Databricks Connect for Python

note

This article covers Databricks Connect for Databricks Runtime 13.3 LTS and above.

Databricks Connect enables you to connect popular IDEs such as PyCharm, notebook servers, and other custom applications to Databricks compute. See What is Databricks Connect?.

• For Databricks Connect for Scala, see Databricks Connect for Scala.
• For Databricks Connect for R, see Databricks Connect for R.

Get started

To get started with Databricks Connect for Python:

• Confirm that your workspace and local development environment meet the Databricks Connect requirements and choose a Databricks Connect package version that is compatible with your configuration. See Databricks Connect usage requirements.
• Install Databricks Connect. See Install Databricks Connect for Python.
• Walk through a Databricks Connect for Python tutorial, either Tutorial: Run code from PyCharm on classic compute or Tutorial: Run code on serverless compute.

Additional resources

To learn more about Databricks Connect, see the following:

• To configure compute, see Compute configuration for Databricks Connect.
• Use Databricks Connect with other IDEs, notebook servers, and the Spark shell.
• For simple code examples, see Code examples for Databricks Connect for Python.
• To view more complex code examples, see the example applications for Databricks Connect repository in GitHub, specifically:
  • A simple ETL application
  • An interactive data application based on Plotly
  • An interactive data application based on Plotly and PySpark AI
• To use Databricks Utilities with Databricks Connect, see Databricks Utilities with Databricks Connect for Python.
• To migrate from Databricks Connect for Databricks Runtime 12.2 LTS and below to Databricks Connect for Databricks Runtime 13.3 LTS and above, see Migrate to Databricks Connect for Python.
• See also information about troubleshooting and limitations.