Dictionary vs Object - which is more efficient and why?

Question

What is more efficient in Python in terms of memory usage and CPU consumption - Dictionary or Object?

Background: I have to load huge amount of data

Answer 1

There is yet another way to reduce memory usage if data structure isn't supposed to contain reference cycles.

Let's compare two classes:

class DataItem:
    __slots__ = ('name', 'age', 'address')
    def __init__(self, name, age, address):
        self.name = name
        self.age = age
        self.address = address

and

$ pip install recordclass

>>> from recordclass import structclass
>>> DataItem2 = structclass('DataItem', 'name age address')
>>> inst = DataItem('Mike', 10, 'Cherry Street 15')
>>> inst2 = DataItem2('Mike', 10, 'Cherry Street 15')
>>> print(inst2)
>>> print(sys.getsizeof(inst), sys.getsizeof(inst2))
DataItem(name='Mike', age=10, address='Cherry Street 15')
64 40

It became possible since structclass-based classes doesn't support cyclic garbage collection, which is not needed in such cases.

There is also one advantage over __slots__-based class: you are able to add extra attributes:

>>> DataItem3 = structclass('DataItem', 'name age address', usedict=True)
>>> inst3 = DataItem3('Mike', 10, 'Cherry Street 15')
>>> inst3.hobby = ['drawing', 'singing']
>>> print(inst3)
>>> print(sizeof(inst3), 'has dict:',  bool(inst3.__dict__))
DataItem(name='Mike', age=10, address='Cherry Street 15', **{'hobby': ['drawing', 'singing']})
48 has dict: True

Answer 2

Attribute access in an object uses dictionary access behind the scenes - so by using attribute access you are adding extra overhead. Plus in the object case, you are incurring additional overhead because of e.g. additional memory allocations and code execution (e.g. of the __init__ method).

In your code, if o is an Obj instance, o.attr is equivalent to o.__dict__['attr'] with a small amount of extra overhead.