Mastering Concurrency in Python: Create faster programs using concurrency, asynchronous, multithreading, and parallel programming

         


Mastering Concurrency in Python: Create faster programs using concurrency, asynchronous, multithreading, and parallel programming
By 作者: Quan Nguyen
ISBN-10 书号: 1789343054
ISBN-13 书号: 9781789343052
Release Finelybook 出版日期: 2018-11-27
pages 页数: (446 )

$44.99
Book Description to Finelybook sorting
Immerse yourself in the world of Python concurrency and tackle the most complex concurrent programming problems
Python is one of the most popular programming languages, with numerous libraries and frameworks that facilitate high-performance computing. Concurrency and parallelism in Python are essential when it comes to multiprocessing and multithreading; they behave differently, but their common aim is to reduce the execution time. This book serves as a comprehensive introduction to various advanced concepts in concurrent engineering and programming.
Mastering Concurrency in Python starts by introducing the concepts and principles in concurrency, right from Amdahl’s Law to multithreading programming, followed by elucidating multiprocessing programming, web scraping, and asynchronous I/O, together with common problems that engineers and programmers face in concurrent programming. Next, the book covers a number of advanced concepts in Python concurrency and how they interact with the Python ecosystem, including the Global Interpreter Lock (GIL). Finally, you’ll learn how to solve real-world concurrency problems through examples.
By the end of the book, you will have gained extensive theoretical knowledge of concurrency and the ways in which concurrency is supported by the Python language
What you will learn

Explore the concepts of concurrency in programming
Explore the core syntax and features that enable concurrency in Python
Understand the correct way to implement concurrency
Abstract methods to keep the data consistent in your program
Analyze problems commonly faced in concurrent programming
Use application scaffolding to design highly-scalable programs

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