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Recently, I tried to load sprtt r package in Kaggle but it was not successful. It is not included in the list of packages in this repo too.
What is the protocol to make a package available in Kaggle?
Best Regards

sprtt package links:

https://cran.r-project.org/web/packages/sprtt/index.html
https://github.com/MeikeSteinhilber/sprtt

Hello there, I'm interested in helping update the R container,
after spending some time working on the build errors I have written a patch,
but I want to discuss the changes before opening a PR because they are significant:

• Upgrade R to 4.4
  the latest R available on Kaggle is 3 years old now, it's about time we get an update ;)

• Drop mxnet
  as of 2023-09, the project has been retired.

• Remove packages: rgdal, rgeos
  these packages have been removed from CRAN:
  Archived on 2023-10-16 at the request of the maintainer. Consider using 'sf' or 'terra' instead.

• Install the latest versions of the packages: randomForest, terra, ranger, imager
  the version of these packages is fixed on package_installs.R,
  the comments imply there is context for these ( internal bug tracker ?), but it's not clear why or if they are still needed.

• Use pak to install packages
  The build is currently failling here:

r$> utils:::.make_dependency_list(pkgs, allPackages, recursive = TRUE)
Error in tools:::.extract_dependency_package_names(x) :
  non-character argument

r$> traceback()
4: tools:::.extract_dependency_package_names(x)
3: unique.default(tools:::.extract_dependency_package_names(x))
2: .clean_up_dependencies(info2[i, ])
1: utils:::.make_dependency_list(pkgs, allPackages, recursive = TRUE)

package_installs.R uses utils:::.make_dependency_list,
this is an internal function and is prone to changing its behavior without warning,
which is what I think happened here.

pak can do parallel downloads and parallel installation of packages, among other features.

I think that by using pak most of the package_installs.R code becomes redundant, and the script can be simplified significantly.

of course, none of these are required but it is what I think would be better, let me know what you think.

Hi Folks, could be possible include NNS package? I'm trying to use it at Optiver Competition but I can only submit without using internet, but I need Internet to install NNS

my code to install at kaggle:

install.packages("NNS"); 
library(NNS)

reticulate::import("sklearn.mixture") results in the following error.

Error in py_module_import(module, convert = convert): ImportError: /usr/lib/x86_64-linux-gnu/libstdc++.so.6: version `GLIBCXX_3.4.30' not found (required by /root/.local/share/r-miniconda/envs/r-reticulate/lib/python3.8/site-packages/scipy/optimize/_highs/_highs_wrapper.cpython-38-x86_64-linux-gnu.so)

Traceback:

1. import("sklearn.mixture")
2. py_module_import(module, convert = convert)