Lab 7: Object-Oriented Programming, Linked Lists, Mutable Trees

Due by 11:59pm on Tuesday, March 9.

Starter Files

Download lab07.zip. Inside the archive, you will find starter files for the questions in this lab, along with a copy of the Ok autograder.

Topics

Consult this section if you need a refresher on the material for this lab. It's okay to skip directly to the questions and refer back here should you get stuck.

Object-Oriented Programming

Minilecture Video: OOP

Object-oriented programming (OOP) is a style of programming that allows you to think of code in terms of "objects." Here's an example of a Car class:

class Car:
    num_wheels = 4

    def __init__(self, color):
        self.wheels = Car.num_wheels
        self.color = color

    def drive(self):
        if self.wheels <= Car.num_wheels:
            return self.color + ' car cannot drive!'
        return self.color + ' car goes vroom!'

    def pop_tire(self):
        if self.wheels > 0:
            self.wheels -= 1

Here's some terminology:

  • class: a blueprint for how to build a certain type of object. The Car class (shown above) describes the behavior and data that all Car objects have.

  • instance: a particular occurrence of a class. In Python, we create instances of a class like this:

    >>> my_car = Car('red')

    my_car is an instance of the Car class.

  • data attributes: a variable that belongs to the instance (also called instance variables). Think of a data attribute as a quality of the object: cars have wheels and color, so we have given our Car instance self.wheels and self.color attributes. We can access attributes using dot notation:

    >>> my_car.color
'red'
>>> my_car.wheels
4

  • method: Methods are just like normal functions, except that they are bound to an instance. Think of a method as a "verb" of the class: cars can drive and also pop their tires, so we have given our Car instance the methods drive and pop_tire. We call methods using dot notation:

    >>> my_car = Car('red')
>>> my_car.drive()
'red car goes vroom!'

  • constructor: As with data abstraction, constructors build an instance of the class. The constructor for car objects is Car(color). When Python calls that constructor, it immediately calls the __init__ method. That's where we initialize the data attributes:

    def __init__(self, color):
    self.wheels = Car.num_wheels
    self.color = color

    The constructor takes in one argument, color. As you can see, this constructor also creates the self.wheels and self.color attributes.

  • self: in Python, self is the first parameter for many methods (in this class, we will only use methods whose first parameter is self). When a method is called, self is bound to an instance of the class. For example:

    >>> my_car = Car('red')
>>> car.drive()

    Notice that the drive method takes in self as an argument, but it looks like we didn't pass one in! This is because the dot notation implicitly passes in car as self for us.


Linked Lists

Minilecture Video: Linked Lists

We've learned that a Python list is one way to store sequential values. Another type of list is a linked list. A Python list stores all of its elements in a single object, and each element can be accessed by using its index. A linked list, on the other hand, is a recursive object that only stores two things: its first value and a reference to the rest of the list, which is another linked list.

We can implement a class, Link, that represents a linked list object. Each instance of Link has two instance attributes, first and rest.

class Link:
    """A linked list.

    >>> s = Link(1)
    >>> s.first
    1
    >>> s.rest is Link.empty
    True
    >>> s = Link(2, Link(3, Link(4)))
    >>> s.first = 5
    >>> s.rest.first = 6
    >>> s.rest.rest = Link.empty
    >>> s                                    # Displays the contents of repr(s)
    Link(5, Link(6))
    >>> s.rest = 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
        self.rest = rest

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

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

A valid linked list can be one of the following:

  1. An empty linked list (Link.empty)
  2. A Link object containing the first value of the linked list and a reference to the rest of the linked list

What makes a linked list recursive is that the rest attribute of a single Link instance is another linked list! In the big picture, each Link instance stores a single value of the list. When multiple Links are linked together through each instance's rest attribute, an entire sequence is formed.

Note: This definition means that the rest attribute of any Link instance must be either Link.empty or another Link instance! This is enforced in Link.__init__, which raises an AssertionError if the value passed in for rest is neither of these things.

To check if a linked list is empty, compare it against the class attribute Link.empty. For example, the function below prints out whether or not the link it is handed is empty:

def test_empty(link):
    if link is Link.empty:
        print('This linked list is empty!')
    else:
        print('This linked list is not empty!')

Mutable Trees

Minilecture Video: Mutable Trees

Recall that a tree is a recursive abstract data type that has a label (the value stored in the root of the tree) and branches (a list of trees directly underneath the root).

