<@U02H1A95XDW> or <@U01QEJ9PP53> Any update on thi...
# prefect-community
j
@Anna Geller or @Kevin Kho Any update on this issue? We’re running into the same issues with no logs appearing when using Prefect with LocalDaskExecutors on a Docker Agent in “processes” mode https://github.com/PrefectHQ/prefect/issues/5769
k
We haven’t had bandwidth to investigate this thoroughly yet as we get 2.0 out of beta. Can try digging myself today and seeing what I find.
Ping me tom if I don’t get back to you
🙏 1
I am still looking and am still clueless, but a good workaround is Dask LocalCluster though if you’re open to using that. Example below:
Copy code
from prefect import task, Flow
from prefect.run_configs import ECSRun, DockerRun
from prefect.storage import S3
from prefect.executors import LocalDaskExecutor, DaskExecutor
import prefect
import time

@task(log_stdout=True)
def abc(x):
    time.sleep(5)
    <http://prefect.context.logger.info|prefect.context.logger.info>(x)
    print(x)
    return "hello"

with Flow("ecs_test", run_config=DockerRun(image="prefecthq/prefect:1.2.0-python3.7", env={"PREFECT__LOGGING__LOG_LEVEL": "DEBUG"}), 
                      executor = DaskExecutor(cluster_kwargs={"n_workers": 4, "threads_per_worker": 1})) as flow:
    abc(1)
    abc(2)

flow.storage = S3(bucket="coiled-prefect")
flow.register("databricks")
j
Is it possible to have n_workers or threader per worker to be set dynamically at flow run time based on agent env variables?
k
Actually that is only possible for DaskExecutor and not LocalDaskExecutor. You can see this