In-Depth Python OOP

In the provided code, we have a class called CinemaHall. The class has a constructor method __init__ that takes two parameters, rows and seats_in_row, which are used to initialize the instance attributes rows and seats_in_row.

The interesting part is the capacity property, which is created using the @property decorator. The capacity property does not have a setter defined, which means it is a read-only property. This property calculates the capacity of the cinema hall based on the number of rows and seats in each row. When the capacity property is accessed, the method defined below it (capacity method) is automatically called, and its return value is used as the value of the property.

The capacity method computes the capacity by multiplying the rows and seats_in_row attributes. When you access the capacity property using hall.capacity, it returns the calculated capacity of the cinema hall.

In the usage part of the code, an instance of the CinemaHall class is created, named hall, with 24 rows and 12 seats in each row. The capacity property is accessed using hall.capacity, and it returns the calculated capacity (24 * 12 = 288) and prints it.

Next, the rows and seats_in_row attributes of the hall instance are updated to 5 and 11, respectively. When you access the capacity property again using hall.capacity, it recalculates the capacity (5 * 11 = 55) and prints the updated value.

In summary, the @property decorator in Python allows you to define a read-only property for a class attribute. It lets you control how the attribute's value is retrieved without the need for explicit method calls, providing a clean and intuitive interface to access derived or computed attributes of the class.