[Numpy-discussion] A change with minor compatibility questions

[Travis Oliphant]

On Oct 17, 2012, at 12:48 PM, Dag Sverre Seljebotn wrote:

> On 10/17/2012 06:56 PM, Dag Sverre Seljebotn wrote:
>> On 10/17/2012 05:22 PM, Travis Oliphant wrote:
>>> Hey all,
>>> 
>>> https://github.com/numpy/numpy/pull/482
>>> 
>>> is  a pull request that changes the hash function for numpy void
>>> scalars.   These are the objects returned from fully indexing a
>>> structured array:  array[i] if array is a 1-d structured array.
>>> 
>>> Currently their hash function just hashes the pointer to the underlying
>>> data.    This means that void scalars can be used as keys in a
>>> dictionary but the behavior is non-intuitive because another void scalar
>>> with the same data but pointing to a different region of memory will
>>> hash differently.
>>> 
>>> The pull request makes it so that two void scalars with the same data
>>> will hash to the same value (using the same algorithm as a tuple hash).
>>>     This pull request also only allows read-only scalars to be hashed.
>>> 
>>> There is a small chance this will break someone's code if they relied on
>>> this behavior.  I don't believe anyone is currently relying on this
>>> behavior -- but I've been proven wrong before.   What do people on this
>>> list think?
>> 
>> I support working on fixing this, but if I understand your fix correctly
>> this change just breaks things in a different way.
>> 
>> Specifically, in this example:
>> 
>> arr = np.ones(4, dtype=[('a', np.int64)])
>> x = arr[0]
>> d = { x : 'value' }
>> arr[0]['a'] = 4
>> print d[x]
>> 
>> Does the last line raise a KeyError? If I understand correctly it does.
> 
> Argh. I overlooked both Travis' second commit, and the explicit mention 
> of read-only above.
> 
> Isn't it possible to produce a read-only array from a writeable one 
> though, and so get a read-only scalar whose underlying value can still 
> change?

Yes, it is possible to do that (just like it is currently possible to change a tuple with a C-extension or even Cython or a string with NumPy). 

We won't be able to prevent people from writing code that will have odd behavior, but we can communicate correctly about what one should do. 

-Travis



> 
> Anyway, sorry about being so quick to post.
> 
> Dag Sverre
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