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Mastering Concurrency in Python

You're reading from   Mastering Concurrency in Python Create faster programs using concurrency, asynchronous, multithreading, and parallel programming

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Product type Paperback
Published in Nov 2018
Publisher Packt
ISBN-13 9781789343052
Length 446 pages
Edition 1st Edition
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Concepts
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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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Table of Contents (22) Chapters Close

Preface 1. Advanced Introduction to Concurrent and Parallel Programming FREE CHAPTER 2. Amdahl's Law 3. Working with Threads in Python 4. Using the with Statement in Threads 5. Concurrent Web Requests 6. Working with Processes in Python 7. Reduction Operators in Processes 8. Concurrent Image Processing 9. Introduction to Asynchronous Programming 10. Implementing Asynchronous Programming in Python 11. Building Communication Channels with asyncio 12. Deadlocks 13. Starvation 14. Race Conditions 15. The Global Interpreter Lock 16. Designing Lock-Based and Mutex-Free Concurrent Data Structures 17. Memory Models and Operations on Atomic Types 18. Building a Server from Scratch 19. Testing, Debugging, and Scheduling Concurrent Applications 20. Assessments 21. Other Books You May Enjoy

The Global Interpreter Lock

One of the major players in Python concurrent programming is the Global Interpreter Lock (GIL). In this chapter, we will cover the definition and purposes of the GIL, and how it affects concurrent Python applications. The problems that the GIL poses for Python concurrent systems and the controversy around its implementation will also be discussed. Finally, we will mention some thoughts on how Python programmers and developers should think about, and interact with, the GIL.

The following topics will be covered in this chapter:

  • A brief introduction to the GIL: what gave rise to it, and the problems it causes
  • Efforts in removing/fixing the GIL in Python
  • How to effectively work with the GIL in Python concurrent programs
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