I am developing a framework for reproducible computing with R. One problem that I am struggling with is that some R code might run perfectly in version X.Y-Z of a package, but then why you try to reproduce it 3 years later, the packages have updated, some functions are changed, and the code doesn't run anymore. This problem affects also for example Sweave documents that use packages.
The only way to confidently reproduce the results is by installing the R version and version of the packages that were used by the original author. If this was a single case, one could pull stuff from the CRAN archives and install appropriate versions. But for my framework this is impractical, and I need to have the package versions preinstalled.
Assume for now that I restrict myself to a single version of R, e.g. 2.14. What would be a practical way to install many versions of R packages, so that I can load them on the fly? I suppose I can do something like creating separate library directories for every version of every package and then using custom lib.loc arguments while loading them. This is going to be messy though. Any tips or previous attempts to do something similar?
My framework runs on Ubuntu server.
You could install packages with versions (e.g. rename to foo_1.0 directory instead of foo) and softlink the versions you want to re-create a given R + packages snapshot into one library. Obviously, the packages could actually live in a separate tree, so you could have library.projectX/foo -> library.all/foo/1.0.
The operating system gives you even more handles for complete separation, and the Debian / Ubuntu stack as a ton of those available. Two I have played with are
chroot environments: We use this to complete separate build environments from host machines. For example, all Debian uploads I produced are built in a i386 pbuilder chroot hosted on my amd64 Ubuntu server. Chroot is a very powerful Unix system call. Chroots, and particularly the pbuilder system built on top of it (for Debian package building) are meant to operate headless.
Virtual machines: This gives you full generality. My not-so-powerful box easily handles three virtual machines: Debian i386, Ubuntu i386 as well as Windoze XP. For this, I currently use KVM along with libvirt; this is Linux specific. I have also used VirtualBox and VMware in the past.
I would try to modify the DESCRIPTION file, and change the field "Package" there by adding the version number.
For example, you download the package source a from CRAN page (http://cran.r-project.org/web/packages/pls/). Unpack the compressed file (pls_2.3-0.zip) to a directory ("pls/"). The following steps are to change the package name in DESCRIPTION ("pls/DESCRIPTION") and installation with R command 'R CMD INSTALL pls/', where 'pls/' is a path to the package source with modified DESCRIPTION file.
Playing with R library paths seems a dangerous thing to me.
Related
We have a ubuntu linux server in our office which is a air-gapped environment. There is no internet access to external network.
However I would like to install few R packages like ggplot2, Database Connector, dplyr, Tidyverse etc. I have more than 10-15 packages to download
While I cannot write the usual command install.packages("DatabaseConnector"), I have to download the zipped folders from CRAN as shown here.
I am new to R. So, can you help me with my questions given below?
a) Why is there are no files for linux systems? I only see windows binaries and macOS binaries. Which one should I download?
b) Should I download binaries or package source? which one is easy to install?
c) When I download packages like above as zipped file from CRAN like shown here, will the dependencies be automatically downloaded as well? Or should I look at error messages and keep downloading them one by one?
d) Since I work in a Air-gapped environment, what would be the best way to do this process efficiently.
Under linux packages are always installed from source. There are no official binary packages for linux. However, your distro might offer some of them in the official repositories. Ubuntu does. However these tend to be quite old versions and usually limited to a handfull of the most important packages. So, for linux you have to download the source packages. The zip files are for windows and will not work.
You will also need to download all of the dependencies of the packages. For something like tidyverse this will be a huge number. Tracking those by hand is a lot of work. Easiest is probably to use a package like miniCRAN outside of your airgapped system to build a selective copy of CRAN. You can specify the packages you want and the package will download all dependencies. You can then copy the downloaded directories to your server, point install.packages in the right direction and install as usually using install.packages. For details see https://andrie.github.io/miniCRAN/articles/miniCRAN-introduction.html.
You might also run into the problem that your system does not have all of the depencies needed to build all of the packages. Under ubuntu you need for example to install libxml2-dev to be able to install the xml package. For that you need to use the package manager of ubuntu. How to do that on an airgapped system is another issue
We have established a simple local CRAN-like repository for R packages. There are many users, all of which use the same version of Linux.
Is there a way of convincing R to provide pre-compiled Linux packages instead just source ones? The compilation step takes a considerable amount of time for anyone using our repository. It should be possible to precompile and reuse the same binaries, since we can guarantee that the Linux version is consistent for all users.
How could one hack something like this together?
In the very narrow sense of "all of which use the same version of Linux" you actually have an option (that happens to be relatively littler known). Create binary packages using e.g.
R CMD INSTALL --build nameOfDirectoryWithSources
As R CMD INSTALL --help says it
--build build binaries of the installed package(s)
and these are not .deb or .rpm alike packages: no dependency information or alike is added. But they do exactly what you ask for: save on compilation time.
I am not aware of a repository structure one can build of this though.
I want to convert certain R packages (which have been installed under windows) for linux usage, then I can simply upload these R package to the linux server, and therefore it is not necessary to install these R packages again under linux environment.
I wonder that is it doable?
Most likely not. Many are precompiled binaries for windows, but need to be compiled in linux. Especially those packages that contain compiled code (such as C or C++), these need to be compiled on the target platform so that they are linked to that platform's libraries.
If the issue is the time it takes to maintain a set of packages, one thing you can do is create your own utilities package, which imports all of the packages you would want. Then, if you install your utilities package, it will automatically install all of the others.
My work setup relies heavily on rcom library, which is so far unavailable for R 3.x (due to licensing problems).
I'm happy to keep using the R v. 2.15.3, but the install.packages doesn't fetch new packages anymore.
Is there any way of making old R download packages on demand with something like install.packages("MASS")?
OK, this is the fallback solution:
We can always download (windows) old packages from this location on the CRAN site and unpack the ZIPs into C:\Program Files\R\R-2.15.3\library or equivalent. But it would be cool to use some form of simple R command for doing it.
It is also possible to try using different mirrors, because mirrors are not equivalent with respect to volume of archives.
At least this is how I do it on (virtual) Windows XP 32 bit.
I'm convinced that using Dirk's package is the best way to install and maintain R on an Ubuntu system. But I want to have some fun and get used to installing R from source.
What are the most common configure flags to use when installing?
Also, if I want to install 2.14.1 and I have 2.14.0 currently installed (which was installed from source), should I first uninstall 2.14.0?
There was a recent thread somewhere about having several versions---one from the apt-get repo, one in /usr/local. Try to find that...
Otherwise, I will roll up 2.14.1 on Friday morning, Michael will do his magic and the repo will have .deb packages of 2.14.1 'real soon', sometimes within a day.
Lastly, you can see which flags are used by getting the package sources for which you just do apt-get source r-base (and that works for any Debian/Ubuntu package that way if you have source references in apt's file.
Edit: By the way, regarding the '64-bit' aspect of your question: Nada. We don't do anything differently. It is "merely" the host OS being more generous with resources. But R finds all it needs to know on its own via its configure etc logic.