The material in this document is taken from Appendix H.1 in the book *A Primer on Scientific Programming with Python*, 4th edition, by the same author, published by Springer, 2014.

The IPython notebook is a splendid interactive tool for doing science,
but it can also be used as a platform for developing Python code.
You can either run it locally on your computer or in a web service
like SageMathCloud or Wakari. Installation on your computer
is trivial on Ubuntu, just `sudo apt-get install ipython-notebook`

, and
also on Windows and Mac by
using Anaconda or Enthought Canopy for the Python installation.

The interface to the notebook is a web browser: you write all the code and see all the results in the browser window. There are excellent YouTube videos on how to use the IPython notebook, so here we provide a very quick "step zero" to get anyone started.

Start the IPython notebook locally by the command `ipython notebook`

or go to SageMathCloud or Wakari as described above.
The default input area is a *cell* for Python code.
Type

```
g = 9.81
v0 = 5
t = 0.6
y = v0*t - 0.5*g*t**2
```

in a cell and *run the cell* by clicking on *Run Selected* (notebook running
locally on your machine)
or on the "play" button (notebook running in the cloud).
This action will execute the Python code and initialize the
variables `g`

, `v0`

, `t`

, and `y`

. You can then write `print y`

in a
new cell, execute that cell, and see the output of this statement in
the browser. It is easy to go back to a cell, edit the code, and
re-execute it.

To download the notebook to your computer, choose the
*File - Download as* menu and select the type of file
to be downloaded: the original notebook format (`.ipynb`

file
extension) or a plain Python program version of the notebook
(`.py`

file extension).

The real strength of IPython notebooks arises when you want to write
a report to document how a problem can be explored and solved.
As a teaser, open a new notebook, click in the first cell, and choose
*Markdown* as format (notebook running locally) or switch from *Code*
to *Markdown* in the pull-down menu (notebook in the cloud). The cell
is now a text field where you can write text with Markdown syntax. Mathematics can be entered
as LaTeX code. Try some text with inline mathematics and an equation on
a separate line:

```
Plot the curve $y=f(x)$, where
$$
f(x) = e^{-x}\sin (2\pi x),\quad x\in [0, 4]
$$
```

Execute the cell and you will see nicely typeset mathematics in the browser. In the new cell, add some code to plot \( f(x) \):

```
import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline # make plots inline in the notebook
x = np.linspace(0, 4, 101)
y = np.exp(-x)*np.sin(2*pi*x)
plt.plot(x, y, 'b-')
plt.xlabel('x'); plt.ylabel('y')
```

Executing these statements results in a plot in the browser, see
Figure 2. It was popular to
start the notebook by `ipython notebook --pylab`

to import
everything from `numpy`

and `matplotlib.pyplot`

and make
all plots inline, but the `--pylab`

option is now
officially discouraged.
If you want the notebook to behave more as MATLAB and not use
the `np`

and `plt`

prefix, you can instead of the first three
lines above write `%pylab`

.

- Python Programming Language.
`http://python.org`. -
**T. E. Oliphant et al.**. NumPy Array Processing Package for Python,`http://www.numpy.org`. -
**T. E. Oliphant**. Python for Scientific Computing,*Computing in Science & Engineering*, 9, 2007. -
**J. D. Hunter et al.**. Matplotlib: Software Package for 2D Graphics,`http://matplotlib.org/`. -
**J. D. Hunter**. Matplotlib: a 2D Graphics Environment,*Computing in Science & Engineering*, 9, 2007. -
**F. Perez, B. E. Granger et al.**. IPython Software Package for Interactive Scientific Computing,`http://ipython.org/`. -
**F. Perez and B. E. Granger**. IPython: a System for Interactive Scientific Computing,*Computing in Science & Engineering*, 9, 2007. - ScientificPython Software Package.
`http://starship.python.net/crew/hinsen`. -
**O. Certik et al.**. SymPy: Python library for symbolic mathematics,`http://sympy.org`. -
**E. Jones, T. E. Oliphant, P. Peterson et al.**. SciPy Scientific Computing Library for Python,`http://scipy.org`.