock.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEADDR, 1) sock.setblocking(0) sock.bind(("", 8888)) sock.listen(128) io_loop = tornado.ioloop.IOLoop.current() callback = functools.partial(connection_ready, sock) io_loop.add_handler(sock.fileno(), callback, io_loop.READ) io_loop.start() .. testoutput:: :hide: By default, a newly-constructed `IOLoop` becomes the thread's current `IOLoop`, unless there already is a current `IOLoop`. This behavior can be controlled with the ``make_current`` argument to the `IOLoop` constructor: if ``make_current=True``, the new `IOLoop` will always try to become current and it raises an error if there is already a current instance. If ``make_current=False``, the new `IOLoop` will not try to become current. In general, an `IOLoop` cannot survive a fork or be shared across processes in any way. When multiple processes are being used, each process should create its own `IOLoop`, which also implies that any objects which depend on the `IOLoop` (such as `.AsyncHTTPClient`) must also be created in the child processes. As a guideline, anything that starts processes (including the `tornado.process` and `multiprocessing` modules) should do so as early as possible, ideally the first thing the application does after loading its configuration in ``main()``. .. versionchanged:: 4.2 Added the ``make_current`` keyword argument to the `IOLoop` constructor. .. versionchanged:: 5.0 Uses the `asyncio` event loop by default. The ``IOLoop.configure`` method cannot be used on Python 3 except to redundantly specify the `asyncio` event loop. """ # These constants were originally based on constants from the epoll module. NONE = 0 READ = 0x001 WRITE = 0x004 ERROR = 0x018 # In Python 3, _ioloop_for_asyncio maps from asyncio loops to IOLoops. _ioloop_for_asyncio = dict() @classmethod def configure(cls, impl, **kwargs): if asyncio is not None: from tornado.platform.asyncio import BaseAsyncIOLoop if isinstance(impl, (str, unicode_type)): impl = import_object(impl) if not issubclass(impl, BaseAsyncIOLoop): raise RuntimeError( "only AsyncIOLoop is allowed when asyncio is available") super(IOLoop, cls).configure(impl, **kwargs)
[docs] @staticmethod def instance(): """Deprecated alias for `IOLoop.current()`. .. versionchanged:: 5.0 Previously, this method returned a global singleton `IOLoop`, in contrast with the per-thread `IOLoop` returned by `current()`. In nearly all cases the two were the same (when they differed, it was generally used from non-Tornado threads to communicate back to the main thread's `IOLoop`). This distinction is not present in `asyncio`, so in order to facilitate integration with that package `instance()` was changed to be an alias to `current()`. Applications using the cross-thread communications aspect of `instance()` should instead set their own global variable to point to the `IOLoop` they want to use. .. deprecated:: 5.0 """ return IOLoop.current()
[docs] def install(self): """Deprecated alias for `make_current()`. .. versionchanged:: 5.0 Previously, this method would set this `IOLoop` as the global singleton used by `IOLoop.instance()`. Now that `instance()` is an alias for `current()`, `install()` is an alias for `make_current()`. .. deprecated:: 5.0 """ self.make_current()
[docs] @staticmethod def clear_instance(): """Deprecated alias for `clear_current()`. .. versionchanged:: 5.0 Previously, this method would clear the `IOLoop` used as the global singleton by `IOLoop.instance()`. Now that `instance()` is an alias for `current()`, `clear_instance()` is an alias for `clear_current()`. .. deprecated:: 5.0 """ IOLoop.clear_current()
[docs] @staticmethod def current(instance=True): """Returns the current thread's `IOLoop`. If an `IOLoop` is currently running or has been marked as current by `make_current`, returns that instance. If there is no current `IOLoop` and ``instance`` is true, creates one. .. versionchanged:: 4.1 Added ``instance`` argument to control the fallback to `IOLoop.instance()`. .. versionchanged:: 5.0 On Python 3, control of the current `IOLoop` is delegated to `asyncio`, with this and other methods as pass-through accessors. The ``instance`` argument now controls whether an `IOLoop` is created automatically when there is none, instead of whether we fall back to `IOLoop.instance()` (which is now an alias for this method). ``instance=False`` is deprecated, since even if we do not create an `IOLoop`, this method may initialize the asyncio loop. """ try: loop = asyncio.get_event_loop() except (RuntimeError, AssertionError): if not instance: return None raise try: return IOLoop._ioloop_for_asyncio[loop] except KeyError: if instance: from tornado.platform.asyncio import AsyncIOMainLoop current = AsyncIOMainLoop(make_current=True) else: current = None return current
