RetroGeo - An Offline Reverse Geocoding Library

Overview

Our reverse geocoding library is a high-performance, offline solution that processes geographical coordinates to retrieve full addresses, including country, state, and city. With pre-downloaded datasets and no need for online queries or API calls, this library excels in applications where internet connectivity is limited or unavailable.

Key Features

• Offline-capable
  Process massive geospatial datasets without relying on external dependencies.

• High accuracy
  Leverage built-in data compression and storage optimizations to minimize disk space while maintaining high accuracy.

• Large-scale operations
  Efficiently handle vast amounts of location data, making it ideal for:

  • Geospatial analysis
    Perform rapid location lookup and analysis without external dependencies.

  • Mobile applications
    Develop offline-capable mobile apps that can handle large geospatial datasets.

  • Data processing pipelines
    Streamline your data processing pipeline with efficient reverse geocoding operations.

Why Choose Our Library?

• No API calls
  Avoid online queries and reliance on external services, ensuring your application's independence and security.

• High performance
  Optimized for speed and accuracy, our library can handle massive datasets without sacrificing performance.

• Easy integration
  Simple to incorporate into your existing projects, with minimal setup required.

Get Started

Installation

Install our library via pip:

pip install RetroGeo

Example

For Single Thread Execution (For a single coordinate pair)

import asyncio

from RetroGeo import GeoLocator, ThreadTypeEnum


async def main():
    rev = GeoLocator()
    locations = [(9.964498569974612, 76.25592213325532)]
    result = await rev.getLocationFromCoordinates(locations, mode=ThreadTypeEnum.SINGLE_THREADED.value)
    print(result)


if __name__ == '__main__':
    asyncio.run(main())

For Multithread Execution (List of coordinates pairs)

import asyncio
import random

from RetroGeo import GeoLocator


async def main():
    rev = GeoLocator()
    locations = []
    for _ in range(10000):
        lat = random.uniform(-90, 90)
        lon = random.uniform(-180, 180)
        locations.append((lon, lat))
    results = await rev.getLocationFromCoordinates(locations)


if __name__ == '__main__':
    asyncio.run(main())

Output

The Output would a dictionary with key as the given coordinates and the output as the LocationBaseModel. Which is a pydantic base model

class LocationBaseModel(BaseModel):
    lat: float = Field(..., description="Latitude of the main location")
    lon: float = Field(..., description="Longitude of the main location")
    name: str = Field(..., description="Name of the location")
    admin1: str = Field(..., description="Name of the primary administrative division (e.g., country)")
    admin2: str = Field(..., description="Name of the secondary administrative division (e.g., state or province)")
    admin1_id: int = Field(..., description="ID of the primary administrative division")
    admin2_id: int = Field(..., description="ID of the secondary administrative division")
    admin1_lat: Optional[float] = Field(None, description="Latitude of the primary administrative division")
    admin1_lon: Optional[float] = Field(None, description="Longitude of the primary administrative division")
    admin2_lat: Optional[float] = Field(None, description="Latitude of the secondary administrative division")
    admin2_lon: Optional[float] = Field(None, description="Longitude of the secondary administrative division")

{(9.964498569974612, 76.25592213325532): LocationBaseModel(lat=9.93988, lon=76.26022, name='Cochin', admin1='India', admin2='Kerala', admin1_id=101, admin2_id=4028, admin1_lat=20.0, admin1_lon=77.0, admin2_lat=10.8505159, admin2_lon=76.2710833)}