google-cloud-bigquery-logging
Google Cloud Bigquery Logging API client library
Decision gist · record as of 2026-08-14
Yes, if you need to interact with BigQuery Logging from Python. The package is production-stable, actively maintained, has no known vulnerabilities, and carries a permissive license. Install friction is low. The main requirement is that you have a Google Cloud project with BigQuery Logging enabled and valid authentication credentials.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 (service account key, Application Default Credentials, or equivalent).
- Low install friction; pure Python wheel with six Google Cloud SDK dependencies.
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) · 589,239 downloads/mo, #5,862 on PyPI
Alternatives
Verify before relying
pip install google-cloud-bigquery-logging
from google.cloud import bigquery_logging
# Requires Google Cloud credentials (via GOOGLE_APPLICATION_CREDENTIALS or ADC)
client = bigquery_logging.Client()- Specific API methods and classes available in the client beyond basic instantiation
- Whether this package is the primary entry point or a lower-level utility within the broader google-cloud-python ecosystem
- Real-world performance characteristics and typical latency for BigQuery logging operations
What it is and what it does
This is Google's official Python client library for the BigQuery Logging API. It wraps the underlying gRPC and REST interfaces to BigQuery's logging service, handling authentication, serialization, and protocol details so you can work with BigQuery logging in idiomatic Python code.
The library depends on google-api-core, google-auth, grpcio, proto-plus, protobuf, and grpc-google-iam-v1 to manage credentials, gRPC transport, and protocol buffer message handling. It requires Python 3.10 or later and is actively maintained by Google. Setup requires a Google Cloud project with BigQuery Logging enabled and proper authentication credentials configured.
Use it for
- Send application logs to BigQuery for centralized analysis and querying alongside other cloud data
- Integrate BigQuery logging into existing Google Cloud monitoring and observability pipelines
- Programmatically manage BigQuery logging configuration from Python applications
- Build audit trails and compliance logging systems that store events in BigQuery tables
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you need to interact with BigQuery Logging from Python.
The package is production-stable, actively maintained, has no known vulnerabilities, and carries a permissive license. Install friction is low. The main requirement is that you have a Google Cloud project with BigQuery Logging enabled and valid authentication credentials.
Install
google-cloud-bigquery-logging on PyPI
Before you install
Low install friction; pure Python wheel with six Google Cloud SDK dependencies. Actively maintained with recent release (72 days ago) and no known vulnerabilities.
Requires Python >= 3.10. Google Cloud authentication must be configured (service account key, Application Default Credentials, or equivalent).
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-logging
from google.cloud import bigquery_logging
# Requires Google Cloud credentials (via GOOGLE_APPLICATION_CREDENTIALS or ADC)
client = bigquery_logging.Client()Verify before relying
- Specific API methods and classes available in the client beyond basic instantiation
- Whether this package is the primary entry point or a lower-level utility within the broader google-cloud-python ecosystem
- Real-world performance characteristics and typical latency for BigQuery logging operations
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 | 589,239 / month, #5,862 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_logging-1.10.0-py3-none-any.whl
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See also google-cloud-bigquery-storage · google-cloud-appengine-logging · google-cloud-audit-log · google-cloud-language · google-cloud-bigquery-connection · google-cloud-dataform · google-cloud-bigquery-biglake · google-cloud-bigquery-reservation · google-cloud-logging · google-cloud-error-reporting