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Scaling Python with Ray: Adventures in Cloud and Serverless Patterns (Sixth Early Release)
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Scaling Python with Ray: Adventures in Cloud and Serverless Patterns (Sixth Early Release)Название: Scaling Python with Ray: Adventures in Cloud and Serverless Patterns (Sixth Early Release)
Автор: Holden Karau, Boris Lublinsky
Издательство: O’Reilly Media, Inc.
Год: 2022-10-07
Страниц: 250
Язык: английский
Формат: epub (true), mobi
Размер: 10.2 MB

Serverless computing enables developers to concentrate solely on their applications rather than worry about where they've been deployed. With the Ray general-purpose serverless implementation in Python, programmers and data scientists can hide servers, implement stateful applications, support direct communication between tasks, and access hardware accelerators.

In this book, authors Holden Karau and Boris Lublinsky show you how to scale existing Python applications and pipelines, allowing you to stay in the Python ecosystem while avoiding single points of failure and manual scheduling. If your data processing has grown beyond what a single computer can handle, this book is for you.

We wrote this book for developers and data scientists looking to build and scale applications in Python without becoming systems administrators. We expect this book to be most beneficial for individuals and teams dealing with the growing complexity and scale of problems moving from single-threaded solutions to multi-threaded, all the way to distributed computing. While you can use Ray from Java, this book is in Python, and we assume a general familiarity with the Python ecosystem.

Written by experienced software architecture practitioners, Scaling Python with Ray is ideal for software architects and developers eager to explore successful case studies and learn more about decision and measurement effectiveness. This book covers distributed processing (the pure Python implementation of serverless) and shows you how to:

Implement stateful applications with Ray actors
Build workflow management in Ray
Use Ray as a unified platform for batch and streaming
Implement advanced data processing with Ray
Build microservices with Ray
Implement reliable Ray applications

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