Book Image

Building Data Science Applications with FastAPI

By : François Voron
5 (1)
Book Image

Building Data Science Applications with FastAPI

5 (1)
By: François 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)
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

Basics of Python programming

First of all, let's review some of the key aspects of Python:

  • It's an interpreted language. Contrary to languages such as C or Java, it doesn't need to be compiled, which allows us to run Python code interactively.
  • It's dynamically typed. The type of values is determined at runtime.
  • It supports several programming paradigms: procedural, object-oriented, and functional programming.

This makes Python quite a versatile language, from simple automation scripts to complex data science projects.

Let's now write and run some Python!

Running Python scripts

As we said, Python is an interpreted language. Hence, the simplest and quickest way to run some Python code is to launch an interactive shell. Just run the following command to start a session:

$ python
Python 3.7.10 (default, Mar  7 2021, 10:12:14) 
[Clang 12.0.0 (clang-1200.0.32.29)] on darwin
Type "help", "copyright"...