Consider this snippet:
class SomeClass(object):
def __init__(self, someattribute="somevalue"):
self.someattribute = someattribute
def __eq__(self, other):
return self.someattribute == other.someattribute
def __ne__(self, other):
return not self.__eq__(other)
list_of_objects = [SomeClass()]
print(SomeClass() in list_of_objects)
set_of_objects = set([SomeClass()])
print(SomeClass() in set_of_objects)
which evaluates to:
True
False
Can anyone explain why the 'in' keyword has a different meaning for sets and lists? I would have expected both to return True, especially when the type being tested has equality methods defined.
In pretty much any hashtable implementation, including Python's, if you override the equality method you must override the hashing method (in Python, this is
__hash__
). Thein
operator for lists just checks equality with every element of the list, which thein
operator for sets first hashes the object you are looking for, checks for an object in that slot of the hashtable, and then checks for equality if there is anything in the slot. So, if you override__eq__
without overriding__hash__
, you cannot be guaranteed that thein
operator for sets will check in the right slot.The meaning is the same, but the implementation is different. Lists simply examine each object, checking for equality, so it works for your class. Sets first hash the objects, and if they don't implement hash properly, the set appears not to work.
Your class defines
__eq__
, but doesn't define__hash__
, and so won't work properly for sets or as keys of dictionaries. The rule for__eq__
and__hash__
is that two objects that__eq__
as True must also have equal hashes. By default, objects hash based on their memory address. So your two objects that are equal by your definition don't provide the same hash, so they break the rule about__eq__
and__hash__
.If you provide a
__hash__
implementation, it will work fine. For your sample code, it could be:Define
__hash__()
method that corresponds to your__eq__()
method. Example.