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databricks-isv-python-dbconnect

Configure PWAF-compliant Databricks Connect authentication and telemetry for Python Spark workloads.

5|1|Updated Apr 8, 2026
Search Tags:#authentication#oauth#python#telemetry#spark#databricks#connect
One-click install
npx skills add https://github.com/databricks-solutions/partner-ai-dev-kit --skill databricks-isv-python-dbconnect
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: databricks-isv-python-dbconnect
Source: https://github.com/databricks-solutions/partner-ai-dev-kit/tree/main/skills/python-dbconnect
Command: npx skills add https://github.com/databricks-solutions/partner-ai-dev-kit --skill databricks-isv-python-dbconnect

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Databricks Connect for Python enables PWAF-aligned Spark applications to securely authenticate (PAT, OAuth M2M, or OAuth U2M) and to emit standard telemetry, allowing ISVs to build compliant Databricks integrations that work with serverless or classic compute.

Core Features & Use Cases

  • PWAF-aligned authentication patterns: PAT, OAuth M2M, and U2M (PKCE or token-env)
  • Telemetry guidance and User-Agent instrumentation for Databricks Connect
  • Flexible compute options: serverless or classic clusters, with host and token management

Quick Start

Install the databricks-connect package, configure DATABRICKS_HOST and authentication vars, and run a sample Spark job against Databricks.

Frequently Asked Questions about databricks-isv-python-dbconnect

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I configure Databricks Connect for Python authentication on serverless compute?▼

You can configure authentication by setting DATABRICKS_HOST alongside PAT, OAuth M2M, or U2M credentials, enabling PWAF-compliant Databricks Connect for Python access on serverless or classic compute.

What authentication methods does Databricks Connect for Python support?▼

Databricks Connect for Python supports PAT, OAuth M2M, and U2M (PKCE or token-env) authentication methods, allowing ISVs to build secure PWAF-compliant Spark integrations for Databricks.

Can I use OAuth U2M with PKCE for Databricks Connect Python workloads?▼

Yes, OAuth U2M with PKCE is fully supported for Databricks Connect Python workloads, enabling interactive user authentication flows that satisfy PWAF compliance for Spark applications.

How do I add telemetry and User-Agent instrumentation to Spark applications on Databricks?▼

You add telemetry by configuring the provided environment variables and Config options, ensuring Databricks Connect for Python emits standard User-Agent instrumentation for compliant Spark workloads.

Does databricks-connect work with both serverless and classic compute clusters?▼

Yes, databricks-connect works with both serverless and classic compute clusters, supporting flexible compute configuration through host normalization and token management for Spark workloads.

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