[docs] def make_current(self): """Makes this the `IOLoop` for the current thread. An `IOLoop` automatically becomes current for its thread when it is started, but it is sometimes useful to call `make_current` explicitly before starting the `IOLoop`, so that code run at startup time can find the right instance. .. versionchanged:: 4.1 An `IOLoop` created while there is no current `IOLoop` will automatically become current. .. versionchanged:: 5.0 This method also sets the current `asyncio` event loop. """ # The asyncio event loops override this method. raise NotImplementedError()
[docs] @staticmethod def clear_current(): """Clears the `IOLoop` for the current thread. Intended primarily for use by test frameworks in between tests. .. versionchanged:: 5.0 This method also clears the current `asyncio` event loop. """ old = IOLoop.current(instance=False) if old is not None: old._clear_current_hook() if asyncio is None: IOLoop._current.instance = None
def _clear_current_hook(self): """Instance method called when an IOLoop ceases to be current. May be overridden by subclasses as a counterpart to make_current. """ pass @classmethod def configurable_base(cls): return IOLoop @classmethod def configurable_default(cls): from tornado.platform.asyncio import AsyncIOLoop return AsyncIOLoop
[docs] def initialize(self, make_current=None): if make_current is None: if IOLoop.current(instance=False) is None: self.make_current() elif make_current: current = IOLoop.current(instance=False) # AsyncIO loops can already be current by this point. if current is not None and current is not self: raise RuntimeError("current IOLoop already exists") self.make_current()
[docs] def close(self, all_fds=False): """Closes the `IOLoop`, freeing any resources used. If ``all_fds`` is true, all file descriptors registered on the IOLoop will be closed (not just the ones created by the `IOLoop` itself). Many applications will only use a single `IOLoop` that runs for the entire lifetime of the process. In that case closing the `IOLoop` is not necessary since everything will be cleaned up when the process exits. `IOLoop.close` is provided mainly for scenarios such as unit tests, which create and destroy a large number of ``IOLoops``. An `IOLoop` must be completely stopped before it can be closed. This means that `IOLoop.stop()` must be called *and* `IOLoop.start()` must be allowed to return before attempting to call `IOLoop.close()`. Therefore the call to `close` will usually appear just after the call to `start` rather than near the call to `stop`. .. versionchanged:: 3.1 If the `IOLoop` implementation supports non-integer objects for "file descriptors", those objects will have their ``close`` method when ``all_fds`` is true. """ raise NotImplementedError()
[docs] def add_handler(self, fd, handler, events): """Registers the given handler to receive the given events for ``fd``. The ``fd`` argument may either be an integer file descriptor or a file-like object with a ``fileno()`` method (and optionally a ``close()`` method, which may be called when the `IOLoop` is shut down). The ``events`` argument is a bitwise or of the constants ``IOLoop.READ``, ``IOLoop.WRITE``, and ``IOLoop.ERROR``. When an event occurs, ``handler(fd, events)`` will be run. .. versionchanged:: 4.0 Added the ability to pass file-like objects in addition to raw file descriptors. """ raise NotImplementedError()
[docs] def update_handler(self, fd, events): """Changes the events we listen for ``fd``. .. versionchanged:: 4.0 Added the ability to pass file-like objects in addition to raw file descriptors. """ raise NotImplementedError()
[docs] def remove_handler(self, fd): """Stop listening for events on ``fd``. .. versionchanged:: 4.0 Added the ability to pass file-like objects in addition to raw file descriptors. """ raise NotImplementedError()
[docs] def start(self): """Starts the I/O loop. The loop will run until one of the callbacks calls `stop()`, which will make the loop stop after the current event iteration completes. """ raise NotImplementedError()
def _setup_logging(self): """The IOLoop catches and logs exceptions, so it's important that log output be visible. However, python's default behavior for non-root loggers (prior to python 3.2) is to print an unhelpful "no handlers could be found" message rather than the actual log entry, so we must explicitly configure logging if we've made it this far without anything. This method should be called from start() in subclasses. """ if not any([logging.getLogger().handlers, logging.getLogger('tornado').handlers, logging.getLogger('tornado.application').handlers]): logging.basicConfig()
