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 3

What is a thread? What are the core differences between a thread and a process?

A thread of execution is the smallest unit of programming commands. More than one thread can be implemented within a same process, usually executing concurrently and accessing/sharing the same resources, such as memory, while separate processes do not do this.

What are the API options provided by the thread module in Python?

The main feature of the thread module is its fast and efficient method of creating new threads to execute functions: the thread.start_new_thread() function. Aside from this, the module only supports a number of low-level ways of working with multithreaded primitives and sharing their global data space. Additionally, simple lock objects (for example, mutexes and semaphores) are provided for synchronization purposes.

What are the API options provided by the threading module...