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FastAPI Cookbook

You're reading from   FastAPI Cookbook Develop high-performance APIs and web applications with Python

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Product type Paperback
Published in Aug 2024
Publisher Packt
ISBN-13 9781805127857
Length 358 pages
Edition 1st Edition
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Author (1):
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Giunio De Luca Giunio De Luca
Author Profile Icon Giunio De Luca
Giunio De Luca
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Table of Contents (15) Chapters Close

Preface 1. Chapter 1: First Steps with FastAPI 2. Chapter 2: Working with Data FREE CHAPTER 3. Chapter 3: Building RESTful APIs with FastAPI 4. Chapter 4: Authentication and Authorization 5. Chapter 5: Testing and Debugging FastAPI Applications 6. Chapter 6: Integrating FastAPI with SQL Databases 7. Chapter 7: Integrating FastAPI with NoSQL Databases 8. Chapter 8: Advanced Features and Best Practices 9. Chapter 9: Working with WebSocket 10. Chapter 10: Integrating FastAPI with other Python Libraries 11. Chapter 11: Middleware and Webhooks 12. Chapter 12: Deploying and Managing FastAPI Applications 13. Index 14. Other Books You May Enjoy

Running the server across multiple workers

In high-traffic environments, running a FastAPI application with a single worker may not be sufficient to handle all incoming requests efficiently. To improve performance and ensure better resource use, you can run your FastAPI instance across multiple workers. This can be achieved using tools such as Gunicorn.

In this recipe, we will explore how to run a FastAPI application with multiple workers using Gunicorn in a Docker container, and we will also discuss Uvicorn’s ability to handle multiple workers along with its limitations.

Getting ready

The gunicorn package is not Windows compatible. To ensure operating system operability, we will run our Live Application in a Docker container.

The recipe will be based on the project created in the previous recipe, Running FastAPI applications in Docker containers.

How to do it…

FastAPI with multiple workers runs multiple copies of the app on different CPU processes.

...
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