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Building Data Science Applications with FastAPI

Building Data Science Applications with FastAPI - Second Edition

By : Voron
4.2 (9)
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Building Data Science Applications with FastAPI

Building Data Science Applications with FastAPI

4.2 (9)
By: Voron

Overview of this book

Building Data Science Applications with FastAPI is the go-to resource for creating efficient and dependable data science API backends. This second edition incorporates the latest Python and FastAPI advancements, along with two new AI projects – a real-time object detection system and a text-to-image generation platform using Stable Diffusion. The book starts with the basics of FastAPI and modern Python programming. You'll grasp FastAPI's robust dependency injection system, which facilitates seamless database communication, authentication implementation, and ML model integration. As you progress, you'll learn testing and deployment best practices, guaranteeing high-quality, resilient applications. Throughout the book, you'll build data science applications using FastAPI with the help of projects covering common AI use cases, such as object detection and text-to-image generation. These hands-on experiences will deepen your understanding of using FastAPI in real-world scenarios. By the end of this book, you'll be well equipped to maintain, design, and monitor applications to meet the highest programming standards using FastAPI, empowering you to create fast and reliable data science API backends with ease while keeping up with the latest advancements.
Table of Contents (21 chapters)
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1
Part 1: Introduction to Python and FastAPI
7
Part 2: Building and Deploying a Complete Web Backend with FastAPI
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13
Part 3: Building Resilient and Distributed Data Science Systems with FastAPI

Part 2: Building and Deploying a Complete Web Backend with FastAPI

The goal of this section is to show you how to build a real-world backend with FastAPI that can read and write data and authenticate users, and that is properly tested and correctly configured for a production environment.

This section comprises the following chapters:

  • Chapter 6, Databases and Asynchronous ORMs
  • Chapter 7, Managing Authentication and Security in FastAPI
  • Chapter 8, Defining WebSockets for Two-Way Interactive Communication in FastAPI
  • Chapter 9, Testing an API Asynchronously with pytest and HTTPX
  • Chapter 10, Deploying a FastAPI Project
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Building Data Science Applications with FastAPI
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