Workflow runner

The WorkflowRunner class is compatible with the Workbench Workflow Definition Language (WWDL) schema.

Instantiating a runner

Provided your run-time environment has the necessary environment variables to connect to an Azure Table Storage resource (for persisting log messages), you can create a workflow runner simply by:

from workbench.workflows import WorkflowRunner
from workbench.bindings import AzureBlobSession

session = AzureBlobSession(organization, workspace, session_id, user_id)

# The workflow can be defined in-line, provided it adheres to the schema
workflow = session.workflow

runner = WorkflowRunner(workflow=workflow)

For more details on setting up environment variables, see Local installation.

Workflow context

Some workflows require additional attributes to run. You can pass these attributes to a workflow runner as context when instantiating the workflow runner or by updating the runner's context dictionary.

context = {
    organization: "example-org",
    workspace:"My Test Workspace",
    session_id: "clever-birds-learn".
    user_id: "waad_..."
    }

runner = WorkflowRunner(workflow=workflow, context=context)

Tip

Constructing your workflow to accept a DocumentVersion or Session object via the context is a clean way of scoping your workflow to operate on a particular file or dataset.

Running a workflow

To run a workflow call:

runner.run()