How to Create an Efficient API: A 4-Step Guide

Application programming interfaces (APIs) are a ubiquitous part of the modern-day software and computing infrastructure. They enable seamless communication between different applications, allowing them to easily connect and exchange data. You interact with APIs every day in your life, from sending a text on your smartphone to making an online payment.

Given their significance in building quality applications, it becomes crucial to understand what APIs are, how they work, and how to build one effectively. A well-crafted API not only enhances an application’s user experience, but also ensures smoother integrations, reduces development time, and provides a robust foundation for future growth and scalability.

In this blog post, we’ll build a simple yet efficient REST API in four easy-to-understand steps using Python and FastAPI. By the end of this guide, you will have a solid foundation in API development and be able to build and deploy APIs for your needs in the future. We’ll also explore how you can use CData Connect to easily integrate your newly built API with any application, and seamlessly connect with real-time data from over 300 enterprise sources.

Let’s get started!

What is an API?

An API (application programming interface) is a set of instructions, protocols, and routines that enable different software programs and computer systems to communicate with each other by exchanging data.

APIs act as intermediaries that handle the exchange of data between applications, ensuring that different systems can work together effectively without needing to understand the underlying code or architecture of each other.

For instance, when you use a weather app on your phone, it uses an API to fetch data from a remote server. The API handles the request, retrieves the weather data, and sends it back to the app in a format that can be easily displayed. You’ll get a similar experience when you check the weather on a web browser or from your car.

How to build an API in 4 steps

For our example, we will be building a REST API using Python that fetches order customer details from an e-commerce store. This guide assumes that you have the basic familiarity with the Python programming language, as well as a rudimentary understanding of databases and SQL.

Here are the four steps to guide you through building the API:

1. API planning: Determine the goals and requirements of the API based on user needs.
2. API design: Create the API’s structure and define its security measures.
3. API development: Build and optimize the API, ensuring it meets defined specifications.
4. API testing: Evaluate the API for functionality and performance to confirm it works as intended.

Let's explore each step in detail.

API planning

This is the most important step in the API development process, as it lays the foundation for building a well-structured and functional API. Be clear and to the point in terms of your API's purpose, the resources it will manage, and how clients will interact with it. For better clarity, consider visualizing the API plan using a tool like draw.io to map out the structure and flow.

Here's a plan for our e-commerce order retrieval API:

Define the target users and goals

• Define target users: To build an effective and useful API, you need to understand its end users, which equally defines the scope, complexity, and capabilities of the API. A line-of-business user may only need the ability to request simple data sets, while a data engineer may need to write data back to the system or even change its structure. For our e-commerce API, the primary users would be the customer support agents, analysts, and customers accessing their order details through the web or mobile applications.
• Set goals: Unequivocally defining the API’s functionality is equally important. For example, you may build an API that will enable users to retrieve and update order information. However, for some users, the requirements might also include additional functionalities such as real-time notifications or historical data analysis. It's essential to clearly define the API’s functionality and ensure it adapts to evolving user needs. For our e-commerce example, the API should deliver accurate and timely order information to improve order management and support.

Understand the users’ needs

• Gather feedback: Collect input from potential users to identify essential features, such as real-time order status updates and detailed item information. This helps you determine which features are crucial and whether to include additional functionalities. For our e-commerce API, we can gather feedback from customers, support agents, and shoppers to ensure it supports key functions.
• Analyze use cases: Document scenarios like retrieving order history or checking the status of an order. For example, a customer may want to view past purchases or track a shipment. Document different use cases such as real-time order tracking and filtering order history to ensure the API addresses both common and edge cases.

