Skip to content

Latest commit

 

History

History
118 lines (82 loc) · 3.78 KB

README.md

File metadata and controls

118 lines (82 loc) · 3.78 KB
Raw

tableschema-bigquery-py

Travis Coveralls PyPi Github Gitter

Generate and load BigQuery tables based on Table Schema descriptors.

Features

  • implements tableschema.Storage interface

Contents

Getting Started

Installation

The package use semantic versioning. It means that major versions could include breaking changes. It's highly recommended to specify package version range in your setup/requirements file e.g. package>=1.0,<2.0.

pip install tableschema-bigquery

Prepare BigQuery

To start using Google BigQuery service:

  • Create a new project - link
  • Create a service key - link
  • Download json credentials and set GOOGLE_APPLICATION_CREDENTIALS environment variable

Documentation

import io
import os
import json
from datapackage import Package
from apiclient.discovery import build
from oauth2client.client import GoogleCredentials

# Prepare BigQuery credentials
os.environ['GOOGLE_APPLICATION_CREDENTIALS'] = '.credentials.json'
credentials = GoogleCredentials.get_application_default()
service = build('bigquery', 'v2', credentials=credentials)
project = json.load(io.open('.credentials.json', encoding='utf-8'))['project_id']

# Save package to BigQuery
package = Package('datapackage.json')
package.save(storage='bigquery', service=service, project=project, dataset='dataset')

# Load package from BigQuery
package = Package(storage='bigquery', service=service, project=project, dataset='dataset')
package.resources

API Reference

Storage

Storage(self, service, project, dataset, prefix='')

BigQuery storage

Package implements Tabular Storage interface (see full documentation on the link):

Storage

Only additional API is documented

Arguments

  • service (object): BigQuery Service object
  • project (str): BigQuery project name
  • dataset (str): BigQuery dataset name
  • prefix (str): prefix for all buckets

Contributing

The project follows the Open Knowledge International coding standards.

Recommended way to get started is to create and activate a project virtual environment. To install package and development dependencies into active environment:

$ make install

To run tests with linting and coverage:

$ make test

Changelog

Here described only breaking and the most important changes. The full changelog and documentation for all released versions could be found in nicely formatted commit history.

v1.0

  • Initial driver realease