Best Choice For Passing Float Arrays In Cython

Say there is a C++ class in which we would like to define a function to be called in python. On the python side the goal is being able to call this function with: Input: of type 2

Solution 1:

Cython Input

The most natural Cython type to use for the input interface between Python and Cython would be a 2D typed memoryview. This will take a 2D numpy array, as well as any other 2D array type that exports the buffer interface (there aren't too many other types since Numpy is pretty ubiquitous, but some image-handling libraries have some alternatives).

I'd avoid using list-of-lists as an interface - the length of the second dimension is poorly defined. However, Numpy arrays are easily created from list-of-lists.

Cython Output

For output you return either a Cython memoryview, or a Numpy array (easily created from a memoryview with np.asarray(memview)). I'd probably return a Numpy array, but make a decision based on whether you want to make Numpy a hard dependency.

C++ interface

This is very difficult to answer without knowing about your code. If you have existing code you should just use the type that's most natural to that if at all possible.

You can get a pointer from your memoryview with &memview[0,0], and access its attributes .shape and .strides to get information about how the data is stored. (If you make the memoryview contiguous then you know strides from shape so it's simpler). You then need to decided whether to copy the data, or just use a pointer to the Python-owned data (if C++ only keeps the data for the duration of the function call then using a pointer is good).

Similar considerations apply to the output data, but it's hard to know without knowing what you're trying to do in C++.