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iterating through humongously large key lists!!

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[Mark blobby Robinson]> I needed a non-destructive method so popitem was not a viable option> ...[Alex Martelli]> In many cases it should not be a problem to 'restore' into _another_> dictionary.  Or do you have many references to the starting dict> which it would be a problem to update...?  Then you can do the> same trick again -- sure, it's gonna be slower, but...>> The general idea would be:>> newdic = {}> while len(oldict):>     key, value = oldict.popitem()>     process(key, value)>     newdic[key] = value>> and now in newdic you have all you earlier had in oldict, and may> pour it back if need be.  Of course, not thread-safe, not fastest, &c,> but still it may be useful.Well, if he was concerned about the memory burden of materializing the fulllist of keys before, *this* one is gonna kill him:  the memory consumed byoldict does not decrease during this loop, so in the end you have two dictsof the original size, and dicts consume about 4-5x the memory of a list withthe same # of entries.BTW, I'm describing an accident of the implementation here, not an inherentfeature of dicts, so this may change:  under all implementations of Pythondicts to date, a dict never resizes except possibly in response to__setitem__.  You can *delete* things from a dict until the sun goes nova (orWin95 crashes, whichever comes first <wink>), but the dict won't shrinkinternally before you starting adding keys to it again.  This is partlyintentional, (a) to avoid pointless thrashing for ping-pong dicts, and (b) tominimize the number of cycles burned checking *whether* to resize.A curious fact under 2.0 and earlier is that a dict can resize even whenmerely replacing the value for a key that already exists.  We stopped that in2.1, though.pragmatically y'rs  - tim

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