On 16 August 2013 20:00, <chris.bar...@noaa.gov> wrote: > > > One other point -- for performance reason, is would be nice to have some > compiled code in there -- this adds incentive to put it in the stdlib -- > external packages that need compiling is what makes numpy unacceptable to > some folks. >> >> It might be good to have a C accelerator one day but actually I think >> the pure-Python-ness of it is a strong reason to have it since it >> provides accurate statistics functions to all Python implementations >> (unlike numpy) at no additional cost. > > Well, I'd rather not have a package that is great for education and toy > problems, but not-so-good for the real ones...
Again it depends what you mean by "real". From the other lists where we meet I'd guess that your problems are in the "needs a nuclear reactor" camp. I doubt that the stdlib will ever be sufficiently mathematically/computationally oriented to fully service either of our needs (and I don't mean that as a criticism). I persuaded the IT guys at my work that we needed the whole Enthought Python Distribution on all machines just because I didn't want to have to argue about individual packages. However in my real work, where I compute means and variances etc. I very often do work with very small datasets and I know a lot of others who work almost exclusively with them (think e.g. clinical data where N is often less than 100). > I guess my point is this: > > This is a way to make the standard python distribution better for some common > computational tasks. But rather than think of it as "we need some stats > functions in the python stdlib", perhaps we should be thinking: "out of the > box python should be better for computation" -- in which case, I'd start with > a decent array object. I think that, whether or not the statistics module gains a C accelerator, if a fast numerical array type comes along then I'd expect that the statistics module would use its methods as a fast path. And if it provides a speed boost without compromising boundedness or accuracy I'm sure that the array type would be used internally where appropriate (just as numpy converts collections to arrays before computation). Oscar -- http://mail.python.org/mailman/listinfo/python-list
