in reply to
Putting Perl Back on Top in the Fields of Scientific and Financial Computing
Also knowing Perl well requires more time than knowing Python well.
You need time to study Perl's quircks and variables, to give only a few examples:
Also, the book Modern Perl, if everybody agrees that it's such a nice book and all, should be
integrated in perldoc or in Perl's official documentation, because only in this way people can
have easy access to it (It should be distributed with the perldoc package in Ubuntu for example).
PDL is pretty slow, also, compared to other available software for doing what it doesn't provide
the speed, ease of use of other pieces of software.
Also, a weird thing is that PDL depends on OpenGL, so on a machine without X you can't actually do anything with PDL(or you can but it takes you some additional $amount_of_time).That is not normal
since machines that only crunch numbers needn't have X on them.
Also, how portable is PDL actually ? Haven't tried it on windows.
So Python is used for financial and scientific computing because its syntax is easier to learn.
Perl is something that was an improvisation and it's starting to get more organized. But nobody knows that it's organized because they don't have the time to read all the blogs in the Perl "ecosystem" and go on IRC and ask a ton of questions on various channels. So if they include the "Modern Perl" modules and docs in the documentation that comes with every Perl distro then maybe the situation will change.
But in bioinformatics I think Perl is used a lot, I see recurring questions from students in bioinformatics here on perlmonks and some books are out on that and the BioPerl package is pretty vast, lots of people worked on it and I'm pretty sure it's development was well-funded by some big companies in the domain.