We saw one way to implement the tree ADT -- using constructor and selector functions that treat trees as lists. Another, more formal, way to implement the tree ADT is with a class. Here is part of the class definition for Tree, which can be found in lab07.py:

class Tree:
    """
    >>> t = Tree(3, [Tree(2, [Tree(5)]), Tree(4)])
    >>> t.label
    3
    >>> t.branches[0].label
    2
    >>> t.branches[1].is_leaf()
    True
    """
    def __init__(self, label, branches=[]):
        for b in branches:
            assert isinstance(b, Tree)
        self.label = label
        self.branches = list(branches)

    def is_leaf(self):
        return not self.branches

Even though this is a new implementation, everything we know about the tree ADT remains true. That means that solving problems involving trees as objects uses the same techniques that we developed when first studying the tree ADT (e.g. we can still use recursion on the branches!). The main difference, aside from syntax, is that tree objects are mutable.

Here is a summary of the differences between the tree ADT implemented using functions and lists vs. implemented using a class:

- Tree constructor and selector functions Tree class
Constructing a tree To construct a tree given a label and a list of branches, we call tree(label, branches) To construct a tree object given a label and a list of branches, we call Tree(label, branches) (which calls the Tree.__init__ method)
Label and branches To get the label or branches of a tree t, we call label(t) or branches(t) respectively To get the label or branches of a tree t, we access the instance attributes t.label or t.branches respectively
Mutability The tree ADT is immutable because we cannot assign values to call expressions The label and branches attributes of a Tree instance can be reassigned, mutating the tree
Checking if a tree is a leaf To check whether a tree t is a leaf, we call the convenience function is_leaf(t) To check whether a tree t is a leaf, we call the bound method t.is_leaf(). This method can only be called on Tree objects.

Required Questions

WWPD: Objects

Q1: The Car class

Note: These questions use inheritance. For an overview of inheritance, see the inheritance portion of Composing Programs

Below is the definition of a Car class that we will be using in the following WWPD questions. Note: This definition can also be found in car.py.

class Car:
    num_wheels = 4
    gas = 30
    headlights = 2
    size = 'Tiny'

    def __init__(self, make, model):
        self.make = make
        self.model = model
        self.color = 'No color yet. You need to paint me.'
        self.wheels = Car.num_wheels
        self.gas = Car.gas

    def paint(self, color):
        self.color = color
        return self.make + ' ' + self.model + ' is now ' + color

    def drive(self):
        if self.wheels < Car.num_wheels or self.gas <= 0:
            return 'Cannot drive!'
        self.gas -= 10
        return self.make + ' ' + self.model + ' goes vroom!'

    def pop_tire(self):
        if self.wheels > 0:
            self.wheels -= 1

    def fill_gas(self):
        self.gas += 20
        return 'Gas level: ' + str(self.gas)

Use Ok to test your knowledge with the following What would Python Display questions.

python3 ok -q wwpd-car -u

If an error occurs, type Error. If nothing is displayed, type Nothing.

>>> deneros_car = Car('Tesla', 'Model S')
>>> deneros_car.model

______
'Model S'

>>> deneros_car.gas = 10
>>> deneros_car.drive()

______
'Tesla Model S goes vroom!'

>>> deneros_car.drive()

______
'Cannot drive!'

>>> deneros_car.fill_gas()

______
'Gas level: 20'

>>> deneros_car.gas

______
20

>>> Car.gas

______
30
>>> deneros_car = Car('Tesla', 'Model S')
>>> deneros_car.wheels = 2
>>> deneros_car.wheels

______
2

>>> Car.num_wheels

______
4

>>> deneros_car.drive()

______
'Cannot drive!'

>>> Car.drive()

______
Error (TypeError)

>>> Car.drive(deneros_car)

______
'Cannot drive!'

For the following, we reference the MonsterTruck class below. Note: The MonsterTruck class can also be found in car.py.

 class MonsterTruck(Car):
     size = 'Monster'

     def rev(self):
         print('Vroom! This Monster Truck is huge!')

     def drive(self):
         self.rev()
         return Car.drive(self)
>>> deneros_car = MonsterTruck('Monster', 'Batmobile')
>>> deneros_car.drive()

______
Vroom! This Monster Truck is huge!
'Monster Batmobile goes vroom!'

>>> Car.drive(deneros_car)

______
'Monster Batmobile goes vroom!'

>>> MonsterTruck.drive(deneros_car)

______
Vroom! This Monster Truck is huge!
'Monster Batmobile goes vroom!'

>>> Car.rev(deneros_car)

______
Error (AttributeError)

Magic: The Lambda-ing

In the next part of this lab, we will be implementing a card game! This game is inspired by the similarly named Magic: The Gathering.

