On Tue, Aug 6, 2013 at 8:32 PM, Andrew Dalke <[email protected]>wrote:
> Hi all, > > I mostly develop software related cheminformatics. There > isn't much direct overlap between the tools of that field > and NumPy and SciPy provide, but it's increasing with the > use of scikit-learn and pandas. > > I tend to write command-line tools which indirectly > import numpy. I've noticed that 25% of the "import numpy" > cost of about 0.081 seconds is due to the chebyshev, laguerre, > legendre, hermite_e, and hermite_e modules. Each module > takes about 0.004 seconds to import. > > This is because each of them does a: > > exec(polytemplate.substitute(name='Chebyshev', nick='cheb', > domain='[-1,1]')) > > during import. It appears that *everyone* takes a 0.02 second > overhead during "import numpy" in order to simplify maintenance. > This balance doesn't seem correct, given the number of people > who use numpy vs. how rarely the polytemplate changes. > > > Last year I submitted a patch which pre-computed all of those > templates, so they would only be byte-compiled once. > > > I knew (and still know) almost nothing about git/github, so > Scott Sinclair kindly took it up and made it a pull request at: > > https://github.com/numpy/numpy/pull/334 > > > I see that there's been no activity for at least 10 months. > > Is there anything more I can do to encourage that this patch > be accepted? > > Hi Andrew, I haven't forgotten and intend to look at it before the next release. Chuck
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