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Hi guys :wave:
Someone have experience with the DaskTaskRunner() and runing tasks in parallel?
We can’t make tasks run in parallel.
I’ve detailed the problem here:
<https://discourse.prefect.io/t/tasks-are-not-running-in-parallel-when-using-dasktaskrunner/2180/1>

Does this work for you?
```import time

from prefect import flow, task
from prefect_dask import DaskTaskRunner

@task
def shout(number):
    time.sleep(5)
    print(f"#{number}")

@flow(task_runner=DaskTaskRunner)
def count_to(highest_number):
    for number in range(highest_number):
        shout.submit(number)

if __name__ == "__main__":
    count_to(10)```

This is exactly my setup, but let me try your code as is.

I tried to mimic your code

```import time

from prefect import flow, task
from prefect_dask import DaskTaskRunner

@task
def shout(number):
    print(f"before sleep")
    time.sleep(5)
    print(f"#{number}")

@flow(task_runner=DaskTaskRunner(), log_prints=True)
def count_to(highest_number):
    cats = ["fluffy", "loaf", "fat", "squishy"]
    for cat in cats:
        shout.submit(cat)

if __name__ == "__main__":
    count_to(10)```

I don’t have a deployment set up. are you able to run it locally first?

ok, so locally it’s the same thing.
won’t parallel.

So when you run it locally it dose run in parallel right?

```import time

from prefect import flow, task
from prefect_dask import DaskTaskRunner

@task
def shout(number):
    print(f"before sleep")
    time.sleep(5)
    print(f"#{number}")

@flow(task_runner=DaskTaskRunner(cluster_kwargs={"n_workers": 4, "threads_per_worker": 2}), log_prints=True)
def count_to(highest_number):
    cats = ["fluffy", "loaf", "fat", "squishy"]
    for cat in cats:
        shout.submit(cat)

if __name__ == "__main__":
    count_to(10)```

what if you explicitly set n workers and yes it runs in parallel for me

ok this code works in parallel localy :+1::+1:

got it (-:
it was that return_state=True!
after I removed it, we are back to parallel.

Interesting… that seems like a surprise. I think we could potentially improve this. do you mind submitting an issue to prefect-dask?

<https://github.com/PrefectHQ/prefect-dask/issues/69>