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Regarding benchmarks: It's difficult to come up with decent benchmarks
for things like this. A possible strategy is to use an instrumented
interpreter that records which Unicode objects are created and when they
are deleted. If you then run this instrumented interpreter against a few
larger applications such as Zope for a while, you'll get a data set that
can be used as input for a more real-life like benchmark. I've done this
in the past for Python byte codes to see which are used how often -
based on such data you can create optimizations that have a real-life
effect.
Regarding the lazy slice patches: those were not using subclassing, they
were patches to the existing type implementations. With subclassing you
don't affect all uses of an object, but instead let the user control
which uses should take advantage of the slice operations. Since the user
also controls the objects which are kept alive this way, the main
argument against Unicode slice objects goes away. This is different than
patching the type itself and doesn't change the main object
implementation in any way. Furthermore, it's possible to implement and
provide such subclasses outside the Python core, which gives developers
a lot more freedom.
Regarding discussions on the py3k list: I'm not on that list, since I
already get more email than I can manage. I am on the python-dev list,
if you want to take up the discussions there.