Hey, we are *currently experiencing some performance problems with prefect 2. As soon as we decorate a function with

@flow

it runs slower by a factor of 2-10x. This is our test setup:

def run_flow():
    calculate_something()


@flow(
    name=FLOW_NAME,
    task_runner=get_default_task_runner(),
    version=get_file_hash(__file__),
    timeout_seconds=get_default_timeout(),
)
def run_prefect_flow():
    global USE_PREFECT_LOGGER
    USE_PREFECT_LOGGER = True
    run_flow()


if __name__ == "__main__":
    if len(sys.argv) > 1 and sys.argv[1] == "--no-prefect":
        # Normal performance 
        run_flow()
    else:
        # Bad performance
        run_prefect_flow()

We can't share any code from inside

calculate_something

- are there any circumstances that you know of where this might happen? What overhead brings `@flow`into play? Does it analyze http or DB requests for debugging purposes which might explain the performance degradation? What I can offer is a pstats profile/graph in a dm because it also may contain sensitive data. *currently = as long as we can remember using prefect 2.

What could be more helpful to troubleshoot would be a minimal reproducible example that you can share The overhead is making an API call and then the calls for tracking state changes