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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

Common problems – permissions and environments


Different computers might run our code under different user accounts, and our application might expect to be able to read a file or write data into a specific directory and hit an unexpected permission error. Even in cases where the user accounts used by our code are all the same (down to the same user ID and group ID), their environment may be different on different hosts. Therefore, an environment variable we assumed to be defined might not be or, even worse, might be set to an incompatible value.

These problems are common when our code runs as a special, unprivileged user, such as nobody. Defensive coding, especially when accessing the environment, and making sure to always fall back to sensible defaults when variables are undefined (that is, value = os.environ.get('SOME_VAR', fallback_value) instead of simply value = os.environ.get['SOME_VAR']) is often necessary.

A common approach, when this is possible, is to only run our applications under...

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