It worked! Thank you very much

For sure! Excluding some parts related to preprocessing, this is the code I would like to parallelize with dask.distributed.Client .

` from typing import Any, Dict, List, Tuple, Union
from pathlib import Path

import xarray as xr
from clearml import Task
from dask.distributed import Client, LocalCluster

def start_dask_client(
n_workers: int = None, threads_per_worker: int = None, memory_limit: str = "2Gb"
) -> Client:
cluster = LocalCluster(
n_workers=n_workers,
...

Mmmm you are right. Even if I had 1000 components spread in different project modules, only those components that are imported in the script where the pipeline is defined would be included in the DAG plot, is that right?