I am using pacman to install and load the mentioned libraries. But it is throwing a dependency error and lock error in installing caret.
My main motive to use this library was to auto detect the libraries in R so that if present, load the library else install and load.
pacman::p_load(dplyr,caret,plyr) was the code that I used.
install.packages("Rcpp", dependencies = TRUE, INSTALL_opts = '--no-lock')
In place of Rcpp you can pass a variable which will change according to your iterations for every record on the list having the names of libraries to be downloaded.
It solved my issue.
The dependency error may be due to pacman::p_load() default behaviour being not to update packages that already exist in your r library.
Thus, if in this example, you are trying to install caret (which you don't have in your library) and it has a dependency Rcpp (which is already in your library because it is also a dependency for several other packages that you have already installed, or you installed it separately previously), pacman::p_load() will install caret and not update Rcpp.
This may then generate a conflict if the latest version of caret also depends on the latest version of Rcpp, but you have an old version of Rcpp.
Instead, you can change the update argument to TRUE:
# Check for, install (if necessary) and load packages:
pacman::p_load(dplyr, caret, plyr, update = TRUE)
This may not be a sufficiently targeted solution, because it will update the desired packages AND their dependencies, whereas ideally it would be better if only dependencies that failed to meet the minimum required version number for the desired packages are updated.
Related
I updated R using installr and asked to copy my library. (Even though I've never had this work, I keep hoping maybe it will someday as the package gets updated.) Opened up RStudio and, as usual, it can't find any of the packages that were in my old library. I next copied all the files from my old library into my new library, and several critical ones still don't work. For example, when I tried to load tidyverse, the message I receive is:
Error: package or namespace load failed for ‘tidyverse’: package ‘lazyeval’ was installed by an R version with different internals; it needs to be reinstalled for use with this R version.
I tried remove.packages("tidyverse") and then install.packages("tidyverse", dependencies = TRUE), and I still get the same message about the package lazyeval. I tried installing lazyeval, but then, when I go through those same steps again to try to use tidyverse, now it's lubridate that was installed by an R version with different internals.
How can I avoid this incredibly irritating and time-sucking iterative process of trying to install a package, seeing that the internals are wrong for some dependent package, installing whatever package was the problem, installing the package I actually care about, and then figuring out what other dependencies are problems?
The tidyverse package hardly contains anything: its main purpose is to get a bunch of other packages loaded. Removing it and updating it won't help update the other packages. You could do what #phago29 suggested in their comment, but an easier way is just to update everything. Run this command in an R session:
update.packages(ask = FALSE, checkBuilt = TRUE)
A few notes:
If you have admin capabilities, run as admin, and it will update your main library. If you don't, it'll install new copies in your user account.
Even though you're saying ask = FALSE, it may ask some questions about whether you can build packages from source. Answer "Yes" if your system is set up to do that, "No" if not. If you're not sure, try "Yes", and if you get install failures, run it again and say "No".)
This is likely to run for a while, so go away and have a coffee or something.
I updated R using installr and asked to copy my library. (Even though I've never had this work, I keep hoping maybe it will someday as the package gets updated.) Opened up RStudio and, as usual, it can't find any of the packages that were in my old library. I next copied all the files from my old library into my new library, and several critical ones still don't work. For example, when I tried to load tidyverse, the message I receive is:
Error: package or namespace load failed for ‘tidyverse’: package ‘lazyeval’ was installed by an R version with different internals; it needs to be reinstalled for use with this R version.
I tried remove.packages("tidyverse") and then install.packages("tidyverse", dependencies = TRUE), and I still get the same message about the package lazyeval. I tried installing lazyeval, but then, when I go through those same steps again to try to use tidyverse, now it's lubridate that was installed by an R version with different internals.
How can I avoid this incredibly irritating and time-sucking iterative process of trying to install a package, seeing that the internals are wrong for some dependent package, installing whatever package was the problem, installing the package I actually care about, and then figuring out what other dependencies are problems?
The tidyverse package hardly contains anything: its main purpose is to get a bunch of other packages loaded. Removing it and updating it won't help update the other packages. You could do what #phago29 suggested in their comment, but an easier way is just to update everything. Run this command in an R session:
update.packages(ask = FALSE, checkBuilt = TRUE)
A few notes:
If you have admin capabilities, run as admin, and it will update your main library. If you don't, it'll install new copies in your user account.
Even though you're saying ask = FALSE, it may ask some questions about whether you can build packages from source. Answer "Yes" if your system is set up to do that, "No" if not. If you're not sure, try "Yes", and if you get install failures, run it again and say "No".)
This is likely to run for a while, so go away and have a coffee or something.
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)
The package is available on this website.
http://cran.r-project.org/src/contrib/Archive/rlandscape/
When I use:
install.packages("rlandscape",
repos = "http://cran.r-project.org/src/contrib/Archive/rlandscape/",
type="source")
I get the following error:
package 'rlandscape' is not available (for R version 3.1.2)
I have tried older versions too but no luck..
The devtools package has a function that can install archived versions. Try:
library("devtools")
install_version("rlandscape",version="1.0",
repos="http://cran.r-project.org")
(You should be able to use repos=getOption("repos")["CRAN"] instead, but it looks like your repos option is slightly messed up, i.e. the URL is missing the http://.)
(The repos argument is necessary to work around what I think is a glitch in install_version, i.e. it assumes that repos is a length-1 character vector.)
This should, I think, also automatically install appropriate dependencies -- although it's a bit of a catch-22 if they are in the CRANextra repository for Windows, since that has to be suppressed in order to get install_version to work ...
It may also be the case that install_version automatically assumes that you want the package and all dependencies installed as source (not binary) installations, in which case you will need to have compilation tools installed. The rlandscape package doesn't actually have any compiled code included, but its dependencies do ...
This is an old (archived) package that is no longer supported. If you really need it, you can install it using R CMD INSTALL but you need also to install all its dependencies manually.
Installing your desired package gave me the following:
>R CMD INSTALL ~/Downloads/rlandscape_1.0.tar.gz
* installing to library ‘/Users/mohamedahmed/Rlibs’
ERROR: dependencies ‘spatstat’, ‘deldir’, ‘gWidgets’, ‘gWidgetsRGtk2’ are not available for package ‘rlandscape’
* removing ‘/Users/mohamedahmed/Rlibs/rlandscape’
I am not sure all dependencies are still available on CRAN, but it seems to be challenging task.