![]() ![]() Languageserver is a regular R package, so I can go back to RStudio or an R terminal and install it the usual way, with install.packages("languageserver"). (Update: vscode-r-lsp capabilities have now been integrated into the vscode-R extension, so you no longer need to install it separately.) ![]() There are a couple of other recommended installations for the vscode-R extension: languageserver and vscode-r-lsp. If you don’t have Python already installed on your system, see the video below for easy instructions on how to install Python for use with R and RStudio. There is also a pip install command for those who use the popular Python package manager: pip install -U radian I already have Python and the conda package manager installed on my Mac, so I used this installation command for radian: conda install -c conda-forge radian That’s not a VS Code extension but an application written in Python-which means your system needs Python installed in order for radian to run. One of the first suggestions is to use the radian terminal. I also read the vscode-R project’s GitHub wiki page and main GitHub page to see what else I might want to add or change to improve my R experience. Once an extensions is installed, you should see a screen with details about how to optimize and use the extension. Once you click the install button, you should see a screen with information about how to configure and run the extension. Sharon Machlis, IDGĬlick the extensions icon to search for R Language extensions. Smith recommended Yuki Ueda’s R Extension for Visual Studio Code, aka vscode-R, which offers basic R language support (run, snippet, viewer). I searched for “R language” because a search for “R” will return oodles of non-relevant results. ![]() On the left “activity” navigation bar in Visual Studio Code, click the icon with the four squares to search for extensions. Install it like any other software package. VS Code is free and available for Windows, Mac, and Linux. Step one, obviously, is downloading Visual Studio Code, which you can find on the Visual Studio Code website. For R users, that means installing a couple of extensions and tweaking a few settings. ![]()
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