Reputation: 185
I am having some issue with installing a package in R 4.0.2 from binaries. Here is my attempt:
> install.packages("C:/Users/MNestor/Downloads/libSBML_5.18.0.zip", repos = NULL, type = "win.binary")
Installing package into ‘C:/Users/MNestor/Documents/R/win-library/4.0’ (as ‘lib’ is unspecified)
package ‘libSBML’ successfully unpacked and MD5 sums checked
Warning messages:
1: multiple methods tables found for ‘type’
2: multiple methods tables found for ‘type<-’
Next I load library:
> library('libSBML')
Error: package or namespace load failed for ‘libSBML’:
package ‘libSBML’ was installed before R 4.0.0: please re-install it
This error is confusing to me because I am working in R 4.0.2 and have clearly just done a fresh install.
I have tried
remove.packages('libSBML')
and reinstallingFor reference here are my library directories:
> .libPaths()
[1] "C:/Users/MNestor/Documents/R/win-library/4.0"
[2] "C:/Program Files/R/R-4.0.2/library"
The libSMBL
folder is located in the first library path, and not the second (as expected).
Here is session info:
> sessionInfo()
R version 4.0.2 (2020-06-22)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 17134)
Matrix products: default
locale:
[1] LC_COLLATE=English_United States.1252 LC_CTYPE=English_United States.1252
[3] LC_MONETARY=English_United States.1252 LC_NUMERIC=C
[5] LC_TIME=English_United States.1252
attached base packages:
[1] parallel stats graphics grDevices utils datasets methods base
other attached packages:
[1] rsbml_2.46.0 BiocGenerics_0.34.0
loaded via a namespace (and not attached):
[1] BiocManager_1.30.10 compiler_4.0.2 tools_4.0.2 remotes_2.2.0
[5] stats4_4.0.2 SBMLR_1.84.0 graph_1.66.0
Upvotes: 1
Views: 5062
Reputation: 9705
The error message is maybe a bit confusing, but it's saying the package is already compiled for an earlier version of R. (That's what the option "win.binary" means).
R 4.0 and earlier binaries are not compatible because of updated compilers and build tools.
You'll need to install the package from source, which likely means installing R tools (https://cran.r-project.org/bin/windows/Rtools/) or you'll need to use a version that is pre-built for R 4.0 or later.
Upvotes: 3