Book Image

Mastering Concurrency in Python

By : Quan Nguyen
Book Image

Mastering Concurrency in Python

By: Quan Nguyen

Overview of this book

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
Table of Contents (22 chapters)

Memory Models and Operations on Atomic Types

The considerations that need to be made during concurrent programming processes, and the problems that follow, are all connected to the way in which Python manages its memory. A deep understanding of how variables and values are stored and referenced in Python, therefore, would not only help to pinpoint the low-level bugs that cause the concurrent program to malfunction but also helps to optimize the concurrent codes. In this chapter, we will take an in-depth look into the Python memory model as well as its atomic types, specifically their places in the Python concurrency ecosystem.

The following topics will be covered in this chapter:

  • The Python memory model, its components that support memory allocation on various levels, and the general philosophy in managing memory in Python
  • The definition of atomic operations, the roles they play...