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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 8: Defining WebSockets for Two-Way Interactive Communication in FastAPI

The HyperText Transfer Protocol (HTTP) is a simple yet powerful technique to send or receive data to and from a server. As we've seen, the principles of request and response are at the core of this protocol: when developing our application programming interface (API), our goal is to process the incoming request and build a response for the client. Thus, in order to get data from the server, the client always has to initiate a request first. In some contexts, however, this may not be very convenient. Imagine a typical chat application: when a user receives a new message, we would like them to be notified immediately by the server. Working only with HTTP, we would have to make requests every second to check if new messages have arrived, which would be a massive waste of resources. This is why a new protocol has emerged: WebSocket. The goal of this protocol is to open a communication channel between a...

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Building Data Science Applications with FastAPI
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