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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

Product type Paperback

Published in Nov 2018

Publisher Packt

ISBN-13 9781789343052

Length 446 pages

Edition 1st Edition

Languages

Python

Tools

Abstract

Concepts

Concurrency

Author (1):

Quan Nguyen

View More author details

Table of Contents (22) Chapters

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

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Questions

What is asynchronous programming? What advantages does it provide?
What are the main elements in an asynchronous program? How do they interact with each other?
What are the async and await keywords? What purposes do they serve?
What options does the asyncio module provide, in terms of the implementation of asynchronous programming?
What are the improvements in regards to asynchronous programming provided in Python 3.7?
What are blocking functions? Why do they pose a problem for traditional asynchronous programming?
How does concurrent.futures provide a solution to blocking functions for asynchronous programming? What options does it provide?

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Authors (1)

Quan Nguyen

Quan Nguyen

Quan Nguyen, the author of the first edition of this book, is a Python programmer with a strong passion for machine learning. He holds a dual degree in mathematics and computer science, with a minor in philosophy, earned from DePauw University. Quan is deeply involved in the Python community and has authored multiple Python books, contributing to the Python Software Foundation and regularly sharing insights on DataScience portal. He is currently pursuing a Ph.D. in computer science at Washington University in St. Louis.

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