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<@ULVA73B9P> i have a flow that uses .submit() to ...
# ask-marvin
g
@Marvin i have a flow that uses .submit() to run tasks in parallel, i use .wait() at the last chain of dependencies in order to resolve the concurrencies, but when a task that doesn't have .wait() in it fails, my flow status still shows as completed
m
In Prefect 3.x, the final state of a flow run is determined by the return value of the flow function and whether any exceptions are allowed to propagate. If a task fails but the flow function itself does not raise an exception, the flow can still be marked as completed. This behavior contrasts with Prefect 2.x, where any task failure would cause the flow to be marked as failed. To ensure that your flow reflects task failures accurately, consider the following: 1. Raise Exceptions: Allow exceptions to propagate by not suppressing them. This will mark the flow as failed if any task raises an exception. 2. Return State Objects: You can explicitly return state objects from your flow. If any of these states are failed, the flow will be marked as failed. 3. Use 
.result()
or 
.wait()
: Ensure that you resolve all futures by using 
.result()
or 
.wait()
. This way, any exceptions raised by tasks will propagate to the flow level. For more detailed information, you can refer to the Prefect 3.x documentation on flow final states. If you would like more specific guidance or examples, let me know.
g
how do i allow exceptions to propagate when using .submit() or .map()
@Marvin how do i allow exceptions to propagate when using .submit() or .map()
m
To allow exceptions to propagate when using 
.submit()
or 
.map()
in Prefect, you should ensure that you handle the futures returned by these methods properly. Here's how you can do it: 1. Resolve Futures: Use 
.result()
or 
.wait()
on the futures returned by 
.submit()
or 
.map()
. This will cause any exceptions raised during task execution to propagate to the flow level.
Copy code
python
   from prefect import flow, task

   @task
   def my_task(x):
       if x == 2:
           raise ValueError("An error occurred!")
       return x

   @flow
   def my_flow():
       futures = [my_task.submit(i) for i in range(5)]
       results = [future.result() for future in futures]  # This will raise the exception
       return results

   my_flow()
2. Error Handling: If you want to handle exceptions more gracefully, you can catch them when resolving the futures.
Copy code
python
   @flow
   def my_flow():
       futures = [my_task.submit(i) for i in range(5)]
       results = []
       for future in futures:
           try:
               result = future.result()
               results.append(result)
           except Exception as e:
               print(f"Task failed with exception: {e}")
       return results

   my_flow()
By ensuring that you resolve the futures, you allow any exceptions to be raised and handled at the flow level. For more details, you can refer to the Prefect documentation on task execution and error handling.
g
@Marvin but if i use .result() or .wait() in a future, the tasks will not run in parallel
m
When using 
.result()
or 
.wait()
, you're indeed resolving the futures, which means you're waiting for each task to complete sequentially. To maintain parallel execution while allowing exceptions to propagate, you can still submit tasks in parallel and then resolve them afterward. Here's how you can achieve this: 1. Submit Tasks in Parallel: Use 
.submit()
to start all tasks concurrently. 2. Resolve After Submission: After submitting all tasks, loop through the futures to resolve them. This way, the tasks run in parallel, but you still handle exceptions. Here's an example:
Copy code
python
from prefect import flow, task

@task
def my_task(x):
    if x == 2:
        raise ValueError("An error occurred!")
    return x

@flow
def my_flow():
    # Submit tasks to run in parallel
    futures = [my_task.submit(i) for i in range(5)]
    
    # Resolve futures to propagate exceptions
    results = []
    for future in futures:
        try:
            result = future.result()  # This will wait for the task to complete
            results.append(result)
        except Exception as e:
            print(f"Task failed with exception: {e}")
    
    return results

my_flow()
In this setup, tasks are initiated in parallel, and the resolution of their results is done afterward, allowing exceptions to propagate correctly. This maintains parallel execution while providing proper error handling.
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