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Advanced Python Programming

You're reading from   Advanced Python Programming Accelerate your Python programs using proven techniques and design patterns

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Product type Paperback
Published in Mar 2022
Publisher Packt
ISBN-13 9781801814010
Length 606 pages
Edition 2nd Edition
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Author (1):
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Quan Nguyen Quan Nguyen
Author Profile Icon Quan Nguyen
Quan Nguyen
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Toc

Table of Contents (32) Chapters Close

Preface 1. Section 1: Python-Native and Specialized Optimization
2. Chapter 1: Benchmarking and Profiling FREE CHAPTER 3. Chapter 2: Pure Python Optimizations 4. Chapter 3: Fast Array Operations with NumPy, Pandas, and Xarray 5. Chapter 4: C Performance with Cython 6. Chapter 5: Exploring Compilers 7. Chapter 6: Automatic Differentiation and Accelerated Linear Algebra for Machine Learning 8. Section 2: Concurrency and Parallelism
9. Chapter 7: Implementing Concurrency 10. Chapter 8: Parallel Processing 11. Chapter 9: Concurrent Web Requests 12. Chapter 10: Concurrent Image Processing 13. Chapter 11: Building Communication Channels with asyncio 14. Chapter 12: Deadlocks 15. Chapter 13: Starvation 16. Chapter 14: Race Conditions 17. Chapter 15: The Global Interpreter Lock 18. Section 3: Design Patterns in Python
19. Chapter 16: The Factory Pattern 20. Chapter 17: The Builder Pattern 21. Chapter 18: Other Creational Patterns 22. Chapter 19: The Adapter Pattern 23. Chapter 20: The Decorator Pattern 24. Chapter 21: The Bridge Pattern 25. Chapter 22: The Façade Pattern 26. Chapter 23: Other Structural Patterns 27. Chapter 24: The Chain of Responsibility Pattern 28. Chapter 25: The Command Pattern 29. Chapter 26: The Observer Pattern 30. Assessments 31. Other Books You May Enjoy

Chapter 10: Concurrent Image Processing

This chapter discusses the task of processing and manipulating images via concurrent programming, specifically multiprocessing. Since images are processed independently of one another, concurrent programming is an attractive option for achieving a significant speedup. This chapter lays out the basics behind image processing techniques, illustrates the improvements that concurrent programming provides, and goes over some of the best practices that are used in image processing applications. This discussion will consolidate our knowledge of how to leverage concurrent and parallel processing tools in Python.

The following topics will be covered in this chapter:

  • Image processing fundamentals
  • Applying concurrency to image processing
  • Good concurrent image processing practices
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