fzhcary commented on a change in pull request #1043:
URL: https://github.com/apache/airflow/pull/1043#discussion_r477289538
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File path: airflow/example_dags/example_trigger_controller_dag.py
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@@ -0,0 +1,48 @@
+from airflow import DAG, utils
+from airflow.operators import *
+from datetime import date, datetime, time, timedelta
+
+import pprint
+
+pp = pprint.PrettyPrinter(indent=4)
+
+# This example illustrates the use of the TriggerDagRunOperator. There are 2
+# entities at work in this scenario:
+# 1. The Controller DAG - the DAG that conditionally executes the trigger
+# 2. The Target DAG - DAG being triggered (in example_trigger_target_dag.py)
+#
+# This example illustrates the following features :
+# 1. A TriggerDagRunOperator that takes:
+# a. A python callable that decides whether or not to trigger the Target DAG
+# b. An optional params dict passed to the python callable to help in
+# evaluating whether or not to trigger the Target DAG
+# c. The id (name) of the Target DAG
+# d. The python callable can add contextual info to the DagRun created by
+# way of adding a Pickleable payload (e.g. dictionary of primitives). This
+# state is then made available to the TargetDag
+# 2. A Target DAG : c.f. example_trigger_target_dag.py
+
+# This function decides whether or not to Trigger the remote DAG
+def conditionally_trigger(context, dag_run_obj):
+ c_p =context['params']['condition_param']
+ print("Controller DAG : conditionally_trigger = {}".format(c_p))
+ if context['params']['condition_param']:
+ dag_run_obj.payload = {'message' :context['params']['message'] }
+ pp.pprint(dag_run_obj.payload)
+ return dag_run_obj
+
+
+# Define the DAG
+dag = DAG(dag_id='example_trigger_controller_dag',
+ default_args={"owner" : "me",
+ "start_date":datetime.now()},
+ schedule_interval='@once')
+
+
+# Define the single task in this controller example DAG
+trigger = TriggerDagRunOperator(task_id='test_trigger_dagrun',
Review comment:
need import TriggerDagRunOperator
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