English | MP4 | AVC 1280×720 | AAC 44KHz 2ch | 1h 03m | 143 MB
If you were cooking a multicourse meal, would you prep one thing at a time? Put bread in the oven, wait. Warm the soup on the stove, wait. Then the main course. Wouldn’t it be more efficient to spend time prepping other food instead of waiting on tasks that don’t need your immediate attention? In the same way that having multiple things happen at the same time leads to faster meal prep, having multiple things happen in Python—or using an asynchronous approach—can be leveraged to boost application performance and make your Python programs extremely efficient. In this course, Ronnie Sheer gives you the tools to use async Python to solve real-world problems, gain familiarity with the async Python ecosystem, complete challenges with working examples, and become a more attractive candidate for engineering positions. If you’re an experienced Python user looking to take async Python from theory to practice, check out this hands-on course.
Table of Contents
Introduction
1 Supercharging Python async
2 What you should know
3 Setting up locally or using Gitpod
1. Understanding Asynchronous Programs
4 What makes programs slow and when async execution can help
5 How async works (asyncawait)
6 How async Python differs from other languages
7 Async sleep and gather
8 Challenge Sleep five
9 Solution Sleep five
2. Async Web Clients with aiohttp
10 Supercharging requests
11 Async WebSocket client
12 Challenge Write the response to a JSON file
13 Solution Write the response to a JSON file
3. Storage and Caching with aioredis
14 How Redis shines in modern applications
15 Getting started with aioredis
16 Challenge Redis chat
17 Solution Redis chat
4. Modern Servers with ASGI
18 What is ASGI
19 ASGI landscape
20 Chat app using Quart
21 Async Django and Django Channels at a glance
22 Challenge Store feed data in Redis
23 Solution Store feed data in Redis
Conclusion
24 Next steps
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