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Building Data Science Applications with FastAPI

You're reading from  Building Data Science Applications with FastAPI

Product type Book
Published in Oct 2021
Publisher Packt
ISBN-13 9781801079211
Pages 426 pages
Edition 1st Edition
Languages
Author (1):
François Voron François Voron
Profile icon François Voron

Table of Contents (19) Chapters

Preface Section 1: Introduction to Python and FastAPI
Chapter 1: Python Development Environment Setup Chapter 2: Python Programming Specificities Chapter 3: Developing a RESTful API with FastAPI Chapter 4: Managing Pydantic Data Models in FastAPI Chapter 5: Dependency Injections in FastAPI Section 2: Build and Deploy a Complete Web Backend with FastAPI
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 Section 3: Build a Data Science API with Python and FastAPI
Chapter 11: Introduction to NumPy and pandas Chapter 12: Training Machine Learning Models with scikit-learn Chapter 13: Creating an Efficient Prediction API Endpoint with FastAPI Chapter 14: Implement a Real-Time Face Detection System Using WebSockets with FastAPI and OpenCV Other Books You May Enjoy

Summary

In this chapter, you've learned how to work with one of the latest web technologies available: WebSocket. You are now able to open a two-way communication channel between a client and a server, allowing you to implement applications with real-time constraints. As you've seen, FastAPI makes it very easy to add such endpoints. Still, the way of thinking inside a WebSocket logic is quite different from traditional HTTP endpoints: managing an infinite loop and handling several tasks at a time are completely new challenges. Fortunately, the asynchronous nature of the framework makes our life easier in this matter and helps us write concurrent code that is easily understandable.

Finally, we also had a quick overview of the challenges to solve when handling multiple clients that share messages between them. You saw that message broker software such as Apache Kafka or RabbitMQ is necessary to make this use case reliable across several server processes.

You are now acquainted...

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