A brief tour of the IPython notebook

This document will give you a brief tour of the capabilities of the IPython notebook.
You can view its contents by scrolling around, or execute each cell by typing Shift-Enter. After you conclude this brief high-level tour, you should read the accompanying notebook titled 01_notebook_introduction, which takes a more step-by-step approach to the features of the system.

The rest of the notebooks in this directory illustrate various other aspects and capabilities of the IPython notebook; some of them may require additional libraries to be executed.

NOTE: This notebook must be run from its own directory, so you must cd to this directory and then start the notebook, but do not use the --notebook-dir option to run it from another location.

The first thing you need to know is that you are still controlling the same old IPython you're used to, so things like shell aliases and magic commands still work:

In [1]:
pwd
Out[1]:
u'/Users/minrk/dev/ip/mine/docs/examples/notebooks'
In [2]:
ls

00_notebook_tour.ipynb          callbacks.ipynb                 python-logo.svg
01_notebook_introduction.ipynb  cython_extension.ipynb          rmagic_extension.ipynb
Animations_and_Progress.ipynb   display_protocol.ipynb          sympy.ipynb
Capturing Output.ipynb          formatting.ipynb                sympy_quantum_computing.ipynb
Script Magics.ipynb             octavemagic_extension.ipynb     trapezoid_rule.ipynb
animation.m4v                   progbar.ipynb
In [3]:
message = 'The IPython notebook is great!'
# note: the echo command does not run on Windows, it's a unix command.
!echo $message

The IPython notebook is great!

Plots with matplotlib

IPython adds an 'inline' matplotlib backend, which embeds any matplotlib figures into the notebook.

In [4]:
%pylab inline

Welcome to pylab, a matplotlib-based Python environment [backend: module://IPython.zmq.pylab.backend_inline].
For more information, type 'help(pylab)'.
In [5]:
x = linspace(0, 3*pi, 500)
plot(x, sin(x**2))
title('A simple chirp');

You can paste blocks of input with prompt markers, such as those from the official Python tutorial

In [6]:
>>> the_world_is_flat = 1
>>> if the_world_is_flat:
...     print "Be careful not to fall off!"

Be careful not to fall off!

Errors are shown in informative ways:

In [7]:
%run non_existent_file

ERROR: File `u'non_existent_file.py'` not found.
In [8]:
x = 1
y = 4
z = y/(1-x)

---------------------------------------------------------------------------
ZeroDivisionError                         Traceback (most recent call last)
<ipython-input-8-dc39888fd1d2> in <module>()
      1 x = 1
      2 y = 4
----> 3 z = y/(1-x)

ZeroDivisionError: integer division or modulo by zero

When IPython needs to display additional information (such as providing details on an object via x? it will automatically invoke a pager at the bottom of the screen:

In [18]:
magic

Non-blocking output of kernel

If you execute the next cell, you will see the output arriving as it is generated, not all at the end.

In [19]:
import time, sys
for i in range(8):
    print i,
    time.sleep(0.5)

0 1 2 3 4 5 6 7

Clean crash and restart

We call the low-level system libc.time routine with the wrong argument via ctypes to segfault the Python interpreter:

In [*]:
import sys
from ctypes import CDLL
# This will crash a Linux or Mac system; equivalent calls can be made on Windows
dll = 'dylib' if sys.platform == 'darwin' else '.so.6'
libc = CDLL("libc.%s" % dll) 
libc.time(-1)  # BOOM!!

Markdown cells can contain formatted text and code

You can italicize, boldface

and embed code meant for illustration instead of execution in Python:

def f(x):
    """a docstring"""
    return x**2

or other languages:

if (i=0; i<n; i++) {
  printf("hello %d\n", i);
  x += 4;
}

Courtesy of MathJax, you can include mathematical expressions both inline: $e^{i\pi} + 1 = 0$ and displayed:

$$e^x=\sum_{i=0}^\infty \frac{1}{i!}x^i$$

Rich displays: include anyting a browser can show

Note that we have an actual protocol for this, see the display_protocol notebook for further details.

Images

In [1]:
from IPython.display import Image
Image(filename='../../source/_static/logo.png')
Out[1]:

An image can also be displayed from raw data or a url

In [2]:
Image(url='http://python.org/images/python-logo.gif')
Out[2]:

SVG images are also supported out of the box (since modern browsers do a good job of rendering them):

In [3]:
from IPython.display import SVG
SVG(filename='python-logo.svg')
Out[3]:
image/svg+xml

Embedded vs Non-embedded Images

As of IPython 0.13, images are embedded by default for compatibility with QtConsole, and the ability to still be displayed offline.

