> Libraries that you have to know might as well be language features. What you have to know depends on where you're working and what you're doing. You don't ha

> Libraries that you have to know might as well be language features. What you have to know depends on where you're working and what you're doing. You don't have to know GRPC Python libraries, unless it's a company that uses GRPC for internal communication. You don't have to know Flask unless you're building a REST API using Flask. You don't have to know beautifulsoup unless you're building a web scraper. You don't have to know Pydantic unless you're working on a project that uses Pydantic for data validation. > The phrasing of "The engineering decision" in your reply is telling -- you are coming from it as an engineer. But I'm looking at the population of Python programmers, which extends far beyond software engineers. You don't have to be a software engineer to make an engineering decision. When a data scientist uses conda because they don't want to manage their Python environment manually, but runs into performance issues on production because their Docker containers are multiple gigabytes larger than they should be -- that's the result of an engineering decision. When a business analyst writes a Python script and manually installs packages without a requirements file, then tries to get it running on a new computer 8 months later but can't because they forget which package versions they used -- that's the result of an engineering decision. So when you deploy your code without any data validation that runs fine now, but breaks in unexpected ways next week because the result of an external REST API you're calling changed unexpectedly... > The more such people have to learn, the more problematic the language becomes. Python succeeded despite not being a statically compiled language with clear typechecking because there is an audience for which those aren't the critical factors. ... none of these changes are free. I agree with all this, which is why I said that the engineering decision is deciding whether or not the cost is worth it. Different projects, companies, and people will have different needs. Your original assertion was that "if this is a feature you must have, Python seems like the wrong language" -- but this contradicts what you're saying. The overhead of learning a single Python library is far, far less than, say, introducing Rust into a company that only uses Python for everything else.