This series completes the basic introduction to Python with Classes, demonstrating how they can be used to represent custom reuseable structures within our code, allowing us to create more complex yet easier to maintain code
In this module, we will learn how to extend the functionality of Python through custom Classes, which allow you to represent an 'object' of any kind through the combination of local variables which store information about a particular instance of the object, as well as a set of functions that define what the object can do.
Functions and Classes | |
---|---|
1 | Functions |
2 | Classes |
While Functions make our code more efficient and reuseble, they still assume that the code is meant to be executed a single time. This is typical in design applications, where code is used to create relatively short 'scripts' that are meant to be run when needed to accomplish a specific task. This type of programming is commonly referred to as procedural programming, since each passage of code defines a single procedure that is meant to be executed once and runs top to bottom until it is complete.
For more complex modern programs, however, the program does not have a single specific behavior, but runs continuously and changes based on a user's input. Instead of just using Conditionals, Loops, and Functions to control the execution of the code, such programs rely on objects that define the different functionalities of the program. As the program runs, these objects can interact with each other and change their behavior based on user input and other events that are happening within the program.
This type of programming is called object-oriented programming or OOP, and is one of the major foundations of modern programming. The key to OOP are Classes, which defines the behavior of these objects. Although we will not get too deep into OOP within this sequence, creating custom Classes can be very useful for defining custom objects with specific behaviors even if we are using a mostly procedural approach. In a later module we will see how we can use Classes and OOP to create interesting design models based on agent-based behavior.
Like Functions, Classes are structures in our code that contain passages of code that define functionality that can be used in our main script. However, while Functions define a single set of procedures, Classes can define a set of related Functions that define the behavior of a particular object, as well as a set of local variables that keep track of the state of each instance of that object. Functions defined within a Class are commonly called Methods, while variables that are local to that Class are referred to as its Properties. Together, these variables and methods define the 'behavior' of the object, and dictate how it interacts with other objects in the programming 'environment'.
Like Functions, Classes are structures that define certain functionality, but don't do anything on their own. Just like a class needs to be called within the main script to run its code, we can use Class definions to create Instances of the Class, which we can then use within our script.
Let’s think about this in everyday terms. For an animal, an example of a Method might be 'running'. Lots of things can run, so the definition of running as a Function would be general, and would not necessarily relate to who is doing the running. On the other hand, an example of a Class might be 'dog', which would have an instance of the 'running' Method, as well as other Methods related to being a dog such as 'eating' and 'barking'. It would also have a set of Properties for storing information about a given dog, such as its age, breed, or weight. Another class might be 'human', which would store different Properties, and would have its own particular version of Methods such as 'running' and 'eating' (but hopefully not 'barking').
You may not realize it, but we've already used Classes and Methods throughout this sequence. With the exception of a few basic data types such as int
, float
, and bool
, all data types we've worked with including str (string)
, list
, and dict (dictionary)
are actually implemented as Classes that come built into Python. When we created strings
or lists
we've actually been creating Instances of those Classes, and when we've run operations on them (for example calling .append
to add an item to a list), we've actually been using the Methods implemented for those Classes.
For the rest of this module we will look at how we can define custom Classes in Python and use them within our scripts to create Instances of the Class.
Let's define a very basic class to see how it works. We will use an example of a counter, which will store a value, and increment that value based on user requests:
class Counter:
count = 0
def add_to_counter(self, input_value):
self.count += input_value
def get_count(self):
return self.count
Notice we are again using the +=
shorthand to increment the value of the Instance's count
Property by the input value. To use this Class, we first need to create an Instance of it, which we will store in a variable just like any other piece of data:
my_counter = Counter()
Once we create an instance of a Class, we can run that Instance's Methods, and query it's internal Properties. Note that the general class definition is only a construct. All Properties defined within the Class only apply to a particular Instance, and the Methods can only be run as they relate to that Instance. For example:
my_counter.add_to_counter(2)
print(my_counter.get_count())
Right away, you will notice a few differences between how we define Functions and Classes. First of all, no variables are passed on the first line of the definition since the Class
keyword only defines the overall structure of the class. After the first line you will find a list of Variables which define the local Parameters of that Class, and keep track of data for individual Instances. After this you will have a collection of local Methods (remember 'Methods' are simply Functions that belong to a particular Class) that define the Class functionality. These Methods are defined just like Functions, except you see that the first input is always the keyword 'self'. This is a reference to the Instance that is calling the Method, and is always passed as the first input into each Method within a Class. This allows you to query the local Parameters of the Instance, as you can see us doing with the 'count' variable.
To call a Method within a Class, you use the name of the variable that is storing the Instance, and use the dot (.
) notation to call the Method. The dot is basically your way into the Instance and all of its data and functionality. It is also possible to use the dot syntax to query the local Parameters of the Class instance. For example, if we want to find the value of my_counter’s count
variable, we can just ask it by typing:
my_counter.count
However, this is discouraged because it reveals the true name of the local Parameters to the end user of the Class. In a production environment this would pose severe security risks, but it is considered bad practice even in private uses. Instead, you are encouraged to create special 'accessor' methods to pull Parameter values from the Instance, as we have done with the get_count()
method in the example above. Another advantage of this practice (which is called encapsulation) is that the code is easier to maintain. You are free to make any changes within the Class definition, including changing the names of the local Parameters and what they do. As long as you maintain the accessor functions and they return the expected result, you do not have to update anything in the main code that uses the Class.
As far as naming Classes goes, you can follow the same rule as naming variables or functions, however the standard practice is to capitalize every word, including the first one.
Finally, in the example above every Instance we make of the Counter will start the counter at 0. However, what if we want to specify what this count should be when we make an Instance of the Class? For this we can implement the __init__()
method (those are two underscores on each side of init
):
class Counter:
def __init__(self, initial_value):
self.count = initial_value
def add_to_counter(self, input_value):
self.count += input_value
def get_count(self):
return self.count
Now when we can create a new Instance of the counter we can pass in a starting value for the count:
my_counter = Counter(10)
my_counter.add_to_counter(2)
#this should now return 12
print(my_counter.get_count())
When the Class Instance is initialized, it will automatically run the __init__()
Method, which will utilize any variable passed into it during initialization. __init__()
is one of a series of special methods that Classes can implement to achieve different functionality. The rest of these are beyond the scope of this module, but you can find a more thorough description of these, as well as other aspects of Classes, in the Python documentation.