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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 2: Python Programming Specificities

The Python language was designed to emphasize code readability. As such, it provides syntaxes and constructs that allow developers to quickly express complex concepts in few and readable lines. However, this makes it quite different from other programming languages.

The goal of this chapter is thus to get you acquainted with its specificities, but we expect you already have some experience with programming. We'll first get started with the basics of the language, the standard types, and the flow control syntaxes. You'll also be introduced to the list comprehension and generator concepts, which are very powerful ways to go through and transform sequences of data. You'll also see that Python can be used as an object-oriented language, still through a very lightweight yet powerful syntax. Before moving on, we'll also review the concepts of type hinting and asynchronous I/O, which are quite new in Python but are at the...

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