Performing I/O concurrently is one of asyncio's superpowers (if not its main superpower). This is accomplished, directly or indirectly (through helpers like asyncio.gather), by the creation and use of asyncio tasks.
Over the years, I've put a lot of effort into making cattrs fast. Let's take a look at how the cattrs structuring code evolved during this time.
This post is an account of why I prefer using the attrs library over Pydantic. I'm writing it since I am often asked this question and I want to have something concrete to link to.
If you've ever gone through the Mypy docs, you might have seen the section on TypedDict. The section goes on to introduce the feature by stating: Python programs often use dictionaries with string
Arq is a job library for Python's asyncio. This article is up-to-date with Arq v0.19 The Point of Job Libraries The main point of (what I colloquially call) a job library is,