Grade Forecast

Note

This project was created using Gatlen's Opinionated Template (GOTem), a cutting-edge project template for power users and researchers.

Grade Forecast

[?] Provide a brief description of your project here. What does it do? Why is it useful? [View the full documentation here](https://Gatlen Culp.github.io/grade-forecast) ➡️

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00 Table of Contents

• Grade Forecast
  • 00 Table of Contents
  • 01 About
  • 02 Getting Started
    • 02.01 Prerequisites
    • 02.02 Installation
  • 03 Usage
  • 04 Project Structure
  • 05 Contributing
  • 06 License

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01 About

[?] Provide detailed information about your project here.

• What problem does it solve?
• What makes it unique?
• What are its key features?
• Who is it for?

📸 Screenshots

[?] Please provide your screenshots here.

Home Page	Login Page

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02 Getting Started

02.01 Prerequisites

[?] List all dependencies and requirements needed before installing the project:

# Example
python >= 3.8
pip >= 21.0

02.02 Installation

[?] Provide step-by-step installation instructions:

01. Clone the repository

git clone https://github.com/GatlenCulp/grade-forecast.git
cd grade-forecast

02. Install dependencies

pip install -e .

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03 Usage

[?] Provide basic usage examples with code snippets:

from gf import example

# Initialize
example.start()

# Run a basic operation
result = example.process("data")
print(result)

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04 Project Structure

This project follows the structure of Gatlen's Opinionated Template (GOTem):

📁 .
├── 📁 data               <- Data directories for various stages
├── 📚 docs               <- Documentation
├── 📋 logs               <- Log files
├── 📁 notebooks          <- Jupyter notebooks
├── 🗑️ out                <- Output files, models, etc.
└── 🚰 gf  <- Source code
    ├── ⚙️ config.py      <- Configuration settings
    ├── 🐍 dataset.py     <- Data processing
    ├── 🐍 features.py    <- Feature engineering
    ├── 📁 modeling       <- Model training and prediction
    └── 🐍 plots.py       <- Visualization code

For a more detailed explanation of the project structure, see the CONTRIBUTING.md file.

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05 Contributing

We welcome contributions to this project! Please see our contribution guidelines for detailed information on how to:

• Set up your development environment
• Submit issues and feature requests
• Create pull requests
• Get support

---

06 License

This project is licensed under the MIT - see the LICENSE file for details.

A tool for forecasting and tracking your university grades to adjust your priorities.

Installation

Clone the repository and install the package:

git clone https://github.com/yourusername/grade-forecast.git
cd grade-forecast
pip install -e .

Usage

Grade Forecast provides both an interactive CLI and direct command-line commands.

Interactive Mode

To start the interactive CLI:

grade-forecast run

Command-Line Commands

List all courses

grade-forecast list

This will display all available courses with their aliases.

Show a summary of all courses

grade-forecast summary

Display information for a specific course

You can use the course name, alias, or index:

grade-forecast course <course_name>
grade-forecast course <alias>
grade-forecast course <index>

With detailed information:

grade-forecast course <course_name> --details

If you run the command without specifying a course, it will display all available courses with their aliases:

grade-forecast course

List all tasks in a course

grade-forecast tasks <course_name>
grade-forecast tasks <alias>

If you run the command without specifying a course, it will display all available courses with their aliases:

grade-forecast tasks

Analyze a specific task

grade-forecast task <course_name> <task_name>
grade-forecast task <alias> <task_index>

If you run the command without specifying a task, it will display all available tasks in the course:

grade-forecast task <course_name>

Update a task's grade

grade-forecast update <course_name> <task_name> <grade>
grade-forecast update <alias> <task_index> <grade>

If you run the command without specifying a grade, it will prompt you to enter one:

grade-forecast update <course_name> <task_name>

Example:

grade-forecast update compsys "Homework #1" 95
grade-forecast update cs 1 95  # Using alias and task index

Compare multiple courses

grade-forecast compare <course1> <course2> ...
grade-forecast compare <alias1> <alias2> ...

If you run the command without specifying any courses, it will display all available courses with their aliases:

grade-forecast compare

Example:

grade-forecast compare compsys linalg
grade-forecast compare cs la  # Using aliases

Features

• Track and forecast your grades across multiple courses
• Analyze the impact of individual assignments on your final grade
• Visualize grade trends and projections
• Prioritize tasks based on their impact on your final grade
• Compare performance across different courses

License

MIT