.. visualization_toolkit documentation master file, created by
   sphinx-quickstart on Sat Jul 13 13:40:31 2024.
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Welcome to visualization_toolkit's documentation!
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The ``visualization_toolkit``  contains utilities to create interactive charts, and data applications based on plotly and dash while following company styling.
The toolkit is the foundational package installed on every Atlas application to power analytics.

Getting Started
==================

Installing in a python project
--------------------------
* The ``visualization_toolkit`` can be used in a python project and is commonly installed in a dash application
* If you are using the `Atlas Repo Template <https://github.com/Yipit/atlas_repo_template>`_, the dependencies are already in ``requirements.txt``. Run ``make setup`` to install the library.
* For general python use (make sure Jfrog is configured in your environment):
.. code-block:: bash
   :caption: Install via pip

   pip install visualization-toolkit

* Import the library in python
.. code-block:: python
   :caption: Using the library in python

   from visualization_toolkit.helpers.plotly import chart

   fig = chart(...)


Installing from Databricks
--------------------------
* In Databricks notebooks, the ``visualization_toolkit`` operates the same way as a repo-based library
* Add this to the top of your notebook as a cell
.. code-block:: python
   :caption: Enabling repo access in a notebook

   import sys
   sys.path.append("/Workspace/Repos/ETL_Production/visualization_toolkit")

* Then in subsequent notebook cells, import the library in python and use
.. code-block:: python
   :caption: Using the library in a notebook cell

   from visualization_toolkit.helpers.plotly import chart

   fig = chart(...)

   display(fig)

* The ``chart`` function returns a plotly ``go.Figure`` object. If this is returned in a cell it will automatically display the figure. In addition, you can call ``display(figure)`` in databricks to visualize inside a cell.


Using the documentation
--------------------------
Navigate to each module of the ``visualization_toolkit`` to learn about the functions provided and how to use them.

- **plotly**: Contains functions using plotly for generating charts in databricks or dash-based apps.
- **dash**: Contains standard functions to simplify dash application development. Used by Atlas applications.
- **chart recipes**: Contains many examples of how to create and tune charts with live outputs. *Recommended to reference these examples when learning to build visualizations*.

.. toctree::
   :maxdepth: 3
   :caption: Contents:
   :glob:

   plotly

   theme

   dash

   recipes/index

   mutable_table


Indices and tables
==================

* :ref:`genindex`
* :ref:`modindex`
* :ref:`search`


.. meta::
   :description: The visualization toolkit contains many charting functions to build high quality data experiences using plotly and dash.
                 The functions encapsulate standard company styling, visualization best practices, and common utilities to build rich data applications.