cs102-F2020-lab2-starter

Objectives
Introduction
Continuous Learning
Assignment Reminders
Accessing the Assignment
Laboratory Assignment Tasks
Automated Checks with GatorGrader
Assignment Assessment
Advance Feedback on an Assignment
Discussion of a Graded Assignment
Additional Resources

Objectives

The learning objectives for this laboratory assignment are as follows:

To configure Git and GitHub on your laptop and on the GitHub servers
To transfer files from your laptop to your GitHub repository
To use a Docker container to run the automated checks performed by GatorGrader
To install the programs that you need to support the creation of a Python program
To use a terminal window to run a Python program and observe its output
To use your text editor and a terminal window to repair a broken Python program
To use your text editor and a terminal window to run a test suite for a Python program
To practice translating a mathematical equation to its implementation in a Python program

Introduction

Designed for use with GitHub Classroom and GatorGrader, this repository contains a laboratory assignment for an introductory computer science class that uses the Python programming language. The source code and technical writing for this assignment must pass tests set by the GatorGrader tool. When you use the git commit and git push commands to transfer your source code to your GitHub repository, GitHub Actions will initialize a build of your assignment, checking to see if it meets all of the requirements. If both your source code and writing meet all of the established requirements, then you will see a green ✔ in the listing of commits in GitHub. If your submission does not meet the requirements, a red ❌ will appear instead. Please note that, at the option of the course instructor, some checks may be run in GitHub Actions that are not run locally by the GatorGrader tool.

Continuous Learning

If you have not done so already, please read all of the relevant GitHub Guides that explain how to use many of the features that GitHub provides. In particular, please make sure that you have read the following GitHub guides: Mastering Markdown, Hello World, and Documenting Your Projects on GitHub. Each of these guides will help you to understand how to use both GitHub and GitHub Classroom.

Students who want to learn more about how to use Docker should review the Docker Documentation. Students are also encouraged to review the documentation for their text editor, which is available in the VS Code docs. You should also review the Git documentation to learn more about how to use the Git command-line client. In addition to talking with the instructor and technical leader for your course, students are encouraged to search StackOverflow for answers to their technical questions.

As outlined in the course schedule in the course planning repository, students should also read all of the assigned readings for up to and including the week of the semester on which this laboratory assignment was assigned.

Assignment Reminders

Follow each step carefully. Slowly read each sentence in this document, making sure that you precisely follow each instruction. Take notes about each step that you attempt, recording your questions and ideas and the challenges that you faced. If you are stuck, then please tell a technical leader or the course instructor what assignment step you recently completed.
Regularly ask and answer questions. Please log into Slack at the start of the laboratory session and then join the appropriate channel. If you have a question about one of the steps in an assignment, then you can post it to the designated channel, discussing your questions through both Slack and the Google Meet designated for the class.
Store your files in GitHub. Starting with this laboratory assignment, you will be responsible for storing all of your files (e.g., Python source code and Markdown-based writing) in a Git repository using GitHub Classroom. Please verify that you have saved your source code in your Git repository by using git status to ensure that everything is updated. You can see if your assignment submission meets the established correctness requirements by using the provided checking tools on your local computer and by checking the commits in GitHub.
Keep all of your files. Don't delete your programs, output files, and written reports after you submit them through GitHub; you will need them again when you study for the course assessments and work on the other laboratory, practical, and technical challenge assignments.
Hone your technical writing skills. Computer science assignments require to you write technical documentation and descriptions of your experiences when completing each task. Take extra care to ensure that your writing is interesting and both grammatically and technically correct, remembering that computer scientists must effectively communicate and collaborate with their team members and the student technical leaders and course instructor.
Review the Honor Code on the syllabus. While you may discuss your assignments with others, copying source code or technical writing is a violation of Allegheny College's Honor Code.

Accessing the Assignment

To access this assignment, you should go into the #announcements channel in our Slack workspace and find the announcement that provides a link for it. Copy this link and paste it into your web browser. Now, you should accept the laboratory assignment and see that GitHub Classroom created a new GitHub repository for you to access the assignment's starting materials and to store the completed version of your assignment. Specifically, to access your new GitHub repository for this assignment, please click the green "Accept" button and then click the link that is prefaced with the label "Your assignment has been created here". If you accepted the assignment and correctly followed these steps, you should have created a GitHub repository with a name like Allegheny-Computer-Science-102-Fall-2020/computer-science-102-fall-2020-lab-2-gkapfham. Unless you provide the course instructor with documentation of the extenuating circumstances that you are facing, not accepting the assignment means that you automatically receive a failing grade for all of its components.

