multi_resources_example.py

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"""
This example show how to upload file to dolphinscheduler resource center and use them in tasks.

When you want to create a new resource file in resource center, you can add them to ``workflow.resource_list``
use the following code:

.. code-block:: python

    with Workflow(
        name="use_resource_center",
        resource_list=[
            Resource(name="new-name.py", content="print('hello world from resource center')"),
        ],
        ) as workflow:

during the workflow running, the resource file will be created and uploaded to dolphinscheduler resource
center automatically.

If you want to use the resource file in tasks, you can also use ``resource_list`` parameter in task
constructor, just like the following code:

.. code-block:: python

    task_use_resource = Shell(
        name="run_resource",
        command="python new-name.py",
        resource_list=[
            "new-name.py",
        ],
    )

and the resource file will be downloaded to the task runtime working directory which mean you cna execute
them. In this example we run the file ``new-name.py`` like we execute python script in terminal. And we can
also use the resource file already in dolphinscheduler resource center, not only the new we created in
current workflow.
"""

# [start workflow]
from pydolphinscheduler.core import Workflow
from pydolphinscheduler.core.resource import Resource
from pydolphinscheduler.tasks import Shell

dependence = "dependence.py"
main = "main.py"

with Workflow(
    name="multi_resources_example",
    # [start create_new_resources]
    resource_list=[
        Resource(
            name=dependence,
            content="from datetime import datetime\nnow = datetime.now()",
        ),
        Resource(name=main, content="from dependence import now\nprint(now)"),
    ],
    # [end create_new_resources]
) as workflow:
    # [start use_exists_resources]
    task_use_resource = Shell(
        name="use-resource",
        command=f"python {main}",
        resource_list=[
            dependence,
            main,
        ],
    )
    # [end use_exists_resources]

    workflow.run()
# [end workflow]