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Building Data Science Applications with FastAPI

Building Data Science Applications with FastAPI

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

Building Data Science Applications with FastAPI

4.7 (16)
By: 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

Security dependencies in FastAPI

To protect a REST API and, more generally, HTTP endpoints, lots of standards have been proposed. Here is a non-exhaustive list of the most common ones:

  • Basic HTTP authentication: In this scheme, user credentials (usually, an identifier such as an email address and password) are put into an HTTP header called Authorization. The value consists of the Basic keyword, followed by the user credentials encoded in Base64. This is a very simple scheme to implement but not very secure since the password appears in every request.
  • Cookies: Cookies are a useful way to store static data on the client side, usually on web browsers, that is sent in each request to the server. Typically, a cookie can contain a session token that can be verified by the server and linked to a specific user.
  • Tokens in the Authorization header: Probably the most used header in a REST API context, this simply consists of sending a token in an HTTP Authorization header. The...

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