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Iterative Exponentiation

Iterative Exponentiation

Project Goals

This engineering effort invites you to combine what you learned about the basics of Python programming to implement a program that can use a for loop and/or a while loop to perform a series of exponentiations. The function that you will implement will repeatedly perform an exponentiation and then save the result of the computation in the list. Ultimately, the output of the program should confirm that it is possible to use either a for loop or a while loop to produce the same program output! As you learn more about how to translate mathematical equations into Python functions and you continue to enhance your technical skills, you will implement and test a complete Python program while using tools such as the VS Code text editor, a terminal window, and the Poetry package manager.

Project Access

If you are a student enrolled in a Computer Science class at Allegheny College, you can access this assignment by clicking the link provided to you in Discord. Once you click this link it will create a GitHub repository that you can clone to your computer by following the general-purpose instructions in the description of the technical skills. Specifically, you will need to use the git clone command to download the project from GitHub to your computer. Now you are ready to add source code and documentation to the project!

Note

If you are an emerging proactive programmer who is not enrolled in a Computer Science class at Allegheny College, you can still work on this assignment! To get started, you should click the "Use this template" button in the iterative-exponentiation-starter GitHub repository and create your own version of this project's source code. After creating your GitHub repository, you can follow all of the other steps!

Expected Output

This project invites you to implement a program called iterator. The program has two flags called --forloop and --whileloop that control the type of iteration construct with which the program performs iterative exponentiation. To best understand the program's behavior it is nice to observe how it operates when given different command-line arguments. For instance, the command poetry run iterator --forloop --whileloop --minimum 0 --maximum 2 produces the following output. Can you see the pattern? Please note that the use of both the flags --forloop and --whileloop means that the program will iteratively compute the powers of two with both a for and while loop.

Calculating the powers of 2 from 0 to 2 with iteration:

  Should I use a for loop? Yes
  Should I use a while loop? Yes

  Here is the output with the for loop.

   2**0 = 1
   2**1 = 2

  Here is the output with the while loop.

   2**0 = 1
   2**1 = 2

Wow, all of that iteration was exhausting! 😂

It is important to note that the Python program can also produce the output of the powers of two using a single type of iteration construct. For instance, the command poetry run iterator --forloop --minimum 0 --maximum 5 produces the following output demonstrating that the program only ran a for loop. As in the previous output example, this output shows that the program uses the ** operator to raise 2 to the power of a number such as 0, 1, and 2. Both of these output examples also show that the program should contain several lines of diagnostic output that make it clear how it interpreted the command-line arguments before it starting to perform iterative exponentiation.

Calculating the powers of 2 from 0 to 5 with iteration:

  Should I use a for loop? Yes
  Should I use a while loop? No

  Here is the output with the for loop.

   2**0 = 1
   2**1 = 2
   2**2 = 4
   2**3 = 8
   2**4 = 16

Wow, all of that iteration was exhausting! 😂

While all of the prior examples show that the iterator works when you use 0 as the value for the --minimum, it is also important to point out that it should work when you increase the value for this parameter. For instance, when you run poetry run iterator --forloop --minimum 2 --maximum 10 it should produce the following output. Note that this output shows that the first exponentiation that the iterator performs is 2**2 = 4 instead of starting with 2**0 = 1 as was the case in the previous runs.

Calculating the powers of 2 from 2 to 10 with iteration:

  Should I use a for loop? Yes
  Should I use a while loop? No

  Here is the output with the for loop.

   2**2 = 4
   2**3 = 8
   2**4 = 16
   2**5 = 32
   2**6 = 64
   2**7 = 128
   2**8 = 256
   2**9 = 512

Wow, all of that iteration was exhausting! 😂
Note

Remember, if you want to run iterator you must use your terminal to go into the GitHub repository containing this project and then go into the iterator directory that contains the project's source code. Finally, remember that before running the program you must run poetry install to add the dependencies. If you run into errors when using a poetry run command you can often resolve them by deleting the .venv directry and the poetry.lock file and then trying poetry install again.

Adding Functionality

If you study the file iterator/iterator/main.py you will see that it has many TODO markers that designate the parts of the program that you need to implement before iterator will produce the correct output. If you run the program before adding all of the source code required by the TODO markers then iterator will neither produce the correct output or pass the test suite. Ultimately, you are invited to add the required functionality to the functions that have the following signatures. It is important to note that you should not change the signature of these functions in your own implementation unless you receive prior approval from the course instructor.

