I have a package that Requires INLA, which is not hosted on CRAN or a standard GitHub repository. There are multiple SO questions detailing how to install the package on a personal machine, such as this, or even mentions it as a dependency in a package.
The two ways that are typically recommended to install on a personal machine are:
Direct from INLA website
install.packages("INLA",repos=c(getOption("repos"),INLA="https://inla.r-inla-download.org/R/stable"), dep=TRUE)
From the GitHub host
devtools::install_github(repo = "https://github.com/hrue/r-inla", ref = "stable", subdir = "rinla", build = FALSE)
Now, these are fine for personal machines, but don't work in the DESCRIPTION files Remotes: section.
If we do url::https://inla.r-inla-download.org/R/stable, this gives an error that the file extension isn't recognized.
Error: Error: Failed to install 'unknown package' from URL:
Don't know how to decompress files with extension
If we do github::hrue/r-inla, I am unaware of how to pass (or if it's even possible) the ref, subdir, and build arguments in the DESCRIPTION file.
Previous packages used a read only mirror of the INLA code that was hosted on GitHub, solely for this purpose, at this repo and then just using github::inbo/INLA. However, this repository is out of date.
Current solution
What I'm doing instead is to directly reference the tarball hosted on the main webpage.
url::https://inla.r-inla-download.org/R/stable/src/contrib/INLA_21.02.23.tar.gz
This solution works, and passes CI as well as the machines are able to install and load from there. The only issue is that I need to periodically update the static link to this tarball, and would prefer to reference the stable build, either directly from the INLA website as above, or the hrue/inla repo with those other arguments passed. Directly referencing those links also has the advantage that when my package is re-installed on a machine, it would recognize whether or not the latest version of INLA has been installed on that machine. Is there a way to achieve this in the DESCRIPTION file?
This is not a perfect answer but maybe what you can do is add the zip url of the stable branch of INLA from the new github repository of INLA:-
url::https://github.com/hrue/r-inla/archive/refs/heads/stable.zip
Hence, this will always install the latest stable version of the package.
Related
We are testing how to run R in the cloud in a secure isolated environment that is blocked from CRAN and also cannot use packages.install(). We defined an environment which is based on R essentials Anaconda's bundle, still we would like to be able to customize it on demand with extra packages. Is there a way to be able to simulate packages.install(), e.g. by offline downloading the package, zip it, copy to the secure environment and unzipping it to a specific location in the library folder?
thanks!
You can download the package from CRAN as a zip and then transport it to the isolated PC as a file. For example, here is the link to dplyr on CRAN: https://cran.r-project.org/web/packages/dplyr/index.html
Then use the code below to install the local file:
install.packages("~/Downloads/dplyr_1.0.7.zip", repos = NULL)
On Windows you might require Rtools. At least there was a Warning about it but the package still installed.
For Linux machines, you can build the package from source using the tarball from the same page:
install.packages("~/Downloads/dplyr_1.0.7.tar.gz", repos = NULL, type = "source")
In both cases you need to take care of dependencies yourself as they are not checked while installing through this method (look at the "imports" field on the CRAN website for the package).
When I install the packages in R, sometimes it is used by devtools::install_github(). other times it is used by install.packages().
Could I ask what is the essential difference between them?
R's official repository for packages is located on CRAN (Comprehensive R Archive Network). The process of publishing a package there is very strict and is reachable via install.packages(). For the most part, binary packages (opposed to source code, which is not "properly translated" yet) are available and no additional tools need to be present for proper installation (see next paragraph).
GitHub is one of many webservices that offers repositories for code, incl. R code. Author can upload her or his package and if everything is in its place, the user can install a package from source via devtools::install_github(). This means you need to have a proper toolchain installed (also a distributoin of LaTeX). In Windows, this means Rtools. Linux based OS are likely to be shipped with most of the necessary tools.
My Dockerfile includes a step that pulls from an unrelated, public git repository. Specifically, it's installing an R package using the R command
devtools::install_github("bmbroom/NGCHMR")
This should install the latest version of the package from the master branch of that repository, and on local builds that is exactly what it does.
On Dockerhub automated builds, however, I always get the version of the package that was current when I first built the image. There is otherwise nothing special about that particular version. It's as if github access is being cached. The docker build process itself is clearly not cached, based on authoritative replies to other questions here as well as the build logs, which show earlier steps in the build being executed in detail.
Any suggestions why I'm not getting the most recent version of the R package installed?
