BiocManager (the recommended way to install Bioconductor packages) at the end of the day does essentially install.packages(repos = BiocManager::repositories()), ensuring that the right versions of Bioconductor packages are installed for the version of R in use. Maybe this is moot though if the goal is to emulate CRAN, since I believe they use utils:::.BioC_version_associated_with_R_version().
There is a Bioconductor docker container, extending rocker https://github.com/Bioconductor/bioconductor_docker ; I don't know whether this would be more or less work than alternatives. And an exploratory https://github.com/Bioconductor/bioc2u; I don't know the status of that project. At some point the scale tips from installing packages from standard repositories to using a local clone https://bioconductor.org/about/mirrors/mirror-how-to/. Martin Morgan From: R-package-devel <r-package-devel-boun...@r-project.org> on behalf of Ivan Krylov via R-package-devel <r-package-devel@r-project.org> Date: Tuesday, January 30, 2024 at 10:57 AM To: r-package-devel@r-project.org <r-package-devel@r-project.org> Subject: [R-pkg-devel] Bioconductor reverse dependency checks for a CRAN package Hello R-package-devel, What would you recommend in order to run reverse dependency checks for a package with 182 direct strong dependencies from CRAN and 66 from Bioconductor (plus 3 more from annotations and experiments)? Without extra environment variables, R CMD check requires the Suggested packages to be available, which means installing... revdepdep <- package_dependencies(revdep, which = 'most') revdeprest <- package_dependencies( unique(unlist(revdepdep)), which = 'strong', recursive = TRUE ) length(setdiff( unlist(c(revdepdep, revdeprest)), unlist(standard_package_names()) )) ...up to 1316 packages. 7 of these suggested packages aren't on CRAN or Bioconductor (because they've been archived or have always lived on GitHub), but even if I filter those out, it's not easy. Some of the Bioconductor dependencies are large; I now have multiple gigabytes of genome fragments and mass spectra, but also a 500-megabyte arrow.so in my library. As long as a data package declares a dependency on your package, it still has to be installed and checked, right? Manually installing the SystemRequirements is no fun at all, so I've tried the rocker/r2u container. It got me most of the way there, but there were a few remaining packages with newer versions on CRAN. For these, I had to install the system packages manually in order to build them from source. Someone told me to try the rocker/r-base container together with pak. It was more proactive at telling me about dependency conflicts and would have got me most of the way there too, except it somehow got me a 'stringi' binary without the corresponding libicu*.so*, which stopped the installation process. Again, nothing that a bit of manual work wouldn't fix, but I don't feel comfortable setting this up on a CI system. (Not on every commit, of course - that would be extremely wasteful - but it would be nice if it was possible to run these checks before release on a different computer and spot more problems this way.) I can't help but notice that neither install.packages() nor pak() is the recommended way to install Bioconductor packages. Could that introduce additional problems with checking the reverse dependencies? Then there's the check_packages_in_dir() function itself. Its behaviour about the reverse dependencies is not very helpful: they are removed altogether or at least moved away. Something may be wrong with my CRAN mirror, because some of the downloaded reverse dependencies come out with a size of zero and subsequently fail the check very quickly. I am thinking of keeping a separate persistent library with all the 1316 dependencies required to check the reverse dependencies and a persistent directory with the reverse dependencies themselves. Instead of using the reverse=... argument, I'm thinking of using the following scheme: 1. Use package_dependencies() to determine the list of packages to test. 2. Use download.packages() to download the latest version of everything if it doesn't already exist. Retry if got zero-sized or otherwise damaged tarballs. Remove old versions of packages if a newer version exists. 3. Run check_packages_in_dir() on the whole directory with the downloaded reverse dependencies. For this to work, I need a way to run step (3) twice, ensuring that one of the runs is performed with the CRAN version of the package in the library and the other one is performed with the to-be-released version of the package in the library. Has anyone already come up with an automated way to do that? No wonder nobody wants to maintain the XML package. -- Best regards, Ivan ______________________________________________ R-package-devel@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-package-devel [[alternative HTML version deleted]] ______________________________________________ R-package-devel@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-package-devel
