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Databricks Python Sdk

Listed
databricks-solutions·vlatest·backend

Provides Python guidance and assistance for developing backend services and APIs.

Repository

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

  1. 1

    Run this in your project

    terminal
    $ npx skills add databricks-solutions/ai-dev-kit --skill databricks-python-sdk -a claude-code

  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

databricks-solutions

Taken from the source listing. We haven't verified who controls this account.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

No human has reviewed this code. The checks below are a static scan of the files at one commit — nobody has run this skill or judged whether it works. A skill runs with whatever access you give your agent, so read the source before you install it.

Automated safety checks

scanned

This skill failed 1 of 6 checks. A failure is not proof of bad intent; it means something in the code needs a human to look at it before you run it.

  • No undeclared network calls: failed

    Contacts 2 hosts that are neither well-known infrastructure nor declared in the skill's frontmatter: accounts.cloud.databricks.com, adb-123456789.azuredatabricks.net.

    Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.

    Hosts contacted

    databricks-sdk-py.readthedocs.ioproject documentationadb-123456789.azuredatabricks.netundeclaredaccounts.cloud.databricks.comundeclared

    What it found

    • .claude/skills/databricks-python-sdk/examples/1-authentication.py:49contacts adb-123456789.azuredatabricks.net
      host="https://adb-123456789.azuredatabricks.net",
    • .claude/skills/databricks-python-sdk/examples/1-authentication.py:63contacts accounts.cloud.databricks.com
      host="https://accounts.cloud.databricks.com",

  • Declares what it does: passed

    SKILL.md parses and declares a name and a description.

    SKILL.md exists, its frontmatter parses, and it declares a name and a description.

  • No obfuscated payloads: passed

    No encoded or obfuscated payloads.

    No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.

  • No credential access: passed

    Reads no keys, tokens, keychains or credential files.

    Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.

  • No pipe-to-shell installers: passed

    No pipe-to-shell or download-and-run installers.

    No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.

  • Pinned to a commit: passed

    Scanned databricks-solutions/ai-dev-kit at b059fd017a.

    The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.

Commit
b059fd017a
Manifest
.claude/skills/databricks-python-sdk/SKILL.md
Scanned
7 files, 1,766 lines
This is a static scan, not a review. It reads the skill's files; it does not run them, and it cannot tell you whether the skill is any good or whether the code does what its description says. A skill runs with whatever access you give your agent.
What each check looks for →

About this skill

The Databricks Python SDK skill enables AI agents to interact directly with the Databricks platform using official Python libraries. It allows for programmatic access to core services like Delta Lake, MLflow, and Jobs without requiring manual API configuration.

When to use it

  • Automating data pipeline orchestration and job scheduling within a Databricks workspace.
  • Retrieving real-time metrics from MLflow experiments or model registry endpoints.
  • Executing SQL queries against Delta tables for ad-hoc analytics tasks.
  • Deploying machine learning models directly into production environments via the SDK.

Key capabilities

  • Direct integration with Databricks Runtime libraries.
  • Support for managing clusters, notebooks, and workspaces programmatically.
  • Seamless handling of Delta Lake operations and transformations.
  • Native compatibility with MLflow tracking and deployment workflows.

Example prompts

  • "Use the Databricks Python SDK to list all active jobs in my workspace and display their latest run status."
  • "Query the Delta table sales_2024 using the SDK and return the top 10 records by revenue."
  • "Register a new model version in MLflow using the SDK and set it as the current production model."

Tips & gotchas

Ensure your AI agent has valid authentication credentials (e.g., Databricks tokens or service principals) before attempting to execute commands. The SDK requires Python 3.8+ and specific Databricks Runtime versions; verify compatibility with your workspace configuration to avoid runtime errors.