Streamlit-awesome-table
by caiodearaujo
Feature-Rich Interactive Tables for Streamlit Apps
A powerful Streamlit component that transforms data presentation with sortable, searchable, and stylish Bootstrap tables enhanced with FontAwesome icons.
- Built with Python
- Bootstrap-powered responsive design that adapts to all screen sizes
- MIT License license
About This Project
Streamlit Awesome Table elevates data visualization in Streamlit applications by providing an enterprise-grade table component that goes far beyond basic dataframe displays. Built on Bootstrap's robust styling framework and enhanced with FontAwesome icons, this component delivers professional-looking tables with minimal configuration.
The component addresses a common pain point for Streamlit developers: the need for interactive, user-friendly tables that support sorting, searching, and pagination out of the box. Instead of building custom solutions or settling for basic st.dataframe displays, developers can implement feature-complete tables that feel native to modern web applications.
With over 178 stars and active community adoption, this component has proven its value in production Streamlit dashboards and data applications. It seamlessly integrates Bootstrap's responsive design patterns, ensuring tables look great on any device while maintaining Streamlit's signature simplicity.
Whether you're building internal business tools, data analytics dashboards, or customer-facing applications, this component provides the polish and functionality users expect from professional web applications without requiring frontend development expertise.
Key Features
- Bootstrap-powered responsive design that adapts to all screen sizes
- Built-in sorting functionality for organizing data by any column
- Integrated search capability for quick data filtering
- Pagination support for handling large datasets efficiently
- FontAwesome icon integration for enhanced visual communication
How You Can Use It
Building admin dashboards with sortable user data and management controls
Creating data analytics reports with searchable and filterable result tables
Displaying product catalogs or inventory lists with pagination and quick search
Presenting financial data or transaction histories with organized, professional formatting
Who Is This For?
Data scientists, Python developers, and business analysts building Streamlit applications who need professional table displays without frontend coding