# TSYS-AIOS-GIS-Tools-GIS-Processing Container

This container is part of the TSYS-AIOS-GIS project and provides advanced GIS data processing capabilities with Jupyter notebooks and workflow tools.

## Overview

The TSYS-AIOS-GIS-Tools-GIS-Processing container extends the base GIS container with advanced processing tools, Jupyter notebooks for interactive analysis, and workflow orchestration tools. This container is designed for in-depth geospatial data analysis and complex ETL workflows.

## Tools Included

### Extends from Base Container
- All tools from TSYS-AIOS-GIS-Tools-GIS-Base container
- GIS libraries, weather data processing libraries, visualization tools

### Advanced Processing Tools
- **Jupyter Notebook**: Interactive environment for data analysis
- **Node.js/npm**: JavaScript runtime and package manager
- **IPyKernel**: IPython kernel for Jupyter

### Workflow Tools
- **Apache Airflow**: Workflow orchestration platform
- **Prefect**: Modern workflow management

## Usage

### Building the Processing Container
```bash
# From this directory
cd /home/localuser/AIWorkspace/TSYS-AIOS-GIS/Docker/TSYS-AIOS-GIS-Tools-GIS-Processing

# Use the wrapper script to automatically detect and set user IDs
./docker-compose-wrapper.sh build

# Or run commands in the processing container with automatic user mapping
./docker-compose-wrapper.sh run tsys-gis-processing [command]

# Example: Start Jupyter notebook server
./docker-compose-wrapper.sh run tsys-gis-processing jupyter notebook --ip=0.0.0.0 --port=8888 --allow-root --notebook-dir=/workspace --no-browser

# Example: Start an interactive bash session
./docker-compose-wrapper.sh run tsys-gis-processing bash
```

### Using with docker-compose directly
```bash
# Set environment variables and run docker-compose directly
LOCAL_USER_ID=$(id -u) LOCAL_GROUP_ID=$(id -g) docker-compose up --build

# Or export variables first
export LOCAL_USER_ID=$(id -u)
export LOCAL_GROUP_ID=$(id -g) 
docker-compose up
```

### Using the wrapper script
```bash
# Build and start the processing container with automatic user mapping
./docker-compose-wrapper.sh up --build

# Start without rebuilding (Jupyter will be available on port 8888)
./docker-compose-wrapper.sh up

# View container status
./docker-compose-wrapper.sh ps

# Stop containers
./docker-compose-wrapper.sh down
```

## Jupyter Notebook Access

When running the container with `docker-compose up`, Jupyter notebook will be available at:
- http://localhost:8888

The notebook server is preconfigured to:
- Use the workspace directory as the notebook directory
- Allow access without authentication (in container only)
- Accept connections from any IP address

## User ID Mapping (For File Permissions)

The container automatically detects and uses the host user's UID and GID to ensure proper file permissions. This means:

- Files created inside the container will have the correct ownership on the host
- No more root-owned files after container operations
- Works across different environments (development, production servers)

The container detects the user ID from the mounted workspace volume. If needed, you can override the default values by setting environment variables:

```bash
# Set specific user ID and group ID before running docker-compose
export LOCAL_USER_ID=1000
export LOCAL_GROUP_ID=1000
docker-compose up
```

Or run with inline environment variables:
```bash
LOCAL_USER_ID=1000 LOCAL_GROUP_ID=1000 docker-compose up
```

The container runs as a non-root user named `TSYS-Tools` with the detected host user's UID/GID.

## Data Processing Workflows

This container is optimized for:
- Interactive geospatial analysis using Jupyter notebooks
- Complex ETL workflows using Apache Airflow or Prefect
- Advanced visualization and reporting
- Model development and testing
- Integration with PostGIS and other databases