You can start the game by typing:

python3 cardgame.py

This game doesn't work yet. If we run this right now, the code will error, since we haven't implemented anything yet. When it's working, you can exit the game and return to the command line with Ctrl-C or Ctrl-D.

This game uses several different files.

  • Code for all the questions in this lab can be found in classes.py.
  • Some utility for the game can be found in cardgame.py, but you won't need to open or read this file. This file doesn't actually mutate any instances directly - instead, it calls methods of the different classes, maintaining a strict abstraction barrier.
  • If you want to modify your game later to add your own custom cards and decks, you can look in cards.py to see all the standard cards and the default deck; here, you can add more cards and change what decks you and your opponent use. If you're familiar with the original game, you may notice the cards were not created with balance in mind, so feel free to modify the stats and add/remove cards as desired.

Rules of the Game This game is a little involved, though not nearly as much as its namesake. Here's how it goes:

There are two players. Each player has a hand of cards and a deck, and at the start of each round, each player draws a random card from their deck. If a player's deck is empty when they try to draw, they will automatically lose the game. Cards have a name, an attack statistic, and a defense statistic. Each round, each player chooses one card to play from their own hands. The card with the higher power wins the round. Each played card's power value is calculated as follows:

(player card's attack) - (opponent card's defense) / 2

For example, let's say Player 1 plays a card with 2000 attack/1000 defense and Player 2 plays a card with 1500 attack/3000 defense. Their cards' powers are calculated as:

P1: 2000 - 3000/2 = 2000 - 1500 = 500
P2: 1500 - 1000/2 = 1500 - 500 = 1000

So Player 2 would win this round.

The first player to win 8 rounds wins the match!

However, there are a few effects we can add (in the optional questions section) to make this game a bit more interesting. Cards are split into Tutor, TA, and Professor types, and each type has a different effect when they're played. All effects are applied before power is calculated during that round:

  • A Tutor card will cause the opponent to discard and re-draw the first 3 cards in their hand.
  • A TA card will swap the opponent card's attack and defense.
  • A Professor card will add the opponent card's attack and defense to all cards in their deck and then remove all cards in the opponent's deck that share its attack or defense!

These are a lot of rules to remember, so refer back here if you need to review them, and let's start making the game!

Q2: Making Cards

To play a card game, we're going to need to have cards, so let's make some! We're gonna implement the basics of the Card class first.

First, implement the Card class constructor in classes.py. This constructor takes three arguments:

  • the name of the card, a string
  • the attack stat of the card, an integer
  • the defense stat of the card, an integer

Each Card instance should keep track of these values using instance attributes called name, attack, and defense.

You should also implement the power method in Card, which takes in another card as an input and calculates the current card's power. Check the Rules section if you want a refresher on how power is calculated.

class Card:
    cardtype = 'Staff'

    def __init__(self, name, attack, defense):
        """
        Create a Card object with a name, attack,
        and defense.
        >>> staff_member = Card('staff', 400, 300)
        >>> staff_member.name
        'staff'
        >>> staff_member.attack
        400
        >>> staff_member.defense
        300
        >>> other_staff = Card('other', 300, 500)
        >>> other_staff.attack
        300
        >>> other_staff.defense
        500
        """
        "*** YOUR CODE HERE ***"

    def power(self, opponent_card):
        """
        Calculate power as:
        (player card's attack) - (opponent card's defense)/2
        >>> staff_member = Card('staff', 400, 300)
        >>> other_staff = Card('other', 300, 500)
        >>> staff_member.power(other_staff)
        150.0
        >>> other_staff.power(staff_member)
        150.0
        >>> third_card = Card('third', 200, 400)
        >>> staff_member.power(third_card)
        200.0
        >>> third_card.power(staff_member)
        50.0
        """
        "*** YOUR CODE HERE ***"

Use Ok to test your code:

python3 ok -q Card.__init__
python3 ok -q Card.power

Q3: Making a Player

Now that we have cards, we can make a deck, but we still need players to actually use them. We'll now fill in the implementation of the Player class.

A Player instance has three instance attributes:

  • name is the player's name. When you play the game, you can enter your name, which will be converted into a string to be passed to the constructor.
  • deck is an instance of the Deck class. You can draw from it using its .draw() method.
  • hand is a list of Card instances. Each player should start with 5 cards in their hand, drawn from their deck. Each card in the hand can be selected by its index in the list during the game. When a player draws a new card from the deck, it is added to the end of this list.

