Lab 3 Solutions

Solution Files

Submit

In order to facilitate studying for the exam, solutions to this lab are released with the lab. We encourage you to try out the problems first on your own before referencing the solutions as a guide.

Note: You do not need to run python ok --submit to receive credit for this assignment.

All Questions Are Optional

The questions in this assignment are not graded, but they are highly recommended to help you prepare for the upcoming exam. You will receive credit for this lab even if you do not complete these questions.

The questions in this assignment are not graded, but they are highly recommended to help you prepare for the upcoming exam. You will receive credit for this lab even if you do not complete these questions.

Suggested Questions


Walkthrough Videos

These videos provide detailed walkthroughs of the problems presented in this lab.

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Control

Q1: Ordered Digits

Implement the function ordered_digits, which takes as input a positive integer and returns True if its digits, read left to right, are in non-decreasing order, and False otherwise. For example, the digits of 5, 11, 127, 1357 are ordered, but not those of 21 or 1375.

Note: You can solve this with either iteration or recursion. We recommend trying both for practice purposes but you will credit for either one.

def ordered_digits(x):
    """Return True if the (base 10) digits of X>0 are in non-decreasing
    order, and False otherwise.

    >>> ordered_digits(5)
    True
    >>> ordered_digits(11)
    True
    >>> ordered_digits(127)
    True
    >>> ordered_digits(1357)
    True
    >>> ordered_digits(21)
    False
    >>> result = ordered_digits(1375) # Return, don't print
    >>> result
    False

>>> cases = [(1, True), (9, True), (10, False), (11, True), (32, False), ... (23, True), (99, True), (111, True), (122, True), (223, True), ... (232, False), (999, True), ... (13334566666889, True), (987654321, False)] >>> [ordered_digits(s) == t for s, t in cases].count(False) 0
"""
last = x % 10 x = x // 10 while x > 0 and last >= x % 10: last = x % 10 x = x // 10 return x == 0

Use Ok to test your code:

python3 ok -q ordered_digits

We split off each digit in turn from the right, comparing it to the previous digit we split off, which was the one immediately to its right. We stop when we run out of digits or we find an out-of-order digit.

Q2: K Runner

An increasing run of an integer is a sequence of consecutive digits in which each digit is larger than the last. For example, the number 123444345 has four increasing runs: 1234, 4, 4 and 345. Each run can be indexed from the end of the number, starting with index 0. In the example, the 0th run is 345, the first run is 4, the second run is 4 and the third run is 1234.

Implement get_k_run_starter, which takes in integers n and k and returns the 0th digit of the kth increasing run within n. The 0th digit is the leftmost number in the run. You may assume that there are at least k+1 increasing runs in n.

def get_k_run_starter(n, k):
    """Returns the 0th digit of the kth increasing run within n.
    >>> get_k_run_starter(123444345, 0) # example from description
    3
    >>> get_k_run_starter(123444345, 1)
    4
    >>> get_k_run_starter(123444345, 2)
    4
    >>> get_k_run_starter(123444345, 3)
    1
    >>> get_k_run_starter(123412341234, 1)
    1
    >>> get_k_run_starter(1234234534564567, 0)
    4
    >>> get_k_run_starter(1234234534564567, 1)
    3
    >>> get_k_run_starter(1234234534564567, 2)
    2
    """
    i = 0
    final = None
while i <= k:
while n > 10 and (n % 10 > (n // 10) % 10):
n = n // 10
final = n % 10
i = i + 1
n = n // 10
return final

Use Ok to test your code:

python3 ok -q get_k_run_starter

Video walkthrough:

YouTube link

Higher Order Functions

These are some utility function definitions you may see being used as part of the doctests for the following problems.

from operator import add, mul

square = lambda x: x * x

identity = lambda x: x

triple = lambda x: 3 * x

increment = lambda x: x + 1

Q3: Make Repeater

Implement the function make_repeater so that make_repeater(func, n)(x) returns func(func(...func(x)...)), where func is applied n times. That is, make_repeater(func, n) returns another function that can then be applied to another argument. For example, make_repeater(square, 3)(42) evaluates to square(square(square(42))).

def make_repeater(func, n):
    """Return the function that computes the nth application of func.

