What is Fast API and What You Can Do With It

4 min readAug 20, 2023

In web development, speed, efficiency, and ease of use are crucial factors. This is where FastAPI comes into play. FastAPI is a modern, high-performance web framework for building APIs with Python. In this article, we’ll delve into the details of FastAPI and explore the exciting possibilities it offers for developers.

Introduction to FastAPI
Why Choose FastAPI for Web Development
Getting Started with FastAPI
Creating APIs with FastAPI
Defining Data Models and Schemas
Handling Requests and Responses
Authentication and Authorization
Validation and Data Serialization
Background Tasks and Asynchronous Programming
Integrating Databases with FastAPI
Building Real-time Applications
Deployment and Scaling
Monitoring and Testing
Best Practices for FastAPI Development
Conclusion

Introduction to FastAPI

FastAPI is a robust web framework enabling developers to build Python APIs quickly. It combines the simplicity of Python with the performance of asynchronous programming, making it an ideal choice for applications that demand high speed and efficiency.

Why Choose FastAPI for Web Development

FastAPI has gained popularity for several reasons:

1. High Performance

FastAPI leverages asynchronous programming, allowing it to handle many concurrent requests without slowing down. This makes it an excellent choice for applications requiring real-time updates.

2. Automatic Documentation

One standout feature of FastAPI is its automatic generation of interactive API documentation. This saves developers time and effort by creating detailed documentation based on the code.

3. Data Validation

FastAPI provides automatic data validation, ensuring the data sent to and received from APIs is accurate and well-structured. This reduces the chances of errors and improves the overall reliability of the application.

4. Type Hinting

With built-in support for Python-type hints, FastAPI offers enhanced code readability and fewer runtime errors. This feature makes collaboration between developers smoother and more efficient.

Getting Started with FastAPI

To start using FastAPI, follow these simple steps:

1. Install FastAPI

Begin by installing FastAPI using a package manager like pip:

pip install fastapi

2. Create Your First API

Create a Python file (e.g., main.py) and import the necessary modules:

from fastapi import FastAPI

app = FastAPI()

@app.get("/")
def read_root():
    return {"message": "Welcome to FastAPI"}

Creating APIs with FastAPI

FastAPI makes API creation a breeze. Define your API’s routes and the corresponding functions that handle them. Here’s an example:

1. Import FastAPI and Create an App

from fastapi import FastAPI

app = FastAPI()

2. Define an API Route

@app.get("/items/{item_id}")
def read_item(item_id: int, q: str = None):
    return {"item_id": item_id, "q": q}

Defining Data Models and Schemas

FastAPI allows you to define data models and schemas using Python’s pydantic library. This ensures that the data you send and receive is structured and valid.

Define a Data Model

from pydantic import BaseModel

class Item(BaseModel):
    name: str
    description: str = None

Handling Requests and Responses

FastAPI simplifies request handling and response generation. You can easily handle query parameters, request bodies, and headers.

Handling Query Parameters

@app.get("/items/")
def read_items(skip: int = 0, limit: int = 10):
    return {"skip": skip, "limit": limit}

Authentication and Authorization

FastAPI provides various authentication and authorization methods to secure your APIs.

OAuth2 Authentication

from fastapi.security import OAuth2PasswordBearer

oauth2_scheme = OAuth2PasswordBearer(tokenUrl="token")

Validation and Data Serialization

FastAPI automatically validates incoming data against your data models. It also handles data serialization for responses.

Request Data Validation

@app.post("/items/")
def create_item(item: Item):
    return item

Background Tasks and Asynchronous Programming

FastAPI supports background tasks and asynchronous programming, allowing you to perform tasks concurrently without blocking the main application.

Background Task Example

from fastapi import BackgroundTasks

def send_notification(email: str, message: str):
    # Code to send notification
    pass

@app.post("/send-notification/")
async def send_notification_route(email: str, message: str, background_tasks: BackgroundTasks):
    background_tasks.add_task(send_notification, email, message)
    return {"message": "Notification sent"}

Integrating Databases with FastAPI

FastAPI seamlessly integrates with various databases, making storing and retrieving data easy.

SQLAlchemy Integration

from sqlalchemy import create_engine
from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy.orm import sessionmaker

SQLALCHEMY_DATABASE_URL = "sqlite:///./test.db"
engine = create_engine(SQLALCHEMY_DATABASE_URL)
SessionLocal = sessionmaker(autocommit=False, autoflush=False, bind=engine)
Base = declarative_base()

Building Real-time Applications

FastAPI’s asynchronous capabilities make it well-suited to build real-time applications using WebSockets.

WebSocket Example

from fastapi import FastAPI, WebSocket

app = FastAPI()

@app.websocket("/ws")
async def websocket_endpoint(websocket: WebSocket):
    await websocket.accept()
    while True:
        data = await websocket.receive_text()
        await websocket.send_text(f"Message text was: {data}")

Deployment and Scaling

A FastAPI application can be deployed using ASGI servers like Uvicorn or Hypercorn. Scaling can be achieved through load balancers and containerization.

Monitoring and Testing

FastAPI provides tools for monitoring and testing your application, ensuring its reliability and performance.

Best Practices for FastAPI Development

To make the most of FastAPI, keep these best practices in mind:

Use type hints and data models for improved validation and documentation.
Leverage asynchronous programming for handling concurrent requests.
Implement proper authentication and authorization mechanisms.
Regularly test and monitor your application for any issues.

Conclusion

FastAPI revolutionizes web development with its speed, simplicity, and performance. Whether you’re building APIs, real-time applications, or data-driven services, FastAPI empowers developers to create robust and efficient solutions.

FAQs

Q1: Is FastAPI suitable for beginners?

FastAPI is relatively easy to learn, especially if you have prior experience with Python. Its intuitive syntax and automatic documentation generation make it beginner-friendly.

Q2: Can FastAPI be used with databases other than SQLAlchemy?

FastAPI supports integration with various databases, including MongoDB, PostgreSQL, and more. You can choose the one that best fits your project’s requirements.

Q3: Is FastAPI suitable for building microservices?

Absolutely! FastAPI’s asynchronous capabilities and high performance make it an excellent choice for developing microservices that need to handle numerous concurrent requests.

Q4: Does FastAPI work well with frontend frameworks?

FastAPI can be the backend for front-end frameworks like React, Angular, or Vue.js. Frontend applications can easily consume their APIs.

Q5: What deployment options are available for FastAPI?

FastAPI applications can be deployed using ASGI servers like Uvicorn, Hypercorn, or Daphne. Containerization platforms like Docker are also commonly used for deployment.