On Tue, Jul 17, 2012 at 1:31 AM, David Cournapeau <[email protected]>wrote:
> On Mon, Jul 16, 2012 at 5:28 PM, Charles R Harris > <[email protected]> wrote: > > Hi All, > > > > Working lazy imports would be useful to have. Ralf is opposed to the idea > > because it caused all sorts of problems on different platforms when it > was > > tried in scipy. I thought I'd open the topic for discussion so that folks > > who had various problems/solutions could offer input and the common > > experience could be collected in one place. Perhaps there is a solution > that > > actually works. > > I have never seen a lazy import system that did not cause issues in > one way or the other. Lazy imports make a lot of sense for an > application (e.g. mercurial), but I think it is a mistake to solve > this at the numpy level. > > This should be solved at the application level, and there are > solutions for that. For example, using the demandimport code from > mercurial (GPL) cuts down the numpy import time by 3 on my mac if one > uses np.zeros (100ms -> 50 ms, of which 25 are taken by python > itself): > > """ > import demandimport > demandimport.enable() > > import numpy as np > > a = np.zeros(10) > """ > > To help people who need fast numpy imports, I would suggest the > following course of actions: > - start benchmarking numpy import in a per-commit manner to detect > significant regressions (like what happens with polynomial code) > - have a small FAQ on it, with suggestion for people who need to > optimize their short-lived script > > That's really interesting. I'd like to see some folks try that solution. Chuck
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