On Nov 24, 5:44 am, Licheng Fang <[EMAIL PROTECTED]> wrote:
> Yes, millions. In my natural language processing tasks, I almost
> always need to define patterns, identify their occurrences in a huge
> data, and count them. [...] So I end up with unnecessary
> duplicates of keys. And this can be a great waste of memory with huge
> input data.
create a hash that maps your keys to themselves, then use the values
of that hash as your keys.
>>> store = {}
>>> def atom(str):
global store
if str not in store:
store[str] = str
return store[str]
>>> a='this is confusing'
>>> b='this is confusing'
>>> a == b
True
>>> a is b
False
>>> atom(a) is atom(b)
True
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