Running Workflows via API

Workflows can be triggered from the API by calling run_workflow. This method is available on the hatchet.client.admin client:

from hatchet_sdk import Hatchet, ClientConfig
 
hatchet = Hatchet()
 
workflowRun = hatchet.client.admin.run_workflow(
    "ManualTriggerWorkflow",
    {"test": "test"},
    options={"additional_metadata": {"hello": "moon"}},
)

This method takes the following parameters:

• workflow_name (required): The name of the workflow to trigger. If you have not overridden the workflow name in the hatchet.workflow decorator, this should match the name of the workflow class.
• input (required): The input to the workflow. This should be a JSON-serializable dict.
• options (optional): Additional options to pass to the workflow. The current options are supported:
  • additional_metadata: A dict of key-value strings to attach to the workflow run. This metadata will be shown in the Hatchet UI and will be available in API endpoints for listing/filtering.

For more information on how to interact with the return value of run_workflow, see the documentation for getting workflow run results.

Running Workflows in Bulk via API

Workflows can also be triggered in bulk by calling run_workflows. This method is available on the hatchet.client.admin client:

from hatchet_sdk import Hatchet, ClientConfig
 
hatchet = Hatchet()
 
workflowRuns: WorkflowRun = []
 
for i in range(20):
    workflowRuns.append(
        {
            "workflow_name": "BulkParent",
            "input": {"n": i},
            "options": {
                "additional_metadata": {
                    "bulk-trigger": i,
                    "hello-{i}": "earth-{i}",
                },
            },
        }
    )
 
workflowRunRefs = hatchet.admin.run_workflows(
    workflowRuns,
)
 

This method takes the following parameters:

• workflow_runs (required): A list of WorkflowRun objects.