Building a Python Microservice with FastAPI to Return Random African Countries

Building Python microservices is easier and faster with modern frameworks like FastAPI.

In this guide, we’ll walk through creating a Python microservice that returns a list of 10 random African countries using FastAPI. By the end of this tutorial, you’ll have a fully functional microservice that can return data about African countries, following best practices for scalable and maintainable code.

Step-by-Step Guide to Build the FastAPI Microservice

1. Setting up the Environment

To begin, ensure you have Python installed on your machine. Instead of installing dependencies globally, we’ll use a virtual environment for package management. Virtual environments allow you to isolate project dependencies, preventing conflicts with system-wide installations.

Steps to set up a virtual environment:

1. Open your terminal and navigate to your project directory.
2. Create a virtual environment by running the following command:

   python3 -m venv venv

1. Activate the virtual environment:

   source venv/bin/activate

With the virtual environment active, install FastAPI by running:

pip install "fastapi[standard]"

You can check out the full video on setting up a virtual environment in the description of this article or through the YouTube video linked below.

2. Structuring the Project

A well-organized project structure is crucial for scalability and maintainability. We’ll set up a basic structure for this service that separates concerns like data and logic.

african_countries_service/
│
├── main.py # FastAPI entry point
└── data.py # Contains the hardcoded data for African countries

• main.py is where the FastAPI app is defined.
• data.py holds the list of African countries and their details.

3. Coding the Microservice

Now, let’s move on to the implementation. We’ll start with the hardcoded data in data.py, followed by setting up our FastAPI application in main.py.

data.py:

import random

# List of 10 hardcoded African countries with name, population, and capital
COUNTRIES = [
    {'name': 'Nigeria', 'population': '180 million', 'capital': 'Abuja'},
    {'name': 'Ghana', 'population': '80 million', 'capital': 'Accra'},
    {'name': 'Kenya', 'population': '53 million', 'capital': 'Nairobi'},
    {'name': 'South Africa', 'population': '59 million', 'capital': 'Pretoria'},
    {'name': 'Egypt', 'population': '102 million', 'capital': 'Cairo'},
    {'name': 'Morocco', 'population': '36 million', 'capital': 'Rabat'},
    {'name': 'Ethiopia', 'population': '115 million', 'capital': 'Addis Ababa'},
    {'name': 'Ivory Coast', 'population': '26 million', 'capital': 'Yamoussoukro'},
    {'name': 'Uganda', 'population': '45 million', 'capital': 'Kampala'},
    {'name': 'Senegal', 'population': '17 million', 'capital': 'Dakar'},
]

def get_random_countries(n=10):
    """Return a list of n random African countries."""
    return random.sample(COUNTRIES, k=n)

Next, in main.py , we define the FastAPI app and create a route that returns a list of random African countries.

main.py:

from fastapi import FastAPI
from data import get_random_countries

app = FastAPI()

@app.get("/countries", response_model=list)
def read_countries():
    """
    Returns a list of 10 random African countries.
    """
    countries = get_random_countries()
    return countries

Download the source

4. Best Practices for FastAPI Microservices

• Modularity : We keep the data separate from the logic, ensuring that the app is easily maintainable and extendable.
• Validation and Security : FastAPI allows for automatic request validation, though not required here, it’s best to follow this principle when accepting inputs.
• Documentation : FastAPI automatically generates OpenAPI documentation and provides a UI using Swagger.

5. Running the Application

Run the app with the following command:

fastapi dev main.py

By default, the service will be available at http://127.0.0.1:8000.

6. Testing the API

To test the service, you can navigate to http://127.0.0.1:8000/countries. You should see a JSON response with 10 random African countries, for example:

[
  {"name": "Nigeria", "population": "180 million", "capital": "Abuja"},
  {"name": "Uganda", "population": "45 million", "capital": "Kampala"},
  {"name": "Kenya", "population": "53 million", "capital": "Nairobi"},
  {"name": "Morocco", "population": "36 million", "capital": "Rabat"},
  {"name": "Egypt", "population": "102 million", "capital": "Cairo"},
  {"name": "Senegal", "population": "17 million", "capital": "Dakar"},
  {"name": "Ivory Coast", "population": "26 million", "capital": "Yamoussoukro"},
  {"name": "Ethiopia", "population": "115 million", "capital": "Addis Ababa"},
  {"name": "Ghana", "population": "80 million", "capital": "Accra"},
  {"name": "South Africa", "population": "59 million", "capital": "Pretoria"}
]

7. Auto-Generated API Documentation

FastAPI provides auto-generated interactive API documentation. You can access the Swagger UI at http://127.0.0.1:8000/docs and ReDoc documentation at http://127.0.0.1:8000/redoc.

Conclusion

In this tutorial, we built a Python microservice using FastAPI to return a list of 10 random African countries. FastAPI’s simplicity and performance make it a perfect choice for microservices. With auto-generated docs, input validation, and modularity, this approach is highly scalable and maintainable.

Thanks for reading…

Happy Coding!

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