It’s also worth noting that whether you choose Dash or Shiny (or both!), you can deploy your apps through RStudio Connect. We’re not going to throw arbitrary points to Shiny just because we prefer it for enterprise app development. Still, we’ll do our best to provide an honest and unbiased opinion in this article. R Shiny: final face-offĪt Appsilon, we are global leaders in R Shiny and we’ve developed some of the world’s most advanced R Shiny dashboards, so we have a natural bias toward using Shiny. We don’t recommend using PyShiny (Shiny for Python) for production yet, but as it evolves we will share our thoughts and knowledge on when and how you can use it. It’s still in alpha, but if you’re curious to test it, follow our tutorial on PyShiny. In 2022, Posit announced Shiny for Python. For a truly immersive face-off experience, download the source code of the sample dashboard used to illustrate Dash and Shiny capabilities. You’ll also see if it’s worth it to make a long-term switch to either. After reading, you’ll know how these two compare and when it’s better to use one over the other. Today we’ll compare two technologies for building web applications – Python Dash and R Shiny. The question remains – which technology should you use? R or Python? Dash vs. You have to think about a vast amount of technical details and at the same time build something easy and enjoyable to use.
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