Complete the implementation of the constructor for Player so that self.hand is set to a list of 5 cards drawn from the player's deck.

Next, implement the draw and play methods in the Player class. The draw method draws a card from the deck and adds it to the player's hand. The play method removes and returns a card from the player's hand at the given index.

Call deck.draw() when implementing Player.__init__ and Player.draw. Don't worry about how this function works - leave it all to the abstraction!

class Player:
    def __init__(self, deck, name):
        """Initialize a Player object.
        A Player starts the game by drawing 5 cards from their deck. Each turn,
        a Player draws another card from the deck and chooses one to play.
        >>> test_card = Card('test', 100, 100)
        >>> test_deck = Deck([test_card.copy() for _ in range(6)])
        >>> test_player = Player(test_deck, 'tester')
        >>> len(test_deck.cards)
        1
        >>> len(test_player.hand)
        5
        """
        self.deck = deck
        self.name = name
        "*** YOUR CODE HERE ***"

    def draw(self):
        """Draw a card from the player's deck and add it to their hand.
        >>> test_card = Card('test', 100, 100)
        >>> test_deck = Deck([test_card.copy() for _ in range(6)])
        >>> test_player = Player(test_deck, 'tester')
        >>> test_player.draw()
        >>> len(test_deck.cards)
        0
        >>> len(test_player.hand)
        6
        """
        assert not self.deck.is_empty(), 'Deck is empty!'
        "*** YOUR CODE HERE ***"

    def play(self, card_index):
        """Remove and return a card from the player's hand at the given index.
        >>> from cards import *
        >>> test_player = Player(standard_deck, 'tester')
        >>> ta1, ta2 = TACard("ta_1", 300, 400), TACard("ta_2", 500, 600)
        >>> tutor1, tutor2 = TutorCard("t1", 200, 500), TutorCard("t2", 600, 400)
        >>> test_player.hand = [ta1, ta2, tutor1, tutor2]
        >>> test_player.play(0) is ta1
        True
        >>> test_player.play(2) is tutor2
        True
        >>> len(test_player.hand)
        2
        """
        "*** YOUR CODE HERE ***"

Use Ok to test your code:

python3 ok -q Player.__init__
python3 ok -q Player.draw
python3 ok -q Player.play

After you complete this problem, you'll be able to play a working version of the game! Type

python3 cardgame.py

to start a game of Magic: The Lambda-ing!

This version doesn't have the effects for different cards, yet - to get those working, try out the optional questions below.

WWPD: Linked Lists

Q4: WWPD: Linked Lists

Minilecture Video: Linked Lists

Read over the Link class in lab07.py. 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 lab07.py.

>>> from lab07 import *
>>> link = Link(1000)
>>> link.first

______
1000

>>> link.rest is Link.empty

______
True

>>> link = Link(1000, 2000)

______
AssertionError

>>> link = Link(1000, Link())

______
TypeError
>>> from lab07 import *
>>> link = Link(1, Link(2, Link(3)))
>>> link.first

______
1

>>> link.rest.first

______
2

>>> link.rest.rest.rest is Link.empty

______
True

>>> link.first = 9001
>>> link.first

______
9001

>>> link.rest = link.rest.rest
>>> link.rest.first

______
3

>>> link = Link(1)
>>> link.rest = link
>>> link.rest.rest.rest.rest.first

______
1

>>> link = Link(2, Link(3, Link(4)))
>>> link2 = Link(1, link)
>>> link2.first

______
1

>>> link2.rest.first

______
2
>>> from lab07 import *
>>> 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>

Linked Lists

Q5: Convert Link

Write a function convert_link that takes in a linked list and returns the sequence as a Python list. You may assume that the input list is shallow; none of the elements is another linked list.

Try to find both an iterative and recursive solution for this problem!

def convert_link(link):
    """Takes a linked list and returns a Python list with the same elements.

    >>> link = Link(1, Link(2, Link(3, Link(4))))
    >>> convert_link(link)
    [1, 2, 3, 4]
    >>> convert_link(Link.empty)
    []
    """
    "*** YOUR CODE HERE ***"

Use Ok to test your code:

python3 ok -q convert_link

Trees

Q6: Cumulative Mul

Minilecture Video: Mutable Trees

Write a function cumulative_mul that mutates the Tree t so that each node's label becomes the product of all labels in the subtree rooted at the node.

def cumulative_mul(t):
    """Mutates t so that each node's label becomes the product of all labels in
    the corresponding subtree rooted at t.