My Fedora system (Fedora 20, all up to date) has just had R updated to version 3.1.0. Since then, I've had issues installing multiple packages. glmnet failed previously, and now I'm having trouble with treemap. More specifically, I get an error during treemap installation that httpuv has zero exit status.
I never had issues with the previous version of R. Any reason this version should have such problems??
There could be many causes to do with your OS, version, permissions, other installed packages/software, etc, etc. Without seeing the full error message it's hard to know.
One possibility specific to httpuv is root privileges. I've noticed a few threads on various forums when searching for installation errors with this package and Linux, many of them mentioning root v. non-root issues. In another case, libuv needed to be upgraded.
I encounter package installation problems daily and I have some more general work-arounds as well. Hopefully one of these will solve your problem.
Install the package from source
download.file(url="http://cran.r-project.org/src/contrib/httpuv_1.3.0.tar.gz", destfile = "httpuv.tar.gz")
install.packages("httpuv.tar.gz", type = "source", repos = NULL)
Install using devtools via GitHub if the package supports it
Install RTools and re-try your package installation
Install an older version of the package
If those above do not work, then I dig deeper by referring to advice given to me by a VP of IT in my company. These comments were made in reference to frequent package installation problems I encountered when switching from Windows to Solaris:
There are two types of install/make problems. Missing .h files
and/or missing .so/.a libs. The reason for these are multiple:
1.- the package that delivers these is not installed. This means that those files cannot be found anywhere in the /usr tree. Solution is
install right package, make sure the files are there
2.- the includes are not found by the install configurator. This means some environment variable or install option is not properly set (this
is our case for RODBC). Figuring out which variable to set is
challenging without looking at the package documentation [fortunately, documentation is not hard to find!]
3.- the libs are not in the LD_LIBRARY_PATH, easy to fix.
4.- There is a deeper compile/link error, meaning the package is not compatible with the rest of the sw, or has not been properly ported.
I want to set up a local CRAN repository . I want to put just one package in this repository ( let's call it MyPackage ). The reason I'm doing this is that I want to share this package with people at my company. By the way - we all use Ubuntu Linux.
I have already done this:
I have a web server ( BOA web server ) and made a web folder called R. Made folder src and contrib.
In the contrib folder I put my package MyPackage ( tar.gz) plus the PACKAGES file.
However, when I do this:
install.packages("MyPackage", repos = "127.0.0.1/R" )
it does not work ;
Warning: unable to access index for repository [ ]
Warning message:
In getDependencies(pkgs, dependencies, available, lib) :
package ‘MyPackage’ is not available (for R version 2.13.1)
Can you guys guide me a bit and tell me what is the correct folder structure ?
Thanks.
See "Section 6.6 Setting up a package repository" of the R Admin manual.
Edit some three+ years later: We now have the drat package which automates creating a repository, and can use GitHub in a clever way to host it for you.
You might just need to specify the URL properly; http://127.0.0.1/R.
Also, make sure you can access that URL in your browser.
The miniCRAN works good for me. There are few advantages to using miniCRAN to create the repository:
Security: Many R users are accustomed to downloading and installing new R packages at will, from CRAN or one of its mirror sites.
Easier offline installation: To install package to an offline server requires that you also download all package dependencies, Using miniCRAN makes it easier to get all dependencies in the correct format.
Improved version management: In a multiuser environment, there are good reasons to avoid unrestricted installation of multiple package versions on the server.
Use other R Package Indexes: You may wish to make packages available from public repositories other than CRAN, e.g. BioConductor, r-forge, OmegaHat, etc.
Prepare own R repo: You may wish to add custom in-house packages to your repository.
See intro:
Using miniCRAN to create a local CRAN repository
Create a local package repository using miniCRAN
I think the problem is revealed in this statement:
"In the contrib folder I put ... the PACKAGES file."
The PACKAGES file is an index for the repository. You need to create that file after your package files are placed in the repository directory. Don't copy and paste the PACKAGES file from another repository.
If I were you, here's what I would do. First, add the following code to your .Rprofile for a local repository:
utils::setRepositories(ind = 0, addURLs = c(WORK = "127.0.0.1/R"))
Restart R after changing your .Rprofile.
ind = 0 will indicate that you only want the local repository. Additional repositories can be included in the addURLs = option and are comma separated within the character vector.
Then, create the repository index:
tools::write_PACKAGES("127.0.0.1/R/src/contrib", verbose = TRUE)
After you do that, you should be able to generate a data frame that has a list of all the packages. For example, my_packages <- available.packages().
If you see packages in your repository data frame, then install using the following code:
install.packages("MyPackage")
For more information, please see here.