README.md

Project Status: Suspended - Initial development has started, but there has not yet been a stable, usable release; work has been stopped for the time being but the author(s) intend on resuming work.

juno: experimental rstudio/knitr/jupyter notebook mashups

NASA's spacecraft Juno is slated to arrive at the planet Jupiter on July 4, 2016.

juno is an experimental package with utilities to incorporate the jupyter notebook into RStudio and Rmarkdown workflows. Right now it has functions for two things:

Everything here is super experimental and unstable. I have tried this only on OSX, and it almost certainly won't work on Windows because of the way I use system(). The Jupyter R kernel has just been released, and the notebook itself is currently undergoing heavy development as the IPython project splits its codebase into IPython and the language-agnostic notebook.

Comments, issues, pull requests most welcome!

Install

You need some system dependencies to get this going. Here are the links to the install instructions.

To install juno, run

install.packages('devtools')
library(devtools)
install_github('noamross/juno')

Usage

Server

To launch a Jupyter server notebook, run

library(juno)
jupyter_server('new_notebook.ipynb')

If everything is installed properly, a new server will be launched and an R notebook will be created. If the notebook already exists, it will be opened. If you use RStudio, you should see something like this:

screenshot 1

Otherwise the notebook will be launched in a browser (using browseURL()).

The notebook will be saved at whatever path you specified in the (current working directory by default). You can specify the server working directory, port, and IP in jupyter_server(), as well. See ?jupyter_server.

jupyter_server() also returns the URL of your notebook. It also should only allow one server to run per R session. If you launch a new server with different options, it will shut the current one down. If you open a new notebook, it will use the current server/kernel if it can.

Of course, all that is happening here is that jupyter_server() launches the server using system() and then passes the notebook URL to rstudioapi::viewer(). So you can roll your own if you want.

You can also kill_jupyter_server().

Conversions

juno also has rmd_to_jupyter(infile, outfile) and jupyter_to_rmd(infile, outfile), which convert between R Markdown documents and Jupyter Notebooks. The hope is that these can be fully two-way conversions. Metadata at the document and code chunk level are preserved in both directions.

Notebook outputs are not preserved in conversion to Rmd.

Python kernel notebooks will be converted to R Markdown documents with python engines, though these will not be entirely functional as knitr does not maintain Python environments between code chunks. In the other direction, the kernel will be selected based on the engine of the first code chunk.

Right now metedata for markdown cells in jupyter notebook are stored as HTML comments in R Markdown documents, but this conversion isn't two way-yet. If you have multiple, consecutive markdown cells in a notebook, they will be merged into a single markdown cell in the journey from notebook to R markdown and back. Empty markdown cells also will disappear.



noamross/juno documentation built on May 23, 2019, 9:30 p.m.