Let's assume we want to process clients' data from a CSV file. The R6 classes support public and private components. Each one of them will be defined as a list containing both methods or attributes. For example, we will store the customer_id, the name, and the city as public attributes. We need to initialize them to NULL. We also need an initialize method that will be called whenever the class is instantiated. This is the equivalent of a constructor in other programming languages. Inside the initializer or constructor, we typically want to store the variables provided by the user. We need to use the self keyword to refer to the class variables. We then define a method that will return either TRUE or FALSE if the city belongs is in America or not. Another method, called full_print(), will print the contents of the class.

The lock_objects method is not usually very important; it indicates whether we want to lock the elements in the class. If we set lock=FALSE, that means that we can add more attributes later, if we want to.

Here, we only have one private method. Since it is private, it can only be called within the class, but not externally. This method, called upper_, will be used to transform the text into uppercase.

After the class is defined, we loop through the DataFrame and select each row sequentially. We instantiate the class for each row, and then we add each one of these into a list.

The convenience of using classes is that we now have a list containing each instance. We can call the specific methods or attributes for each element in this list. For example, we can get a specific element and then call the is_city_in_america method; and finally we call the full_print method.