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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

Approaches to deadlock situations

As we have seen, deadlock can lead our concurrent programs to an infinite hang, which is undesirable in every way. In this section, we will be discussing potential approaches to prevent deadlocks from occurring. Intuitively, each approach looks to eliminate one of the four Coffman conditions from our program, in order to prevent deadlocks.

Implementing ranking among resources

From both the Dining Philosophers problem and our Python example, we can see that the last condition of the four Coffman conditions, circular wait, is at the heart of the problem of deadlock. It specifies that the different processes (or threads) in our concurrent program wait for resources held by other processes (or...

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