after upgrading R, can I automatically update the packages [duplicate] - r

Andrew Gelman recently lamented the lack of an easy upgrade process for R (probably more relevant on Windows than Linux). Does anyone have a good trick for doing the upgrade, from installing the software to copying all the settings/packages over?
This suggestion was contained in the comments and is what I've been using recently. First you install the new version, then run this in the old verion:
#--run in the old version of R
setwd("C:/Temp/")
packages <- installed.packages()[,"Package"]
save(packages, file="Rpackages")
Followed by this in the new version:
#--run in the new version
setwd("C:/Temp/")
load("Rpackages")
for (p in setdiff(packages, installed.packages()[,"Package"]))
install.packages(p)

Just for completeness, there are some ways to prevent you from having this problem. As Dirk said, save your packages in another directory on your computer.
install.packages("thepackage",lib="/path/to/directory/with/libraries")
You can change the default .Library value using the function .libPaths too
.libPaths("/path/to/directory/with/libraries")
This will put this path as a first value in the .Library variable, and will make it the default.
If you want to automate this further, you can specify this in the Rprofile.site file, which you find in the /etc/ directory of your R build. Then it will load automatically every time R loads, and you don't have to worry about that any more. You can just install and load packages from the specified directory.
Finally, I have some small code included in my Rprofile.site allowing me to reinstall all packages when I install a new R version. You just have to list them up before you update to the new R version. I do that using an .RData file containing an updated list with all packages.
library(utils)
## Check necessary packages
load("G:\Setinfo\R\packagelist.RData") # includes a vector "pkgs"
installed <- pkgs %in% installed.packages()[, 'Package']
if (length(pkgs[!installed]) >=1){
install.packages(pkgs[!installed])
}
I make the packagelist.RData by specifying .Last() in my Rprofile.site. This updates the package list if I installed some :
.Last <- function(){
pkgs <- installed.packages()[,1]
if (length(pkgs) > length(installed)){
save(pkgs,file="G:\Setinfo\R\packagelist.RData")
}
}
When I install a new R version, I just add the necessary elements to the Rprofile.site file and all packages are reinstalled. I have to adjust the Rprofile.site anyway (using sum contrasts, adding the extra code for Tinn-R, these things), so it's not really extra work. It just takes extra time installing all packages anew.
This last bit is equivalent to what is given in the original question as a solution. I just don't need to worry about getting the "installed" list first.
Again, this doesn't work flawless if you have packages that are not installed from CRAN. But this code is easily extendible to include those ones too.

If you are using Windows, you might want to use the installr package:
install.packages("installr")
require(installr)
updateR()
The best way of doing this is from the RGui system. All your packages will be transferred to the new folder and the old ones will be deleted or saved (you can pick either).
Then once you open RStudio again, it immediately recognizes that you are using an updated version. For me this worked like a charm.
More info on installr here.

Two quick suggestions:
Use Gabor's batchfiles which are said to comprise tools helping with e.g. this bulk library relocations. Caveat: I have not used them.
Don't install libraries within the 'filetree' of the installed R version. On Windows, I may put R into C:/opt/R/R-$version but place all libraries into C:/opt/R/library/ using the following snippet as it alleviates the problem in the first place:
$ cat .Renviron # this is using MSys/MinGW which looks like Cygwin
## Example .Renviron on Windows
R_LIBS="C:/opt/R/library"

The method suggested above will not completely work if you have packages that are not from CRAN. For example, a personal package or a package downloaded from a non-CRAN site.
My preferred method on Windows (upgrading 2.10.1 to 2.11.0):
Install R-2.11.0
Copy R-2.10.0/library/* to R-2.11.0/library/
Answer "no" to the prompts asking you if it is okay to overwrite.
Start R 2.11.0
Run the R command update.packages()

With respect to the solution given in the question, it might not be easy to run your older version of R if you have already installed the new version. In this case, you can still reinstall all missing packages from the previous R version as follows.
# Get names of packages in previous R version
old.packages <- list.files("/Library/Frameworks/R.framework/Versions/3.2/Resources/library")
# Install packages in the previous version.
# For each package p in previous version...
for (p in old.packages) {
# ... Only if p is not already installed
if (!(p %in% installed.packages()[,"Package"])) {
# Install p
install.packages(p)
}
}
(Note that the argument to list.files() in the first line of code should be the path to the library directory for your previous R version, where all folders of packages in the previous version are. In my current case, this is "/Library/Frameworks/R.framework/Versions/3.2/Resources/library". This will be different if your previous R version is not 3.2, or if you're on Windows.)
The if statement makes sure that a package is not installed if
It's already installed in the new R version, or
Has been installed as a dependency from a package installed in a previous iteration of the for loop.

