CIS2348 Python Assignments and Projects Repository

github repo

This repository contains a comprehensive collection of Python programming assignments and projects completed for the CIS2348 course in Fall 2022. It demonstrates foundational programming concepts, problem-solving skills, and algorithm implementations across multiple homework assignments and a final project.

Features

  • Solutions to homework assignments (HW1 to HW4) covering topics such as basic input/output, control flow, data structures, sorting algorithms, file handling, and exception management.
  • Final project focused on CSV file processing, data merging, and integration.
  • Examples of object-oriented programming with classes and methods.

Tech Stack

  • Python 3

Getting Started

Prerequisites

  • Python 3 installed on your system.

Installation

  1. Clone the repository:
    git clone https://github.com/justin-napolitano/CIS2348.git
    cd CIS2348
    

Running Code

  • Navigate to the desired homework folder (e.g., HW1, HW2, etc.).
  • Run Python scripts using the command:
    python filename.py
    
  • Some scripts require input files (e.g., inputDates.txt, ManufacturerList.csv), ensure these files are present in the working directory.

Project Structure

CIS2348/
├── FinalProjectPart1/       # Final project code involving CSV data processing
├── HW1/                    # Homework 1 assignments
├── HW2/                    # Homework 2 assignments
├── HW3/                    # Homework 3 assignments
├── HW4/                    # Homework 4 assignments
└── README.md               # This readme file
  • Each homework folder contains Python scripts that solve specific problems or labs.
  • The final project folder contains code for a larger assignment involving data integration from multiple CSV files.

Future Work / Roadmap

  • Add detailed documentation and comments to all scripts for better clarity.
  • Include input sample files and expected outputs for easier testing.
  • Implement automated testing for homework assignments.
  • Expand the final project with more robust data validation and error handling.
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