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Numerical Data

Numerical Data

Project Goals

This assignment invites you to run and observe two Python programs called determine-even-odd and floating-point-confusion. Instead of using the Poetry tool for managing dependencies and packaging these programs, which the technical skills advise as a best practice, these programs are scripts, without any dependencies on other Python packages, that you can run through the Python interpreter. As you learn a new way to run a Python program and use tools like VS Code and a terminal window, this project offers you the opportunity to ensure that you understand how to (i) use the modular arithmetic operation (i.e., %) to determine if a number is even or odd and (ii) correctly multiply and add with float-point variables. Ready for some programming fun? Okay, let's get started!

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 so that you can refine your understanding of how to process numerical data in Python!

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" icon in the numerical-data-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!

Code Survey

If you change into the source/ directory of your GitHub repository, you will see two Python files called determine-even-odd.py and floating-point-confusion.py. You can run the determine-even-odd.py program by typing python determine-even-odd.py in your terminal window. What output does the program produce? Can you explain why it produces this output? The key to understanding this segment of source code is to notice that line 1 uses the modular arithmetic operation, written as %, to compute the remainder that results from dividing the variable called value by 2. If 2 divides value evenly, then the remainder will be 0 and this code segment concludes that the number is even. However, if the remainder resulting from dividing value by 2 is not equal to 0, then there is clear evidence that value is odd.

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if value % 2 == 0:
    return "even"
else:
    return "odd"

The second program is called floating-point-confusion.py because it illustrates some of the initially confusing aspects of using Python's float data type to store decimal values. To understand this program better, it is important to note that lines 1 and 2 in the following segment illustrate the respective use of addition and multiplication with float-point numbers. You can run this program by typing python floating-point-confusion.py in your terminal. Can you explain why it produces this output and what it reveals about the challenges of doing arithmetic with float-point numbers?

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for _ in range(10):
    number = number + 0.1
multiply_number = 10.0 * 0.1
Note

Don't forget that if you want to run one of the provided Python scripts program you must use your terminal window to first go into the GitHub repository containing this project and then go into the source/ directory that contains the project's source code. You should also use VS Code to study the provided source code to ensure that you understand why it produces the output that you see in your terminal window.

Running Checks

Since this project does not use Poetry to manage project dependencies and virtual environments, it does not support the use of commands like poetry run task test. However, 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 GatorGrade runs GatorGrader to automatically check your program and technical writing.

Note

Did you know that GatorGrade and GatorGrader are open-source Python programs implemented by Proactive Programmers? If you finish this source code survey and have extra time, please brainstorm some new features that you think these two tools should have, explain your idea by raising an issue in the relevant project's GitHub repository, and take the first step towards implementing and testing your idea. If the maintainers of these tools accept your new feature then you will have helped to improve the experience of other people who use GatorGrade and GatorGrader!

Project Reflection

Once you have finished all of the previous technical tasks, you can use a text editor to answer all of the questions in the writing/reflection.md file. Since this is a source code survey, you should provide output from running each of the provided Python programs on your own laptop and then explain how the program's source code produced that output. A specific goal for this project is to ensure that you can explain how Python programs should correctly use modular arithmetic and floating point numbers to achieve a practical goal.

Project Assessment

Since this project is source code survey, it is aligned with the remembering and understanding 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 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 at Allegheny College 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 thoroughly understand the 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: 2022-08-19   Created: 2021-09-16
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