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A Python Voilà simplification library

Project description


Python library to simplify the creation of impactful Voilà dashboards.

The online documentation for the vois library is available here

The PDF documentation for the vois library is available here

The source repository is available here

The vois library contains:

package vois: helper functions for tasks not directly related to ipyvuetify (manage geojson files, create an interactive map to display custom geojson, simplify visualization of hierarchical data in Plotly, create custom SVG visualizations, etc.)

package vois/vuetify: classes to simplify the development of GUIs using ipyvuetify (each source file contains a wrapper to simplify the usage of a ipyvuetify widget)


VOIS library is released under a EUPL Version 1.2 license.


The vois library can be installed using this command:

pip install vois


The tutorial section of the documentation available here provides a step by step example for the construction of a dashboard to display EUROSTAT data on Energy Consumption in Europe.


These are the links to all the steps of the example dashboard deployed and published by Hugginface Spaces:

Step.1: Creation of the dashboard structure using the app class

Step.2: Use Pandas to read the input CSVs and display the DataFrame as a table

Step.3: Add the filtering controls to the dashboard to select countries and sector

Step.4: Add the Plotly Bar Chart View

Step.5: Add the SVG Static Map View

Step.6: Add the Dynamic Map View

Step.7: Add the functions for downloading chart, table and map

Step.8: Manage the parameters passsed in the URL and open external URLs

Step.9: Add an interactive AnimatedPieChart in SVG to select the consumption sector

Step.Final: Add minipanel to footer bar and the function to generate and download a report in docx format

Step.Final.Dark: Dark version of the final dashboard

An example multi-page dashboard can be viewed at this link: Example multi-page dashboard


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