# Shiny for Python

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

- Category: [Python data visualization libraries](https://awesomedataviz.com/categories/python/)
- Website: https://shiny.posit.co/py/
- Repository: https://github.com/posit-dev/py-shiny
- License: MIT
- Language: Python
- Status: Active (commits in the last 90 days)
- GitHub stars: 1,756
- Commits in the last 12 months: 217
- Contributors: 48
- Last commit: Oct 2, 2026
- Latest release: v1.8.0 (Sep 13, 2026)
- Install (PyPI): `pip install shiny`, 58K downloads per week

## Overview

Shiny for Python is an open-source Python visualization library released under the MIT license. Its GitHub repository has 1,756 stars, 138 forks, and 48 contributors. It is actively developed with 217 commits in the last 12 months. The latest release, v1.8.0, was published on Sep 13, 2026. On PyPI it is downloaded about 58K times per week.

## Alternatives

- [Streamlit](https://awesomedataviz.com/tools/streamlit/): Framework for turning Python scripts into interactive data apps. (45.9K stars)
- [Dash](https://awesomedataviz.com/tools/dash/): Framework for building data apps and dashboards in Python, built on Plotly.js and React. (24.4K stars)
- [Matplotlib](https://awesomedataviz.com/tools/matplotlib/): 2D plotting library. (23.3K stars)
- [Bokeh](https://awesomedataviz.com/tools/bokeh/): Interactive Web Plotting for Python. (20.5K stars)
- [Taipy](https://awesomedataviz.com/tools/taipy/): Python framework for building data and AI web applications with interactive charts and dashboards. (19.4K stars)
- [Plotly (Python)](https://awesomedataviz.com/tools/plotly-python/): Interactive web based visualization built on top of plotly.js (18.8K stars)

## Comparisons

- [Shiny for Python vs Streamlit](https://awesomedataviz.com/compare/shiny-for-python-vs-streamlit/)

Source: https://awesomedataviz.com/tools/shiny-for-python/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com).