On Mi, 2016-01-27 at 17:12 -0500, Benjamin Root wrote:

I like the idea of bumping the stacklevel in principle, but I am not sure it is all that practical. For example, if a warning came up when doing "x / y", I am assuming that it is emitted from within the ufunc np.divide(). So, you would need two stacklevels based on whether the entry point was the operator or a direct call to np.divide()? Also, I would imagine it might get weird for numpy functions called within other numpy functions. Or perhaps I am not totally understanding how this would be done?

You are right of course, and the answer is that I was never planning on fixing that. This is only for warnings by functions directly called by the users (or those which always go through one more level, though I did not check the C-api for such funcs). Also C-Api warnings are already correct in this regard automatically. Anyway, I still think it is worth it, even if in practice a lot of warnings are such things as ufunc warnings from inside a python func. And there is no real way to change that, that I am aware of, unless maybe we add a warning_stacklevel argument to those C-api funcs ;). - Sebastian

Ben Root

On Wed, Jan 27, 2016 at 5:07 PM, Ralf Gommers <ralf.gommers@gmail.com

wrote:

On Wed, Jan 27, 2016 at 11:02 PM, sebastian < sebastian@sipsolutions.net> wrote:

On 2016-01-27 21:01, Ralf Gommers wrote:

One issue will be how to keep this consistent. `stacklevel` is used so rarely that new PRs will always omit it for new warnings. Will we just rely on code review, or would a private wrapper around `warn` to use inside numpy plus a test that checks that the wrapper is used everywhere be helpful here?

Yeah, I mean you could add tests for the individual functions in principle. I am not sure if adding an alias helps much, how are we going to test that warnings.warn is not being used? Seems like quite a bit of voodoo necessary for that.

I was thinking something along these lines, but with a regexp checking for warnings.warn: https://github.com/scipy/scipy/blob/mas ter/scipy/fftpack/tests/test_import.py

Probably more trouble than it's worth though.

Ralf

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