    >>> add_three = make_repeater(increment, 3)
    >>> add_three(5)
    8
    >>> make_repeater(triple, 5)(1) # 3 * 3 * 3 * 3 * 3 * 1
    243
    >>> make_repeater(square, 2)(5) # square(square(5))
    625
    >>> make_repeater(square, 4)(5) # square(square(square(square(5))))
    152587890625
    >>> make_repeater(square, 0)(5) # Yes, it makes sense to apply the function zero times!
    5
    """
g = identity while n > 0: g = composer(func, g) n = n - 1 return g # Alternative solutions def make_repeater2(func, n): def inner_func(x): k = 0 while k < n: x, k = func(x), k + 1 return x return inner_func
def composer(func1, func2): """Return a function f, such that f(x) = func1(func2(x)).""" def f(x): return func1(func2(x)) return f

Use Ok to test your code:

python3 ok -q make_repeater

Solution using composer:

We create a new function in every iteration of the while statement by calling composer.

Solution not using composer:

We create a single inner function that contains the while logic needed to do calculations directly, as opposed to creating another function for every while loop iteration.

Q4: Apply Twice

Using make_repeater define a function apply_twice that takes a function of one argument as an argument and returns a function that applies the original function twice. For example, if inc is a function that returns 1 more than its argument, then double(inc) should be a function that returns two more:

def apply_twice(func):
    """ Return a function that applies func twice.

    func -- a function that takes one argument

    >>> apply_twice(square)(2)
    16
    """
return make_repeater(func, 2)

Use Ok to test your code:

python3 ok -q apply_twice

Using composer from class, the body of apply_twice can also be written as return composer(func, func).

Q5: It's Always a Good Prime

Implement div_by_primes_under, which takes in an integer n and returns an n-divisibility checker. An n-divisibility-checker is a function that takes in an integer k and returns whether k is divisible by any integers between 2 and n, inclusive. Equivalently, it returns whether k is divisible by any primes less than or equal to n.

Review the Disc 01 is_prime problem for a reminder about prime numbers.

You can also choose to do the no lambda version, which is the same problem, just with defining functions with def instead of lambda.

Hint: If struggling, here is a partially filled out line for after the if statement:

checker = (lambda f, i: lambda x: __________)(checker, i)
def div_by_primes_under(n):
    """
    >>> div_by_primes_under(10)(11)
    False
    >>> div_by_primes_under(10)(121)
    False
    >>> div_by_primes_under(10)(12)
    True
    >>> div_by_primes_under(5)(1)
    False
    """
    checker = lambda x: False
i = 2
while i <= n:
if not checker(i):
checker = (lambda f, i: lambda x: x % i == 0 or f(x))(checker, i)
i = i + 1
return checker
def div_by_primes_under_no_lambda(n): """ >>> div_by_primes_under_no_lambda(10)(11) False >>> div_by_primes_under_no_lambda(10)(121) False >>> div_by_primes_under_no_lambda(10)(12) True >>> div_by_primes_under_no_lambda(5)(1) False """ def checker(x): return False
i = 2
while i <= n:
if not checker(i):
def outer(f, i):
def inner(x):
return x % i == 0 or f(x)
return inner
checker = outer(checker, i)
i = i + 1
return checker

Use Ok to test your code:

python3 ok -q div_by_primes_under
python3 ok -q div_by_primes_under_no_lambda

Q6: Church numerals

The logician Alonzo Church invented a system of representing non-negative integers entirely using functions. The purpose was to show that functions are sufficient to describe all of number theory: if we have functions, we do not need to assume that numbers exist, but instead we can invent them.

Your goal in this problem is to rediscover this representation known as Church numerals. Church numerals are a way to represent non-negative integers via repeated function application. Specifically, church numerals (such as zero, one, and two below) are functions that take in a function f and return a new function which, when called, repeats f a number of times on some argument x. Here are the definitions of zero, as well as a successor function, which takes in a church numeral n as an argument and returns a function that represents the church numeral one higher than n:

def zero(f):
    return lambda x: x

def successor(n):
    return lambda f: lambda x: f(n(f)(x))

First, define functions one and two such that they have the same behavior as successor(zero) and successsor(successor(zero)) respectively, but do not call successor in your implementation.