Before you move to the next step of this laboratory assignment, please make sure that you read all of the content on the web site for your new GitHub repository, paying close attention to the technical details about the commands that you will type and the output that your program must produce. Now you are ready to download the starting materials to your laboratory computer. Click the "Clone or download" button and, after ensuring that you have selected "Clone with SSH", please copy this command to your clipboard. To enter into your course directory directory you should now type cd cs102F2020. Next, you can type the either ls (on either MacOS or Linux) or dir (on Windows 10 Pro or Windows 10 Enterprise) and see that there are no files or directories inside of this directory. By typing git clone in your terminal and then pasting in the string that you copied from the GitHub site you will "download" all of the code for this assignment. For instance, if the course instructor ran the git clone command in the terminal, it would look like:

git clone git@github.com:Allegheny-Computer-Science-102-F2020/computer-science-102-fall-2020-lab-2-gkapfham.git

After this command finishes, you can use cd to change into the new directory. If you want to "go back" one directory from your current location, then you can type the command cd ... Finally, please continue to use the cd and ls commands to explore the files that you automatically downloaded from GitHub. If one of the aforementioned commands does not work correctly, then it is possible that your terminal window is not up-to-date or not configured correctly. In this case, please share your specific error messages with the instructor, ultimately working to master the use of terminal commands. What files and directories do you see? What do you think is their purpose? Spend some time exploring, telling your discoveries to a student technical leader.

Laboratory Assignment Tasks

Installing Programs that Support Python Programming

In order to implement a full-fledge Python program, you need to install the Poetry tool for dependency management and packaging of Python programs. After ensuring that you have Python 3.8 installed on your laptop, please follow the installation instructions for Poetry. For instance, you are using either MacOS or Linux you need to type the following command in your terminal window curl -sSL https://raw.githubusercontent.com/python-poetry/poetry/master/get-poetry.py | python. Importantly, this command will only work if you have already installed a program called curl. If you are using Windows 10 Pro then you will need to follow the PowerShell installation instructions on Poetry's web site.

Now, making sure that you are in your "home base" directory for this laboratory assignment, you need to install the dependencies for the rootfinder program that you will implement, debug, and observe. To complete this step you need to type cd rootfinder and then poetry install. What output did this command produce? What do you think that this step did? Why is important to type these commands? Make sure that you know the answers to these question before moving onto the next step of the assignment.

Calculating the Roots of a Quadratic Equation

To learn more about the equations for calculating the roots of a quadratic equation, please try out the quadratic formula calculator. For instance, input a=1, b=2, and c=1 into this calculator and see what answer it produces. After repairing your program, as explained in the next step of this assignment, it will also be possible for you to run the provided Python program by typing poetry run python rootfinder --a 1 --b 2 --c 1 in your terminal window and observing that the programs produces the following output:

Calculating the roots of a quadratic equation with:
   a = 1.0
   b = 2.0
   c = 1.0
   x_one = -1.0
   x_two = -1.0

Does the Python program produce the same output as the web site suggests it should? If it does, then try to run the program with different inputs by typing poetry run python rootfinder --a 1 --b 1 --c 1. In this case, your program should produce the following output:

Calculating the roots of a quadratic equation with:
   a = 1.0
   b = 1.0
   c = 1.0
   x_one = (-0.49999999999999994+0.8660254037844386j)
   x_two = (-0.5-0.8660254037844386j)

Is this output the same as what the web-based quadratic formula calculator produces? Please note that the output of this program includes numbers like -0.5-0.8660254037844386j, which means that this is a program that has an "imaginary" component. If you would like to learn more about "imaginary" numbers and how you can intuitively and geometrically interpret them, please read the visual and intuitive guide to imaginary numbers, bearing in mind that the referenced article uses the variable i and Python programs always use the variable j to mean the same thing. Finally, please make sure that you try your program with several additional inputs, always confirming that it works correctly by using the web-based quadratic formula calculator.

