YRDSB Mark Fetcher & Teaching Assistant AI

This repository contains a Flask-based web application designed to help students fetch their marks from the YRDSB portal, view detailed assignment reports, and interact with an AI-powered teaching assistant.

Overview

The application provides the following functionalities:

• Fetch Marks: Log in with your YRDSB credentials to get current and midterm marks for your courses.
• Advanced Reports: View a detailed breakdown of assignment marks and see your Knowledge, Thinking, Communication, Application, and Culminating marks with weighting.
• AI Chat Assistant: Engage in a chat with an AI teaching assistant that can answer questions and offer guidance based on your mark data, using Google’s GenAI services.

Features

• User Authentication & Session Management:
  Uses Flask sessions to store user information temporarily during the session.

• Data Parsing:
  Utilizes requests and BeautifulSoup to scrape and parse HTML from the YRDSB website for marks and assignment reports.

• Local Data Storage:
  Stores fetched data in a JSON file (user_marks.json)

• AI Integration:
  Incorporates Google GenAI to create an interactive chat experience, providing responses based on user input and fetched data.

Requirements

• Python 3.x
• Flask
• requests
• BeautifulSoup4 (bs4)
• google-genai (and its dependencies)
• Other dependencies as listed in requirements.txt

Installation

1. Clone the repository:

   git clone https://github.com/KaiStephens/TeachAssistScraper
   cd TeachAssistScraper
   

2. Set up a virtual environment (optional but recommended):

   python3 -m venv venv
   source venv/bin/activate   # On Windows use: venv\Scripts\activate
   

3. Install dependencies:

   pip install -r requirements.txt

4. If planning on using AI use If you run that AI app without setting your google API key in your environment it will return a server error. To set your google API key run this command:

    export GOOGLE_API_KEY="YOUR_API_KEY"

   If you do not have an api get one at https://aistudio.google.com/u/1/apikey free of charge (as of 01/14/25)

Security Configuration

Flask Secret Key

To ensure the security of user sessions, it's crucial to set a strong, random secret key for the Flask application.

Set the FLASK_SECRET_KEY environment variable to a unique, random string. For example:

On Linux/macOS:

export FLASK_SECRET_KEY='your_strong_random_secret_key_here'

On Windows (Command Prompt):

set FLASK_SECRET_KEY=your_strong_random_secret_key_here

On Windows (PowerShell):

$env:FLASK_SECRET_KEY='your_strong_random_secret_key_here'

You can generate a strong key using Python:

import secrets
secrets.token_hex(16)

The application includes a default fallback key for development if FLASK_SECRET_KEY is not set, but this fallback should not be used in any environment other than local development.

Running the Application

Start the Flask server by running:

  python app.py

Or run the app without the AI Assistant with

  python appNoAI.py

By default, the application will run on your local network and locally on http://{your_ip}:5001 and http://127.0.0.1:5001. Open this URL in your web browser to access the application.

Running Tests

Basic unit tests are provided for some helper functions in yrdsb_scraper.py. To run them, navigate to the project's root directory and execute:

python -m unittest tests.test_yrdsb_scraper

Alternatively, you can run the test file directly:

python tests/test_yrdsb_scraper.py

The test file tests/test_yrdsb_scraper.py includes logic to adjust sys.path to ensure that the yrdsb_scraper module can be imported correctly when run directly.