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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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Toc

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

Technical requirements

For this chapter, you'll need a Python virtual environment, similar to the one we set up in Chapter 1, Python Development Environment Setup.

For the Testing with a database section, you'll need a running MongoDB server on your local computer. The easiest way to do this is to run it as a Docker container. If you've never used Docker before, we recommend that you read the Get Started tutorial in the official documentation: https://docs.docker.com/get-started/. Once done, you'll be able to run a MongoDB server with this simple command:

$ docker run -d --name fastapi-mongo -p 27017:27017 mongo:4.4

The MongoDB server instance will then be available on your local computer on port 27017.

You can find all the code examples for this chapter in its dedicated GitHub repository: https://github.com/PacktPublishing/Building-Data-Science-Applications-with-FastAPI/tree/main/chapter9.

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