# 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 # # http://www.apache.org/licenses/LICENSE-2.0 # # 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. See the License for the # specific language governing permissions and limitations # under the License. r""" A tutorial example take you to experience pydolphinscheduler. After tutorial.py file submit to Apache DolphinScheduler server a DAG would be create, and workflow DAG graph as below: --> task_child_one / \ task_parent --> --> task_union \ / --> task_child_two it will instantiate and run all the task it have. """ from pydolphinscheduler.core.process_definition import ProcessDefinition from pydolphinscheduler.tasks.shell import Shell with ProcessDefinition( name="aklsfkkalsfjkol", tenant="tenant_exists", ) as pd: task_child_one = Shell(name="task_child_one", command="echo 'child one'") task_child_two = Shell(name="task_child_two", command="echo 'child two'") task_union = Shell(name="task_union", command="echo union") task_group = [task_child_one, task_child_two] task_union << task_group pd.run()