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
Related
I did put R on path using the .bashrc file. And yet, I do not have access to R through the command line. I have nevertheless no issues with RStudio. When I check for the R location with which R, I get /home/myself/anaconda3/bin/R. I have Ubuntu 20.04. The error message that I get is /home/myself/anaconda3/lib/R/bin/exec/R: error while loading shared libraries: libreadline.so.6: cannot open shared object file: No such file or directory. I have version R version 4.1.3 which I have installed recently. Working in JupyterLab in anaconda, I installed again R in a conda environement. Unfortunately, I get inside the conda environment the same error message.
When I try to install the missing package, I get the message:libreadline6 : PreDepends: multiarch-support but it is not installable.
I also tried to install libreadline with conda, conda install -c conda-forge m2-libreadline (as suggested on the anaconda site) as well as conda install -n base -c conda-forge libreadline.so.6. The message I get is: `PackagesNotFoundError: The following packages are not available from current channels:
libreadline.so.6
m2-libreadline`
I will highly appreciate your help. Thanks.
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.
I am still in progress to get Jupyter-Notebook and R working together on Windows 10 machine. After solving the problem with install_github() I am now facing just another issue. I am still following the official installation guide, I am stuck at step 2:
Every time I get this error - I have tried this in R GUI and RStudio, the same:
> IRkernel::installspec()
Error in IRkernel::installspec() :
jupyter-client has to be installed but “jupyter kernelspec --version” exited with code 127.
In addition: Warning message:
In system2("jupyter", c("kernelspec", "--version"), FALSE, FALSE) :
'"jupyter"' not found
My attempts so far: It was suggested here and here, that this could be a problem with the PATH variable setting, so I have added Anaconda to the PATH enviroment. I also installed the jupyter-client via the Anaconda console. No change so far. Any ideas?
This answer is based on this by #Ryan, but since the question answered was actually about a Linux based system I put it here in a Windows question:
One way to overcome the problem - if adding PATH variables to the environment doesn't work - is the following:
If Anaconda is installed and the Jupyter-Notebook with it (should be the standard install), open up the Anaconda prompt, not the Windows command prompt or the Anaconda Navigator
Look up the executable of R (not Rgui or Rstudio), it should be somewhere like C:\Program Files\R\R-3.5.1\bin and copy the path
Paste the path into the Anaconda prompt and start R by typing R
Now execute IRkernel::installspec() once again, this time there shouldn't be an error
Now you can start an R kernel within Jupyter-Notebook
You should try to open R in the terminal, if you changed directory where R il located type:
R.exe
and then run:
IRkernel::installspec()
I was having this issue trying to run Jupyter Lab on my Ubuntu 18.04 LTS headless server running in an Azure VM.
To resolve the issued, I had to navigate to /usr/bin and open R from there. It turns out that despite my path, calling R from the terminal opened the anaconda3 version in /home/<you>/anaconda3/bin/R.
Run IRkernel::installspec() from /usr/bin/R in as sudo and it should add the kernel.
If jupyter.exe is installed under c:\python36\sripts, run
"setwd("c:/python36/scripts")" on R GUI, run "IRkernel::installspec()"
Simply create a new virtual environment for R. Either using the CLI or the anaconda Navigator (best recommended, If and if you're using Anaconda).
I had Tensorflow installed with Anaconda. Now I want use it in R and I need to reinstall Tensorflow, because the note here
NOTE: You should NOT install TensorFlow with Anaconda as there are
issues with the way Anaconda builds the python shared library that
prevent dynamic linking from R.
I already tried to uninstall from Anaconda and install with pip but its came to the same place in anaconda directory. Tesorflow is working from terminal but in R shows Error: Command failed (1)
Anybody can help me to how I can solve the problem? Should I uninstall anaconda and install Tensorflow using pip?
You have several options on what to do. Probably the cleanest one is to install a system-wide python (if not installed yet) and then create a virtual environment. This basically takes your system python binaries and moves them to its own compartment where everythign is isolated from the rest, incl. anaconda. Once you are inside an activated virtual environment you can install all the necessary Python appendages for TensorFlow. Once that is done, make sure you set up a correct environmental PATH for TensorFlow from where R can reach it:
Sys.setenv(TENSORFLOW_PYTHON="/path/to/virtualenv/python/binary")
devtools::install_github("rstudio/tensorflow")
Example of the path to where you installed the virtual environment project would be, I think, something like ~/minion/medvedi/venv_medvedi/bin/python.
