Async and await

Async and Await in FastAPI

FastAPI is built on the foundations of Python's async and await features. These keywords allow developers to write asynchronous code in a more readable, straightforward style that resembles synchronous code. This article will explain how async and await work, their benefits and how you can use them in your FastAPI applications.

Understanding Async and Await

Before we dive into how to use async and await in FastAPI, it's crucial to understand what they are.

async and await are Python keywords that are used to define and work with asynchronous code. Asynchronous code allows tasks to run concurrently, rather than sequentially. This means that while one task is waiting for an external resource (like a database or a network), other tasks can continue running.

• async is used to declare a function as a coroutine. Coroutines are special functions that can be paused and resumed, allowing for asynchronous behavior.

• await is used to wait for a coroutine to finish. It can only be used inside an async function.

Here's a simple example:

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

In this example, the async keyword declares my_function as a coroutine. Inside my_function, we use the await keyword to pause the function, wait for asyncio.sleep(1) to finish, and then resume the function.

Using Async and Await in FastAPI

FastAPI fully supports async and await. Any route function can be declared with async, and FastAPI will run it as a coroutine.

Here's an example:

from fastapi import FastAPI

app = FastAPI()

@app.get('/')
async def read_root():
    return {"Hello": "World"}

In this example, read_root is declared as a coroutine with async. FastAPI will run it as a coroutine whenever a GET request is made to the '/' path.

When to Use Async and Await

In a FastAPI application, you should use async and await when you're performing IO-bound tasks, such as:

• Reading from or writing to a database
• Making network requests
• Reading from or writing to a file

Using async and await for these tasks allows your application to continue processing other requests while waiting for the IO-bound task to complete. This can significantly improve the performance of your application.

Conclusion

Async and await are powerful features of Python that allow you to write asynchronous code in a more readable and straightforward style. FastAPI fully supports these features, allowing you to build highly efficient and performant web applications.

Remember, the key to effectively using async and await in FastAPI is to understand when to use them. They are most effective when used for IO-bound tasks, where they allow your application to handle other tasks while waiting for the IO-bound task to complete.

In the next article, we will explore more advanced topics in FastAPI. Stay tuned!