[docs] def stop(self): """Stop the I/O loop. If the event loop is not currently running, the next call to `start()` will return immediately. Note that even after `stop` has been called, the `IOLoop` is not completely stopped until `IOLoop.start` has also returned. Some work that was scheduled before the call to `stop` may still be run before the `IOLoop` shuts down. """ raise NotImplementedError()
[docs] def run_sync(self, func, timeout=None): """Starts the `IOLoop`, runs the given function, and stops the loop. The function must return either an awaitable object or ``None``. If the function returns an awaitable object, the `IOLoop` will run until the awaitable is resolved (and `run_sync()` will return the awaitable's result). If it raises an exception, the `IOLoop` will stop and the exception will be re-raised to the caller. The keyword-only argument ``timeout`` may be used to set a maximum duration for the function. If the timeout expires, a `tornado.util.TimeoutError` is raised. This method is useful to allow asynchronous calls in a ``main()`` function:: async def main(): # do stuff... if __name__ == '__main__': IOLoop.current().run_sync(main) .. versionchanged:: 4.3 Returning a non-``None``, non-awaitable value is now an error. .. versionchanged:: 5.0 If a timeout occurs, the ``func`` coroutine will be cancelled. """ future_cell = [None] def run(): try: result = func() if result is not None: from tornado.gen import convert_yielded result = convert_yielded(result) except Exception: future_cell[0] = Future() future_set_exc_info(future_cell[0], sys.exc_info()) else: if is_future(result): future_cell[0] = result else: future_cell[0] = Future() future_cell[0].set_result(result) self.add_future(future_cell[0], lambda future: self.stop()) self.add_callback(run) if timeout is not None: def timeout_callback(): # If we can cancel the future, do so and wait on it. If not, # Just stop the loop and return with the task still pending. # (If we neither cancel nor wait for the task, a warning # will be logged). if not future_cell[0].cancel(): self.stop() timeout_handle = self.add_timeout(self.time() + timeout, timeout_callback) self.start() if timeout is not None: self.remove_timeout(timeout_handle) if future_cell[0].cancelled() or not future_cell[0].done(): raise TimeoutError('Operation timed out after %s seconds' % timeout) return future_cell[0].result()
[docs] def time(self): """Returns the current time according to the `IOLoop`'s clock. The return value is a floating-point number relative to an unspecified time in the past. By default, the `IOLoop`'s time function is `time.time`. However, it may be configured to use e.g. `time.monotonic` instead. Calls to `add_timeout` that pass a number instead of a `datetime.timedelta` should use this function to compute the appropriate time, so they can work no matter what time function is chosen. """ return time.time()
[docs] def add_timeout(self, deadline, callback, *args, **kwargs): """Runs the ``callback`` at the time ``deadline`` from the I/O loop. Returns an opaque handle that may be passed to `remove_timeout` to cancel. ``deadline`` may be a number denoting a time (on the same scale as `IOLoop.time`, normally `time.time`), or a `datetime.timedelta` object for a deadline relative to the current time. Since Tornado 4.0, `call_later` is a more convenient alternative for the relative case since it does not require a timedelta object. Note that it is not safe to call `add_timeout` from other threads. Instead, you must use `add_callback` to transfer control to the `IOLoop`'s thread, and then call `add_timeout` from there. Subclasses of IOLoop must implement either `add_timeout` or `call_at`; the default implementations of each will call the other. `call_at` is usually easier to implement, but subclasses that wish to maintain compatibility with Tornado versions prior to 4.0 must use `add_timeout` instead. .. versionchanged:: 4.0 Now passes through ``*args`` and ``**kwargs`` to the callback. """ if isinstance(deadline, numbers.Real): return self.call_at(deadline, callback, *args, **kwargs) elif isinstance(deadline, datetime.timedelta): return self.call_at(self.time() + deadline.total_seconds(), callback, *args, **kwargs) else: raise TypeError("Unsupported deadline %r" % deadline)
[docs] def call_later(self, delay, callback, *args, **kwargs): """Runs the ``callback`` after ``delay`` seconds have passed. Returns an opaque handle that may be passed to `remove_timeout` to cancel. Note that unlike the `asyncio` method of the same name, the returned object does not have a ``cancel()`` method. See `add_timeout` for comments on thread-safety and subclassing. .. versionadded:: 4.0 """ return self.call_at(self.time() + delay, callback, *args, **kwargs)
