Source code for airflow.sensors.date_time_sensor

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import datetime

from airflow.sensors.base_sensor_operator import BaseSensorOperator
from airflow.utils import timezone
from airflow.utils.decorators import apply_defaults

[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 ``execution_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='{{ next_execution_date.tomorrow().replace(hour=1) }}', ) :param target_time: datetime after which the job succeeds. (templated) :type target_time: str or datetime.datetime """
[docs] template_fields = ("target_time",)
@apply_defaults def __init__( self, target_time, *args, **kwargs ): super(DateTimeSensor, self).__init__(*args, **kwargs) 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( "Expected str or datetime.datetime type for target_time. Got {}".format( type(target_time) ) )
[docs] def poke(self, context):"Checking if the time (%s) has come", self.target_time) return timezone.utcnow() > timezone.parse(self.target_time)

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