On Wed, Aug 7, 2013 at 3:26 PM, Andrew Dalke <dalke@dalkescientific.com> wrote:
On Aug 7, 2013, at 4:37 AM, Charles R Harris wrote:
> I haven't forgotten and intend to look at it before the next release.

Thanks!

On a related topic, last night I looked into deferring the
import for numpy.testing. This is the only other big place
where numpy's import overhead might be reduced without
breaking backwards compatibility.

It does break backwards compatibility though, because now you can do:

    import numpy as np
    np.testing.assert_equal(x, y)

 
I made a _DeferredTester [1] and replaced the 10 __init__.py
uses of:

from .testing import Tester
test = Tester().test
bench = Tester().bench

to use the _DeferredTester instead.

With that in place the "import numpy" time (best of 5)
goes from 0.0796 seconds to 0.0741 seconds, or 7%.

That 0.0796 includes the 0.02 seconds for the exec()
of the polynomial templates. Without that 0.02 seconds
in the baseline would give a 10% speedup. [2]

Would this sort of approach be acceptable to NumPy?
If so, I could improve the patch to make it be acceptable.

I think if it's tested well, implementing np.test() with a deferred tester is OK imho.

However, I would not be happy with breaking backwards compatibility for the numpy.testing module. Do you have more detailed timings? I'm guessing the bottleneck is importing nose. If so, you can still import numpy.testing into the numpy namespace without losing your gain in import time (nose is an optional dependency, so not imported by default inside numpy.testing).


The outstanding code issues to be resolve before making
a pull request are:

1) The current wrapper uses *args and **kwargs to forward
   any test() and bench() calls to the actual function.
   As a result, parameter introspection doesn't work.

2) The current wrapper doesn't have a __doc__

3) The only way to fix 1) and 2) is to copy the signatures
   and docstring from the actual Tester() implementation,
   which causes code/docstring duplication.

That all sounds fixable.
 

4) I don't know if it's appropriate to add my _DeferredTester
   to numpy.core vs. some other place in the code base.

numpy.lib I'd think.
 
If you want to see the patch, I followed the NumPy instructions at
 http://docs.scipy.org/doc/numpy/dev/gitwash/git_development.html
and made an experimental fork at
 https://github.com/adalke/numpy/tree/no-default-tester-import

I have no git/github experience beyond what I did for this
patch, so let me know if there are problems in what I did.

You did everything correctly.

Cheers,
Ralf

P.S. I also see some unused imports and files. Will send a cleanup PR.