Lab 7: Inheritance, Linked Lists

Due by 11:59pm on Wednesday, March 13.

Starter Files

Download Inside the archive, you will find starter files for the questions in this lab, along with a copy of the Ok autograder.

Required Questions

Getting Started Videos

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Consult the drop-down if you need a refresher on Inheritance. It's okay to skip directly to the questions and refer back here should you get stuck.

To avoid redefining attributes and methods for similar classes, we can write a single base class from which more specialized 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!!! = name
        self.owner = owner

    def eat(self, thing):
        print( + " 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.

Q1: WWPD: Inheritance ABCs

Important: For all WWPD questions, type Function if you believe the answer is <function...>, Error if it errors, and Nothing if nothing is displayed.

Use Ok to test your knowledge with the following "What Would Python Display?" questions:

python3 ok -q inheritance-abc -u

>>> class A:
...   x, y = 0, 0
...   def __init__(self):
...         return
>>> class B(A):
...   def __init__(self):
...         return
>>> class C(A):
...   def __init__(self):
...         return
>>> print(A.x, B.x, C.x)
>>> B.x = 2 >>> print(A.x, B.x, C.x)
>>> A.x += 1 >>> print(A.x, B.x, C.x)
>>> obj = C() >>> obj.y = 1 >>> C.y == obj.y
>>> A.y = obj.y >>> print(A.y, B.y, C.y, obj.y)

Class Practice

Let's say we'd like to model a bank account that can handle interactions such as depositing funds or gaining interest on current funds. In the following questions, we will be building off of the Account class. Here's our current definition of the class:

class Account:
    """An account has a balance and a holder.
    >>> a = Account('John')
    >>> a.deposit(10)
    >>> a.balance
    >>> a.interest
    >>> a.time_to_retire(10.25)  # 10 -> 10.2 -> 10.404
    >>> a.balance                # Calling time_to_retire method should not change the balance
    >>> a.time_to_retire(11)     # 10 -> 10.2 -> ... -> 11.040808032
    >>> a.time_to_retire(100)
    max_withdrawal = 10
    interest = 0.02

    def __init__(self, account_holder):
        self.balance = 0
        self.holder = account_holder

    def deposit(self, amount):
        self.balance = self.balance + amount
        return self.balance

    def withdraw(self, amount):
        if amount > self.balance:
            return "Insufficient funds"
        if amount > self.max_withdrawal:
            return "Can't withdraw that amount"
        self.balance = self.balance - amount
        return self.balance

Q2: Retirement

Add a time_to_retire method to the Account class. This method takes in an amount and returns how many years the holder would need to wait in order for the current balance to grow to at least amount, assuming that the bank adds the interest (calculated as the current balance multiplied by the interest rate) to the balance at the end of each year.

    def time_to_retire(self, amount):
        """Return the number of years until balance would grow to amount."""
        assert self.balance > 0 and amount > 0 and self.interest > 0
        "*** YOUR CODE HERE ***"

Use Ok to test your code:

python3 ok -q Account

Q3: FreeChecking

Implement the FreeChecking class, which is like the Account class from lecture except that it charges a withdraw fee withdraw_fee after withdrawing free_withdrawals number of times. If a withdrawal is unsuccessful, it still counts towards the number of free withdrawals remaining, but no fee for the withdrawal will be charged.

class FreeChecking(Account):
    """A bank account that charges for withdrawals, but the first two are free!
    >>> ch = FreeChecking('Jack')
    >>> ch.balance = 20
    >>> ch.withdraw(100)  # First one's free. Still counts as a free withdrawal even though it was unsuccessful
    'Insufficient funds'
    >>> ch.withdraw(3)    # Second withdrawal is also free
    >>> ch.balance
    >>> ch.withdraw(3)    # Ok, two free withdrawals is enough, as free_withdrawals is only 2
    >>> ch.withdraw(3)
    >>> ch2 = FreeChecking('John')
    >>> ch2.balance = 10
    >>> ch2.withdraw(3) # No fee
    >>> ch.withdraw(3)  # ch still charges a fee
    >>> ch.withdraw(5)  # Not enough to cover fee + withdraw
    'Insufficient funds'
    withdraw_fee = 1
    free_withdrawals = 2

    "*** YOUR CODE HERE ***"

Use Ok to test your code:

python3 ok -q FreeChecking

Linked Lists

Consult the drop-down if you need a refresher on Linked Lists. It's okay to skip directly to the questions and refer back here should you get stuck.

