 So yeah, is that basically what we needed to say? Personally, I think this was a better introduction to the topics than last time. So when you'd spend all the time to do all the exercises, although I think you really need to try some of these exercises because especially the data stuff you'll be doing all the time. Yeah, but usually like whenever you have a new project, you usually just let's say transfer the input data to try it and you write your scripts there, you put them into the queue, the script break, you edit the scripts, you put them into the queue, your code breaks, then you edit your code, you put them back again to the queue, and then you get some results, you copy the results back and then you visualize the results. Like usually the workflow is something like you need to do some of these more specific things like data copying, like big data copying or something like that at the start and at the end maybe of the project. But in the middle of it, it's mostly about the queue and running the stuff and that is like I hope that everybody gathers from this today's lecture about like how do you actually run stuff in the queue and how do you get your stuff run. And tomorrow we'll look at the more advanced stuff that you can run like in bigger scale or with bigger resources. Yeah. Okay. Please fill out the feedback as you see on HackMD and we're right on time so we can hang out and answer a few more questions if or maybe we can do it asynchronously on HackMD. Yeah. Yeah. So should we hang up for the day? Yeah. Okay. Thanks everybody for listening. Yeah. So please everyone come down and give us feedback. This is really the most important thing we can get. Yeah. Even if you hated this, then give us feedback because then like we know what to fix. Exactly. That's what we do every iteration like it's similar to the actual work in the cluster iterations. Okay. So talk to you all later then. Bye for now.