Comment by csirac2 | Hacker News Reader

Comment by csirac2 | Hacker News Reader

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Perl I think, if nothing else, shows a great example of how a language can evolve dramatically. You can almost date the code you're reading (or the programmer, or the age of the online tutorials the coder read) based on style of the code.

I've been paid to write perl in a team maintaining high-volume web properties and internal APIs for a large telco, and I also spent a few years in a Bioinformatics role which used it a fair bit at a national science agency (the research community in that particular corner of the discipline had some pretty awesome tools/libraries written in perl, but the full gamut of stuff we used also included ruby, python, R, C, Fortran...)

Just a few days ago I wrote how I missed Perl's Moose OO framework now that I'm doing mostly Python [1] [2], and that interestingly it's this that has prompted me to think more seriously about using a more strongly/statically typed language for large projects in future.

[1] https://news.ycombinator.com/item?id=8627143 [2] https://news.ycombinator.com/item?id=8627819

I'm at a military hospital, the only language they'll allow is perl. But I can have any version I want installed (eg Padre). But I can remote I to HPC systems with ipython. Not sure if the left hand is talking to the right.

Although large organisations tend to have a goal of minimizing the number of languages and platforms they depend on, rarely does this turn out to be the case in practice. HPC systems in particular are expensive assets which could never justify themselves if they could only run one kind of workload in one particular language :-)

If I had to guess, you're working in a business unit that is heavily invested in perl and so sticking other stuff in that environment is perceived as an unnecessary future maintenance burden. The HPC system on the other hand is perhaps shared across multiple business units who don't have the exact same stacks as each other so it's flexible in that way.

python + pandas is pretty awesome though, I was able to delete thousands of lines old perl code dealing with irregular time series when I re-wrote with pandas - it made sense in that instance to ditch the old perl code, it doesn't always though.

To be clear, I'm a pathology resident trying to do research. My code wouldn't affect anyone. I just want to think in python instead of perl.

Ah, so a little more arbitrary than I assumed. I initially hated perl when I first started with it, for what it's worth. I guess you've progressed beyond the point of finding [1] helpful (even if the perl looks a bit strange to me in places). And, apart from Moose I also miss perl's lexically scoped variables :)

It would suck to do numerical work without pandas though. I love pandas.

[1] https://wiki.python.org/moin/PerlPhrasebook

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