⚡ HeroAlgorithm

Instant AI/ML Problem Sheets, Datasets & Code Vault
Download, extract, and organize all your AI & Machine Learning lab assignments, problem sheets, datasets, Jupyter Notebooks (.ipynb), and Python scripts cleanly onto your PC with a single command.

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🌟 The Magic Experience

Install and organize all your AI/ML lab problem sheets into C:\AIML_Assignments in one step:

pip install heroalgorithm; heroalgorithm

Or run heroalgorithm anytime in your terminal:

heroalgorithm

And your C: drive folder is cleanly populated:

C:\AIML_Assignments\
├── PS-1/
│   ├── dataset/
│   │   └── data.csv
│   ├── notebook.ipynb
│   ├── solution.py
│   └── README.md
├── PS-2/
│   ├── dataset/
│   │   └── housing.csv
│   ├── notebook.ipynb
│   ├── solution.py
│   └── README.md
└── PS-3/
    ├── dataset/
    │   └── iris.csv
    ├── notebook.ipynb
    ├── solution.py
    └── README.md

Clean & Quiet by Design: No noisy spam or "installing file x" lines. Everything stays hidden and extracts quietly into your folder!

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🚀 Key Features

• ⚡ Bundled Offline Vault: Problem sheets, datasets, notebooks, and solutions are packaged directly inside the package. Works 100% offline without needing GitHub.
• 📁 Automatic C: Drive Placement: Automatically organizes files into C:\AIML_Assignments on Windows (or ~/AIML_Assignments).
• 🎯 Selective Extraction: Run heroalgorithm 1 or heroalgorithm ps-1 to unpack just Problem Sheet 1.
• 🤫 Silent Mode: Zero annoying logs. Use -q or --quiet for 100% silent execution.
• 🔄 GitHub Sync (Optional): Connect to a remote GitHub repository anytime with heroalgorithm config --set-repo <user>/<repo> to sync the latest assignments.
• 🪶 Zero Dependencies: 100% built on Python's standard library. Instant installation.

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🛠️ Usage Examples

1. Extract All Problem Sheets to C:\AIML_Assignments

heroalgorithm

2. Extract Only Problem Sheet 1

# Shorthand:
heroalgorithm 1

# Or:
heroalgorithm ps-1

3. Choose a Custom Output Folder

heroalgorithm -o "D:\MyCollege\AI_Lab"

4. Run Completely Silently

heroalgorithm -q

5. Preview Available Problem Sheets

heroalgorithm list

6. Configure Default Destination or Remote Repo

# Change default destination:
heroalgorithm config --set-dest "D:\AIML_Lab"

# Connect to a GitHub repository:
heroalgorithm config --set-repo your-username/aiml-assignments

# Check active configuration:
heroalgorithm config

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🚢 Publishing to PyPI (Step-by-Step)

The package name heroalgorithm is verified available on PyPI!

Step 1: Build the Package

python -m build

This creates the distribution files in dist/:

• heroalgorithm-0.1.0-py3-none-any.whl
• heroalgorithm-0.1.0.tar.gz

Step 2: Upload to PyPI

python -m twine upload dist/*

(Enter __token__ as the username, and paste your PyPI API Token as the password).

Once published, anyone in the world can run:

pip install heroalgorithm; heroalgorithm

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📄 License

This project is licensed under the MIT License.