What's a correct and good way to implement __hash__()?
What's a correct and good way to implement __hash__()
?
I am talking about the function that returns a hashcode that is then used to insert objects into hashtables aka dictionaries.
As __hash__()
returns an integer and is used for "binning" objects into hashtables I assume that the values of the returned integer should be uniformly distributed for common data (to minimize collisions).
What's a good practice to get such values? Are collisions a problem?
In my case I have a small class which acts as a container class holding some ints, some floats and a string.
An easy, correct way to implement __hash__()
is to use a key tuple. It won't be as fast as a specialized hash, but if you need that then you should probably implement the type in C.
Here's an example of using a key for hash and equality:
class A:
def __key(self):
return (self.attr_a, self.attr_b, self.attr_c)
def __hash__(self):
return hash(self.__key())
def __eq__(self, other):
if isinstance(other, A):
return self.__key() == other.__key()
return NotImplemented
Also, the documentation of __hash__
has more information, that may be valuable in some particular circumstances.
John Millikin proposed a solution similar to this:
class A(object):
def __init__(self, a, b, c):
self._a = a
self._b = b
self._c = c
def __eq__(self, othr):
return (isinstance(othr, type(self))
and (self._a, self._b, self._c) ==
(othr._a, othr._b, othr._c))
def __hash__(self):
return hash((self._a, self._b, self._c))
The problem with this solution is that the hash(A(a, b, c)) == hash((a, b, c))
. In other words, the hash collides with that of the tuple of its key members. Maybe this does not matter very often in practice?
Update: the Python docs now recommend to use a tuple as in the example above. Note that the documentation states
The only required property is that objects which compare equal have the same hash value
Note that the opposite is not true. Objects which do not compare equal may have the same hash value. Such a hash collision will not cause one object to replace another when used as a dict key or set element as long as the objects do not also compare equal.
Outdated/bad solution
The Python documentation on , which gives us this:__hash__
suggests to combine the hashes of the sub-components using something like XOR
class B(object):
def __init__(self, a, b, c):
self._a = a
self._b = b
self._c = c
def __eq__(self, othr):
if isinstance(othr, type(self)):
return ((self._a, self._b, self._c) ==
(othr._a, othr._b, othr._c))
return NotImplemented
def __hash__(self):
return (hash(self._a) ^ hash(self._b) ^ hash(self._c) ^
hash((self._a, self._b, self._c)))
Update: as Blckknght points out, changing the order of a, b, and c could cause problems. I added an additional ^ hash((self._a, self._b, self._c))
to capture the order of the values being hashed. This final ^ hash(...)
can be removed if the values being combined cannot be rearranged (for example, if they have different types and therefore the value of _a
will never be assigned to _b
or _c
, etc.).
Paul Larson of Microsoft Research studied a wide variety of hash functions. He told me that
for c in some_string:
hash = 101 * hash + ord(c)
worked surprisingly well for a wide variety of strings. I've found that similar polynomial techniques work well for computing a hash of disparate subfields.