Learn how to implement rate limiting in FastAPI in just 2 minutes

Rate limiting is a crucial aspect of any API to prevent abuse and ensure fair usage for all users. In this tutorial, we will be using FastAPI to implement rate limiting for our API endpoints.

Step 1: Installing FastAPI
First, install FastAPI using pip:

pip install fastapi

Step 2: Installing Uvicorn
Next, install Uvicorn to run our FastAPI application:

pip install uvicorn

Step 3: Creating the FastAPI Application
Create a new Python file, for example main.py, and add the following code to create a FastAPI application:

from fastapi import FastAPI

app = FastAPI()

Step 4: Implementing Rate Limiting
To implement rate limiting in FastAPI, we can use the Starlette library, which provides a middleware for rate limiting. Install starlette using pip:

pip install starlette

Next, import and configure the rate limiting middleware in your FastAPI application:

from starlette.middleware import Middleware
from starlette.middleware.throttling import ThrottlingMiddleware

middleware = [
    Middleware(ThrottlingMiddleware, requests_per_minute=100),
]

app = FastAPI(middleware=middleware)

In the above code snippet, we are limiting the number of requests to 100 per minute. You can adjust the requests_per_minute parameter to fit your needs.

Step 5: Running the FastAPI Application
To run the FastAPI application, use Uvicorn:

uvicorn main:app --reload

Now, your FastAPI application with rate limiting is up and running. Any requests exceeding the defined rate limit will receive a 429 Too Many Requests response indicating that the request has been rate limited.

In conclusion, implementing rate limiting in FastAPI is essential to protect your API from abuse and provide a fair experience for all users. By following the steps outlined in this tutorial, you can easily add rate limiting to your FastAPI application.