<@ULVA73B9P> Can I retry individual subflows insid...
# marvin-in-the-wild
e
@Marvin Can I retry individual subflows inside a flow run?
m
Based on the information gathered from the Prefect documentation and GitHub issues: ### Can You Retry Individual Subflows Inside a Flow Run? Retrying individual subflows within a flow run isn't directly addressed in Prefect's documentation, but it appears that subflows adhere to their parent flow's lifecycle. This means specific retry mechanisms might need to be managed by the parent flow. ### Relevant Docs & Issues: 1. Suspension and Resumption: - Subflows can't be suspended independently of their parent run. The suspension and resumption features for the entire flow run might apply to subflows indirectly, but they don't provide granularity for individual subflow retries. - Prefect Documentation on Flow Concepts 2. GitHub Issue on Subflow Crashes: - A user reported issues with subflow executions and potential memory leaks, highlighting that subflows are managed within their parent flow's context. - GitHub Issue: Flow Crashing After Multiple Subflow Runs ### Suggested Solution To achieve retries for individual subflows: - Implement a retry mechanism within the parent flow that specifically targets the subflow logic. - Use condition checks or exception handling within your parent flow to trigger retries for subflows. ### Example
Copy code
python
from prefect import flow, task
from prefect.exceptions import PrefectException

@task
def some_task():
    # Task logic here
    pass

@flow
def subflow():
    some_task()

@flow
def parent_flow():
    for _ in range(3):  # Retry logic
        try:
            subflow()
            break
        except PrefectException as e:
            print(f"Retry due to: {e}")

if __name__ == "__main__":
    parent_flow()
This example shows a basic implementation of retry logic within the parent flow for managing subflow execution retries. Feel free to reach out for more detailed solutions or other questions.
e
@Marvin would using the run_deployment function work?
m
### Using
run_deployment
to Retry Subflows Yes, you can use the
run_deployment
function to manage and potentially retry individual subflows inside a flow run. ### Features of `run_deployment`: - Scheduling Flow Runs: The
run_deployment
function can initiate a flow run for an existing deployment from within your Python code. - Non-blocking Execution: By default,
run_deployment
blocks until the scheduled flow run finishes. However, you can set
timeout=0
to return immediately without waiting for it to finish. - As Subflow: By default, the flow run scheduled is linked as a subflow to the calling flow. You can override this by setting
as_subflow=False
. ### Example Implementation Here's how you can use
run_deployment
to retry a subflow:
Copy code
python
from prefect import flow, task, get_run_logger
from prefect.deployments import run_deployment

@task
def some_task():
    logger = get_run_logger()
    <http://logger.info|logger.info>("Executing some task.")
    return True

@flow
def parent_flow():
    deployment_name = "my_subflow/my_deployment"
    for _ in range(3):  # Retry mechanism
        try:
            result = run_deployment(name=deployment_name, as_subflow=True)
            if result.state.is_completed():
                get_run_logger().info(f"Subflow {deployment_name} completed successfully.")
                break
        except Exception as e:
            get_run_logger().error(f"Retrying subflow due to: {e}")
            continue

if __name__ == "__main__":
    parent_flow()
### Links for Further Reading: 1. Prefect Documentation on
run_deployment
: - Prefect Deployments Documentation - Concepts of Deployments 2. Relevant GitHub Issues: - Issue: Give run_deployment the same wait-properties as subflow - Issue: Subflows fired with `run_deployment` cause parent to be incorrectly marked as failed - Issue: Difficulty canceling sub-flow runs created by run_deployment Using the
run_deployment
function provides flexibility in scheduling and managing subflows, including the ability to implement retry logic within parent flows. This approach addresses the granularity needed for individual subflow retries.