The discussions from the OP and all the responders intrigue me and I enjoy the diverse perspecives on the issue. Thanks to all for their rich ideas, thoughts, and perspectives.

In my work place we have had a real world example of this very discussion. Our language of choice for testing and command and control of many of our space missions has been Perl. It has been a wonderful and trustworthy workhorse and we rarely use or need the various CPAN modules and capabilities of additions like PDL or MOOSE or the like. Not that they aren't useful or great; we just don't need them or use them...and on our command and control systems we're generally not allowed to import externally generated code except as comes in the core of Perl. We have a few internally developed and maintained libraries that we have used for almost 15 years and, while they've grown and morphed over the years, they get our job done.

We recently, however, decided to do a complete re-look, from the ground up, at our whole system and to "bring it into the 21st century" as our senior leadership likes to say.

We are looking at a whole nest of more "modern" approaches to capabilities to try to harness everything from "data mining" to "adaptive, emergent behaviors". I'm not saying that we *need* such capabilities per se; but rather that we're trying to consider in various niches how we could be much more effective, efficient, and capable.

I and my collegues have for about a year now been casting our nets wide throughout the community looking at where the state-of-the-art is today and we are considering how (or even if) we could benefit.

One outcome that crept in somewhat unexpectedly is that we have found several promising techniques (especially in terms of Service Oriented Architectures (SOA), data mining, etc.) that we are migrating towards. So we have all been absorbing, at high rate, every book and article that we can get our hands on to try to figure out how best to embrace these promising technologies.

The surprise is that almost *all* of these various currently popular techniques are richly described and even have lots of learning examples and algorithms readily available...in Python!

So over the last 2-3 months a movement has gone afoot to discard our Perl backbone and replace it with Python.

The only real impediment is that we would truly have to "start from scratch"...all the way from retraining our programmers to the learning curve of beginning to reprogram in another language to having to redevelop and test and verify all of our decade-long work in libraries that are still (and look to be into the future) our bread-n-butter. All because folks are starting to say, "Python *must* be the way to go since all of these 'modern' topics use it...none of them use Perl as their backbone or examples!"

I have a beginner's knowledge of Python and find it interesting but have yet to find anything that makes it any *better* than Perl. It is more compact in some ways; more troublesome and clunky in others. But in no instance that I've found so far is it *better*...just different. I can certainly see that it is fine language and can do the job, too. But I'm having a hard time getting that point across to those who keep pointing out that "it (Python) *must* be better because that's what all the gurus of these neat new gadgets use!"

So, to me, the problem with Perl is that noone is using it in a very visible, documenting-state-of-the-art new ideas using it. It is *not* sufficient, in my view, to just do great research and new technology developments in Perl and to publish the results such that Perl's contribution is better highlighted; it has to be used in popular, easily accessed examples for newly emerging techniques such as SOA, data mining, etc...especially in course text-book and popular introductions to those new techniques and technologies.

That's just my view; obviously it's just one more perspective.