Source code for airflow.providers.standard.sensors.date_time
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from __future__ import annotations
import datetime
from collections.abc import Sequence
from dataclasses import dataclass
from typing import TYPE_CHECKING, Any, NoReturn
from airflow.providers.standard.utils.version_references import AIRFLOW_V_3_0_PLUS
from airflow.sensors.base import BaseSensorOperator
try:
from airflow.triggers.base import StartTriggerArgs
except ImportError:
# TODO: Remove this when min airflow version is 2.10.0 for standard provider
@dataclass
[docs] class StartTriggerArgs: # type: ignore[no-redef]
"""Arguments required for start task execution from triggerer."""
[docs] trigger_kwargs: dict[str, Any] | None = None
[docs] next_kwargs: dict[str, Any] | None = None
[docs] timeout: datetime.timedelta | None = None
from airflow.triggers.temporal import DateTimeTrigger
from airflow.utils import timezone
if TYPE_CHECKING:
from airflow.utils.context import Context
[docs]class DateTimeSensor(BaseSensorOperator):
"""
Waits until the specified datetime.
A major advantage of this sensor is idempotence for the ``target_time``.
It handles some cases for which ``TimeSensor`` and ``TimeDeltaSensor`` are not suited.
**Example** 1 :
If a task needs to wait for 11am on each ``logical_date``. Using
``TimeSensor`` or ``TimeDeltaSensor``, all backfill tasks started at
1am have to wait for 10 hours. This is unnecessary, e.g. a backfill
task with ``{{ ds }} = '1970-01-01'`` does not need to wait because
``1970-01-01T11:00:00`` has already passed.
**Example** 2 :
If a DAG is scheduled to run at 23:00 daily, but one of the tasks is
required to run at 01:00 next day, using ``TimeSensor`` will return
``True`` immediately because 23:00 > 01:00. Instead, we can do this:
.. code-block:: python
DateTimeSensor(
task_id="wait_for_0100",
target_time="{{ data_interval_end.tomorrow().replace(hour=1) }}",
)
:param target_time: datetime after which the job succeeds. (templated)
"""
[docs] template_fields: Sequence[str] = ("target_time",)
def __init__(self, *, target_time: str | datetime.datetime, **kwargs) -> None:
super().__init__(**kwargs)
# self.target_time can't be a datetime object as it is a template_field
if isinstance(target_time, datetime.datetime):
self.target_time = target_time.isoformat()
elif isinstance(target_time, str):
self.target_time = target_time
else:
raise TypeError(
f"Expected str or datetime.datetime type for target_time. Got {type(target_time)}"
)
[docs] def poke(self, context: Context) -> bool:
self.log.info("Checking if the time (%s) has come", self.target_time)
return timezone.utcnow() > timezone.parse(self.target_time)
[docs]class DateTimeSensorAsync(DateTimeSensor):
"""
Wait until the specified datetime occurs.
Deferring itself to avoid taking up a worker slot while it is waiting.
It is a drop-in replacement for DateTimeSensor.
:param target_time: datetime after which the job succeeds. (templated)
:param start_from_trigger: Start the task directly from the triggerer without going into the worker.
:param trigger_kwargs: The keyword arguments passed to the trigger when start_from_trigger is set to True
during dynamic task mapping. This argument is not used in standard usage.
:param end_from_trigger: End the task directly from the triggerer without going into the worker.
"""
[docs] start_trigger_args = StartTriggerArgs(
trigger_cls="airflow.triggers.temporal.DateTimeTrigger",
trigger_kwargs={"moment": "", "end_from_trigger": False},
next_method="execute_complete",
next_kwargs=None,
timeout=None,
)
[docs] start_from_trigger = False
def __init__(
self,
*,
start_from_trigger: bool = False,
end_from_trigger: bool = False,
trigger_kwargs: dict[str, Any] | None = None,
**kwargs,
) -> None:
super().__init__(**kwargs)
self.end_from_trigger = end_from_trigger
self.start_from_trigger = start_from_trigger
if self.start_from_trigger:
self.start_trigger_args.trigger_kwargs = dict(
moment=timezone.parse(self.target_time),
end_from_trigger=self.end_from_trigger,
)
[docs] def execute(self, context: Context) -> NoReturn:
self.defer(
method_name="execute_complete",
trigger=DateTimeTrigger(
moment=timezone.parse(self.target_time),
end_from_trigger=self.end_from_trigger,
)
if AIRFLOW_V_3_0_PLUS
else DateTimeTrigger(moment=timezone.parse(self.target_time)),
)
[docs] def execute_complete(self, context: Context, event: Any = None) -> None:
"""Handle the event when the trigger fires and return immediately."""
return None