traffic-aware-route-optimizer 1.0.0

Traffic-aware route optimization using Google Routes API

Traffic-Aware Route Optimizer

A lightweight, extensible Python library for traffic-aware route optimization using Google Routes API. This tool provides multi-waypoint route optimization with real-time traffic consideration, time window constraints, and flexible scheduling options.

Project Description

The Traffic-Aware Route Optimizer aims to provide an extendable, efficient route optimization solution for Python applications. This tool is built for Python 3.8+ and provides a simple yet powerful interface for complex routing problems.

Documentation

The documentation and examples can be found in this README and the project's GitHub repository.

Project Status

This tool is actively maintained and has been successfully deployed in various logistics and routing applications. We welcome contributions and feedback from the community.

Features

• Multi-waypoint route optimization - Optimize routes with multiple stops
• Real-time traffic consideration - Uses Google Routes API for current traffic data
• Time window constraints - Support for delivery time windows and scheduling
• Flexible scheduling options - Configurable work hours, break times, and visit durations
• Distance and duration calculations - Accurate travel time and distance metrics
• Priority-based routing - Support for different destination priorities

Installation and Usage

We recommend using a virtual environment for development.

Installation from PyPI

pip install traffic-aware-route-optimizer

Development Installation

Clone the repository and install in development mode:

git clone https://github.com/lutic1/traffic-aware-route-optimizer.git
cd traffic-aware-route-optimizer
pip install -e .

Usage Example

from route_planner import GoogleRoutesClient, Location, Destination

# Initialize client with your Google Routes API key
client = GoogleRoutesClient(api_key="YOUR_GOOGLE_ROUTES_API_KEY")

# Define starting location
start_location = Location(lat=40.7128, lng=-74.0060)

# Define destinations to visit
destinations = [
    Destination(
        destination_id="stop_1",
        name="First Stop",
        address="123 Main St, New York, NY",
        lat=40.7589,
        lng=-73.9851,
        priority=1,  # Higher priority (1=urgent, 5=low)
        time_window_start="09:00",
        time_window_end="17:00"
    ),
    Destination(
        destination_id="stop_2", 
        name="Second Stop",
        address="456 Broadway, New York, NY",
        lat=40.7831,
        lng=-73.9712,
        priority=2
    )
]

# Optimize the route
try:
    optimized_route = client.optimize_route(
        start_location=start_location,
        destinations=destinations,
        visit_duration_minutes=30,
        work_start="08:00",
        work_end="18:00"
    )
    
    print(f"Total distance: {optimized_route.total_drive_km:.2f} km")
    print(f"Total time: {optimized_route.total_drive_minutes} minutes")
    
    for stop in optimized_route.stops:
        print(f"Stop {stop.sequence_number}: {stop.destination.name}")
        print(f"  Arrival: {stop.arrival}")
        print(f"  Departure: {stop.departure}")
        
except Exception as e:
    print(f"Route optimization failed: {e}")

Requirements

• Python 3.8+
• Google Routes API key
• Dependencies:
  • pydantic>=2.0.0 - Data validation and parsing
  • googlemaps>=4.10.0 - Google Maps API client
  • httpx>=0.24.0 - HTTP client for API requests

Configuration

Set your Google Routes API key as an environment variable:

export GOOGLE_MAPS_API_KEY="your_api_key_here"

Or pass it directly to the client:

client = GoogleRoutesClient(api_key="your_api_key_here")

API Reference

Core Classes

• GoogleRoutesClient - Main client for route optimization
• Location - Geographic coordinate representation
• Destination - Destination with metadata and constraints
• OptimizedSchedule - Complete optimized route result
• ScheduleStop - Individual stop in the optimized route

Contributing

We welcome contributions! Please feel free to submit issues, feature requests, or pull requests.

License

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

Author

Luis Ticas - [e-mail]

Acknowledgments

• Built using Google Routes API for accurate traffic-aware routing
• Inspired by the need for efficient logistics and route planning solutions

Requirements

• Python 3.8+
• Google Maps API key
• pydantic>=2.0.0
• googlemaps>=4.10.0
• httpx>=0.24.0