Lab 8: Midterm Review lab08.zip

Due by 11:59pm on Wednesday, March 16.

Starter Files

Download lab08.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.

Iterators

Generators

Required Questions

Iterators & Generators

Q1: Repeated

Implement repeated, which takes in an iterator t and returns the first value in t that appears k times in a row.

Note: You can assume that the iterator t will have a value that appears at least k times in a row. If you are receiving a StopIteration, your repeated function is likely not identifying the correct value.

Your implementation should iterate through the items in a way such that if the same iterator is passed into repeated twice, it should continue in the second call at the point it left off in the first. An example of this behavior is in the doctests.

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def repeated(t, k):
    """Return the first value in iterator T that appears K times in a row.
    Iterate through the items such that if the same iterator is passed into
    the function twice, it continues in the second call at the point it left
    off in the first.

    >>> s = iter([10, 9, 10, 9, 9, 10, 8, 8, 8, 7])
    >>> repeated(s, 2)
    9
    >>> s2 = iter([10, 9, 10, 9, 9, 10, 8, 8, 8, 7])
    >>> repeated(s2, 3)
    8
    >>> s = iter([3, 2, 2, 2, 1, 2, 1, 4, 4, 5, 5, 5])
    >>> repeated(s, 3)
    2
    >>> repeated(s, 3)
    5
    >>> s2 = iter([4, 1, 6, 6, 7, 7, 8, 8, 2, 2, 2, 5])
    >>> repeated(s2, 3)
    2
    """
    assert k > 1
    "*** YOUR CODE HERE ***"
    cnt, prev = 1, next(t)
    for item in t:
        if item == prev:
            cnt += 1
            if cnt == k:
                return item
        else:
            cnt = 1
        prev = item

Use Ok to test your code:

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python3 ok -q repeated✂️

Q2: Merge

Implement merge(incr_a, incr_b), which takes two iterables incr_a and incr_b whose elements are ordered. merge yields elements from incr_a and incr_b in sorted order, eliminating repetition. You may assume incr_a and incr_b themselves do not contain repeats, and that none of the elements of either are None. You may not assume that the iterables are finite; either may produce an infinite stream of results.

You will probably find it helpful to use the two-argument version of the built-in next function: next(incr, v) is the same as next(incr), except that instead of raising StopIteration when incr runs out of elements, it returns v.

See the doctest for examples of behavior.

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def merge(incr_a, incr_b):
    """Yield the elements of strictly increasing iterables incr_a and incr_b, removing
    repeats. Assume that incr_a and incr_b have no repeats. incr_a or incr_b may or may not
    be infinite sequences.

    >>> m = merge([0, 2, 4, 6, 8, 10, 12, 14], [0, 3, 6, 9, 12, 15])
    >>> type(m)
    <class 'generator'>
    >>> list(m)
    [0, 2, 3, 4, 6, 8, 9, 10, 12, 14, 15]
    >>> def big(n):
    ...    k = 0
    ...    while True: yield k; k += n
    >>> m = merge(big(2), big(3))
    >>> [next(m) for _ in range(11)]
    [0, 2, 3, 4, 6, 8, 9, 10, 12, 14, 15]
    """
    iter_a, iter_b = iter(incr_a), iter(incr_b)
    next_a, next_b = next(iter_a, None), next(iter_b, None)
    "*** YOUR CODE HERE ***"    
    while next_a is not None and next_b is not None:
        val_a, val_b = next_a, next_b
        if val_a == val_b:
            yield next_a
            next_a, next_b = next(iter_a, None), next(iter_b, None)
        elif val_a < val_b:
            yield next_a
            next_a = next(iter_a, None)
        else:
            yield next_b
            next_b = next(iter_b, None)
    # incr_a is not empty
    while next_a:
        yield next_a
        next_a = next(iter_a, None)
    # incr_b is not empty
    while next_b:
        yield next_b
        next_b = next(iter_b, None)

Use Ok to test your code:

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python3 ok -q merge✂️

Linked Lists & Trees

Q3: Deep Linked List Length

A linked list that contains one or more linked lists as elements is called a deep linked list. Write a function deep_len that takes in a (possibly deep) linked list and returns the deep length of that linked list. The deep length of a linked list is the total number of non-link elements in the list, as well as the total number of elements contained in all contained lists. See the function’s doctests for examples of the deep length of linked lists.

Hint: Use isinstance to check if something is an instance of an object.

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def deep_len(lnk):
    """ Returns the deep length of a possibly deep linked list.

