The point of xdress is to wrap code. The purpose of xdress is to generate idiomatic wrappers. This tutorial describes some awesome things that you can do with xdress.
When using stlwrap, the vector type actually creates custom numpy dtypes for the templated type. This works not only on primitive types, other STL containers (map, set, vector), but also on any custom type that the type system knows about! Say we have the following run control file, which is used to wrap a C++ class Joan:
xdressrc.py:
package = "france"
classes = [('Joan', 'france.cpp')]
stlcontainers = [('vector', 'Joan')]
The classes list, with the autodescribe and cythongen plugins, will create Python wrappers for he Joan class. The stlcontainers will then see that the vector template is dependent on Joan. This will create and register a dtype called xd_joan that you can use with ndarrays. You may then get and set elements out of this array via the wrapper class that was created with cythongen. For exmaple:
import numpy as np
from france.stlcontainer import xd_joan
x = np.zeros(10, dtype=xd_joan)
# A scalar array with dtype xd_joan
x[0]
# A Joan wrapper object with a copy of the 0th element of the array
x[0].item()
Note that the underlying memory is a contiguous block of Joans. The Python wrappers are regenerated on every getitem() call. Thus this is more truly an array of structs, as opposed to a structured array ;).
Note
This is only starting to be explored
The TypeSystem class has a mechanism to save and reload via dump() and load() methods. Furthermore, type system variables by the name ts in run control and side car files are all merged together with the default type system. This allows the users of xdress in project-beta to use the type system developed in project-alpha with out having to re-expose, re-register, or re-parse any project-alpha code at all!
This is an import-esque mechanism for acting on the type systems themselves. This should be a huge boon to mutlti-project systems. You can also choose to provide xdress type systems to down stream users and a convenience or favor to them. Only pickle and gzip pickle are currently supported, though others may be forthcoming.