在 R 4.0.0 之前安装了包“xxx”：请重新安装（已经完成全新安装并检查了 lib 路径）

Question

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

1. deleting the library folder and reinstalling
2. running remove.packages('libSBML') and reinstalling

For 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  

Answer 1

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.