Airflow github examples how to#

''' # Tutorial Documentation Documentation that goes along with the Airflow tutorial located () ''' from _future_ import annotations # from datetime import datetime, timedelta from textwrap import dedent # The DAG object we'll need this to instantiate a DAG from airflow import DAG # Operators we need this to operate! from airflow.operators. Firstly, we define some default arguments, then instantiate a DAG class with a DAG name monitorerrors, the DAG name will be shown in Airflow UI. Short guide: How to use PostgresOperator in Apache Airflow code samples in postgresoperatorexample/. See the License for the # specific language governing permissions and limitations # under 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 # 'AS IS' BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY # KIND, either express or implied. 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. See the NOTICE file # distributed with this work for additional information # regarding copyright ownership. Getting-Started is maintained by airflow-plugins. This was chosen to follow suit with the core Apache Airflow project. Unless otherwise specified, everything in the airflow-plugins org is by default licensed under Apache 2.0. # Licensed to the Apache Software Foundation (ASF) under one # or more contributor license agreements. It fetches the Github specified object and saves the result in GCS. DAGs are defined using Python code in Airflow, heres one of the examples dag from Apache Airflows Github repository. All example DAGs that use the plugins can be found in the Example Airflow DAGs repo.