Python and R have become essential tools for data scientists and engineers working in various industries, from web giants such as Google and Facebook to scientific researchers, data journalists and more. There is no week that we don't see a breakthrough in science, machine learning, or an app were one of this languages are involved.

While Python and R independently are changing the world, historically there hasn't been that much collaboration between the two languages, and more important between the two communities, on the contrary for the longest time we have been hearing about a “data science language war” between Python and R. Recently we have seen new initiatives like Apache Arrow and Ursa labs whose main goal is to make it easier for data scientists working in different programming languages to collaborate. Does that mean that the language war between these two is over? If it is, was there a winner and a loser?

In general, the competition between them made both winners since long are the days where there was a library or tool in one language that doesn't have a decent alternative in the other. There are still some differences, like R being used more by statisticians and Python by software engineers but it’s weird to see today a data science team where these two types of people are not present, interact and help each other. If that's not the case in your organization you are missing on some diversity that will benefit your team.

We will discuss these topics and see what can we learn about our different communities. We will look at some tools that RStudio has been working for collaboration and deployment of data science assets in both R and Python. We will talk about how to build data science projects that use both languages using reticulate, a new library for communication between R and Python, how to deploy shiny apps that use Python for computation and other exciting examples of what's possible today and in the future between two awesome communities. Finally, we will see the RStudio enterprise stack that we offer to our customers for data science collaboration and the new Python and Jupyter functionality.