4.1 "Splits and Joins and Alien Invasions"

This chapter and the next continue our look at the system utilities domain in Python. They present a collection of larger Python scripts that do real systems work -- comparing and copying directory trees, splitting files, searching files and directories, testing other programs, configuring program shell environments, launching web browsers, and so on. To make this collection easier to absorb, it's been split into a two-chapter set. This chapter presents assorted Python system utility programs that illustrate typical tasks and techniques in this domain. The next chapter presents larger Python programs that focus on more advanced file and directory tree processing.

Although the main point of these two case-study chapters is to give you a feel for realistic scripts in action, the size of these examples also gives us an opportunity to see Python's support for development paradigms like OOP and reuse at work. It's really only in the context of nontrivial programs like the ones we'll meet here that such tools begin to bear tangible fruit. These chapters also emphasize the "why" of systems tools, not just the "how" -- along the way, I'll point out real-world needs met by the examples we'll study, to help you put the details in context.

One note up front: these chapters move quickly, and a few of their examples are largely just listed for independent study. Because all the scripts here are all heavily documented and use Python system tools described in the prior two chapters, I won't go through all code in detail. You should read the source code listings and experiment with these programs on your own computer, to get a better feel for how to combine system interfaces to accomplish realistic tasks. They are all available in source code form on the book's CD-ROM (view CD-ROM content online at http://examples.oreilly.com/python2), and most work on all major platforms.

I should also mention that these are programs I really use -- not examples written just for this book. In fact, they were coded over years and perform widely differing tasks, so there is no obvious common thread to connect the dots here. On the other hand, they help explain why system tools are useful in the first place, demonstrate larger development concepts that simpler examples cannot, and bear collective witness to the simplicity and portability of automating system tasks with Python. Once you've mastered the basics, you'll probably wish you had done so sooner.