databricks-hello-world

name	databricks-hello-world
description	Create a minimal working Databricks example with cluster and notebook. Use when starting a new Databricks project, testing your setup, or learning basic Databricks patterns. Trigger with phrases like "databricks hello world", "databricks example", "databricks quick start", "first databricks notebook", "create cluster".
allowed-tools	Read, Write, Edit, Bash(databricks:*), Bash(python:*)
version	1.0.0
license	MIT
author	Jeremy Longshore <[e-mail]>
compatible-with	claude-code, codex, openclaw
tags	["saas","databricks","testing"]

Databricks Hello World

Overview

Create your first Databricks cluster and notebook via the REST API and Python SDK. Covers single-node dev clusters, SQL warehouses, notebook upload, one-time job runs, and Delta Lake smoke tests.

Prerequisites

• Completed databricks-install-auth setup
• Workspace access with cluster creation permissions
• Valid API credentials in env vars or ~/.databrickscfg

Instructions

Step 1: Create a Single-Node Dev Cluster

# POST /api/2.0/clusters/create
databricks clusters create --json '{
  "cluster_name": "hello-world-dev",
  "spark_version": "14.3.x-scala2.12",
  "node_type_id": "i3.xlarge",
  "autotermination_minutes": 30,
  "num_workers": 0,
  "spark_conf": {
    "spark.databricks.cluster.profile": "singleNode",
    "spark.master": "local[*]"
  },
  "custom_tags": {
    "ResourceClass": "SingleNode"
  }
}'
# Returns: {"cluster_id": "0123-456789-abcde123"}

Or via Python SDK:

from databricks.sdk import WorkspaceClient
from databricks.sdk.service.compute import AutoScale

w = WorkspaceClient()

# create_and_wait blocks until cluster reaches RUNNING state
cluster = w.clusters.create_and_wait(
    cluster_name="hello-world-dev",
    spark_version="14.3.x-scala2.12",
    node_type_id="i3.xlarge",
    num_workers=0,
    autotermination_minutes=30,
    spark_conf={
        "spark.databricks.cluster.profile": "singleNode",
        "spark.master": "local[*]",
    },
)
print(f"Cluster ready: {cluster.cluster_id} ({cluster.state})")

Step 2: Create and Upload a Notebook

import base64
from databricks.sdk import WorkspaceClient
from databricks.sdk.service.workspace  ImportFormat, Language

w = WorkspaceClient()

notebook_source = 

me = w.current_user.me()
notebook_path = 

w.workspace.import_(
    path=notebook_path,
    =ImportFormat.SOURCE,
    language=Language.PYTHON,
    content=base64.b64encode(notebook_source.encode()).decode(),
    overwrite=,
)
()