    >>> t = Tree(1, [Tree(3, [Tree(5)]), Tree(7)])
    >>> cumulative_mul(t)
    >>> t
    Tree(105, [Tree(15, [Tree(5)]), Tree(7)])
    """
    "*** YOUR CODE HERE ***"

Use Ok to test your code:

python3 ok -q cumulative_mul

Optional Questions

The following code-writing questions will all be in classes.py.

For the following sections, do not overwrite any lines already provided in the code. Additionally, make sure to uncomment any calls to print once you have implemented each method. These are used to display information to the user, and changing them may cause you to fail tests that you would otherwise pass.

Q7: Tutors: Flummox

To really make this card game interesting, our cards should have effects! We'll do this with the effect function for cards, which takes in the opponent card, the current player, and the opponent player.

Implement the effect method for Tutors, which causes the opponent to discard the first 3 cards in their hand and then draw 3 new cards. Assume there at least 3 cards in the opponent's hand and at least 3 cards in the opponent's deck.

Remember to uncomment the call to print once you're done!

class TutorCard(Card):
    cardtype = 'Tutor'

    def effect(self, opponent_card, player, opponent):
        """
        Discard the first 3 cards in the opponent's hand and have
        them draw the same number of cards from their deck.
        >>> from cards import *
        >>> player1, player2 = Player(player_deck, 'p1'), Player(opponent_deck, 'p2')
        >>> opponent_card = Card('other', 500, 500)
        >>> tutor_test = TutorCard('Tutor', 500, 500)
        >>> initial_deck_length = len(player2.deck.cards)
        >>> tutor_test.effect(opponent_card, player1, player2)
        p2 discarded and re-drew 3 cards!
        >>> len(player2.hand)
        5
        >>> len(player2.deck.cards) == initial_deck_length - 3
        True
        """
        "*** YOUR CODE HERE ***"
        #Uncomment the line below when you've finished implementing this method!
        #print('{} discarded and re-drew 3 cards!'.format(opponent.name))

Use Ok to test your code:

python3 ok -q TutorCard.effect

Q8: TAs: Shift

Let's add an effect for TAs now! Implement the effect method for TAs, which swaps the attack and defense of the opponent's card.

class TACard(Card):
    cardtype = 'TA'

    def effect(self, opponent_card, player, opponent):
        """
        Swap the attack and defense of an opponent's card.
        >>> from cards import *
        >>> player1, player2 = Player(player_deck, 'p1'), Player(opponent_deck, 'p2')
        >>> opponent_card = Card('other', 300, 600)
        >>> ta_test = TACard('TA', 500, 500)
        >>> ta_test.effect(opponent_card, player1, player2)
        >>> opponent_card.attack
        600
        >>> opponent_card.defense
        300
        """
        "*** YOUR CODE HERE ***"

Use Ok to test your code:

python3 ok -q TACard.effect

Q9: The Professor Arrives

A new challenger has appeared! Implement the effect method for the Professor, who adds the opponent card's attack and defense to all cards in the player's deck and then removes all cards in the opponent's deck that have the same attack or defense as the opponent's card.

Note: You might run into trouble when you mutate a list as you're iterating through it. Try iterating through a copy instead! You can use slicing to copy a list:

  >>> lst = [1, 2, 3, 4]
  >>> copy = lst[:]
  >>> copy
  [1, 2, 3, 4]
  >>> copy is lst
  False
class ProfessorCard(Card):
    cardtype = 'Professor'

    def effect(self, opponent_card, player, opponent):
        """
        Adds the attack and defense of the opponent's card to
        all cards in the player's deck, then removes all cards
        in the opponent's deck that share an attack or defense
        stat with the opponent's card.
        >>> test_card = Card('card', 300, 300)
        >>> professor_test = ProfessorCard('Professor', 500, 500)
        >>> opponent_card = test_card.copy()
        >>> test_deck = Deck([test_card.copy() for _ in range(8)])
        >>> player1, player2 = Player(test_deck.copy(), 'p1'), Player(test_deck.copy(), 'p2')
        >>> professor_test.effect(opponent_card, player1, player2)
        3 cards were discarded from p2's deck!
        >>> [(card.attack, card.defense) for card in player1.deck.cards]
        [(600, 600), (600, 600), (600, 600)]
        >>> len(player2.deck.cards)
        0
        """
        orig_opponent_deck_length = len(opponent.deck.cards)
        "*** YOUR CODE HERE ***"
        discarded = orig_opponent_deck_length - len(opponent.deck.cards)
        if discarded:
            #Uncomment the line below when you've finished implementing this method!
            #print('{} cards were discarded from {}\'s deck!'.format(discarded, opponent.name))
            return

Use Ok to test your code:

python3 ok -q ProfessorCard.effect

After you complete this problem, we'll have a fully functional game of Magic: The Lambda-ing! This doesn't have to be the end, though - we encourage you to get creative with more card types, effects, and even adding more custom cards to your deck!

