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Install & Compatibility
Where this runs
tested against v1.22.0 · pip install
no network on importno background threads
Install × environment matrix
Each cell = how many times install + import succeeded across repeated harness runs. Partial = flaky.
glibc = Debian/Ubuntu slim · musl = Alpine Linux
muslpy 3.10–3.920 runs
installs and imports cleanly · install 0.0s · import 0.000s · 68.4MB
glibcpy 3.10–3.920 runs
installs and imports cleanly · install 5.4s · import 0.000s · 66MB
67MB installed
● package 67MB
Code
Verified usage
Verified import paths — ran on the pinned version, not inferred.
BigQueryConnectionServiceClient
✓ from google.cloud import bigquery_connection_v1
✗ from google.cloud.bigquery_connection_v1 import BigQueryConnectionServiceClient
This quickstart demonstrates how to instantiate the BigQuery Connection client and list existing connections within a specified Google Cloud project and location. Authentication is typically handled automatically via Application Default Credentials (ADC) or the `GOOGLE_APPLICATION_CREDENTIALS` environment variable.
import os
from google.cloud import bigquery_connection_v1
# It is highly recommended to set the GOOGLE_APPLICATION_CREDENTIALS environment variable
# to the path of your service account key file for authentication.
# For example (Linux/macOS): export GOOGLE_APPLICATION_CREDENTIALS="/path/to/keyfile.json"
# Or set programmatically, but generally discouraged for production:
# os.environ["GOOGLE_APPLICATION_CREDENTIALS"] = "/path/to/keyfile.json"
def list_bigquery_connections(project_id: str, location: str):
"""Lists all BigQuery connections in a given project and location."""
client = bigquery_connection_v1.BigQueryConnectionServiceClient()
# The parent resource for connections is formatted as 'projects/{project}/locations/{location}'
parent = f"projects/{project_id}/locations/{location}"
print(f"Listing connections in project '{project_id}' at location '{location}':")
try:
# API call to list connections
for connection in client.list_connections(parent=parent):
print(f" Connection Name: {connection.name}")
print(f" Connection Type: {connection.cloud_resource.connection_type.name}")
print(f" Description: {connection.friendly_name or 'N/A'}")
# You can access other connection properties like `cloud_sql` or `aws` here
except Exception as e:
print(f"Error listing connections: {e}")
print("Please ensure the BigQuery Connection API is enabled for your project ")
print("and the service account has the 'BigQuery Connection User' role or equivalent permissions.")
# Replace with your actual project ID and desired location
# It's best practice to get project_id from the environment or Google Cloud metadata.
PROJECT_ID = os.environ.get("GOOGLE_CLOUD_PROJECT", "your-gcp-project-id")
LOCATION = "us" # Example: "us", "eu", "asia-east1"
if PROJECT_ID == "your-gcp-project-id":
print("WARNING: Please set the 'GOOGLE_CLOUD_PROJECT' environment variable ")
print(" or replace 'your-gcp-project-id' with your actual project ID.")
print(" Authentication and API calls will likely fail without proper setup.")
else:
list_bigquery_connections(PROJECT_ID, LOCATION)
Debug
Known issues
breakingThe library officially supports Python 3.9 and newer. Older Python versions (3.8 and below) are not supported, and new major versions of Google Cloud client libraries often drop support for end-of-life Python versions.fixUpgrade your Python environment to 3.9 or a newer supported version.
affects: <1.0.0 (older versions), >=1.0.0 (current)
gotchaAuthentication is a common hurdle. Ensure your environment is correctly set up for Google Cloud authentication (e.g., `GOOGLE_APPLICATION_CREDENTIALS` environment variable pointing to a service account key file, or running in a Google Cloud environment with appropriate service account permissions).fixRefer to Google Cloud authentication documentation. Ensure the service account used has necessary roles like 'BigQuery Connection User' and 'BigQuery Connection Admin'.
affects: All versions
gotchaMany BigQuery Connection API methods (like `list_connections`) require `project_id` and `location` parameters, often combined into a 'parent' resource path (e.g., `projects/{project}/locations/{location}`). Incorrectly formatted resource paths will result in API errors.fixAlways construct resource paths carefully following the API's expected format, as specified in the method's documentation.
affects: All versions
gotchaThe BigQuery Connection API must be explicitly enabled in your Google Cloud Project. If not enabled, API calls will result in 'API not enabled' or similar permission errors.fixEnable the 'BigQuery Connection API' via the Google Cloud Console or `gcloud services enable bigqueryconnection.googleapis.com`.
affects: All versions
gotchaIn the broader Google Cloud client ecosystem, version incompatibilities can occur between `google-api-core` and specific `google-cloud-*` client libraries. For instance, `google-api-core==1.34.0` caused issues with older `google-cloud-bigquery` versions.fixIf encountering unexpected errors, try pinning `google-api-core` to a slightly older version (e.g., `pip install google-api-core==1.33.2`) or ensure all `google-cloud-*` libraries are updated to their latest versions.
affects: Potentially specific minor versions of `google-cloud-bigquery-connection` with `google-api-core`
Upgrade
Version history
1.22.0latest on PyPI · released Jun 3, 2026
Audit
Dependencies
PythonrequiredRequires Python 3.9 or newer.
google-api-corerequiredCore dependency for Google Cloud Python client libraries, handles API requests and common client functionality.
google-authrequiredManages authentication with Google Cloud services.