Python 3 Object Oriented Programming: If you feel it’s time you learned object-oriented programming techniques, this is the perfect book for you. Clearly written with practical exercises, it’s the painless way to learn how to harness the power of OOP in Python.

We don't have to write much Python code to realize that Python is a very "clean" language. When we want to do something, we just do it, without having to go through a lot of setup. The ubiquitous, "hello world" in Python, as you've likely seen, is only one line.

Similarly, the simplest class in Python 3 looks like this:

class MyFirstClass:
    pass

There's our first object-oriented program! The class definition starts with the class keyword. This is followed by a name (of our choice) identifying the class, and is terminated with a colon.

The class definition line is followed by the class contents...

Now that we know how to create classes and instantiate objects, it is time to think about organizing them. For small programs, we can just put all our classes into one file and put some code at the end of the file to start them interacting. However, as our projects grow, it can become difficult to find one class that needs to be edited among the many classes we've defined. This is where modules come in. Modules are simply Python files, nothing more. The single file in our small program is a module. Two Python files are two modules. If we have two files in the same folder, we can load a class from one module for use in the other module.

For example, if we are building an e-commerce system, we will likely be storing a lot of data in a database. We can put all the classes and functions related to database access into a separate file (we'll call it something sensible: database.py). Then our other modules (for example: customer models, product information, and inventory) can...

Most object-oriented programming languages have a concept of "access control". This is related to abstraction. Some attributes and methods on an object are marked "private", meaning only that object can access them. Others are marked "protected", meaning only that class and any subclasses have access. The rest are "public", meaning any other object is allowed to access them.

Python doesn't do that. Python doesn't really believe in enforcing laws that might someday get in your way. Instead, it provides unenforced guidelines and best practices. Technically, all methods and attributes on a class are publicly available. If we want to suggest that a method should not be used publicly, we can put a note in docstrings indicating if a method is meant for internal use only, (preferably with an explanation of how the public-facing API works!).

By convention, we can also prefix an attribute or method with an underscore character: _. Most Python programmers will interpret this...

To tie it all together, let's build a simple command-line notebook application. This is a fairly simple task, so we won't be experimenting with multiple packages. We will, however, see common usage of classes, functions, methods, and docstrings.

Let's start with a quick analysis: Notes are short memos stored in a notebook. Each note should record the day it was written and can have tags added for easy querying. It should be possible to modify notes. We also need to be able to search for notes. All of this should be done from the command-line.

The obvious object is the Note. Less obvious is a Notebook container object. Tags and dates also seem to be objects, but we can use dates from Python's standard library and a comma-separated string for tags. To avoid complexity at this point, let's not define separate classes for these objects.

Note objects have attributes for the memo itself, tags, and a creation_date. Each note will also need a unique integer id, so that users can select them...

Write some object-oriented code. The goal is to use the principles and syntax you learned in this chapter to ensure you can use it, instead of just reading about it. If you've been working on a Python project, go back over it and see if there are some objects you can create and add properties or methods to. If it's large, try dividing it into a few modules or even packages and play with the syntax.

If you don't have such a project, try starting a new one. It doesn't have to be something you intend to finish, just stub out some basic design parts. You don't need to fully implement everything, often just a print("this method will do something") is all you need to get the overall design in place. This is called top-down design, when you work out the different interactions and describe how they should work before actually implementing what they do. The converse, bottom-up design, implements details first and then ties them all together. Both patterns are useful at different times, but...

In this chapter, we learned how simple it is to create classes and assign properties and methods in Python. We also covered access control and different levels of scope (packages, modules, classes, and functions). In particular, we covered:

In the next chapter, we'll learn how to share implementation using inheritance.