Next, implement a function church_to_int that converts a church numeral argument to a regular Python integer.

Finally, implement functions add_church, mul_church, and pow_church that perform addition, multiplication, and exponentiation on church numerals.

def one(f):
    """Church numeral 1: same as successor(zero)"""
return lambda x: f(x)
def two(f): """Church numeral 2: same as successor(successor(zero))"""
return lambda x: f(f(x))
three = successor(two) def church_to_int(n): """Convert the Church numeral n to a Python integer. >>> church_to_int(zero) 0 >>> church_to_int(one) 1 >>> church_to_int(two) 2 >>> church_to_int(three) 3 """
return n(lambda x: x + 1)(0)
def add_church(m, n): """Return the Church numeral for m + n, for Church numerals m and n. >>> church_to_int(add_church(two, three)) 5 """
return lambda f: lambda x: m(f)(n(f)(x))
def mul_church(m, n): """Return the Church numeral for m * n, for Church numerals m and n. >>> four = successor(three) >>> church_to_int(mul_church(two, three)) 6 >>> church_to_int(mul_church(three, four)) 12 """
return lambda f: m(n(f))
def pow_church(m, n): """Return the Church numeral m ** n, for Church numerals m and n. >>> church_to_int(pow_church(two, three)) 8 >>> church_to_int(pow_church(three, two)) 9 """
return n(m)

Use Ok to test your code:

python3 ok -q church_to_int
python3 ok -q add_church
python3 ok -q mul_church
python3 ok -q pow_church

Church numerals are a way to represent non-negative integers via repeated function application. The definitions of zero, one, and two show that each numeral is a function that takes a function and repeats it a number of times on some argument x.

The church_to_int function reveals how a Church numeral can be mapped to our normal notion of non-negative integers using the increment function.

Addition of Church numerals is function composition of the functions of x, while multiplication is composition of the functions of f.

Environment Diagrams

Q7: Doge

Draw the environment diagram for the following code.

wow = 6

def much(wow):
    if much == wow:
        such = lambda wow: 5
        def wow():
            return such
        return wow
    such = lambda wow: 4
    return wow()

wow = much(much(much))(wow)

You can check out what happens when you run the code block using Python Tutor. Please ignore the “ambiguous parent frame” message on step 18. The parent is in fact f1.

Q8: Environment Diagrams - Challenge

These questions were originally developed by Albert Wu and are included here for extra practice. We recommend checking your work in PythonTutor after filling in the diagrams for the code below.

Challenge 1

Draw the environment diagram that results from executing the code below.

Guiding Notes: Pay special attention to the names of the frames!

Multiple assignments in a single line: We will first evaluate the expressions on the right of the assignment, and then assign those values to the expressions on the left of the assignment. For example, if we had x, y = a, b, the process of evaluating this would be to first evaluate a and b, and then assign the value of a to x, and the value of b to y.

def funny(joke):
    hoax = joke + 1
    return funny(hoax)

def sad(joke):
    hoax = joke - 1
    return hoax + hoax

funny, sad = sad, funny
result = funny(sad(1))

In the line funny, sad = sad, funny, we will end up with the result that the variable funny now references the function whose intrinsic name (the name with which it was defined) is sad, and the variable sad now references the function whose intrinsic name is funny.

Thus, when we call funny(sad(1)) in the last line, we will evaluate the variable funny to be the function called sad (defined from def sad(joke): ...). The argument we want to pass into the function call is sad(1), where the variable sad references the function funny (defined from def funny(joke): ...).

Thus, our first function frame will be to evaluate funny(1) where this funny represents the intrinsic name of the actual function we're calling.

Inside of funny, we have the call funny(hoax), which will prompt us to look up what funny as a variable points to. No local variable in our function frame is called funny, so we go to the global frame, where the variable funny points to the function sad. As a result we will call sad on the value hoax.

The return value of this function call then gets passed into a function call to sad (where this sad represents the intrinsic name of the function), and finally the return value of this function call to sad will be assigned to result in the global frame.

Video walkthrough:

YouTube link

Challenge 2

Draw the environment diagram that results from executing the code below.

def double(x):
    return double(x + x)

first = double

def double(y):
    return y + y

result = first(10)

Video walkthrough:

YouTube link