Question

I have a large number of objects I need to store in memory for processing in Python. Specifically, I’m trying to remove duplicates from a large set of objects. I want to consider two objects “equal” if a certain instance variable in the object is equal. So, I assumed the easiest way to do this would be to insert all my objects into a set, and override the __hash__ method so that it hashes the instance variable I’m concerned with.

So, as a test I tried the following:

class Person:
    def __init__(self, n, a):
        self.name = n
        self.age = a

    def __hash__(self):
        return hash(self.name)

    def __str__(self):
        return "{0}:{1}".format(self.name, self.age)

myset = set()
myset.add(Person("foo", 10))
myset.add(Person("bar", 20))
myset.add(Person("baz", 30))
myset.add(Person("foo", 1000)) # try adding a duplicate

for p in myset: print(p)

Here, I define a Person class, and any two instances of Person with the same name variable are to be equal, regardless of the value of any other instance variable. Unfortunately, this outputs:

baz:30
foo:10
bar:20
foo:1000

Note that foo appears twice, so this program failed to notice duplicates. Yet the expression hash(Person("foo", 10)) == hash(Person("foo", 1000)) is True. So why doesn’t this properly detect duplicate Person objects?

Answer 1

You forgot to also define __eq__().

If a class does not define a __cmp__() or __eq__() method it should not define a __hash__() operation either; if it defines __cmp__() or __eq__() but not __hash__(), its instances will not be usable in hashed collections. If a class defines mutable objects and implements a __cmp__() or __eq__() method, it should not implement __hash__(), since hashable collection implementations require that a object’s hash value is immutable (if the object’s hash value changes, it will be in the wrong hash bucket).