In #586 and #595 we added support to bind Vector[Int64], Vector[Float32] and Vector[Float64] (as CocoIndex data types) to corresponding numpy array types like NDArray[numpy.int64], NDArray[numpy.float32] and NDArray[numpy.float64].

For consistency and composability, we want to support numpy type binding on scalar number level too. e.g.
Users should be able to use numpy.int64 for a field with Int64 type, etc.

Also see a related comment #595 (comment) for implementation hint:

BTW, actually I was thinking np_number_type should be a property for the element type, instead of the vector type. It should resolve information one level at a time, and it'll also allows us consistently support individual np.float32 types outside a vector - if we want to support it.

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