Fully-transparent exposure of Eigen::Vector/Matrix types using pybind11 - pybind11

Question

I have a simple class definition:
class State {
private:
Eigen::Vector3f m_data;
public:
State(const Eigen::Vector3f& state) : m_data(state) { }
Eigen::Vector3f get() const { return m_data; }
void set(const Eigen::Vector3f& _state) { m_data = _state; }
std::string repr() const {
return "state data: [x=" + std::to_string(m_data[0]) + ", y=" + std::to_string(m_data[1]) + ", theta=" + std::to_string(m_data[2]) + "]";
}
};
I then expose the above in python with pybind11:
namespace py = pybind11;
PYBIND11_MODULE(bound_state, m) {
m.doc() = "python bindings for State";
py::class_<State>(m, "State")
.def(py::init<Eigen::Vector3f>())
.def("get", &_State::get)
.def("set", &_State::set)
.def("__repr__", &_State::repr);
}
And everything works fine; I am able to import this module into python and construct a State instance with a numpy array. This isn't exactly what I want though. I want to be able to access this object as if it were a numpy array; I want to be able to do something like the following in python:
import bound_state as bs
arr = np.array([1, 2, 3])
a = bs.State(arr)
print(a[0])
(the above throws a TypeError: 'bound_state.State' object does not support indexing)
In the past, I've used boost::python to expose lists by using add_property and this allowed indexing of the underlying data in C++. does pybind11 have something similar that can work with Eigen? Could someone provide an example showing how to expose a State instance that is indexable?

Answer 1

Per the API Docs, this can be done easily with the def_property method.
Turn this bit:
namespace py = pybind11;
PYBIND11_MODULE(bound_state, m) {
m.doc() = "python bindings for State";
py::class_<State>(m, "State")
.def(py::init<Eigen::Vector3f>())
.def("get", &State::get)
.def("set", &State::set)
.def("__repr__", &State::repr);
}
Into this:
namespace py = pybind11;
PYBIND11_MODULE(bound_state, m) {
m.doc() = "python bindings for State";
py::class_<State>(m, "State")
.def(py::init<Eigen::Vector3f>())
.def_property("m_data", &State::get, &State::set)
.def("__repr__", &State::repr);
}
Now, from the python-side, I can do:
import bound_state as bs
arr = np.array([1, 2, 3])
a = bs.State(arr)
print(a.m_data[0])
This is not exactly what I want, but is a step in the right direction.