multi-Singleton-like using __new__

[Gabriel Genellina]

En Fri, 08 Feb 2008 22:04:26 -0200, Matt Nordhoff  
<mnordhoff at mattnordhoff.com> escribió:

> J Peyret wrote:
>> - Same with using try/except KeyError instead of in cls.cache.
>> Has_key might be better if you insist on look-before-you-leap, because
>> 'in cls.cache' probably expends to uri in cls.cache.keys(), which can
>> be rather bad for perfs if the cache is very big.  i.e. dict lookups
>> are faster than scanning long lists.
>
> Not true. 'in' is (marginally) faster than has_key. It's also been
> preferred to has_key for a while now.

I don't understand your assertion, given your own timings below. I'd say  
that `has_key` is about 50% slower than `in`, not "marginally"

> $ python -m timeit -s "d = dict.fromkeys(xrange(5))" "4 in d"
> 1000000 loops, best of 3: 0.233 usec per loop
> $ python -m timeit -s "d = dict.fromkeys(xrange(5))" "d.has_key(4)"
> 1000000 loops, best of 3: 0.321 usec per loop
> $ python -m timeit -s "d = dict.fromkeys(xrange(500000))" "499999 in d"
> 1000000 loops, best of 3: 0.253 usec per loop
> $ python -m timeit -s "d = dict.fromkeys(xrange(500000))"
> "d.has_key(499999)"
> 1000000 loops, best of 3: 0.391 usec per loop
> $ python -m timeit -s "d = dict.fromkeys(xrange(500000))" "1000000 in d"
> 1000000 loops, best of 3: 0.208 usec per loop
> $ python -m timeit -s "d = dict.fromkeys(xrange(500000))"
> "d.has_key(1000000)"
> 1000000 loops, best of 3: 0.324 usec per loop

-- 
Gabriel Genellina