Determine requirements

• Technical requirements: To build an API, you need to select the appropriate language, framework, and tools, and design the database schema based on the API’s functional needs. FastAPI is ideal for efficient routing and request validation. Performance optimization is crucial for handling high traffic and maintaining fast response times. For our e-commerce API, Python and FastAPI will be used to ensure effective data handling and robust performance, while also implementing security measures to protect sensitive order information.
• Functional requirements: Define clear API endpoints (e.g., /orders/{orderId}) and decide on data formats (such as JSON) to maintain consistency and ease of use. Establish what each endpoint will retrieve from the database, and how it will handle various types of requests. For our e-commerce API, the endpoints will facilitate actions like retrieving order details and updating order statuses, ensuring seamless integration and user interaction.
• Non-functional requirements: Ensure the API is scalable, reliable, and maintainable by leveraging FastAPI’s asynchronous capabilities. This approach helps manage high performance demands and supports a growing number of users and requests. For our e-commerce API, this means implementing efficient error handling and performance monitoring to maintain service quality under varying loads.

API design

This step focuses on crafting the structure and functionality of the API to ensure it meets the defined goals and requirements. For our e-commerce order retrieval API, the design phase involves:

Choose an architectural style

• RESTful architecture: Opt for REST (Representational State Transfer) for its simplicity, scalability, and use of standard HTTP methods such as GET, POST, PUT, and DELETE. RESTful APIs leverage a stateless nature, meaning each request from a client to the server must contain all the information needed to understand and process the request, independent of previous interactions. This ensures a clear and consistent interface, making it easier to interact with the API. In our e-commerce API, using REST will streamline operations like fetching order details or updating statuses, allowing for a straightforward and efficient way to handle various user requests while maintaining a scalable and easy-to-manage architecture.

Structure your API

• Design endpoints: Create clear and intuitive endpoints, such as /orders/{orderId} for retrieving individual order details and /orders for retrieving multiple orders or order history.
• Resource models: Define resource models that represent orders and customer details. Ensure that each resource is accessible via unique URLs and adheres to REST principles for simplicity and uniformity.
• Data representation: Use JSON for data representation due to its ease of use and compatibility with most client applications.

Prioritize security

• Authentication and authorization: Implement authentication mechanisms (e.g., OAuth 2.0) to ensure that only authorized users can access the API.
• Data encryption: Use HTTPS to encrypt data transmitted between the client and server, safeguarding sensitive information from unauthorized access.
• Rate limiting: Apply rate limiting to prevent abuse and ensure fair usage of the API resources.

API development

This is the step of building and implementing the API. The API will work on the request and response format, where a client (such as a web or mobile application) will send a request to the API for a resource (customer ID, order number, item details etc.). The API will then process the request, retrieve the relevant resource, and return a structured response in the JSON format.

Define API responses

1. Set up your environment

   Install Python’s FastAPI framework. You’ll also need an async server like uvicorn to run the FastAPI app. Open a terminal or command prompt and run the following command.

   pip install fastapi uvicorn

   This command installs the necessary packages — FastAPI for building APIs and Uvicorn as the server to run the FastAPI app.

2. Create a basic FastAPI application

   Start by creating a Python file, e.g., main.py, and set up a basic FastAPI application. Import all the required modules.

   from fastapi import FastAPI, HTTPException
from typing import Optional
from pydantic import BaseModel
import asyncio

app = FastAPI()
@app.get("/")
def read_root():
      return {"message": "Welcome to the e-Commerce Order API"}

   Here, FastAPI is used to create a new application instance, and a simple root endpoint is defined. This endpoint returns a welcome message when the API is accessed at the base URL.

3. Define endpoints for order retrieval

   Add an endpoint to fetch order details by order ID. This endpoint will simulate retrieving data from a database.

   # Mock database

orders_db = {

      "123": {"order_id": "123", "customer_id": "456", "item":
"Laptop", "quantity": 1},
      "789": {"order_id": "789", "customer_id": "456", "item":
"Smartphone", "quantity": 2},
      "101": {"order_id": "101", "customer_id": "789", "item":
"Tablet", "quantity": 3},
      "102": {"order_id": "102", "customer_id": "101", "item":
"Monitor", "quantity": 1},
      "103":{"order_id": "103", "customer_id": "202", "item":
"Keyboard", "quantity": 5}

}

@app.get("/orders/{order_id}")
def get_order(order_id: str):
      order = orders_db.get(order_id)

     if order is None:
      return {"error": "Order not found"}
      return order

   This endpoint handles GET requests to /orders/{order_id}. It simulates a database call using asyncio.sleep(1), retrieves the order details from the orders_db, and returns the order information. If the order ID doesn’t exist in the database, a 404 error is raised.

