Python – Can Python’s list comprehensions (ideally) do the equivalent of ‘count(*)…group by…’ in SQL

I think list comprehensions may give me this, but I'm not sure: any elegant solutions in Python (2.6) in general for selecting unique objects in a list and providing a count?

(I've defined an __eq__ to define uniqueness on my object definition).

So in RDBMS-land, something like this:

CREATE TABLE x(n NUMBER(1));
INSERT INTO x VALUES(1);
INSERT INTO x VALUES(1);
INSERT INTO x VALUES(1);
INSERT INTO x VALUES(2);

SELECT COUNT(*), n FROM x
GROUP BY n;

Which gives:

COUNT(*) n
==========
3        1
1        2

So , here's my equivalent list in Python:

[1,1,1,2]

And I want the same output as the SQL SELECT gives above.

EDIT: The example I gave here was simplified, I'm actually processing lists of user-defined object-instances: just for completeness I include the extra code I needed to get the whole thing to work:

import hashlib

def __hash__(self):
    md5=hashlib.md5()
    [md5.update(i) for i in self.my_list_of_stuff]
    return int(md5.hexdigest(),16)

The __hash__ method was needed to get the set conversion to work (I opted for the list-comprehension idea that works in 2.6 [despite the fact that I learnt that involves an inefficiency (see comments) – my data set is small enough for that not be an issue]). my_list_of_stuff above is a list of (Strings) on my object definition.