The RStudio team has a forthcoming webinar on February 3rd that will go into the improvements in detail. There's also now support for Dash, Bokeh and Streamlit, making it possible for users to share a full suite of Python applications, and the ability to use Flask to share Python APIs.įinally, in RStudio Package Manager, which helps organize, manage and centralize packages, there's now beta support for PyPI, giving users access to full documentation, automatic syncs, and historic snapshots of Python packages. In practical terms, this starts with improvements to the publishing options in Connect to make it easier to share Jupyter Notebooks and mixed R and Python content. 'solved the same challenges for Python users that have made Connect so popular with R users'

Improvements have also been made to RStudio Connect, which provides a centralized platform for running solutions created in R and Python. In In RStudio Server Pro, the commercial version of RStudio that provides collaboration, centralized management, and security for data science teams developing in R and Python, there is now beta support for the VSCode IDE. In addition, the Environment pane now displays a summary of Python objects available in the main module when the reticulate REPL is active, and Python objects can now be viewed and explored within the RStudio data viewer and object explorer.

The RStudio IDE now comes with a Python environment and object explorer, and the default Python interpreter to be used by RStudio / reticulate can now be customized in the Global Options pane. To facilitate this, a number of improvements have been made to the products in the RStudio range, both commercial and open source. The developers say that many data science teams today are bilingual, using both R and Python in their work. RStudio is an integrated development environment (IDE) for R which includes a code console, syntax-highlighting editor, and tools for plotting, history, debugging and workspace management. The developers at RStudio have announced a number of improvements designed to make it easier to use R and Python together in a single data science project, including more options for native Python coding in the RStudio IDE, including a Python environment and object explorer.

Python code in rstudio