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Introduction to FastAPI Async

Today, we will explore the basics of asynchronous programming in FastAPI and how to use it to build high-performance APIs.

What is Async/Await?

Async/await is a syntax for writing asynchronous code that's easier to read and maintain. It allows for non-blocking I/O operations, which improves performance and responsiveness.

  • Async/await is a syntax for writing asynchronous code that's easier to read and maintain
  • Allows for non-blocking I/O operations
  • Improves performance and responsiveness
import asyncio

async def main():
    print("Hello")
    await asyncio.sleep(1)
    print("World")

asyncio.run(main())

Basics of Async in FastAPI

Let's understand the basics of async in FastAPI. We need to understand the concept of async/await in Python and know how to define async routes in FastAPI.

  • Understand the concept of async/await in Python
  • Know how to define async routes in FastAPI
from fastapi import FastAPI

app = FastAPI()

@app.get("/async")
async def read_async():
    return {"message": "Hello, World!"}

Async with Databases

we will learn how to use async with databases in FastAPI. We need to understand how to use async database drivers and define async database models.

Async Background Tasks

we want to learn how to use async background tasks in FastAPI. We need to understand how to use the background parameter and define async background tasks

  • Understand how to use the background parameter in FastAPI
  • Know how to define async background tasks
from fastapi import FastAPI, BackgroundTasks

app = FastAPI()

@app.get("/async_bg")
async def read_async_bg(background_tasks: BackgroundTasks):
    background_tasks.add_task(write_notification, "some notification")
    return {"message": "Hello, World!"}

def write_notification(notification: str):
    # simulate a long-running task
    import time
    time.sleep(5)
    print(notification)

Async with External Services

we will learn how to use async with external services in FastAPI. We need to understand how to use async HTTP clients and define async routes that make requests to external APIs.

  • Understand how to use async HTTP clients with FastAPI
  • Know how to define async routes that make requests to external APIs
from fastapi import FastAPI
import httpx

app = FastAPI()

@app.get("/async_ext")
async def read_async_ext():
    async with httpx.AsyncClient() as client:
        response = await client.get("https://example.com")
        return response.json()

Error Handling

we want to learn how to handle errors in async code. We need to understand how to handle exceptions and use try-except blocks with async/await.

  • Understand how to handle exceptions in async code
  • Know how to use try-except blocks with async/await
from fastapi import FastAPI

app = FastAPI()

@app.get("/async_error")
async def read_async_error():
    try:
        # simulate an error
        raise Exception("Something went wrong")
    except Exception as e:
        return {"error": str(e)}

Best Practices

To get the most out of async/await in FastAPI, it's essential to follow best practices. This includes using async/await consistently, avoiding synchronous code, handling exceptions, and logging your application.

  • Use async/await consistently throughout your code
  • Avoid using await with synchronous code
  • Use try-except blocks to handle exceptions
  • Use logging to debug and monitor your application

Conclusion

FastAPI and async/await provide a powerful combination for building high-performance APIs. By following best practices and using the features provided by FastAPI, you can create scalable and maintainable applications.

Summary of key points: - FastAPI is a modern web framework that supports async/await - Async/await is a syntax for writing asynchronous code that's easier to read and maintain - FastAPI provides built-in support for async/await with databases, background tasks, and external services - Error handling is crucial in async code, and try-except blocks should be used consistently