Python -> R bridge rpy2 is an interface to R running embedded in a Python process. 1) a high-level interface making R functions and objects just like Python functions and providing a seamless conversion to numpy and pandas data structures 2) a low-level interface closer to the C-API It is also providing features for when working with jupyter notebooks or ipython. Building the package - see also the rpy2.Slackbuild: Remove installed rpy2 before building and upgrading to a new version. R needs to be compiled with the shared library flag, that is: build R on SBo with `R_SHLIB=yes` and `BLAS_SHLIB=yes`, now the default for R at SBo. For linking to R, the path to installed R-libraries - e.g. `/usr/lib64/R/lib` - has to be exported. This is done by having this path in a `Rlibs.conf` file that is placed into `/etc/ld.so.conf.d/` during installation of the package via a `doinst.sh`. Because the $LIBDIRSUFFIX defines this path, the 'doinst.sh' is generated when running the rpy2.Slackbuild and directly saved to the `package-rpy2/install` folder. A `douninst.sh` removes this file when rpy2 is uninstalled via `removepkg`. A utility module is included to check rpy2’s environment after installation: bash-5.3$ python -m rpy2.situation Home: https://rpy2.github.io/ Documentation: https://rpy2.github.io/doc.html Examples: https://rpy2.github.io/doc/latest/html/introduction.html#examples Quick test (with example outcomes from 3.6.7): bash-5.3$ python3 >>> import rpy2.robjects as robjects >>> r = robjects.r >>> rpy2.robjects.__version__ # '3.6.5' >>> r("print('test')") # [1] "test" >>> r("print(version)") # _ # platform x86_64-slackware-linux-gnu # arch x86_64 # os linux-gnu # system x86_64, linux-gnu # status # major 4 # minor 6.1 # year 2026 # month 06 # day 24 # svn rev 90187 # language R # version.string R version 4.6.1 (2026-06-24) # nickname Happy Hop >>> r("library(stats)") >>> x = robjects.IntVector(range(10)) >>> y = r.rnorm(10) >>> r.X11() # [0] # you see a frame "R Graphics Device # (ACTIVE)" popping up >>> r.layout(r.matrix(robjects.IntVector([1,2,3,2]), nrow=2, ncol=2)) # [13] # R classes: ('integer',) # [3] >>> r.plot(r.runif(10), y, xlab="runif", ylab="foo/bar", col="red") # [0] # you see a diagram >>> import rpy2.rinterface >>> rpy2.rinterface.__version__ # could be missing >>> import rpy2.situation >>> for row in rpy2.situation.iter_info(): ... print(row) ...