google-cloud-dataproc
Google Cloud Dataproc API client library
Decision gist · record as of 2026-08-14
Yes. This is the official, actively maintained client library for Dataproc—essential if you need to manage Dataproc clusters or jobs from Python. Low install friction, permissive license, no known vulnerabilities, and broad Python version support make it a straightforward choice for any GCP-based data processing workflow.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python >= 3.10.
- Google Cloud authentication must be configured (via service account key, Application Default Credentials, or environment variable).
- Low install friction with a pure-Python wheel distribution.
License · maintenance · safety
Apache-2.0 (permissive) — Licensed under Apache-2.0 (permissive), allowing commercial use, modification, and distribution with minimal restrictions—suitable for most production and proprietary projects.
last release 2026-07-08 (37 days) · last repo commit 2026-08-14 · 5,371 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 27,559,983 downloads/mo, #858 on PyPI
Alternatives
Verify before relying
pip install google-cloud-dataproc
from google.cloud import dataproc_v1
client = dataproc_v1.ClusterControllerClient()
# Use client to manage Dataproc clusters- Specific examples of cluster creation, job submission, or monitoring workflows are not detailed in the excerpt.
- Performance characteristics or rate limits for large-scale cluster operations are not documented in the provided material.
What it is and what it does
This is the official Python client library for Google Cloud Dataproc, a managed service for running Apache Hadoop, Spark, and other open-source data processing frameworks on Google Cloud Platform. It provides a programmatic interface to create, manage, monitor, and delete Dataproc clusters, as well as submit and track jobs running on those clusters.
The library wraps the Dataproc REST API and uses gRPC for communication, built on top of google-api-core and google-auth for authentication and request handling. It supports current Python versions (3.10 through 3.14) and is actively maintained by Google. The package is designed for developers who need to automate Dataproc infrastructure and job orchestration as part of larger data pipelines or cloud applications.
Use it for
- Automate provisioning and teardown of Hadoop or Spark clusters for batch data processing jobs.
- Submit and monitor MapReduce, Spark, or Hive jobs to Dataproc clusters from Python applications.
- Integrate Dataproc cluster management into data pipeline orchestration tools or workflow frameworks.
- Programmatically scale cluster resources or update cluster configurations in response to workload demands.
- Build multi-tenant data processing platforms that dynamically allocate Dataproc resources per tenant or job.
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—essential if you need to manage Dataproc clusters or jobs from Python. Low install friction, permissive license, no known vulnerabilities, and broad Python version support make it a straightforward choice for any GCP-based data processing workflow.
Install
google-cloud-dataproc on PyPI
Before you install
Low install friction with a pure-Python wheel distribution. Actively maintained with a recent release 37 days ago. Depends on standard Google Cloud client libraries (google-api-core, google-auth, grpcio, proto-plus, protobuf, grpc-google-iam-v1), all of which are widely used and stable.
Requires Python >= 3.10. Google Cloud authentication must be configured (via service account key, Application Default Credentials, or environment variable).
License in practice
Licensed under Apache-2.0 (permissive), allowing commercial use, modification, and distribution with minimal restrictions—suitable for most production and proprietary projects.
Quickstart
pip install google-cloud-dataproc
from google.cloud import dataproc_v1
client = dataproc_v1.ClusterControllerClient()
# Use client to manage Dataproc clustersVerify before relying
- Specific examples of cluster creation, job submission, or monitoring workflows are not detailed in the excerpt.
- Performance characteristics or rate limits for large-scale cluster operations are not documented in the provided material.
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-api-coregoogle-authgrpcioproto-plusprotobufgrpc-google-iam-v1 |
| Maintenance | Actively maintained 37 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 27,559,983 / month, #858 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-5.30.0-py3-none-any.whl
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See also google-cloud-dataproc-metastore · yarn-api-client · dataproc-spark-connect · google-cloud-dataflow-client · google-cloud-monitoring · google-cloud-build · google-cloud-batch · google-cloud-functions · hdfs · snakebite-py3