According to MAINT: silence Cython warnings about changes dtype/ufunc size. – numpy/numpy:
These warnings are visible whenever you import scipy (or another package) that was compiled against an older numpy than is installed.
and the checks are inserted by Cython (hence are present in any module compiled with it).
Long story short, these warnings should be benign in the particular case of numpy, and these messages are filtered out since numpy 1.8 (the branch this commit went onto). While scikit-learn 0.18.1 is compiled against numpy 1.6.1.
To filter these warnings yourself, you can do the same as the patch does:
import warnings
warnings.filterwarnings("ignore", message="numpy.dtype size changed")
warnings.filterwarnings("ignore", message="numpy.ufunc size changed")
Of course, you can just recompile all affected modules from source against your local numpy with pip install --no-binary :all:¹ instead if you have the balls tools for that.
Longer story: the patch’s proponent claims there should be no risk specifically with numpy, and 3rd-party packages are intentionally built against older versions:
[Rebuilding everything against current numpy is] not a feasible solution, and certainly shouldn’t be necessary. Scipy (as many other packages) is compatible with a number of versions of numpy. So when we distribute scipy binaries, we build them against the lowest supported numpy version (1.5.1 as of now) and they work with 1.6.x, 1.7.x and numpy master as well.
The real correct would be for Cython only to issue warnings when the size of dtypes/ufuncs has changes in a way that breaks the ABI, and be silent otherwise.
As a result, Cython’s devs agreed to trust the numpy team with maintaining binary compatibility by hand, so we can probably expect that using versions with breaking ABI changes would yield a specially-crafted exception or some other explicit show-stopper.
¹The previously available --no-use-wheel option has been removed since pip 10.0.0.