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|GA| |pypi| |versions|
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
_.. |GA| image:: https://img.shields.io/badge/support-GA-gold.svg :target: https://github.com/googleapis/google-cloud-python/blob/main/README.rst#general-availability .. |pypi| image:: https://img.shields.io/pypi/v/bigquery-magics.svg :target: https://pypi.org/project/bigquery-magics/ .. |versions| image:: https://img.shields.io/pypi/pyversions/bigquery-magics.svg :target: https://pypi.org/project/bigquery-magics/ .. _BigQuery: https://cloud.google.com/bigquery/what-is-bigquery .. _Library Documentation: https://googleapis.dev/python/bigquery-magics/latest .. _Product Documentation: https://cloud.google.com/bigquery/docs/reference/v2/
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.
_.. _Select or create a Cloud Platform project.: https://console.cloud.google.com/project .. _Enable billing for your project.: https://cloud.google.com/billing/docs/how-to/modify-project#enable_billing_for_a_project .. _Enable the Google Cloud BigQuery API.: https://cloud.google.com/bigquery .. _Setup Authentication.: https://googleapis.dev/python/google-api-core/latest/auth.html
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.
.. _`virtualenv`: https://virtualenv.pypa.io/en/latest/
Supported Python Versions
^^^^^^^^^^^^^^^^^^^^^^^^^
Python >= 3.7
Unsupported Python Versions
^^^^^^^^^^^^^^^^^^^^^^^^^^^
Python == 3.5, Python == 3.6.
Mac/Linux
^^^^^^^^^
.. code-block:: console
pip install virtualenv
virtualenv <your-env>
source <your-env>/bin/activate
<your-env>/bin/pip install bigquery-magics
Windows
^^^^^^^
.. code-block:: console
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.
.. code-block::
%load_ext bigquery_magics
Perform a query
.. code:: python
%%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
Since BigQuery supports Python via BigQuery DataFrames, %%bqsql
is offered as
an alias to clarify the language of these cells.
.. code:: python
%%bqsql
SELECT name, SUM(number) as count
FROM 'bigquery-public-data.usa_names.usa_1910_current'
GROUP BY name
ORDER BY count DESC
LIMIT 3
FAQs
Google BigQuery magics for Jupyter and IPython
We found that bigquery-magics demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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