Matrix Processing Programming Project

Introduction

• Due date: Check Discord or the Course Materials Schedule
• This assignment is graded as described in the syllabus section for a Programming Project Assignment Evaluation
• Submit this assignment on GitHub following the expectations in the syllabus on Assignment Submission.
• To begin, read this README
• This project has been adapted from Proactive Programmers' material, thus discrepancies are possible.
• Post to the #data-structures Discord channel for questions and clarifications.
• For reference, check the starter repo
• Modifications to the gatorgrade.yml file are not permitted without explicit instruction.

Learning Objectives

The learning objectives of this assignment are to:

1. Use Git and GitHub to manage source code file changes
2. Check files, read files
3. Index into lists
4. Use data structure of nested lists
5. Write clearly about the programming concepts in this assignment.

Seeking Assistance

Please review the course expectations on the syllabus about Seeking Assistance. Students are reminded to uphold the Honor Code. Cloning the assignment repository is a commitment to the latter.

For this assignment, you may use class materials, textbooks, notes, and the internet. Ensure that your writing is original and based on your own understanding of the concepts.

To claim that work is your own, it is essential to craft the logic and the writing together without copying or using the logical structure of another source. The honor code holds everyone to this standard.

If outside of lab you have questions, the #data-structures Discord channel, TL office hours, instructor office hours, and GitHub Issues can be utilized.

Project Goals (Project Overview Below)

This project invites you to implement a matrix program that processes a two-dimensional "list of lists" called a matrix. The main feature of the program is that it can count the number of negative numbers inside of a matrix that it inputs from a file specified on its command-line. In addition to implementing part of the command-line interface for matrix you will add source code that traverses the input matrix and counts the negative numbers. As you enhance your technical skills by implementing and documenting a Python program, you will continue to explore tools such as VS Code and a terminal window and the Python programming language and the Poetry package manager.

Expected Output

As previously mentioned, this project invites you to implement a matrix processing program program called matrix. The program accepts through its command-line interface a matrix-file parameter that designates a file with a matrix inside of it and the matrix-dir that is the directory containing the specified file. For this project, you should use the matrix.txt file inside of the input directory that contains these contents:

100,19,9,9
10,9,8,7
6,4,2,-1
4,2,0,-1
3,0,-1,-2
-1,-1,-2,-5

After correctly adding all of the required features, you can use Poetry to run the program with the command poetry run matrix --matrix-dir input --matrix-file matrix.txt and see that it it produces the following output:

✨ Searching for negative numbers in a matrix stored in input/matrix.txt!

📦 The matrix contains the following integer values:

---  --  --  --
100  19   9   9
 10   9   8   7
  6   4   2  -1
  4   2   0  -1
  3   0  -1  -2
 -1  -1  -2  -5
---  --  --  --

🧮 The matrix contains 8 negative numbers!

To learn more about how to run this program, you can type the command poetry run matrix --help to see the following output showing how to use matrix:

╭─ Options ─────────────────────────────────────────────────────────────╮
│ --matrix-dir                PATH                 [default: None]      │
│ --matrix-file               PATH                 [default: None]      │
│ --install-completion        [bash|zsh|fish|powe  Install completion   │
│                             rshell|pwsh]         for the specified    │
│                                                  shell.               │
│                                                  [default: None]      │
│ --show-completion           [bash|zsh|fish|powe  Show completion for  │
│                             rshell|pwsh]         the specified shell, │
│                                                  to copy it or        │
│                                                  customize the        │
│                                                  installation.        │
│                                                  [default: None]      │
│ --help                                           Show this message    │
│                                                  and exit.            │
╰───────────────────────────────────────────────────────────────────────╯

Please note that the provided source code does not contain all of the functionality to produce this output. As explained in the next section, you are invited to add the missing features and ensure that matrix produces the expected output. Once the program is working correctly, it should produce output similar to that shown in this section.

Don't forget that if you want to run the matrix program you must use your terminal to first go into the GitHub repository containing this project and then go into the matrix directory that houses the project's code. Finally, remember that before running the program you must run poetry install to add the dependencies.

