Implicit dependency on NumPy headers not made explicit anywhere

Hi, I've been on a quest the past two days to figure out why PyCall (through pyjulia) does not turn an `Array` on the Julia side into a NumPy array on the Python side (and produces a Python list instead). See https://github.com/paulmelis/blender-julia-test/issues/2 for all the gory details in nailing it down, particularly https://github.com/paulmelis/blender-julia-test/issues/2#issuecomment-687354497

The problem turns out to be that the NumPy installation I was using (as part of Blender) did not contain any header files and so `npyinitialize` in `numpy.jl` fails. There is an `error()` raised at that point with message `could not read __multiarray_api.h to parse PyArray_API` but that apparently never surfaces to the user level. In this case it gets raised further on from `NpyArray` but gets hidden in the catch part of `function PyObject(a::StridedArray{T}) where T<:PYARR_TYPES`. The message certainly isn't printed. It's also not mentioned anywhere in the docs that NumPy headers are being parsed (I could only find a reference to this in #38 from 2013).

So please add a note somewhere in the readme that the headers are a requirement for the NumPy installation used and are being parsed (which is quite unexpected). And NumPy initialization silently failing is also pretty suboptimal.

Comienza con el README y numpy.jl, especialmente con npyinitialize y el método PyObject(a::StridedArray{T}) descrito en el issue. Documenta el requisito de la cabecera de NumPy y el comportamiento del análisis, y verifica que los fallos de inicialización sean visibles para los usuarios en lugar de capturarse silenciosamente.

Escrito por el modelo de indexación a partir del texto del issue.