AwesomeDataviz

Python dashboard & data app frameworks

Turn Python scripts and notebooks into interactive web apps. 7 tools, ranked by GitHub stars and updated .

Frameworks for building dashboards and data apps entirely in Python, without writing JavaScript. Streamlit reruns a script top to bottom on each interaction, Dash and Shiny for Python use callbacks and reactive programming, and Panel and Voilà turn notebooks into apps.

By GitHub stars, the most popular Python dashboard frameworks here are Streamlit (46.2K stars), Dash (24.5K stars), and Taipy (19.5K stars). 6 of 7 had commits in the last 90 days.
1 Streamlit

Framework for turning Python scripts into interactive data apps.

 46.2K 2,690 Apache-2.0
2 Dash

Framework for building data apps and dashboards in Python, built on Plotly.js and React.

 24.5K 1,388 MIT
3 Taipy

Python framework for building data and AI web applications with interactive charts and dashboards.

 19.5K 59 Apache-2.0
4 Voilà

Turns Jupyter notebooks into standalone interactive web applications.

 6K 12 BSD
5 Panel

Data exploration and web app framework for Python that works with many plotting libraries.

 5.8K 497 BSD-3-Clause
6 Vizro

Low-code toolkit from McKinsey for building data visualization apps and dashboards, built on Dash.

 3.8K 326 Apache-2.0
7 Shiny for Python

Python version of the Shiny reactive framework for interactive data apps.

 1.8K 263 MIT

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Frequently asked questions

What is the most popular Python dashboard framework?

By GitHub stars, Streamlit is the most popular, with 46.2K stars, followed by Dash (24.5K) and Taipy (19.5K).

Which Python dashboard frameworks are actively maintained?

7 of the 7 tools listed had commits in the last 12 months, including Streamlit, Dash, Taipy, Voilà, and Panel. Each tool page shows monthly commit activity.

Are these Python dashboard frameworks free and open source?

7 of the 7 tools listed use an OSI-approved open-source license. The most common license here is Apache-2.0.

Missing a tool? Add it with a one-line pull request to the README.