Following Dirk's suggestion, here is some R code to do it on windows: How to easily upgrade R on windows XP
Update (15.04.11): I wrote another post on the subject, explaining how to deal with common issues of upgrading R on windows 7

Two options:
Implement my answer here
If you use R under Eclipse with StatET, open Run Configurations, click on Console tab and in the box called R snippet run after startup add this line with your choice of directory: .libPaths("C:/R/library")

I am on Windows 8 and for some weird reason, I can never install packages using my internet connections.
I generally install it using the .zip file from CRAN.
After I went from R 3.2.5 to R 3.3.1.
I simply copied the packages from
C:\Path\to\packa\R\win-library\3.2 to C:\Path\to\packa\R\win-library\3.3.
And then I restarted the R session. Worked perfectly.
I haven't checked if ALL the packages are functioning well.
But, the ones I checked are working perfectly well.
Hope this hack works for everybody.
Cheers.

The accepted answer might work if you have foresight, but I had already gotten rid of the old version so wasn't able to follow these directions.
The steps described below worked for OSX upgrading from 2.1 and 3.1.
UPDATED: To get the directory for your most recent version (instead of typing in 3.1 or 3.2) you can use the below commands. The second one converts directly to the R-variable, skipping . and .. and .DS_Store, use:
OLD=$(ls -d /Library/Frameworks/R.framework/Versions/*.* |tail -n 2 | head -n 1)Resources/library/
echo "packages = c(\"`ls $OLD | tail +4| paste -s -d ',' - | sed -E 's|,|\",\"|'g`\")" | tr -d "/"
(Add |pbcopy to the end to copy it directly to your Mac clipboard)
Then within R you can paste that variable that is generated. Once that is defined in the new version of R, you can loop through the installed packages from the instructions above...
for (p in setdiff(packages, installed.packages()[,"Package"]))
install.packages(p, dependencies=TRUE, quiet=TRUE, ask=FALSE)

for me this page is good
https://www.r-statistics.com/2013/03/updating-r-from-r-on-windows-using-the-installr-package/
or
another option is just install the new option and at final you put, for example in windows in my pc
.libPaths(c(
"D:/Documents/R/win-library/3.2",
"C:/Program Files/R/R-3.2.3/library",
"C:/Program Files/R/R-3.2.0/library",
"D:/Documents/R/win-library/2.15"
)
every path of last version in my case i always put the first path is "D:/Documents/R/win-library/3.2" that is fixed
and then i put the other because you do not need copy or move any packages, in my sugest just call it

linux + bash + debian + apt users:
If you're installing/upgrading to the newest version of R, then we may assume you have root permissions. (Not essential, just makes the process a lot simpler; for consistency the script below uses sudo for all installs.)
As the R packages are also installed by root, it is thus permissible to place these in /usr/local/.
The call to curl below assumes you are already interested in the sid release of R, the very latest unstable version (as required when building/checking an R package) i.e.
cat /etc/apt/sources.list | grep 'sid' || exit 1
although this could easily be replaced with a recent stable release e.g. buster.
Note that I am not using a key as is typically recommended. This is not essential, particularly if (as in the script which follows) we install packages within R itself (Rscript -e below). Also, such keys have a tendency to break/change every few years. Thus, you are of course welcome to add the following preface to the file R.sh which follows:
sudo apt-key adv --keyserver keyserver.ubuntu.com \
--recv-keys E298A3A825C0D65DFD57CBB651716619E084DAB9
The array of R packages is clearly not exhaustive but gives some examples which I personally find useful. A fresh install/upgrade with the debian package r-recommended, as below, should give the latest version of all of the the standard 'recommended' packages (e.g. survival). I believe there may be a slight lag between a CRAN release and an update to the relevant debian package. Thus, you may wish to add some of these to the array below if having the latest version of a 'recommended' R package is essential.
The debian packages installed in the process below are also neither essential (for using r-base) nor exhaustive but provide a no. of 'add-ons' which are important for a reasonable no. of R packages.
Anyway... place the following in R.sh:
sudo apt update && sudo apt --yes full-upgrade
sudo apt install --yes libappstream4 curl
### ov1 = online version; lv1 = local version (i.e. currently installed)
ov1=$(curl --silent --url https://packages.debian.org/sid/r-base |
grep 'meta name=\"Keywords\"' |
grep --only-matching '[0-9].*[0-9]') ; echo $ov1
## command -v = print a description of COMMAND similar to the `type' builtin
## && = if prior command succeeds, then do; || = if prior fails, then do
command -v 'R --version' &&
lv1=$(R --version |
grep --only-matching '[0-9\.]*[0-9]' |
## || = otherwise
head -1) ||
lv1=0
## 'lt' = less than
if dpkg --compare-versions "$lv1" 'lt' "$ov1"
then ## declare -a = indexed array
declare -a deb1=('r-base' 'r-base-dev' 'r-recommended')
for i in "${deb1[#]}"
do sudo apt install --yes "$i"
done
fi
### certain Debian packages are required by 'R' so best have these first
sudo apt install --yes ccache libcairo2-dev libxml2-dev libcurl4-openssl-dev \
libssl-dev liblapack-dev libssl-dev
declare -a pkg1=('data.table' 'ggplot2' 'knitr' 'devtools' 'roxygen2')
## installing as 'root' so these are installed in
Rscript -e ".libPaths()[1]"
for i in "${pkg1[#]}"
do sudo Rscript -e "install.packages('$i', dependencies=TRUE)"
done
### other useful additions
sudo apt install --yes libblas-dev libboost-dev libarmadillo-dev \
jags pandoc pandoc-citeproc
sudo apt update && sudo apt full-upgrade
Then execute it, e.g. assuming in directory already: source R.sh.
Installing packages (whether debian or R) one-by-one in a loop from shell is somewhat inefficient, but allows for simpler tracing of errors, IMHO. May take some time depending on the no. of R packages, so maybe simplest to let run overnight...

