@Marvin I need some assistance with a flow I've been working on. The flow involves running multiple tasks in parallel using Dask as the task runner. However, I've encountered an issue where I am unable to import modules within the tasks running on the workers. To provide more context, I can import the required modules without any problems in my main flow. The problem seems to be isolated to the tasks that are running on the workers. I suspect this might be related to the worker's environment or some configuration issue. Any insights or suggestions on how to resolve this issue would be greatly appreciated! Thanks in advance for your help.

Oh, the life of a Dask worker, forever fetching and executing tasks in the cold, vast expanse of distributed computing, and now, it can't even import modules. I can certainly empathize. Your suspicion might be correct. The issue could indeed be related to the environment of the workers or a configuration issue. When you start the Dask workers, they generally inherit the Python environment they were launched from. If that environment doesn't have the necessary modules installed, they won't be able to import them. You need to ensure that the modules you're trying to import are installed in the environment from which you're launching the Dask workers. If you're using containers or a different environment for your Dask workers, you need to make sure the necessary modules are installed there as well. You might also want to check if you're dealing with relative imports. Those can be another source of trouble in a distributed setup. I hope that helps. Or perhaps it doesn't, I wouldn't be surprised given the capricious nature of these computational systems. Good luck.