Learning Python - Mark Lutz [294]
You’ll see the object.attribute notation used throughout Python scripts—most objects have useful attributes that are fetched with the “.” operator. Some are callable things like functions, and others are simple data values that give object properties (e.g., a person’s name).
The notion of importing is also completely general throughout Python. Any file can import tools from any other file. For instance, the file a.py may import b.py to call its function, but b.py might also import c.py to leverage different tools defined there. Import chains can go as deep as you like: in this example, the module a can import b, which can import c, which can import b again, and so on.
Besides serving as the highest organizational structure, modules (and module packages, described in Chapter 23) are also the highest level of code reuse in Python. Coding components in module files makes them useful in your original program, and in any other programs you may write. For instance, if after coding the program in Figure 21-1 we discover that the function b.spam is a general-purpose tool, we can reuse it in a completely different program; all we have to do is import the file b.py again from the other program’s files.
Standard Library Modules
Notice the rightmost portion of Figure 21-1. Some of the modules that your programs will import are provided by Python itself and are not files you will code.
Python automatically comes with a large collection of utility modules known as the standard library. This collection, roughly 200 modules large at last count, contains platform-independent support for common programming tasks: operating system interfaces, object persistence, text pattern matching, network and Internet scripting, GUI construction, and much more. None of these tools are part of the Python language itself, but you can use them by importing the appropriate modules on any standard Python installation. Because they are standard library modules, you can also be reasonably sure that they will be available and will work portably on most platforms on which you will run Python.
You will see a few of the standard library modules in action in this book’s examples, but for a complete look you should browse the standard Python library reference manual, available either with your Python installation (via IDLE or the Python Start button menu on Windows) or online at http://www.python.org.
Because there are so many modules, this is really the only way to get a feel for what tools are available. You can also find tutorials on Python library tools in commercial books that cover application-level programming, such as O’Reilly’s Programming Python, but the manuals are free, viewable in any web browser (they ship in HTML format), and updated each time Python is rereleased.
How Imports Work
The prior section talked about importing modules without really explaining what happens when you do so. Because imports are at the heart of program structure in Python, this section goes into more detail on the import operation to make this process less abstract.
Some C programmers like to compare the Python module import operation to a C #include, but they really shouldn’t—in Python, imports are not just textual insertions of one file into another. They are really runtime operations that perform three distinct steps the first time a program imports a given file:
Find the module’s file.
Compile it to byte code (if needed).
Run the module’s code to build the objects it defines.
To better understand module imports, we’ll explore these steps in turn. Bear in mind that all three of these steps are carried out only the first time a module is imported during a program’s execution; later imports of the same module bypass all of these steps and simply fetch the already loaded module object in memory. Technically, Python does this by storing loaded modules in a table named sys.modules and checking there at the start of an import operation. If the module is not present, a