Having the ability to run python code outside of the notebook environment (like we can for pyspark jobs) could be a real win for efficiency and modularity. It would allow users to package robust, unit-tested code and deploy it to the fabric environment where it could run as a cost-effective single-node job. Databricks has an implementation for this, and it would be really nice to see something similar come to Fabric.
Notebooks are great for ad-hoc or exploratory stuff, but building something robust in them feels like shoving a peg into a wrong-shaped hole. They are (nearly) impossible to unit test, so you often end up creating libraries which allow you to package transformations in a way that can be tested, then your notebooks end up being essentially thin wrappers around a bunch of external code.
I think the most obvious example for this is the number of Fabric DBT implementations that essentially involve installing DBT core into a notebook and running it there (I know there is DBT jobs coming, but this is beside the point). This is a symptom of a larger need for this type of hosting/execution of code within the environment. Yes, you could host the code on a vm external to Fabric but that goes against the ethos of a unified data platform. Offering something like this would be a great way to increase the flexibility and extensibility of the platform.
The implementation can be fairly barebones and developer forward, aiming to provide maximum flexibility and extensibility. Basically a way to run python scripts/CLI tools on the Fabric capacity.
on:
Improve error message when dataset mixes cloud and...
on:
Deployment pipeline rule for data factory pipeline...
on:
Epic Idea: Show visual dependencies for bookmarks
on:
Customize messaging for Report Access Requests
dm-p
on:
Allow standard Focus Mode for custom visuals that ...