# -*- mode: org -*-
#+TITLE:     Rstudio
#+AUTHOR:    Arnaud Legrand
#+DATE: June, 2018
#+STARTUP: overview indent

* Table of Contents                                                     :TOC:
 - [[#interacting-with-gitlab][Interacting with gitlab]]
 - [[#additional-jupyter-resources-or-tricks][Additional Jupyter resources or tricks]]
     - [[#tips-and-tricks][Tips and tricks]]
     - [[#running-r-and-python-in-the-same-notebook][Running R and Python in the same notebook]]
     - [[#exporting-a-notebook][Exporting a notebook]]
 - [[#installing-jupyter-or-jupyter-hub-on-your-own-machine][Installing jupyter or jupyter hub on your own machine]]
     - [[#installing-jupyter][Installing jupyter]]
     - [[#using-r][Using R]]
     - [[#exporting-your-notebooks-with-latex][Exporting your notebooks with latex]]
     - [[#interacting-with-gitlab][Interacting with gitlab]]
     - [[#interesting-extensions][Interesting extensions]]
     - [[#installing-jupyterhub][Installing jupyterhub]]

* Interacting with gitlab
#+BEGIN_QUOTE
This section needs some love.
#+END_QUOTE

As you may have seen from the videos, we provide two buttons to sync
with gitlab. Indeed, even if you recover your files when you log back
into fun, the jupyter runs on a different machine than the gitlab
server and you need to commit your notebook every time you have made a
significant step. This is also the only way to really make it public
and to share your notebook with others.
* Additional Jupyter resources or tricks
** Tips and tricks
The following [[https://www.dataquest.io/blog/jupyter-notebook-tips-tricks-shortcuts/][webpage]] lists several Jupyter tricks (in particular, it
illustrates many =Ipython magic= commands) that should improve your
efficiency (note that this blog post is about two years old so some of
the tricks may have been integrated in the default behavior of jupyter
now).
** Running R and Python in the same notebook
The best solution to this is to install rpy2. On my machine, I have
installed the =python3-rpy2= debian package with =apt-get install=. An
other alternative consists in going through the python package manager
with 
#+begin_src python :results output :exports both
pip install rpy2
#+end_src
Then you'll be able to use both languages in the same notebook by:
1. Loading =rpy2=: 
   #+begin_src python :results output :exports both
   %load_ext rpy2.ipython
   #+end_src
2. Using the =%R= Ipython magic:
   #+begin_src python :results output :exports both
   %R 
   summary(cars)
   #+end_src
   Python objects can then even be passed to R as follows (assuming df
   is a pandas dataframe:
   #+begin_src python :results output :exports both
   %%R -i df
   plot((df)
   #+end_src
** Exporting a notebook
Obviously, you can convert to html or pdf using the using the =File >
Download as > HTML= (or =PDF=) menu option.  This can also be done from
the command line with the following command:

#+begin_src sh :results output :exports both
ipython3 nbconvert --to pdf Untitled.ipynb
#+end_src

If you want to use a specific style, then the nbconvert exporter
should be customised. This is discussed and demoed [[http://markus-beuckelmann.de/blog/customizing-nbconvert-pdf.html][here]]. We encourage
you to simply read the [[https://nbconvert.readthedocs.io/en/latest/][doc of nbconvert]]. 

Instead of going directly through LaTeX and playing too much with the
nbconvert exporter, an other option consists in exporting to Markdown
and playing with [[https://pandoc.org/][pandoc]]. Both approaches work, it's rather a matter of
taste.
* Installing jupyter or jupyter hub on your own machine
** Installing jupyter
Here is what you should install:
#+begin_src shell :results output :exports both
sudo apt-get install jupyter-notebook python3-pip python3-matplotlib python3-numpy
#+end_src

On my machine, I got the version 5.4.1:
#+begin_src shell :results output :exports both
jupyter-notebook --version
#+end_src

#+RESULTS:
: 5.4.1

The ipython notebook can then be run with the following command:
#+begin_src shell :results output :exports both
jupyter-notebook
#+end_src
** Using R
If you also want to have the R kernel in jupyter, follow [[https://github.com/IRkernel/IRkernel#installation][these
instructions]].

Alternatively, you can install =rpy2= (see the [[*Running R and Python in the same notebook][Running R and Python in
the same notebook]] section).
#+begin_src shell :results output :exports both
sudo apt-get python3-rpy2
#+end_src
** Exporting your notebooks with latex
Here is what I had to install to make sure the notebook export via
latex works:
#+begin_src shell :results output :exports both
sudo apt-get install wkhtmltopdf
sudo apt-get install texlive-xetex
#+end_src
** Interacting with gitlab
Here is our [[https://github.com/brospars/nb-git][jupyter extension that allows to git push/pull from the
notebooks]]:
#+begin_src shell :results output :exports both
jupyter nbextension install https://raw.githubusercontent.com/brospars/nb-git/master/nb-git.js
jupyter nbextension enable nb-git
#+end_src
** Interesting extensions
- [[https://stackoverflow.com/questions/33159518/collapse-cell-in-jupyter-notebook][Code folding]]
  #+begin_src shell :results output :exports both
  pip3 install jupyter_contrib_nbextensions
  # jupyter contrib nbextension install --user # not done yet
  #+end_src
- [[https://github.com/kirbs-/hide_code][Hiding code]]
  #+begin_src sh :results output :exports both
  sudo pip3 install hide_code
  sudo jupyter-nbextension  install --py hide_code
  jupyter-nbextension  enable --py hide_code
  jupyter-serverextension enable --py hide_code
  #+end_src
** Installing jupyterhub
#+BEGIN_QUOTE
Benoit may give a few hints on this.
#+END_QUOTE