In linux, Now it is very simple. Just make:
install.packages("ropenblas")
ropenblas::rcompiler()

Related

updating packages in older R version with new R version [duplicate]

Andrew Gelman recently lamented the lack of an easy upgrade process for R (probably more relevant on Windows than Linux). Does anyone have a good trick for doing the upgrade, from installing the software to copying all the settings/packages over?
This suggestion was contained in the comments and is what I've been using recently. First you install the new version, then run this in the old verion:
#--run in the old version of R
setwd("C:/Temp/")
packages <- installed.packages()[,"Package"]
save(packages, file="Rpackages")
Followed by this in the new version:
#--run in the new version
setwd("C:/Temp/")
load("Rpackages")
for (p in setdiff(packages, installed.packages()[,"Package"]))
install.packages(p)
Just for completeness, there are some ways to prevent you from having this problem. As Dirk said, save your packages in another directory on your computer.
install.packages("thepackage",lib="/path/to/directory/with/libraries")
You can change the default .Library value using the function .libPaths too
.libPaths("/path/to/directory/with/libraries")
This will put this path as a first value in the .Library variable, and will make it the default.
If you want to automate this further, you can specify this in the Rprofile.site file, which you find in the /etc/ directory of your R build. Then it will load automatically every time R loads, and you don't have to worry about that any more. You can just install and load packages from the specified directory.
Finally, I have some small code included in my Rprofile.site allowing me to reinstall all packages when I install a new R version. You just have to list them up before you update to the new R version. I do that using an .RData file containing an updated list with all packages.
library(utils)
## Check necessary packages
load("G:\Setinfo\R\packagelist.RData") # includes a vector "pkgs"
installed <- pkgs %in% installed.packages()[, 'Package']
if (length(pkgs[!installed]) >=1){
install.packages(pkgs[!installed])
}
I make the packagelist.RData by specifying .Last() in my Rprofile.site. This updates the package list if I installed some :
.Last <- function(){
pkgs <- installed.packages()[,1]
if (length(pkgs) > length(installed)){
save(pkgs,file="G:\Setinfo\R\packagelist.RData")
}
}
When I install a new R version, I just add the necessary elements to the Rprofile.site file and all packages are reinstalled. I have to adjust the Rprofile.site anyway (using sum contrasts, adding the extra code for Tinn-R, these things), so it's not really extra work. It just takes extra time installing all packages anew.
This last bit is equivalent to what is given in the original question as a solution. I just don't need to worry about getting the "installed" list first.
Again, this doesn't work flawless if you have packages that are not installed from CRAN. But this code is easily extendible to include those ones too.
If you are using Windows, you might want to use the installr package:
install.packages("installr")
require(installr)
updateR()
The best way of doing this is from the RGui system. All your packages will be transferred to the new folder and the old ones will be deleted or saved (you can pick either).
Then once you open RStudio again, it immediately recognizes that you are using an updated version. For me this worked like a charm.
More info on installr here.
Two quick suggestions:
Use Gabor's batchfiles which are said to comprise tools helping with e.g. this bulk library relocations. Caveat: I have not used them.
Don't install libraries within the 'filetree' of the installed R version. On Windows, I may put R into C:/opt/R/R-$version but place all libraries into C:/opt/R/library/ using the following snippet as it alleviates the problem in the first place:
$ cat .Renviron # this is using MSys/MinGW which looks like Cygwin
## Example .Renviron on Windows
R_LIBS="C:/opt/R/library"
The method suggested above will not completely work if you have packages that are not from CRAN. For example, a personal package or a package downloaded from a non-CRAN site.
My preferred method on Windows (upgrading 2.10.1 to 2.11.0):
Install R-2.11.0
Copy R-2.10.0/library/* to R-2.11.0/library/
Answer "no" to the prompts asking you if it is okay to overwrite.
Start R 2.11.0
Run the R command update.packages()
With respect to the solution given in the question, it might not be easy to run your older version of R if you have already installed the new version. In this case, you can still reinstall all missing packages from the previous R version as follows.
# Get names of packages in previous R version
old.packages <- list.files("/Library/Frameworks/R.framework/Versions/3.2/Resources/library")
# Install packages in the previous version.
# For each package p in previous version...
for (p in old.packages) {
# ... Only if p is not already installed
if (!(p %in% installed.packages()[,"Package"])) {
# Install p
install.packages(p)
}
}
(Note that the argument to list.files() in the first line of code should be the path to the library directory for your previous R version, where all folders of packages in the previous version are. In my current case, this is "/Library/Frameworks/R.framework/Versions/3.2/Resources/library". This will be different if your previous R version is not 3.2, or if you're on Windows.)
The if statement makes sure that a package is not installed if
It's already installed in the new R version, or
Has been installed as a dependency from a package installed in a previous iteration of the for loop.
Following Dirk's suggestion, here is some R code to do it on windows: How to easily upgrade R on windows XP
Update (15.04.11): I wrote another post on the subject, explaining how to deal with common issues of upgrading R on windows 7
Two options:
Implement my answer here