Let's look at the differences:

In [4]:
# by default Image data are embedded
Embed      = Image(    'http://scienceview.berkeley.edu/view/images/newview.jpg')

# if kwarg `url` is given, the embedding is assumed to be false
SoftLinked = Image(url='http://scienceview.berkeley.edu/view/images/newview.jpg')

# In each case, embed can be specified explicitly with the `embed` kwarg
# ForceEmbed = Image(url='http://scienceview.berkeley.edu/view/images/newview.jpg', embed=True)

Today's image from a webcam at Berkeley, (at the time I created this notebook). This should also work in the Qtconsole. Drawback is that the saved notebook will be larger, but the image will still be present offline.

In [5]:
Embed
Out[5]:

Today's image from same webcam at Berkeley, (refreshed every minutes, if you reload the notebook), visible only with an active internet connexion, that should be different from the previous one. This will not work on Qtconsole. Notebook saved with this kind of image will be lighter and always reflect the current version of the source, but the image won't display offline.

In [6]:
SoftLinked
Out[6]:

Of course, if you re-run the all notebook, the two images will be the same again.

Video

And more exotic objects can also be displayed, as long as their representation supports the IPython display protocol.

For example, videos hosted externally on YouTube are easy to load (and writing a similar wrapper for other hosted content is trivial):

In [7]:
from IPython.display import YouTubeVideo
# a talk about IPython at Sage Days at U. Washington, Seattle.
# Video credit: William Stein.
YouTubeVideo('1j_HxD4iLn8')
Out[7]:

Using the nascent video capabilities of modern browsers, you may also be able to display local videos. At the moment this doesn't work very well in all browsers, so it may or may not work for you; we will continue testing this and looking for ways to make it more robust.

The following cell loads a local file called animation.m4v, encodes the raw video as base64 for http transport, and uses the HTML5 video tag to load it. On Chrome 15 it works correctly, displaying a control bar at the bottom with a play/pause button and a location slider.

In [8]:
from IPython.display import HTML
video = open("animation.m4v", "rb").read()
video_encoded = video.encode("base64")
video_tag = '<video controls alt="test" src="data:video/x-m4v;base64,{0}">'.format(video_encoded)
HTML(data=video_tag)
Out[8]:

Local Files

The above examples embed images and video from the notebook filesystem in the output areas of code cells. It is also possible to request these files directly in markdown cells if they reside in the notebook directory via relative urls prefixed with files/:

files/[subdirectory/]<filename>

For example, in the example notebook folder, we have the Python logo, addressed as:

<img src="files/python-logo.svg" />

and a video with the HTML5 video tag:

<video controls src="files/animation.m4v" />

Linking to files and directories for viewing in the browser

It is also possible to link directly to files or directories so they can be opened in the browser. This is especially convenient if you're interacting with a tool within IPython that generates HTML pages, and you'd like to easily be able to open those in a new browser window. Alternatively, if your IPython notebook server is on a remote system, creating links provides an easy way to download any files that get generated.

As we saw above, there are a bunch of .ipynb files in our current directory.

In [1]:
ls

00_notebook_tour.ipynb          formatting.ipynb
01_notebook_introduction.ipynb  octavemagic_extension.ipynb
Animations_and_Progress.ipynb   publish_data.ipynb
Capturing Output.ipynb          python-logo.svg
Script Magics.ipynb             rmagic_extension.ipynb
animation.m4v                   sympy.ipynb
cython_extension.ipynb          sympy_quantum_computing.ipynb
display_protocol.ipynb          trapezoid_rule.ipynb

If we want to create a link to one of them, we can call use the FileLink object.

In [2]:
from IPython.display import FileLink
FileLink('00_notebook_tour.ipynb')
Out[2]:
00_notebook_tour.ipynb

Alternatively, if we want to link to all of them, we can use the FileLinks object, passing '.' to indicate that we want links generated for the current working directory. Note that if there were other directories under the current directory, FileLinks would work in a recursive manner creating links to files in all sub-directories as well.

In [7]:
from IPython.display import FileLinks
FileLinks('.')
Out[7]:
00_notebook_tour.ipynb
01_notebook_introduction.ipynb
animation.m4v
Animations_and_Progress.ipynb
Capturing Output.ipynb
cython_extension.ipynb
display_protocol.ipynb
formatting.ipynb
octavemagic_extension.ipynb
publish_data.ipynb
python-logo.svg
rmagic_extension.ipynb
Script Magics.ipynb
sympy.ipynb
sympy_quantum_computing.ipynb
trapezoid_rule.ipynb

External sites

You can even embed an entire page from another site in an iframe; for example this is today's Wikipedia page for mobile users:

In [9]:
HTML('<iframe src=http://en.mobile.wikipedia.org/?useformat=mobile width=700 height=350></iframe>')
Out[9]:

Mathematics

And we also support the display of mathematical expressions typeset in LaTeX, which is rendered in the browser thanks to the MathJax library.

