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)

Chapter 15

What is the difference in memory management between Python and C++?

C++ associates a variable to its value by simply writing the value to the memory location of the variable; Python has its variables reference point to the memory location of the values that they hold. For this reason, Python needs to maintain a reference count for every value in its memory space.

What problem does the GIL solve for Python?

To avoid race conditions, and consequently, the corruption of value reference counts, the GIL is implemented so that only one thread can access and mutate the counts at any given time.

What problem does the GIL create for Python?

The GIL effectively prevents multiple threads from taking advantage of the CPU and executing CPU-bound instructions at the same time. This means that if multiple threads that are meant to be executed concurrently are CPU-bound, they will...