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# Copyright 2009 Facebook
# Licensed under the Apache License, Version 2.0 (the "License"); you may
# not use this file except in compliance with the License. You may obtain
# a copy of the License at
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
# License for the specific language governing permissions and limitations
# under the License.
"""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
import asyncio
import concurrent.futures
import datetime
import logging
import numbers
import os
import sys
import time
import math
import random
from tornado.concurrent import (
from tornado.log import app_log
from tornado.util import Configurable, TimeoutError, import_object
import typing
from typing import Union, Any, Type, Optional, Callable, TypeVar, Tuple, Awaitable
if typing.TYPE_CHECKING:
from typing import Dict, List # noqa: F401
from typing_extensions import Protocol
Protocol = object
class _Selectable(Protocol):
def fileno(self) -> int:
def close(self) -> None:
_T = TypeVar("_T")
_S = TypeVar("_S", bound=_Selectable)
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.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:
connection, address = sock.accept()
except socket.error as e:
if e.args[0] not in (errno.EWOULDBLOCK, errno.EAGAIN):
io_loop = tornado.ioloop.IOLoop.current()
io_loop.spawn_callback(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.bind(("", 8888))
io_loop = tornado.ioloop.IOLoop.current()
callback = functools.partial(connection_ready, sock)
io_loop.add_handler(sock.fileno(), callback, io_loop.READ)
.. testoutput::
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`
.. 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() # type: Dict[asyncio.AbstractEventLoop, IOLoop]
def configure(
cls, impl: Union[None, str, Type[Configurable]], **kwargs: Any
) -> None:
if asyncio is not None:
from tornado.platform.asyncio import BaseAsyncIOLoop
if isinstance(impl, str):
impl = import_object(impl)
if isinstance(impl, type) and not issubclass(impl, BaseAsyncIOLoop):
raise RuntimeError(
"only AsyncIOLoop is allowed when asyncio is available"
super(IOLoop, cls).configure(impl, **kwargs)
def instance() -> "IOLoop":
"""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()
def install(self) -> None:
"""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
def clear_instance() -> None:
"""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
def current() -> "IOLoop":
@typing.overload # noqa: F811
def current(instance: bool = True) -> Optional["IOLoop"]:
@staticmethod # noqa: F811
def current(instance: bool = True) -> Optional["IOLoop"]:
"""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
.. 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.
loop = asyncio.get_event_loop()
except (RuntimeError, AssertionError):
if not instance:
return None
return IOLoop._ioloop_for_asyncio[loop]
except KeyError:
if instance:
from tornado.platform.asyncio import AsyncIOMainLoop
current = AsyncIOMainLoop(make_current=True) # type: Optional[IOLoop]
current = None
return current
def make_current(self) -> None:
"""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
.. 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()
def clear_current() -> None:
"""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:
if asyncio is None:
IOLoop._current.instance = None
def _clear_current_hook(self) -> None:
"""Instance method called when an IOLoop ceases to be current.
May be overridden by subclasses as a counterpart to make_current.
def configurable_base(cls) -> Type[Configurable]:
return IOLoop
def configurable_default(cls) -> Type[Configurable]:
from tornado.platform.asyncio import AsyncIOLoop
return AsyncIOLoop
def initialize(self, make_current: bool = None) -> None:
if make_current is None:
if IOLoop.current(instance=False) is None:
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")
def close(self, all_fds: bool = False) -> None:
"""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
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()
def add_handler(
self, fd: int, handler: Callable[[int, int], None], events: int
) -> None:
@typing.overload # noqa: F811
def add_handler(
self, fd: _S, handler: Callable[[_S, int], None], events: int
) -> None:
def add_handler( # noqa: F811
self, fd: Union[int, _Selectable], handler: Callable[..., None], events: int
) -> None:
"""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()`` and ``close()`` method.
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()
def update_handler(self, fd: Union[int, _Selectable], events: int) -> None:
"""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()
def remove_handler(self, fd: Union[int, _Selectable]) -> None:
"""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()
def start(self) -> None:
"""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) -> None:
"""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(
def stop(self) -> None:
"""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()
def run_sync(self, func: Callable, timeout: float = None) -> Any:
"""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__':
.. 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] # type: List[Optional[Future]]
def run() -> None:
result = func()
if result is not None:
from tornado.gen import convert_yielded
result = convert_yielded(result)
except Exception:
fut = Future() # type: Future[Any]
future_cell[0] = fut
future_set_exc_info(fut, sys.exc_info())
if is_future(result):
future_cell[0] = result
fut = Future()
future_cell[0] = fut
assert future_cell[0] is not None
self.add_future(future_cell[0], lambda future: self.stop())
if timeout is not None:
def timeout_callback() -> None:
