You are a programmer using Python as a scripting language, maybe for software development. Learning IPython will let you use Python interactively in a highly efficient way, for example, when exploring algorithms or analyzing data. In addition, it is the best way to be introduced to the most advanced capabilities of the platform, namely numerical computing, interactive visualization, and parallel programming.
Chapter 1, Getting Started with IPython, is a short, hands-on introduction to the key features of IPython. It will give you a broad overview of what IPython offers. All features introduced in this chapter will be covered in the subsequent chapters.
Chapter 2, Interactive Work with IPython, will show you how to use Python interactively from the IPython command-line interface, and how the numerous magic commands will help you considerably improve your productivity. This chapter will also introduce you to the IPython notebook, a modern tool for reproducible and collaborative interactive programming.
Chapter 3, Numerical Computing with IPython, contains an introduction to the numerical computing features of Numpy and Pandas, which can be conveniently used from IPython. These tools are essential as soon as you need to analyze large amounts of data, or more generally when you need to perform efficient numerical computations.
Chapter 4, Interactive Plotting and Graphical Interfaces, covers the graphical capabilities of Matplotlib, and shows how they integrate smoothly in IPython. Matplotlib is a very powerful graphical library, which allows you to either generate high-quality figures or to visualize data interactively.
Chapter 5, High-Performance and Parallel Computing, is an advanced chapter detailing various ways by which you can accelerate your code, such as parallel computing and dynamic C compilation. The former method consists in distributing tasks across cores or computers, which is particularly easy to do with IPython. The latter method lets you write code in a superset of Python (using the Cython library), which is then dynamically compiled in C for dramatic speed improvements.
Chapter 6, Customizing IPython, shows you how you can customize IPython, create new magic commands, and use custom representations in the IPython notebook.
This book assumes familiarity with the Python language. In addition, you will need to have a Python installation on your computer (Windows, OS X, or Linux). You will also need to install IPython as well as a few other external libraries. The installation procedures are detailed in Chapter 1, Getting Started with IPython.
This book is intended for Python programmers who want to learn IPython for the advanced console, the notebook, and the interactive computing facilities offered by the platform. Students, hackers, scientists, and hobbyists who are interested in interactive computing, data analysis, and visualization will also be interested in this book, but will need to learn the basics of Python first. Fortunately, Python is a very accessible language, and a lot of books, courses, and tutorials are available.
In this book, you will find a number of styles of text that distinguish between different kinds of information. Here are some examples of these styles, and an explanation of their meaning.
Code words in text are shown as follows: "For instance, the standard Unix commands pwd, ls, cd are available in IPython."
A block of code is set as follows:
print("Running script.")
x = 12
print("'x' is now equal to {0:d}.".format(x))Any command-line input or output is written as follows:
In [1]: run script.py Running script. 'x' is now equal to 12. In [2]: x Out[2]: 12
New terms and important words are shown in bold. Words that you see on the screen, in menus or dialog boxes for example, appear in the text like this: "Click on the New Notebook button at the top right of the page".
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