saterys 0.4.1

Saterys — Scalable Analysis Toolkit for Earth Remote sYStemS

SATERYS

Scalable Analysis Toolkit for Earth Remote sYStemS

A modern geospatial pipeline builder with interactive node-based workflows

📖 Documentation • 🚀 Quick Start • 🎯 Examples • 🧩 Plugins

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🌟 Overview

SATERYS is a powerful geospatial analysis platform that combines the best of modern web technologies with robust geospatial processing capabilities. Build complex Earth observation workflows using an intuitive drag-and-drop interface, execute Python-based analysis nodes, and visualize results on interactive maps.

✨ Key Features

🎨 Visual Pipeline Builder Interactive, node-based workflow canvas powered by Svelvet Drag-and-drop creation and editing of geospatial analysis pipelines Real-time connection validation and error highlighting Dark/Light theme support for comfortable use in any environment Visual grouping and annotation of workflow components	⚡ High-Performance Backend FastAPI-powered REST API for rapid, scalable processing Asynchronous execution for efficient resource use Hot-reloadable plugin system for instant extension and customization Automatic error handling and detailed logging Built-in job queue for batch and long-running tasks
🛰️ Geospatial Native Native support for GeoTIFF, COG, and other raster formats Interactive map preview with Leaflet and tile-based raster visualization via rio-tiler Coordinate system handling and automatic reprojection Raster statistics, band math, and index calculation (NDVI, NDWI, PCA, etc.) Vector data support (GeoJSON, SHP, GPKG) for overlays and analysis	🔌 Extensible & Modular Architecture Plugin-based node system: add your own analysis nodes in Python Custom analysis functions and reusable workflow components Easy integration with existing Python geospatial tools (NumPy, Rasterio, Shapely, etc.) Modular design for rapid prototyping and extension Built-in and user-defined nodes auto-discovered at startup
🧩 Plugin Ecosystem Simple plugin API for adding new node types Hot-reload support for rapid development Community-contributed plugins for specialized tasks	🖥️ Modern Web UI Responsive, single-page application built with Svelte Real-time workflow editing and execution feedback Integrated documentation and example workflows User authentication and role-based access (optional)

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🚀 Quick Start

Installation

# Install SATERYS
pip install saterys
# Verify installation
saterys --help

Launch the Application

# Start SATERYS server
saterys

# Access the web interface at http://localhost:8000

The application will automatically:

• 🔍 Discover all available plugins
• 🌐 Start the FastAPI backend
• 🎨 Serve the Svelte frontend
• 📊 Open your default browser

Development Mode

For development with hot-reload:

# Start with auto-reload
saterys --dev

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🎯 Examples

Basic Workflow: Hello World

1. Add a Node: Click "Add Node" and select "hello"
2. Configure: Set the name parameter to "SATERYS"
3. Execute: Click the "Run" button
4. View Results: Check the output in the logs panel

# This runs automatically when you execute the hello node
def run(args, inputs, context):
    name = args.get("name", "world")
    return {"text": f"hello {name}"}

Geospatial Workflow: NDVI Calculation

Create a vegetation index from satellite imagery:

# 1. Add a raster input node
# 2. Set path to your multispectral image (e.g., Landsat, Sentinel)
# 3. Add NDVI calculation node
# 4. Configure band indices (e.g., red=4, nir=5 for Landsat 8)
# 5. Connect nodes and execute

Example NDVI Node Configuration:

{
  "red_band": 4,
  "nir_band": 5,
  "output_path": "./results/ndvi_output.tif",
  "dtype": "float32"
}

Custom Processing with Script Node

Write inline Python for custom analysis:

# Script node example - band math
import numpy as np
import rasterio

def process_raster(input_raster):
    with rasterio.open(input_raster["path"]) as src:
        # Read bands
        red = src.read(4).astype(float)
        nir = src.read(5).astype(float)
        
        # Custom vegetation index
        evi = 2.5 * ((nir - red) / (nir + 6 * red - 7.5 * blue + 1))
        
        return {"custom_index": evi}

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📚 Documentation

Built-in Nodes

Node Type	Description	Use Case
🔢 raster.input	Load GeoTIFF/COG files	Data ingestion
🌿 raster.ndvi	Calculate NDVI	Vegetation analysis
🌊 raster.ndwi	Calculate NDWI	Water body detection
📊 raster.pca	Principal Component Analysis	Dimensionality reduction
➕ sum	Sum numeric values	Basic arithmetic
👋 hello	Hello world example	Testing/demos
📝 script	Custom Python code	Flexible processing

API Endpoints

The FastAPI backend provides REST endpoints for integration:

