>To be clear, I am not taking some specific position, but I think all these topics inform answers to your question. I think it's something with trade-offs that people have a tendency to over-simplify based on a limited view.

That's fair, I wasn't dimsissing the practice but rather just commenting that it's a shame the author didn't clarify their preference.

I don't think the popularity angle is a good proxy for usefulness/correction of the practice. Many factors can influence popularity.

Performance is a very fair point, I don't know enough to understand the details but I could see it being a strong argument. It is counter intuitive to move forward with calculations known to be useless, but maybe the cost of checking all calculations for validity is larger than the savings of skipping early the invalid ones.

There is a catch though. Numpy and R are very oriented to calculation pipelines, which is a very different usecase to general programming, where the side effects of undetected 'corrupt' values can be more serious.