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Comment by sparrc | Hacker News Reader

You're completely misinterpreting (I'm the author of (1)).

C++ and javascript are languages of professional software engineers, of which there are many many more languages with various pros and cons.

Python has been the defacto standard in scientific/data/academic programming for decades. The only other language you could say rivals it would be MATLAB which is even more simplistic.

My point is that simplicity and clarity matters to people who don't care that much about programming and are completely unfocused on it, they are just using it do get data for unrelated research.

'if __name__ == "__main__"' is not in the example code nor is it a required part of a python program so not really sure what your point is here.

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> Python has been the defacto standard in scientific/data/academic programming for decades

In my experience (Genomics) this is simply not true. Python has caught on over the last 5 or so years, but prior to that Perl was the defacto language for genetic analysis. Its still quite heavily used. Perl is not a paragon of simplicity and clarity.

It may not be true for a niche field. It is true broadly for computation in academia.

I don't find this response convincing because:

(a) While I'm being honest that my observations are based on the fields I have experience, there is no such justification that "It is true broadly for computation in academia" in your comment.

(b) Interpreting "niche" as "small" (especially given your "true broadly" claim): Computational genetics is huge in terms of funding dollars and number of researchers.

I was in academic compsci/ai from 2001-2017 and it was entirely c++ and python in my department, except for one oldschool professor who used delphi.

Haha, there is always one :)

I feel like trying out various languages/frameworks would affect compsci labs a lot less than other fields, since the students probably have some foundational knowledge of languages and have already learned a few before getting there. Might be easier for them to pick up new ones.

At my University AI and ML were taught using Java. It was more handy to both teachers and students since most other courses used Java.

Have you honestly not heard of R? Which had more mainstream data science mindshare than python as recently as 5 years ago?

I have, my impression when doing an applied math degree more than 10 years ago was that python was by far more prevalent than R. I know through my wife that python is much more prevalent in bio-informatics and bioengineering too.

Doesnt really change my argument though, R is also a slow but simple language that is popular among academics but not professional software engineers. My whole point is that Swift is never going to be popular with academics because the syntax isn't simple enough.

>MATLAB which is even more simplistic [than Python].

The person you are replying to didn't call Python simplistic (and it certainly is not simple IMHO), they called it slow.

Python has only been around for 30 years? That’s 3 decades. Of which maybe only part of the last 1 had Python gained traction in science and data.

Hasn't been my experience. I was programming mostly in python in 2007 in applied math, oceanography, and physics classes. It had already been established in those fields (at least at my university) in 2007 so it's been at least 15 years.

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