Testing As You Go

This class doesn’t do much yet—it essentially just fills out the fields of a new record—but it’s a real working class. At this point we could add more code to it for more features, but we won’t do that yet. As you’ve probably begun to appreciate already, programming in Python is really a matter of incremental prototyping—you write some code, test it, write more code, test again, and so on. Because Python provides both an interactive session and nearly immediate turnaround after code changes, it’s more natural to test as you go than to write a huge amount of code to test all at once.

Before adding more features, then, let’s test what we’ve got so far by making a few instances of our class and displaying their attributes as created by the constructor. We could do this interactively, but as you’ve also probably surmised by now, interactive testing has its limits—it gets tedious to have to reimport modules and retype test cases each time you start a new testing session. More commonly, Python programmers use the interactive prompt for simple one-off tests but do more substantial testing by writing code at the bottom of the file that contains the objects to be tested, like this:

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# Add incremental self-test code

class Person:
    def __init__(self, name, job=None, pay=0):
        self.name = name
        self.job  = job
        self.pay  = pay

bob = Person('Bob Smith')                         # Test the class
sue = Person('Sue Jones', job='dev', pay=100000)  # Runs __init__ automatically
print(bob.name, bob.pay)                          # Fetch attached attributes
print(sue.name, sue.pay)                          # sue's and bob's attrs differ

Notice here that the bob object accepts the defaults for job and pay, but sue provides values explicitly. Also note how we use keyword arguments when making sue; we could pass by position instead, but the keywords may help remind us later what the data is (and they allow us to pass the arguments in any left-to-right order we like). Again, despite its unusual name, __init__ is a normal function, supporting everything you already know about functions—including both defaults and pass-by-name keyword arguments.

When this file runs as a script, the test code at the bottom makes two instances of our class and prints two attributes of each (name and pay):

C:\misc> person.py
Bob Smith 0
Sue Jones 100000

You can also type this file’s test code at Python’s interactive prompt (assuming you import the Person class there first), but coding canned tests inside the module file like this makes it much easier to rerun them in the future.

Although this is fairly simple code, it’s already demonstrating something important. Notice that bob’s name is not sue’s, and sue’s pay is not bob’s. Each is an independent record of information. Technically, bob and sue are both namespace objects—like all class instances, they each have their own independent copy of the state information created by the class. Because each instance of a class has its own set of self attributes, classes are a natural for recording information for multiple objects this way; just like built-in types, classes serve as a sort of object factory. Other Python program structures, such as functions and modules, have no such concept.