Python Client for BigQuery Data Transfer API

The BigQuery Data Transfer API allows users to transfer data from partner SaaS applications to Google BigQuery on a scheduled, managed basis.

Quick Start

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

Installation

Install this library in a virtualenv using pip. virtualenv is a tool to create isolated Python environments. The basic problem it addresses is one of dependencies and versions, and indirectly permissions.

With virtualenv , it’s possible to install this library without needing system install permissions, and without clashing with the installed system dependencies.

Supported Python Versions

Python >= 3.6

Deprecated Python Versions

Python == 2.7.

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

Mac/Linux

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

Windows

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

Example Usage

DataTransferServiceClient

 from google.cloud import bigquery_datatransfer_v1 
client = bigquery_datatransfer_v1 
. DataTransferServiceClient 
()

parent = client.location_path('[PROJECT]', '[LOCATION]')


# Iterate over all results
for element in client. list_data_sources 
(parent):
    # process element
    pass

# Or iterate over results one page at a time
for page in client. list_data_sources 
(parent).pages:
    for element in page:
        # process element
        pass

Next Steps

Read the Client Library Documentation for BigQuery Data Transfer API API to see other available methods on the client.
Read the Product documentation to learn more about the product and see How-to Guides.