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Scaling Python with Ray

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Scaling Python with Ray Holden Karau, Boris Lublinsky - okladka książki

Scaling Python with Ray Holden Karau, Boris Lublinsky - okladka książki

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Bądź pierwszym, który oceni tę książkę
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268
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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, experienced software architecture practitioners Holden Karau and Boris Lublinsky show you how to scale existing Python applications and pipelines, allowing you to stay in the Python ecosystem while reducing single points of failure and manual scheduling. 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.

If your data processing or server application has grown beyond what a single computer can handle, this book is for you. You'll explore distributed processing (the pure Python implementation of serverless) and learn how to:

  • Implement stateful applications with Ray actors
  • Build workflow management in Ray
  • Use Ray as a unified system for batch and stream processing
  • Apply advanced data processing with Ray
  • Build microservices with Ray
  • Implement reliable Ray applications

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O autorze książki

Holden Karau is a software development engineer and is active in the open source. She has worked on a variety of search, classification, and distributed systems problems at IBM, Alpine, Databricks, Google, Foursquare, and Amazon. She graduated from the University of Waterloo with a bachelor's of mathematics degree in computer science. Other than software, she enjoys playing with fire and hula hoops, and welding.

Holden Karau, Boris Lublinsky - pozostałe książki

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