In article <mailman.2426.1265976954.28905.python-l...@python.org>,
Tim Chase <python.l...@tim.thechases.com> wrote:
>Aahz wrote:
>> Tim Chase <python.l...@tim.thechases.com> wrote:
>>>
>>> Just to add to the mix, I'd put the "anydbm" module on the gradient
>>> between "using a file" and "using sqlite". It's a nice intermediate
>>> step between rolling your own file formats for data on disk, and having
>>> to write SQL since access is entirely like you'd do with a regular
>>> Python dictionary.
>>
>> Not quite. One critical difference between dbm and dicts is the need to
>> remember to "save" changes by setting the key's valud again.
>
>Could you give an example of this? I'm not sure I understand
>what you're saying. I've used anydbm a bunch of times and other
>than wrapping access in
>
> d = anydbm.open(DB_NAME, "c")
> # use d as a dict here
> d.close()
>
>and I've never hit any "need to remember to save changes by
>setting the key's value again". The only gotcha I've hit is the
>anydbm requirement that all keys/values be strings. Slightly
>annoying at times, but my most frequent use case.
Well, you're more likely to hit this by wrapping dbm with shelve (because
it's a little more obvious when you're using pickle directly), but
consider this:
d = anydbm.open(DB_NAME, "c")
x = MyClass()
d['foo'] = x
x.bar = 123
Your dbm does NOT have the change to x.bar recorded, you must do this
again:
d['foo'] = x
With a dict, you have Python's reference semantics.
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Aahz (a...@pythoncraft.com) <*> http://www.pythoncraft.com/
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refer to comments in code as 'lies'. :-)"
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