[docs] def call_at(self, when, callback, *args, **kwargs): """Runs the ``callback`` at the absolute time designated by ``when``. ``when`` must be a number using the same reference point as `IOLoop.time`. Returns an opaque handle that may be passed to `remove_timeout` to cancel. Note that unlike the `asyncio` method of the same name, the returned object does not have a ``cancel()`` method. See `add_timeout` for comments on thread-safety and subclassing. .. versionadded:: 4.0 """ return self.add_timeout(when, callback, *args, **kwargs)
[docs] def remove_timeout(self, timeout): """Cancels a pending timeout. The argument is a handle as returned by `add_timeout`. It is safe to call `remove_timeout` even if the callback has already been run. """ raise NotImplementedError()
[docs] def add_callback(self, callback, *args, **kwargs): """Calls the given callback on the next I/O loop iteration. It is safe to call this method from any thread at any time, except from a signal handler. Note that this is the **only** method in `IOLoop` that makes this thread-safety guarantee; all other interaction with the `IOLoop` must be done from that `IOLoop`'s thread. `add_callback()` may be used to transfer control from other threads to the `IOLoop`'s thread. To add a callback from a signal handler, see `add_callback_from_signal`. """ raise NotImplementedError()
[docs] def add_callback_from_signal(self, callback, *args, **kwargs): """Calls the given callback on the next I/O loop iteration. Safe for use from a Python signal handler; should not be used otherwise. """ raise NotImplementedError()
[docs] def spawn_callback(self, callback, *args, **kwargs): """Calls the given callback on the next IOLoop iteration. As of Tornado 6.0, this method is equivalent to `add_callback`. .. versionadded:: 4.0 """ self.add_callback(callback, *args, **kwargs)
[docs] def add_future(self, future, callback): """Schedules a callback on the ``IOLoop`` when the given `.Future` is finished. The callback is invoked with one argument, the `.Future`. This method only accepts `.Future` objects and not other awaitables (unlike most of Tornado where the two are interchangeable). """ assert is_future(future) future_add_done_callback( future, lambda future: self.add_callback(callback, future))
[docs] def run_in_executor(self, executor, func, *args): """Runs a function in a ``concurrent.futures.Executor``. If ``executor`` is ``None``, the IO loop's default executor will be used. Use `functools.partial` to pass keyword arguments to ``func``. .. versionadded:: 5.0 """ if executor is None: if not hasattr(self, '_executor'): from tornado.process import cpu_count self._executor = ThreadPoolExecutor(max_workers=(cpu_count() * 5)) executor = self._executor c_future = executor.submit(func, *args) # Concurrent Futures are not usable with await. Wrap this in a # Tornado Future instead, using self.add_future for thread-safety. t_future = Future() self.add_future(c_future, lambda f: chain_future(f, t_future)) return t_future
[docs] def set_default_executor(self, executor): """Sets the default executor to use with :meth:`run_in_executor`. .. versionadded:: 5.0 """ self._executor = executor
def _run_callback(self, callback): """Runs a callback with error handling. For use in subclasses. """ try: ret = callback() if ret is not None: from tornado import gen # Functions that return Futures typically swallow all # exceptions and store them in the Future. If a Future # makes it out to the IOLoop, ensure its exception (if any) # gets logged too. try: ret = gen.convert_yielded(ret) except gen.BadYieldError: # It's not unusual for add_callback to be used with # methods returning a non-None and non-yieldable # result, which should just be ignored. pass else: self.add_future(ret, self._discard_future_result) except Exception: app_log.error("Exception in callback %r", callback, exc_info=True) def _discard_future_result(self, future): """Avoid unhandled-exception warnings from spawned coroutines.""" future.result()
[docs] def split_fd(self, fd): """Returns an (fd, obj) pair from an ``fd`` parameter. We accept both raw file descriptors and file-like objects as input to `add_handler` and related methods. When a file-like object is passed, we must retain the object itself so we can close it correctly when the `IOLoop` shuts down, but the poller interfaces favor file descriptors (they will accept file-like objects and call ``fileno()`` for you, but they always return the descriptor itself). This method is provided for use by `IOLoop` subclasses and should not generally be used by application code. .. versionadded:: 4.0 """ try: return fd.fileno(), fd except AttributeError: return fd, fd