If you use R under Eclipse with StatET, open Run Configurations, click on Console tab and in the box called R snippet run after startup add this line with your choice of directory: .libPaths("C:/R/library")
I am on Windows 8 and for some weird reason, I can never install packages using my internet connections.
I generally install it using the .zip file from CRAN.
After I went from R 3.2.5 to R 3.3.1.
I simply copied the packages from
C:\Path\to\packa\R\win-library\3.2 to C:\Path\to\packa\R\win-library\3.3.
And then I restarted the R session. Worked perfectly.
I haven't checked if ALL the packages are functioning well.
But, the ones I checked are working perfectly well.
Hope this hack works for everybody.
Cheers.
The accepted answer might work if you have foresight, but I had already gotten rid of the old version so wasn't able to follow these directions.
The steps described below worked for OSX upgrading from 2.1 and 3.1.
UPDATED: To get the directory for your most recent version (instead of typing in 3.1 or 3.2) you can use the below commands. The second one converts directly to the R-variable, skipping . and .. and .DS_Store, use:
OLD=$(ls -d /Library/Frameworks/R.framework/Versions/*.* |tail -n 2 | head -n 1)Resources/library/
echo "packages = c(\"`ls $OLD | tail +4| paste -s -d ',' - | sed -E 's|,|\",\"|'g`\")" | tr -d "/"
(Add |pbcopy to the end to copy it directly to your Mac clipboard)
Then within R you can paste that variable that is generated. Once that is defined in the new version of R, you can loop through the installed packages from the instructions above...
for (p in setdiff(packages, installed.packages()[,"Package"]))
install.packages(p, dependencies=TRUE, quiet=TRUE, ask=FALSE)
for me this page is good
https://www.r-statistics.com/2013/03/updating-r-from-r-on-windows-using-the-installr-package/
or
another option is just install the new option and at final you put, for example in windows in my pc
.libPaths(c(
"D:/Documents/R/win-library/3.2",
"C:/Program Files/R/R-3.2.3/library",
"C:/Program Files/R/R-3.2.0/library",
"D:/Documents/R/win-library/2.15"
)
every path of last version in my case i always put the first path is "D:/Documents/R/win-library/3.2" that is fixed
and then i put the other because you do not need copy or move any packages, in my sugest just call it
linux + bash + debian + apt users:
If you're installing/upgrading to the newest version of R, then we may assume you have root permissions. (Not essential, just makes the process a lot simpler; for consistency the script below uses sudo for all installs.)
As the R packages are also installed by root, it is thus permissible to place these in /usr/local/.
The call to curl below assumes you are already interested in the sid release of R, the very latest unstable version (as required when building/checking an R package) i.e.
cat /etc/apt/sources.list | grep 'sid' || exit 1
although this could easily be replaced with a recent stable release e.g. buster.
Note that I am not using a key as is typically recommended. This is not essential, particularly if (as in the script which follows) we install packages within R itself (Rscript -e below). Also, such keys have a tendency to break/change every few years. Thus, you are of course welcome to add the following preface to the file R.sh which follows:
sudo apt-key adv --keyserver keyserver.ubuntu.com \
--recv-keys E298A3A825C0D65DFD57CBB651716619E084DAB9
The array of R packages is clearly not exhaustive but gives some examples which I personally find useful. A fresh install/upgrade with the debian package r-recommended, as below, should give the latest version of all of the the standard 'recommended' packages (e.g. survival). I believe there may be a slight lag between a CRAN release and an update to the relevant debian package. Thus, you may wish to add some of these to the array below if having the latest version of a 'recommended' R package is essential.
The debian packages installed in the process below are also neither essential (for using r-base) nor exhaustive but provide a no. of 'add-ons' which are important for a reasonable no. of R packages.
Anyway... place the following in R.sh:
sudo apt update && sudo apt --yes full-upgrade
sudo apt install --yes libappstream4 curl
### ov1 = online version; lv1 = local version (i.e. currently installed)
ov1=$(curl --silent --url https://packages.debian.org/sid/r-base |
grep 'meta name=\"Keywords\"' |
grep --only-matching '[0-9].*[0-9]') ; echo $ov1
## command -v = print a description of COMMAND similar to the `type' builtin
## && = if prior command succeeds, then do; || = if prior fails, then do
command -v 'R --version' &&
lv1=$(R --version |
grep --only-matching '[0-9\.]*[0-9]' |
## || = otherwise
head -1) ||
lv1=0
## 'lt' = less than
if dpkg --compare-versions "$lv1" 'lt' "$ov1"
then ## declare -a = indexed array
declare -a deb1=('r-base' 'r-base-dev' 'r-recommended')
for i in "${deb1[#]}"
do sudo apt install --yes "$i"
done
fi
### certain Debian packages are required by 'R' so best have these first
sudo apt install --yes ccache libcairo2-dev libxml2-dev libcurl4-openssl-dev \
libssl-dev liblapack-dev libssl-dev
declare -a pkg1=('data.table' 'ggplot2' 'knitr' 'devtools' 'roxygen2')
## installing as 'root' so these are installed in
Rscript -e ".libPaths()[1]"
for i in "${pkg1[#]}"
do sudo Rscript -e "install.packages('$i', dependencies=TRUE)"
done
### other useful additions
sudo apt install --yes libblas-dev libboost-dev libarmadillo-dev \
jags pandoc pandoc-citeproc
sudo apt update && sudo apt full-upgrade
Then execute it, e.g. assuming in directory already: source R.sh.
Installing packages (whether debian or R) one-by-one in a loop from shell is somewhat inefficient, but allows for simpler tracing of errors, IMHO. May take some time depending on the no. of R packages, so maybe simplest to let run overnight...
In linux, Now it is very simple. Just make:
install.packages("ropenblas")
ropenblas::rcompiler()

