[Numpy-discussion] OpenOpt Suite release 0.45

[Matthieu Brucher]

Even if they have different hashes, they can be stored in the same
underlying list before they are retrieved. Then, an actual comparison is
done to check if the given key (i.e. object instance, not hash) is the same
as one of the stored keys.


2013/3/16 Dmitrey <tmp50 at ukr.net>

>
>
> --- Исходное сообщение ---
> От кого: "Matthieu Brucher" <matthieu.brucher at gmail.com>
> Дата: 16 марта 2013, 11:33:39
>
> Hi,
>
> Different objects can have the same hash, so it compares to find the
> actual correct object.
> Usually when you store something in a dict and later you can't find it
> anymore, it is that the internal state changed and that the hash is not the
> same anymore.
>
>
> my objects (oofuns) definitely have different __hash__() results - it's
> just integers 1,2,3 etc assigned to the oofuns (stored in oofun._id field)
> when they are created.
>
>
> D.
>
>
>
> Matthieu
>
>
> 2013/3/16 Dmitrey <tmp50 at ukr.net>
>
>
>
> --- Исходное сообщение ---
> От кого: "Alan G Isaac" <alan.isaac at gmail.com>
> Дата: 15 марта 2013, 22:54:21
>
> On 3/15/2013 3:34 PM, Dmitrey wrote:
> > the suspected bugs are not documented yet
>
>
> I'm going to guess that the state of the F_i changes
> when you use them as keys (i.e., when you call __le__.
>
> no, their state doesn't change for operations like __le__ . AFAIK
> searching Python dict doesn't calls __le__ on the object keys at all, it
> operates with method .__hash__(), and latter returns fixed integer numbers
> assigned to the objects earlier (at least in my case).
>
>
>  It is very hard to imagine that this is a Python or NumPy bug.
>
> Cheers,
> Alan
>
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