Learning Python - Mark Lutz [375]
The classes in this chapter could be used as boilerplate “template” code to implement a variety of types of databases. Essentially, you can repurpose them by modifying the constructors to record different attributes and providing whatever methods are appropriate for the target application. For instance, you might use attributes such as name, address, birthday, phone, email, and so on for a contacts database, and methods appropriate for this purpose. A method named sendmail, for example, might use Python’s standard library smptlib module to send an email to one of the contacts automatically when called (see Python’s manuals or application-level books for more details on such tools). The AttrDisplay tool we wrote here could be used verbatim to print your objects, because it is intentionally generic. Most of the shelve database code here can be used to store your objects, too, with minor changes.
Chapter 28. Class Coding Details
If you haven’t quite gotten all of Python OOP yet, don’t worry; now that we’ve had a quick tour, we’re going to dig a bit deeper and study the concepts introduced earlier in further detail. In this and the following chapter, we’ll take another look at class mechanics. Here, we’re going to study classes, methods, and inheritance, formalizing and expanding on some of the coding ideas introduced in Chapter 26. Because the class is our last namespace tool, we’ll summarize Python’s namespace concepts here as well.
The next chapter continues this in-depth second pass over class mechanics by covering one specific aspect: operator overloading. Besides presenting the details, this chapter and the next also give us an opportunity to explore some larger classes than those we have studied so far.
The class Statement
Although the Python class statement may seem similar to tools in other OOP languages on the surface, on closer inspection, it is quite different from what some programmers are used to. For example, as in C++, the class statement is Python’s main OOP tool, but unlike in C++, Python’s class is not a declaration. Like a def, a class statement is an object builder, and an implicit assignment—when run, it generates a class object and stores a reference to it in the name used in the header. Also like a def, a class statement is true executable code—your class doesn’t exist until Python reaches and runs the class statement that defines it (typically while importing the module it is coded in, but not before).
General Form
class is a compound statement, with a body of indented statements typically appearing under the header. In the header, superclasses are listed in parentheses after the class name, separated by commas. Listing more than one superclass leads to multiple inheritance (which we’ll discuss more formally in Chapter 30). Here is the statement’s general form:
class data = value # Shared class data def method(self,...): # Methods self.member = value # Per-instance data Within the class statement, any assignments generate class attributes, and specially named methods overload operators; for instance, a function called __init__ is called at instance object construction time, if defined. Example As we’ve seen, classes are mostly just namespaces—that is, tools for defining names (i.e., attributes) that export data and logic to clients. So, how do you get from the class statement to a namespace? Here’s how. Just like in a module file, the statements nested in a class statement body create its attributes. When Python executes a class statement (not a call to a class), it runs all the statements in its body, from