I've no love lost for Python, but in regards to what Python's creator may have said at the beginning, I'm reminded of the Linux announcement -- "just a hobby, won't be big and professional" and "NOT portable", "probably never will support anything other than AT-harddisks."
Julia sounds wonderful on paper, but as soon as I want to work with the sorts of data that is my bread and butter, the ecosystem in Julia is empty, whilst Python is fully featured.
Spoken with the arrogance of a true software engineer.
It's common in science to see computer scientists implement domain-specific software with a hopelessly naive understanding of the domain, leading to biased, wrong, or misinterpreted results. Like, go to any bioinformatics conference and you will find these people.
"What do you mean I can't just use a database of clinical pathogens to make a tool that generalises to all bacteria?"
Mh, I read the parent's post as: "You can count on science producing things that software engineers will complain about (and therefore use). But it's rare for science to use stuff produced by software engineers at all, and hence there's no complaint that way"
It is also common in science to solve problems by producing unmaintainable write-only code and managing dependencies by bundling up the entire universe into one enormous distribution.
This approach works for science, not for software engineering in general. Hence, we do not adopt it.
The problem of a lack of understanding of the domain exists in all domains, but many scientists are particularly inept at expressing their precious ideas in terms that an ordinary person could hope to comprehend.
> It's common in science to see computer scientists implement domain-specific software with a hopelessly naive understanding of the domain, leading to biased, wrong, or misinterpreted results.