Python in sci/tech applications

[mattf]

I've discovered Python and have been trying it out lately as a possible
replacement for computations that would ordinarily be done with a
commercial package like Matlab or IDL. I'd like to mention a few things
I've run across that have either surprised me or kept me from doing
things the way I'd like to.

1) -There's a large and active sci/tech Python community out there.-
This was something of a surprise. If you look at the python.org site
and click down a couple of levels past the front page, there's a rather
brief mention of scientific and numeric applications-- but I don't
think this does justice to the current levels of activity and
accomplishment.

2) -There's a very impressive set of libraries out there-
NumPy, SciPy, Enthought. It's really kind of stunning how mature these
libraries are and how much I had to poke around to figure that out.

3) -There's a problem with development under Windows.
A typical task will entail writing a 'pure python' prototype to get the
'data in, data out' part of a problem straightened out, then writing a
module in C to get adequate performance in production runs. But the C
compiler that my employer provides (the current version of MSVS)
doesn't produce libraries that work with the current version of Python.
Ooops. This, in the real world, is a big problem. I -love- Python. And
I think I could convince other people to use it. But I've got to have a
way to produce compiled modules painlessly, i.e., without installing a
new operating system.