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Building Data Science Applications with FastAPI

Building Data Science Applications with FastAPI

By : François Voron
4.7 (16)
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Building Data Science Applications with FastAPI

Building Data Science Applications with FastAPI

4.7 (16)
By: François Voron

Overview of this book

FastAPI is a web framework for building APIs with Python 3.6 and its later versions based on standard Python-type hints. With this book, you’ll be able to create fast and reliable data science API backends using practical examples. This book starts with the basics of the FastAPI framework and associated modern Python programming language concepts. You'll be taken through all the aspects of the framework, including its powerful dependency injection system and how you can use it to communicate with databases, implement authentication and integrate machine learning models. Later, you’ll cover best practices relating to testing and deployment to run a high-quality and robust application. You’ll also be introduced to the extensive ecosystem of Python data science packages. As you progress, you’ll learn how to build data science applications in Python using FastAPI. The book also demonstrates how to develop fast and efficient machine learning prediction backends and test them to achieve the best performance. Finally, you’ll see how to implement a real-time face detection system using WebSockets and a web browser as a client. By the end of this FastAPI book, you’ll have not only learned how to implement Python in data science projects but also how to maintain and design them to meet high programming standards with the help of FastAPI.
Table of Contents (19 chapters)
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1
Section 1: Introduction to Python and FastAPI
7
Section 2: Build and Deploy a Complete Web Backend with FastAPI
13
Section 3: Build a Data Science API with Python and FastAPI

Chapter 2: 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 few and readable lines. However, 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...

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