Python Classes and Objects
Classes and objects are the two main aspects of object-oriented programming.
A class is the blueprint from which individual objects are created. In the real world, for example, there may be thousands of cars in existence, all of the same make and model.
Each car was built from the same set of blueprints and therefore contains the same components. In object-oriented terms, we say that your car is an instance (object) of the class Car.
Did you know?
In Python, everything is an object – integers, strings, lists, functions, even classes themselves.
However, Python hides the object machinery with the help of special syntax.
For example, when you type
num = 42, Python actually creates a new object of type integer with the value 42, and assign its reference to the name
Create a Class
To create your own custom object in Python, you first need to define a class, using the keyword
Suppose you want to create objects to represent information about cars. Each object will represent a single car. You’ll first need to define a class called Car.
Here’s the simplest possible class (an empty one):
class Car: pass
pass statement is used to indicate that this class is empty.
The __init__() Method
__init__() is the special method that initializes an individual object. This method runs automatically each time an object of a class is created.
__init__() method is generally used to perform operations that are necessary before the object is created.
class Car: # initializer def __init__(self): pass
When you define
__init__() in a class definition, its first parameter should be
The self Parameter
self parameter refers to the individual object itself. It is used to fetch or set attributes of the particular instance.
This parameter doesn’t have to be called
self, you can call it whatever you want, but it is standard practice, and you should probably stick with it.
self should always be the first parameter of any method in the class, even if the method does not use it.
Every class you write in Python has two basic features: attributes and methods.
Attributes are the individual things that differentiate one object from another. They determine the appearance, state, or other qualities of that object.
In our case, the ‘Car’ class might have the following attributes:
- Style: Sedan, SUV, Coupe
- Color: Silver, Black, White
- Wheels: Four
Attributes are defined in classes by variables, and each object can have its own values for those variables.
There are two types of attributes: Instance attributes and Class attributes.
The instance attribute is a variable that is unique to each object (instance). Every object of that class has its own copy of that variable. Any changes made to the variable don’t reflect in other objects of that class.
In the case of our Car() class, each car has a specific color and style.
# A class with two instance attributes class Car: # initializer with instance attributes def __init__(self, color, style): self.color = color self.style = style
The class attribute is a variable that is same for all objects. And there’s only one copy of that variable that is shared with all objects. Any changes made to that variable will reflect in all other objects.
In the case of our Car() class, each car has 4 wheels.
# A class with one class attribute class Car: # class attribute wheels = 4 # initializer with instance attributes def __init__(self, color, style): self.color = color self.style = style
So while each car has a unique style and color, every car will have 4 wheels.
Create an Object
You create an object of a class by calling the class name and passing arguments as if it were a function.
# Create an object from the 'Car' class by passing style and color class Car: # class attribute wheels = 4 # initializer with instance attributes def __init__(self, color, style): self.color = color self.style = style c = Car('Sedan', 'Black')
Here, we created a new object from the Car class by passing strings for the style and color parameters. But, we didn’t pass in the
This is because, when you create a new object, Python automatically determines what self is (our newly-created object in this case) and passes it to the
Access and Modify Attributes
The attributes of an instance are accessed and assigned to by using dot
# Access and modify attributes of an object class Car: # class attribute wheels = 4 # initializer with instance attributes def __init__(self, color, style): self.color = color self.style = style c = Car('Black', 'Sedan') # Access attributes print(c.style) # Prints Sedan print(c.color) # Prints Black # Modify attribute c.style = 'SUV' print(c.style) # Prints SUV
Methods determine what type of functionality a class has, how it handles its data, and its overall behavior. Without methods, a class would simply be a structure.
In our case, the ‘Car’ class might have the following methods:
- Change color
- Start engine
- Stop engine
- Change gear
Just as there are instance and class attributes, there are also instance and class methods.
Instance methods operate on an instance of a class; whereas class methods operate on the class itself.
Instance methods are nothing but functions defined inside a class that operates on instances of that class.
Now let’s add some methods to the class.
- showDescription() method: to print the current values of all the instance attributes
- changeColor() method: to change the value of ‘color’ attribute
class Car: # class attribute wheels = 4 # initializer / instance attributes def __init__(self, color, style): self.color = color self.style = style # method 1 def showDescription(self): print("This car is a", self.color, self.style) # method 2 def changeColor(self, color): self.color = color c = Car('Black', 'Sedan') # call method 1 c.showDescription() # Prints This car is a Black Sedan # call method 2 and set color c.changeColor('White') c.showDescription() # Prints This car is a White Sedan
Delete Attributes and Objects
To delete any object attribute, use the del keyword.
You can delete the object completely with del keyword.
Python Example for Beginners
Two Machine Learning Fields
There are two sides to machine learning:
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- Theoretical Machine Learning: This is about math and abstraction and idealized scenarios and limits and beauty and informing what is possible. It is a whole lot neater and cleaner and removed from the mess of reality.
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