Rstudio does not start "Unable to determine real path of R script" due to previous error during compilation of R

I am using Fedora 32, I have R (3.5.1 ) within conda. I also compiled R 4.0.0 from source but since I was having another problem with Rstudio I removed this version trying to solve these issues. (With 4.0.0 I couldn't install packages because I got an 'C++11 standard requested but CXX11 is not defined' error, I made the mistake of using --with-x=no during that compiling)
Now I tried to either compile a new version (4.0.1) or get R through yum, but every time I try to reinstall Rstudio I get this error:
Unable to determine real path of R script /home/andrespara/R-4.0.0/bin/R (system error 2 (Folder doesn'exist*))
I removed ~/.config/rstudio ~/.local/share/rstudio ~/.rstudio/ every time I removed/reinstalled Rstudio. I also searched for help in the rstudio community forums. I also
I compiled 4.0.1 with this line (deactivating conda before this avoided the X11 error that I had before)
./configure \
--prefix=/opt/R/${R_VERSION} \
--enable-memory-profiling \
--enable-R-shlib \
--with-blas \
--with-lapack
I added symbolic links following these instructions https://docs.rstudio.com/resources/install-r-source/
sudo ln -s /opt/R/${R_VERSION}/bin/R /usr/local/bin/R
sudo ln -s /opt/R/${R_VERSION}/bin/Rscript /usr/local/bin/Rscript
R 4.0.1 is now correctly installed, I even used it today and installed some package the only missing link is with Rstudio and its installation that doesn't recognize it.
My question is how to either jump to another version of R working with Rstudio and get rid of that message when Rstudio starts.
I should add can't even start Rstudio because it still asks for the 'broken version' even when I tried to reinstall it several times.
I managed to solve this thanks to a colleague who found a workaround.
First running RSTUDIO_WHICH_R=$(which R) and then rstudio in the console bypassed the first error.
conda deactivate
RSTUDIO_WHICH_R=$(which R)
rstudio
Then knowing the launcher was the error and thanks to this answer https://askubuntu.com/a/112259/265501 I went to /usr/share/applications
and edited the line pointing to the useless binary with the correct one in the rstudio.desktop file found there.
Edit the file ~/.profile
export RSTUDIO_WHICH_R=$(which R)
The problem is that you've created a symlink from the wrong location. Rstudio launcher is looking for R in /home/andrespara/R-4.0.0/bin/R but it can't find it there. Your symlinks should be redirecting from that location to where you installed R like this:
sudo ln -s /opt/R/${R_VERSION}/bin/R home/andrespara/R-4.0.0/bin/R
sudo ln -s /opt/R/${R_VERSION}/bin/Rscript home/andrespara/R-4.0.0/bin/Rscript
If any of the directories in that file path don't exist, you'll have to create them as well.

