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Distributed Computing with Python

You're reading from   Distributed Computing with Python Harness the power of multiple computers using Python through this fast-paced informative guide

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Product type Paperback
Published in Apr 2016
Publisher
ISBN-13 9781785889691
Length 170 pages
Edition 1st Edition
Languages
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Author (1):
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Rasheedh B Rasheedh B
Author Profile Icon Rasheedh B
Rasheedh B
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Table of Contents (10) Chapters Close

Preface 1. An Introduction to Parallel and Distributed Computing 2. Asynchronous Programming FREE CHAPTER 3. Parallelism in Python 4. Distributed Applications – with Celery 5. Python in the Cloud 6. Python on an HPC Cluster 7. Testing and Debugging Distributed Applications 8. The Road Ahead Index

Challenges – the development environment


Another common challenge in distributed systems is the setup of a representative development and testing environment, especially for individuals or small teams. Ideally, in fact, the development environment should be identical to the worst-case scenario deployment environment. It should allow developers to test common failure scenarios, such as a disk filling up, varying network latencies, intermittent network connections, hardware and software failures, and so on—all things that are bound to happen in real time, sooner or later.

Large teams have the resources to set up development and test clusters, and they almost always have dedicated software quality teams stress testing our code.

Small teams, unfortunately, often find themselves forced to write code on their laptops and use a very simplified (and best-case scenario!) environment made up of two or three virtual machines running on the laptops themselves to emulate the real system.

This pragmatic...

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