Skip to main content

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

Project description

Travis
Coveralls
PyPi
SemVer
Gitter

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.

API Reference

Snapshot

https://github.com/frictionlessdata/jsontableschema-py#snapshot

Detailed

Contributing

Please read the contribution guideline:

How to Contribute

Thanks!

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

jsontableschema-bigquery-0.5.0.tar.gz (8.0 kB view details)

Uploaded Source

Built Distribution

jsontableschema_bigquery-0.5.0-py2.py3-none-any.whl (9.5 kB view details)

Uploaded Python 2 Python 3

File details

Details for the file jsontableschema-bigquery-0.5.0.tar.gz.

File metadata

File hashes

Hashes for jsontableschema-bigquery-0.5.0.tar.gz
Algorithm Hash digest
SHA256 2aa5db666d81c652aa3a0cc6ffc7d5a668518a2455b9901d44f82af0f7d77197
MD5 d545c1d3c8dc1f029b66bc541f8b8983
BLAKE2b-256 07e6acc1ca3ef200c44967705c16f7c2db0c8dd9a8c274786e3b74f4eafa393c

See more details on using hashes here.

Provenance

File details

Details for the file jsontableschema_bigquery-0.5.0-py2.py3-none-any.whl.

File metadata

File hashes

Hashes for jsontableschema_bigquery-0.5.0-py2.py3-none-any.whl
Algorithm Hash digest
SHA256 ab26f4b081130675b7ec0b2f55ecf047ad840a8493a990a93d3356f3ad6a053e
MD5 a00d2925498046f38be74fe091497aa8
BLAKE2b-256 5808efcf7dab5af14aa683d67c519a0f6235c3c940d8d7dbd877093d891f5dc2

See more details on using hashes here.

Provenance

Supported by

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