Remote install of multiple R packages (with, without depends) from Ubuntu CLI

I have to perform a remote R installation on an Ubuntu 16.10 system. As part of this, I have to install specific packages on that host. I want to install these packages Rcmdr,list,ggplot2,afex,lsmeans. Since I am doing this remotely, I cannot use
sudo -i R
to first enter the R CLI and then install with install.packages(). Instead I must somehow install the packages from the Ubuntu CLI.
I found these links:
multiple R package installation with
install.packages()
R CMD INSTALL -l usage syntax to install multiple packages in
section
6.3
Use of repos parameter inside
install.packages()
However, some packages have dependencies:
The list package depends on utils and sandwich.
The Rcmdr package depends on grDevices, utils, splines, RcmdrMisc, car.
The ggplot2 package also has dependencies.
I would like to install only the packages Rcmdr,list,ggplot2 with all their dependencies. Normally, I would do it this way:
install.packages(c('Rcmdr','list','ggplot2'), dependencies=TRUE)
QUESTIONS
How do I specify the dependencies option in R CMD for one package
only? Is this the way to install them
R CMD INSTALL -l Rcmdr dependencies=TRUE, list dependencies=TRUE, \
ggplot2 dependencies=TRUE, afex, lsmeans
or this incorrect?
Also, how to I specify the repos parameter inside R CMD INSTALL -l?
EDIT
As per the first comment below, sudo is not needed above.i.e. sudo -i R can be replaced by R.
Regarding your questions:
Question 1
This may not be the best approach. Consider instead Rscript -e 'install.packages(...)' which is what R CMD INSTALL ... calls anyway. You have better control over options here. And read on...
Question 2
On all Ubuntu machines at work and home I do this via /etc/R/Rprofile.site via something like
## Example of Rprofile.site
local({
r <- getOption("repos")
r["CRAN"] <- "https://cloud.r-project.org"
r["ghrr"] <- "https://ghrr.github.io/drat"
options(repos = r)
})
where we usually add a third and network-local repo. You may just want CRAN here -- it uses the 'always-close to you' CDN administered by RStudio for the R Project and R Consortium. The ghrr drat is a helper repo I set up.
Question 3
sudo is not needed per something I add to the official Debian/Ubuntu package for R -- but you need to be a member of the group that owns /usr/local/lib/R/site-library.
Now, if I may, two more suggestions:
Littler
The r executable is available to you via sudo apt-get install r-cran-littler. I use it on the command-line; and you probably want to look into the basic install.r script and the extended install2.r. I tend to create a softlink from /usr/local/bin to the package directory for these and other (such as update.r). I have been running many (Ubuntu and Debian) machines like that for many years.
Michael Rutter repos, and Docker
We actually have about 3000 CRAN packages as binaries for Ubuntu so you could just do sudo apt-get install ... and all dependendies would get resolved. Look eg in this script of mine (which uses them on Travis) or some of the Docker files I maintain such as this one.

upgrade R 2.7.1 on Debian core procedure

My R version is 2.7.1 (on Debian) and some packages are asking for > 2.10. I cannot find updating instructions and I don't want to remove and reinstall as I have other things depending on R and I don't want to mess up. Is there an update procedure?
Closest thing to my problem is on this thread.
check out the instructions for installing from source. Its easy on a Linux box, and you can do the install in any directory you like, you dont even need superuser permissions. Once compiled you can even run R from that directory without messing up any system-installed R. As long as you give the full path to R's binary, or put the path to it in your PATH environment variable, when starting it it will work fine.
FYI
It seems that R on Debian with versions previous to 2.7.1 cannot be updated.
The current core runs from 2.7.1 up. The only way to do it is to remove the existing version.
As this was not straight forward I post it here. If you have Rapache or other things connecting to R disable them with dismode or related.
apt-get purge r-base r-base-dev
I had to do this as well
dpkg -P r-base-core
until this shows no more installed R packages
dpkg -l r-*
Then follow the instruction from http://cran.r-project.org/bin/linux/debian/, with the amendment that you should use deb instead of deb-src in /etc/apt/sources.list.
deb http://<favorite-cran-mirror>/bin/linux/debian lenny-cran/
Before installing run this and it should not say 2.7.1.
apt-cache policy r-base-dev

Painless way to install a new version of R?