Q10: Cycles

The Link class can represent lists with cycles. That is, a list may contain itself as a sublist.

>>> s = Link(1, Link(2, Link(3)))
>>> s.rest.rest.rest = s
>>> s.rest.rest.rest.rest.rest.first
3

Implement has_cycle,that returns whether its argument, a Link instance, contains a cycle.

Hint: Iterate through the linked list and try keeping track of which Link objects you've already seen.

def has_cycle(link):
    """Return whether link contains a cycle.

    >>> s = Link(1, Link(2, Link(3)))
    >>> s.rest.rest.rest = s
    >>> has_cycle(s)
    True
    >>> t = Link(1, Link(2, Link(3)))
    >>> has_cycle(t)
    False
    >>> u = Link(2, Link(2, Link(2)))
    >>> has_cycle(u)
    False
    """
    "*** YOUR CODE HERE ***"

Use Ok to test your code:

python3 ok -q has_cycle

As an extra challenge, implement has_cycle_constant with only constant space. (If you followed the hint above, you will use linear space.) The solution is short (less than 20 lines of code), but requires a clever idea. Try to discover the solution yourself before asking around:

def has_cycle_constant(link):
    """Return whether link contains a cycle.

    >>> s = Link(1, Link(2, Link(3)))
    >>> s.rest.rest.rest = s
    >>> has_cycle_constant(s)
    True
    >>> t = Link(1, Link(2, Link(3)))
    >>> has_cycle_constant(t)
    False
    """
    "*** YOUR CODE HERE ***"

Use Ok to test your code:

python3 ok -q has_cycle_constant

Q11: Every Other

Implement every_other, which takes a linked list s. It mutates s such that all of the odd-indexed elements (using 0-based indexing) are removed from the list. For example:

>>> s = Link('a', Link('b', Link('c', Link('d'))))
>>> every_other(s)
>>> s.first
'a'
>>> s.rest.first
'c'
>>> s.rest.rest is Link.empty
True

If s contains fewer than two elements, s remains unchanged.

Do not return anything! every_other should mutate the original list.

def every_other(s):
    """Mutates a linked list so that all the odd-indiced elements are removed
    (using 0-based indexing).

    >>> s = Link(1, Link(2, Link(3, Link(4))))
    >>> every_other(s)
    >>> s
    Link(1, Link(3))
    >>> odd_length = Link(5, Link(3, Link(1)))
    >>> every_other(odd_length)
    >>> odd_length
    Link(5, Link(1))
    >>> singleton = Link(4)
    >>> every_other(singleton)
    >>> singleton
    Link(4)
    """
    "*** YOUR CODE HERE ***"

Use Ok to test your code:

python3 ok -q every_other

Q12: Reverse Other

Write a function reverse_other that mutates the tree such that labels on every other (odd-depth) level are reversed. For example, Tree(1,[Tree(2, [Tree(4)]), Tree(3)]) becomes Tree(1,[Tree(3, [Tree(4)]), Tree(2)]). Notice that the nodes themselves are not reversed; only the labels are.

def reverse_other(t):
    """Mutates the tree such that nodes on every other (odd-depth) level
    have the labels of their branches all reversed.

    >>> t = Tree(1, [Tree(2), Tree(3), Tree(4)])
    >>> reverse_other(t)
    >>> t
    Tree(1, [Tree(4), Tree(3), Tree(2)])
    >>> t = Tree(1, [Tree(2, [Tree(3, [Tree(4), Tree(5)]), Tree(6, [Tree(7)])]), Tree(8)])
    >>> reverse_other(t)
    >>> t
    Tree(1, [Tree(8, [Tree(3, [Tree(5), Tree(4)]), Tree(6, [Tree(7)])]), Tree(2)])
    """
    "*** YOUR CODE HERE ***"

Use Ok to test your code:

python3 ok -q reverse_other