Login: Password:  Do not remember me




E-BooksPython Concurrency with asyncio





Python Concurrency with asyncio
English | 2022 | ISBN: 1617298662 , 978-1617298660 | 378 pages | True PDF | 6.07 MB
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 asyncioteaches 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 asynciointroduces 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 Fowlerhas 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


Buy Premium From My Links To Get Resumable Support,Max Speed & Support Me



📌🔥Contract Support Link FileHost🔥📌
✅💰Contract Email: [email protected]

Help Us Grow – Share, Support

We need your support to keep providing high-quality content and services. Here’s how you can help:

  1. Share Our Website on Social Media! 📱
    Spread the word by sharing our website on your social media profiles. The more people who know about us, the better we can serve you with even more premium content!
  2. Get a Premium Filehost Account from Website! 🚀
    Tired of slow download speeds and waiting times? Upgrade to a Premium Filehost Account for faster downloads and priority access. Your purchase helps us maintain the site and continue providing excellent service.

Thank you for your continued support! Together, we can grow and improve the site for everyone. 🌐

[related-news]

Related News

    {related-news}
[/related-news]

Comments (0)

Ooops, Error!

Information

Users of Guests are not allowed to comment this publication.

Search



Updates




Partner


» TutBB
» Byte
» Crawli
» Warezomen
» Warez-DDL
» Raidrush
» KATZCD
» Free Ebooks Library

Your Link Here ?
(Pagerank 4 or above)