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:mod:`airflow.sensors.external_task_sensor`
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.. py:module:: airflow.sensors.external_task_sensor
Module Contents
---------------
.. py:class:: ExternalTaskSensor(external_dag_id, external_task_id=None, allowed_states=None, execution_delta=None, execution_date_fn=None, check_existence=False, *args, **kwargs)
Bases: :class:`airflow.sensors.base_sensor_operator.BaseSensorOperator`
Waits for a different DAG or a task in a different DAG to complete for a
specific execution_date
:param external_dag_id: The dag_id that contains the task you want to
wait for
:type external_dag_id: str
:param external_task_id: The task_id that contains the task you want to
wait for. If ``None`` (default value) the sensor waits for the DAG
:type external_task_id: str or None
:param allowed_states: list of allowed states, default is ``['success']``
:type allowed_states: list
:param execution_delta: time difference with the previous execution to
look at, the default is the same execution_date as the current task or DAG.
For yesterday, use [positive!] datetime.timedelta(days=1). Either
execution_delta or execution_date_fn can be passed to
ExternalTaskSensor, but not both.
:type execution_delta: datetime.timedelta
:param execution_date_fn: function that receives the current execution date
and returns the desired execution dates to query. Either execution_delta
or execution_date_fn can be passed to ExternalTaskSensor, but not both.
:type execution_date_fn: callable
:param check_existence: Set to `True` to check if the external task exists (when
external_task_id is not None) or check if the DAG to wait for exists (when
external_task_id is None), and immediately cease waiting if the external task
or DAG does not exist (default value: False).
:type check_existence: bool
.. attribute:: template_fields
:annotation: = ['external_dag_id', 'external_task_id']
.. attribute:: ui_color
:annotation: = #19647e
.. method:: poke(self, context, session=None)
.. method:: _handle_execution_date_fn(self, context)
This function is to handle backwards compatibility with how this operator was
previously where it only passes the execution date, but also allow for the newer
implementation to pass all context through as well, to allow for more sophisticated
returns of dates to return.
Namely, this function check the number of arguments in the execution_date_fn
signature and if its 1, treat the legacy way, if it's 2, pass the context as
the 2nd argument, and if its more, throw an exception.
.. py:class:: ExternalTaskMarker(external_dag_id, external_task_id, execution_date='{{ execution_date.isoformat() }}', recursion_depth=10, *args, **kwargs)
Bases: :class:`airflow.operators.dummy_operator.DummyOperator`
Use this operator to indicate that a task on a different DAG depends on this task.
When this task is cleared with "Recursive" selected, Airflow will clear the task on
the other DAG and its downstream tasks recursively. Transitive dependencies are followed
until the recursion_depth is reached.
:param external_dag_id: The dag_id that contains the dependent task that needs to be cleared.
:type external_dag_id: str
:param external_task_id: The task_id of the dependent task that needs to be cleared.
:type external_task_id: str
:param execution_date: The execution_date of the dependent task that needs to be cleared.
:type execution_date: str or datetime.datetime
:param recursion_depth: The maximum level of transitive dependencies allowed. Default is 10.
This is mostly used for preventing cyclic dependencies. It is fine to increase
this number if necessary. However, too many levels of transitive dependencies will make
it slower to clear tasks in the web UI.
.. attribute:: template_fields
:annotation: = ['external_dag_id', 'external_task_id', 'execution_date']
.. attribute:: ui_color
:annotation: = #19647e
.. attribute:: __serialized_fields
.. classmethod:: get_serialized_fields(cls)
Serialized ExternalTaskMarker contain exactly these fields + templated_fields .