This repository curates and ranks a collection of 100 Streamlit applications, categorized by domain (e.g., Machine Learning, NLP, Computer Vision) and ranked by GitHub stars. It serves as a showcase for the Streamlit community's projects, providing inspiration and examples for developers building data-centric web applications.

How It Works

The project maintains a projects.yaml file that lists Streamlit applications with details like name, homepage, GitHub ID, and category. This YAML file is then used to generate the README.md, which presents the ranked gallery. The ranking is based on the number of GitHub stars for each project, offering a community-driven measure of popularity and impact.

Quick Start & Requirements

To contribute or view the list, no installation is required as it's a curated list presented in the README. The primary interaction is browsing the README itself.

Highlighted Details

• Showcases 100 Streamlit apps across 9 categories.
• Projects collectively have over 17,000 GitHub stars.
• Includes official Streamlit demos and community-contributed components.
• Provides clear contribution guidelines for adding new apps.

Maintenance & Community

The project is maintained by jrieke. Contributions are encouraged via GitHub issues or direct edits to the projects.yaml file. Related resources include awesome-streamlit and the official Streamlit App Gallery.

Licensing & Compatibility

The repository itself does not specify a license. The listed applications likely fall under their respective project licenses.

Limitations & Caveats

The ranking is solely based on GitHub stars, which may not reflect the quality or utility of an application. The list is a snapshot and requires manual updates to include new projects.