geocoding API built with FastAPI and the Nominatim service Part 1

Geocoding is the process of converting addresses or place names into geographic coordinates (latitude and longitude). It is a common task in many applications that deal with location data, such as mapping platforms, location-based search engines, and logistics systems.

In this article, we will introduce a simple geocoding API that allows users to get the geographic coordinates of an address. The API is built with FastAPI, a modern, fast, and easy-to-use web framework for building APIs in Python, and the Nominatim service, an open source geocoding service provided by the OpenStreetMap project..

Prerequisites

Before we start building the API, make sure you have the following prerequisites installed:

• FastAPI: a modern, fast, web framework for building APIs with automatic documentation and validation.
• Uvicorn: a lightning-fast ASGI server.
• You can install these dependencies by running the following command:

pip install fastapi
pip install uvicorn
pip install requests

Creating the API Views

Next, we will create the views for the API using FastAPI. We will create two views: one for geocoding an address, and another for reverse geocoding coordinates.

from fastapi import FastAPI
import requests

app = FastAPI()

@app.get("/geocode")
def geocode(address: str):
    # Make a request to the Nominatim service
    response = requests.get("http://nominatim.openstreetmap.org/search", params={"q": address, "format": "json"})
    data = response.json()
    
    # Extract the latitude and longitude from the response
    lat = data[0]["lat"]
    lon = data[0]["lon"]
    
    return {"latitude": lat, "longitude": lon}

Using the API

Now that our API is up and running, let’s see how we can use it in a simple Python script:

import requests

# Make a GET request to the API endpoint
response = requests.get("http://localhost:8000/geocode", params={"address": "1 rue de la Paix, Paris"})

# Print the response
print(response.json())

# the response
{'latitude': '48.8685535', 'longitude': '2.3303318'}

This will make a request to the API endpoint with the address “1 rue de la Paix, Paris” and print the response, which should be a JSON object containing the latitude and longitude of the address.

We can also use the API in other programming languages by making HTTP requests to the endpoint using a library or tool of our choice. For example, we could use the fetch function in JavaScript or the httplib module in Python to make a request to the API and get the response.

Conclusion

In this article, we introduced a simple geocoding API built with FastAPI and the Nominatim service.

While the API that we have built is basic, it demonstrates the power and flexibility of FastAPI and the Nominatim service. With a few lines of code, we were able to create a functional API that can be used in a wide range of applications that deal with location data.

There are many other features and capabilities that we could add to the API, such as error handling, rate limiting, caching, and authentication. We could also use other geocoding services or data sources to improve the accuracy and coverage of the API.

Overall, building a geocoding API with FastAPI and Nominatim is a quick and easy way to add geocoding functionality to our applications, and opens up many possibilities for working with location data in new and innovative ways.

Here are a few ideas for adding additional features and capabilities to the geocoding API:

• Error handling: It is important to handle errors and exceptions gracefully in the API to provide a reliable and user-friendly experience. For example, we could add some error handling to the API endpoint to check for cases where the Nominatim service returns an error, or the input address is invalid. We could then return a custom error message or status code to the user, depending on the type of error that occurred.
• Rate limiting: To prevent excessive use of the API and protect the underlying geocoding service, we could implement rate limiting to restrict the number of requests that can be made by a single user or IP address in a given time period. This can be done using a library like FastAPI-Limiter or by adding custom code to the endpoint.
• Caching: To improve the performance and scalability of the API, we could add caching to store the results of previous requests and reuse them for subsequent requests. This would reduce the number of requests made to the geocoding service and make the API more responsive. We could use a library like FastAPI-Cache or implement our own caching system using a database or cache store like Redis.
• Authentication: Depending on the intended use of the API, we may want to add authentication to restrict access to authorized users or applications. We could use a library like FastAPI-Security or FastAPI-JWT to implement JWT-based authentication, or we could use a third-party authentication provider like Auth0 or Okta.
• Additional geocoding services: To improve the accuracy and coverage of the API, we could consider using additional geocoding services or data sources. For example, we could use the Google Maps Geocoding API or the Mapbox Geocoding API, which offer more comprehensive coverage and a range of advanced features. We could also use open data sources like OpenStreetMap or OpenAddresses to supplement the results from the Nominatim service.

I hope these ideas give you some inspiration for adding additional features and capabilities to your geocoding API.

Continued in part 2