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Building Data Science Applications with FastAPI

You're reading from   Building Data Science Applications with FastAPI Develop, manage, and deploy efficient machine learning applications with Python

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Product type Paperback
Published in Oct 2021
Publisher Packt
ISBN-13 9781801079211
Length 426 pages
Edition 1st Edition
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Author (1):
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François Voron François Voron
Author Profile Icon François Voron
François Voron
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Table of Contents (19) Chapters Close

Preface 1. Section 1: Introduction to Python and FastAPI
2. Chapter 1: Python Development Environment Setup FREE CHAPTER 3. Chapter 2: Python Programming Specificities 4. Chapter 3: Developing a RESTful API with FastAPI 5. Chapter 4: Managing Pydantic Data Models in FastAPI 6. Chapter 5: Dependency Injections in FastAPI 7. Section 2: Build and Deploy a Complete Web Backend with FastAPI
8. Chapter 6: Databases and Asynchronous ORMs 9. Chapter 7: Managing Authentication and Security in FastAPI 10. Chapter 8: Defining WebSockets for Two-Way Interactive Communication in FastAPI 11. Chapter 9: Testing an API Asynchronously with pytest and HTTPX 12. Chapter 10: Deploying a FastAPI Project 13. Section 3: Build a Data Science API with Python and FastAPI
14. Chapter 11: Introduction to NumPy and pandas 15. Chapter 12: Training Machine Learning Models with scikit-learn 16. Chapter 13: Creating an Efficient Prediction API Endpoint with FastAPI 17. Chapter 14: Implement a Real-Time Face Detection System Using WebSockets with FastAPI and OpenCV 18. Other Books You May Enjoy

Chapter 6: Databases and Asynchronous ORMs

The main goal of a REST API is, of course, to read and write data. So far, we've solely worked with the tools given by Python and FastAPI, allowing us to build reliable endpoints to process and answer requests. However, we haven't been able to effectively retrieve and persist that information: we missed a database.

The goal of this chapter is to show you how you can interact with different types of databases and related libraries inside FastAPI. It's worth noting that FastAPI is completely agnostic regarding databases: you can use any system you want and it's your responsibility to integrate it. This is why we'll review three different approaches to integrate a database, that is, using basic SQL queries, using Object-Relational Mapping (ORM), and, finally, using a NoSQL database.

In this chapter, we're going to cover the following main topics:

  • An overview of relational and NoSQL databases
  • Communicating...
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