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Generate BigQuery tables, load and extract data, based on JSON Table Schema descriptors.

Project Description

Generate and load BigQuery tables based on JSON Table Schema descriptors.

Version v0.3 contains breaking changes:
  • renamed Storage.tables to Storage.buckets
  • changed Storage.read to read into memory
  • added Storage.iter to yield row by row

Getting Started

Installation

pip install jsontableschema-bigquery

Storage

Package implements Tabular Storage interface.

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

We can get storage this way:

import io
import os
import json
from apiclient.discovery import build
from oauth2client.client import GoogleCredentials
from jsontableschema_bigquery import Storage

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']
storage = Storage(service, project, 'dataset', prefix='prefix')

Then we could interact with storage:

storage.buckets
storage.create('bucket', descriptor)
storage.delete('bucket')
storage.describe('bucket') # return descriptor
storage.iter('bucket') # yields rows
storage.read('bucket') # return rows
storage.write('bucket', rows)

Mappings

schema.json -> bigquery table schema
data.csv -> bigquery talbe data

Drivers

Default Google BigQuery client is used - docs.

Contributing

Please read the contribution guideline:

How to Contribute

Thanks!

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