> A simple way to do this would be to push objects whose > refcounts had reached 0 onto a list instead of finalizing them > immediately, and have PyEval_EvalFrameEx periodically swap > in a new to-delete list and delete the objects on the old one. Some of the memory management threads discussed something similar to this, and pointed to IBM papers on Java. By adding states like "tenatively finalizable", the cost of using multiple processors was reduced. The down side is that objects which could be released (and recycled) immediately won't be -- which slows down a fair number of real-world programs that are used to the CPython refcount model. If the resource not being immediately released is scarce (such as file handles), it gets even worse. -jJ
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