A set of utilities for client/server computing with R, controlling a remote R session (the server) from a local one (the client). Simply set up a server (see package vignette for more details) and connect to it from your local R session ('RStudio', terminal, etc). The client/server framework is a custom 'REPL' and runs entirely in your R session without the need for installing a custom environment on your system. Network communication is handled by the 'ZeroMQ' library by way of the 'pbdZMQ' package.
Control a remote R session from your local R session. The package uses pbdZMQ to handle the communication and networking. Encryption is supported if the sodium package is (optionally) installed. Details below.
You can install the stable version from CRAN using the usual
In order to be able to create and connect to secure servers, you need to also install the sodium package. The use of sodium is optional because it is a non-trivial systems dependency, but it is highly recommended. You can install it manually with a call to
install.packages("sodium") or by installing remoter via:
The development version is maintained on GitHub, and can easily be installed by any of the packages that offer installations from GitHub:
### Pick your preferencedevtools::install_github("RBigData/remoter")ghit::install_github("RBigData/remoter")remotes::install_github("RBigData/remoter")
To simplify installations on cloud systems, we also have a Docker container available.
For setting up a local server, you can do:
And connect to it interactively via:
There is also the option to pipe commands to the server in batch using the
### Passing an R script fileremoter::batch(file="my_rscript_file.r")### Passing in a script manuallyremoter::batch(script="1+1")
For more details, including working with remote machines, see the package vignette.
Work for the remoter package was supported in part by the project Harnessing Scalable Libraries for Statistical Computing on Modern Architectures and Bringing Statistics to Large Scale Computing funded by the National Science Foundation Division of Mathematical Sciences under Grant No. 1418195.
Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.