Generate BigQuery tables, load and extract data, based on JSON Table Schema descriptors.
Project description
tableschema-bigquery-py
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):
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
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
Built Distribution
Hashes for tableschema-bigquery-1.0.1.tar.gz
Algorithm | Hash digest | |
---|---|---|
SHA256 | b756a5375be8d4682679c1b57d52eadc468e517fcff3f061a28d002383e0b03b |
|
MD5 | 3d4339fa0a9bd03783e1af34ab255d14 |
|
BLAKE2b-256 | de91bc21d6c0878594be9227fbf6b1caf6a144d19ce82dc0bb9081391dc9c1d1 |
Hashes for tableschema_bigquery-1.0.1-py2.py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 5ab94f089fce21c83dd8614e99bd33e59d6df5b16b6c07f98ab8f16f918775b0 |
|
MD5 | 70e688f55df325eac913a60bd0265230 |
|
BLAKE2b-256 | a93961fd22e9ebdff4bc8b0f37b84361567b9c8aeeac0836dba103493e061f84 |