Repairing the Root Finding Program for Quadratic Equations

Upon receiving the Python program for today's laboratory assignment, you will notice that it does not produce the correct answer and, importantly, it does not produce all of the required output that was evident in the previous section. This means that you will need to follow the TODO markers in the program's source code to add in all of the required repairs, ensuring that the executed of commands like poetry run python rootfinder --a 1 --b 2 --c 1 and poetry run python rootfinder --a 1 --b 1 --c 1 produce the expected output.

Your GitHub repository for this assignment also contains a small Pytest test suite that provides the function under test with inputs and then checks to see if it produces the expected output. You can run the two tests in the test suite by typing the following command in your terminal window: poetry run pytest -s. If your program is implemented correctly, then it should produce output like the following:

=========================== test session starts ============================
platform linux -- Python 3.8.5, pytest-5.4.3, py-1.9.0, pluggy-0.13.1
rootdir: /home/gkapfham/working/teaching/github-classroom/Allegheny-Computer-Science-102-F2020/solutions/cs102-F2020-lab2-solution/rootfinder
collected 2 items

tests/test_rootfind.py ..

============================ 2 passed in 0.01s =============================

If your test suite has failing test cases in it, then you need to keep working to repair your program, ultimately ensuring that the test suites passes and that all runs of the program produce the expected output. If you are interested in doing so, please add more test cases to the tests/test_rootfind.py test suite so as to ensure that the rootfind.calculate_quadratic_equation_roots works correctly. Since it is also important to ensure that your program's source code adheres to all industry-standard best practices, you should run the command poetry run pylint rootfinder tests, fixing any issues that it raises. Finally, you can ensure that your program's source code has an industry-standard format by running the command poetry run black rootfinder tests.

Reflecting on the Laboratory Assignment

Once you have finished both of the previous technical tasks, use your 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 three provided commands, and answer all of the other questions about your experiences in completing this laboratory assignment.

Transferring Your Source code and Technical Writing to GitHub

As you are working on your laboratory assignment, please make sure that you use VSCode to regularly save your work and transfer it to the GitHub servers. For instance, please use the git commit command in your terminal window or use the similar feature in VSCode to "stage" your changes in your repository. Once you have committed your source code to your repository, you can use the git push command to transfer your work to your GitHub repository, making it available for the course instructor to assess. Please make sure that you regularly commit your source code and technical writing, using descriptive commit messages to explain how each commit changes the contents of the repository.

Automated Checks with GatorGrader

In addition to meeting all of the requirements outlined in this assignment sheet, your submission must pass the following checks that GatorGrader automatically assesses:

If GatorGrader's automated checks pass correctly, the tool will produce the output like the following in addition to returning a zero exit code (which you can access by typing the command echo $?). You will need to run GatorGrader in a Docker container by following the steps in the Using Docker section.

The command cd rootfinder; poetry run python rootfinder --a 1 --b 1 --c 1; cd .. executes correctly
The command output has exactly 6 lines
The file main.py exists in the rootfinder/rootfinder directory
The file reflection.md exists in the writing directory
The file rootfind.py exists in the rootfinder/rootfinder directory
The main.py in rootfinder/rootfinder has at least 2 multiple-line Python comment(s)
The main.py in rootfinder/rootfinder has at least 4 single-line Python comment(s)
The main.py in rootfinder/rootfinder has exactly 0 of the TODO fragment
The reflection.md in writing has at least 3 of the code_block tag
The reflection.md in writing has at least 400 word(s) in total
The reflection.md in writing has at least 4 of the code tag
The reflection.md in writing has exactly 0 of the Add Your Name Here fragment
The reflection.md in writing has exactly 0 of the TODO fragment
The reflection.md in writing has exactly 1 of the list tag
The reflection.md in writing has exactly 8 of the heading tag
The repository has at least 5 commit(s)
The rootfind.py in rootfinder/rootfinder has at least 2 multiple-line Python comment(s)
The rootfind.py in rootfinder/rootfinder has exactly 0 of the TODO fragment

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        ┃ Passed 18/18 (100%) of checks for cs102-F2020-lab2! ┃
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Assignment Assessment

Taking inspiration from the principles of specification-based grading, the grade that a student receives on a laboratory assignment will be based on whether or not it meets the standards for technical work in the fields of software engineering and discrete structures. Instead of receiving a single numerical or letter grade for this assignment, your grade will have the following components:

