I'm facing difficulties downloading the r package rsvg. I created first an environment with conda for the latest R version 4.0.2 following these instructions. I was able to download many other R packages & bioconductor packages without problem, however, this one produces huge pile of lines while configuring it and ends with errors downloadind its dependencies (systemfonts, stringi, stringr, gdtools, magick, svglite, knitr). My exact command is install.packages("rsvg", dependencies =T). Trying to download each of those packages produced also a tree of required dependencies (with configuration fail at the end of each).
Among the lines I noticed this error /user/include/freetype2/freetype/config/ftheader.h:3:12: fatal error x86_64-linux-gnu/freetype2/config/fthreader.h no such file or directory which make me suspect that my R installation is incopmlete or corrupted. I tested it with other R versions (e.g. R 3.6.0) yet the same error appear. Installing it on windows (Rstudio 3.6.2) also didn't work, and now I'm wondering if this package needs to be installed differently or it is system related problem? Any help would be highly appreciated
You need to create a new environment and then you can install R 4.+ in Anaconda. Follow these steps.
conda create --name r4-base
After activating r4-base run these commands
conda install -c conda-forge r-base
conda install -c conda-forge/label/gcc7 r-base
Finally, you will notice r-basa version 4 will be installed.
Thereafter, you can install any supported packages. But with this only, you won't have the ability to use it in the Jupyter notebook. You need to install install.packages('IRkernel') and Jupyter notebook as well if you want to use it. Otherwise you are good to go with R-Studio.
For Jupyter Installation and RKernel.
conda install jupyter
Then open the R console. Write in R console
install.packages('IRkernel')
IRkernel::installspec()
Congrats! You can use Notebook for Python and R.
Related
My goal is to use this package (https://github.com/tiagodc/TreeLS) but it was deprecated from CRAN (https://cran.r-project.org/web/packages/TreeLS/index.html). It requires an older version of R yet its dependencies such as the raster package require R 3.5 or up. I considered two approaches.
using R studio and changing the global options to an older version of R, but I frequently use many geospatial packages and since this package has older dependencies I didn't want to install older versions of packages I use all the time.
Create a virtual environment in Mini Conda 3 dedicated to use for this package. I choose this option because it would be self contained.
Here is the workflow so far.
conda search -c r r
conda create -n newR351 -c conda-forge r-base=3.5.1 -y
conda install -c r rtools -y
Successfully creates a conda environment called newR351 and installs r tools to that environment folder within mini conda 3.
Location of conda environment with R 3.5.1 install
C:\Users\me\Miniconda3\envs\newR351
When I try to install devtools so I can remote install TreeLS from github I get a warning with zero exit status. The devtools package installs, but it installed to my appdata folder and not my mini conda environment.
conda install -c r devtools -y
The downloaded source packages are in
'C:\Users\me\AppData\Local\Temp\RtmpYByvp8\downloaded_packages'
How can I access devtools on my conda environment newR351? Do I need to build a cran skeleton? When I activate R in this environment and try to load the devtools library I get this.
(newR351) C:\Users\me>R
R version 3.5.1 (2018-07-02) -- "Feather Spray"
Copyright (C) 2018 The R Foundation for Statistical Computing
Platform: x86_64-w64-mingw32/x64 (64-bit)
...
>library(devtools)
Error in library(devtools) : there is no package called 'devtools'
What are best practices for creating an environment specific for an older R package? Anyone else use TreeLS?
First, the devtools isn't showing up because R packages in Conda repositories are conventionally prefixed with "r-", so installing conda install r-devtools should do the trick. However, I don't think Conda is the best strategy here.
Below R version 3.6, the Conda package coverage for R packages is rather poor. Also, installing non-Conda packages that require compilation into a Conda R environment is a pain and generally doesn't work out-of-the-box in my experience. Plus, not only does the TreeLS require compilation, but it has dependencies that are not Conda packages which require compilation. I would avoid this.
Option 1 is feasible. R allows multiple installations, and with manipulating environment variables (I think RSTUDIO_WHICH_R, R_LIBS are the pertinent ones) one can switch between them.
