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.
Related
I am creating my first package, which shall be installed through Github. I thought that Rtools was needed only for the person creating it. However, people that tried to install it using Github were asked to update Rtools. Is this really necessary?
Doing some research, I found this: https://community.rstudio.com/t/missing-rtools-should-i-be-worried/27817
One of the answers says the following:
"This means that if you are going to install packages that need
compilation, you also have to install Rtools in your system. "
This is the repo with the package: https://github.com/datazoompuc/PNAD_Covid/tree/master/R/datazoom_pnad_covid
What does this actually mean? How do I know that my package needs compilation?
I thought that Rtools was needed only for the person creating it.
Yes, if and only if you distribute it as a binary. Then the creator uses Rtools to compile and link, and the user just installs, and enjoys.
That is how CRAN works as CRAN compiles for Windows users.
GitHub, however, is foremost a source repository so the installation from GitHub is using a source mode ... and every user will need to compile, and hence have Rtools. (Unless the package and all its depedencies are R-code only.)
You can also have a package repository on GitHub using e.g. the drat package to create it, but that is getting us a little further from the original question.
Your package "needs compilation" — i.e. needs Rtools to install from source (on Windows) — if it contains C or Fortran components, i.e. if you have anything in the src/ directory of your package ...
If you, the package author, don't know if you have C or Fortran code as part of your package, then you almost certainly don't.
It's quite possible that devtools is being overzealous, i.e. detecting that users have a not-most-current Rtools and suggesting (requiring??) that they update it, even though it's not needed for this installation.
For many R packages I try to install (on my Windows 10 machine), I get a warning:
> install.packages('rstan')
WARNING: Rtools is required to build R packages but is not currently installed. Please download and install the appropriate version of Rtools before proceeding:
I thought this was just an erroneous error message since the installation seemed to proceed anyway, but recently I tried to install a package (rstan) and found it completely nonfunctional. My hunch is that since rstan relies completely on compiling code with rcpp, maybe I only got away with the previous packages because I wasn't using the functions in them that relied on Rtools.
I reinstalled Rtools 4.0, and devtools::find_rtools() returns TRUE. But when I run Sys.getenv()['PATH'] there is no Rtools on the path. There isn't a place in the installation process to tell it I want Rtools on the path either, so these instructions don't help - the menus they refer to don't exist for me. So I thought this might be an issue where the new Rtools 4.0 doesn't put itself on the system path. But the problem persisted even after I directly edited the Windows path environment variables (both system and user versions) to include the path given to me by pkgbuild::rtools_path() (C:\rtools40\usr\bin, a path which both exists and appears to be correct).
This doesn't seem to be the same problem as Rtools 4.0 (Rstudio falsely claims it was deleted), since there are no claims Rtools was deleted. It's also not the same as Rtools not being detected by R as far as I can tell: I'm not leaving any features out of my Rtools installation - I'm not even getting the option to in my install wizard.
Would appreciate any advice or recommendations.
Rtools40 requires that you add its bin directory to your PATH variable. The full instructions are here.
You can update your ~/.Renviron file with any of the following methods:
You can do that manually by opening ~/.Renviron and putting the following in it:
PATH="${RTOOLS40_HOME}\usr\bin;${PATH}"
You can also use R (Gui or RStudio or Shell) with the following:
writeLines(
'PATH="${RTOOLS40_HOME}\\usr\\bin;${PATH}"',
con = file("~/.Renviron", open = "a")
)
Both of these methods require a restart of R.
I have a code to track objects in the images. This code uses few function from the package clue. So clue is already installed in my system. Now I have created a package using the same code.
My description file has following lines.
Depends: R (>= 3.4.3),
clue
Because clue is already installed, I thought it will not get installed again when I use install("mypackage"). But to my surprise it re-installed the package. I have tried this with other installed packages, too. When I give it as "depends" or "import", it re-installs the packages. I do not want to re-install the packages if they are already on my system. Is there a way to tell R package installer to avoid re-installing packages that exist on the user's system? Some of these packages are quite large and take a lot of time to install. In addition, I have installed some packages with binary source/dependency that required me to give path for several libraries.
You can just use
install.packages(..., dependencies = FALSE)
or if you use devtools::install:
install(..., dependencies = FALSE)
EDIT: see edit in end.
I have a R package in github and I'm using devtools::install_github to install it, which also install dependency packages.
Recently this process will install httpuv as source package, but compiling it in Mac meet errors with automake (something like this). I installed automake, then there was error with clang: error: unsupported option '-fopenmp'.
The issue and the possible solutions 1 2 seemed to be quite complicated. I think the CRAN version of httpuv probably will work for me, and I don't want my users to go through so many errors and fixing compiler errors.
I'd like to just install all dependency packages from CRAN in binary. For some packages that do need the more up to date version, I have specified it in my package description with remote section.
I checked install_github, then install, then install.packages. It seemed that the default behavior for binary vs source package is
An alternative (and the current default) is "both" which means ‘use
binary if available and current, otherwise try source’. The action if
there are source packages which are preferred but may contain code
which needs to be compiled is controlled by
getOption("install.packages.compile.from.source").
