What is the Databricks extension for Visual Studio Code?

To start using the Databricks extension for Visual Studio Code right away, skip ahead to the VSCode extension for Databricks tutorial: Run Python on a cluster and as a job.

The Databricks extension for Visual Studio Code enables you to connect to your remote Databricks workspaces from the Visual Studio Code integrated development environment (IDE) running on your local development machine. Through these connections, you can:

• Synchronize local code that you develop in Visual Studio Code with code in your remote workspaces.

• Run local Python code files from Visual Studio Code on Databricks clusters in your remote workspaces.

• Run local Python code files (.py) and Python, R, Scala, and SQL notebooks (.py, .ipynb, .r, .scala, and .sql) from Visual Studio Code as automated Databricks jobs in your remote workspaces.

Note

The Databricks extension for Visual Studio Code supports running R, Scala, and SQL notebooks as automated jobs but does not provide any deeper support for these languages within Visual Studio Code.

The Databricks extension for Visual Studio Code, version 2, currently in Private Preview, also enables you to use Visual Studio Code to define, deploy, and run Databricks Asset Bundles by applying CI/CD patterns and best practices to your Databricks jobs, Delta Live Tables pipelines, and MLOps Stacks. See What are Databricks Asset Bundles? and Use Databricks Asset Bundles with version 2 of the extension.

To start using the Databricks extension for Visual Studio Code, version 2, see VSCode extension for Databricks, version 2 tutorial: Run Python on a cluster and as a job.

Getting started

• Try out the extension by starting with a hands-on tutorial. See the VSCode extension for Databricks tutorial: Run Python on a cluster and as a job.

• After you complete the tutorial, do one or more of the following with the extension:

  • Authenticate the Databricks extension for Visual Studio Code to your Databricks workspace by using a Databricks authentication type other than Databricks personal access token authentication. See Authentication setup for the Databricks extension for Visual Studio Code.

  • Select a different cluster to connect to in your workspace. See Select a cluster for the Databricks extension for Visual Studio Code.

  • Select a different workspace directory to connect to in your workspace. See Select a workspace directory for the Databricks extension for Visual Studio Code.

  • Debug your code by using Databricks Connect integration. See Debug code by using Databricks Connect for the Databricks extension for Visual Studio Code.

  • Test your code by using pytest. See Run tests with pytest for the Databricks extension for Visual Studio Code.