However, were this my situation, I'd spin up a docker container, probably rocker/rstudio:3.5 and use that for this project. Since the underlying image is Linux, it'll take awhile to compile, but you can version it at that point and then always have that available to spin up. This avoids having to muck around with any system settings and should be mostly straight-forward installing.
I used to work in R 3.4.0 version. Hovewer, this version doesn't support such packages as keras and tensorflow.
I was adviced to upgrade my R version to the newest one.
I downloaded the most recent R version 4.0.2 from the official site, then ran the following code:
install.packages("keras")
library(keras)
install_keras()
And got the following error:
Error in install_keras() :
You should call install_keras() only in a fresh R session that has not yet initialized Keras and TensorFlow (this is to avoid DLL in use errors during installation)
After this, when I tried to quit R session by q() , I faced the following error:
Error: option error has NULL value
Error: no more error handlers available (recursive errors?); invoking 'abort' restart
Error: option error has NULL value
I've never faced such an error before. When I used old R version, I typed q() and then had to choose between y and n. No errors appeared.
I'm asking you to help to to solve this problem.
You need to create a new environment and then you can install R 4.+ in Anaconda. Follow these steps.
conda create --name r4-base
After activating r4-base run these commands
conda activate r4-base
conda install -c conda-forge r-base
conda install -c conda-forge/label/gcc7 r-base
Finally, you will notice r-basa version 4 will be installed.
Thereafter, you can install any supported packages. But with this only, you won't have the ability to use it in the Jupyter notebook. You need to install install.packages('IRkernel') and Jupyter notebook as well if you want to use it. Otherwise you are good to go with R-Studio.
For Jupyter Installation and RKernel.
conda install jupyter
Then open the R console. Write in R console
install.packages('IRkernel')
IRkernel::installspec()
Congrats! You can use Notebook for Python and R.
Find the location of R.exe on your computer. In my computer, this executable is at
C:\Program Files\R\R-3.4.3\bin
Open another Anaconda Prompt as Administrator and change directories to wherever R.exe is on your computer with cd file path. On my computer, it’s cd C:\Program Files\R\R-3.4.3\bin, but it might be different for you.
Then run R from within Anaconda Prompt in Admin mode with R.exe
You’ll notice that you’re in an R session. From here, run the following three commands into the terminal.
install.packages("devtools")
devtools::install_github("IRkernel/IRkernel")
IRkernel::installspec()
In order, they (1) install the devtools package which gets you the install_github() function, (2) install the IR Kernel from GitHub, and (3) tell Jupyter where to find the IR Kernel.
Open Jupyter notebook and enjoy your new R kernel!
Get more information here
#Rheatey Bash works perfectly. but i was facing python.exe this program cant start because api-ms-win-core-path-l1-1-0.dll python system error. this is a problem running on windows 7 but i resolved this issue by installing the kernel following https://richpauloo.github.io/2018-05-16-Installing-the-R-kernel-in-Jupyter-Lab/ and it works fine
I'm getting a little bit crazy with this issue. I'm trying to install an R package using conda in my environment (python 2.7) in my home on a cluster (i.e. without root permissions). I firstly installed R in my env using:
conda install -c r r=3.4
Then:
conda install -c conda-forge python-igraph
(because igraph is required by my library of interest)
and finally:
conda install -c conda-forge r-diffusionmap
Unfortunately when I launch R the following message appears:
Error: package or namespace load failed for 'RevoUtilsMath': .onLoad
failed in loadNamespace() for 'RevoUtilsMath', details: call: NULL
error: Remove Microsoft R and then re-install. Be sure to select MKL
libraries as an install option.
During startup - Warning message:
package 'RevoUtils' was built under R version 3.4.3
What does it mean? How can I solve this?
Thank you in advance
I had this same issue after I installed some libraries (Rcpp included) in my root R, but not my conda environment (which screwed up conda). This would cause kernel death anytime a jupyter notebook running R was even opened.
The fix for me was:
Uninstall Anaconda3
Reinstall Anaconda3
Reinstall all the libraries I needed (mostly just Bioconductor in R)
A few other issues popped up, like package inconsistencies, but I dealt with those as described here.
