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A simple CLI tool to interact with Supernote devices

Project description

Supynote CLI

A simple, clean CLI tool to interact with your Supernote device.

Requirements

  • Python 3.8.1+
  • Supernote device connected to same local network
  • Device must have "Export via LAN" enabled (Settings → System → Export via LAN)

System Dependencies (for PDF conversion)

PDF conversion requires the Cairo graphics library. Install it before installing supynote:

macOS:

brew install cairo pkg-config

Ubuntu/Debian:

sudo apt-get update
sudo apt-get install -y libcairo2-dev pkg-config python3-dev

Windows: No additional dependencies needed (pre-built wheels available)

Optional Features

  • OCR: Requires additional dependencies (transformers, torch) - see Installation
  • Apple Silicon: OCR automatically uses MPS acceleration on M1/M2/M3/M4 Macs

Features

  • 🔍 Auto-discovery: Automatically find your Supernote on the network
  • 📂 File listing: Browse files and directories on your device
  • ⬇️ Download: Download individual files or entire directories
  • 📄 PDF conversion: Convert .note files to high-quality vector PDFs
  • 🌐 Web interface: Open the device web interface in your browser
  • Fast downloads: Multithreaded downloads for speed

Installation

From PyPI (Recommended)

# Basic installation
pip install supynote

# With OCR features
pip install supynote[ocr]

From Source (Development)

# Clone and install
git clone https://github.com/thopiax/supynote.git
cd supynote
pip install -e .

# With OCR features
pip install -e .[ocr]

Using uv (For Development)

uv sync  # Installs all dependencies including dev tools

Quick Start

# Find your Supernote device
supynote find

# List all files
supynote list

# List files in Note directory
supynote list Note

# Download Note directory
supynote download Note

# Download a specific file
supynote download Note/my-note.note

# Convert .note file to PDF (vector format)
supynote convert my-note.note

# Convert all .note files in a directory
supynote convert Note/

# Open device web interface
supynote browse

# Show device info
supynote info

Commands

supynote find

Scan the local network to find your Supernote device.

  • --open: Open the device web interface after finding it

supynote list [directory]

List files and directories on the device.

supynote download <path>

Download files or directories from the device.

  • --workers N: Number of parallel download workers (default: 4)
  • --convert-pdf: Automatically convert downloaded .note files to PDF

supynote convert <path>

Convert .note files to PDF format (vector by default).

  • --output DIR: Output directory or specific file path
  • --no-vector: Use raster format instead of vector
  • --no-links: Disable hyperlinks in PDF output
  • --recursive: Process subdirectories (default: true)

supynote browse

Open the device web interface in your default browser.

supynote info

Show device connection information.

Options

  • --ip IP: Manually specify device IP address
  • --port PORT: Device port (default: 8089)
  • --output DIR: Local output directory for downloads

Environment Variables

Configure supynote-cli behavior with these environment variables:

  • SUPYNOTE_JOURNALS_DIR: Default directory for markdown journal exports (used by merge command)
  • SUPYNOTE_IP: Default device IP (alternative to --ip flag)
  • SUPYNOTE_OUTPUT_DIR: Default output directory (alternative to --output flag)

Example .env file:

SUPYNOTE_JOURNALS_DIR=$HOME/Documents/journals
SUPYNOTE_IP=192.168.1.100

Load with: export $(cat .env | xargs)

See examples/automation/.env.example for more configuration options.

Examples

# Find device and open in browser
supynote find --open

# Download with custom output directory
supynote download Note --output ~/my-notes

# Use specific IP address
supynote --ip 192.168.1.100 list

# Download with more workers for speed
supynote download EXPORT --workers 8

# Download and convert to PDF in one step  
supynote download Note --convert-pdf

# Convert with custom output directory
supynote convert Note/ --output ~/my-pdfs

# Convert single file with specific output name
supynote convert my-note.note --output my-document.pdf

Troubleshooting

PDF Conversion Errors

  • Error: "cairo not found" or "pycairo build failed"
    • Install Cairo system dependencies (see System Dependencies section above)
    • macOS: brew install cairo pkg-config
    • Linux: sudo apt-get install libcairo2-dev pkg-config python3-dev
  • After installing Cairo, reinstall supynote: pip install --force-reinstall supynote

Device Not Found

  • Ensure device is on same network as computer
  • Try manually specifying IP: supynote --ip YOUR_IP list
  • Some networks block device discovery - use --ip flag with your device's IP address

OCR Not Working

  • Install OCR dependencies: pip install -e .[ocr]
  • First run downloads ML models (~500MB) - may take time
  • Requires internet connection for initial model download
  • On Apple Silicon, ensure MPS is available (macOS 12.3+)

Slow Performance

  • Increase workers: supynote download --workers 30
  • Use async mode (default in v1.0+)
  • OCR is CPU/GPU intensive - fewer workers may help on older machines
  • Check network connection quality

Permission Errors

  • Ensure output directory is writable
  • On macOS, you may need to grant Terminal full disk access
  • Check firewall settings aren't blocking network discovery

For more help, see GitHub Issues

License

MIT License - see LICENSE file for details.

Contributing

Contributions welcome! See CONTRIBUTING.md for guidelines.

Steps:

  1. Fork the repository
  2. Create a feature branch
  3. Make your changes with tests
  4. Submit a pull request

Acknowledgments

  • Supernote Team: For creating excellent e-ink tablets that inspire tools like this
  • supernotelib: Unofficial library for .note file conversion - the foundation of PDF conversion in this tool
  • Claude Code: This project was built with significant assistance from Claude Code, which handled much of the heavy lifting in development and refactoring
  • TrOCR (Microsoft) and LLaVA: Powering the OCR capabilities for handwritten text recognition

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