rstudio::conf(2022)

Internal packages are great for boosting productivity and promoting good practice, but what kinds of challenges do we face when designing solutions for multi-lingual teams? Here I will advocate for a design approach we are using at Bumble to build Python and R packages with the same foundations. I will discuss the benefits of this approach for the developer and the wider organisation.

Talk materials are available at https://github.com/jamie-ralph/rstudio-conf-2022.

Some of my best friends use Python...and all of my coworkers use SAS.

Statistics Canada is the official statistical agency of Canada and employs over 6,000 employees. Statistics Canada has a legal obligation to ensure that personal information collected for statistical purposes is kept strictly confidential. An internal system which prevents the release of confidential information is only implemented in SAS. As such, many Analysts and Data Scientists at Statistics Canada must use the SAS programming language as part of their workflow. It is therefore imperative to find ways to work with open source programming languages and SAS seamlessly. I will present a method for achieving a harmonious workflow between R, Python, and SAS, all within RStudio.

Talk materials are available at https://github.com/melissavanbussel/rstudio-conf-2022.

Are you a bilingual data scientist who wants to use Python in RStudio products? Or do you have colleagues who use Python for data science? In this talk, we will present an end to end data science use case including automated jobs, model training and monitoring, APIs, and interactive dashboards, entirely built and deployed in Python with RStudio Pro products.

Shiny for Python has the ability to be deployed without a server that runs Python. These applications can be served by any web hosting service. They are easily deployed and can scale to handle large amounts of traffic.

This mode of deployment is called Shinylive. It works by running Python in the user’s web browser, using Pyodide, which is a version of Python that is compiled to WebAssembly. Shinylive opens up new possibilities for how Shiny applications can be used. In this talk I discuss the advantages and the limitations of Shinylive applications.