TheBigQuery Data Transfer API allows users to transfer data from partnerSaaS applications to Google BigQuery on a scheduled, managed basis.

• Client Library Documentation

• Product Documentation

Quick Start

In order to use this library, you first need to go through the following steps:

1. Select or create a Cloud Platform project.

2. Enable the BigQuery Data Transfer API.

3. Setup Authentication.

Installation

Install this library in avirtualenv using pip.virtualenv is a tool tocreate isolated Python environments. The basic problem it addresses is one ofdependencies and versions, and indirectly permissions.

Withvirtualenv, it’s possible to install this library without needing systeminstall permissions, and without clashing with the installed systemdependencies.

Supported Python Versions

Python >= 3.6

Deprecated Python Versions

Python == 2.7.

The last version of this library compatible with Python 2.7 isgoogle-cloud-bigquery-datatransfer==1.1.1.

Mac/Linux

pip install virtualenvvirtualenv <your-env>source <your-env>/bin/activate<your-env>/bin/pip install google-cloud-bigquery-datatransfer

Windows

pip install virtualenvvirtualenv <your-env><your-env>\Scripts\activate<your-env>\Scripts\pip.exe install google-cloud-bigquery-datatransfer

Example Usage

DataTransferServiceClient

from google.cloud importbigquery_datatransfer_v1client =bigquery_datatransfer_v1.DataTransferServiceClient()parent = client.location_path('[PROJECT]', '[LOCATION]')# Iterate over all resultsfor element in client.list_data_sources(parent):    # process element    pass# Or iterate over results one page at a timefor page in client.list_data_sources(parent).pages:    for element in page:        # process element        pass

Next Steps

• Read theClient Library Documentation for BigQuery Data Transfer APIAPI to see other available methods on the client.

• Read theProduct documentation to learnmore about the product and see How-to Guides.