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)

Amdahl's Law

How do you find a balance between parallelizing a sequential program (by increasing the number of processors) and optimizing the execution speed of the sequential program itself? For example, which is the better option: Having four processors running a given program for 40% of its execution, or using only two processors executing the same program, but for twice as long? This type of trade-off, which is commonly found in concurrent programming, can be strategically analyzed and answered by applying Amdahl's Law.

Additionally, while concurrency and parallelism can be a powerful tool that provides significant improvements in program execution time, they are not a silver bullet that can speed up any non-sequential architecture infinitely and unconditionally. It is therefore important for developers and programmers to know and understand the limits of the speed...