bigquery-magics 0.2.0

Description:

bigquerymagics 0.2.0

Querying massive datasets can be time consuming and expensive without the
right hardware and infrastructure. Google BigQuery solves this problem by
enabling super-fast, SQL queries against append-mostly tables, using the
processing power of Google’s infrastructure.

Library Documentation
Product Documentation


Quick Start
In order to use this library, you first need to go through the following steps:

Select or create a Cloud Platform project.
Enable billing for your project.
Enable the Google Cloud BigQuery API.
Setup Authentication.


Installation
Install this library in a virtualenv using pip. virtualenv is a tool to
create isolated Python environments. The basic problem it addresses is one of
dependencies and versions, and indirectly permissions.
With virtualenv, it’s possible to install this library without needing system
install permissions, and without clashing with the installed system
dependencies.

Supported Python Versions
Python >= 3.7


Unsupported Python Versions
Python == 3.5, Python == 3.6.


Mac/Linux
pip install virtualenv
virtualenv <your-env>
source <your-env>/bin/activate
<your-env>/bin/pip install bigquery-magics


Windows
pip install virtualenv
virtualenv <your-env>
<your-env>\Scripts\activate
<your-env>\Scripts\pip.exe install bigquery-magics




Example Usage
To use these magics, you must first register them. Run the %load_ext bigquery_magics
in a Jupyter notebook cell.
%load_ext bigquery_magics

Perform a query
%%bigquery
SELECT name, SUM(number) as count
FROM 'bigquery-public-data.usa_names.usa_1910_current'
GROUP BY name
ORDER BY count DESC
LIMIT 3