My getOption("install.packages.compile.from.source") is interactive. This is actually a preferred behavior for me. However I never see the interactive prompt.
I tried to give a type = "binary" parameter in install_github, but it doesn't seem to work, maybe it's not passed to every dependency package install?
EDIT:
I found the situation is a little bit more complex:
my app specified to install shiny github version via remote in description. shiny specified to install httpuv github version in remote section too. So this is actually the intended behavior.
I'm not sure if there is a solution available, other than require CRAN version of shiny in my package.
EDIT 2: It's more complex than my previous findings.
I removed remote section in my package description, supposedly only CRAN version is needed. However install_github still install most dependencies from github.
I finally found out that I have these dependencies github version installed, so their description in my local disk have the github remote information, and install_github found this information and "upgrade" them again, even when some of them have no change.
So I need to uninstall them first, only use CRAN version.
The really problem here is that if a dependency package is already new, it should not be installed. It could be a bug of devtools.
install_github passes arguments to devtools::install, and there upgrade_dependencies= FALSE and maybe even dependencies = FALSE might be what you're after:
install_github("you/urPackage", upgrade_dependencies = FALSE)
Some time ago, you used to be able to install the rcom package in R to use COM scripting (eg, access to external programs.) Unfortunately, it seems to be discontinued:
Package ‘rcom’ was removed from the CRAN repository.
Formerly available versions can be obtained from the archive.
This depends on statconnDCOM, which nowadays restricts use, contrary
to the CRAN policy for a package with a FOSS licence. See
http://rcom.univie.ac.at/ and http://www.statconn.com/.
Following the archive and statconn links and installing one of the older versions in R version 3 gives the error:
“Error: package ‘rcom’ was built before R 3.0.0: please re-install
it”.
I am not very familiar with R, but there seems no way around this message - after all, it occurs when installing, so re-installing doesn't seem to be the answer. It appears as though rcom is simply not available for recent (3.0+) versions of R. I have also scanned the package list, although searching for "COM" there returns over a hundred results and it is possible I missed the right one when clicking through them.
How can I use the rcom package, or use COM from within R some other way?
(Note: I am asking this question on behalf of a colleague. I have no experience with R myself at all. Both of us, when searching for answers, could not find anything. I am sure that others are also using COM in the latest version of R, though!)
I looked at the rcom source code a few months ago. It seems I can get it to build and install OK on R3.0.1. Below is the procedure if it helps.
Get a checkout of the latest source code of rcom. I have rcom_2.2-5.tar.gz locally. I can google something at the following address, but I have no idea of the provenance, so up to you to check it is legit. http://cran.open-source-solution.org/web/packages/rcom/index.html
in R do install.packages('rscproxy')
install Rtools as per the instructions on the R web site (http://cran.r-project.org/bin/windows/Rtools),
open a Windows command prompt i.e. run "CMD"
go to the folder containing the 'rcom' folder, and at the command prompt:
set R="c:\Program Files\R\R-3.0.1\bin\i386\R.exe"
%R% CMD check --no-manual rcom
check it passes without too many complaints. Your call as to the --no-manual option (if you have MiKTeX installed you may remove it)
%R% CMD INSTALL rcom
should result in
installing to c:/Rlib/rcom/libs/i386
** R
** inst
** preparing package for lazy loading
** help
*** installing help indices
** building package indices
** testing if installed package can be loaded
rcom requires a current version of statconnDCOM installed.
To install statconnDCOM type
installstatconnDCOM()
This will download and install the current version of statconnDCOM
You will need a working Internet connection
because installation needs to download a file.
* DONE (rcom)
in R:
library(rcom)
installstatconnDCOM()
I tried a comRegisterRegistry() ; comRegisterServer()
; x<-comGetObject("Excel.Application") but I get a NULL for x. I am not a user of rcom so while it all seems to compile fine; it may just not work anymore.
If you happen to need to access .NET code, a viable option (and yes I have a vested interest in mentioning it) may be the rClr package.
Hope this helps; I'd be interested to hear how you go.
This really should be a comment, but I don't have enough rep points yet to leave one.
I found that the above steps did not work for me, but the answer posted by Lisa Ann on this question, RExcel in R 3.0.x, did solve my problem installing rcom. Since you need rcom to run RExcel, the initial steps to install RExcel cover installing rcom on newer versions of R (such as 3.0.2).
Specifically, following the advice on statconn's wiki, http://homepage.univie.ac.at/erich.neuwirth/php/rcomwiki/doku.php?id=wiki:how_to_install
You also need to follow these instructions if you upgrade R, i.e. you install a new >release of R after you have installed RExcel.
Download the statconn DCOM server and execute the program you downloaded
Start R as administrator (on Windows 7 you need to right-click the R icon and click the >corresponding item)
In R, run the following commands (you must start R as administrator to do this)
install.packages(c("rscproxy","rcom"),repos="http://rcom.univie.ac.at/download",lib=.Library)
library(rcom)
comRegisterRegistry()
Now you have rcom installed, [instructions for installing RExcel follow...]
New versions of rcom and rscproxy (also for current versions of R) are available from a different repository. Just use http://rcom.univie.ac.at/download as the R repository to install from and you can download and install binary versions of statconn packages from there.
Hope this helps!