Source code for airflow.operators.dagrun_operator

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from airflow.models import BaseOperator
from airflow.utils import timezone
from airflow.utils.decorators import apply_defaults
from airflow.api.common.experimental.trigger_dag import trigger_dag

import json


class DagRunOrder(object):
    def __init__(self, run_id=None, payload=None):
        self.run_id = run_id
        self.payload = payload


[docs]class TriggerDagRunOperator(BaseOperator): """ Triggers a DAG run for a specified ``dag_id`` :param trigger_dag_id: the dag_id to trigger :type trigger_dag_id: str :param python_callable: a reference to a python function that will be called while passing it the ``context`` object and a placeholder object ``obj`` for your callable to fill and return if you want a DagRun created. This ``obj`` object contains a ``run_id`` and ``payload`` attribute that you can modify in your function. The ``run_id`` should be a unique identifier for that DAG run, and the payload has to be a picklable object that will be made available to your tasks while executing that DAG run. Your function header should look like ``def foo(context, dag_run_obj):`` :type python_callable: python callable :param execution_date: Execution date for the dag :type execution_date: datetime.datetime """ template_fields = tuple() template_ext = tuple() ui_color = '#ffefeb' @apply_defaults def __init__( self, trigger_dag_id, python_callable=None, execution_date=None, *args, **kwargs): super(TriggerDagRunOperator, self).__init__(*args, **kwargs) self.python_callable = python_callable self.trigger_dag_id = trigger_dag_id self.execution_date = execution_date def execute(self, context): dro = DagRunOrder(run_id='trig__' + timezone.utcnow().isoformat()) if self.python_callable is not None: dro = self.python_callable(context, dro) if dro: trigger_dag(dag_id=self.trigger_dag_id, run_id=dro.run_id, conf=json.dumps(dro.payload), execution_date=self.execution_date, replace_microseconds=False) else: self.log.info("Criteria not met, moving on")