Discussion 7: Object-Oriented Programming, String Representation

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Object-oriented programming (OOP) is a programming paradigm that allows us to treat data as objects, like we do in real life.

For example, consider the class Student. Each of you as individuals is an instance of this class.

Details that all CS 61A students have, such as name, are called instance variables. Every student has these variables, but their values differ from student to student. A variable that is shared among all instances of Student is known as a class variable. For example, the max_slip_days attribute is a class variable as it is a property of all students.

All students are able to do homework, attend lecture, and go to office hours. When functions belong to a specific object, they are called methods. In this case, these actions would be methods of Student objects.

Here is a recap of what we discussed above:

  • class: a template for creating objects
  • instance: a single object created from a class
  • instance variable: a data attribute of an object, specific to an instance
  • class variable: a data attribute of an object, shared by all instances of a class
  • method: a bound function that may be called on all instances of a class

Instance variables, class variables, and methods are all considered attributes of an object.

Q1: WWPD: Student OOP

Below we have defined the classes Professor and Student, implementing some of what was described above. Remember that Python passes the self argument implicitly to methods when calling the method directly on an object.

class Student:

    max_slip_days = 3 # this is a class variable

    def __init__(self, name, staff):
        self.name = name # this is an instance variable
        self.understanding = 0
        print("Added", self.name)

    def visit_office_hours(self, staff):
        print("Thanks, " + staff.name)

class Professor:

    def __init__(self, name):
        self.name = name
        self.students = {}

    def add_student(self, student):
        self.students[student.name] = student

    def assist(self, student):
        student.understanding += 1

    def grant_more_slip_days(self, student, days):
        student.max_slip_days = days

What will the following lines output?

>>> callahan = Professor("Callahan")
>>> elle = Student("Elle", callahan)
>>> elle.visit_office_hours(callahan)
>>> elle.visit_office_hours(Professor("Paulette"))
>>> elle.understanding
>>> [name for name in callahan.students]
>>> x = Student("Vivian", Professor("Stromwell")).name
>>> x
>>> [name for name in callahan.students]
>>> elle.max_slip_days
>>> callahan.grant_more_slip_days(elle, 7)
>>> elle.max_slip_days
>>> Student.max_slip_days

Q2: Keyboard

We'd like to create a Keyboard class that takes in an arbitrary number of Buttons and stores these Buttons in a dictionary. The keys in the dictionary will be ints that represent the postition on the Keyboard, and the values will be the respective Button. Fill out the methods in the Keyboard class according to each description, using the doctests as a reference for the behavior of a Keyboard.

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To avoid redefining attributes and methods for similar classes, we can write a single base class from which the similar classes inherit. For example, we can write a class called Pet and define Dog as a subclass of Pet:

class Pet:

    def __init__(self, name, owner):
        self.is_alive = True    # It's alive!!!
        self.name = name
        self.owner = owner

    def eat(self, thing):
        print(self.name + " ate a " + str(thing) + "!")

    def talk(self):

class Dog(Pet):

    def talk(self):
        print('This Dog says woof!')

Inheritance represents a hierarchical relationship between two or more classes where one class is a more specific version of the other: a dog is a pet (We use is a to describe this sort of relationship in OOP languages, and not to refer to the Python is operator).

Since Dog inherits from Pet, the Dog class will also inherit the Pet class's methods, so we don't have to redefine __init__ or eat. We do want each Dog to talk in a Dog-specific way, so we can override the talk method.

We can use super() to refer to the superclass of self, and access any superclass methods as if we were an instance of the superclass. For example, super().talk() in the Dog class will call the talk() method from the Pet class, but passing the Dog instance as the self.

This is a little bit of a simplification, and if you're interested you can read more in the Python documentation on super.

Q3: Cat

Below is a skeleton for the Cat class, which inherits from the Pet class. To complete the implementation, override the __init__ and talk methods and add a new lose_life method.

Hint: You can call the __init__ method of Pet (the superclass of Cat) to set a cat's name and owner.

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Q4: NoisyCat

More cats! Fill in this implementation of a class called NoisyCat, which is just like a normal Cat. However, NoisyCat talks a lot -- twice as much as a regular Cat! If you'd like to test your code, feel free to copy over your solution to the Cat class above.

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Class Methods

Now we'll try out another feature of Python classes: class methods. A method can be turned into a class method by adding the classmethod decorator. Then, instead of receiving the instance as the first argument (self), the method will receive the class itself (cls).

Class methods are commonly used to create "factory methods": methods whose job is to construct and return a new instance of the class.

For example, we can add a robo_factory class method to our Dog class that makes robo-dogs:

class Dog(Pet):
    # With the previously defined methods not written out
    def robo_factory(cls, owner):
        return cls("RoboDog", owner)

Then a call to Dog.robo_factory('Sally') would return a new Dog instance with the name "RoboDog" and owner "Sally".

Q5: Cat Adoption

Now you can implement the adopt_random_cat method below, which should construct a cat with a random name and lives. To generate random values, you can use functions like random.choice and random.randint from the random module.

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Representation: Repr, Str

There are two main ways to produce the "string" of an object in Python: str() and repr(). While the two are similar, they are used for different purposes.

str() is used to describe the object to the end user in a "Human-readable" form, while repr() can be thought of as a "Computer-readable" form mainly used for debugging and development.

When we define a class in Python, __str__ and __repr__ are both built-in methods for the class.

We can call those methods using the global built-in functions str(obj) or repr(obj) instead of dot notation, obj.__repr__() or obj.__str__().

In addition, the print() function calls the __str__ method of the object, while simply calling the object in interactive mode calls the _repr__ method.

Here's an example:

class Rational:

    def __init__(self, numerator, denominator):
        self.numerator = numerator
        self.denominator = denominator

    def __str__(self):
        return f'{self.numerator}/{self.denominator}'

    def __repr__(self):
        return f'Rational({self.numerator},{self.denominator})'

>>> a = Rational(1, 2)
>>> str(a)
>>> repr(a)
>>> print(a)
>>> a

Q6: WWPD: Repr-esentation

class A:
    def __init__(self, x):
        self.x = x

    def __repr__(self):
         return self.x

    def __str__(self):
         return self.x * 2

class B:
    def __init__(self):
         self.a = []

    def add_a(self, a):

    def __repr__(self):
         ret = ''
         for a in self.a:
             ret += str(a)
         return ret

Given the above class definitions, what will the following lines output?

>>> A('one')
>>> print(A('one'))
>>> repr(A('two'))
>>> b = B()
>>> b.add_a(A('a'))
>>> b.add_a(A('b'))
>>> b