Andrew Gelman recently lamented the lack of an easy upgrade process for R (probably more relevant on Windows than Linux). Does anyone have a good trick for doing the upgrade, from installing the software to copying all the settings/packages over?
This suggestion was contained in the comments and is what I've been using recently. First you install the new version, then run this in the old verion:
#--run in the old version of R
setwd("C:/Temp/")
packages <- installed.packages()[,"Package"]
save(packages, file="Rpackages")
Followed by this in the new version:
#--run in the new version
setwd("C:/Temp/")
load("Rpackages")
for (p in setdiff(packages, installed.packages()[,"Package"]))
install.packages(p)
Just for completeness, there are some ways to prevent you from having this problem. As Dirk said, save your packages in another directory on your computer.
install.packages("thepackage",lib="/path/to/directory/with/libraries")
You can change the default .Library value using the function .libPaths too
.libPaths("/path/to/directory/with/libraries")
This will put this path as a first value in the .Library variable, and will make it the default.
If you want to automate this further, you can specify this in the Rprofile.site file, which you find in the /etc/ directory of your R build. Then it will load automatically every time R loads, and you don't have to worry about that any more. You can just install and load packages from the specified directory.
Finally, I have some small code included in my Rprofile.site allowing me to reinstall all packages when I install a new R version. You just have to list them up before you update to the new R version. I do that using an .RData file containing an updated list with all packages.
library(utils)
## Check necessary packages
load("G:\Setinfo\R\packagelist.RData") # includes a vector "pkgs"
installed <- pkgs %in% installed.packages()[, 'Package']
if (length(pkgs[!installed]) >=1){
install.packages(pkgs[!installed])
}
I make the packagelist.RData by specifying .Last() in my Rprofile.site. This updates the package list if I installed some :
.Last <- function(){
pkgs <- installed.packages()[,1]
if (length(pkgs) > length(installed)){
save(pkgs,file="G:\Setinfo\R\packagelist.RData")
}
}
When I install a new R version, I just add the necessary elements to the Rprofile.site file and all packages are reinstalled. I have to adjust the Rprofile.site anyway (using sum contrasts, adding the extra code for Tinn-R, these things), so it's not really extra work. It just takes extra time installing all packages anew.
This last bit is equivalent to what is given in the original question as a solution. I just don't need to worry about getting the "installed" list first.
Again, this doesn't work flawless if you have packages that are not installed from CRAN. But this code is easily extendible to include those ones too.
If you are using Windows, you might want to use the installr package:
install.packages("installr")
require(installr)
updateR()
The best way of doing this is from the RGui system. All your packages will be transferred to the new folder and the old ones will be deleted or saved (you can pick either).
Then once you open RStudio again, it immediately recognizes that you are using an updated version. For me this worked like a charm.
More info on installr here.
Two quick suggestions:
Use Gabor's batchfiles which are said to comprise tools helping with e.g. this bulk library relocations. Caveat: I have not used them.
Don't install libraries within the 'filetree' of the installed R version. On Windows, I may put R into C:/opt/R/R-$version but place all libraries into C:/opt/R/library/ using the following snippet as it alleviates the problem in the first place:
$ cat .Renviron # this is using MSys/MinGW which looks like Cygwin
## Example .Renviron on Windows
R_LIBS="C:/opt/R/library"
The method suggested above will not completely work if you have packages that are not from CRAN. For example, a personal package or a package downloaded from a non-CRAN site.
My preferred method on Windows (upgrading 2.10.1 to 2.11.0):
Install R-2.11.0
Copy R-2.10.0/library/* to R-2.11.0/library/
Answer "no" to the prompts asking you if it is okay to overwrite.
Start R 2.11.0
Run the R command update.packages()
With respect to the solution given in the question, it might not be easy to run your older version of R if you have already installed the new version. In this case, you can still reinstall all missing packages from the previous R version as follows.
# Get names of packages in previous R version
old.packages <- list.files("/Library/Frameworks/R.framework/Versions/3.2/Resources/library")
# Install packages in the previous version.
# For each package p in previous version...
for (p in old.packages) {
# ... Only if p is not already installed
if (!(p %in% installed.packages()[,"Package"])) {
# Install p
install.packages(p)
}
}
(Note that the argument to list.files() in the first line of code should be the path to the library directory for your previous R version, where all folders of packages in the previous version are. In my current case, this is "/Library/Frameworks/R.framework/Versions/3.2/Resources/library". This will be different if your previous R version is not 3.2, or if you're on Windows.)
The if statement makes sure that a package is not installed if
It's already installed in the new R version, or
Has been installed as a dependency from a package installed in a previous iteration of the for loop.
Following Dirk's suggestion, here is some R code to do it on windows: How to easily upgrade R on windows XP
Update (15.04.11): I wrote another post on the subject, explaining how to deal with common issues of upgrading R on windows 7
Two options:
Implement my answer here
If you use R under Eclipse with StatET, open Run Configurations, click on Console tab and in the box called R snippet run after startup add this line with your choice of directory: .libPaths("C:/R/library")