All R packages on conda-forge (or Bioconda) are compiled against one single version or R for each new release branch (usually starting from patch 1, so 3.x.1, except for 3.4.3). This is due to ABI incompatibility problems.
Also note that defaults and conda-forge channels are (where) not binary compatible (although now they should be). And that since 2018 the default anaconda channel is distributing Microsoft R Open as default R, whether all packages from conda-forge should be preferably used with R from conda-forge.
You should be able to solve this issue by installing R using conda install -c conda-forge r-base.
the same error information for me when I open R for run code in ubuntu platform(18.4), and there is no other useful methods to solve it.My R version is 3.4.3.enter image description here
I am trying to run R code in Jupyter and the R Kernel was added. Most of the time, packages can be installed successfully. However, some of the packages, such as RCurl and ggmap, would got error while installing.
Example:
install.packages("RCurl")
Warning message in install.packages("RCurl"):
“installation of package ‘RCurl’ had non-zero exit status”Updating HTML index of packages in '.Library'
Making 'packages.html' ... done
What should I do?
Try to specify CRAN as repository in your install.packages statement when installing RCurl and ggmap. For example:
install.packages("RCurl", repos='http://cran.us.r-project.org')
This Stack Overflow post on installing R packages through Anaconda/Jupyter beyond those included in R essential provides more detail.
(Side note: I had encountered the same issue when trying to install R packages on computer clusters. This solution worked for me.)
use conda comment:
conda install r-RCurl
I kept getting the non-zero exit status when trying to install packages with Jupyter notebook with R kernel and was failing because of multiple dependencies when wanting to install a package. I am not an expert in any of these so please forgive me if I make an error in explaining or if it is a non-issue for you but please feel free to comment to clear things out. I just want to share my success story so hopefully it can help someone else: I am working on a MacBook Pro. Here are the information I get when I run R.version() on my jupyter notebook with R kernel:
$platform 'x86_64-conda_cos6-linux-gnu'
$arch 'x86_64'
$os 'linux-gnu'
$system 'x86_64, linux-gnu'
$language 'R'
$version.string 'R version 3.6.1 (2019-07-05)'
These are the steps to take to fix the issue:
Go to https://anaconda.org/
Search the package name that you are trying to install
Copy the one line that is given to install the package, it should be something like:
Conda install -c r r-caret #conda install -c r r-package_name
NOTE: sometimes during installing packages, you’re asked whether or not you want to continue, so add --y at the end of the above statement to continue, so something like this
Conda install -c r r-caret --y
(I will always add it just to be on the safe side)
Click on the new launcher (+ icon) to create a new notebook with PySpark (once opened it has .ipynp extension)
On the first cell paste the copied line from step 2 and run
Once done, restart the kernel on the current notebook
Restart the kernel on your other notebook with R kernel
Run library(package_name) on your notebook with R kernel (e.x. library(caret))
install.packages("Hmisc", .libPaths(), repos='http://cran.us.r-project.org')
This command will install the packagae in the conda
"/home/user/anaconda3/lib/R/library" and use the cran r repository as source.
Add path in Anaconda
As per this answer,
one can also add additional paths in anaconda to load libraries from (for eg., the location where R studio saves the user-installed packages) with
.libPaths( c( .libPaths(), "~/userLibrary") )
For example, the following worked for me:
In Anaconda :
.libPaths( c( .libPaths(), "C:\Users\name\Documents\R\win-library\3.5") )
When I tried to add anaconda's library path to RStudio, it resulted in errors (The procedure entry point MARK_NOT_MUTABLE could not be located in the dynamic link library << arose 4 times in succession) after installation of a package, though the package seemed to load.
Replace name with your local user folder name
Add/change path in RStudio
A useful link to make changes in default user-installed library paths :
https://www.accelebrate.com/library/how-to-articles/r-rstudio-library
To find out where a package has been installed:
find.package('package_name')
The directions nobody else supplied worked for me, but I found this guide, and it worked. Spent way too much time trying all these when I just needed a few simple commands. https://developers.refinitiv.com/en/article-catalog/article/setup-jupyter-notebook-r
I already had R and python installed, so I skipped to step 3. The only seems to mention windows, but it worked for me on mac as well. After following them I was able to install the packages using install.packages("dplyr", repos = "http://cran.us.r-project.org") in a cell in jupyter.
