How we design Streamlit to bias you toward forward progress

Streamlit's platform is a resource for data scientists and machine learning engineers, offering insights into building interactive data applications and machine learning prototypes. Through articles, tutorials, and case studies, Streamlit offers insights into creating data visualization dashboards, deploying machine learning models, and building web applications with Python. Readers can learn about streamlining the data science workflow, designing intuitive user interfaces, and sharing insights with stakeholders to drive data-driven decision-making.

Streamlit

Streamlit is a Python framework designed specifically for building data apps, promoting fast, iterative development and following a specific design system. Its opinionated nature includes a library with most necessary components, enabling users to create functional apps quickly. Streamlit supports a minimal viable product (MVP) approach, allowing users to build, test, and refine apps incrementally. The framework aims to eliminate distractions from engineering details like HTML and CSS, fostering forward progress and immediate usability. New features and iterations are regularly driven by feedback from its active community.

Just build it