google-cloud-dataproc-metastore

Google Cloud Dataproc Metastore API client library

google-cloud-dataproc-metastore Permissive license Apache-2.0 Active ★ 5,370 v1.23.0 released 2026-06-03

Install

google-cloud-dataproc-metastore on PyPI

pip

pip install google-cloud-dataproc-metastore

uv

uv add google-cloud-dataproc-metastore

poetry

poetry add google-cloud-dataproc-metastore

Package facts

License	Apache-2.0 (permissive)
Python support	supports the current Python release (>=3.10)
Install friction	low — pure-Python wheel
Runtime dependencies	6 — google-auth, grpcio, proto-plus, protobuf, grpc-google-iam-v1, google-api-core
Maintenance	actively maintained — 71 days since the last release
Last repo commit	2026-08-13
First released	2021-03-16
Popularity	one of the top 1,000 most-downloaded packages on PyPI (30-day window, as of 2026-08-13)
Known vulnerabilities	none known (OSV.dev, checked 2026-08-13)

Evidence: google_cloud_dataproc_metastore-1.23.0-py3-none-any.whl

Development Status :: 5 - Production/StableIntended Audience :: DevelopersLicense :: OSI Approved :: Apache Software LicenseOperating System :: OS IndependentProgramming Language :: PythonProgramming Language :: Python :: 3Programming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14Topic :: Internet

About google-cloud-dataproc-metastore

from the package's own PyPI description — quoted content, verbatim

Python Client for Dataproc Metastore

Dataproc Metastore_: The Dataproc Metastore API is used to manage the lifecycle and configuration of metastore services.

Client Library Documentation_
Product Documentation_

.. |stable| image:: https://img.shields.io/badge/support-stable-gold.svg :target: https://github.com/googleapis/google-cloud-python/blob/main/README.rst#stability-levels .. |pypi| image:: https://img.shields.io/pypi/v/google-cloud-dataproc-metastore.svg :target: https://pypi.org/project/google-cloud-dataproc-metastore/ .. |versions| image:: https://img.shields.io/pypi/pyversions/google-cloud-dataproc-metastore.svg :target: https://pypi.org/project/google-cloud-dataproc-metastore/ .. _Dataproc Metastore: https://cloud.google.com/dataproc-metastore/ .. _Client Library Documentation: https://cloud.google.com/python/docs/reference/metastore/latest/summary_overview .. _Product Documentation: https://cloud.google.com/dataproc-metastore/

Quick Start

In order to use this library, you first need to go through the following steps:

`Select or create a Cloud Platform...

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AI interpretation — verify before relying

AI-generated interpretation of the package facts above; every digit, version, license, or vulnerability id it cites is grounded in the facts already shown on this page

Python client library for managing Dataproc Metastore services on Google Cloud, handling lifecycle and configuration of metastore instances through the Dataproc Metastore API.

Low friction: pure Python wheel with six Google Cloud dependencies (google-auth, grpcio, proto-plus, protobuf, grpc-google-iam-v1, google-api-core). Active maintenance with recent release 71 days ago and ongoing repository activity.

Apache-2.0 permissive license allows commercial use, modification, and distribution with minimal restrictions; suitable for most projects.

Usage

pip install google-cloud-dataproc-metastore

from google.cloud import dataproc_metastore_v1

client = dataproc_metastore_v1.DataprocMetastoreClient()

Requires Python >= 3.10; Google Cloud credentials must be configured (via GOOGLE_APPLICATION_CREDENTIALS or Application Default Credentials).

Verdict: Production-ready Google Cloud client library with active maintenance, no known vulnerabilities, and permissive licensing. Straightforward installation with standard Google Cloud dependencies. Best suited for teams already using Google Cloud Platform and needing programmatic metastore management.

Needs verification

Whether the six runtime dependencies introduce any transitive security concerns beyond the OSV scan performed.
Specific use cases or limitations when working with Dataproc Metastore versions across different GCP regions.

google cloud dataproc metastore clientdataproc metastore api pythonmanage metastore services gcpgoogle cloud python client librarydataproc metadata managementcloud metastore lifecycle managementgcp dataproc configuration