databricks-sdk
Databricks SDK for Python (Beta)
Decision gist · record as of 2026-08-14
Yes. The SDK is actively maintained, has no known vulnerabilities, low install friction, and permissive licensing. It is the official client for Databricks REST APIs and is suitable for production use despite its Beta label. Install it if you need programmatic access to Databricks workspaces from Python.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.10 or later; authentication credentials must be configured via environment variables, configuration profiles, or hard-coded arguments.
- Low install friction; pure Python wheel with four common dependencies (requests, google-auth, protobuf, urllib3).
- Actively maintained with a release 1 day old.
License · maintenance · safety
permissive license (permissive) — Permissive license (Apache) allows commercial and private use without restriction.
last release 2026-08-13 (1 days)
0 known vulnerabilities (OSV.dev, 2026-08-14) · 136,969,643 downloads/mo, #280 on PyPI
Alternatives
Verify before relying
pip install databricks-sdk
from databricks.sdk import WorkspaceClient
w = WorkspaceClient()
for cluster in w.clusters.list():
print(cluster.cluster_name)- Exact scope of REST API coverage—whether all endpoints are wrapped or only a subset.
- Performance characteristics and rate-limiting behavior of the internal HTTP client.
- Whether interface stability guarantees apply to specific API groups or the entire SDK.
What it is and what it does
The Databricks SDK for Python is an official client library that wraps all public Databricks REST APIs into Python objects and methods. It handles authentication automatically via environment variables or configuration profiles, and includes built-in retry logic and error handling for robust HTTP communication. The SDK is marked Beta, meaning it is supported for production use but may have breaking changes in future releases.
Typical usage involves instantiating a WorkspaceClient, then calling methods to list, create, or manage Databricks resources—clusters, jobs, notebooks, Unity Catalog objects, and more. The SDK integrates with Databricks Runtimes (bundled in version 13.1+) and supports OAuth, PAT tokens, and cloud-native authentication methods (Azure, GCP, AWS). Long-running operations and paginated responses are handled transparently.
Use it for
- Automate cluster provisioning, job scheduling, and workspace resource management from Python scripts or applications.
- Build CI/CD pipelines that deploy notebooks, run jobs, and validate Lakehouse configurations programmatically.
- Migrate or sync metadata between Databricks workspaces or integrate Databricks with external data platforms.
- Write monitoring and governance tools that query workspace state, audit logs, and access controls.
- Develop web applications or services that need to interact with Databricks on behalf of users (OAuth flow).
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
The SDK is actively maintained, has no known vulnerabilities, low install friction, and permissive licensing. It is the official client for Databricks REST APIs and is suitable for production use despite its Beta label. Install it if you need programmatic access to Databricks workspaces from Python.
Install
databricks-sdk on PyPI
Before you install
Low install friction; pure Python wheel with four common dependencies (requests, google-auth, protobuf, urllib3). Actively maintained with a release 1 day old. Supports current Python versions (3.10+).
Requires Python 3.10 or later; authentication credentials must be configured via environment variables, configuration profiles, or hard-coded arguments.
License in practice
Permissive license (Apache) allows commercial and private use without restriction.
Quickstart
pip install databricks-sdk
from databricks.sdk import WorkspaceClient
w = WorkspaceClient()
for cluster in w.clusters.list():
print(cluster.cluster_name)Verify before relying
- Exact scope of REST API coverage—whether all endpoints are wrapped or only a subset.
- Performance characteristics and rate-limiting behavior of the internal HTTP client.
- Whether interface stability guarantees apply to specific API groups or the entire SDK.
Package facts
| License | permissive license permissive |
| Python support | Supports the current Python release >=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 4 packagesrequestsgoogle-authprotobufurllib3 |
| Maintenance | Actively maintained 1 days since the last release |
| First released | |
| Downloads | 136,969,643 / month, #280 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 4 - BetaIntended Audience :: DevelopersIntended Audience :: Science/ResearchIntended Audience :: System AdministratorsLicense :: OSI Approved :: Apache Software LicenseOperating System :: OS IndependentProgramming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13 |
Evidence: databricks_sdk-0.128.0-py3-none-any.whl
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