On Jan 11, 6:15 pm, Steven D'Aprano <[EMAIL PROTECTED] cybersource.com.au> wrote: > Your users are *scientists*, and you don't trust their intellectual > ability to learn a programming language as simple as Python? > > Instead of spending time and effort writing, debugging and maintaining > such a fragile approach, why not invest in a couple of introductory books > on Python programming and require your scientists to go through the first > few chapters? Or write out a one-page "cheat sheet" showing them simple > examples. Or, and probably most effectively, make sure all your classes > have doc strings with lots of examples, and teach them how to use help(). > > Some people problems are best dealt with by a technical solution, and > some are not. > > -- > Steven
I am currently talking very similar trash on my blog, See http://initforthegold.blogspot.com/2008/01/staying-geeky.html and http://initforthegold.blogspot.com/2007/12/why-is-climate-modeling-stuck.html You seem to think that learning the simple language is equivalent to grasping the expressive power that the language provides. Yes, users are scientists. Therefore they do not have the time or interest to gain the depth of skill to identify the right abstractions to do their work. There are many abstractions that could be useful in science that are currently provided with awkward libraries or messy one-off codes. The idea that a scientist should be expected to be able to write correct and useful Python is reasonable. I and the OP are relying on it. The idea that a scientist should be expected to identify and build clever and elegant abstractions is not. If you think every scientist can be a really good programmer you underestimate at least one of what good scientists do or what good programmers do or what existing high performance scientific codes are called upon to do. mt -- http://mail.python.org/mailman/listinfo/python-list
