Awesome Streamlit
Purpose: The Awesome Streamlit project aims to share knowledge and resources related to Streamlit, a powerful Python library for building beautiful web applications from data science projects.
Key Features:
- Curated Resources: Comprehensive lists of Streamlit applications, tutorials, articles, and alternative technologies.
- Community Contributions: Allows users to contribute their own resources, helping to build a collaborative space for learning.
- Getting Started Guide: Detailed instructions on setting up the development environment and deploying apps locally or on the cloud.
- Testing and Quality Assurance: Built-in testing frameworks to ensure code quality and functionality.
Benefits:
- Streamlined Development: Facilitates building quick and effective data applications with minimal setup.
- Resource Accessibility: Central hub for discovering educational material about Streamlit, enhancing learning opportunities for users.
- Community Engagement: Encourages contributions and discussions to support an open-source community.
Highlights:
- Home to multiple real-world applications showcasing the power and simplicity of Streamlit.
- Maintained by Marc Skov Madsen, an experienced data scientist and developer.
Engage with the project here or visit the Awesome Streamlit website!