  • Functions in the display module:
    • def convert_bool_to_answer(argument: bool)
    • def display_list(values: List, indent="")
  • Functions in the iterate module:
    • def calculate_powers_of_two_for_loop(minimum: int, maximum: int)
    • def calculate_powers_of_two_while_loop(minimum: int, maximum: int)

When you are finished implementing both of the iterative approaches, please take time to evaluate each of them, comparing and contrasting their syntactic structure. Which one do you think is easier to understand? Why? Can you develop any good rules of thumb that suggest when it is better to use one type of loop over the other loop type?

Finally, the following source code segment shows how the main module should implement the Python source code that calls the calculate_powers_of_two_for_loop and calculate_powers_of_two_while_loop functions. Lines 1 and 7 of this source code segment ensure that the correct function in the iterate module is called. Next, lines 2 and 3 and 8 and 9 produce the correct labels that will appear in the console output. Finally, lines 4 and 10 call the correct iteration function depending on the command-line arguments specified by the person running the program. Once either the calculate_powers_of_two_for_loop or calculate_powers_of_two_while_loop function returns a list of values, the display function will show the contents of that list with the amount of indentation specified in the string constant.

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if forloop is True:
    typer.echo("  Here is the output with the for loop.")
    typer.echo("")
    forloop_list = iterate.calculate_powers_of_two_for_loop(minimum, maximum)
    display.display_list(forloop_list, "   ")
    typer.echo("")
if whileloop is True:
    typer.echo("  Here is the output with the while loop.")
    typer.echo("")
    whileloop_list = iterate.calculate_powers_of_two_while_loop(minimum, maximum)
    display.display_list(whileloop_list, "   ")
    typer.echo("")
Note

Before you start to implement the source code required by this project is worth pausing to remember that the instructor will give advance feedback to any learner who requests it through GitHub and Discord at least 24 hours before the project's due date! Seriously, did you catch that? This policy means that you can have a thorough understanding of ways to improve your project before its final assessment! To learn more about this opportunity, please read the assessment strategy for this site.

Running Checks

As you continue to add and confirm the correctness of iterator's functionality, you should study the source code in the pyproject.toml file. This file contains the specification of several tasks that will help you to easily run checks on your Python source code. Now, you can run commands like poetry run task lint to automatically run all of the linters designed to check the Python source code in your program and its test suite. You can also use the command poetry run task black to confirm that your source code adheres to the industry-standard format defined by the black tool. If it does not adhere to the standard then you can run the command poetry run fixformat and it will automatically reformat the source code. By following a tutorial, you can configure VS Code to use the black tool to automatically reformat the source code when you save a file.

Along with running tasks like poetry run task lint, you can leverage the relevant instructions in the technical skills to run the command gatorgrade --config config/gatorgrade.yml to check your work. If your work meets the baseline requirements and adheres to the best practices that proactive programmers adopt you will see that all the checks pass when you run gatorgrade. You can study the config/gatorgrade.yml file in your repository to learn how the GatorGrade program runs GatorGrader to automatically check your program and technical writing.

Note

Don't forget that when you commit source code or technical writing to your GitHub repository for this project, it will trigger the run of a GitHub Actions workflow. If you are a student at Allegheny College, then running this workflow consumes build minutes for the course's organization! As such, you should only commit to your repository once you have made substantive changes to your project and you are ready to confirm its correctness. Before you commit to your repository, you can should run checks on your own computer by running gatorgrade --config config/gatorgrade.yml.

Project Reflection

Once you have finished both of the previous technical tasks, you can use a text editor to answer all of the questions in the writing/reflection.md file. For instance, you should provide the output of the Python program in a fenced code block, explain the meaning of the Python source code segments that you implemented and used, and answer all of the other questions about your experiences in completing this project.

Project Assessment

Since this project is an engineering effort, it is aligned with the evaluating and creating levels of Bloom's taxonomy. You can learn more about how a proactive programming expert will assess your work by examining the assessment strategy. From the start to the end of this project you may make an unlimited number of reattempts at submitting source code and technical writing that meet every aspect of the project's specification.

Note

Before you finish all of the required deliverables required by this project is worth pausing to remember that the instructor will give advance feedback to any learner who requests it through GitHub and Discord at least 24 hours before the project's due date! Seriously, did you catch that? This policy means that you can have a thorough understanding of ways to improve your project before its final assessment! To learn more about this opportunity, please read the assessment strategy for this site.

Seeking Assistance

Emerging proactive programmers who have questions about this project are invited to ask them in either the GitHub discussions forum or the Proactive Programmers Discord server. Before you ask your question, please read the advice concerning how to best participate in the Proactive Programmers community. If you find a mistake in this project, please describe it and propose a solution by creating an issue in the GitHub Issue Tracker.


Updated: 2023-03-17   Created: 2021-08-12
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