Lab 3: Recursion, Python Lists

Due by 11:59pm on Wednesday, February 14.

Starter Files

Download lab03.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.

Lists

A list is a data structure that can hold an ordered collection of items. These items, known as elements, can be of any data type, including numbers, strings, or even other lists. A comma-separated list of expressions in square brackets creates a list:

>>> list_of_values = [2, 1, 3, True, 3]
>>> nested_list = [2, [1, 3], [True, [3]]]

Each position in a list has an index, with the left-most element indexed 0.

>>> list_of_values[0]
2
>>> nested_list[1]
[1, 3]

A negative index counts from the end, with the right-most element indexed -1.

>>> nested_list[-1]
[True, [3]]

Adding lists creates a longer list containing the elements of the added lists.

>>> [1, 2] + [3] + [4, 5]
[1, 2, 3, 4, 5]

List Comprehensions

A list comprehension describes the elements in a list and evaluates to a new list containing those elements.

There are two forms:

[<expression> for <element> in <sequence>]
[<expression> for <element> in <sequence> if <conditional>]

Here's an example that starts with [1, 2, 3, 4], picks out the even elements 2 and 4 using if i % 2 == 0, then squares each of these using i*i. The purpose of for i is to give a name to each element in [1, 2, 3, 4].

>>> [i*i for i in [1, 2, 3, 4] if i % 2 == 0]
[4, 16]

This list comprehension evaluates to a list of:

  • The value of i*i
  • For each element i in the sequence [1, 2, 3, 4]
  • For which i % 2 == 0

In other words, this list comprehension will create a new list that contains the square of every even element of the original list [1, 2, 3, 4].

We can also rewrite a list comprehension as an equivalent for statement, such as for the example above:

>>> result = []
>>> for i in [1, 2, 3, 4]:
...     if i % 2 == 0:
...         result = result + [i*i]
>>> result
[4, 16]

For Statements

A for statement executes code for each element of a sequence, such as a list or range. Each time the code is executed, the name right after for is bound to a different element of the sequence.

for <name> in <expression>:
    <suite>

First, <expression> is evaluated. It must evaluate to a sequence. Then, for each element in the sequence in order,

  1. <name> is bound to the element.
  2. <suite> is executed.

Here is an example:

for x in [-1, 4, 2, 0, 5]:
    print("Current elem:", x)

This would display the following:

Current elem: -1
Current elem: 4
Current elem: 2
Current elem: 0
Current elem: 5

Ranges

A range is a data structure that holds integer sequences. A range can be created by:

  • range(stop) contains 0, 1, ..., stop - 1
  • range(start, stop) contains start, start + 1, ..., stop - 1

Notice how the range function doesn't include the stop value; it generates numbers up to, but not including, the stop value.

For example:

>>> for i in range(3):
...     print(i)
...
0
1
2

While ranges and lists are both sequences, a range object is different from a list. A range can be converted to a list by calling list():

>>> range(3, 6)
range(3, 6)  # this is a range object
>>> list(range(3, 6))
[3, 4, 5]  # list() converts the range object to a list
>>> list(range(5))
[0, 1, 2, 3, 4]
>>> list(range(1, 6))
[1, 2, 3, 4, 5]

Required Questions


Lists

Q1: WWPD: Lists & Ranges

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

python3 ok -q lists-wwpd -u

Predict what Python will display when you type the following into the interactive interpreter. Then try it to check your answers.

>>> s = [7//3, 5, [4, 0, 1], 2]
>>> s[0]
______
2
>>> s[2]
______
[4, 0, 1]
>>> s[-1]
______
2
>>> len(s)
______
4
>>> 4 in s
______
False
>>> 4 in s[2]
______
True
>>> s[2] + [3 + 2]
______
[4, 0, 1, 5]
>>> 5 in s[2]
______
False
>>> s[2] * 2
______
[4, 0, 1, 4, 0, 1]
>>> list(range(3, 6))
______
[3, 4, 5]
>>> range(3, 6)
______
range(3, 6)
>>> r = range(3, 6) >>> [r[0], r[2]]
______
[3, 5]
>>> range(4)[-1]
______
3

Q2: Print If

Implement print_if, which takes a list s and a one-argument function f. It prints each element x of s for which f(x) returns a true value.

def print_if(s, f):
    """Print each element of s for which f returns a true value.

    >>> print_if([3, 4, 5, 6], lambda x: x > 4)
    5
    6
    >>> result = print_if([3, 4, 5, 6], lambda x: x % 2 == 0)
    4
    6
    >>> print(result)  # print_if should return None
    None
    """
    for x in s:
        "*** YOUR CODE HERE ***"

Use Ok to test your code:

python3 ok -q print_if

Q3: Close

Implement close, which takes a list of numbers s and a non-negative integer k. It returns how many of the elements of s are within k of their index. That is, the absolute value of the difference between the element and its index is less than or equal to k.

Remember that list is "zero-indexed"; the index of the first element is 0.

def close(s, k):
    """Return how many elements of s that are within k of their index.

