11/3/2022 0 Comments Azure data studio extensions![]()
Jupyter Books are organized collections of Notebooks that you can section into chapters to clearly communicate to the reader different topics associated with the Notebooks. Notebooks are a powerful tool to implement tasks from data cleaning and transformation to statistical modeling, and to data visualization. #AZURE DATA STUDIO EXTENSIONS CODE#Tip: Jupyter Notebooks, documents that can contain rich text cells and executable code cells are supported in Azure Data Studio. The Jupyter Notebook and Jupyter Book templates guide the user through creating, packaging, and shipping a book or notebook extension, which allows you to spend more time focused on content creation. Jupyter Notebooks and Books templatesĪzure Data Studio extensions are a mechanism by which you can share your Notebooks with other data professionals. Or, for step-by-step instructions, follow this tutorial. When prompted, select New Dashboard from the list of template options. ![]() #AZURE DATA STUDIO EXTENSIONS INSTALL#To get started with the dashboard template, install and run the extension generator. Dashboard contributions allow you to surface your additions in the UI, with little to no TypeScript code required. If you are a prospective extension author interested in expanding the functionality of Azure Data Studio, contributing to the dashboard is an easy to use, powerful solution. Dashboard insights: Graphs that run against a SQL Server connection.Toolbar actions: Actions on the homepage toolbar, such as Run Query and Get Notebook.Dashboard tabs: Separate tabs dedicated to your extension.Our template eases the process of writing extensions that contribute to the dashboard. The Azure Data Studio dashboard is a tool that summarizes and provides insight into users’ server and database connections. Jupyter Notebooks and Jupyter Books template.In our most recent release, we have added three highly requested extension templates to the generator. It includes extension templates that enable users to create and publish extensions with minimal technical knowledge required. #AZURE DATA STUDIO EXTENSIONS GENERATOR#The Azure Data Studio extension generator is a command line tool designed to help extension authors get started with the process of extension development. Install the generator through npm and get started with extension development with these Azure Data Studio extension tutorials. The release of the Azure Data Studio extension generator is now available. In the Data > Connection section, modify the settings.json to reflect your color choices.This post is co-authored by Anjali Agarwal and Laura Jiang. Go back to File > Preferences > Settings. I used the Fill setting.ĭrag your server connections to the appropriate server group.Īnd voila! The next time you create a query, the query tab will take on the color of the server group.īy the way, if you ever want to get fancy and modify the color palette, you can: Let’s set up the tabs!Ī critical point to remember is that connections have to be organized into server groups.Ĭlick the New Server Group folder to create.Īdd the Server group name, Group description, and Group color. ![]() I operate under the basic assumption that I’m usually at fault, but maybe a more thorough explanation could benefit others as well. However, I soon found myself struggling a bit. Microsoft’s Docs are usually a dream resource. My first step was to read the Azure Data Studio documentation. So as I normally do, I set out to create these tabs. My thinking is that I’ll better understand and explain new features and functionality. ![]() Typically I go through all steps when documenting a process. In addition, one of our backend developers recently introduced me to the Feynman Technique. Below is an example of what you can accomplish using this feature.Īs a documentarian, I don’t work with Azure Data Studio daily. Better visual indicators mean less opportunity for errors and mistakes when running queries. They allow you to visually separate different connections to development, staging, and production databases. If you’ve ever worked in Azure Data Studio, you may find tab colors very useful. ![]()
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