Tag Archives: TMDL

Release of Fabric Studio v1.0

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I am very proud to announce the first public release of Fabric Studio v1.0 – a VSCode extension that allows you to manage and develop your Fabric workspace(s). Similar to Power BI Studio, it seamlessly integrates into VSCode for increased productivity for professional developers and admins alike.

It includes a lot of different features of which the most notable are probably these:

  • a generic workspace browser supporting all Fabric item types and their most common API actions
  • a custom file system provider allowing you to modify Fabric items as if they were local
  • a dedicated deployment pipeline manager
  • an integration of the Fabric Git into VSCode source control
  • a VSCode Fabric notebook to run arbitrary API calls
  • …

Workspace Browser

The workspace browser gives you an overview of all items that currently exist in your workspaces. This includes all items that currently exist and automatically extends to new items that might get added in the future. For selected items specific entries in the context menu were added e.g. Copy SQL ConnectionString, Run Notebook, …

There is also a common set of actions that exist for every item like opening the selected item directly in the Fabric Service via your browser or copy its ID or Name.

At the top you will find icons that allow you to filter the list of workspaces, refresh the current item, edit the items (e.g. semantic models, pipelines, … see below) or open a notebook that allows you to run arbitrary calls against the Fabric REST API.

Edit Fabric Items from VSCode

Using the context menu in the Workspace Browser you can select Edit Items which will open the definition of the selected item in your VSCode Solution Explorer as a new folder. You can either do this on the workspace level, a specific item type folder (Pipelines, Notebooks, …) or on an individual item. As of now, not all items are supported – here is a list of items that are supported as of now:

  • Semantic Models using TMDL (.tmdl)
  • Reports using PBIR (.json)
  • Data Pipelines using JSON (.json)
  • Notebooks using Python (.py) or Jupyter Notebooks (.ipynb)
  • Spark Job Definitions using JSON (.json)
  • Mirrored Databases using JSON (.json)
  • …

This feature is implemented using VSCode Custom File System providers which makes it behave as if it were a local file system. This means you can also copy&paste or drag&drop between Fabric and your local file system – in both directions! The use-cases are unlimited here:

  • easily copy a semantic model or report from one workspace to another
  • upload the report of a local PBI Project (.pbip) to Fabric without having to also publish and overwrite the dataset
  • do bulk-edits on your notebooks or pipelines
  • …

Once you are done with your changes, you can use “Publish to Fabric” to upload them back to Fabric and make the new version available to your users.

Deployment Pipelines

Selectively deploy individual items or whole item types (multi-select!)into the next stage directly from VSCode.

Fabric Git Integration

If your Fabric workspace is linked to GIT, you can now mange it from VSCode as if it were a local repository. Stage/Unstage/Discard changes or pull the latest changes from the underlying GIT repository.

Fabric API Notebooks

As Fabric Studio is solely based on the REST APIs provided by Fabric, I also wanted to offer a way to make running arbitrary API calls as easy as possible. The main problem when it comes to REST APIs is always authentication. As the API is already authenticated in the background, we can use the same mechanisms to also run any other API calls as well. Notebooks in VSCode offer an intuitive way to to do this. Another reason for this generic way of doing API calls is that not all endpoints will be covered by the UI so it just made sense to offer this option as well.

There would be a lot more features worth being mentioned here but instead I will create short demo videos and publish them via my social media channels (Bluesky, X/Twitter, LinkedIn). So to stay up-to-date with the most recent developments, make sure to also follow me there!

The last thing I want to mention is that the whole project is 100% open source and can be used under the MIT license. The repository is currently hosted in my GitHub account: https://github.com/gbrueckl/FabricStudio. If you are interested in the project and maybe want to contribute to it, please reach out to me!

If you like Fabric Studio but are working mainly with Power BI, make sure to also check out Power BI Studio – another extension developed by me, specifically tailored towards Power BI developers and admins!

Release of Power BI-VSCode Extension

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Download from VSCode Gallery

I am working a lot with Power BI in my daily business and there have always been a couple of things that bothered me since the very beginning. Most of this is related to the web UI and its usability, mainly that you need too many clicks to get to where you want (e.g. viewing Datasets refreshes) but also that some features are simply not exposed in the UI that are possible with the Power BI REST APIs (e.g. rebinding a report to another dataset). So I thought there must be some better way to do this and make management and usability of Power BI easier and I came up with the idea for a Visual Studio Code extension for Power BI to close this gap.

