Python Concurrency with Asyncio

Matthew Fowler

ISBN 10: 1617298662 / ISBN 13: 9781617298660

Published by Manning Publications Mär 2022, 2022

About this Item

Neuware - Python Concurrency with asyncio teaches you to write concurrent Python code that will boost the speed of your apps and APIs. The book demystifies asynchio's unique single-threaded concurrency model, giving you a behind-the-scenes understanding of the library and its new async/await syntax. Hard-to-grok concurrency topics are broken down into simple flowcharts so you can easily see how your coroutines and tasks are running. You'll learn to apply asyncio to solve common performance problems, such as batch database jobs, slow web servers, and scaling microservices. All examples you'll build are designed to be usable in the real world, including a clever command line SQL client that can run multiple slow queries at the same time. By the time you're done, you'll even be able to combine asyncio with traditional multiprocessing and multithreading techniques for huge improvements to performance.

Seller Inventory # 9781617298660

Bibliographic Details

• Title: Python Concurrency with Asyncio
• Publisher: Manning Publications Mär 2022
• Publication Date: 2022
• Language: English
• ISBN 10: 1617298662
• ISBN 13: 9781617298660
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 234W x 190H x 22D millimeters 234 millimeters width by 190 millimeters height by 22 millimeters depth
• Weight: 603 grams

About this title

Synopsis

Learn how to speed up slow Python code with concurrent programming and the cutting-edge asyncio library.

    Use coroutines and tasks alongside async/await syntax to run code concurrently
    Build web APIs and make concurrency web requests with aiohttp
    Run thousands of SQL queries concurrently
    Create a map-reduce job that can process gigabytes of data concurrently
    Use threading with asyncio to mix blocking code with asyncio code

Python is flexible, versatile, and easy to learn. It can also be very slow compared to lower-level languages. Python Concurrency with asyncio teaches you how to boost Python's performance by applying a variety of concurrency techniques. You'll learn how the complex-but-powerful asyncio library can achieve concurrency with just a single thread and use asyncio's APIs to run multiple web requests and database queries simultaneously. The book covers using asyncio with the entire Python concurrency landscape, including multiprocessing and multithreading.

Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.

About the technology
It’s easy to overload standard Python and watch your programs slow to a crawl. Th e asyncio library was built to solve these problems by making it easy to divide and schedule tasks. It seamlessly handles multiple operations concurrently, leading to apps that are lightning fast and scalable.

About the book
Python Concurrency with asyncio introduces asynchronous, parallel, and concurrent programming through hands-on Python examples. Hard-to-grok concurrency topics are broken down into simple flowcharts that make it easy to see how your tasks are running. You’ll learn how to overcome the limitations of Python using asyncio to speed up slow web servers and microservices. You’ll even combine asyncio with traditional multiprocessing techniques for huge improvements to performance.

What's inside

    Build web APIs and make concurrency web requests with aiohttp
    Run thousands of SQL queries concurrently
    Create a map-reduce job that can process gigabytes of data concurrently
    Use threading with asyncio to mix blocking code with asyncio code

About the reader
For intermediate Python programmers. No previous experience of concurrency required.

About the author
Matthew Fowler has over 15 years of software engineering experience in roles from architect to engineering director.

Table of Contents
1 Getting to know asyncio
2 asyncio basics
3 A first asyncio application
4 Concurrent web requests
5 Non-blocking database drivers
6 Handling CPU-bound work
7 Handling blocking work with threads
8 Streams
9 Web applications
10 Microservices
11 Synchronization
12 Asynchronous queues
13 Managing subprocesses
14 Advanced asyncio

About the Author

Matthew Fowler has over 15 years of software engineering experience in roles from architect to engineering director. He has worked on Python codebases in the machine learning space, as well as led development of a Python-based ecommerce site with tens of millions of users.