In a message of Sun, 26 Jul 2015 18:58:14 -0500, "E.D.G." writes:
> This is an indirect URL for a potentially important computer program >that I feel needs to be developed. Unfortunately, although Python could be >used to create PC or Mac versions of the program I don't think that those >programs would run on Internet server computers. But I don't yet know >enough about Python to be able to tell if that is the case or not. Sure they will. That thing about the Affordable Health Care Act you mentioned -- do you know how this got _fixed_? People in this community, notably Alex Gaynor went and turned the lot into a Django Python app. He's now working for the US department of Veteran Affairs, turning more things into Django apps so that veterans can get their claims processed in weeks (they are aiming for days) rather than 6-8 months which was the norm before he got their. His plan is to speed up the US government with Python one agency at a time. There are many techniques you can use to make your Python code fast. I think we are much better off in that regard than the Perl users are. If you need better than CPython performance, you might be able to just use numpy numerical arrays and get the improvement you need. Or you might just stop using CPython, and use PyPy, which is a completely different implementation and which has a JIT that gives rather good performance, often on the order of pure C code. see http://speed.pypy.org/ Or you can use Cython http://cython.org/ to make C extensions out of the part of your python code you would like to run faster. Or maybe there already is a C or Fortran library that already does what you want, you just want to use it in your code. There are techniques for just doing this -- and if the library is well known then chances are somebody else has already made python bindings for it so you can just use it with CPython. I wouldn't worry about speed. If you want to reimplement your webscraping Perl program in Python, I suggest you start with this library http://scrapy.org/ rather than reinventing things from scratch. The scrapy community is very happy to get code with new techniques which they add to the library, and then we all benefit. Laura -- https://mail.python.org/mailman/listinfo/python-list
