Native Rmarkdown kernel for Jupyter ![b-CI]
LICENSE: MIT
- Jupyter.
- A current R installation.
This package is not available on CRAN. You can install with remotes:
remote::instal_github('facebookexperimental/Rmdkernel')
Rmdkernel::installspec() # to register the kernel in the current R installation
Per default Rmdkernel::installspec()
will install a kernel with the name “rmarkdown” and a
display name of “Rmarkdown”. Multiple calls will overwrite the kernel with a kernel spec pointing to the last
R interpreter you called that commands from. You can install kernels for multiple versions of R
by supplying a name
and displayname
argument to the installspec()
call (You still need to
install these packages in all interpreters you want to run as a jupyter kernel!):
# in R 3.3
Rmdkernel::installspec(name = 'rmd33', displayname = 'R 3.3')
# in R 3.2
Rmdkernel::installspec(name = 'rmd32', displayname = 'R 3.2')
By default, it installs the kernel per-user. To install system-wide,
use user = FALSE
. To install in the sys.prefix
of the currently
detected jupyter
command line utility, use sys_prefix = TRUE
.
Now both R versions are available as an Rmarkdown kernel in the notebook.
If you have Jupyter installed, you can create a notebook using Rmdkernel from the dropdown menu.
You can also start other interfaces with an R kernel:
# “rmarkdown” is the kernel name installed by the above `Rmdkernel::installspec()`
# change if you used a different name!
jupyter qtconsole --kernel=rmarkdown
jupyter console --kernel=rmarkdown
The Rmdkernel does not have any Python dependencies whatsoever, and
does not know anything about any other Jupyter/Python installations
you may have. It only requires the jupyter
command to be available
on $PATH
. To install the kernel, it prepares a kernelspec directory
(containing kernel.json
and so on), and passes it to the command
line jupyter kernelspec install [options] prepared_kernel_dir/
,
where options such as --name
, --user
, --prefix
, and
--sys-prefix
are given based on the options.