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

Installing Python packages with pip

As we said earlier, pip is the built-in Python package manager that will help us install third-party libraries. To get started, let's install FastAPI and Uvicorn:

$ pip install fastapi uvicorn[standard]

We'll talk about it in later chapters, but Uvicorn is required to run a FastAPI project.

Tip

You have probably noticed the word standard inside square brackets just after uvicorn. Sometimes, some libraries have sub-dependencies that are not required to make the library work. Usually, they are needed for optional features or specific project requirements. The square brackets are here to indicate that we want to install the standard sub-dependencies of uvicorn.

To make sure the installation worked, we can open a Python interactive shell and try to import the FastAPI package:

$ python
>>> from fastapi import FastAPI

If it passes without any errors, congratulations, FastAPI is installed and ready to use!