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Hands-On Software Engineering with Python

You're reading from   Hands-On Software Engineering with Python Move beyond basic programming and construct reliable and efficient software with complex code

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Product type Paperback
Published in Oct 2018
Publisher Packt
ISBN-13 9781788622011
Length 736 pages
Edition 1st Edition
Languages
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Authors (2):
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 Verma Verma
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Verma
 Allbee Allbee
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Allbee
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Table of Contents (21) Chapters Close

Preface 1. Programming versus Software Engineering 2. The Software Development Life Cycle FREE CHAPTER 3. System Modeling 4. Methodologies, Paradigms, and Practices 5. The hms_sys System Project 6. Development Tools and Best Practices 7. Setting Up Projects and Processes 8. Creating Business Objects 9. Testing Business Objects 10. Thinking About Business Object Data Persistence 11. Data Persistence and BaseDataObject 12. Persisting Object Data to Files 13. Persisting Data to a Database 14. Testing Data Persistence 15. Anatomy of a Service 16. The Artisan Gateway Service 17. Handling Service Transactions 18. Testing and Deploying Services 19. Multiprocessing and HPC in Python 20. Other Books You May Enjoy

Integrating Python with large-scale, cluster computing frameworks

Large-scale, cluster computing frameworks, in order to provide as much compatibility with custom written operations as possible, will probably accept input in only two different ways: as command-line arguments, or using standard input, with the latter being more common for systems that are targeted for big data operations. In either case, what's needed to allow a custom process to be executed at and scaled to a clustered environment is a self-contained, command-line executable that usually returns its data to standard output.

A minimal script that accepts standard input—whether by passing data into it with a pipe, or by reading the contents of a file and using that—could be implemented like this:

#!/usr/bin/env python
"""factors_stdin.py

A command-line-ready script that allows...
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