3.6.3 Magic commands

Jupyter provides a number of so-called magic commands that can be used in code cells to simplify common tasks. Magic commands are interpreted by Jupyter and, for instance, transformed into Python code before the content is passed on to the kernel for execution. This happens behind the scenes, so you will always only see the magic command in your notebook. Magic commands start with a single % symbol if they are line-oriented meaning they should be applied to the remaining content of the line, and with %% if they are cell-oriented meaning they should be applied to the rest of the cell. As a first example, you can use the magic command %lsmagic to list the available magic commands (Figure 3.11). To get the output you have to execute the cell as with any other code cell.

The %load_ext magic command can be used for loading IPython extension which can add new magic commands. The following command loads the IPython rpy2 extension. If that code gives you a long list of errors then the rpy2 package isn't installed and you will need to go back to Section 3.2 and follow the instructions there.

We recently had cases where loading rpy2 failed on some systems due to the R_HOME environment variable not being set correctly. We therefore added the first line below which you will have to adapt to point to the lib\R folder in your AC Python environment.

import os, rpy2
os.environ['R_HOME'] = r'C:\Users\username\anaconda3\envs\AC37\lib\R' # workaround for R.dll issue occurring on some systems
%load_ext rpy2.ipython

Using a ? symbol in front of a magic command will open a subwindow with the documentation of that command at the bottom of the browser window. Give it a try by executing the command

     ?%R 

in a cell. %R is a magic command from the rpy2 extension that we just loaded and the documentation will tell you that this command can be used to execute some line of R code that follows the %R and optionally pass variable values between the Python and R environments. We will use this command several times in the lesson’s walkthrough to bridge between Python and R. Keep in mind that it is just an abbreviation that will be replaced with a bunch of Python statements by Jupyter. If you would want the same code to work as a stand-alone Python script outside of Jupyter, you would have to replace the magic command by these Python statements yourself. You can also use the ? prefix to show the documentation of Python elements such as classes and functions, for instance by writing

?BeautifulSoup

or

?soup.get_text()

Give it a try and see if you understand what the documentation is telling you.