Using dis
to look at the bytecode generated for the two versions:
not ==
4 0 LOAD_FAST 0 (foo)
3 LOAD_FAST 1 (bar)
6 COMPARE_OP 2 (==)
9 UNARY_NOT
10 RETURN_VALUE
!=
4 0 LOAD_FAST 0 (foo)
3 LOAD_FAST 1 (bar)
6 COMPARE_OP 3 (!=)
9 RETURN_VALUE
The latter has fewer operations, and is therefore likely to be slightly more efficient.
It was pointed out in the commments (thanks, @Quincunx) that where you have if foo != bar
vs. if not foo == bar
the number of operations is exactly the same, it's just that the COMPARE_OP
changes and POP_JUMP_IF_TRUE
switches to POP_JUMP_IF_FALSE
:
not ==
:
2 0 LOAD_FAST 0 (foo)
3 LOAD_FAST 1 (bar)
6 COMPARE_OP 2 (==)
9 POP_JUMP_IF_TRUE 16
!=
2 0 LOAD_FAST 0 (foo)
3 LOAD_FAST 1 (bar)
6 COMPARE_OP 3 (!=)
9 POP_JUMP_IF_FALSE 16
In this case, unless there was a difference in the amount of work required for each comparison, it's unlikely you'd see any performance difference at all.
However, note that the two versions won't always be logically identical, as it will depend on the implementations of __eq__
and __ne__
for the objects in question. Per the data model documentation:
There are no implied relationships among the comparison operators. The
truth of x==y
does not imply that x!=y
is false.
For example:
>>> class Dummy(object):
def __eq__(self, other):
return True
def __ne__(self, other):
return True
>>> not Dummy() == Dummy()
False
>>> Dummy() != Dummy()
True
Finally, and perhaps most importantly: in general, where the two are logically identical, x != y
is much more readable than not x == y
.
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