Conversion of read-only numpy arrays

Currently, a read-only numpy array is not converted into either an `Array` or a `PyArray` automatically:

```julia
using PyCall

py"""
import numpy

def get_read_only_narray():
x = numpy.zeros(10)
x.flags.writeable = False
return x
"""

arr = py"get_read_only_narray"()
@assert isa(arr, PyObject)
```

Attempting to convert manually into a `PyArray` with `PyArray(arr)` gives an error "buffer source array is read-only", which makes sense because https://github.com/JuliaPy/PyCall.jl/blob/master/src/pyarray.jl#L16 seems to be assuming the buffer is writeable (`PyBUF_ND_STRIDED` implies `PyBUF_WRITABLE`). This seems like it could be considered a bug in `PyArray` constructor, since `PyArray` does check for the `readonly` flag later in the constructor: https://github.com/JuliaPy/PyCall.jl/blob/master/src/pyarray.jl#L22

I worked around this:

```julia
# workaround
function convert_it(read_only_numpy_arr::PyObject)

# See https://github.com/JuliaPy/PyCall.jl/blob/master/src/pyarray.jl#L14-L24

# instead of PyBUF_ND_STRIDED = Cint(PyBUF_WRITABLE | PyBUF_FORMAT | PyBUF_ND | PyBUF_STRIDES)
# See https://github.com/JuliaPy/PyCall.jl/blob/master/src/pybuffer.jl#L113
pybuf = PyBuffer(read_only_numpy_arr, PyCall.PyBUF_FORMAT | PyCall.PyBUF_ND | PyCall.PyBUF_STRIDES)

T, native_byteorder = PyCall.array_format(pybuf)
sz = size(pybuf)
strd = PyCall.strides(pybuf)
length(strd) == 0 && (sz = ())
N = length(sz)
isreadonly = pybuf.buf.readonly==1
info = PyCall.PyArray_Info{T,N}(native_byteorder, sz, strd, pybuf.buf.buf, isreadonly, pybuf)

# See https://github.com/JuliaPy/PyCall.jl/blob/master/src/pyarray.jl#L123-L126
PyCall.PyArray{T,N}(read_only_numpy_arr, info)
end

arr2 = convert_it(arr) # arr2 is a PyArray
@assert isa(arr2, PyArray)
@assert size(arr2) == (10,)
println(arr2)
```

Based on the above, it seems possible to fix the `PyArray` constructor to handle this case. Separately, it would be even more useful to automatically convert read-only numpy arrays into an `Array` (and do a copy).

Start with src/pyarray.jl, especially the PyArray constructor, and compare its buffer request with the read-only handling described in src/pybuffer.jl. Reproduce the example using a read-only NumPy array, then determine and test the intended behavior for PyArray conversion and copying into Array.

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