Skip to main content

BigQuery Data Transfer API client library

Project description

GA pypi versions

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:

  1. Select or create a Cloud Platform project.

  2. Enable the BigQuery Data Transfer API.

  3. Setup Authentication.

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

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

google-cloud-bigquery-datatransfer-2.1.0.tar.gz (62.3 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

google_cloud_bigquery_datatransfer-2.1.0-py2.py3-none-any.whl (65.8 kB view details)

Uploaded Python 2Python 3

File details

Details for the file google-cloud-bigquery-datatransfer-2.1.0.tar.gz.

File metadata

  • Download URL: google-cloud-bigquery-datatransfer-2.1.0.tar.gz
  • Upload date:
  • Size: 62.3 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.5.0.1 requests/2.24.0 setuptools/50.3.0 requests-toolbelt/0.9.1 tqdm/4.50.0 CPython/3.8.0

File hashes

Hashes for google-cloud-bigquery-datatransfer-2.1.0.tar.gz
Algorithm Hash digest
SHA256 0cca79f6ee312159ec3f3b7fea218c3dd51408d39c429ecbea037982e91cc827
MD5 81bf8ffeaac98e4684ff5b84b25dc035
BLAKE2b-256 9cd789236c54e421d8be7b0dbfc86d6cb5a4df7f37da596772ca012fac4685b1

See more details on using hashes here.

File details

Details for the file google_cloud_bigquery_datatransfer-2.1.0-py2.py3-none-any.whl.

File metadata

  • Download URL: google_cloud_bigquery_datatransfer-2.1.0-py2.py3-none-any.whl
  • Upload date:
  • Size: 65.8 kB
  • Tags: Python 2, Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.5.0.1 requests/2.24.0 setuptools/50.3.0 requests-toolbelt/0.9.1 tqdm/4.50.0 CPython/3.8.0

File hashes

Hashes for google_cloud_bigquery_datatransfer-2.1.0-py2.py3-none-any.whl
Algorithm Hash digest
SHA256 1622f08249c740cf7a5bb1eafa5fba5de26b3ad615886a5c06c2cbb12d2183fa
MD5 ef8ef95d26b3e5a2953430b64e577d57
BLAKE2b-256 3ee2386af37e55ee7de59b867c6c5fc25bd8772361b18006e8b61dd03bdc5fa5

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page