tutorial.py 1.9 KB

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  1. # Licensed to the Apache Software Foundation (ASF) under one
  2. # or more contributor license agreements. See the NOTICE file
  3. # distributed with this work for additional information
  4. # regarding copyright ownership. The ASF licenses this file
  5. # to you under the Apache License, Version 2.0 (the
  6. # "License"); you may not use this file except in compliance
  7. # with the License. You may obtain a copy of the License at
  8. #
  9. # http://www.apache.org/licenses/LICENSE-2.0
  10. #
  11. # Unless required by applicable law or agreed to in writing,
  12. # software distributed under the License is distributed on an
  13. # "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
  14. # KIND, either express or implied. See the License for the
  15. # specific language governing permissions and limitations
  16. # under the License.
  17. r"""
  18. A tutorial example take you to experience pydolphinscheduler.
  19. After tutorial.py file submit to Apache DolphinScheduler server a DAG would be create,
  20. and workflow DAG graph as below:
  21. --> task_child_one
  22. / \
  23. task_parent --> --> task_union
  24. \ /
  25. --> task_child_two
  26. it will instantiate and run all the task it have.
  27. """
  28. from pydolphinscheduler.core.process_definition import ProcessDefinition
  29. from pydolphinscheduler.tasks.shell import Shell
  30. with ProcessDefinition(
  31. name="tutorial",
  32. schedule="0 0 0 * * ? *",
  33. start_time="2021-01-01",
  34. tenant="tenant_exists",
  35. ) as pd:
  36. task_parent = Shell(name="task_parent", command="echo hello pydolphinscheduler")
  37. task_child_one = Shell(name="task_child_one", command="echo 'child one'")
  38. task_child_two = Shell(name="task_child_two", command="echo 'child two'")
  39. task_union = Shell(name="task_union", command="echo union")
  40. task_group = [task_child_one, task_child_two]
  41. task_parent.set_downstream(task_group)
  42. task_union << task_group
  43. pd.run()