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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
13
Part 3: Building Resilient and Distributed Data Science Systems with FastAPI

Python Programming Specificities

The Python language was designed to emphasize code readability. As such, it provides syntaxes and constructs that allow developers to quickly express complex concepts in a few readable lines. This makes it quite different from other programming languages.

The goal of this chapter is thus to get you acquainted with its specificities, but we expect you already have some experience with programming. We’ll first get started with the basics of the language, the standard types, and the flow control syntaxes. You’ll also be introduced to the list comprehension and generator concepts, which are very powerful ways to go through and transform sequences of data. You’ll also see that Python can be used as an object-oriented language, still through a very lightweight yet powerful syntax. Before moving on, we’ll also review the concepts of type hinting and asynchronous I/O, which are quite new in Python but are at the core of the FastAPI...

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