[Numpy-discussion] Bump warning stacklevel

[sebastian]

On 2016-01-27 21:01, Ralf Gommers wrote:
> On Wed, Jan 27, 2016 at 7:26 PM, Sebastian Berg
> <sebastian at sipsolutions.net> wrote:
> 
>> Hi all,
>> 
>> in my PR about warnings suppression, I currently also have a commit
>> which bumps the warning stacklevel to two (or three), i.e. use:
>> 
>> warnings.warn(..., stacklevel=2)
>> 
>> (almost) everywhere. This means that for example (take only the
>> empty
>> warning):
>> 
>> np.mean([])
>> 
>> would not print:
>> 
>> /usr/lib/python2.7/dist-packages/numpy/core/_methods.py:55:
>> RuntimeWarning: Mean of empty slice.
>> warnings.warn("Mean of empty slice.", RuntimeWarning)
>> 
>> but instead print the actual `np.mean([])` code line (the repetition
>> of
>> the warning command is always a bit funny).
>> 
>> The advantage is nicer printing for the user.
>> 
>> The disadvantage would probably mostly be that existing warning
>> filters
>> that use the `module` keyword argument, will fail.
>> 
>> Any objections/thoughts about doing this change to try to better
>> report
>> the offending code line?
> 
> This has annoyed me for a long time, it's hard now to figure out where
> warnings really come from. Especially when running something large
> like scipy.test(). So +1.
> 
>> Frankly, I am not sure whether there might be
>> a python standard about this, but I would expect that for a library
>> such as numpy, it makes sense to change. But, if downstream uses
>> warning filters with modules, we might want to reconsider for
>> example.
> 
> There probably are usages of `module`, but I'd expect that it's used a
> lot less than `category` or `message`. A quick search through the
> scipy repo gave me only a single case where `module` was used, and
> that's in deprecated weave code so soon the count is zero.  Also, even
> for relevant usage, nothing will break in a bad way - some more noise
> or a spurious test failure in numpy-using code isn't the end of the
> world I'd say.
> 
> 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.

- Sebastian



> Ralf
> 
> 
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