Mastering IPython: Boost Your Python Productivity

IPython is an enhanced Python REPL, and it’s actually the core for Jupyter notebook. In short, Jupyter is an open-source web application that allows you to create and share documents containing live code, equations, visualizations, and narrative text. If you use the interactive shell a lot and you don’t know IPython, you should really check this one out!

Table of contents

IPython features

Some of the features the IPython shell offers are:

• Comprehensive object introspection.
• Input history, persistent across sessions.
• Caching of output results during a session with automatically generated references.
• Tab completion, with support for completion of python variables and keywords, filenames, and Python functions.
• Magic commands for controlling the environment and performing many tasks.
• Session logging and reloading.
• Integrated access to the pdb debugger and the Python profiler.
• A less known feature of IPython: its architecture also allows for parallel and distributed computing.

Magic commands

These are just a selection of the magic commands that are built into IPython that I think you’ll like:

• %cd — change the current working directory
• %edit — open an editor and execute the code you typed in after closing the editor
• %env — show the current environment variables
• %pip install [pkgs] — install packages without leaving the interactive shell
• %time and %timeit — time the execution of Python code

Read the full list in the documentation here.

Referencing previous input and output

Another useful feature is referencing the input and output of a previous command. In and Out are actual objects. You can use the output of the 3rd command by using Out[3]. You can re-execute the third command with In[3].

Install IPython

You probably know the drill, but just to be complete, here’s how you install IPython with pip install:

$ pip install ipython

Although it’s often better to use a virtual environment, in this case you may want to install it system-wide or for your entire user account with pip install --user.