This book is about using Python, a very high-level, object-oriented, open source programming language, designed to optimize development speed. Although it is completely general-purpose, Python is often called an object-oriented scripting language, partly because of its sheer ease of use, and partly because it is commonly used to orchestrate or "glue" other software components in an application.
 Open source systems are sometimes called freeware, in that their source code is freely distributed and community-controlled. Don't let that concept fool you, though; with roughly half a million users in that community today, Python is very well supported.
If you are new to Python, chances are you've heard about the language somewhere, but are not quite sure what it is about. To help you get started, this chapter provides a nontechnical introduction to Python's features and roles. Most of it will make more sense once you have seen real Python programs, but let's first take a quick pass over the forest before wandering among the trees.
In the preface, I mentioned that Python emphasizes concepts such as quality, productivity, portability, and integration. Since these four terms summarize most of the reasons for using Python, I'd like to define them in a bit more detail:
Python makes it easy to write software that can be reused and maintained. It was deliberately designed to raise development quality expectations in the scripting world. Python's clear syntax and coherent design almost forces programmers to write readable code -- a critical feature for software that may be changed by others. The Python language really does look like it was designed, not accumulated. Python is also well tooled for modern software reuse methodologies. In fact, writing high-quality Python components that may be applied in multiple contexts is almost automatic.
Python is optimized for speed of development. It's easy to write programs fast in Python, because the interpreter handles details you must code explicitly in lower-level languages. Things like type declarations, memory management, and build procedures are nowhere to be found in Python scripts. But fast initial development is only one component of productivity. In the real world, programmers must write code both for a computer to execute and for other programmers to read and maintain. Because Python's syntax resembles executable pseudocode, it yields programs that are easy to understand long after they have been written. In addition, Python supports (but does not impose) advanced paradigms such as object-oriented programming, which further boost developer productivity and shrink development schedules.
Most Python programs run without change on almost every computer system in use today. In fact, Python programs run today on everything from IBM mainframes and Cray Supercomputers to notebook PCs and handheld PDAs. Although some platforms offer nonportable extensions, the core Python language and libraries are platform-neutral. For instance, most Python scripts developed on Linux will generally run on Windows immediately, and vice versa -- simply copy the script over. Moreover, a graphical user interface (GUI) program written with Python's standard Tkinter library will run on the X Windows system, Microsoft Windows, and the Macintosh, with native look-and-feel on each, and without modifying the program's source code at all.
Python is designed to be integrated with other tools. Programs written in Python can be easily mixed with and script (i.e., direct) other components of a system. Today, for example, Python scripts can call out to existing C and C++ libraries, talk to Java classes, integrate with COM and CORBA components, and more. In addition, programs written in other languages can just as easily run Python scripts by calling C and Java API functions, accessing Python-coded COM servers, and so on. Python is not a closed box.
In an era of increasingly short development schedules, faster machines, and heterogeneous applications, these strengths have proven to be powerful allies in both small and large development projects. Naturally, there are other aspects of Python that attract developers, such as its simple learning curve for developers and users alike, libraries of precoded tools to minimize up-front development, and completely free nature that cuts product development and deployment costs.
But Python's productivity focus is perhaps its most attractive and defining quality. As I write this, the main problem facing the software development world is not just writing programs quickly, but finding developers with time to write programs at all. Developers' time has become paramount -- much more critical than execution speed. There are simply more projects than programmers to staff them.
As a language optimized for developer productivity, Python seems to be the right answer to the questions being asked by the development world. Not only can Python developers implement systems quickly, but the resulting systems will be maintainable, portable, and easily integrated with other application components.
Part I: System Interfaces
Parallel System Tools
Larger System Examples I
Larger System Examples II
Part II: GUI Programming
Graphical User Interfaces
A Tkinter Tour, Part 1
A Tkinter Tour, Part 2
Larger GUI Examples
Part III: Internet Scripting
Larger Web Site Examples I
Larger Web Site Examples II
Advanced Internet Topics
Part IV: Assorted Topics
Databases and Persistence
Text and Language
Part V: Integration
VI: The End
Conclusion Python and the Development Cycle