    >>> deep_len(Link(1, Link(2, Link(3))))
    3
    >>> deep_len(Link(Link(1, Link(2)), Link(3, Link(4))))
    4
    >>> levels = Link(Link(Link(1, Link(2)), \
            Link(3)), Link(Link(4), Link(5)))
    >>> print(levels)
    <<<1 2> 3> <4> 5>
    >>> deep_len(levels)
    5
    """
   	if lnk == Link.empty:
        return 0
    elif not isinstance(lnk, Link):
        return 1
    else:
        return deep_len(lnk.first) + deep_len(lnk.rest)

Use Ok to test your code:

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python3 ok -q deep_len✂️

Q4: Add Leaves

Implement add_d_leaves, a function that takes in a Tree instance t and a number v.

We define the depth of a node in t to be the number of edges from the root to that node. The depth of root is therefore 0.

For each node in the tree, you should add d leaves to it, where d is the depth of the node. Every added leaf should have a label of v. If the node at this depth has existing branches, you should add these leaves to the end of that list of branches.

For example, you should be adding 1 leaf with label v to each node at depth 1, 2 leaves to each node at depth 2, and so on.

Here is an example of a tree t(shown on the left) and the result after add_d_leaves is applied with v as 5.add

Try drawing out the second doctest to visualize how the function is mutating t3.

Hint: Use a helper function to keep track of the depth!

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def add_d_leaves(t, v):
    """Add d leaves containing v to each node at every depth d.

    >>> t_one_to_four = Tree(1, [Tree(2), Tree(3, [Tree(4)])])
    >>> print(t_one_to_four)
    1
      2
      3
        4
    >>> add_d_leaves(t_one_to_four, 5)
    >>> print(t_one_to_four)
    1
      2
        5
      3
        4
          5
          5
        5

    >>> t1 = Tree(1, [Tree(3)])
    >>> add_d_leaves(t1, 4)
    >>> t1
    Tree(1, [Tree(3, [Tree(4)])])
    >>> t2 = Tree(2, [Tree(5), Tree(6)])
    >>> t3 = Tree(3, [t1, Tree(0), t2])
    >>> print(t3)
    3
      1
        3
          4
      0
      2
        5
        6
    >>> add_d_leaves(t3, 10)
    >>> print(t3)
    3
      1
        3
          4
            10
            10
            10
          10
          10
        10
      0
        10
      2
        5
          10
          10
        6
          10
          10
        10
    """
    "*** YOUR CODE HERE ***"
    def dfs(root, depth, v):
        if root.is_leaf():
            for _ in range(depth):
                root.branches.append(Tree(v))
            return

        for b in root.branches:
            dfs(b, depth + 1, v)
        
        for _ in range(depth):
            root.branches.append(Tree(v))

    dfs(t, 0, v)

Use Ok to test your code:

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python3 ok -q add_d_leaves✂️

Efficiency

Q5: Efficiency Practice

Choose the term that fills in the blank for the functions defined below: <function> runs in ____ time in the length of its input.

  • Constant
  • Logarithmic
  • Linear
  • Quadratic
  • Exponential
  • None of these

Assume that len runs in constant time and all runs in linear time in the length of its input. Selecting an element of a list by its index requires constant time. Constructing a range requires constant time.

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def count_partitions(n, m):
    """Counts the number of partitions of a positive integer n, 
    using parts up to size m."""
    if n == 0:
        return 1
    elif n < 0:
        return 0
    elif m == 0:
        return 0
    else:
        with_m = count_partitions(n-m, m)
        without_m = count_partitions(n, m-1)
        return with_m + without_m

def is_palindrome(s):
    """Return whether a list of numbers s is a palindrome."""
    return all([s[i] == s[len(s) - i - 1] for i in range(len(s))])

def binary_search(lst, n):
    """Takes in a sorted list lst and returns the index where integer n
    is contained in lst. Returns -1 if n does not exist in lst."""
    low = 0
    high = len(lst)
    while low <= high:
        middle = (low + high) // 2
        if lst[middle] == n:
            return middle
        elif n < lst[middle]:
            high = middle - 1
        else:
            low = middle + 1
    return -1

The is_palindrome question was reformatted from question 6(d) on fall 2019’s final.

Use Ok to test your understanding:

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python3 ok -q efficiency_practice -u
Q: The count_partitions function runs in ____ time in the length of its input.

Choose the number of the correct choice:
0) Quadratic
1) None of these
2) Constant
3) Logarithmic
4) Linear
5) Exponential
? 5
-- OK! --

---------------------------------------------------------------------
efficiency_practice > Suite 1 > Case 2
(cases remaining: 2)

Q: The is_palindrome function runs in ____ time in the length of its input.
Choose the number of the correct choice:
0) Linear
1) Quadratic
2) None of these
3) Exponential
4) Constant
5) Logarithmic
? 0
-- OK! --

---------------------------------------------------------------------
efficiency_practice > Suite 1 > Case 3
(cases remaining: 1)

Q: The binary_search function runs in ____ time in the length of its input.
Choose the number of the correct choice:
0) Linear
1) Logarithmic
2) Constant
3) None of these
4) Exponential
5) Quadratic
? 1
-- OK! --

---------------------------------------------------------------------
OK! All cases for efficiency_practice unlocked.

