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Manage workflow schedules

Schedule a workflow run

2.1.8

Directly on run:

You can directly add a schedule to a workflow run. For example, with Snowflake Miner:

Coming soon

Add schedule directly on run
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from pyatlan.client.atlan import AtlanClient
from pyatlan.model.packages import SnowflakeMiner
from pyatlan.model.workflow import WorkflowSchedule

client = AtlanClient()

miner = ( # (1)
    SnowflakeMiner(
        connection_qualified_name="default/snowflake/1234567890"
    )
    .s3(
        s3_bucket="test-s3-bucket",
        s3_prefix="test-s3-prefix",
        s3_bucket_region="test-s3-bucket-region",
        sql_query_key="TEST_QUERY",
        default_database_key="TEST_SNOWFLAKE",
        default_schema_key="TEST_SCHEMA",
        session_id_key="TEST_SESSION_ID",
    )
    .popularity_window(days=15)
    .native_lineage(enabled=True)
    .custom_config(config={"test": True, "feature": 1234})
    .to_workflow()
)

schedule = WorkflowSchedule(
    cron_schedule="45 5 * * *",
    timezone="Europe/Paris",
) # (2)

response = client.workflow.run(
    workflow=miner, workflow_schedule=schedule
) # (3)
  1. Begin by constructing the Snowflake miner workflow.

  2. To create a new schedule for the workflow, specify:

    • cron schedule expression, for example: 45 5 * * * (scheduled for tomorrow at 04:05:00).
    • time zone for the cron schedule, such as Europe/Paris.

  3. Finally, use the client.workflow.run() method to add this new schedule. It will both add the schedule and execute the workflow in Atlan.

Coming soon

Existing workflow:

You can also add a schedule to an existing workflow run:

Coming soon

Schedule an existing workflow run
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from pyatlan.client.atlan import AtlanClient
from pyatlan.model.workflow import WorkflowSchedule

client = AtlanClient()

existing_workflow = client.workflow.find_by_type(
    prefix=WorkflowPackage.SNOWFLAKE_MINER
)[0] # (1)

schedule = WorkflowSchedule(
    cron_schedule="45 5 * * *",
    timezone="Europe/Paris",
) # (2)

response = client.workflow.add_schedule(
    workflow=existing_workflow, workflow_schedule=schedule
) # (3)
  1. You can retrieve workflows based on their type (prefix). Note: Only workflows that have been run will be found.

  2. To create a new schedule for an existing workflow, provide:

  3. Finally, to apply this new schedule to the existing workflow, use client.workflow.add_schedule() method.

Coming soon

Retrieve a scheduled workflow run

2.1.8

Retrieve by name:

To retrieve an existing scheduled workflow run by its name:

Coming soon

Retrieve scheduled workflow run by its name
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from pyatlan.client.atlan import AtlanClient

client = AtlanClient()

response = client.workflow.get_scheduled_run(
    workflow_name="atlan-snowflake-miner-1714638976"
) # (1)

  1. To retrieve an existing scheduled workflow runs, specify:

    • name of the workflow as displayed in the UI (e.g: atlan-snowflake-miner-1714638976).

Retrieve all scheduled runs:

To retrieve all existing scheduled workflow runs:

Coming soon

Retrieve all scheduled workflow runs
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from pyatlan.client.atlan import AtlanClient

client = AtlanClient()

response = client.workflow.get_all_scheduled_runs() # (1)
  1. To retrieve all scheduled runs for workflows, use client.workflow.get_all_scheduled_runs() method.

Coming soon

Remove a schedule from workflow run

2.1.8

To remove a schedule from an existing workflow run:

Coming soon

Remove a schedule from an existing workflow run
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from pyatlan.client.atlan import AtlanClient

client = AtlanClient()

existing_workflow = client.workflow.find_by_type(
    prefix=WorkflowPackage.SNOWFLAKE_MINER
)[0] # (1)

response = client.workflow.remove_schedule(
    workflow=existing_workflow
) # (2)

  1. You can retrieve workflows based on their type (prefix). Note: Only workflows that have been run will be found.

  2. Finally, to remove a schedule from this workflow, use the client.workflow.remove_schedule() method.

Coming soon