My Takeaways From the ShinyConf2025: Shiny for Python

This was probably the very one topic on which I was not expecting that it would actually shift my mindset in such a radical way.

I’m definitely a R / Shiny enthusiast and as my GitHub stats show I’m doing about 80% R versus 15% Python - mostly to support mentoring activities at OpenClassrooms as well as do some modeling (for example with TensorFlow).

But I’m also a realistic person and I work in a field / country where a wide majority of the data science related code is made of Python. A quick look at the job descriptions and freelance missions demonstrates how popular Python has become and is now in a position to be a standard in many companies stack.

While I keep the same enthusiasm for R when it comes to data analysis & visualization, I sometimes feel like such a niche specialization makes me a bit invisible among the data science community in France (except traditional field like Research, Finance is the only domain where I see R in the stacks).

That was until the very first day of the conference:

“Workshop: Transferring your R Shiny skills to Python” by PJ Van Camp

The workshop helped me realize that mixing both my knowledge about Shiny and Python could help me get stronger at Python with a specific skill that is not so common yet in the community. Therefore I don’t see Python as a replacement or obligation but as an opportunity to grow specific skills that can be explained by something more robust than ‘python has become so popular’.