# 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).
assert future_cell[0] is not None
if not future_cell[0].cancel():
timeout_handle = self.add_timeout(self.time() + timeout, timeout_callback)
if timeout is not None:
assert future_cell[0] is not None
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()
def time(self) -> float:
"""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()
def add_timeout(
deadline: Union[float, datetime.timedelta],
callback: Callable[..., None],
*args: Any,
**kwargs: Any
) -> object:
"""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
raise TypeError("Unsupported deadline %r" % deadline)
def call_later(
self, delay: float, callback: Callable[..., None], *args: Any, **kwargs: Any
) -> object:
"""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)
def call_at(
self, when: float, callback: Callable[..., None], *args: Any, **kwargs: Any
) -> object:
"""Runs the ``callback`` at the absolute time designated by ``when``.
``when`` must be a number using the same reference point as
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)
def remove_timeout(self, timeout: object) -> None:
"""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()
def add_callback(self, callback: Callable, *args: Any, **kwargs: Any) -> None:
"""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
raise NotImplementedError()
def add_callback_from_signal(
self, callback: Callable, *args: Any, **kwargs: Any
) -> None:
"""Calls the given callback on the next I/O loop iteration.
Safe for use from a Python signal handler; should not be used
raise NotImplementedError()
def spawn_callback(self, callback: Callable, *args: Any, **kwargs: Any) -> None:
"""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)
def add_future(
future: Union["Future[_T]", "concurrent.futures.Future[_T]"],
callback: Callable[["Future[_T]"], None],
) -> None:
"""Schedules a callback on the ``IOLoop`` when the given
`.Future` is finished.
The callback is invoked with one argument, the
This method only accepts `.Future` objects and not other
awaitables (unlike most of Tornado where the two are
assert is_future(future)
future, lambda future: self.add_callback(callback, future)
def run_in_executor(
executor: Optional[concurrent.futures.Executor],
func: Callable[..., _T],
*args: Any
) -> Awaitable[_T]:
"""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 = concurrent.futures.ThreadPoolExecutor(
max_workers=(cpu_count() * 5)
) # type: concurrent.futures.Executor
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() # type: Future[_T]
self.add_future(c_future, lambda f: chain_future(f, t_future))
return t_future
def set_default_executor(self, executor: concurrent.futures.Executor) -> None:
"""Sets the default executor to use with :meth:`run_in_executor`.
.. versionadded:: 5.0
self._executor = executor
def _run_callback(self, callback: Callable[[], Any]) -> None:
"""Runs a callback with error handling.
For use in subclasses.
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.
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.
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: Future) -> None:
"""Avoid unhandled-exception warnings from spawned coroutines."""
def split_fd(
self, fd: Union[int, _Selectable]
) -> Tuple[int, Union[int, _Selectable]]:
"""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
if isinstance(fd, int):
return fd, fd
return fd.fileno(), fd
def close_fd(self, fd: Union[int, _Selectable]) -> None:
"""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
if isinstance(fd, int):
except OSError:
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: float, callback: Callable[[], None], io_loop: IOLoop
) -> None:
if not isinstance(deadline, numbers.Real):
raise TypeError("Unsupported deadline %r" % deadline)
self.deadline = deadline
self.callback = callback
self.tdeadline = (
) # type: Tuple[float, int]
# 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: "_Timeout") -> bool:
return self.tdeadline < other.tdeadline
def __le__(self, other: "_Timeout") -> bool:
return self.tdeadline <= other.tdeadline
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
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: Callable[[], None], callback_time: float, jitter: float = 0
) -> None:
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 # type: object
def start(self) -> None:
"""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()
def stop(self) -> None:
"""Stops the timer."""
self._running = False
if self._timeout is not None:
self._timeout = None
def is_running(self) -> bool:
"""Return True if this `.PeriodicCallback` has been started.
.. versionadded:: 4.1
return self._running
def _run(self) -> None:
if not self._running:
return self.callback()
except Exception:
app_log.error("Exception in callback %r", self.callback, exc_info=True)
def _schedule_next(self) -> None:
if self._running:
self._timeout = self.io_loop.add_timeout(self._next_timeout, self._run)
def _update_next(self, current_time: float) -> None:
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
# 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().
self._next_timeout += callback_time_sec