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https://github.com/melff/rkernel

Yet another R kernel for Jupyter
https://github.com/melff/rkernel

jupyter jupyter-kernel jupyter-kernels jupyter-notebook r rstats

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Yet another R kernel for Jupyter

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README 

        
# RKernel



This is a re-creation from scratch of an [*R*](http://www.r-project.org) kernel

for [*Jupyter*](http://juypter.org).



![A demonstration of interactive distribution plots](https://raw.githubusercontent.com/melff/RKernel/main/gifs/Display-demo.gif)



To install run the following lines in *R*:



```r

install.packages('RKernel', repos = c('https://melff.r-universe.dev', 'https://cloud.r-project.org'))

RKernel::installspec()

```

For dynamic help you also need to install the python package [jupyter-server-proxy](https://pypi.org/project/jupyter-server-proxy/).



This kernel differs from the already existing [*IRKernel*](http://irkernel.github.io) by:



  - Users can decide whether objects of certain classes are output via the 

    "stdout" stream - which allows using any dedicated `print()`-methods

    or via rich HTML/LaTeX output. By default the "stdout" stream is used 

    for most classes of objects. Classes can be designated for rich output 

    by calling `add_displayed_classes("some class")`. For individual objects,

    rich output can be requested using `display(some.object)`.

  - Users can decide wether an error or calling `stop()` leads to the termination

    of a notebook run or whether the succeeding notebook cells will be run.

    (This may be useful for teaching with notebooks.) Whether an error of `stop()` 

    leads to an notebook abort can be controlled by the option 

    `rkernel_stop_on_error`. 

  - Error and warning messages appear via the `stderr` stream, ordinary messages

    (created by `message()`) appear via the `stdout` stream. Consequently,

    "ordinary" messages (e.g. that appear while a package is loaded via

    `library()`) are less obtrusive, while error messages clearly stand out. 

  - Graphics can be "updated", so that e.g. `curve(gamma(x),add=TRUE)` 

    works as expected even if the 

    plot to which the curve is added has been created by code in a previous cell. 

  - It is based on the [*R6*](https://cran.r-project.org/package=R6) package

    instead of S4 reference classes.

  - Links in help pages work. To this purpose, help pages are not paged, but included

    into the notebook. This also allows to show several help pages in the notebook.

    Also `help.start()` now works. HTML help is shown using [jupyter-server-proxy](https://pypi.org/project/jupyter-server-proxy/)

  - The polling loop allows for providing services e.g. with the "htmluv"

    package.

  - It is possible to make use of the Widgets infrastructure provided by

    [*ipywidgets*](https://ipywidgets.readthedocs.io) to constructed interactive

    user interfaces. These can be used with jupyter notebooks, JupyterLab and

    [*voilà*](https://voila.readthedocs.io). *ipywidgets* are supported up to 

    version 8.0.

  - [HTML widgets](https://cran.r-project.org/package=htmlwidgets) generally

    work. However, *some* htmlwidgets (notably those created with

    [*plotly*](https://plotly.com/r/)) displayed with the setting

    `options(htmlwidgets_embed=TRUE)` however to not appear if the notebook is 

    opened in Google Chrome. 

    

  - There is also a support for virtual table display (based on the ipywidget

    infrastructure).

    

![A demonstration of some display facilities](https://raw.githubusercontent.com/melff/RKernel/main/gifs/Display-demo.gif)

   

    

Some demonstration notebooks can be found [here](https://tmphub.elff.eu/user-redirect/).

    

A widget demonstration can be found [here](https://tmphub.elff.eu/user-redirect/voila/render/RKernel-demo-interact-linear-regression.ipynb).

    

TODO:



  - [x] Add documentation

  - [x] Make HTML help work on servers

  - [ ] Add example notebooks

  - [x] Make HTML widgets work more generally