[Python-Dev] PyObject_RichCompareBool identity shortcut (original) (raw)

Glenn Linderman v+python at g.nevcal.com
Thu Apr 28 00:26:15 CEST 2011

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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