In Tim Peter's answer to "Are there any reasons not to use an ordered dictionary", he says
OrderedDict is a subclass of dict.
It's not a lot slower, but at least doubles the memory over using a plain dict.
Now, while going through a particular question, I tried some sample checks using ipython and both of them contradict the earlier reasoning:
dict and OrderedDict are of same sizeOrderedDict takes easily around 7-8 times more time than operating on a dict (Hence a lot slower)Can someone explain to me where I'm going wrong in my reasoning?
import sys
import random
from collections import OrderedDict
test_dict = {}
test_ordered_dict = OrderedDict()
for key in range(10000):
    test_dict[key] = random.random()
    test_ordered_dict[key] = random.random()
sys.getsizeof(test_dict)
786712
sys.getsizeof(test_ordered_dict)
786712
%timeit:import sys
import random
from collections import OrderedDict
def operate_on_dict(r):
    test_dict = {}
    for key in range(r):
        test_dict[key] = random.random()
def operate_on_ordered_dict(r):
    test_ordered_dict = OrderedDict()
    for key in range(r):
        test_ordered_dict[key] = random.random()
%timeit for x in range(100): operate_on_ordered_dict(100)
100 loops, best of 3: 9.24 ms per loop
%timeit for x in range(100): operate_on_dict(100)
1000 loops, best of 3: 1.23 ms per loop
                I think the problem with size is due to the fact that there's no __sizeof__ method defined in Python 2.X implementation of OrderedDict, so it simply falls back to dict's __sizeof__ method.
To prove this here I've created a class A here which extends list and also added an additional method foo to check if that affects the size.
class A(list):
    def __getitem__(self, k):
        return list.__getitem__(self, k)
    def foo(self):
        print 'abcde'
>>> a = A(range(1000))
>>> b = list(range(1000))
But still same size is returned by sys.getsizeof:
>>> sys.getsizeof(a), sys.getsizeof(b)
(9120, 9120)
Of course A is going to be slow because its methods are running in Python while list's method will run in pure C.
>>> %%timeit
... for _ in xrange(1000):
...     a[_]
... 
1000 loops, best of 3: 449 µs per loop
>>> %%timeit
for _ in xrange(1000):
    b[_]
... 
10000 loops, best of 3: 52 µs per loop
And this seems to be fixed in Python 3 where there's a well defined __sizeof__ method now:
def __sizeof__(self):
    sizeof = _sys.getsizeof
    n = len(self) + 1                       # number of links including root
    size = sizeof(self.__dict__)            # instance dictionary
    size += sizeof(self.__map) * 2          # internal dict and inherited dict
    size += sizeof(self.__hardroot) * n     # link objects
    size += sizeof(self.__root) * n         # proxy objects
    return size
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