Ruter - Public Transport Real-Time Tracking and Ticketing System

Event-sourced, CQRS-based architecture for real-time vehicle tracking and ticketing.

Tech Stack

• Event Store: InfluxDB
• Command/Query Services: Python + FastAPI
• Event Bus: Kafka
• Real-Time Bus: NATS
• Graph Database: Neo4j
• Relational Database: PostgreSQL

Quick Start

Prerequisites

• Docker and Docker Compose
• Python 3.10+

Setup

1. Clone the repository
2. Copy .env.example to .env and adjust if needed
3. Start infrastructure:

   docker-compose up -d

4. Install Python dependencies:

   pip install -r requirements.txt

5. Run database migrations:

   alembic upgrade head

6. Start services (each in separate terminal):

   # Command Service
   uvicorn services.command_service.main:app --reload --port 8000
   
   # Query Service
   uvicorn services.query_service.main:app --reload --port 8001
   
   # Vehicle Tracker Service
   uvicorn services.vehicle_tracker_service.main:app --reload --port 8002
   
   # Vehicle Projection Service
   python -m services.vehicle_projection_service.main
   
   # Ticket Service
   uvicorn services.ticket_service.main:app --reload --port 8003
   
   # Ticket Projection Service
   python -m services.ticket_projection_service.main
   
   # Validation Service
   uvicorn services.validation_service.main:app --reload --port 8004
   
   # Neo4j Graph Updater
   python -m services.neo4j_graph_updater.main
   
   # Route Graph Service
   uvicorn services.route_graph_service.main:app --reload --port 8005
   
   # Replay Service
   uvicorn services.replay_service.main:app --reload --port 8006

Running Tests

pytest tests/

Architecture

The system follows Event Sourcing and CQRS patterns:

• Commands → Command Services → Events → Kafka → InfluxDB (Event Store)
• Events → Projection Services → Read Models → PostgreSQL
• Real-Time Updates → NATS → UI Clients

Project Structure

See the implementation plan for detailed structure.