Random.sample was changed to work with sets and other non-
indexable iterables, but random.choice still requires that its 
argument be a full sequence.

Should that possibly be changed, so that for lists random.choice 
uses the current implementation, but for other iterables that 
random.sample supports, it could return random.sample(iterable, 
1)[0]?

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I would not like to see that accommodation extended to
random.choice().

In random.sample(), it was done to eliminate a surprising
assymetry  between the two internal algorithms.  Because one
used list(population) and the other used
population.__getitem__(), the first would work with any
iterable and the second demanded random access.  So, for
certain values of n, dictionaries would work find and for
other values they would  fail.  

This consideration does not apply to random.choice().  I
think most people have a mental model of how it works and
would be surprised to have an iterable input fully
manitested in memory.  Though, I do grant that it is also
surprising that it does not work with sets.  C'est le vie.

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An iterable input does not have to be fully manifested in memory for 
random.choice to work.

See the implementation at <http://www.pastebin.de/pastebin.py?
id=594>.

Is this to say that random.sample entirely manifests large iterables in 
memory?  I would say that this would be just as unexpected as 
random.choice doing so.  If it's not the case, then why can't 
random.choice do what it does now for proper sequences, but just 
dispatch to random.sample(iterable, 1)[0] in all other cases?

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Sorry, I don't think this is a good idea and do not want to
introduce 
O(n) behavior into an otherwise O(1) function.

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I agree with Raymond on this -- making random.choice() an O
(n) function in some cases would make it an attractive 
nuisance.  In the absence of an efficient implementation, it's 
regrettable that random.sample() decided to cater to sets.  
Doing more damage of the same kind would primarily be doing 
more damage.