Sign In Start Free Trial
Account

Add to playlist

Create a Playlist

Modal Close icon
You need to login to use this feature.
  • Mastering Concurrency in Python
  • Toc
  • feedback
Mastering Concurrency in Python

Mastering Concurrency in Python

By : Quan Nguyen
1 (1)
close
Mastering Concurrency in Python

Mastering Concurrency in Python

1 (1)
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)
close

Summary

While the GIL in Python offers a simple and intuitive solution to one of the more difficult problems in the language, it also raises a number of problems of its own, concerning the ability to run multiple threads in a Python program to process CPU-bound tasks. Multiple attempts have been made to remove the GIL from the main implementation of Python, but none have been able to achieve it while maintaining the effectiveness of processing non-CPU-bound tasks, which are affected by the GIL.

In Python, multiple methods are available to provide options for working with the GIL. All in all, while it possesses considerable notoriety among the Python programming community, the GIL only affects a certain portion of the Python ecosystem, and can be seen as a necessary evil that is too essential to remove from the language. Python developers should learn to coexist with the GIL, and...

bookmark search playlist download font-size

Change the font size

margin-width

Change margin width

day-mode

Change background colour

Close icon Search
Country selected

Close icon Your notes and bookmarks

Delete Bookmark

Modal Close icon
Are you sure you want to delete it?
Cancel
Yes, Delete