google-cloud-bigquery-reservation
Google Cloud Bigquery Reservation API client library
Decision gist · record as of 2026-08-14
Yes, if you need to manage BigQuery reservations programmatically. The library is production-stable, actively maintained, has no known vulnerabilities, and low install friction. It's the official Google client, so it's the right choice for reservation automation. Not needed if you only query BigQuery data or manage reservations exclusively through the console.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python >= 3.10.
- Google Cloud credentials must be configured (via GOOGLE_APPLICATION_CREDENTIALS or Application Default Credentials).
- Low install friction with a pure-wheel distribution.
License · maintenance · safety
Apache-2.0 (permissive) — Apache-2.0 permissive license allows commercial and private use with minimal restrictions; suitable for most production environments.
last release 2026-06-03 (72 days) · last repo commit 2026-08-14 · 5,373 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 147,517 downloads/mo, #11,062 on PyPI
Alternatives
Verify before relying
pip install google-cloud-bigquery-reservation
from google.cloud import bigquery_reservation_v1
client = bigquery_reservation_v1.ReservationServiceClient()
project = "projects/my-project"
reservations = client.list_reservations(parent=project)- Specific reservation management operations supported (create, update, delete, list) beyond what the excerpt confirms.
- Whether the library handles slot commitments and flex slots or only standard reservations.
- Real-world performance characteristics and latency for large-scale reservation queries.
What it is and what it does
This is Google's official Python client library for the BigQuery Reservation API, a service that lets you manage reserved compute capacity on Google Cloud. It wraps the underlying gRPC and REST APIs into a Pythonic interface, handling authentication, serialization, and error handling automatically. The library is built on google-api-core and uses proto-plus for message handling, making it consistent with other Google Cloud client libraries.
You use it to programmatically create, modify, and query BigQuery reservations—the dedicated compute slots that give you predictable query performance and costs. It's primarily for infrastructure-as-code workflows, automation, and integration with larger cloud management systems. The library requires Python 3.10 or later and assumes you have Google Cloud credentials configured; it's production-stable and actively maintained by Google.
Use it for
- Automate BigQuery reservation provisioning and scaling in response to workload demands or cost optimization policies.
- Query and monitor existing reservations and slot commitments as part of a cloud cost management dashboard.
- Integrate BigQuery capacity management into infrastructure-as-code pipelines (Terraform, Pulumi, etc.).
- Build internal tools to manage team or project-level reservation allocations across multiple Google Cloud projects.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you need to manage BigQuery reservations programmatically.
The library is production-stable, actively maintained, has no known vulnerabilities, and low install friction. It's the official Google client, so it's the right choice for reservation automation. Not needed if you only query BigQuery data or manage reservations exclusively through the console.
Install
google-cloud-bigquery-reservation on PyPI
Before you install
Low install friction with a pure-wheel distribution. Actively maintained as of 2026-06-03 with recent activity. Depends on standard Google Cloud libraries (google-api-core, google-auth, grpcio, proto-plus, protobuf, grpc-google-iam-v1), all widely used and stable.
Requires Python >= 3.10. Google Cloud credentials must be configured (via GOOGLE_APPLICATION_CREDENTIALS or Application Default Credentials).
License in practice
Apache-2.0 permissive license allows commercial and private use with minimal restrictions; suitable for most production environments.
Quickstart
pip install google-cloud-bigquery-reservation
from google.cloud import bigquery_reservation_v1
client = bigquery_reservation_v1.ReservationServiceClient()
project = "projects/my-project"
reservations = client.list_reservations(parent=project)Verify before relying
- Specific reservation management operations supported (create, update, delete, list) beyond what the excerpt confirms.
- Whether the library handles slot commitments and flex slots or only standard reservations.
- Real-world performance characteristics and latency for large-scale reservation queries.
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 72 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 147,517 / month, #11,062 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_bigquery_reservation-1.25.0-py3-none-any.whl
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See also google-cloud-bigquery-datapolicies · google-cloud-bigquery-connection · google-cloud-bigquery-storage · google-cloud-bigquery-logging · google-cloud-bigquery-datatransfer · google-cloud-bigquery-biglake · google-cloud-functions · google-cloud-tasks · google-cloud-billing · excel