Using Asyncio in Python: Understanding Python's Asynchronous Programming Features

Hattingh, Caleb

ISBN 10: 1492075337 / ISBN 13: 9781492075332

Published by O'Reilly Media, 2020

About this Item

The book has been read, but is in excellent condition. Pages are intact and not marred by notes or highlighting. The spine remains undamaged.

Seller Inventory # GOR013175512

Bibliographic Details

• Title: Using Asyncio in Python: Understanding Python's Asynchronous Programming Features
• Publisher: O'Reilly Media
• Publication Date: 2020
• Language: English
• ISBN 10: 1492075337
• ISBN 13: 9781492075332
• Binding: Paperback
• Condition: Very Good
• Weight: 299 grams

About this title

Synopsis

If you’re among the Python developers put off by asyncio’s complexity, it’s time to take another look. Asyncio is complicated because it aims to solve problems in concurrent network programming for both framework and end-user developers. The features you need to consider are a small subset of the whole asyncio API, but picking out the right features is the tricky part. That’s where this practical book comes in.

Veteran Python developer Caleb Hattingh helps you gain a basic understanding of asyncio’s building blocks—enough to get started writing simple event-based programs. You’ll learn why asyncio offers a safer alternative to preemptive multitasking (threading) and how this API provides a simpleway to support thousands of simultaneous socket connections.

• Get a critical comparison of asyncio and threading for concurrent network programming
• Take an asyncio walk-through, including a quickstart guidefor hitting the ground looping with event-based programming
• Learn the difference between asyncio features for end-user developers and those for framework developers
• Understand asyncio’s new async/await language syntax, including coroutines and task and future APIs
• Get detailed case studies (with code) of some popular asyncio-compatible third-party libraries

About the Author

Caleb Hattingh is passionate about coding and has been programming for over 20 years, specializing in Python. He holds a master's degree in chemical engineering and has consequently written a great deal of scientific software within chemical engineering, from dynamic chemical reactor models all the way through to data analysis. He is very experienced with the Python scientific software stack, as well as CRM, financial software development in the hospitality industry, GPS tracking, natural-language processing, and various other projects.