Learning Python - Mark Lutz [24]
Gaming, Images, Serial Ports, XML, Robots, and More
Python is commonly applied in more domains than can be mentioned here. For example, you can do:
Game programming and multimedia in Python with the pygame system
Serial port communication on Windows, Linux, and more with the PySerial extension
Image processing with PIL, PyOpenGL, Blender, Maya, and others
Robot control programming with the PyRo toolkit
XML parsing with the xml library package, the xmlrpclib module, and third-party extensions
Artificial intelligence programming with neural network simulators and expert system shells
Natural language analysis with the NLTK package
You can even play solitaire with the PySol program. You’ll find support for many such fields at the PyPI websites, and via web searches (search Google or http://www.python.org for links).
Many of these specific domains are largely just instances of Python’s component integration role in action again. Adding it as a frontend to libraries of components written in a compiled language such as C makes Python useful for scripting in a wide variety of domains. As a general-purpose language that supports integration, Python is widely applicable.
How Is Python Supported?
As a popular open source system, Python enjoys a large and active development community that responds to issues and develops enhancements with a speed that many commercial software developers would find remarkable (if not downright shocking). Python developers coordinate work online with a source-control system. Changes follow a formal PEP (Python Enhancement Proposal) protocol and must be accompanied by extensions to Python’s extensive regression testing system. In fact, modifying Python today is roughly as involved as changing commercial software—a far cry from Python’s early days, when an email to its creator would suffice, but a good thing given its current large user base.
The PSF (Python Software Foundation), a formal nonprofit group, organizes conferences and deals with intellectual property issues. Numerous Python conferences are held around the world; O’Reilly’s OSCON and the PSF’s PyCon are the largest. The former of these addresses multiple open source projects, and the latter is a Python-only event that has experienced strong growth in recent years. Attendance at PyCon 2008 nearly doubled from the prior year, growing from 586 attendees in 2007 to over 1,000 in 2008. This was on the heels of a 40% attendance increase in 2007, from 410 in 2006. PyCon 2009 had 943 attendees, a slight decrease from 2008, but a still very strong showing during a global recession.
What Are Python’s Technical Strengths?
Naturally, this is a developer’s question. If you don’t already have a programming background, the language in the next few sections may be a bit baffling—don’t worry, we’ll explore all of these terms in more detail as we proceed through this book. For developers, though, here is a quick introduction to some of Python’s top technical features.
It’s Object-Oriented
Python is an object-oriented language, from the ground up. Its class model supports advanced notions such as polymorphism, operator overloading, and multiple inheritance; yet, in the context of Python’s simple syntax and typing, OOP is remarkably easy to apply. In fact, if you don’t understand these terms, you’ll find they are much easier to learn with Python than with just about any other OOP language available.
Besides serving as a powerful code structuring and reuse device, Python’s OOP nature makes it ideal as a scripting tool for object-oriented systems languages such as C++ and