Marc-Andre Lemburg added the comment: I don't really see the connection with #1629305.
An optimization that would be worth checking is hooking up the Py_UNICODE pointer to interned Unicode objects if the contents match (e.g. do a quick check based on the hash value and then a memcmp). That would save memory and the call to the pymalloc allocator. Another strategy could involve a priority queue style cache with the aim of identifying often used Unicode strings and then reusing them. This could also be enhanced using an offline approach: you first run an application with an instrumented Python interpreter to find the most often used strings and then pre-fill the cache or interned dictionary on the production Python interpreter at startup time. Coming from a completely different angle, you could also use the Py_UNICODE pointer to share slices of a larger data buffer. A Unicode sub-type could handle this case, keeping a PyObject* reference to the larger buffer, so that it doesn't get garbage collected before the Unicode slice. Regarding memory constrained environments: these should simply switch off all free lists and pymalloc. OTOH, even mobile phones come with gigabytes of RAM nowadays, so it's not really worth the trouble, IMHO. __________________________________ Tracker <[EMAIL PROTECTED]> <http://bugs.python.org/issue1943> __________________________________ _______________________________________________ Python-bugs-list mailing list Unsubscribe: http://mail.python.org/mailman/options/python-bugs-list/archive%40mail-archive.com
