- 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
- Commands for an Interactive Docker Shell
- Upgrading the Docker Container
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 implement iterative functions in a Python program
- To use iteration constructs to calculate a sequence of mathematical functions that use exponentiation
- To learn how Python programs can use iteration, conditional logic, and lists of integers
- To use your text editor and a terminal window to run a test suite for a Python program
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 β
in the listing of commits in GitHub. If your submission does not meet the
requirements, a red β 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.
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.
-
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.
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-3-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 [email protected]:Allegheny-Computer-Science-102-F2020/computer-science-102-fall-2020-lab-3-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.
If you have not already done so, 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 iterator
program
that you will implement, debug, and observe. To complete this step you need to
type cd iterator
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.
Finally, it is important to note that if you are not able to correctly install Python 3.8.5 and Poetry on your laptop, you can opt to use Python and the Poetry tool in the Docker container provided by the course instructor. Please refer to the content in this assignment sheet about how to run an interactive shell in a Docker container and then use the Poetry commands mentioned in both this section and the next sections of the assignment sheet.
Please make sure that you investigate all of the Python source code files
provided in the assignment repository. You should notice that there are TODO
markers indicating that you need to add source code that will correctly use two
different types of iteration constructs, namely the for
loop and the while
loop, to iteratively display the powers of two from an inclusive minimum to an
exclusive maximum. Before you start to implement the required Python functions
make sure that you understand the meaning of the phrases "inclusive minimum" and
"exclusive maximum".
Perhaps the best way to understand the meaning of these terms is to observe the
output of a completed version of the program. For instance, the command poetry run python 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
loop and a 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! π
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 python iterator --forloop --minimum 0 --maximum 5
produces
the following output:
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! π
Your GitHub repository for this assignment also contains a small Pytest
test suite that provides a function under
test with inputs and then checks to see if it produces the expected output. You
can run the four tests in the test suite by typing the following command in your
terminal window: poetry run pytest
. 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-lab3-solution/iterator
collected 4 items
tests/test_iterate.py .... [100%]
=================================================================== 4 passed in 0.01s ===================================================================
If your test suite has failing test cases in it, then you need to keep working
to enhance 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_iterate.py
test
suite so as to ensure that the functions under test work 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 iterator 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 iterator tests
.
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 source code segments, and answer all of the
other questions about your experiences in completing this laboratory assignment.
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. Please do not use
vacuous commit messages that do not explain how your commit changes the contents
of the repository!
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 iterator; poetry install; poetry run python iterator --forloop --whileloop --minimum 0 --maximum 5; cd ..
executes correctly - The display.py in iterator/iterator has at least 2 multiple-line Python comment(s)
- The display.py in iterator/iterator has at least 3 multiple-line Python comment(s)
- The display.py in iterator/iterator has exactly 0 of the
TODO
fragment - The file display.py exists in the iterator/iterator directory
- The file iterate.py exists in the iterator/iterator directory
- The file __main__.py exists in the iterator/iterator directory
- The file reflection.md exists in the writing directory
- The file test_iterate.py exists in the iterator/tests directory
- The iterate.py in iterator/iterator has at least 2 multiple-line Python comment(s)
- The iterate.py in iterator/iterator has exactly 0 of the
TODO
fragment - The __main__.py in iterator/iterator has at least 2 multiple-line Python comment(s)
- The __main__.py in iterator/iterator has at least 4 single-line Python comment(s)
- The __main__.py in iterator/iterator has exactly 0 of the
TODO
fragment - The reflection.md in writing has at least 1 of the
code
tag - The reflection.md in writing has at least 3 of the
code_block
tag - The reflection.md in writing has at least 500 word(s) in total
- 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 8 of the
heading
tag - The repository has at least 5 commit(s)
- The test_iterate.py in iterator/tests has at least 5 multiple-line Python comment(s)
- The test_iterate.py in iterator/tests has exactly 0 of the
TODO
fragment
βββββββββββββββββββββββββββββββββββββββββββββββββββββββ
β Passed 23/23 (100%) of checks for cs102-F2020-lab3! β
βββββββββββββββββββββββββββββββββββββββββββββββββββββββ
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 β or β: 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 β appears in the GitHub commit log instead of an β. The build status reported by GitHub Actions will only be a β 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 β or β: Students will also receive a β 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 β 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 β or β: 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.
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.
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.
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.
