Shiny vs Streamlit: What are the differences?

In the world of web application frameworks, Shiny and Streamlit stand out as two popular options for building interactive and data-driven applications. Let's explore the key differences between them.

1. Design Philosophy: Shiny is designed for R users, focusing on providing an interactive web framework for R-based data analysis and visualization. On the other hand, Streamlit emphasizes simplicity and ease of use, aiming to enable Python developers to quickly build and share data applications with minimal code.

2. Language: Shiny primarily uses R as its programming language, allowing R developers to leverage their existing skills and libraries. In contrast, Streamlit is based on Python, a widely used language for data analysis and machine learning, enabling Python developers to utilize their knowledge and take advantage of the vast Python ecosystem.

3. Deployment: Shiny applications are typically deployed on Shiny Server or Shinyapps.io, which require a separate server infrastructure for hosting the applications. In contrast, Streamlit applications can be easily deployed on popular cloud platforms like Heroku, AWS, or even as a Docker container, providing more flexibility and ease of deployment.

4. Ecosystem: Shiny benefits from the large and mature R ecosystem, including a wide range of statistical and visualization packages. This allows Shiny developers to tap into a vast resource of R packages to enhance their applications. Streamlit, being built on Python, leverages the extensive Python ecosystem, which offers a multitude of libraries for various purposes, from data manipulation to machine learning.

5. Reactive Programming: Shiny utilizes a reactive programming model, allowing developers to create dynamic applications by specifying reactive dependencies between input data and output visualizations. Streamlit, on the other hand, follows a more imperative approach, where developers explicitly define the code flow and interactions within the application, making it easier for Python developers to grasp and build applications quickly.

6. Ease of Use: Shiny provides a higher level of abstraction, allowing developers to create interactive web applications with minimal HTML or CSS knowledge. It offers user-friendly components, including built-in widgets and layouts, simplifying the development process. Streamlit, inspired by Python's simplicity, enables developers to quickly iterate and build data applications with straightforward Python code, making it accessible to both beginners and experienced developers alike.

In summary, Shiny caters more towards R developers and provides a mature ecosystem, Streamlit appeals to Python developers with its simplicity and ease of deployment.