Access the Labelbox Connector for Google BigQuery to easily perform the following functionalities:

• lbbq.client.create_data_rows_from_table : Creates Labelbox data rows (and metadata) given a BigQuery table
• lbbq.client.create_table_from_dataset : Creates a BigQuery table given a Labelbox dataset
• lbbq.client.upsert_table_metadata : Updates BigQuery table metadata columns given a Labelbox dataset
• lbbq.client.upsert_labelbox_metadata : Updates Labelbox metadata given a BigQuery table

The Demo code supplied in this Github is designed to run in a Google Colab, but the code can be adapted to any notebook environment.

Labelbox is the enterprise-grade training data solution with fast AI enabled labeling tools, labeling automation, human workforce, data management, a powerful API for integration & SDK for extensibility. Visit Labelbox for more information.

This library is currently in beta. It may contain errors or inaccuracies and may not function as well as commercially released software. Please report any issues/bugs via Github Issues.

• Requirements
• Configuration
• Use

• Google Cloud BigQuery Authenticated Client
• Google BigQuery SDK
• Labelbox account
• Generate a Labelbox API key

Install Labelbox-BigQuery to your Python environment. The installation will also add the Labelbox SDK and BigQuery SDK.

pip install labelboxbigquery
import labelboxbigquery

The client class requires the following arguments:

• lb_api_key = Labelbox API Key
• google_key = Google Service Account Permissions dict, how to create one here
• google_project_name = Google Project ID / Name