jsontableschema-bigquery-py
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-bigqueryStorage
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.
API Reference
Snapshot
https://github.com/frictionlessdata/jsontableschema-py#snapshot
Detailed
Contributing
Please read the contribution guideline:
Thanks!
Release files for jsontableschema-bigquery 0.5.0
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