Sturla Molden brought up a point in an earlier thread ("Please help with
subclassing numpy.ndarray") that I think is worth highlighting. A "common"
approach to subclassing ndarray in python (http://www.scipy.org/Subclasses)
results in code that is not thread safe. This approach involves setting some
class level variables inside the __new__ method, and then retrieving those
values inside the __array_finalize__ method.
A simple work around that Sturla alluded to is to explictly set a lock inside
the __new__ method, and later release it in the __array_finalize__ method.
However, this would cause problems if someone invoked the __new__ method in
such a way that __array_finalize__ was not called afterwards (which I think is
possible, isn't it?).
The two subclasses of ndarray in the core numpy distribution (that I am aware
of) , chararray and matrix, don't run into this problem because they can get
all the relevant info they need by directly inspecting the ndarray that comes
out of the __new__ method, and so they don't need to share any extra info
between __new__ and __array_finalize__
So, I am wondering if perhaps one of the experts on this list would be able to
shed some light on a good way to create thread safe subclasses of ndarray.
Thanks,
- Matt Knox_______________________________________________
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