Source code for airflow.sensors.external_task_sensor

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import datetime
import os

from sqlalchemy import func

from airflow.exceptions import AirflowException
from airflow.models import DagBag, DagModel, DagRun, TaskInstance
from airflow.operators.dummy_operator import DummyOperator
from airflow.sensors.base_sensor_operator import BaseSensorOperator
from airflow.utils.db import provide_session
from airflow.utils.decorators import apply_defaults
from airflow.utils.state import State


[docs]class ExternalTaskSensor(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 """
[docs] template_fields = ['external_dag_id', 'external_task_id']
[docs] ui_color = '#19647e'
@apply_defaults def __init__(self, external_dag_id, external_task_id=None, allowed_states=None, execution_delta=None, execution_date_fn=None, check_existence=False, *args, **kwargs): super(ExternalTaskSensor, self).__init__(*args, **kwargs) self.allowed_states = allowed_states or [State.SUCCESS] if external_task_id: if not set(self.allowed_states) <= set(State.task_states): raise ValueError( 'Valid values for `allowed_states` ' 'when `external_task_id` is not `None`: {}'.format(State.task_states) ) else: if not set(self.allowed_states) <= set(State.dag_states): raise ValueError( 'Valid values for `allowed_states` ' 'when `external_task_id` is `None`: {}'.format(State.dag_states) ) if execution_delta is not None and execution_date_fn is not None: raise ValueError( 'Only one of `execution_delta` or `execution_date_fn` may ' 'be provided to ExternalTaskSensor; not both.') self.execution_delta = execution_delta self.execution_date_fn = execution_date_fn self.external_dag_id = external_dag_id self.external_task_id = external_task_id self.check_existence = check_existence @provide_session
[docs] def poke(self, context, session=None): if self.execution_delta: dttm = context['execution_date'] - self.execution_delta elif self.execution_date_fn: dttm = self._handle_execution_date_fn(context=context) else: dttm = context['execution_date'] dttm_filter = dttm if isinstance(dttm, list) else [dttm] serialized_dttm_filter = ','.join( [datetime.isoformat() for datetime in dttm_filter]) self.log.info( 'Poking for %s.%s on %s ... ', self.external_dag_id, self.external_task_id, serialized_dttm_filter ) DM = DagModel TI = TaskInstance DR = DagRun if self.check_existence: dag_to_wait = session.query(DM).filter( DM.dag_id == self.external_dag_id ).first() if not dag_to_wait: raise AirflowException('The external DAG ' '{} does not exist.'.format(self.external_dag_id)) else: if not os.path.exists(dag_to_wait.fileloc): raise AirflowException('The external DAG ' '{} was deleted.'.format(self.external_dag_id)) if self.external_task_id: refreshed_dag_info = DagBag(dag_to_wait.fileloc).get_dag(self.external_dag_id) if not refreshed_dag_info.has_task(self.external_task_id): raise AirflowException('The external task' '{} in DAG {} does not exist.'.format(self.external_task_id, self.external_dag_id)) if self.external_task_id: # .count() is inefficient count = session.query(func.count()).filter( TI.dag_id == self.external_dag_id, TI.task_id == self.external_task_id, TI.state.in_(self.allowed_states), TI.execution_date.in_(dttm_filter), ).scalar() else: # .count() is inefficient count = session.query(func.count()).filter( DR.dag_id == self.external_dag_id, DR.state.in_(self.allowed_states), DR.execution_date.in_(dttm_filter), ).scalar() session.commit() return count == len(dttm_filter)
[docs] def _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. """ num_fxn_params = self.execution_date_fn.__code__.co_argcount if num_fxn_params == 1: return self.execution_date_fn(context['execution_date']) elif num_fxn_params == 2: return self.execution_date_fn(context['execution_date'], context) else: raise AirflowException( 'execution_date_fn passed {} args but only allowed up to 2'.format(num_fxn_params)
)
[docs]class ExternalTaskMarker(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. """
[docs] template_fields = ['external_dag_id', 'external_task_id', 'execution_date']
[docs] ui_color = '#19647e'
# The _serialized_fields are lazily loaded when get_serialized_fields() method is called
[docs] __serialized_fields = None
@apply_defaults def __init__(self, external_dag_id, external_task_id, execution_date="{{ execution_date.isoformat() }}", recursion_depth=10, *args, **kwargs): super(ExternalTaskMarker, self).__init__(*args, **kwargs) self.external_dag_id = external_dag_id self.external_task_id = external_task_id if isinstance(execution_date, datetime.datetime): self.execution_date = execution_date.isoformat() elif isinstance(execution_date, str): self.execution_date = execution_date else: raise TypeError('Expected str or datetime.datetime type for execution_date. Got {}' .format(type(execution_date))) if recursion_depth <= 0: raise ValueError("recursion_depth should be a positive integer") self.recursion_depth = recursion_depth @classmethod
[docs] def get_serialized_fields(cls): """Serialized ExternalTaskMarker contain exactly these fields + templated_fields .""" if not cls.__serialized_fields: cls.__serialized_fields = frozenset( super(ExternalTaskMarker, cls).get_serialized_fields() | { "recursion_depth" } ) return cls.__serialized_fields