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Most of this would apply to Perl, as well. Which I can't fathom why Perl didn't easily beat out Python in the data science world. It's incredibly stable (versio
by deckard1 7y ago
Most of this would apply to Perl, as well. Which I can't fathom why Perl didn't easily beat out Python in the data science world. It's incredibly stable (version 5, that is), fast, and can just about rip apart and parse any raw data you have with ease. Python may "feel" newer, but there are only a few years age difference. Even Ruby isn't that much newer.
Tragically, Perl developed its "unreadable" reputation because it was the language du jour of the system admin/hacking world. The first time most people experienced Perl was by finding some crufty old script that glued a bunch of shell tools together haphazardly. Few developers today have actually seen what good, production Perl can look like.
No disrespect to the wonderful system admins of years past, but those guys were a different breed. They weren't programmers. But Perl still let them get their job done. Their unmaintainable messes caused a great deal of harm to Perl.
- acomjean 7y agoI maintain others Perl code and am no expert. Its our most use web tool and has been running for 10 years. I think Perl is different enough to confuse people who look at it (@,%,$) and it can make it hard to follow. I still have a little problems switching to it from other languages sometimes (do x unless y seems backward to me). I've also been told I write perl like a c programmer. Perl does have some beautiful parts though.. CPAN is great, but its hard sometimes when I just want to install something easy. It was the first great shared library and it shows its age a bit. Last time I ran it, it was compiling C code for some strange reason. We have trouble setting up shared perl environments, something we don'e have with python. Biology has a lot of Perl code still, but it seems to moving to python. Terrible code exists in many languages.