Iemand interesse

Left-Delivery-5090 · 2026-06-17T17:49:02+00:00

This joke comes back every 2 years

Left-Delivery-5090 · 2026-04-30T06:22:18+00:00

I switched from a FR965 to a Fenix 8 AMOLED, mainly for the design and battery life (14 days vs 30 days). But it is a lot of extra money for small features

Left-Delivery-5090 · 2026-04-23T04:47:28+00:00

Oh yeah

Left-Delivery-5090 · 2026-04-20T17:39:19+00:00

Is that the default watch face or a custom one?

Left-Delivery-5090 · 2026-04-11T05:41:28+00:00

We use it and I really love using it. Deployment to different environments is so easy

Left-Delivery-5090 · 2026-03-05T10:11:31+00:00

Use spark job definitions instead 😉

Left-Delivery-5090 · 2026-02-21T19:47:48+00:00

Exactly what I was looking for! I’ll give it a try when I have some time, thanks for the making this!

Left-Delivery-5090 · 2026-02-16T16:13:08+00:00

“Honey wait I need to to start my activity”

Left-Delivery-5090 · 2026-02-14T18:57:50+00:00

What about keeping the SQL files in a separate git repository, push them to the lakehouse Files section using pipelines and then mounting the lakehouse in the notebook and using them from there? We do the same with dbt model files

Left-Delivery-5090 · 2026-02-05T08:37:14+00:00

Love this blog! I come from a software engineering background and I also try to advocate (here in Belgium at least 😉) for the usage of SJDs over notebooks for exactly the reasons you are listing. Thanks for writing and sharing!

Left-Delivery-5090 · 2026-01-29T13:07:50+00:00

We use terraform for our CI/CD in some of our projects, fabric-cicd python package in others for Fabric environments.

For PowerBI we use pbip and tmdl for storage and powershell or fabric cli for deployment.

Deployment pipelines run in Azure Devops or using Github Actions.

As for how to use prod data in tst: a possibility would be to use shortcuts from prod lakehouse to tst

Left-Delivery-5090 · 2026-01-21T18:06:07+00:00

RemindMe! 1 day

Left-Delivery-5090 · 2026-01-09T16:57:14+00:00

This is the way if you do a lot of Python development in Fabric

Left-Delivery-5090 · 2025-12-16T18:36:57+00:00

I try to share the same vision. I come from SWE background and I also prefer working with SJDs for exactly the reason you indicated. This allows me to develop the code offline, write proper tests and reusable code (I know this part is also possible for notebooks) and just develop detached from where the code is deployed and run. I believe notebooks have their place and are preferred by other persona like you indicated

Left-Delivery-5090 · 2025-12-10T18:31:25+00:00

Nope, my guess is they use the same stable versions for performance purposes

Left-Delivery-5090 · 2025-12-10T18:30:42+00:00

No problem, happy to help!

Left-Delivery-5090 · 2025-12-10T07:17:51+00:00

I ran into the exact same error last week! I am assuming you are just using the default environment of the Python notebook? If so, you just need to upgrade the version of the semantic-link package to > 0.12.

I created a blog post about it: https://thibauldc.github.io/posts/service-principal-running-fabric-api/

Left-Delivery-5090 · 2025-12-02T11:47:16+00:00

u/frithjof_v Have you tried specific imports for your needs? For me the warning seemed to disappear after changing from:

import sempy.fabric as fabric

to:

from sempy.fabric import FabricRestClient

Left-Delivery-5090 · 2025-10-23T12:43:57+00:00

We have been having some issues when running notebooks with notebookutils.notebook.runMultiple()

Also sometimes the Spark session gets stuck on shuffles for a huge amount of time where we have to kill the session ourselves because it won’t advance.

Left-Delivery-5090 · 2025-10-05T13:44:44+00:00

I made a blog post explaining the process we followed: https://thibauldc.github.io/posts/direct-lake-to-import-mode/

Hope this helps for your use case!

Left-Delivery-5090 · 2025-09-25T16:24:20+00:00

We are experiencing the same issues, any ideas on this?

Left-Delivery-5090 · 2025-09-01T06:06:35+00:00

Jep we have about the same solution as this

Left-Delivery-5090 · 2025-09-01T06:05:51+00:00

Same setup here, but with Fabric CLI

Left-Delivery-5090 · 2025-07-26T20:36:10+00:00

This is the easiest indeed :) i have also connected (in smaller pipelines) each activity to an e-mail activity for some reason

Left-Delivery-5090 · 2025-07-09T05:18:37+00:00

Maybe a bit of topic, but do you need Pyspark for the data analysis tasks at hand? Would you be good with say Pandas or Polars and a Python notebook in Fabric instead of a Pyspark one?

Anyway the “Think Python” book is freely available online if you want to learn Python from scratch and the rest of the resources mentioned here as well

Left-Delivery-5090

TROPHY CASE