Learning Python - Mark Lutz [292]
Part V. Modules
Chapter 21. Modules: The Big Picture
This chapter begins our in-depth look at the Python module, the highest-level program organization unit, which packages program code and data for reuse. In concrete terms, modules usually correspond to Python program files (or extensions coded in external languages such as C, Java, or C#). Each file is a module, and modules import other modules to use the names they define. Modules are processed with two statements and one important function:
import
Lets a client (importer) fetch a module as a whole
from
Allows clients to fetch particular names from a module
imp.reload
Provides a way to reload a module’s code without stopping Python
Chapter 3 introduced module fundamentals, and we’ve been using them ever since. This part of the book begins by expanding on core module concepts, then moves on to explore more advanced module usage. This first chapter offers a general look at the role of modules in overall program structure. In the following chapters, we’ll dig into the coding details behind the theory.
Along the way, we’ll flesh out module details omitted so far: you’ll learn about reloads, the __name__ and __all__ attributes, package imports, relative import syntax, and so on. Because modules and classes are really just glorified namespaces, we’ll formalize namespace concepts here as well.
Why Use Modules?
In short, modules provide an easy way to organize components into a system by serving as self-contained packages of variables known as namespaces. All the names defined at the top level of a module file become attributes of the imported module object. As we saw in the last part of this book, imports give access to names in a module’s global scope. That is, the module file’s global scope morphs into the module object’s attribute namespace when it is imported. Ultimately, Python’s modules allow us to link individual files into a larger program system.
More specifically, from an abstract perspective, modules have at least three roles:
Code reuse
As discussed in Chapter 3, modules let you save code in files permanently. Unlike code you type at the Python interactive prompt, which goes away when you exit Python, code in module files is persistent—it can be reloaded and rerun as many times as needed. More to the point, modules are a place to define names, known as attributes, which may be referenced by multiple external clients.
System namespace partitioning
Modules are also the highest-level program organization unit in Python. Fundamentally, they are just packages of names. Modules seal up names into self-contained packages, which helps avoid name clashes—you can never see a name in another file, unless you explicitly import that file. In fact, everything “lives” in a module—code you execute and objects you create are always implicitly enclosed in modules. Because of that, modules are natural tools for grouping system components.
Implementing shared services or data
From an operational perspective, modules also come in handy for implementing components that are shared across a system and hence require only a single copy. For instance, if you need to provide a global object that’s used by more than one function or file, you can code it in a module that can then be imported by many clients.
For you to truly understand the role of modules in a Python system, though, we need to digress for a moment and explore the general structure of a Python program.
Python Program Architecture
So far in this book, I’ve sugarcoated some of the complexity in my descriptions of Python programs. In practice, programs usually involve more than just one file; for all but the simplest scripts, your programs will take the form of multifile systems. And even if you can get by with coding a single file yourself,