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compatibility.py
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compatibility.py
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from __future__ import annotations
import asyncio
import logging
import random
import sys
import warnings
from collections.abc import Callable, Coroutine
from typing import Any, TypeVar
import tornado
__all__ = ["logging_names", "PeriodicCallback", "to_thread", "randbytes"]
logging_names: dict[str | int, int | str] = {}
logging_names.update(logging._levelToName) # type: ignore
logging_names.update(logging._nameToLevel) # type: ignore
LINUX = sys.platform == "linux"
MACOS = sys.platform == "darwin"
WINDOWS = sys.platform == "win32"
def to_thread(*args, **kwargs):
warnings.warn(
"to_thread is deprecated and will be removed in a future release; use asyncio.to_thread instead.",
DeprecationWarning,
stacklevel=2,
)
return asyncio.to_thread(*args, **kwargs)
def randbytes(*args, **kwargs):
warnings.warn(
"randbytes is deprecated and will be removed in a future release; use random.randbytes instead.",
DeprecationWarning,
stacklevel=2,
)
return random.randbytes(*args, **kwargs)
if tornado.version_info >= (6, 2, 0, 0):
from tornado.ioloop import PeriodicCallback
else:
# Backport from https://github.com/tornadoweb/tornado/blob/a4f08a31a348445094d1efa17880ed5472db9f7d/tornado/ioloop.py#L838-L962
# License https://github.com/tornadoweb/tornado/blob/v6.2.0/LICENSE
# Includes minor modifications to source code to pass linting
# This backport ensures that async callbacks are not overlapping if a run
# takes longer than the interval
import datetime
import math
from collections.abc import Awaitable
from inspect import isawaitable
from tornado.ioloop import IOLoop
from tornado.log import app_log
class PeriodicCallback: # type: ignore[no-redef]
"""Schedules the given callback to be called periodically.
The callback is called every ``callback_time`` milliseconds when
``callback_time`` is a float. Note that the timeout is given in
milliseconds, while most other time-related functions in Tornado use
seconds. ``callback_time`` may alternatively be given as a
`datetime.timedelta` object.
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.
.. versionchanged:: 6.2
If the ``callback`` argument is a coroutine, and a callback runs for
longer than ``callback_time``, subsequent invocations will be skipped.
Previously this was only true for regular functions, not coroutines,
which were "fire-and-forget" for `PeriodicCallback`.
The ``callback_time`` argument now accepts `datetime.timedelta` objects,
in addition to the previous numeric milliseconds.
"""
def __init__(
self,
callback: Callable[[], Awaitable | None],
callback_time: datetime.timedelta | float,
jitter: float = 0,
) -> None:
self.callback = callback
if isinstance(callback_time, datetime.timedelta):
self.callback_time = callback_time / datetime.timedelta(milliseconds=1)
else:
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()
self._schedule_next()
def stop(self) -> None:
"""Stops the timer."""
self._running = False
if self._timeout is not None:
self.io_loop.remove_timeout(self._timeout)
self._timeout = None
def is_running(self) -> bool:
"""Returns ``True`` if this `.PeriodicCallback` has been started.
.. versionadded:: 4.1
"""
return self._running
async def _run(self) -> None:
if not self._running:
return
try:
val = self.callback()
if val is not None and isawaitable(val):
await val
except Exception:
app_log.error("Exception in callback %r", self.callback, exc_info=True)
finally:
self._schedule_next()
def _schedule_next(self) -> None:
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: 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
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
_T = TypeVar("_T")
if sys.version_info >= (3, 12):
asyncio_run = asyncio.run
elif sys.version_info >= (3, 11):
def asyncio_run(
main: Coroutine[Any, Any, _T],
*,
debug: bool = False,
loop_factory: Callable[[], asyncio.AbstractEventLoop] | None = None,
) -> _T:
# asyncio.run from Python 3.12
# https://docs.python.org/3/license.html#psf-license
with asyncio.Runner(debug=debug, loop_factory=loop_factory) as runner:
return runner.run(main)
else:
# modified version of asyncio.run from Python 3.10 to add loop_factory kwarg
# https://docs.python.org/3/license.html#psf-license
def asyncio_run(
main: Coroutine[Any, Any, _T],
*,
debug: bool = False,
loop_factory: Callable[[], asyncio.AbstractEventLoop] | None = None,
) -> _T:
try:
asyncio.get_running_loop()
except RuntimeError:
pass
else:
raise RuntimeError(
"asyncio.run() cannot be called from a running event loop"
)
if not asyncio.iscoroutine(main):
raise ValueError(f"a coroutine was expected, got {main!r}")
if loop_factory is None:
loop = asyncio.new_event_loop()
else:
loop = loop_factory()
try:
if loop_factory is None:
asyncio.set_event_loop(loop)
if debug is not None:
loop.set_debug(debug)
return loop.run_until_complete(main)
finally:
try:
_cancel_all_tasks(loop)
loop.run_until_complete(loop.shutdown_asyncgens())
loop.run_until_complete(loop.shutdown_default_executor())
finally:
if loop_factory is None:
asyncio.set_event_loop(None)
loop.close()
def _cancel_all_tasks(loop: asyncio.AbstractEventLoop) -> None:
to_cancel = asyncio.all_tasks(loop)
if not to_cancel:
return
for task in to_cancel:
task.cancel()
loop.run_until_complete(asyncio.gather(*to_cancel, return_exceptions=True))
for task in to_cancel:
if task.cancelled():
continue
if task.exception() is not None:
loop.call_exception_handler(
{
"message": "unhandled exception during asyncio.run() shutdown",
"exception": task.exception(),
"task": task,
}
)