Hi all, I have been working on a project at a startup. I just started working 2 months ago (recently graduated), and I'm the only one with techinical knowledge inside the company. I suggested we use fabric for the project my boss wanted to start (it is mostly getting data from API's/ scrapers, and then modifying it through medallion architecture). I am now facing some issues. First of all, using the web interface 8 hours a day is really tiring (and slow), especially when all debugging is done in the cloud too. The synapse extension in VSC is not working as expected for me, the spark session does not start and things like ```%run notebook_file``` don't work. Is there an alternative so that I can develop locally and push to the cloud once finished? Or can I change the way I use the synapse extension so that I can use the same code I wrote locally and push it to the cloud through the extension.

Hi, I'm quite new in the world of working with data (at least professionally). I have been coding python for quite some time though, and have found that during my job there are little to no problems that I can't solve with python (expected), but also that python is a really simple tool that is easy to re-use. In my team I'm the only one who can really code, my colleagues use Excel and data pipelines to work with the data. Now my question is (appart from the fact that I might be one of the only ones that can write python): are there any drawbacks of primarily using python (so notebooks) for all data collecting, handling, ...? I'm currently not that far into the course, so excuse me if my question overlooks some obvious technicalities. I'll be sure to come back to this topic at the end of the course. I'd appreciate some real world examples of why python can be a suboptimal tool, inside the Fabric eco-system.