Azure Management Data Bricks Client Library for Python

Warnings

• breaking The credential system was completely revamped in v2.x. Classes like `azure.common.credentials` or `msrestazure.azure_active_directory` are no longer supported. You must migrate to `azure-identity` classes (e.g., `DefaultAzureCredential`). The client constructor parameter `credentials` was renamed to `credential`.
  Fix: Replace old credential classes with `azure.identity` and update the client instantiation to use the `credential` parameter.
• breaking Operations that previously returned `msrest.polling.LROPoller` for long-running operations (LROs) now return `azure.core.polling.LROPoller` and are typically prefixed with `begin_` (e.g., `create_or_update` becomes `begin_create_or_update`).
  Fix: Update method calls to use the `begin_` prefix for LROs and handle the `azure.core.polling.LROPoller` return type.
• breaking The exception hierarchy has been simplified. Most exceptions are now `azure.core.exceptions.HttpResponseError`. The `CloudError` exception has been removed.
  Fix: Update exception handling to catch `azure.core.exceptions.HttpResponseError` instead of `CloudError`.
• gotcha This library (`azure-mgmt-databricks`) is for *managing* Azure Databricks workspaces and resources (create, update, delete). It is distinct from the `Databricks SDK for Python` (pypi: `databricks-sdk`), which is used for interacting with Databricks *within* a Databricks environment (e.g., notebooks, jobs, clusters, data plane operations) or through the Databricks REST API. Users often confuse these two, leading to incorrect package usage for their intended task.
  Fix: Ensure you are using the correct SDK for your task: `azure-mgmt-databricks` for Azure resource management, `databricks-sdk` for in-workspace or Databricks API interactions.
• gotcha Python 2.7 support for Azure SDK for Python packages ended on January 1, 2022. This `azure-mgmt-databricks` package specifically requires Python 3.7 or newer.
  Fix: Ensure your environment uses Python 3.7 or a later version.

Install

• pip install azure-mgmt-databricks azure-identity Install package and authentication library

Imports

• AzureDatabricksManagementClient

  from azure.mgmt.databricks import AzureDatabricksManagementClient

• DefaultAzureCredential

  from azure.identity import DefaultAzureCredential

Quickstart

This quickstart demonstrates how to authenticate using `DefaultAzureCredential` and list Azure Databricks workspaces within a subscription. Ensure `AZURE_SUBSCRIPTION_ID`, and potentially `AZURE_CLIENT_ID`, `AZURE_TENANT_ID`, `AZURE_CLIENT_SECRET` environment variables are set for successful authentication.

import os
from azure.identity import DefaultAzureCredential
from azure.mgmt.databricks import AzureDatabricksManagementClient

# Set these environment variables or replace with actual values
# AZURE_SUBSCRIPTION_ID, AZURE_CLIENT_ID, AZURE_TENANT_ID, AZURE_CLIENT_SECRET
subscription_id = os.environ.get("AZURE_SUBSCRIPTION_ID", "")

if not subscription_id:
    raise ValueError("AZURE_SUBSCRIPTION_ID environment variable not set.")

# Authenticate using DefaultAzureCredential
# This will try to authenticate using various methods (env vars, managed identity, Azure CLI, etc.)
credential = DefaultAzureCredential()

# Create the Databricks Management Client
client = AzureDatabricksManagementClient(credential=credential, subscription_id=subscription_id)

# Example: List all Databricks workspaces in the subscription
print("Listing Databricks workspaces:")
for workspace in client.workspaces.list_by_subscription():
    print(f"  - {workspace.name} (Resource Group: {workspace.id.split('/')[4]}) (Location: {workspace.location})")