Submit

Make sure to submit this assignment by running:

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python3 ok --submit

Extra Practice

Recursion and Tree Recursion

Q6: Subsequences

A subsequence of a sequence S is a subset of elements from S, in the same order they appear in S. Consider the list [1, 2, 3]. Here are a few of it’s subsequences [], [1, 3], [2], and [1, 2, 3].

Write a function that takes in a list and returns all possible subsequences of that list. The subsequences should be returned as a list of lists, where each nested list is a subsequence of the original input.

In order to accomplish this, you might first want to write a function insert_into_all that takes an item and a list of lists, adds the item to the beginning of each nested list, and returns the resulting list.

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def insert_into_all(item, nested_list):
    """Return a new list consisting of all the lists in nested_list,
    but with item added to the front of each. You can assume that
     nested_list is a list of lists.

    >>> nl = [[], [1, 2], [3]]
    >>> insert_into_all(0, nl)
    [[0], [0, 1, 2], [0, 3]]
    """
    "*** YOUR CODE HERE ***"

def subseqs(s):
    """Return a nested list (a list of lists) of all subsequences of S.
    The subsequences can appear in any order. You can assume S is a list.

    >>> seqs = subseqs([1, 2, 3])
    >>> sorted(seqs)
    [[], [1], [1, 2], [1, 2, 3], [1, 3], [2], [2, 3], [3]]
    >>> subseqs([])
    [[]]
    """
    if len(s) <= 1:
        return [[], s] if s != [] else [[]]
    else:
        tmp = subseqs(s[1:])
        return insert_into_all(s[0], tmp) + tmp

Use Ok to test your code:

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python3 ok -q subseqs✂️

Q7: Non-Decreasing Subsequences

Just like the last question, we want to write a function that takes a list and returns a list of lists, where each individual list is a subsequence of the original input.

This time we have another condition: we only want the subsequences for which consecutive elements are nondecreasing. For example, [1, 3, 2] is a subsequence of [1, 3, 2, 4], but since 2 < 3, this subsequence would not be included in our result.

Fill in the blanks to complete the implementation of the non_decrease_subseqs function. You may assume that the input list contains no negative elements.

You may use the provided helper function insert_into_all, which takes in an item and a list of lists and inserts the item to the front of each list.

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def non_decrease_subseqs(s):
    """Assuming that S is a list, return a nested list of all subsequences
    of S (a list of lists) for which the elements of the subsequence
    are strictly nondecreasing. The subsequences can appear in any order.

    >>> seqs = non_decrease_subseqs([1, 3, 2])
    >>> sorted(seqs)
    [[], [1], [1, 2], [1, 3], [2], [3]]
    >>> non_decrease_subseqs([])
    [[]]
    >>> seqs2 = non_decrease_subseqs([1, 1, 2])
    >>> sorted(seqs2)
    [[], [1], [1], [1, 1], [1, 1, 2], [1, 2], [1, 2], [2]]
    """
    def subseq_helper(s, prev):
        if not s:
            return ____________________
        elif s[0] < prev:
            return ____________________
        else:
            a = ______________________
            b = ______________________
            return insert_into_all(________, ______________) + ________________
    return subseq_helper(____, ____)

Use Ok to test your code:

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python3 ok -q non_decrease_subseqs✂️

Mutable Lists

Q8: Shuffle

Define a function shuffle that takes a sequence with an even number of elements (cards) and creates a new list that interleaves the elements of the first half with the elements of the second half.

To interleave two sequences s0 and s1 is to create a new sequence such that the new sequence contains (in this order) the first element of s0, the first element of s1, the second element of s0, the second element of s1, and so on. If the two lists are not the same length, then the leftover elements of the longer list should still appear at the end.

Note: If you’re running into an issue where the special heart / diamond / spades / clubs symbols are erroring in the doctests, feel free to copy paste the below doctests into your file as these don’t use the special characters and should not give an “illegal multibyte sequence” error.

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def card(n):
    """Return the playing card numeral as a string for a positive n <= 13."""
    assert type(n) == int and n > 0 and n <= 13, "Bad card n"
    specials = {1: 'A', 11: 'J', 12: 'Q', 13: 'K'}
    return specials.get(n, str(n))

def shuffle(cards):
    """Return a shuffled list that interleaves the two halves of cards.

