[Python] A Journey to Python Async - 1. Intro

• Pandas

  394 41,923 10.0 Python

  Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more

  

But whereas I took for granted that async syntax in JS, async in Python was quite unfamiliar to me when I saw it for the first time. I had some experiences of using Python for writing really simple scripts, without ever worrying about those async features. That was probably because many big popular libraries such as numpy, pandas, or even selenium didn’t require any async logics to be considered. And those libraries were(and still are) the main reasons for using Python at all.

• NumPy

  272 26,360 10.0 Python

  The fundamental package for scientific computing with Python.

  

But whereas I took for granted that async syntax in JS, async in Python was quite unfamiliar to me when I saw it for the first time. I had some experiences of using Python for writing really simple scripts, without ever worrying about those async features. That was probably because many big popular libraries such as numpy, pandas, or even selenium didn’t require any async logics to be considered. And those libraries were(and still are) the main reasons for using Python at all.

• WorkOS

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  The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.

  

• fastapi

  466 70,779 9.8 Python

  FastAPI framework, high performance, easy to learn, fast to code, ready for production

However, after I joined the current company and started using FastAPI, I had to use that async feature in Python, although I didn’t really need to understand what those syntaxes meant - I only guessed that they’re acting pretty much like the ones in JS/Node.js. That was quite correct, and everything works just fine.

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