How can I use PyCharm with Azure Databricks?

PyCharm by JetBrains is a dedicated Python integrated development environment (IDE) providing a wide range of essential tools for Python developers, tightly integrated to create a convenient environment for productive Python, web, and data science development. You can use PyCharm on your local development machine to write, run, and debug Python code in remote Azure Databricks workspaces:

Name	Use this when you want to…
Databricks Connect in PyCharm with Python	Use PyCharm to write, run, and debug local Python code on a remote Azure Databricks workspace.
Databricks Asset Bundles	Use PyCharm to make authoring, deploying, and running bundles easier. Databricks Asset Bundles (or bundles for short) enable you to programmatically define, deploy, and run Azure Databricks jobs, Delta Live Tables pipelines, and MLOps Stacks by using CI/CD best practices and workflows.
Databricks CLI	Use the built-in Terminal in PyCharm to work with Azure Databricks from the command line.
Databricks SDK for Python	Use PyCharm to write, run, and debug Python code that works with Azure Databricks.
Databricks SQL Connector for Python	Use PyCharm to write, run, and debug Python code that works with Databricks SQL warehouses in remote Azure Databricks workspaces.
Provision infrastructure	Use the Terraform and HCL plugin for PyCharm to make it easier to provision Azure Databricks infrastructure with Terraform and follow infrastructure-as-code (IaC) best practices. Use PyCharm to write and deploy Python definitions of Azure Databricks infrastructure through third-party offerings such as the Cloud Development Kit for Terraform (CDKTF) and Pulumi.