RStudio Server is an open-source integrated development environment (IDE) for R programming that enables users to run R code remotely on a server. It is a powerful tool for data analysis, statistical modeling, and reporting. In this tutorial, we will show you how to install RStudio Server on Alpine Linux.
Before we start, make sure to have the following prerequisites:
It is important to ensure that the system is up-to-date and has the latest security patches. To do this, run the following command on your terminal:
sudo apk update && sudo apk upgrade
This will update the package lists and upgrade any outdated packages to the latest versions.
RStudio Server requires R to be installed on the system. To install R, run the following command:
sudo apk add R
This will install the latest version of R available in the Alpine Linux repositories.
To download and install the latest version of RStudio Server on Alpine Linux, follow these steps:
Go to the RStudio Server download page at https://www.rstudio.com/products/rstudio/download-server/.
Select the version of RStudio Server that matches the version of R installed on your system. For example, if you installed R version 4.1.1, select the link to download RStudio Server 1.4.1717 or later.
Open a terminal on your Alpine Linux server and download the RStudio Server package using the wget
command. This command downloads the package file to your current working directory.
wget https://download2.rstudio.org/server/alpine/edge/x86_64/rstudio-server-1.4.1717-x86_64.apk
Install the downloaded package using the apk
command:
sudo apk add rstudio-server-1.4.1717-x86_64.apk
Once the installation is complete, start the RStudio Server service with the following command:
sudo service rstudio-server start
Now that we have installed RStudio Server on our Alpine Linux server, we can access it via a web browser. Follow these steps to access the RStudio Server:
https://<your-server-ip>:8787
.Congratulations! You have successfully installed RStudio Server on Alpine Linux and can now use it to run R code remotely.
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Alternatively, for the best virtual desktop, try Shells!