# Get available node types
GET /node_types

# Execute a node
POST /run_node
{
  "nodeId": "unique-id",
  "type": "raster.ndvi", 
  "args": {"red_band": 4, "nir_band": 5},
  "inputs": {...}
}

# Register raster for preview
POST /preview/register
{
  "id": "my-raster",
  "path": "/path/to/file.tif"
}

# Get map tiles
GET /preview/tile/{id}/{z}/{x}/{y}.png

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🧩 Creating Plugins

SATERYS uses a simple plugin architecture. Create custom nodes by adding Python files to a nodes/ directory:

Basic Plugin Structure

# nodes/my_custom_node.py

NAME = "my.custom.node"  # Unique identifier
DEFAULT_ARGS = {         # Default configuration
    "param1": "default_value",
    "param2": 42
}

def run(args, inputs, context):
    """
    Execute the node logic
    
    Args:
        args: Node configuration parameters
        inputs: Data from connected upstream nodes  
        context: Runtime context (nodeId, etc.)
        
    Returns:
        Dictionary with output data
    """
    # Your processing logic here
    result = process_data(args, inputs)
    
    return {
        "type": "custom",
        "data": result,
        "metadata": {...}
    }

Raster Processing Plugin Example

# nodes/custom_filter.py

NAME = "raster.custom_filter"
DEFAULT_ARGS = {
    "filter_size": 3,
    "operation": "gaussian"
}

def run(args, inputs, context):
    import rasterio
    import numpy as np
    from scipy import ndimage
    
    # Get input raster
    raster_input = next(
        (inp for inp in inputs.values() 
         if inp.get("type") == "raster"), 
        None
    )
    
    if not raster_input:
        raise ValueError("No raster input found")
    
    # Process the raster
    with rasterio.open(raster_input["path"]) as src:
        data = src.read(1)
        
        # Apply filter
        if args["operation"] == "gaussian":
            filtered = ndimage.gaussian_filter(
                data, 
                sigma=args["filter_size"]
            )
        
        # Save result...
        output_path = "/tmp/filtered_result.tif"
        # ... saving logic here ...
        
    return {
        "type": "raster",
        "path": output_path,
        "operation": "custom_filter"
    }

Plugin Discovery

SATERYS automatically discovers plugins from:

1. Built-in nodes: saterys/nodes/ (package installation)
2. User nodes: ./nodes/ (current working directory)

Simply restart the application after adding new plugins!

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🛠️ Advanced Usage

Environment Configuration

# Custom host and port
export SATERYS_HOST=0.0.0.0  
export SATERYS_PORT=8080

# Raster cache directory
export RASTER_CACHE=./my_cache

# Development frontend origin (for CORS)
export SATERYS_DEV_ORIGIN=http://localhost:5173

Docker Usage

FROM python:3.10-slim

RUN pip install saterys

# Add your custom nodes
COPY nodes/ /app/nodes/

WORKDIR /app

EXPOSE 8000

CMD ["saterys", "--host", "0.0.0.0"]

Programmatic Usage

import uvicorn
from saterys.app import app

# Customize the FastAPI app
@app.get("/custom")  
def custom_endpoint():
    return {"message": "Custom endpoint"}

# Run programmatically
if __name__ == "__main__":
    uvicorn.run(app, host="0.0.0.0", port=8000)

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🤝 Contributing

We welcome contributions! Here's how to get started:

Development Setup

# Clone the repository
git clone https://github.com/bastian6666/SATERYS.git
cd SATERYS

# Install in development mode
pip install -e .

# Install frontend dependencies (if modifying UI)
cd saterys/web
npm install

# Start development server
npm run dev

Code Style

• Follow PEP 8 for Python code
• Use type hints where possible
• Add docstrings for public functions
• Test your changes before submitting

Submitting Changes

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

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📄 License

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

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🙏 Acknowledgments

• FastAPI: For building modern, high-performance APIs with ease.
• Uvicorn: An ASGI server for lightning-fast application deployment.
• Pydantic: Ensuring data validation and management is smooth and reliable.
• NumPy: The foundation for numerical computing in Python.
• rio-tiler: Efficient raster tiling and preview generation.
• Rasterio: Simplifying geospatial raster data I/O.
• Fiona: A powerful library for vector data handling (GPKG/SHP).
• PyProj: For seamless coordinate reference system transformations.
• Shapely: Geometry manipulation made easy.
• APScheduler: A flexible scheduling library for background jobs.
• SQLAlchemy: The go-to library for database interaction and ORM functionality.
• pytz: Comprehensive timezone support.
• tzlocal: Simplifies local timezone detection.

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📞 Support

• 📖 Documentation
• 🐛 Issue Tracker
• 💬 Discussions
• 📧 Email

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Made with ❤️ for the geospatial community