As you may know, I have already written another VSCode extension for Databricks (Databricks Power Tools) which is basically also “just” a wrapper around the various Databricks APIs but makes various features of Databricks much more accessible, especially for people that spend most of their time in a local IDE anyway and are already used to it. At this point I also want to thank my company paiqo for supporting this engagements and making all this possible!

For about a year now I have been developing the Power BI VSCode extension and it finally reached a state where I want to release it. It has been in the VSCode market place for quite some time now but was never officially released by a blog post like this. To stay up-to-date I highly recommend to follow the repository which will always be updated to include the latest features and documentation.

So what is this Power BI VSCode extension all about and how can it help me in my daily work? There are currently three core components included which all serve different purposes:

  • Workspace browser
  • Notebooks to run arbitrary API calls and DAX
  • TMDL editor (!)

The workspace browser allows you to access all artifacts that you have access to and run the most common API calls directly from the VSCode UI. Besides features that are also available in the web UI like taking over an artifact, triggering a refresh/viewing the history or changing parameters, this includes additional features like Rebind, Clone, Configuring Query Scale Out, Update Report Content, etc. For some features you can also use Drag&Drop instead of the context menu. For example, if you drag a report and drop it on a dataset, a popup will ask you whether you want to rebind the report to that dataset or clone the report and link the clone to the dataset!

Besides the workspace browser there is also a dedicated one for Deployment Pipelines which allows you to configure Power BI deployment pipelines and also run selective deployments directly from VSCode!

There are also UIs for Capacities and Gateways, but those are mainly for informational purposes and are read-only.

The second component of the extension are Power BI Notebooks which allow you to run any arbitrary API call . This is especially useful as not every API call can be built into the UI properly (e.g. due to too many parameters, etc.). Power BI Notebooks also support notebook magics like %dax or %cmd to run DAX queries or to set variables within the notebook. There is also intellisense/autocomplete which should help you a lot to discover and write your final API call. This also includes samples for more complex API calls like calling the Enhanced Refresh API.

To run a DAX statement via the Execute Queries API, you can simply use %dax in the first line of the notebook call and then start writing your DAX query:

The last – but definitely not least(!) – part is the just recently added TMDL (Tabular Model Definition Language) integration, which allows you to modify Power BI datasets using TMDL. If your dataset resides in a premium capacity and the XMLA endpoint is enabled for read/write mode, you can select “Edit TMDL” from the context menu of your dataset. This will add a new folder to your VSCode workspace that represents the TMDL structure of that dataset. You can now navigate the individual .tmdl files, change them and validate them. once you are happy with the changes, you can also publish your changes back to the online dataset. The .tmdl files only reside in memory for the time of your VSCode session and will be reloaded every time. If necessary, you can also force a manual reload at any time to the the most recent version from the Power BI service.

Besides this “online”-mode, you can also save the TMDL definition locally – e.g. if you want to check it into a Git repository. The same features as described above are also available for locally stored TMDL definitions. this also includes TMDL definitions generated by other tools like Tabular Editor or pbi-tools!

To ease debugging, there is also a [Go to Error] button if your TMDL is not valid which jumps directly to the faulty TMDL file and highlights the line with the error:

To make this all work, you need to have ASP.NET Core Runtime 7.0 or higher installed as described in the docs.

So whats next?

While I do have some new features already in the backlog, I am also eagerly looking forward to gather some feedback from the community to drive future developments. So if you have a feature that you want to have added to the extension, simply open a feature request in the repository.

Due to the open architecture of VSCode, the extension also integrates with/leverages all other extensions in the Power BI space. Though, there is not much available at the moment but I hope that his ecosystem grows and sooner or later there will be a language extension for DAX or TMDL that provides intellisense/autocomplete here too, or simply syntax highlighting for the very beginning.

As this is an open-source project, you can also contribute directly by creating pull requests. If you like the extension and make sure I don’t run out of coffee while continuously improving it you can also sponsor a cup of coffee for me to contribute to this extension.