In python, a value x
is not always constrained to equal itself. Perhaps the best known example is NaN
:
>>> x = float("NaN")
>>> x == x
False
Now consider a list of exactly one item. We might consider two such lists to be equal if and only the items they contained were equal. For example:
>>> ["hello"] == ["hello"]
True
But this does not appear to be the case with NaN
:
>>> x = float("NaN")
>>> x == x
False
>>> [x] == [x]
True
So these lists of items that are "not equal", are "equal". But only sometimes ... in particular:
NaN
are considered equal; while NaN
are not equalObserve:
>>> x = float("NaN")
>>> [x] == [x]
True
>>> [x] == [float("NaN")]
False
This general behaviour also applies to other collection types such as tuples and sets. Is there a good rationale for this?
Per the docs,
In enforcing reflexivity of elements, the comparison of collections assumes that for a collection element x, x == x is always true. Based on that assumption, element identity is compared first, and element comparison is performed only for distinct elements. This approach yields the same result as a strict element comparison would, if the compared elements are reflexive. For non-reflexive elements, the result is different than for strict element comparison, and may be surprising: The non-reflexive not-a-number values for example result in the following comparison behavior when used in a list:
>>> nan = float('NaN') >>> nan is nan True >>> nan == nan False <-- the defined non-reflexive behavior of NaN >>> [nan] == [nan] True <-- list enforces reflexivity and tests identity first
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