[docs] def close_fd(self, fd): """Utility method to close an ``fd``. If ``fd`` is a file-like object, we close it directly; otherwise we use `os.close`. This method is provided for use by `IOLoop` subclasses (in implementations of ``IOLoop.close(all_fds=True)`` and should not generally be used by application code. .. versionadded:: 4.0 """ try: try: fd.close() except AttributeError: os.close(fd) except OSError: pass
class _Timeout(object): """An IOLoop timeout, a UNIX timestamp and a callback""" # Reduce memory overhead when there are lots of pending callbacks __slots__ = ['deadline', 'callback', 'tdeadline'] def __init__(self, deadline, callback, io_loop): if not isinstance(deadline, numbers.Real): raise TypeError("Unsupported deadline %r" % deadline) self.deadline = deadline self.callback = callback self.tdeadline = (deadline, next(io_loop._timeout_counter)) # Comparison methods to sort by deadline, with object id as a tiebreaker # to guarantee a consistent ordering. The heapq module uses __le__ # in python2.5, and __lt__ in 2.6+ (sort() and most other comparisons # use __lt__). def __lt__(self, other): return self.tdeadline < other.tdeadline def __le__(self, other): return self.tdeadline <= other.tdeadline
[docs]class PeriodicCallback(object): """Schedules the given callback to be called periodically. The callback is called every ``callback_time`` milliseconds. Note that the timeout is given in milliseconds, while most other time-related functions in Tornado use seconds. If ``jitter`` is specified, each callback time will be randomly selected within a window of ``jitter * callback_time`` milliseconds. Jitter can be used to reduce alignment of events with similar periods. A jitter of 0.1 means allowing a 10% variation in callback time. The window is centered on ``callback_time`` so the total number of calls within a given interval should not be significantly affected by adding jitter. If the callback runs for longer than ``callback_time`` milliseconds, subsequent invocations will be skipped to get back on schedule. `start` must be called after the `PeriodicCallback` is created. .. versionchanged:: 5.0 The ``io_loop`` argument (deprecated since version 4.1) has been removed. .. versionchanged:: 5.1 The ``jitter`` argument is added. """ def __init__(self, callback, callback_time, jitter=0): self.callback = callback if callback_time <= 0: raise ValueError("Periodic callback must have a positive callback_time") self.callback_time = callback_time self.jitter = jitter self._running = False self._timeout = None
[docs] def start(self): """Starts the timer.""" # Looking up the IOLoop here allows to first instantiate the # PeriodicCallback in another thread, then start it using # IOLoop.add_callback(). self.io_loop = IOLoop.current() self._running = True self._next_timeout = self.io_loop.time() self._schedule_next()
[docs] def stop(self): """Stops the timer.""" self._running = False if self._timeout is not None: self.io_loop.remove_timeout(self._timeout) self._timeout = None
[docs] def is_running(self): """Return True if this `.PeriodicCallback` has been started. .. versionadded:: 4.1 """ return self._running
def _run(self): if not self._running: return try: return self.callback() except Exception: app_log.error("Exception in callback %r", self.callback, exc_info=True) finally: self._schedule_next() def _schedule_next(self): if self._running: self._update_next(self.io_loop.time()) self._timeout = self.io_loop.add_timeout(self._next_timeout, self._run) def _update_next(self, current_time): callback_time_sec = self.callback_time / 1000.0 if self.jitter: # apply jitter fraction callback_time_sec *= 1 + (self.jitter * (random.random() - 0.5)) if self._next_timeout <= current_time: # The period should be measured from the start of one call # to the start of the next. If one call takes too long, # skip cycles to get back to a multiple of the original # schedule. self._next_timeout += (math.floor((current_time - self._next_timeout) / callback_time_sec) + 1) * callback_time_sec else: # If the clock moved backwards, ensure we advance the next # timeout instead of recomputing the same value again. # This may result in long gaps between callbacks if the # clock jumps backwards by a lot, but the far more common # scenario is a small NTP adjustment that should just be # ignored. # # Note that on some systems if time.time() runs slower # than time.monotonic() (most common on windows), we # effectively experience a small backwards time jump on # every iteration because PeriodicCallback uses # time.time() while asyncio schedules callbacks using # time.monotonic(). # https://github.com/tornadoweb/tornado/issues/2333 self._next_timeout += callback_time_sec