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Python Parallel Programming Cookbook by Giancarlo Zaccone

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Chapter 5. Distributed Python

In this chapter, we will cover the following recipes:

  • Using Celery to distribute tasks
  • How to create a task with Celery
  • Scientific computing with SCOOP
  • Handling map functions with SCOOP
  • Remote method invocation with Pyro4
  • Chaining objects with Pyro4
  • Developing a client-server application with Pyro4
  • Communicating sequential processes with PyCSP
  • Using MapReduce with Disco
  • A remote procedure call with RPyC

Introduction

The basic idea of distributed computing is to break each workload into an arbitrary number of tasks, usually indicated with the name, into reasonable pieces for which a computer in a distributed network will be able to finish and return the results flawlessly. In distributed computing, there is the absolute certainty ...

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