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Streamlit is a framework that is open-source and designed to assist data scientists in creating applications that are driven by data. It provides a user-friendly interface and incorporates interactive elements into data applications, enabling users to explore data in real-time. The Streamlit framework is efficient in building applications quickly, which can help speed up data science workflows and the development of machine learning models. It supports both Python and R programming languages, although it is primarily used with Python. The customizable dashboard of Streamlit allows data scientists to visualize data in a more interactive and intuitive manner, with features such as drop-down menus and sliders. This means that developers can easily create applications that are rich in data, while also giving end-users more control and enhancing their understanding of the data. Additionally, Streamlit enables the sharing of apps through a cloud platform, making them more accessible to a wider audience. Being an open-source framework, Streamlit has a large and active community of developers who constantly contribute their ideas and knowledge to improve the effectiveness of the tool. As a result, it has been adopted by various industries, including finance and healthcare, to gain valuable insights from critical data. Overall, Streamlit simplifies the entire process of developing, deploying, sharing, and collaborating on data-driven applications, allowing developers to focus on the data and the core functionalities of the app.