[Python-Dev] PyObject_RichCompareBool identity shortcut

[Glenn Linderman]

On 4/27/2011 2:15 PM, Mark Dickinson wrote:
> On Wed, Apr 27, 2011 at 7:41 PM, Glenn Linderman<v+python at g.nevcal.com>  wrote:
>> One issue that I don't fully understand: I know there is only one instance
>> of None in Python, but I'm not sure where to discover whether there is only
>> a single, or whether there can be multiple, instances of NaN or Inf.  The
>> IEEE 754 spec is clear that there are multiple bit sequences that can be
>> used to represent these, so I would hope that there can be, in fact, more
>> than one value containing NaN (and Inf).
>>
>> This would properly imply that a collection should correctly handle the case
>> of storing multiple, different items using different NaN (and Inf)
>> instances.  A dict, for example, should be able to hold hundreds of items
>> with the index value of NaN.
>>
>> The distinction between "is" and "==" would permit proper operation, and I
>> believe that Python's "rebinding" of names to values rather than the copying
>> of values to variables makes such a distinction possible to use in a correct
>> manner.
> For infinities, there's no issue:  there are exactly two distinct
> infinities (+inf and -inf), and they don't have any special properties
> that affect membership tests.   Your float-keyed dict can contain both
> +inf and -inf keys, or just one, or neither, in exactly the same way
> that it can contain both +5.0 and -5.0 as keys, or just one, or
> neither.
>
> For nans, you *can* put multiple nans into a dictionary as separate
> keys, but under the current rules the test for 'sameness' of two nan
> keys becomes a test of object identity, not of bitwise equality.
> Python takes no notice of the sign bits and 'payload' bits of a float
> nan, except in operations like struct.pack and struct.unpack.  For
> example:
Thanks, Mark, for the succinct description and demonstration.  Yes, only 
two Inf values, many possible NaNs.  And this is what I would expect.

I would not, however expect the original case that was described:
 >>> nan = float('nan')
 >>> nan == nan
False
 >>> [nan] == [nan]
True                  # also True in tuples, dicts, etc.

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