Handle exceptions and errors

Ensure the API gracefully handles errors, such as when an order is not found. The example above includes basic error handling, but you can expand it for more complex scenarios, such as validation errors, database connection issues, and unauthorized access.

#Handling Errors
@app.get("/orders/{order_id}")
async def get_order(order_id: str):
     order = orders_db.get(order_id)

    if order is None:
     raise HTTPException(status_code=404, detail="Order not found")

    return order

In the case where an order is not found, the API responds with a 404 error and a detailed message. This ensures the API provides meaningful feedback to the client, which is crucial for debugging and improving user experience.

Analyze and optimize performance

For a production setup, consider using caching and database indexing to improve performance. FastAPI supports asynchronous operations, which helps in handling multiple requests efficiently.

#performance optimization

class Order(BaseModel):

     order_id: str
     customer_id: str
     item: str
     quantity: int

@app.get("/orders/{order_id}")

async def get_order(order_id: str):
     await asyncio.sleep(1) # Simulate database call
     order = orders_db.get(order_id)

    if order is None:
     raise HTTPException(status_code=404, detail="Order not found")
     return order

The Order class is defined using Pydantic's BaseModel, which helps ensure that the data structure is maintained correctly. This can be useful if you need to validate the data structure or if you plan to extend the API to accept POST requests in the future.

Run the application

Use uvicorn to run the FastAPI application locally.

uvicorn main:app –reload

With these steps, you've now successfully built an API using FastAPI that retrieves e-commerce order details. You've planned the API, defined the endpoints, handled errors, and optimized performance.

API testing

Testing is a critical step in the API development process to ensure that the API functions as expected, meets requirements, and handles edge cases effectively. It helps identify and fix bugs, improves reliability, and enhances the user experience.

To test your API, use an http client like Postman. Postman is a widely used API testing tool that provides an intuitive interface for sending requests and viewing responses.

Test the API by submitting requests to the various API endpoints, ensuring that proper requests receive the 200 OK status and an appropriate response and improper requests receive appropriate error messaging.

Below, you'll find some sample tests for our mock API. Our API server is running on http://localhost:8000/. Start the server using uvicorn main:app --reload from your API’s directory. Stop the server with Ctrl-C.

Test #1: Retrieve an existing order

Create a GET request for the URL http://localhost:8000/orders/123. Check to see if the API returns a 200 OK status and displays the order details.

Test #2: Retrieve a non-existent order

Create a GET request with URL http://localhost:8000/orders/999. Verify that the API returns a 404 Not Found status with an error message indicating that the order does not exist.

Test #3: Add a new order (mock POST request)

Simulate adding an order with a POST request to http://localhost:8000/orders/. The response will result in an error ss we have not implemented the POST functionality. However, you can consider adding it in the future by modifying your source code.

Test #4: Handle multiple orders for the same customer

Create a GET request with URL http://localhost:8000/orders?customer_id=456. Verify the API returns orders for the specified customer. Since we have not implemented this feature in our code, you can add it to your API in future updates to retrieve multiple orders of the same customer.

Test #5: Security testing

• Add authorization header: In Postman, add an Authorization header with incorrect credentials or leave it blank.
• Send request: Send the request to any API endpoint.
• Check response: The API should return a 401 Unauthorized or 403 Forbidden

This test highlights the need for future security features such as API keys or OAuth. To enhance security, you can integrate authentication mechanisms like API keys or OAuth to manage access and protect endpoints from usage abuse.

CData Connect for your API

Your API is now ready for deployment. But what if you need a streamlined way to connect it to different data tools? CData Connect has you covered.

CData Connect is a universal data connectivity platform that simplifies integrating your API with various applications. It offers real-time data connectivity, data virtualization, and centralized management, allowing you to seamlessly connect with real-time data from over 300 enterprise sources, whether on-premises or in the cloud.

Unlock the full potential of your API with CData Connect. Start your free trial today!