Adding Functionality

If you study the file matrix/matrix/main.py you will see that it has many TODO markers that designate the parts of the program that you need to implement before matrix will produce correct output. Specifically, you should implement these functions in matrix:

• def confirm_valid_file(file: Path) -> bool
• def count_negatives_in_matrix(matrix: List[List[int]]) -> int
• def matrix(matrix_dir: Path = typer.Option(None), matrix_file: Path = typer.Option(None)) -> None

Once you have correctly resolved all of the TODO markers in the matrix program, it should produce the expected output described in the previous section. The most important function you need to implement for this project is count_negatives_in_matrix, which has a signature indicating that it accepts as input a List of Lists that contain int values (i.e., List[List[int]]) and returns as output an int for the number of negative numbers in the file. You may assume that the matrix parameter that is input to the confirm_valid_file function is organized such that each row and column of the matrix is sorted in a non-increasing order.

The following excerpt of output created by a correct implementation of matrix, which was produced through the use of the python-tabulate package, illustrates the organization of the input matrix. For instance, note that the first column of the matrix contains the values 100, 10, 6, 4, 3, -1 which are organized in a non-increasing manner from the top to the bottom of the matrix. It is also worth noting that all of the other column in the matrix are also organized in the same non-increasing fashion. Moreover, the third-from-the-top row of the matrix contains the values 6, 4, 2, -1 while the last row contains -1, -1, -2, -5 which are also organized in a non-increasing style.

---  --  --  --
100  19   9   9
 10   9   8   7
  6   4   2  -1
  4   2   0  -1
  3   0  -1  -2
 -1  -1  -2  -5
---  --  --  --

Running Checks

If you study the source code in the pyproject.toml file you will see that it includes the following section that specifies different executable tasks like ruff. If you are in the matrix directory that contains the pyproject.toml file and the poetry.lock file, the tasks in this section make it easy to run commands like poetry run task ruff to automatically run the ruff linter designed to check the Python source code in your program and its test suite to confirm that your source code adheres to the industry-standard. You can also use the command poetry run task fix to automatically reformat the source code. poetry run task ruffdetails will print out detailed linting errors that point to exactly what ruff views as a linting error. Make sure to examine the pyproject.toml file for other convenient tasks that you can use to both check and improve your project!

Along with running tasks like poetry run task ruff, you can 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 :material-github: GatorGrade program runs :material-github: GatorGrader to automatically check your program and technical writing. If your program has all of the anticipated functionality, you can run the command poetry run task test and see that the test suite produces output like the following.

Can you think of any additional tests to add to the test suite? If you can, then add them so that you can increase your confident in program correctness!

collected 3 items

tests/test_matrix.py ....

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 GitHub repository, you can still run checks on your own computer by using Poetry and GatorGrader. You can also add and commit work locally before pushing it by using git commands in the terminal: git add . and git commit -m "Commit Message".

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. 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 tested, compare and contrast the performance of different implementations of the matrix processing algorithm, and answer all of the other questions about your experiences in completing this project.

Project Assessment

Since this is a programming project, it is aligned with the applying and analyzing 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 all aspects of the project's specification.

Project Overview

After cloning this repository to your computer, please take the following steps:

• Use the cd command to change into the directory for this repository.
• Specifically, you can change into the program directory by typing cd matrix.
• Install the dependencies for the project by typing poetry install.
• Run the program to perform matrix processing by typing the following command:
  • poetry run matrix --matrix-dir input --matrix-file matrix.txt
  • Please note that the program will not work unless you add the required source code
  • Please refer to the writing/reflection.md file for all of the ways to run the program
• Please note that the program will not work unless you add the required source code at the designated TODO markers.
• Confirm that the program is producing the expected output described above
• Run the automated grading checks by typing gatorgrade --config config/gatorgrade.yml.
• You may also review the output from running GatorGrader in GitHub Actions.
• Don't forget to provide all of the required responses to the technical writing prompts in the writing/reflection.md file.
• Please make sure that you completely delete the TODO markers and their labels from all of the provided source code.
• Please make sure that you also completely delete the TODO markers and their labels from every line of the writing/reflection.md file.