I would like to be able to call R (2.15.3) from within R (3.0.2). In order to use a package (windows binary, not on cran) that is available in only the older version of R. Is this possible?
This is R. There is no if, only how
said Simon Blomberg.
You could call an older version of R using system() and the appropriate hacks in your OS. Which is something odd to do, and opens tons of possibilities for serious damage to your computer when you hit it in frustration.
Or you could download the source of the package and rebuild it in R 3.0. There's been some rather drastic internal changes in the way packages are built and used in R (the most obvious being the removal of support for packages without a namespace).
Hence :
if the package does not have a namespace: download the source (.tar.gz), read the manual "Writing R extensions" if you didn't before, and add a namespace file with the usual exports. As explained in Writing R extensions, this can be as simple as adding a single line
exportPattern("^[^\\.]")
if the package has a namespace, build from source on your machine and you should be good to go. This is simply done by using:
install.packages("path/to/package.tar.gz",type="source")
Note that if you want to install from source on a Windows machine, you'll need a compatible version of Rtools : http://cran.r-project.org/bin/windows/Rtools/
If you don't want to be bothered with it, mail the author/maintainer of the package and kindly ask if they'd like to rebuild it for you.
Related
I am trying to embed RInside to my application on win7 64-bit system but when I initialize an RInside:
Rin = new RInside(argc, argv);
the following message appears:
Error in loadNamespace(name) : there is no package called 'Rcpp'
This error only occurs with Windows.
I think you get that issue when your .libPaths() differ--in other words run the .libPaths() function to see the paths stored by R for its use. Then check where RInside is installed, and make sure Rcpp is installed there too. It is a setup issue.
In other words, it should work if you have Rcpp and RInside installed where the basic R libraries are. Otherwise you have to tell the (embedded) R session about the other location (and before it starts).
There are more Windows users on the list, so you could try asking on rcpp-devel.
First get your default library locations by command ".Library" in R.
Get Rcpp package from https://cran.r-project.org/web/packages/Rcpp/index.html.
Unzip and copy folder "Rcpp" to your default library locations obtained from step1.
Now you are ready to install packages which have dependencies on Rcpp.
Dirk is right in this case, BUT if the .libPaths() does not work, then please also check if you have the latest packages.
I am posting this as an ancillary answer backup which I ran into with the shiny package backend switch of their code needing Rcpp!
In this case of getting the "no package" error message, I fixed it by:
Selecting devtools package and then using this line below. (if you don't have devtools then get it with install.packages("devtools")
devtools::install_github("rstudio/shiny")
The development version of the package handled this better, and added the package as a dependency.
Mods - I realize this is an answer to an old question, but I might help others not wasting an hour like I just did.
You might find it easy if the answers are for both R studio users and non R studio users.
R Studio users
First get your default library locations by command ".Library" in R.
Get Rcpp package from https://cran.r-project.org/web/packages/Rcpp/index.html.
Unzip and copy folder "Rcpp" to your default library locations obtained from step 1, you will find another folder named library, paste the unzip folder in it.
Non R studio Users
First get your default library locations by command ".libPath" in R.
Get Rcpp package from https://cran.r-project.org/web/packages/Rcpp/index.html.
Unzip and copy folder "Rcpp" to your default library locations obtained from step 1, you will find another folder named library, paste the unzip folder in it.
I was also getting this error while trying to run the 'ggplot' function from the ggplot2 package. After trying the suggestions posted here and elsewhere (checking file paths, restarting R, clearing out my environment, etc.) and encountering several other cryptic error messages, it turned out that I needed to download the latest version of base R for Windows (v3.4.1) and update my version of R-Studio to the latest version also (v1.0.153).
After doing this my 'ggplot' function was working again and I was able to render my figure from R Studio without any further issues.
I was also getting this message when trying to use ggplot. I first updating both my R for Windows to 3.4.3. Then updating R studio to version 1.1.423; then, updating all of the packages and being sure to access the R version 3.4.3 from R studio, I still got the message. None of these things fixed the error. I was ready to give up until I noticed that I was calling library(ggplot) and had ggplot::ggplot in my code. THIS WAS THE PROBLEM. I changed it to library(ggplot2) and the instance to ggplot2::ggplot(...). THIS FIXEd the problems.
I was facing a similar issue, and I simply installed the said package. It's working perfectly for me.
I am trying to implement a reducer for Hadoop Streaming using R. However, I need to figure out a way to access certain libraries that are not built in R, dplyr..etc. Based on my research seems like there are two approaches:
(1) In the reducer code, install the required libraries to a temporary folder and they will be disposed when the session is done, like this:
.libPaths(c(.libPaths(), temp <- tempdir()))
install.packages("dplyr", lib=temp, repos='http://cran.us.r-project.org')
library(dplyr)
...
However, this approach will have a dramatic overhead depending on how many libraries you are trying to install. So most of the time will be wasted on installing libraries(sophisticated libraries like dplyr has tons of dependencies which will take minutes to install on a vanilla R session).
So sounds like I need to install it before hand, which leads us to approach2.
(2) My cluster is fairly big. And I have to use some tool like Ansible to make it work. So I prefer to have one Linux shell command to install the library. I have seen R CMD INSTALL... before, however, it feels like will only install packages from source file instead of doing install.packages() in R console, figure out the mirror, pull the source file, install it in one command.
Can anyone show me how to use one command line in shell to non-interactively install a R package?
(sorry for this much background knowledge, if anyone thinks I am not even following the right phylosophy, feel free to leave in the comment how this whole cluster R package should be managed.)
tl;dr
Rscript -e 'install.packages("drat", repos="https://cloud.r-project.org")'
You mentioned you are trying to install dplyr into custom lib location on your disk. Be aware that dplyr package does not support that. You can read more in dplyr#4641.
Moreover if you are installing private package published in internal CRAN-like repository (created by drat or tools::write_PACKAGES), you can easily combine repos argument and resolve dependencies from CRAN automatically.
Rscript -e 'install.packages("priv.pkg", repos=c("cran.priv","https://cloud.r-project.org"))'
This is very handy feature of R repositories, although for production use I would recommend to cache packages from CRAN locally, and use those, so you will never be surprised by a breaking changes in your dependencies. For quality information about handling R in production I suggest to look into talk by Wit Jakuczun at WhyR2019 How to make R great for machine learning in (not only) Enterprise: slides, video.
You may find littler useful. It is a command-line front-end / variant of R (which uses the R-embedding interface).
I use the install.r script all the time to install package from the shell. There is a second variant with more command-line argument parsing but it has an added dependency.
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 have a windows server that does not allow me to install anything but it allows me to run exe files (Meaning that I cannot simply download the R installation package and install R that way). I want to run R on it and I like to know if it is possible for me to make an R.exe with some packages like ggplot and lattice included?
Do you have any filestore on the server? I can't imagine that you wouldn't have. You can install packages to any directory, which can then be your own personal library. Look at the help(install.packages) and help(library) and there's a lib or lib.loc argument that tells it where to stick it.
If the reason you can't install is because install.packages can't get through the network to CRAN, then download the binary from CRAN, transfer it to the server, and install that way.
Note that I didn't answer your question about building an R exe with bundled packages (here's that answer: "No") because you thought the answer to that question was the solution to your real problem ("I can't install packages"). Always ask a question to your original problem...
I ran across the portable version of R that could do it for me. It generates a folder that can be moved to the new server.
http://sourceforge.net/projects/rportable/
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.