On Mac OS X, you have two choices for installing Python: install it, or don't install it. You probably want to install it.

Mac OS X 10.2 and later comes with a command-line version of Python preinstalled. If you are comfortable with the command line, you can use this version for the first third of the book. However, the preinstalled version does not come with an XML parser, so when you get to the XML chapter, you'll need to install the full version.

Rather than using the preinstalled version, you'll probably want to install the latest version, which also comes with a graphical interactive shell.

Ruby follows strict concepts of Object Oriented programming languages and thus has objects, methods and classes available for programming. It has all the ways by which we can handle these objects and classes in a smooth manner.

Now let’s have a look at a few basic phenomenas which are available in OOPS Ruby is also facilitated by them . The common features of OOPS are Objects, Classes and Instances, methods, Portability, Security.

If you are lucky enough to be running Debian GNU/Linux, you install Python through the apt command.

Example 1.3. Installing on Debian GNU/Linux

localhost:~$ su - Password: [enter your root password] localhost:~# apt-get install python Reading Package Lists... Done Building Dependency Tree... Done The following extra packages will be installed:

Numeric Arrays are really nice on the Python side of things. They are faster and much more efficient then lists. They tend to provide some difficulty for people when they are working with both SWIG'ed and handrolled Python/C extensions however.

While Numeric Arrays can really improve performance of some applications it often isn't enough. If you need the best performance possible it sometimes becomes necessary to rewrite parts of your Python program as C Extensions. (Numeric is a C Extension actually). For example, perhaps you want to extend Numeric by adding a new operation to it. So you'd like to write a routine that takes a Numeric array and manipulates the C array structure inside of it.

The Python language's huge object library includes a full set of features for systems programming. Here we present a couple of small Python scripts to help you manage disk space, and an object that is reused for both these scripts.