Here's the official website for **Streamlit:**: [https://streamlit.io/](https://streamlit.io/) - **What is Streamlit?** - **Superpower for Python Developers:** Streamlit is an open-source Python framework that allows data scientists and machine learning engineers to quickly turn their code into beautiful, interactive web applications. - **Minimal Web Dev Knowledge Needed:** Its unique approach abstracts away most of the web development complexity. You primarily write familiar Python code with Streamlit commands to create UI elements. - **Data Science & ML Focus:** Streamlit comes with built-in support for common data science and visualization libraries (pandas, matplotlib, plotly, etc.), making it ideal for showcasing models, data analysis, and dashboards. **Key Features** - **Simple API:** Uses intuitive commands to create interactive elements like sliders, text boxes, buttons, plots, and more. - **Dynamic Updates:** Apps intelligently re-run relevant code sections when a user interacts with UI elements, providing a seamless experience. - **Flexible Layouts:** While not drag-and-drop, Streamlit offers layout controls to organize components, and is adapting more advanced CSS styling options. - **Caching:** Improves performance by caching expensive computations and data loading. - **Community and Ecosystem:** Streamlit has a thriving community, abundant resources, and integrations with popular libraries. **Why Choose Streamlit** - **Rapid Prototyping:** Perfect for quickly building and sharing internal tools, data exploration dashboards, or machine learning demos. - **Interactive Data Exploration:** Lets you and your users interactively investigate data through filters, visualizations, and transformations directly within a web app. - **Lowering Barrier to Entry:** Enables Python developers with less web experience to create polished applications, democratizing the deployment process. - **Beyond Simple Demos:** While it excels in quick prototyping, Streamlit is powerful enough to build full-fledged data analysis applications and user-facing tools. **Considerations** - **Some Layout Limitations:** If you need highly granular, pixel-perfect web design, Streamlit might feel restrictive compared to traditional frontend frameworks. - **Evolving Framework:** Streamlit is rapidly developing, so some features and APIs might change as it matures. # References ```dataview Table title as Title, authors as Authors where contains(subject, "Streamlit" ) sort modified desc, authors, title ```