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
Please note that not all version of the Windows terminal window will correctly
recognize the use of the %cd%
and %HomeDrive%%HomePath%
variables. In this
case, you should substitute the actual directory for a specific course
assignment for the %cd%
variable and the drive letter that contains the
.dockagator
directory for the %HomeDrive%%HomePath%
variable. Finally, the
Windows terminal window may not work correctly when you attempt to run a
multi-line command. In this case, you should break up the aforementioned
four-line command into separate lines, like docker run --rm --name dockagator
and -v "%cd%:/project"
and then connect them into a single long line that you
separate by a single space. Here is an example of what the long command would
look like, again assuming that the Windows cmd
terminal correctly interprets
the %cd%
and %HomeDrive%%HomePath%
variables:
docker run -it --rm --name dockagator -v "%cd%:/project" -v "%HomeDrive%%HomePath%/.dockagator:/root/.local/share" gatoreducator/dockagator /bin/bash
Here are some additional commands that you may need to run when using Docker:
docker info
: display information about how Docker runs on your workstationdocker images
: show the Docker images installed on your workstationdocker container list
: list the active images running on your workstationdocker system prune
: remove many types of "dangling" components from your workstationdocker image prune
: remove all "dangling" docker images from your workstationdocker container prune
: remove all stopped docker containers from your workstationdocker rmi $(docker images -q) --force
: remove all docker images from your workstation
Since the above docker run
command uses a Docker images that, by default, runs
gradle grade
and then exits the Docker container, you may want to instead run
the following command so that you enter an "interactive terminal" that will
allow you to repeatedly run commands within the Docker container. Don't forget
that, if you are using the Windows operating system, then you will need to use a
different command to run Docker, as explained previously in this document.
Importantly, the command that you type if you are a Windows user should still
contain the -it
at the start of the docker run
and the /bin/bash
at the
end of the command. However, the other components of this command need to be
customized for the Windows operating system.
If you use either MacOS or Linux, then this is the command that you would run to enter into the interactive terminal provided by a Docker container:
docker run -it --rm --name dockagator \
-v "$(pwd)":/project \
-v "$HOME/.dockagator":/root/.local/share \
gatoreducator/dockagator /bin/bash
If you use Windows, then this is the command that you would run to enter into the interactive terminal provided by a Docker container:
docker run -t --rm --name dockagator \
-v "%cd%:/project" \
-v "%HomeDrive%%HomePath%/.dockagator:/root/.local/share" \
gatoreducator/dockagator /bin/bash
Once you have typed this command, you can use the GatorGrader
tool in the Docker container by
typing the command gradle grade
in your terminal. Running this command will
produce a lot of output that you should carefully inspect. If GatorGrader's
output shows that there are no mistakes in a course assignment, then your source
code and technical writing are passing all of the automated baseline checks.
However, if the output indicates that there are mistakes, then you will need to
understand what they are and then try to fix them.
Remember, to correctly run any of the commands mentioned in this guide, you must
be in the main (i.e., "home base") directory for this assignment where the
build.gradle
file is located.
If the course instructor provides a new version of the Docker container called
gatoreducator/dockagator
and you want to receive it immediately, you must
first delete the existing Docker container on your laptop by running the command
docker rmi gatoreducator/dockagator
. Next, you can re-run one of the
aforementioned Docker commands, like the following one, which would work on
MacOS or Linux:
docker run -it --rm --name dockagator \
-v "$(pwd)":/project \
-v "$HOME/.dockagator":/root/.local/share \
gatoreducator/dockagator /bin/bash
Please note that if you attempt to run gradle grade
in an updated Docker
container it is possible that the command will execute incorrectly if you
previously used GatorGrader with a Docker container that featured a different
version of the Python programming language. In this situation, you should delete
the directories inside of the .dockagator
directory and then again attempt to
run the gradle grade
command inside of the Docker container. Specifically, you
will need to delete directories in .dockagator
that are normally called
gatorgrader
, virtualenv
, and virtualenvs
.
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 [email protected]:Allegheny-Computer-Science-102-F2020/cs102-F2020-lab3-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.
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 β thus creating your own private repository β and the course instructor and/or GitHub enables GitHub Actions on it. If you do not see either a yellow β or a green β or a red β in your listing of commits, then please ask the instructor to see whether or not GitHub Actions was correctly enabled.
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
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.
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.