This is no longer an issue, the documentation was updated too.
See here:
https://github.com/rstudio/tensorflow/commit/4e1e11d6ba2fe7efe1a03356f96172dbf8db365e
With the help of Keras, we can install the TensorFlow package in R.
install_keras()
library(keras)
devtools::install_github("rstudio/keras")
install_tensorflow(package_url = "https://pypi.python.org/packages/b8/d6/af3d52dd52150ec4a6ceb7788bfeb2f62ecb6aa2d1172211c4db39b349a2/tensorflow-1.3.0rc0-cp27-cp27mu-manylinux1_x86_64.whl#md5=1cf77a2360ae2e38dd3578618eacc03b")
library(tensorflow)
Keras is a high-level neural network API for deep learning from TensorFlow Google.
my suggestion is to install anaconda and create an environment called "r-reticulate".
you can do it using anaconda navigator or
reticulate::conda_create(envname = "r-reticulate")
then to check that env detected by reticulate, use reticulate::conda_python().it must return directory of python.exe for your env.
after that you can install tensorflow by install_tensorflow(). [not working in my case]
so I install the tesnorflow from CMD.
follow these steps:
open the cmd :]
activate the r-reticulate env using conda activate r-reticulate (you may need your directory to conda directory if you did not add conda to your PATH)
use : conda install -c anaconda tensorflow
now in R, you can use TensorFlow.
for installing Keras, you can use pip install Keras. [i tried install_keras() function after the installation of tensorflow, but it ruined my TensorFlow installation also]
Eventually I found the best and fast method to do it in R:
devtools::install_github("rstudio/keras")
library(keras)
install_keras(method = "conda")
install_keras(tensorflow = "gpu")
tensorflow::install_tensorflow()
I recently installed the Anaconda3 distribution and I want to have the R and Julia Kernels available besides Python. I use windows 10.
To install IJulia I installed the Julia language and follewed the steps indicated in the IJulia page; everything went fine.
To install the R kernel I used the command conda install -c r r-essentials in the anaconda command prompt, again, no problems. I also installed R.
When I launch the notebook the only available kernel is Python, the R and Julia kernels doesn't appear in the list, I have no clue why this since I got no errors in the installation of IJulia and IRKernel. Anyone could help?
After a fresh installation of Anaconda Distribution (either 2 or 3), following steps should be performed to achieve the desired kernels (R & Julia) on your notebook.
To install R on Anaconda(2/3) Jupyter Notebook :
Open 'Anaconda Command Prompt' & execute conda update notebook to update your Jupyter notebook to the most recent version.
Then install IRkernel by conda install -c r notebook r-irkernel
Now you may open R in your command prompt by running R.exe
Install all necessary R packages using the following lines in the R console by executing :
install.packages(c('repr', 'IRdisplay', 'evaluate', 'crayon', 'pbdZMQ',
'devtools', 'uuid', 'digest'))
devtools::install_github('IRkernel/IRkernel')
Finally, make the R kernel available to your Jupyter Notebook by executing:
Install only for the current user ➡ IRkernel::installspec()
For System-wide installation(all Users) ➡ IRkernel::installspec(user = FALSE)
To install Julia on Anaconda(2/3) Jupyter Notebook :
First, download Julia version 0.4 or later and run the installer. Then run the Julia application (double-click on it); the Julia Console with a julia> prompt will appear.
Now, for the most important step, open 'Anaconda Command Prompt' & execute where jupyter to see the actual path of your Jupyter Notebook. The output will be something like "C:\Users\JohnDoe\AppData\Local\Continuum\Anaconda3\bin\jupyter.exe"
Copy the above location and go to your Julia console. Now, execute the following respectively:
ENV["JUPYTER"]="C:\\Users\\JohnDoe\\AppData\\Local\\Continuum\\Anaconda3\\bin\\jupyter.exe"
Pkg.add("IJulia")
Pkg.build("IJulia") (Optional, execute if further error occurs again.)
⬆ Notice that the backslashes have to be doubled when you type them as a Julia string. I've just assumed that the path is your Anaconda path with \bin\jupyter appended, but replace that with whatever where jupyter tells you.
After few minutes, in Julia console execute:
using IJulia
notebook()
Now, you can program Julia in your Anaconda Jupyter Notebook.
Excellent, it worked.
However, it is important to import the package first before adding it.
import Pkg; Pkg.add("IJulia")