    >>> t = [6, 2, 4, 3, 5]
    >>> close(t, 0)  # Only 3 is equal to its index
    1
    >>> close(t, 1)  # 2, 3, and 5 are within 1 of their index
    3
    >>> close(t, 2)  # 2, 3, 4, and 5 are all within 2 of their index
    4
    >>> close(list(range(10)), 0)
    10
    """
    count = 0
    for i in range(len(s)):  # Use a range to loop over indices
        "*** YOUR CODE HERE ***"
    return count

Use Ok to test your code:

python3 ok -q close

List Comprehensions

Q4: WWPD: List Comprehensions

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

python3 ok -q list-comprehensions-wwpd -u

Predict what Python will display when you type the following into the interactive interpreter. Then try it to check your answers.

>>> [2 * x for x in range(4)]
______
[0, 2, 4, 6]
>>> [y for y in [6, 1, 6, 1] if y > 2]
______
[6, 6]
>>> [[1] + s for s in [[4], [5, 6]]]
______
[[1, 4], [1, 5, 6]]
>>> [z + 1 for z in range(10) if z % 3 == 0]
______
[1, 4, 7, 10]

Q5: Close List

Implement close_list, which takes a list of numbers s and a non-negative integer k. It returns a list of the elements of s that are within k of their index. That is, the absolute value of the difference between the element and its index is less than or equal to k.

def close_list(s, k):
    """Return a list of the elements of s that are within k of their index.

    >>> t = [6, 2, 4, 3, 5]
    >>> close_list(t, 0)  # Only 3 is equal to its index
    [3]
    >>> close_list(t, 1)  # 2, 3, and 5 are within 1 of their index
    [2, 3, 5]
    >>> close_list(t, 2)  # 2, 3, 4, and 5 are all within 2 of their index
    [2, 4, 3, 5]
    """
    return [___ for i in range(len(s)) if ___]

Use Ok to test your code:

python3 ok -q close_list

Q6: Squares Only

Implement the function squares, which takes in a list of positive integers. It returns a list that contains the square roots of the elements of the original list that are perfect squares. Use a list comprehension.

To find if x is a perfect square, you can check if sqrt(x) equals round(sqrt(x)).

from math import sqrt

def squares(s):
    """Returns a new list containing square roots of the elements of the
    original list that are perfect squares.

    >>> seq = [8, 49, 8, 9, 2, 1, 100, 102]
    >>> squares(seq)
    [7, 3, 1, 10]
    >>> seq = [500, 30]
    >>> squares(seq)
    []
    """
    return [___ for n in s if ___]

Use Ok to test your code:

python3 ok -q squares

Recursion

Q7: Double Eights

Write a recursive function that takes in a positive integer n and determines if its digits contain two adjacent 8s. Do not use for or while.

Hint: Start by coming up with a recursive plan: the digits of a number have double eights if either (think of something that is straightforward to check) or double eights appear in the rest of the digits.

def double_eights(n):
    """ Returns whether or not n has two digits in row that
    are the number 8. Assume n has at least two digits in it.

    >>> double_eights(1288)
    True
    >>> double_eights(880)
    True
    >>> double_eights(538835)
    True
    >>> double_eights(284682)
    False
    >>> double_eights(588138)
    True
    >>> double_eights(78)
    False
    >>> from construct_check import check
    >>> # ban iteration
    >>> check(LAB_SOURCE_FILE, 'double_eights', ['While', 'For'])
    True
    """
    "*** YOUR CODE HERE ***"

Use Ok to test your code:

python3 ok -q double_eights

Q8: Making Onions

Write a function make_onion that takes in two one-argument functions, f and g. It returns a function that takes in three arguments: x, y, and limit. The returned function returns True if it is possible to reach y from x using up to limit calls to f and g, and False otherwise.

For example, if f adds 1 and g doubles, then it is possible to reach 25 from 5 in four calls: f(g(g(f(5)))).

def make_onion(f, g):
    """Return a function can_reach(x, y, limit) that returns
    whether some call expression containing only f, g, and x with
    up to limit calls will give the result y.

    >>> up = lambda x: x + 1
    >>> double = lambda y: y * 2
    >>> can_reach = make_onion(up, double)
    >>> can_reach(5, 25, 4)      # 25 = up(double(double(up(5))))
    True
    >>> can_reach(5, 25, 3)      # Not possible
    False
    >>> can_reach(1, 1, 0)      # 1 = 1
    True
    >>> add_ing = lambda x: x + "ing"
    >>> add_end = lambda y: y + "end"
    >>> can_reach_string = make_onion(add_ing, add_end)
    >>> can_reach_string("cry", "crying", 1)      # "crying" = add_ing("cry")
    True
    >>> can_reach_string("un", "unending", 3)     # "unending" = add_ing(add_end("un"))
    True
    >>> can_reach_string("peach", "folding", 4)   # Not possible
    False
    """
    def can_reach(x, y, limit):
        if limit < 0:
            return ____
        elif x == y:
            return ____
        else:
            return can_reach(____, ____, limit - 1) or can_reach(____, ____, limit - 1)
    return can_reach

Use Ok to test your code:

python3 ok -q make_onion

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

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

In addition, all students who are not in the mega lab must complete this attendance form. Submit this form each week, whether you attend lab or missed it for a good reason. The attendance form is not required for mega section students.