After your modification to getitem, what is the running time of the function? –

Lab 1: Arrays
Recommended Due Date: Thursday, September 17, 11:59pm
Submission
 Submit all code and answers to questions in a single zip file to the Lab 1 assignment
folder on Kodiak.
Goal: Analyze and compare the operations of dynamically-sized arrays.
Introduction
In recent lecture periods, we built the DynamicArray class in order to gain a better
understanding of how lists work in Python. We may not be able to see the code that defines
a Python list, but we can make educated guesses about what the methods of list might
look like. Using these guesses, we can recognize why the efficiency of Python list methods
are what they are. In this lab, we will continue this process, making further additions to our
list-substitute, DynamicArray.
Part I
The DynamicArray class is provided in dynamic_array.py. Modify this class as described
below. Make sure that each new function has a comment describing its purpose and what
each parameter represents.
 Modify the __getitem__ method so that the DynamicArray class can use negative
indices just like a Python list. Make sure to raise exceptions if/when appropriate.
o Hint: Remember that the DynamicArray may have extra capacity which you
shouldn’t be counting when trying to figure out the correct index.
 Implement the __setitem__ method, which allows indexing notation to be used on
the left side of an assignment statement. The header for this method is given below,
where k is the index and val is the item to be assigned to that index. You only need
to make this work for positive values of k; don’t worry about negative indices.
However, you should raise an exception if k is too large.
def __setitem__(self, k, val):
 Implement a pop() method that removes and returns the last element of the array.
The method should also shrink the capacity C of the array by half any time the
number of elements in the array goes below C/4. Make sure to raise exceptions
if/when appropriate. Your solution must not call remove().
 Implement the __eq__ method, which will allow us to compare two DynamicArrays
using the == operator. This method should return True if the contents of both
DynamicArrays are identical, including its length and the order of the elements.
Otherwise, it should return False. The header for this method is given below, where
self will be whichever DynamicArray is on the left side of the operator, and other
will be the DynamicArray on the right side.
def __eq__(self, other):
Create lab1.py in which you demonstrate the use of these methods. The table below shows
proper usage of each “special” (double underscore) method.
__getitem__ Any use of [] notation, except assigning to an index and using del, like:
print(myarray[3]) or y = myarray[0] + myarray[-1]
__setitem__ Assigning to an index using bracket notation, like:
myarray[0] = ‘bears’
__eq__ Comparison of two Dynamic Arrays using ==, like:
if myfirstarray == mysecondarray:
print(‘They match!’)
Part II
Two new methods for the DynamicArray class are included in lab1b.py. Copy those
methods into the DynamicArray class in dynamicarray.py. You may wish to test these
methods out before answering the questions in Part III.
There is no deliverable for this part.
Part III
Answer the questions below. Put your answers into a txt, Word, or PDF file.
Questions 1-4 refer to your work in Part I.
1. After your modification to getitem, what is the running time of the function? Is
this the same or different than it was before?
2. What is the running time of your __setitem__ function?
3. What is the running time of your pop function?
4. What is the running time of your __eq__ function?
Questions 5-6 refer to the functions given in Part II.
5. Both functions from Part II do the exact same task in different ways. What do they
do? What would be a good name for these methods? (Your answer should tell me the
overall effect of the functions. Do not walk me through them line-by-line.)
6. What are the running times of the lab1_v1 and lab1_v2 functions? Assume that any
use of the random module is ?(1).
What to Submit
Submit the following in a single zip file:
 Submit all code: lab1.py and dynamic_array.py
 Submit a file containing the answers to the questions in Part III.
Rubric
Grade Overall Part I Part III
4
A 4 in Part I, and at
least a 3 in Part III.
Code contains at most
minor bugs that only
occur in edge cases.
Code is adequately
commented.
Correct answers to all
questions.
3
At least a 3 for Part I
and a 2 for Part III.
One function does not
behave as expected.
Other functions have
only minor bugs.
Adequate comments.
–OR—
All functions have only
minor bugs, but lacks
sufficient comments.
Correct answers to all
but one question.
2
At least a 2 for Part I
and a 1 for Part III.
More than one function
has a significant bug
impairing its use or
violating given
instructions.
May lack sufficient
comments.
Correct answers to some
questions.
1
At least a 1 for Part I
and Part III.
Most functions have a
significant bug impairing
its use or violating given
instructions.
Attempts all questions.
0
0 for Part I or no
submission.
Most functions cause
errors.
No submission

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Lab 1