Percentage of Correct GatorGrader Checks Ranging Between 0 and 100: Your submitted Python program must pass all of GatorGrader's checks by, for instance, ensuring that it produces the correct output and has all of the required characteristics. Your technical writing must pass all of GatorGrader's checks about, for instance, the length of its output and its use of the required Markdown language features for technical writing. For this component of a laboratory assignment's grade, your work will receive a percentage, ranging from 0 to 100, that corresponds to the percentage of GatorGrader checks that automatically pass inside of a GitHub Actions build.
GitHub Actions Build Status of Either ✔ or ❌: Since additional checks on the Python source code and/or technical writing are encoded in GitHub Action workflows and, moreover, all of the GatorGrader checks are also run in GitHub Actions, your work will receive a checkmark grade if the last before-the-deadline build in GitHub Actions passes and a ✔ appears in the GitHub commit log instead of an ❌. The build status reported by GitHub Actions will only be a ✔ if the source code and technical writing in the GitHub repository pass all of both the GatorGrader checks and the additional checks.
Technical Writing Mastery of Either ✔ or ❌: Students will also receive a ✔ grade when the responses to the technical writing questions presented in the writing/reflection.md reveal a mastery of technical writing skills. To receive a checkmark grade, the submitted writing should have correct spelling, grammar, punctuation, and formatting in addition to following the rules of the Markdown language. Your work will receive a ✔ grade for this component if the build report from GitHub Actions reveals that there are no detected mistakes in the technical writing.
Technical Knowledge and Skill Mastery of Either ✔ or ❌: Students will also receive a checkmark grade when the GitHub repository reveals that they have mastered all of the technical knowledge and skills developed during the completion of the laboratory assignment. As a part of this grade, the instructor will assess aspects of the project including, but not limited to, the use of effective Python source code comments, correct Git commit messages, and accurate responses to the technical writing questions.

Advance Feedback on an Assignment

Students who wish to receive feedback on their work for any course assignment should first open an issue on the issue tracker for their assignment's GitHub repository, giving an appropriate title and description for the type of feedback that you would like the course instructor to provide. After creating this issue, you will see that GitHub has created a unique web site that references it. To alert the course instructor to the fact that the issue was created and that you want feedback on your work, please send it to him by a Slack direct message at least 24 hours in advance of the project's due date. After the instructor responds to the issue, please resolve all of the stated concerns and participate in the discussion until the issue is resolved and ultimately marked as closed.

Discussion of a Graded Assignment

Students who wish to receive feedback on their work for any graded course assignment should leave question in the same region of Github where the course instructor submitted the assignment's grade. For example, if the instructor submits your grade to a pull request in your repository for a laboratory assignment, then you should ask questions about your grade in that pull request, bearing in mind the need to @-mention the course instructor in the body of your comment. Students can continue to discuss the graded assignment with the course instructor until they understand all the technical topics that were the focus of the particular assignment.

Additional Resources

System Commands

This project invites students to enter system commands into a terminal window. This assignment uses Docker to deliver programs, such as gradle and the source code and packages needed to run GatorGrader, to a students' computer, thereby eliminating the need for a programmer to install them on their development workstation. Individuals who do not want to install Docker can optionally install of the programs mentioned in the Project Requirements section of this document.

Using Docker

Once you have installed Docker Desktop, with MacOS and Linux you can use the following docker run command to start gradle grade as a containerized application, using the DockaGator Docker image available on DockerHub.

docker run --rm --name dockagator \
  -v "$(pwd)":/project \
  -v "$HOME/.dockagator":/root/.local/share \
  gatoreducator/dockagator

The aforementioned command will use "$(pwd)" (i.e., the current working directory) as the project directory and "$HOME/.dockagator" as the cached GatorGrader directory. Please note that both of these directories must exist, although only the project directory must contain something. Generally, the project directory should contain the source code and technical writing for this assignment, as provided to a student by the instructor through GitHub. Additionally, the cache directory should not contain anything other than directories and programs created by DockaGator, thus ensuring that they are not otherwise overwritten during the completion of the assignment. To ensure that the previous command will work correctly, you should create the cache directory by running the command mkdir $HOME/.dockagator on the MacOS and Linux operating systems. However, if you are using the Windows operating system then you will instead need to type the command mkdir %HomeDrive%%HomePath%/.dockagator. Finally, if the above docker run command does not work correctly on the Windows operating system, you may need to instead run the following command to adapt to the differences in the cmd terminal window:

docker run --rm --name dockagator \
  -v "%cd%:/project" \
  -v "%HomeDrive%%HomePath%/.dockagator:/root/.local/share" \
  gatoreducator/dockagator

