Source code for airflow.sensors.external_task

# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements.  See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership.  The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not use this file except in compliance
# with the License.  You may obtain a copy of the License at
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# KIND, either express or implied.  See the License for the
# specific language governing permissions and limitations
# under the License.

import datetime
import os
from typing import Any, Callable, FrozenSet, Iterable, Optional, Union

from sqlalchemy import func

from airflow.exceptions import AirflowException
from airflow.models import BaseOperatorLink, DagBag, DagModel, DagRun, TaskInstance
from airflow.operators.dummy import DummyOperator
from airflow.sensors.base import BaseSensorOperator
from airflow.utils.helpers import build_airflow_url_with_query
from airflow.utils.session import provide_session
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 logical 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 external_task_ids: The list of task_ids that you want to wait for. If ``None`` (default value) the sensor waits for the DAG. Either external_task_id or external_task_ids can be passed to ExternalTaskSensor, but not both. :type external_task_ids: Iterable of task_ids or None, default is None :param allowed_states: Iterable of allowed states, default is ``['success']`` :type allowed_states: Iterable :param failed_states: Iterable of failed or dis-allowed states, default is ``None`` :type failed_states: Iterable :param execution_delta: time difference with the previous execution to look at, the default is the same logical 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: Optional[datetime.timedelta] :param execution_date_fn: function that receives the current execution's logical date as the first positional argument and optionally any number of keyword arguments available in the context dictionary, and returns the desired logical dates to query. Either execution_delta or execution_date_fn can be passed to ExternalTaskSensor, but not both. :type execution_date_fn: Optional[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'
@property def __init__( self, *, external_dag_id: str, external_task_id: Optional[str] = None, external_task_ids: Optional[Iterable[str]] = None, allowed_states: Optional[Iterable[str]] = None, failed_states: Optional[Iterable[str]] = None, execution_delta: Optional[datetime.timedelta] = None, execution_date_fn: Optional[Callable] = None, check_existence: bool = False, **kwargs, ): super().__init__(**kwargs) self.allowed_states = list(allowed_states) if allowed_states else [State.SUCCESS] self.failed_states = list(failed_states) if failed_states else [] total_states = self.allowed_states + self.failed_states total_states = set(total_states) if set(self.failed_states).intersection(set(self.allowed_states)): raise AirflowException( "Duplicate values provided as allowed " "`{}` and failed states `{}`".format(self.allowed_states, self.failed_states) ) if external_task_id is not None and external_task_ids is not None: raise ValueError( 'Only one of `external_task_id` or `external_task_ids` may ' 'be provided to ExternalTaskSensor; not both.' ) if external_task_id is not None: external_task_ids = [external_task_id] if external_task_ids: if not total_states <= set(State.task_states): raise ValueError( f'Valid values for `allowed_states` and `failed_states` ' f'when `external_task_id` or `external_task_ids` is not `None`: {State.task_states}' ) if len(external_task_ids) > len(set(external_task_ids)): raise ValueError('Duplicate task_ids passed in external_task_ids parameter') elif not total_states <= set(State.dag_states): raise ValueError( f'Valid values for `allowed_states` and `failed_states` ' f'when `external_task_id` is `None`: {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.external_task_ids = external_task_ids self.check_existence = check_existence self._has_checked_existence = False @provide_session
[docs] def poke(self, context, session=None): if self.execution_delta: dttm = context['logical_date'] - self.execution_delta elif self.execution_date_fn: dttm = self._handle_execution_date_fn(context=context) else: dttm = context['logical_date'] dttm_filter = dttm if isinstance(dttm, list) else [dttm] serialized_dttm_filter = ','.join(dt.isoformat() for dt in dttm_filter) 'Poking for tasks %s in dag %s on %s ... ', self.external_task_ids, self.external_dag_id, serialized_dttm_filter, ) # In poke mode this will check dag existence only once if self.check_existence and not self._has_checked_existence: self._check_for_existence(session=session) count_allowed = self.get_count(dttm_filter, session, self.allowed_states) count_failed = -1 if self.failed_states: count_failed = self.get_count(dttm_filter, session, self.failed_states) if count_failed == len(dttm_filter): if self.external_task_ids: raise AirflowException( f'Some of the external tasks {self.external_task_ids} ' f'in DAG {self.external_dag_id} failed.' ) else: raise AirflowException(f'The external DAG {self.external_dag_id} failed.') return count_allowed == len(dttm_filter)
def _check_for_existence(self, session) -> None: dag_to_wait = session.query(DagModel).filter(DagModel.dag_id == self.external_dag_id).first() if not dag_to_wait: raise AirflowException(f'The external DAG {self.external_dag_id} does not exist.') if not os.path.exists(dag_to_wait.fileloc): raise AirflowException(f'The external DAG {self.external_dag_id} was deleted.') if self.external_task_ids: refreshed_dag_info = DagBag(dag_to_wait.fileloc).get_dag(self.external_dag_id) for external_task_id in self.external_task_ids: if not refreshed_dag_info.has_task(external_task_id): raise AirflowException( f'The external task {external_task_id} in ' f'DAG {self.external_dag_id} does not exist.' ) self._has_checked_existence = True
[docs] def get_count(self, dttm_filter, session, states) -> int: """ Get the count of records against dttm filter and states :param dttm_filter: date time filter for execution date :type dttm_filter: list :param session: airflow session object :type session: SASession :param states: task or dag states :type states: list :return: count of record against the filters """ TI = TaskInstance DR = DagRun if self.external_task_ids: count = ( session.query(func.count()) # .count() is inefficient .filter( TI.dag_id == self.external_dag_id, TI.task_id.in_(self.external_task_ids), TI.state.in_(states), TI.execution_date.in_(dttm_filter), ) .scalar() ) count = count / len(self.external_task_ids) else: count = ( session.query(func.count()) .filter( DR.dag_id == self.external_dag_id, DR.state.in_(states), DR.execution_date.in_(dttm_filter), ) .scalar() ) return count
def _handle_execution_date_fn(self, context) -> Any: """ 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 variables as keyword arguments, to allow for more sophisticated returns of dates to return. """ from airflow.utils.operator_helpers import make_kwargs_callable # Remove "logical_date" because it is already a mandatory positional argument logical_date = context["logical_date"] kwargs = {k: v for k, v in context.items() if k not in {"execution_date", "logical_date"}} # Add "context" in the kwargs for backward compatibility (because context used to be # an acceptable argument of execution_date_fn) kwargs["context"] = context kwargs_callable = make_kwargs_callable(self.execution_date_fn) return kwargs_callable(logical_date, **kwargs)
[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 logical date of the dependent task execution 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 __serialized_fields: Optional[FrozenSet[str]] = None def __init__( self, *, external_dag_id: str, external_task_id: str, execution_date: Optional[Union[str, datetime.datetime]] = "{{ logical_date.isoformat() }}", recursion_depth: int = 10, **kwargs, ): super().__init__(**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( f'Expected str or datetime.datetime type for execution_date. Got {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().get_serialized_fields() | {"recursion_depth"}) return cls.__serialized_fields

Was this entry helpful?