How to Install R-Packages Not in the Conda Repositories

How to install R packages that are not available in R-essentials?

Now I have found the documentation:

This is the documentation that explains how to generate R packages that are only available in the CRAN repository:
https://www.continuum.io/content/conda-data-science

Go to the section "Building a conda R package".

(Hint: As long as the R package is available under anaconda.org use this resource. See here: https://www.continuum.io/blog/developer/jupyter-and-conda-r)

alistaire's answer is another possibility to add R packages:

If you install packages from inside of R via the regular install.packages (from CRAN mirrors), or devtools::install_github (from GitHub), they work fine. @alistaire

How to do this:
Open your (independent) R installation, then run the following command:

install.packages("png", "/home/user/anaconda3/lib/R/library")

to add new package to the correct R library used by Jupyter, otherwise the package will be installed in /home/user/R/i686-pc-linux-gnu-library/3.2/png/libs mentioned in .libPaths() .

How to install R-packages not in the conda repositories?

In the end, I got around the rl_event_hookproblems by following the approach recommended here and symlinking anaconda's libreadline to the system one:

mv ~/anaconda3/lib/libreadline.s.6.2 ~/anaconda3/lib/libreadline.s.6.2.bak
ln -s /usr/lib/libreadline.so.6.3 ~/anaconda3/lib/libreadline.s.6.2

I am still having troubles installing some dependency heavy R-packages due to failure to load shared objects when using install.packages() from withing R. However, simpler packages work fine and I can get most of the dependency heavy packages from anacondas R-repositories.

R-Package not found for conda

This is now available through Conda Forge. Try

conda install -c conda-forge r-miceadds

Set up conda environment for R package not on CRAN, installs to wrong location

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.

How to install packages in conda that are not available in anaconda

in terminal type:

conda activate <env_name>

then:

pip install edx-dl

will work on conda env this library

Errors building R-packages for conda

Although I started out with a different problem, the final solution turned out to be the same as I posted elsewhere How to install R-packages not in the conda repositories?. I am adding it here for completeness.