When I first tried to install tidyverse
in R 3.5 on my Linux system, I ran into a frustrating wall of error messages. At first glance, they were overwhelming, but once I dug deeper, I realized they were pointing to a common issue: package version mismatches across R versions.
The First Code I Ran
Like many R users, I started with the straightforward approach:
install.packages("tidyverse")
But R fired back with:
namespace ‘vctrs’ 0.3.6 is being loaded, but >= 0.3.7 is required
ERROR: lazy loading failed for package ‘tidyr’
Error : .onLoad failed in loadNamespace() for 'rlang'
error: 'is_character' is not an exported object from 'namespace:rlang'
At this point, I felt stuck.
What the Error Really
tidyr
needs vctrs ≥ 0.3.7. My R session was still holding onto an oldervctrs
(0.3.6).- The
'is_character'...from 'rlang'
error was a namespace mismatch. I had a mix of old and new versions ofrlang
,vctrs
, and friends (tibble
,pillar
, etc.). They depend tightly on each other, so mismatches cause load failures. - The root cause? I was sharing one user library across multiple R versions (R 3.5 and R 4.x). That mix is toxic for old R installs.
My Quick Checklist to Fix This (Linux, R 3.5)
- Restart R 3.5
In R:q()
(choosen
when asked to save). Then relaunch withR35
in the terminal. - Give R 3.5 its own clean library
mkdir -p "$HOME/R/3.5-library" export R_LIBS_USER="$HOME/R/3.5-library"
Adding the export line to~/.bashrc
made it permanent. - Pin CRAN to an older snapshot
Modern CRAN versions often drop R 3.5 support, so I pinned to mid-2021, when tidyverse still supported 3.5:options(repos = c(CRAN = "https://packagemanager.posit.co/cran/2021-06-01"))
- Install exact package versions that work together
Here’s where I built a little helper function.
The One Shot Script That Solve It for Me
I ran this inside R 3.5:
## 0) Safety: show where we're installing
print(.libPaths())
## 1) Pin repo
options(repos = c(CRAN = "https://packagemanager.posit.co/cran/2021-06-01"))
## 2) Helper: install pinned version if missing
ensure_version <- function(pkg, version) {
if (!requireNamespace("remotes", quietly = TRUE))
install.packages("remotes")
if (!requireNamespace(pkg, quietly = TRUE) ||
utils::packageVersion(pkg) != version) {
remotes::install_version(pkg, version = as.character(version),
upgrade = "never", dependencies = TRUE)
}
}
## 3) Core low-level deps
ensure_version("rlang", "0.4.10")
ensure_version("vctrs", "0.3.8")
ensure_version("ellipsis","0.3.1")
ensure_version("glue", "1.4.2")
## 4) Building blocks
ensure_version("tibble", "3.1.2")
ensure_version("pillar", "1.6.1")
ensure_version("hms", "1.1.0")
ensure_version("cli", "2.5.0")
## 5) Core tidyverse members
ensure_version("dplyr", "1.0.7")
ensure_version("tidyr", "1.1.3")
ensure_version("readr", "1.4.0")
ensure_version("stringr","1.4.0")
ensure_version("purrr", "0.3.4")
ensure_version("forcats","0.5.1")
ensure_version("ggplot2","3.3.5")
## 6) Finally, tidyverse meta-package
ensure_version("tidyverse", "1.3.1")
## 7) Smoke test
cat("\nLoaded versions:\n")
pkgs <- c("rlang","vctrs","dplyr","tidyr","tibble","pillar","hms","tidyverse")
print(sapply(pkgs, function(p) as.character(utils::packageVersion(p))))
This gave me a clean, working tidyverse stack under R 3.5.
My “Practice Utility” to Double Check Compatibility
I also wrote a quick checker:
check_tidyverse_compat <- function() {
need <- list(
rlang = "0.4.10",
vctrs = "0.3.7",
dplyr = "1.0.0",
tidyr = "1.1.0",
tibble = "3.0.0",
pillar = "1.5.0",
hms = "1.0.0",
tidyverse = "1.3.0"
)
have <- lapply(names(need), function(p) {
if (requireNamespace(p, quietly = TRUE))
as.character(utils::packageVersion(p))
else NA_character_
})
df <- data.frame(
package = names(need),
have = unlist(have),
need = unlist(need),
ok = mapply(function(h, n) {
if (is.na(h)) FALSE else utils::compareVersion(h, n) >= 0
}, unlist(have), unlist(need)),
stringsAsFactors = FALSE
)
print(df, row.names = FALSE)
if (!all(df$ok)) {
message("\nSome packages are too old or missing. Re-run the setup script.")
} else {
message("\nLooks good for R 3.5.")
}
}
check_tidyverse_compat()
This gave me instant peace of mind after installation.
Common Pitfalls I Learn
- Mixing libraries across R 3.5 and R 4.x caused almost all my namespace errors. Keeping
.libPaths()
separate solved it. - Updating packages without pinning CRAN pulled in versions that flat-out didn’t support R 3.5.
- Running
R35 --vanilla
helped rule out side-effects from.Rprofile
or saved workspaces.
Final Thought
At first, the error messages felt like a brick wall. But once I broke them down, I realized the solution was straightforward: isolate R 3.5’s library, pin package versions, and install in the right order. Now, not only do I have a working tidyverse on R 3.5, but I also have a reproducible script I can share with teammates. And the little compatibility checker I wrote gives me confidence that everything is consistent before I start scripting.