    >>> shuffle(range(6))
    [0, 3, 1, 4, 2, 5]
    >>> suits = ['H', 'D', 'S', 'C']
    >>> cards = [card(n) + suit for n in range(1,14) for suit in suits]
    >>> cards[:12]
    ['AH', 'AD', 'AS', 'AC', '2H', '2D', '2S', '2C', '3H', '3D', '3S', '3C']
    >>> cards[26:30]
    ['7S', '7C', '8H', '8D']
    >>> shuffle(cards)[:12]
    ['AH', '7S', 'AD', '7C', 'AS', '8H', 'AC', '8D', '2H', '8S', '2D', '8C']
    >>> shuffle(shuffle(cards))[:12]
    ['AH', '4D', '7S', '10C', 'AD', '4S', '7C', 'JH', 'AS', '4C', '8H', 'JD']
    >>> cards[:12]  # Should not be changed
    ['AH', 'AD', 'AS', 'AC', '2H', '2D', '2S', '2C', '3H', '3D', '3S', '3C']
    """
    assert len(cards) % 2 == 0, 'len(cards) must be even'
    half = _______________
    shuffled = []
    for i in _____________:
        _________________
        _________________
    return shuffled

Use Ok to test your code:

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python3 ok -q shuffle✂️

Generators & Iterators

Q9: Pairs (generator)

Write a generator function pairs that takes a list and yields all the possible pairs of elements from that list.

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def pairs(lst):
    """
    >>> type(pairs([3, 4, 5]))
    <class 'generator'>
    >>> for x, y in pairs([3, 4, 5]):
    ...     print(x, y)
    ...
    3 3
    3 4
    3 5
    4 3
    4 4
    4 5
    5 3
    5 4
    5 5
    """
    "*** YOUR CODE HERE ***"
    for x in lst:
        for y in lst:
            yield x, y

Use Ok to test your code:

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python3 ok -q pairs✂️

Q10: Pairs (iterator)

Important note (March 14): This question is not in scope for this semester (Spring 2022), as it involves __iter__ and __next__.

Now write an iterator that does the same thing. You are only allowed to use a linear amount of space - so computing a list of all of the possible pairs is not a valid answer. Notice how much harder it is - this is why generators are useful.

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class PairsIterator:
    """
    >>> for x, y in PairsIterator([3, 4, 5]):
    ...     print(x, y)
    ...
    3 3
    3 4
    3 5
    4 3
    4 4
    4 5
    5 3
    5 4
    5 5
    """
    def __init__(self, lst):
        "*** YOUR CODE HERE ***"

    def __next__(self):
        "*** YOUR CODE HERE ***"

    def __iter__(self):
        "*** YOUR CODE HERE ***"

Use Ok to test your code:

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python3 ok -q PairsIterator✂️

Trees

Q11: Long Paths

Implement long_paths, which returns a list of all paths in a tree with length at least n. A path in a tree is a linked list of node values that starts with the root and ends at a leaf. Each subsequent element must be from a child of the previous value’s node. The length of a path is the number of edges in the path (i.e. one less than the number of nodes in the path). Paths are listed in order from left to right. See the doctests for some examples.

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def long_paths(tree, n):
    """Return a list of all paths in tree with length at least n.

    >>> t = Tree(3, [Tree(4), Tree(4), Tree(5)])
    >>> left = Tree(1, [Tree(2), t])
    >>> mid = Tree(6, [Tree(7, [Tree(8)]), Tree(9)])
    >>> right = Tree(11, [Tree(12, [Tree(13, [Tree(14)])])])
    >>> whole = Tree(0, [left, Tree(13), mid, right])
    >>> for path in long_paths(whole, 2):
    ...     print(path)
    ...
    <0 1 2>
    <0 1 3 4>
    <0 1 3 4>
    <0 1 3 5>
    <0 6 7 8>
    <0 6 9>
    <0 11 12 13 14>
    >>> for path in long_paths(whole, 3):
    ...     print(path)
    ...
    <0 1 3 4>
    <0 1 3 4>
    <0 1 3 5>
    <0 6 7 8>
    <0 11 12 13 14>
    >>> long_paths(whole, 4)
    [Link(0, Link(11, Link(12, Link(13, Link(14)))))]
    """
    "*** YOUR CODE HERE ***"

Use Ok to test your code:

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python3 ok -q long_paths✂️

Linked Lists

Q12: Flip Two

Write a recursive function flip_two that takes as input a linked list s and mutates s so that every pair of values in the linked list is flipped.

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def flip_two(s):
    """
    >>> one_lnk = Link(1)
    >>> flip_two(one_lnk)
    >>> one_lnk
    Link(1)
    >>> lnk = Link(1, Link(2, Link(3, Link(4, Link(5)))))
    >>> flip_two(lnk)
    >>> lnk
    Link(2, Link(1, Link(4, Link(3, Link(5)))))
    """
    "*** YOUR CODE HERE ***"

    # For an extra challenge, try writing out an iterative approach as well below!
    "*** YOUR CODE HERE ***"

Use Ok to test your code:

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python3 ok -q flip_two✂️