Hopefully some of you will end up loving this tool as much as I do. I think I originally saw it on a defcon talk, and never looked back. Perhaps it's a bit long-winded, but I wanted to be detailed. Personally, I've used it almost everyday since learning to use it, it's become an invaluable tool for working with Python. I urge anyone who loves their Python to give it a go.
What Is IPython?
In a nutshell, it's the IDLE* you always dreamed of. IPython is a richly featured replacement for the standard Python IDLE. It offers a much wider range of functionality, that the standard IDLE, which generally ships with python, sorely lacks. It's a great tool for learning Python faster than you would without it, kind of like a handy cheat-sheet that's at your fingertips. It excels as a quick Python object reference (examples below), for testing snippets of code on-the-fly and exploring new modules. But these are just a few of the many features useful to the Python scripter. In this introduction, I will show off some it's most useful features. IPython is available for Linux, Mac and Windows.
* Integrated Development & Learning Environment
I will assume here that you are using Kali linux/debian. If not, just replace the commands with the relevant ones for your distro. To install on kali, type:
apt-get install ipython
OR for the python 3.x version
apt-get install ipython3
If you're trying this on windows, already have Python installed(I will assume you do), and have some experience installing packages, you can get it with the command:
pip install ipython replace with ipython3 if you use python 3.x
Here are some links that can help with installation issues:
To start IPython, open a command prompt, and type
You should see this new prompt in the terminal:
In my examples below, I will be using Kali and the IPython for Python 2.x
Why Use IPython?
Exploring objects, a handy on-the-fly reference.
IPython makes exploring and learning more about python objects (modules, data-types, data-structures etc etc.) a breeze. See for yourself. Let's say you wanted to find out more about the
itertools module (a very useful module). IPython makes this simple:
The command takes the form
<return>, and Boom!
We get the modules docstring, and we find out that
itertools contains "Functional tools for creating and using iterators"... Great!
<Enter> or the up/down directional keys will navigate through the rest of the docstring. We can escape back to IPython by pressing 'q'.
However, it's not just modules you can do this with, you can also do this for pythons types (
dict ... etc), variables you have created and ... well pretty much any object in python... and that's pretty useful, because in python, everything is an object!
Another great feature of IPython is it's Tab-completion. We can find out what methods
itertools has by typing:
object_name. <TAB> (
<TAB> here means press the TAB key)
Now I want to know more about
itertools.permutations, again I can use
This is also useful if you can't quite remember the name of the method you want, but you do remember for instance, the letter it started with. In this instance we could type,
(remember this means hit tab) which gives you all the methods starting with that letter.
In short, typing
object_name. <TAB> will work for almost any object, displaying it's attributes and methods, if it has any. This also works on file and directory names and any objects you may have created yourself!
These are 'magic' predefined functions whose syntax is much like that of a command line call. There are two types, line magics and cell magics.
Line magics syntax takes the form
<args> is the rest of the line, without quotes or parentheses.
Cell magics syntax is
<args> are both the rest of the line, and in a separate argument, the lines that follow it. Note that we use
% twice for cell magics, once for line magics.
A brief example:
A full list of magic functions can be seen by typing
Finally, to exit IPython, simply type
exit and hit
IPython is a very useful tool for scripting with python as a quick, easy, in-depth reference, scratchpad (for testing snippets of code on the the fly) and last, but not least, for expanding your knowledge of python (very handy for exploring new modules). I hope this will prove useful, it's my first post, and I appreciate any comments or criticism. Thanks for reading!