Note that this is different from the above examples. Above we were typing mathematical expressions in Markdown cells (along with normal text) and letting the browser render them; now we are displaying the output of a Python computation as a LaTeX expression wrapped by the Math() object so the browser renders it. The Math object will add the needed LaTeX delimiters ($$) if they are not provided:

In [10]:
from IPython.display import Math
Math(r'F(k) = \int_{-\infty}^{\infty} f(x) e^{2\pi i k} dx')
Out[10]:
$$F(k) = \int_{-\infty}^{\infty} f(x) e^{2\pi i k} dx$$

With the Latex class, you have to include the delimiters yourself. This allows you to use other LaTeX modes such as eqnarray:

In [11]:
from IPython.display import Latex
Latex(r"""\begin{eqnarray}
\nabla \times \vec{\mathbf{B}} -\, \frac1c\, \frac{\partial\vec{\mathbf{E}}}{\partial t} & = \frac{4\pi}{c}\vec{\mathbf{j}} \\
\nabla \cdot \vec{\mathbf{E}} & = 4 \pi \rho \\
\nabla \times \vec{\mathbf{E}}\, +\, \frac1c\, \frac{\partial\vec{\mathbf{B}}}{\partial t} & = \vec{\mathbf{0}} \\
\nabla \cdot \vec{\mathbf{B}} & = 0 
\end{eqnarray}""")
Out[11]:
\begin{eqnarray} \nabla \times \vec{\mathbf{B}} -\, \frac1c\, \frac{\partial\vec{\mathbf{E}}}{\partial t} & = \frac{4\pi}{c}\vec{\mathbf{j}} \\ \nabla \cdot \vec{\mathbf{E}} & = 4 \pi \rho \\ \nabla \times \vec{\mathbf{E}}\, +\, \frac1c\, \frac{\partial\vec{\mathbf{B}}}{\partial t} & = \vec{\mathbf{0}} \\ \nabla \cdot \vec{\mathbf{B}} & = 0 \end{eqnarray}

Or you can enter latex directly with the %%latex cell magic:

In [12]:
%%latex
\begin{aligned}
\nabla \times \vec{\mathbf{B}} -\, \frac1c\, \frac{\partial\vec{\mathbf{E}}}{\partial t} & = \frac{4\pi}{c}\vec{\mathbf{j}} \\
\nabla \cdot \vec{\mathbf{E}} & = 4 \pi \rho \\
\nabla \times \vec{\mathbf{E}}\, +\, \frac1c\, \frac{\partial\vec{\mathbf{B}}}{\partial t} & = \vec{\mathbf{0}} \\
\nabla \cdot \vec{\mathbf{B}} & = 0
\end{aligned}
\begin{aligned} \nabla \times \vec{\mathbf{B}} -\, \frac1c\, \frac{\partial\vec{\mathbf{E}}}{\partial t} & = \frac{4\pi}{c}\vec{\mathbf{j}} \\ \nabla \cdot \vec{\mathbf{E}} & = 4 \pi \rho \\ \nabla \times \vec{\mathbf{E}}\, +\, \frac1c\, \frac{\partial\vec{\mathbf{B}}}{\partial t} & = \vec{\mathbf{0}} \\ \nabla \cdot \vec{\mathbf{B}} & = 0 \end{aligned}

There is also a %%javascript cell magic for running javascript directly, and %%svg for manually entering SVG content.

Loading external codes

In this notebook we've kept the output saved so you can see the result, but you should run the next cell yourself (with an active internet connection).

Let's make sure we have pylab again, in case we have restarted the kernel due to the crash demo above

In [12]:
%pylab inline

Welcome to pylab, a matplotlib-based Python environment [backend: module://IPython.zmq.pylab.backend_inline].
For more information, type 'help(pylab)'.
In [15]:
%load http://matplotlib.sourceforge.net/mpl_examples/pylab_examples/integral_demo.py
In [16]:
#!/usr/bin/env python

# implement the example graphs/integral from pyx
from pylab import *
from matplotlib.patches import Polygon

def func(x):
    return (x-3)*(x-5)*(x-7)+85

ax = subplot(111)

a, b = 2, 9 # integral area
x = arange(0, 10, 0.01)
y = func(x)
plot(x, y, linewidth=1)

# make the shaded region
ix = arange(a, b, 0.01)
iy = func(ix)
verts = [(a,0)] + zip(ix,iy) + [(b,0)]
poly = Polygon(verts, facecolor='0.8', edgecolor='k')
ax.add_patch(poly)

text(0.5 * (a + b), 30,
     r"$\int_a^b f(x)\mathrm{d}x$", horizontalalignment='center',
     fontsize=20)

axis([0,10, 0, 180])
figtext(0.9, 0.05, 'x')
figtext(0.1, 0.9, 'y')
ax.set_xticks((a,b))
ax.set_xticklabels(('a','b'))
ax.set_yticks([])
show()