A linked list is a data structure for storing a sequence of values. It is more efficient than a regular built-in list for certain operations, such as inserting a value in the middle of a long list. Linked lists are not built in, and so we define a class called Link to represent them. A linked list is either a Link instance or Link.empty (which represents an empty linked list).

A instance of Link has two instance attributes, first and rest.

class Link:
    """A linked list.

    >>> s = Link(1)
    >>> s.first
    >>> is Link.empty
    >>> s = Link(2, Link(3, Link(4)))
    >>> s.first = 5
    >>> = 6
    >>> = Link.empty
    >>> s                                    # Displays the contents of repr(s)
    Link(5, Link(6))
    >>> = Link(7, Link(Link(8, Link(9))))
    >>> s
    Link(5, Link(7, Link(Link(8, Link(9)))))
    >>> print(s)                             # Prints str(s)
    <5 7 <8 9>>
    empty = ()

    def __init__(self, first, rest=empty):
        assert rest is Link.empty or isinstance(rest, Link)
        self.first = first = rest

    def __repr__(self):
        if is not Link.empty:
            rest_repr = ', ' + repr(
            rest_repr = ''
        return 'Link(' + repr(self.first) + rest_repr + ')'

    def __str__(self):
        string = '<'
        while is not Link.empty:
            string += str(self.first) + ' '
            self =
        return string + str(self.first) + '>'

The rest attribute of a Link instance should always be a linked list: either another Link instance or Link.empty. It SHOULD NEVER be None.

To check if a linked list is empty, compare it to Link.empty. Since there is only ever one empty list, we can use is to compare, but == would work too.

def is_empty(s):
    """Return whether linked list s is empty."""
    return s is Link.empty:

Q4: WWPD: Linked Lists

Read over the Link class. Make sure you understand the doctests.

Use Ok to test your knowledge with the following "What Would Python Display?" questions:

python3 ok -q link -u

Enter Function if you believe the answer is <function ...>, Error if it errors, and Nothing if nothing is displayed.

If you get stuck, try drawing out the box-and-pointer diagram for the linked list on a piece of paper or loading the Link class into the interpreter with python3 -i

>>> link = Link(1000)
>>> link.first
>>> is Link.empty
>>> link = Link(1000, 2000)
>>> link = Link(1000, Link())
>>> link = Link(1, Link(2, Link(3)))
>>> link.first
>>> is Link.empty
>>> link.first = 9001 >>> link.first
>>> = >>>
>>> link = Link(1) >>> = link >>> is Link.empty
>>> link = Link(2, Link(3, Link(4))) >>> link2 = Link(1, link) >>> link2.first
>>> link = Link(5, Link(6, Link(7)))
>>> link                 # Look at the __repr__ method of Link
Link(5, Link(6, Link(7)))
>>> print(link) # Look at the __str__ method of Link
<5 6 7>

Write a function duplicate_link that takes in a linked list s and a value val. It mutates s so that each element equal to val is followed by an additional val (a duplicate copy). It returns None.

Note: In order to insert a link into a linked list, reassign the rest attribute of the Link instances that have val as their first. Try drawing out a doctest to visualize!

def duplicate_link(s, val):
    """Mutates s so that each element equal to val is followed by another val.

    >>> x = Link(5, Link(4, Link(5)))
    >>> duplicate_link(x, 5)
    >>> x
    Link(5, Link(5, Link(4, Link(5, Link(5)))))
    >>> y = Link(2, Link(4, Link(6, Link(8))))
    >>> duplicate_link(y, 10)
    >>> y
    Link(2, Link(4, Link(6, Link(8))))
    >>> z = Link(1, Link(2, (Link(2, Link(3)))))
    >>> duplicate_link(z, 2) # ensures that back to back links with val are both duplicated
    >>> z
    Link(1, Link(2, Link(2, Link(2, Link(2, Link(3))))))
    "*** YOUR CODE HERE ***"

Use Ok to test your code:

python3 ok -q duplicate_link

Check Your Score Locally

You can locally check your score on each question of this assignment by running

python3 ok --score

This does NOT submit the assignment! When you are satisfied with your score, submit the assignment to Gradescope to receive credit for it.


Submit this assignment by uploading any files you've edited to the appropriate Gradescope assignment. Lab 00 has detailed instructions.

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