Huffman Compression Tool

A lightweight, efficient, and cross-platform Python tool implementing the Huffman Coding Algorithm for lossless data compression and decompression. It features both a modern graphical user interface (Tkinter GUI) and a lightweight command-line interface (CLI).

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🚀 Features

• Lossless Compression: Safely compresses any file format (text, images, PDFs, media) using optimal prefix-free codes.
• Extension Metadata Preservation: Preserves original file extension metadata inside the compressed file (.huff), ensuring seamless restoration of the original format upon decompression.
• Interactive GUI Dashboard: Simple-to-use Tkinter dashboard for browsing files, initiating compression, and viewing performance telemetry.
• Telemetry & Analysis:
  • Original vs. Compressed Size: Visualizes bytes saved.
  • Compression Ratio: Computes the exact reduction ratio.
  • Shannon Entropy: Measures the statistical complexity (entropy) of the source file to evaluate compression feasibility.

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🛠️ Project Structure

Huffman_Compression_Project V3/
├── main.py            # CLI entry point (compress & decompress)
├── huffman_gui.py     # Tkinter Graphical User Interface entry point
├── huffman_app.py     # Commented backup app
├── modules/
│   ├── huffman_encoding.py     # Tree building, frequency map, and encoder
│   ├── huffman_decoding.py     # Bitstream parser and tree-based decoder
│   ├── entropy_calculation.py  # Shannon entropy computation module
│   ├── compression_analysis.py # Ratio and savings metrics calculations
│   └── media_utils.py          # File size and type checkers
└── output/            # Default directory for compressed/restored files

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⚙️ Installation & Setup

Prerequisites

• Python 3.12+

1. Clone & Navigate to Project

git clone https://github.com/omar230101276/Huffman_Compressor.git
cd Huffman_Compressor

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🖥️ Running the Application

Option A: Run the GUI Application (Recommended for Desktop)

To run the interactive desktop application:

python huffman_gui.py

• Browse: Select any file.
• Compress: Compresses the file and creates a .huff archive under the output/ directory.
• Decompress: Select any .huff archive to restore the original file.

Option B: Run the Command-Line Interface (CLI)

To run the CLI application:

python main.py

You will be prompted to enter the path of the file you want to compress. The script will compress it, save it, and then automatically perform a test decompression to verify the integrity of the output.

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📊 Telemetry and Algorithm Metrics

Shannon Entropy

The tool calculates the Shannon Entropy of the input file in bits per character. $$\text{Entropy } H(X) = - \sum_{i=1}^{n} P(x_i) \log_2 P(x_i)$$ Where $P(x_i)$ is the probability of character $x_i$ appearing in the stream. This gives the theoretical limit of lossless compression for the file, allowing users to analyze how close the Huffman tree gets to the ideal limit.