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FastAPI Cookbook

FastAPI Cookbook

By : Giunio De Luca
4.3 (4)
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FastAPI Cookbook

FastAPI Cookbook

4.3 (4)
By: Giunio De Luca

Overview of this book

FastAPI is a cutting-edge Python framework that is revolutionizing the way web apps and APIs are built. Known for its speed, simplicity, and scalability, FastAPI empowers developers to create high-performing applications with ease. This book will help you leverage FastAPI’s immense potential to handle high-traffic scenarios and integrate seamlessly with modern Python tools. The book begins by familiarizing you with the basics of setting up and configuring your FastAPI environment before moving to the intricacies of building RESTful APIs, managing data with SQL and NoSQL databases, and handling authentication and authorization. Next, you'll focus on advanced topics such as custom middleware, WebSocket communication, and integration with various Python libraries. Each chapter is meticulously crafted with practical recipes, progressing from foundational concepts to advanced features and best practices. The concluding chapters show you how to optimize performance, implement rate limiting, and execute background tasks, empowering you to become a proficient FastAPI developer. By the end of this book, you'll have gained the skills you need to migrate existing apps to FastAPI, and be equipped to tackle any challenge in the modern web development landscape, ensuring your apps are not only functional, but also efficient, secure, and scalable.
Table of Contents (15 chapters)
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Working with data validation and serialization

Effective data validation stands as a cornerstone of robust web applications, ensuring that incoming data meets predefined criteria and remains safe for processing.

FastAPI harnesses the power of Pydantic, a Python library dedicated to data validation and serialization. By integrating Pydantic models, FastAPI streamlines the process of validating and serializing data, offering an elegant and efficient solution. This recipe shows how to utilize Pydantic models within FastAPI applications, exploring how they enable precise validation and seamless data serialization.

Getting ready

Pydantic models are essentially Python classes that define the structure and validation rules of your data. They use Python’s type annotations to validate that incoming data matches the expected format. When you use a Pydantic model in your FastAPI endpoints, FastAPI automatically validates incoming request data against the model.

In this recipe...

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FastAPI Cookbook
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