tl;dr:“Semantic unit testing is a testing approach that evaluates whether a function’s implementation aligns with its documented behavior. The code is analyzed using LLMs to assess if the implementation matches the expected behavior described in the docstring. It’s basically having an AI review your code and documentation together to spot discrepancies or bugs, without running the code.”
tl;dr:“Good code is rarely read. Good code is so ergonomic that you almost don’t need to read it; you just use it. It allows developers to focus on building features and solving problems rather than deciphering existing code. This is the ultimate goal of good coding practices: to create code that is so clear and intuitive that it almost disappears, allowing the functionality to shine through.”
tl;dr:“Ever heard of the “Small Website Discoverability Crisis”? The problem it’s basically that small websites, ones like this one, are impossible to be found using Google or any other search engine. My mission? Making those tiny websites great again. In this post I will walk you through the journey of buliding a search engine from scratch using Python. This implementation doesn’t pretend to be a production-ready search engine, just a usable toy example showing how a search engine works under the hood.”