On 11 Mar 2014 13:28, "Paul Brossier" <[email protected]> wrote: > If I understand correctly, the current version is the one installed on > the user system. So using NPY_API_VERSION would mean "this code should > work with any version of numpy". I guess this is what I want (I would > even expect this to be the default setting). Did I miss something?
Using NPY_API_VERSION here means "this code will work with any version of numpy, *including ones that aren't released yet and might have arbitrary API changes*". This is almost certainly not what you want. The idea of the deprecation support is that it gives you a grace period to adapt to upcoming changes before they break your code. Suppose PyArray_foo is going to be removed in numpy 1.10. If we just removed it, your first warning would be when we release 1.10 and suddenly you have angry users who find your software no longer works. So the trick is that before we remove it entirely, we release 1.9, in which PyArray_foo is available if your NPY_DEPRECATED_API version is set to 1.8 or earlier, but not if it's set to 1.9. Your released versions thus continue to work, your users are happy, and the first person to encounter the problem is you, when you try to update your NPY_DEPRECATED_API to 1.9. You fix the problem, you make a new release, and then when 1.10 comes along everything works. Moral: set NPY_DEPRECATED_API to match the highest numpy version you've tested. -n
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