google-cloud-dataproc-metastore
Google Cloud Dataproc Metastore API client library
Decision gist · record as of 2026-08-14
Yes. This is the official, actively maintained client library for Dataproc Metastore on Google Cloud. Install it if you need to manage metastore services programmatically. It has low install friction, permissive licensing, no known vulnerabilities, and supports current Python versions. If you only query metadata via Hive or Spark clients, you do not need this library.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.10 or later; Google Cloud authentication credentials must be configured (via Application Default Credentials, service account key, or environment variable).
- Low install friction with a pure-Python wheel and six standard Google Cloud dependencies.
- Actively maintained with a recent release (72 days ago) and current Python version support (3.10–3.14).
License · maintenance · safety
Apache-2.0 (permissive) — Licensed under Apache-2.0 (permissive), allowing use in most commercial and open-source projects without significant legal constraints.
last release 2026-06-03 (72 days) · last repo commit 2026-08-14 · 5,371 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 78,065,066 downloads/mo, #436 on PyPI
Alternatives
Verify before relying
pip install google-cloud-dataproc-metastore
from google.cloud import metastore_v1
client = metastore_v1.DataprocMetastoreClient()
# Use client to manage metastore services- Specific metastore operations supported (create, update, delete, list, etc.) beyond lifecycle and configuration management.
- Whether the library includes async/await support or is synchronous-only.
- Performance characteristics or rate limits when managing large numbers of metastore services.
What it is and what it does
This is Google's official Python client library for the Dataproc Metastore API, a managed service for running Apache Hive metastores on Google Cloud. It wraps the underlying gRPC service definitions and provides a Pythonic interface to create, configure, monitor, and delete metastore instances. The library depends on google-auth for credential handling, grpcio and protobuf for serialization, and google-api-core for common Cloud client patterns.
Developers use this library when they need to programmatically manage metastore services as part of a larger data pipeline or infrastructure-as-code workflow. It is not a metastore itself, but rather a control-plane client—you call it to provision and configure metastores that other tools (like Spark or Hive clients) will then connect to. The library is actively maintained, supports modern Python versions, and carries no known security vulnerabilities.
Use it for
- Provision and configure Dataproc Metastore instances programmatically within infrastructure-as-code or deployment automation.
- List and monitor existing metastore services across Google Cloud projects for inventory or compliance auditing.
- Update metastore configuration (scaling, backups, network settings) in response to operational requirements.
- Integrate metastore lifecycle management into data pipeline orchestration tools or custom management dashboards.
- Automate metastore cleanup and deprovisioning as part of ephemeral data processing workflows.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
This is the official, actively maintained client library for Dataproc Metastore on Google Cloud. Install it if you need to manage metastore services programmatically. It has low install friction, permissive licensing, no known vulnerabilities, and supports current Python versions. If you only query metadata via Hive or Spark clients, you do not need this library.
Install
google-cloud-dataproc-metastore on PyPI
Before you install
Low install friction with a pure-Python wheel and six standard Google Cloud dependencies. Actively maintained with a recent release (72 days ago) and current Python version support (3.10–3.14).
Requires Python 3.10 or later; Google Cloud authentication credentials must be configured (via Application Default Credentials, service account key, or environment variable).
License in practice
Licensed under Apache-2.0 (permissive), allowing use in most commercial and open-source projects without significant legal constraints.
Quickstart
pip install google-cloud-dataproc-metastore
from google.cloud import metastore_v1
client = metastore_v1.DataprocMetastoreClient()
# Use client to manage metastore servicesVerify before relying
- Specific metastore operations supported (create, update, delete, list, etc.) beyond lifecycle and configuration management.
- Whether the library includes async/await support or is synchronous-only.
- Performance characteristics or rate limits when managing large numbers of metastore services.
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 packagesgoogle-authgrpcioproto-plusprotobufgrpc-google-iam-v1google-api-core |
| Maintenance | Actively maintained 72 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 78,065,066 / month, #436 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | 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 |
Evidence: google_cloud_dataproc_metastore-1.23.0-py3-none-any.whl
Tags
Let your AI agent find packages like this
Example. Real query, live index.
You found this page by searching. An agent finds it by wishing: SkillFed indexes 14,416 PyPI packages by what they can do, searchable in plain language.
wish › “google cloud dataproc metastore client”
- google-cloud-dataproc-metastoreA Python client library for managing Dataproc Metastore services on…
- google-cloud-dataprocA Python client library for managing Hadoop-based clusters and jobs…
- dataproc-spark-connectWraps Apache Spark Connect to let Python applications connect to…
Give your agent the search over MCP, or paste the wish link into any chat.
More Internet packages
Botocore provides low-level, data-driven access to Amazon Web Services APIs, serving as the foundation for the AWS CLI and boto3 libraries.
Install it if you need programmatic access to AWS services.
Provides an async client for AWS services using botocore and aiohttp, allowing you to call AWS APIs asynchronously within asyncio-based applications.
Install it if you need to call AWS services from async Python code; it is the standard way to do so.
Pydantic validates Python data structures against type hints, coercing and checking input at runtime to ensure it matches a declared schema.
Provides a platform-independent file locking mechanism to coordinate access to files across processes and threads.
FastAPI is a Python web framework for building REST APIs using type hints, with automatic request validation, serialization, and interactive API documentation.
Provides common Protocol Buffer message definitions used across Google Cloud APIs, enabling Python clients to interact with Google services.
See also google-cloud-dataproc · pymetastore · dataproc-spark-connect · google-cloud-bigquery-biglake · hive-metastore-client · google-cloud-filestore · google-cloud-build · google-cloud-monitoring · google-cloud-dataflow-client · google-cloud-resource-manager