IPython Magics for BigQuery
===========================
|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/
Quick Start
-----------
In order to use this library, you first need to go through the following steps:
1. `Select or create a Cloud Platform project.`_
2. `Enable billing for your project.`_
3. `Enable the Google Cloud BigQuery API.`_
4. `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
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"description": "IPython Magics for BigQuery\n===========================\n\n|GA| |pypi| |versions|\n\nQuerying massive datasets can be time consuming and expensive without the\nright hardware and infrastructure. Google `BigQuery`_ solves this problem by\nenabling super-fast, SQL queries against append-mostly tables, using the\nprocessing power of Google's infrastructure.\n\n- `Library Documentation`_\n- `Product Documentation`_\n\n.. |GA| image:: https://img.shields.io/badge/support-GA-gold.svg\n :target: https://github.com/googleapis/google-cloud-python/blob/main/README.rst#general-availability\n.. |pypi| image:: https://img.shields.io/pypi/v/bigquery-magics.svg\n :target: https://pypi.org/project/bigquery-magics/\n.. |versions| image:: https://img.shields.io/pypi/pyversions/bigquery-magics.svg\n :target: https://pypi.org/project/bigquery-magics/\n.. _BigQuery: https://cloud.google.com/bigquery/what-is-bigquery\n.. _Library Documentation: https://googleapis.dev/python/bigquery-magics/latest\n.. _Product Documentation: https://cloud.google.com/bigquery/docs/reference/v2/\n\nQuick Start\n-----------\n\nIn order to use this library, you first need to go through the following steps:\n\n1. `Select or create a Cloud Platform project.`_\n2. `Enable billing for your project.`_\n3. `Enable the Google Cloud BigQuery API.`_\n4. `Setup Authentication.`_\n\n.. _Select or create a Cloud Platform project.: https://console.cloud.google.com/project\n.. _Enable billing for your project.: https://cloud.google.com/billing/docs/how-to/modify-project#enable_billing_for_a_project\n.. _Enable the Google Cloud BigQuery API.: https://cloud.google.com/bigquery\n.. _Setup Authentication.: https://googleapis.dev/python/google-api-core/latest/auth.html\n\nInstallation\n~~~~~~~~~~~~\n\nInstall this library in a `virtualenv`_ using pip. `virtualenv`_ is a tool to\ncreate isolated Python environments. The basic problem it addresses is one of\ndependencies and versions, and indirectly permissions.\n\nWith `virtualenv`_, it's possible to install this library without needing system\ninstall permissions, and without clashing with the installed system\ndependencies.\n\n.. _`virtualenv`: https://virtualenv.pypa.io/en/latest/\n\n\nSupported Python Versions\n^^^^^^^^^^^^^^^^^^^^^^^^^\nPython >= 3.7\n\nUnsupported Python Versions\n^^^^^^^^^^^^^^^^^^^^^^^^^^^\nPython == 3.5, Python == 3.6.\n\n\nMac/Linux\n^^^^^^^^^\n\n.. code-block:: console\n\n pip install virtualenv\n virtualenv <your-env>\n source <your-env>/bin/activate\n <your-env>/bin/pip install bigquery-magics\n\n\nWindows\n^^^^^^^\n\n.. code-block:: console\n\n pip install virtualenv\n virtualenv <your-env>\n <your-env>\\Scripts\\activate\n <your-env>\\Scripts\\pip.exe install bigquery-magics\n\nExample Usage\n-------------\n\nTo use these magics, you must first register them. Run the ``%load_ext bigquery_magics``\nin a Jupyter notebook cell.\n\n.. code-block::\n\n %load_ext bigquery_magics\n\nPerform a query\n~~~~~~~~~~~~~~~\n\n.. code:: python\n\n %%bigquery\n SELECT name, SUM(number) as count\n FROM 'bigquery-public-data.usa_names.usa_1910_current'\n GROUP BY name\n ORDER BY count DESC\n LIMIT 3\n",
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