Building Data Science Applications with FastAPI: Develop, manage, and deploy efficient machine learning applications with Python
Author: François Voron
Publisher Finelybook 出版社：Packt Publishing (8 Oct. 2021)
pages 页数：426 pages
Get well-versed with FastAPI features and best practices for testing, monitoring, and deployment to run high-quality and robust data science applications
Key FeaturesCover the concepts of the FastAPI framework, including aspects relating to asynchronous programming, type hinting, and dependency injectionDevelop efficient RESTful APIs for data science with modern PythonBuild, test, and deploy high performing data science and machine learning systems with FastAPI
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.
What you will learnExplore the basics of modern Python and async I/O programmingGet to grips with basic and advanced concepts of the FastAPI frameworkImplement a FastAPI dependency to efficiently run a machine learning modelIntegrate a simple face detection algorithm in a FastAPI backendIntegrate common Python data science libraries in a web backendDeploy a performant and reliable web backend for a data science applicationWho this book is for
This Python data science book is for data scientists and software developers interested in gaining knowledge of FastAPI and its ecosystem to build data science applications. Basic knowledge of data science and machine learning concepts and how to apply them in Python is recommended.
Table of ContentsPython Development Environment SetupPython Programming SpecificitiesDeveloping RESTful API with FastAPIManaging pydantic Data Models in FastAPIDependency Injections in FastAPIDatabases and Asynchronous ORMsManaging Authentication and Security in FastAPIDefining WebSockets for Two-Way Interactive Communication in FastAPITesting an API Asynchronously with pytest and HTTPXDeploying a FastAPI ProjectIntroduction to NumPy and PandasTraining Machine Learning Models with scikit-learnCreating an Efficient Prediction API Endpoint with FastAPIImplement a Real-Time Face Detection System Using WebSockets with FastAPI and OpenCV