memvid-rs 0.1.1

High-performance video memory encoding library (Rust bindings)

memvid-rs (Python Bindings)

Memvid-rs combines the performance of Rust with the ease of use of Python. It encodes text data into QR codes and then into video frames, allowing for efficient storage and retrieval of large datasets.

This project exposes the core logic written in Rust (MemvidEncoder) as a Python module via PyO3.

Attribution: This project is a port reimplemented in Rust based on the ideas and design of Olow304/memvid. We deeply appreciate the innovative approach of the original project.

🚀 Key Features

• High Performance: Leverages Rust's parallel processing and efficient memory management for fast text-to-video conversion.
• Pythonic: Easy to install via pip and use naturally as a Python object.
• Strong Compression: Significantly reduces storage space via Text -> QR -> Video (H.264/H.265) conversion.

📦 Installation

From Source (Development)

Requires Rust and Python development environments.

# 1. Install Rust & FFmpeg
brew install rust ffmpeg

# 2. Create and activate virtual environment
python3 -m venv .venv
source .venv/bin/activate

# 3. Install Maturin
pip install maturin

# 4. Build and install
maturin develop --release

From PyPI (Recommended)

pip install memvid-rs

From GitHub

pip install git+https://github.com/drivenbycode/memvid-rs.git

💻 Usage

import memvid_rs

# 1. Initialize Encoder
encoder = memvid_rs.MemvidEncoder()

# 2. Add Text
# add_text(text, chunk_size, overlap)
text_data = "Memvid-rs is fast and efficient. " * 100
encoder.add_text(text_data, chunk_size=200, overlap=20)

# 3. Build Video
try:
    encoder.build("output.mp4", "index.json")
    print("Video created: output.mp4")
except Exception as e:
    print(f"Error: {e}")

⚠️ Requirements

• System: macOS (Tested), Linux, Windows
• Runtime: ffmpeg (Required for video encoding)
  • macOS: brew install ffmpeg

📄 License

MIT License