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| import logging as logger | |
| from datetime import datetime | |
| import boto3 | |
| import pandas as pd | |
| from airflow.models import DAG, Variable | |
| from airflow.operators.dummy_operator import DummyOperator | |
| from airflow.operators.python_operator import PythonOperator | |
| from utils import update_context | |
| DAG_OWNER = '[email protected]' | |
| DAG_ID = 'dag_name' | |
| SCHEDULE_INTERVAL = '@weekly' | |
| default_args = { | |
| 'owner': DAG_OWNER, | |
| 'start_date': datetime(2020, 1, 1), | |
| 'executor_config': { | |
| 'KubernetesExecutor': { | |
| 'request_memory': '512Mi', | |
| 'limit_memory': '1Gi', | |
| 'request_cpu': '500m', | |
| 'limit_cpu': '1000m' | |
| } | |
| }, | |
| 'retries': 3, | |
| } | |
| def python_task_callable(**kwargs): | |
| pass | |
| def create_dag(): | |
| dag = DAG(DAG_ID, default_args=default_args, | |
| schedule_interval=SCHEDULE_INTERVAL) | |
| start = DummyOperator(task_id='start', dag=dag) | |
| python_task = PythonOperator(task_id='python_task', | |
| provide_context=True, | |
| python_callable=python_task_callable, | |
| dag=dag) | |
| complete = DummyOperator(task_id='complete', dag=dag) | |
| start >> python_task >> complete | |
| return dag | |
| globals()[DAG_ID] = create_dag() |
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