| I love Python, but I also love the ability to tell what is what. I kickstarted a project in Python a decade ago that was wild on dynamic typing. As it passed a critical threshold of ~10k LoC, it became nearly ummaintainable. What's that `response` passed here? A verbatim response object from `requests`? A proxy mapping? Bytes? A JSON string? If so, a list or a dict? And what fields are inside? Multiply it by tens or hundreds of methods and classes, and it's easy to see why projects based on purely dynamic patterns fail to scale. By now I have almost completely rewritten that project to use type hints everywhere I could. And guess what? In 95% of the cases I knew exactly what was being passed - or the choice was about 2-3 types at most, so a Union sufficed. Yes, there's a 5% of cases where Python's dynamic typing features are a blessing. The power of meta programming in Python is often underestimated. Reflection is amazingly intuitive compared to the patchwork mess of Java, Kotlin and friends. Everything can be mocked without hassle and boilerplate. And duck typing can really be useful sometimes. But, again, in an average project I wouldn't expect code that benefits from these features to make up more than 5-10% of the codebase. For everything else, just do yourself, your future self and anyone who will work on your code a favour, and use type hints. |