databricks-install-auth

Install and configure Databricks CLI and SDK authentication. Use when setting up a new Databricks integration, configuring tokens, or initializing Databricks in your project. Trigger with phrases like "install databricks", "setup databricks", "databricks auth", "configure databricks token", "databricks CLI".

Zur Installation springen

Repository: ComeOnOliver/skillshub
Letzte Quellaktivität: 23. März 2026 um 17:43
Erkannte Sprache von SKILL.md: Englisch
Sterne: 58
Forks: 20

Installationsoptionen

Standardmäßig ist der Prompt ausgewählt, der zuerst die Quelle prüft. Sie können zu einem direkten Befehl wechseln oder eine lokale Kopie herunterladen.

Quelldateien prüfen

Lesen Sie SKILL.md und alle von SkillsMP angezeigten Begleitdateien, bevor Sie sich für eine Installation entscheiden.

Zurück zur Suche Zurück zur Installation

name	databricks-install-auth
description	Install and configure Databricks CLI and SDK authentication. Use when setting up a new Databricks integration, configuring tokens, or initializing Databricks in your project. Trigger with phrases like "install databricks", "setup databricks", "databricks auth", "configure databricks token", "databricks CLI".
allowed-tools	Read, Write, Edit, Bash(pip:), Bash(databricks:), Bash(curl:*), Grep
version	1.0.0
license	MIT
author	Jeremy Longshore <jeremy@intentsolutions.io>
compatible-with	claude-code, codex, openclaw
tags	["saas","databricks","authentication"]

Databricks Install & Auth

Overview

Set up Databricks CLI v2, Python SDK, and authentication. Covers Personal Access Tokens (legacy), OAuth U2M (interactive), and OAuth M2M (service principal for CI/CD). Databricks strongly recommends OAuth over PATs for production.

Prerequisites

Python 3.8+ with pip
Databricks workspace URL (e.g., https://adb-1234567890123456.7.azuredatabricks.net)
For PAT: User Settings > Developer > Access Tokens in workspace UI
For OAuth M2M: Service principal with client ID and secret

Instructions

Step 1: Install Databricks CLI and Python SDK

set -euo pipefail

# Install CLI v2 (standalone binary — recommended)
curl -fsSL https://raw.githubusercontent.com/databricks/setup-cli/main/install.sh | sh

# Verify CLI
databricks --version

# Install Python SDK
pip install databricks-sdk

# Install Databricks Connect for local Spark development
pip install databricks-connect==14.3.*

Step 2: Configure Authentication

Option A: Personal Access Token (Quick Start)

Generate a PAT in workspace UI: User Settings > Developer > Access Tokens.

# Interactive setup — prompts for host and token
databricks configure --token

# Or set environment variables directly
export DATABRICKS_HOST="https://adb-1234567890123456.7.azuredatabricks.net"
export DATABRICKS_TOKEN="dapi_your_token_here"

Option B: OAuth U2M (User-to-Machine — Interactive)

Opens browser for OAuth consent. Token auto-refreshes (1-hour lifetime).

# Interactive OAuth login
databricks auth login --host https://adb-1234567890123456.7.azuredatabricks.net

# Verify — prints current user
databricks current-user me

Option C: OAuth M2M (Service Principal — CI/CD)

Uses client credentials flow. No browser required. Create a service principal in Account Console > Service Principals, then generate an OAuth secret.

export DATABRICKS_HOST="https://adb-1234567890123456.7.azuredatabricks.net"
 DATABRICKS_CLIENT_ID=
 DATABRICKS_CLIENT_SECRET=


databricks current-user me

# ~/.databrickscfg — one section per workspace
[DEFAULT]
host  = https://adb-dev-workspace.7.azuredatabricks.net
token = dapi_dev_token_here

[staging]
host  = https://adb-staging-workspace.7.azuredatabricks.net
token = dapi_staging_token_here

[production]
host       = https://adb-prod-workspace.7.azuredatabricks.net
client_id  = 00000000-0000-0000-0000-000000000000
client_secret = dose_prod_secret_here

# Use a specific profile
databricks workspace list / --profile staging

from databricks.sdk import WorkspaceClient

# Auto-detects from env vars or ~/.databrickscfg
w = WorkspaceClient()

me = w.current_user.me()
print(f"Authenticated as: {me.user_name}")
print(f"Workspace: {w.config.host}")
print(f"Auth type: {w.config.auth_type}")

# Quick smoke test — list clusters
clusters = list(w.clusters.list())
print(f"Clusters found: {len(clusters)}")

from databricks.sdk import WorkspaceClient
from databricks.sdk.config import Config

# Explicit M2M config for CI/CD scripts
config = Config(
    host="https://adb-1234567890123456.7.azuredatabricks.net",
    client_id="00000000-0000-0000-0000-000000000000",
    client_secret="dose00000000000000000000000000000000",
)
w = WorkspaceClient(config=config)

# Or use a named profile
w = WorkspaceClient(profile="production")

Error	Cause	Solution
`INVALID_TOKEN`	Token expired or revoked	Generate a new PAT or re-run `databricks auth login`
`Could not resolve host`	Wrong workspace URL	Verify URL format: `https://adb-<id>.<region>.azuredatabricks.net`
`PERMISSION_DENIED`	Token lacks required entitlements	Ensure user/SP has workspace access in Account Console
`SSL: CERTIFICATE_VERIFY_FAILED`	Corporate proxy intercepts TLS	Set `REQUESTS_CA_BUNDLE=/path/to/cert.pem`
`Connection refused`	VPN or firewall blocking	Check corporate firewall rules for workspace domain
`No matching profile`	Profile name typo in `~/.databrickscfg`	Run `databricks auth profiles` to list available profiles

from databricks.sdk import AccountClient

# Account-level operations (manage workspaces, users, billing)
a = AccountClient(
    host="https://accounts.cloud.databricks.com",
    account_id="00000000-0000-0000-0000-000000000000",
    client_id="sp-client-id",
    client_secret="sp-secret",
)

for ws in a.workspaces.list():
    print(f"{ws.workspace_name}: {ws.deployment_name}")

from databricks.sdk import WorkspaceClient

# Uses Azure Default Credential chain (works in Azure VMs, AKS, Functions)
w = WorkspaceClient(
    host="https://adb-1234567890123456.7.azuredatabricks.net",
    azure_workspace_resource_id="/subscriptions/<sub>/resourceGroups/<rg>/providers/Microsoft.Databricks/workspaces/<ws>",
)