Allow passing numpy array to PyDiGraph::extend_from_edge_list

[biswash47]

What is the expected enhancement?

Per current api, one way to extend an existing graph is to use the PyDiGraph::extend_from_edge_list. This method expects a list of tuples. The enhancement would be extend this method so that it accepts a numpy array. This could possibly improve performance if the underlying memory array is directly accessed.

This issue came up in a discussion about the performance of qiskit.transpiler.CouplingMap object initialization: Qiskit/qiskit#11919

[IvanIsCoding]

I think this should be an OK addition, but it will need to be a separate method.

We had issues with conversions from ndarray -> Rust types before and that is why we have from_complex_adjacency_matrix and from_adjacency_matrix. So let's try to avoid those and just create a new method. Upstream users will need to adapt.

[jakelishman]

Ivan: an alternative is to accept a Py<PyAny> in the slot and implement the conversion logic using the PyO3 traits manually (with a little bit of type checking). That's more complex from the implementation side, but potentially more convenient for users?

[IvanIsCoding]

Ivan: an alternative is to accept a Py<PyAny> in the slot and implement the conversion logic using the PyO3 traits manually (with a little bit of type checking). That's more complex from the implementation side, but potentially more convenient for users?

I think it is possible but I would like to keep the method straightforward. Nominally, I don't want to deal with two things:

• Handling people passing Python objects that are Sequence[tuple[int, int]] but are not lists. I do not want to accidentally cast that to NumPy
• Handling the different NumPy types. For even the slightest mismatch we get stuff like TypeError: argument 'matrix': type mismatch: from=uint8, to=float64 (this is like Add a method to make a graph from a complex matrix #411 but I called adjacency matrix with uint8 from NumPy)

So I'd rather implement a separate function and document well the specific ndarray format and type we want