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Mastering Python 2E

You're reading from   Mastering Python 2E Write powerful and efficient code using the full range of Python's capabilities

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Product type Paperback
Published in May 2022
Last Updated in May 2022
Publisher Packt
ISBN-13 9781800207721
Length 710 pages
Edition 2nd Edition
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Author (1):
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Rick Hattem Rick Hattem
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Rick Hattem
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Table of Contents (21) Chapters Close

Preface 1. Getting Started – One Environment per Project FREE CHAPTER 2. Interactive Python Interpreters 3. Pythonic Syntax and Common Pitfalls 4. Pythonic Design Patterns 5. Functional Programming – Readability Versus Brevity 6. Decorators – Enabling Code Reuse by Decorating 7. Generators and Coroutines – Infinity, One Step at a Time 8. Metaclasses – Making Classes (Not Instances) Smarter 9. Documentation – How to Use Sphinx and reStructuredText 10. Testing and Logging – Preparing for Bugs 11. Debugging – Solving the Bugs 12. Performance – Tracking and Reducing Your Memory and CPU Usage 13. asyncio – Multithreading without Threads 14. Multiprocessing – When a Single CPU Core Is Not Enough 15. Scientific Python and Plotting 16. Artificial Intelligence 17. Extensions in C/C++, System Calls, and C/C++ Libraries 18. Packaging – Creating Your Own Libraries or Applications 19. Other Books You May Enjoy
20. Index

Remote processes

So far, we have only executed our scripts on multiple local processors, but we can actually expand this much further. Using the multiprocessing library, it’s actually very easy to execute jobs on remote servers, but the documentation is currently still a bit cryptic. There are actually a few ways of executing processes in a distributed way, but the most obvious one isn’t the easiest one. The multiprocessing.connection module has both the Client and Listener classes, which facilitate secure communication between the clients and servers in a simple way.

Communication is not the same as process management and queue management, however; those features require some extra effort. The multiprocessing library is still a bit bare in this regard, but it’s most certainly possible given a few different processes.

Distributed processing using multiprocessing

We will start with a module containing a few constants that should be shared between all...

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