I am on Windows 8 and for some weird reason, I can never install packages using my internet connections.
I generally install it using the .zip file from CRAN.
After I went from R 3.2.5 to R 3.3.1.
I simply copied the packages from
C:\Path\to\packa\R\win-library\3.2 to C:\Path\to\packa\R\win-library\3.3.
And then I restarted the R session. Worked perfectly.
I haven't checked if ALL the packages are functioning well.
But, the ones I checked are working perfectly well.
Hope this hack works for everybody.
Cheers.
The accepted answer might work if you have foresight, but I had already gotten rid of the old version so wasn't able to follow these directions.
The steps described below worked for OSX upgrading from 2.1 and 3.1.
UPDATED: To get the directory for your most recent version (instead of typing in 3.1 or 3.2) you can use the below commands. The second one converts directly to the R-variable, skipping . and .. and .DS_Store, use:
OLD=$(ls -d /Library/Frameworks/R.framework/Versions/*.* |tail -n 2 | head -n 1)Resources/library/
echo "packages = c(\"`ls $OLD | tail +4| paste -s -d ',' - | sed -E 's|,|\",\"|'g`\")" | tr -d "/"
(Add |pbcopy to the end to copy it directly to your Mac clipboard)
Then within R you can paste that variable that is generated. Once that is defined in the new version of R, you can loop through the installed packages from the instructions above...
for (p in setdiff(packages, installed.packages()[,"Package"]))
install.packages(p, dependencies=TRUE, quiet=TRUE, ask=FALSE)
for me this page is good
https://www.r-statistics.com/2013/03/updating-r-from-r-on-windows-using-the-installr-package/
or
another option is just install the new option and at final you put, for example in windows in my pc
.libPaths(c(
"D:/Documents/R/win-library/3.2",
"C:/Program Files/R/R-3.2.3/library",
"C:/Program Files/R/R-3.2.0/library",
"D:/Documents/R/win-library/2.15"
)
every path of last version in my case i always put the first path is "D:/Documents/R/win-library/3.2" that is fixed
and then i put the other because you do not need copy or move any packages, in my sugest just call it
linux + bash + debian + apt users:
If you're installing/upgrading to the newest version of R, then we may assume you have root permissions. (Not essential, just makes the process a lot simpler; for consistency the script below uses sudo for all installs.)
As the R packages are also installed by root, it is thus permissible to place these in /usr/local/.
The call to curl below assumes you are already interested in the sid release of R, the very latest unstable version (as required when building/checking an R package) i.e.
cat /etc/apt/sources.list | grep 'sid' || exit 1
although this could easily be replaced with a recent stable release e.g. buster.
Note that I am not using a key as is typically recommended. This is not essential, particularly if (as in the script which follows) we install packages within R itself (Rscript -e below). Also, such keys have a tendency to break/change every few years. Thus, you are of course welcome to add the following preface to the file R.sh which follows:
sudo apt-key adv --keyserver keyserver.ubuntu.com \
--recv-keys E298A3A825C0D65DFD57CBB651716619E084DAB9
The array of R packages is clearly not exhaustive but gives some examples which I personally find useful. A fresh install/upgrade with the debian package r-recommended, as below, should give the latest version of all of the the standard 'recommended' packages (e.g. survival). I believe there may be a slight lag between a CRAN release and an update to the relevant debian package. Thus, you may wish to add some of these to the array below if having the latest version of a 'recommended' R package is essential.
The debian packages installed in the process below are also neither essential (for using r-base) nor exhaustive but provide a no. of 'add-ons' which are important for a reasonable no. of R packages.
Anyway... place the following in R.sh:
sudo apt update && sudo apt --yes full-upgrade
sudo apt install --yes libappstream4 curl
### ov1 = online version; lv1 = local version (i.e. currently installed)
ov1=$(curl --silent --url https://packages.debian.org/sid/r-base |
grep 'meta name=\"Keywords\"' |
grep --only-matching '[0-9].*[0-9]') ; echo $ov1
## command -v = print a description of COMMAND similar to the `type' builtin
## && = if prior command succeeds, then do; || = if prior fails, then do
command -v 'R --version' &&
lv1=$(R --version |
grep --only-matching '[0-9\.]*[0-9]' |
## || = otherwise
head -1) ||
lv1=0
## 'lt' = less than
if dpkg --compare-versions "$lv1" 'lt' "$ov1"
then ## declare -a = indexed array
declare -a deb1=('r-base' 'r-base-dev' 'r-recommended')
for i in "${deb1[#]}"
do sudo apt install --yes "$i"
done
fi
### certain Debian packages are required by 'R' so best have these first
sudo apt install --yes ccache libcairo2-dev libxml2-dev libcurl4-openssl-dev \
libssl-dev liblapack-dev libssl-dev
declare -a pkg1=('data.table' 'ggplot2' 'knitr' 'devtools' 'roxygen2')
## installing as 'root' so these are installed in
Rscript -e ".libPaths()[1]"
for i in "${pkg1[#]}"
do sudo Rscript -e "install.packages('$i', dependencies=TRUE)"
done
### other useful additions
sudo apt install --yes libblas-dev libboost-dev libarmadillo-dev \
jags pandoc pandoc-citeproc
sudo apt update && sudo apt full-upgrade
Then execute it, e.g. assuming in directory already: source R.sh.
Installing packages (whether debian or R) one-by-one in a loop from shell is somewhat inefficient, but allows for simpler tracing of errors, IMHO. May take some time depending on the no. of R packages, so maybe simplest to let run overnight...
In linux, Now it is very simple. Just make:
install.packages("ropenblas")
ropenblas::rcompiler()

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