Switchr

4.3/5 Best for: R developers, bioinformaticians, data scientists managing multiple R versions or library configurations. GitHub: gmcmacran/switchr

When sharing code with a team, ensuring everyone has the same setup is difficult. switchr streamlines this by allowing project leads to define a "manifest" of required packages. Team members can "switch" into the project context, automatically loading the exact library versions needed. switchr

: Users can "seed" a new library directly from a sessionInfo() output. By reading a text file containing version information, switchr can automatically retrieve and install the exact versions required to recreate a specific research result. Team members can "switch" into the project context,

You can commit this manifest to Git, then on another machine: You can commit this manifest to Git, then

manifest <- switchr::writeManifest() # manifest is a data.frame with Package, Version, Repository, Sha (for GitHub)

Unlike Python’s virtualenv or conda , R lacks a first-class, built-in mechanism for per-project library stacks. Switchr fills this gap by providing programmatic switching between sets of installed packages (called "sandboxes" or "library stacks" ). It allows you to maintain, e.g., a "Production 3.6" stack, an "Experimental tidyverse" stack, and a "Legacy CRAN 2020" stack on the same machine.

: While tools like workflowr manage the sequence of research steps, switchr complements them by handling the actual deployment of the necessary computational dependencies. 2. The SWITCH-R Wellness Intervention