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BigQuery Data Transfer: 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:

  1. Select or create a Cloud Platform project.

  2. Enable billing for your project.

  3. Enable the BigQuery Data Transfer.

  4. Setup Authentication.

Installation

Install this library in a virtual environment using venv. venv is a tool that creates isolated Python environments. These isolated environments can have separate versions of Python packages, which allows you to isolate one project’s dependencies from the dependencies of other projects.

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

Code samples and snippets

Code samples and snippets live in the samples/ folder.

Supported Python Versions

Our client libraries are compatible with all current active and maintenance versions of Python.

Python >= 3.7

Unsupported Python Versions

Python <= 3.6

If you are using an end-of-life version of Python, we recommend that you update as soon as possible to an actively supported version.

Mac/Linux

python3 -m venv <your-env>
source <your-env>/bin/activate
pip install google-cloud-bigquery-datatransfer

Windows

py -m venv <your-env>
.\<your-env>\Scripts\activate
pip install google-cloud-bigquery-datatransfer

Next Steps

Project links

Key dates

PyPI data
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  • Released:
Newer release available (3.23.0)

2 maintainers

PyPI data
Data sourced directly from PyPI's database.
Avatar for gcloudpypi from gravatar.com gcloudpypi Avatar for google_opensource from gravatar.com google_opensource

Credits

Author: Google LLC

License

Apache Software License (Apache 2.0)

Requires

Python >=3.7

Classifiers

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3.23.0

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3.22.0

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3.21.0

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3.20.0

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3.19.2

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