Here are some additional commands that you may need to run when using Docker:

docker info: display information about how Docker runs on your workstation
docker images: show the Docker images installed on your workstation
docker container list: list the active images running on your workstation
docker system prune: remove many types of "dangling" components from your workstation
docker image prune: remove all "dangling" docker images from your workstation
docker container prune: remove all stopped docker containers from your workstation
docker rmi $(docker images -q) --force: remove all docker images from your workstation

Using the Docker Shell

Since the above docker run command uses a Docker images that, by default, runs gradle grade and then exits the Docker container, you may want to instead run the following command so that you enter an "interactive terminal" that will allow you to repeatedly run commands within the Docker container. Don't forget that, if you are using the Windows operating system, then you will need to use a different command to run Docker, as explained previously in this document.

docker run -it --rm --name dockagator \
  -v "$(pwd)":/project \
  -v "$HOME/.dockagator":/root/.local/share \
  gatoreducator/dockagator /bin/bash

Once you have typed this command, you can use the GatorGrader tool in the Docker container by typing the command gradle grade in your terminal. Running this command will produce a lot of output that you should carefully inspect. If GatorGrader's output shows that there are no mistakes in the assignment, then your source code and writing are passing all of the automated baseline checks. However, if the output indicates that there are mistakes, then you will need to understand what they are and then try to fix them.

To run one of these commands, you must be in the main (i.e., "home base") directory for this assignment where the build.gradle file is located.

Downloading Project Updates

If GatorGrader's maintainers push updates to this sample assignment and you received it through GitHub Classroom and you would like to also receive these updates, then you can type this command in the main directory for this assignment:

git remote add download git@github.com:Allegheny-Computer-Science-102-F2020/cs102-F2020-lab2-starter/

You should only need to type this command once; running the command additional times may yield an error message but will not negatively influence the state of your Git repository. Now, you are ready to download the updates provided by the GatorGrader maintainers by typing this command:

git pull download master

This second command can be run whenever the maintainers needs to provide you with new source code for this assignment. However, please note that, if you have edited the files that we updated, running the previous command may lead to Git merge conflicts. If this happens, you may need to manually resolve them with the help of the instructor or a student technical leader. Finally, please note that the Gradle plugin for GatorGrader will automatically download the newest version of GatorGrader.

Using GitHub Actions

This assignment uses GitHub Actions to automatically run GatorGrader and additional checking programs every time you commit to your GitHub repository. The checking will start as soon as you have accepted the assignment — thus creating your own private repository — and the course instructor and/or GitHub enables GitHub Actions on it. If you do not see either a yellow ● or a green ✔ or a red ❌ in your listing of commits, then please ask the instructor to see whether or not GitHub Actions was correctly enabled.

System Requirements

This assignment was developed to work with the following software and versions:

Docker Desktop
Operating Systems
- Linux
- MacOS
- Windows 10 Pro
- Windows 10 Enterprise
Programming Language Tools
- Gradle 6.6
- MDL 0.5.0
- Python 3.7 or 3.8

Reporting Problems

If you have found a problem with this assignment's provided source code or documentation, then you can go to the Computer Science 102 Fall 2020 Planning Repository and raise an issue. If you have found a problem with the GatorGrader tool and the way that it checks your assignment, then you can also raise an issue in that repository. To ensure that your issue is properly resolved, please provide as many details as is possible about the problem that you experienced. Individuals who find, and use the appropriate GitHub issue tracker to correctly document, a mistake in any aspect of this assignment will receive extra credit towards their grade for the course.

Receiving Assistance

If you are having trouble completing any part of this project, then please talk with either the course instructor or a student technical leader during the course session. Alternatively, you may ask questions in the Slack workspace for this course. Finally, you can schedule a meeting during the course instructor's office hours.

JakeBoord / cs102-F2020-lab2-jakeb