You have to create a directory in which your package will be and do for eg:
install.packages('ggplot2',loc='your directory')
First Step: You can install the IRkernel packages by running the following command in an R console:install.packages('IRkernel')
Second Step: You will have to make Jupyter see the newly installed R kernel by installing a kernel spec. To install system-wide, set user to False in the installspec command IRkernel::installspec(user = FALSE)
Setup Jupyter Notebook for R
When I go File-New File-R Notebook, it tells me to install some packages, but then it fails giving me this message:
Notebook Creation Failed:
"One of more packages required for R Notebook creation were not installed"
I'm trying to install those packages manually, but the package installation window disappears so quickly that I can't even see which ones I should install.
I googled it around, but couldn't fine any resource.
Can anyone help me with this?
Maybe at least provide a list of packages required to run R Notebook?
R notebooks are actually not created with a package named either RNotebook or notebook or anything similar but rather with the rmarkdown package, and it needs to be a current version. So the command would be:
install.packages("rmarkdown", dependencies=TRUE) # needs to be >= version 1.3
Then your pulldown menu selections should succeed in a current version of RStudio. .... at least that is if you have the system requirements listed in the CRAN webpage:
SystemRequirements: pandoc (>= 1.12.3) - http://pandoc.org
This worked for me:
Install latest version of R from cran website
Start RStudio pointing to this version of R.
On Mac set env variable as show below and start RStudio from terminal
Then "Install Package" in RStudio for "markdown" and other ppackages will work properly installing latest required packages to open notebook
➜ export RSTUDIO_WHICH_R=/usr/local/bin/R
Don't press the error message, and read whatever you can from the installation popup under it. In my case the last message was that it has problems compiling "digest". I installed "digest" manually (install.packages("digest",type = "binary")). Then it all worked.
Mac, R version 3.6, Rstudio desktop 1.2.
I had exactly the same problem. By reading the error logs, I found g++ command not found. So just installed it and it worked fine next time I've tried.
I faced the same problem. I am using the latest version of R and RStudio and all of the installed packages are up-to-date.
Now, talking about the error in installation of packages. Follow the steps below and you will have R Notebook up and running:
Run the command
install.packages("rmarkdown", dependencies=TRUE)
You will observe several messages on the console during installation. Browse through them and jot the ones where there is ERROR in installation of some other dependent package. In my case, it was 'backports'. The error message will be like this:
ERROR: compilation failed for package 'backports'
It can be different in your case but the point is to note down the name of the package that is facing compilation issues. Use an editor(npp) to save the name of the package.
Once you get the name of the package, execute the following command:
install.packages("backports", type="binary")
After successful execution of the above command, go to File drop down and select R Markdown. Go with auto installation of the rmarkdown and rprojroot packages. They will be successfully installed and you can now use R Notebook
Let us know if this solution worked for you.
I just found the answer myself so I'm posting.
I guess there was something wrong with the server.
I went into tools-global options-packages and chose different CRAN mirror, then it worked.
UPDATE YOUR VERSION OF R - that was my solution, I had the same problem.
( First two commands ensure you get the MOST RECENT version of R which I found on a Digital Ocean page)
$ sudo apt-key adv --keyserver keyserver.ubuntu.com --recv-keys E298A3A825C0D65DFD57CBB651716619E084DAB9
$ sudo add-apt-repository 'deb [arch=amd64,i386] https://cran.rstudio.com/bin/linux/ubuntu xenial/'
$ sudo apt-get update
$ sudo apt-get install r-base
WITHOUT the first two lines I ended up with R version 3.2.3 (2015-12-10) -- "Wooden Christmas-Tree"
WITH the first two lines I got R version 3.4.4 (2018-03-15) -- "Someone to Lean On"
After reinstalling R Studio, the Files -> RMarkdown was able to install all those subpackages and WORK. Hurray!