<@ULVA73B9P> In Prefect 3, how can I retry a flow ...
# ask-marvin
n
@Marvin In Prefect 3, how can I retry a flow run when the flow run crashes, meaning it finishes in the Crashed state?
m
In Prefect 3.x, retrying a flow run that ends in the "Crashed" state isn't directly supported through a built-in retry mechanism specifically for "Crashed" states. However, you can implement custom logic to handle this situation. Here's a general approach you can take: 1. Monitoring State Changes: You can monitor the state of your flow run using Prefect's state handlers or by querying the Prefect API for flow run states. 2. Custom Retry Logic: If a flow run ends in the "Crashed" state, you can programmatically trigger a new run of the flow. You might use Prefect's Python client to do this, checking the state and re-submitting the flow when necessary. 3. Error Handling: Implement error handling within your flow to catch exceptions that might lead to a crash, potentially allowing you to set a retry state before the flow crashes entirely. For more specific implementation details, you can refer to the Prefect documentation or explore the Prefect API to manage flow runs programmatically. You can view more about handling states and retries in the Prefect documentation. If you have specific requirements or constraints, feel free to share them, and I can help refine the approach further.
n
@Marvin Does the flow decorator have the parameter "retry_condition_fn"?
m
The
flow
decorator in Prefect 3.x does not have a parameter named
retry_condition_fn
. This parameter is available for tasks, allowing you to specify a callable that determines whether a task should be retried based on its state. If you're looking to implement similar retry logic for a flow, you might need to handle it manually by monitoring the flow's state and re-triggering the flow run under certain conditions. This would involve using Prefect's API or client to programmatically manage flow runs. You can find more about flow management in the Prefect documentation. For tasks, the
retry_condition_fn
parameter is used to define custom retry behavior, which might be useful if you have tasks within your flow that need this functionality.