Ah, the VTK Python wrappers… my favorite little programming project when there are other things that I should be doing instead. My goal for the Python wrappers is to make it possible to do anything with VTK that can be done in C++, also doable in Python. And bit-by-bit, I think that I'm getting there.

My most recent mini-project was to wrap the C++ "[ ]" operator in python. Not too difficult, because last year I had already enhanced vtkParse so that it pulls all operator methods from the C++ header files. One thing that I don't like about how I did it, is that the range checking (i.e. to make sure that a bad index does not crash the program) uses a hard-coded range. There is no mechanism in VTK to add a hint to the header files so that the wrappers know what the valid index range for the "[ ]" operator is. Eventually, there will be… but that is a battle for another day.

There is another wrapping project that I've been working on, one that is slightly more ambitions: wrapping templated VTK classes. Templates are also something that I added to vtkParse last year, but hadn't added to the wrappers. Without going into the details of the implementation, the idea is that in Python, a template class like vtkVector<float,3> will be specialized and instantiated like so:

v = vtkVector['f',3]()

where 'f' is the Python type character for 'float'. So more or less, the syntax is very similar to C++ except that square brackets are used instead of angle brackets. Of course the trick is that, unlike C++, new template specializations cannot be created on-the-fly… only the template specializations that are wrapped are available. So what I'm working on is a method to figure out what template specializations will be needed so that they can be wrapped ahead of time. This can be done by looking at how templated types are used within VTK, i.e. looking at where the templated types appear either as method arguments or as superclass types of other classes.