RStudio Projects + renv: Stop Letting One Analysis Break Another

You upgrade dplyr for a new analysis, and a month-old report suddenly renders differently. The cause is almost always the same: every R session on your machine shares one package library, so every project shares every package version. The fix that actually sticks is pairing an RStudio Project with renv, so each analysis gets its own isolated, recorded environment.

Two tools, two jobs

An RStudio Project (the .Rproj file) scopes your session: its own working directory, history, and settings. That alone kills setwd() hacks and cross-project contamination of your workspace. But it does nothing about packages.

renv handles the package half. renv::init() creates a project-local library plus an renv.lock lockfile that records exact package versions. Anyone who clones the project runs renv::restore() and gets the same environment. renv keeps a global package cache and links into project libraries, so ten projects sharing dplyr 1.1.x don't cost ten copies of disk space.

The workflow is a three-step loop

Run these in the R console inside the project (no special permissions needed):

renv::init()      # once, at project start
install.packages("dplyr")  # work as usual
renv::snapshot()  # record the new state in renv.lock

That's the whole discipline: install and update normally, then snapshot when things work. Commit renv.lock and renv/activate.R to git; ignore the renv/library folder itself.

Worked example: two projects, two dplyr versions

Project A is a legacy report pinned to dplyr 1.0.10. Project B is new work on dplyr 1.1.4. With a shared library this is impossible; with renv it's boring:

# In Project A's console:
renv::install("dplyr@1.0.10")
renv::snapshot()

# In Project B's console:
install.packages("dplyr")  # gets the current CRAN version
renv::snapshot()

Switching projects in RStudio switches the active library automatically. Verify with:

.libPaths()          # project library should be first
packageVersion("dplyr")
renv::status()       # lockfile vs. library consistency check

A stronger end-to-end check: delete the contents of the project's renv/library folder, run renv::restore(), and confirm the packages reinstall at the lockfile versions. If that works, a colleague or CI runner can reproduce the environment too.

Where this breaks down

Snapshot workflows fail quietly in two directions. Install packages and forget renv::snapshot(), and the lockfile drifts from reality — get in the habit of running renv::status() before committing. The reverse hazard: renv::restore() will happily downgrade a colleague's newer library to match the lockfile, so treat restore as a deliberate action, not a reflex.

Also know the boundary: renv pins R packages, not the R interpreter or system libraries like GDAL or libxml2. Restoring old CRAN packages can fail if binaries aren't published for your OS/R combination and you lack a source compilation toolchain. For full machine-to-machine reproducibility you still need containers or documented system setup. Behavior varies by renv release, so check packageVersion("renv") before following version-specific advice.

Do this today

Pick your most fragile active project, open it as an RStudio Project, run renv::init() then renv::snapshot(), and commit the lockfile. Then run the delete-and-restore test above. If restore succeeds, you've just made "works on my machine" a solvable problem for that project — and the next dplyr upgrade won't touch it.