Is `namedtuple` really as efficient in memory usage as tuples? My test says NO

Question

It is stated in the Python documentation that one of the advantages of namedtuple is that it is as memory-efficient as tuples.

To validate this, I used iPython with ipython_memory_usage. The test is shown in the images below:

The test shows that:

• 10000000 instances of namedtuple used about 850 MiB of RAM
• 10000000 tuple instances used around 73 MiB of RAM
• 10000000 dict instances used around 570 MiB of RAM

So namedtuple used much more memory than tuple! Even more than dict!!

What do you think? Where did I go wrong?

Answer 1

A simpler metric is to check the size of equivalent tuple and namedtuple objects. Given two roughly analogous objects:

from collections import namedtuple
import sys

point = namedtuple('point', 'x y z')
point1 = point(1, 2, 3)

point2 = (1, 2, 3)

Get the size of them in memory:

>>> sys.getsizeof(point1)
72

>>> sys.getsizeof(point2)
72

They look the same to me...

---

Taking this a step further to replicate your results, notice that if you create a list of identical tuples the way you're doing it, each tuple is the exact same object:

>>> test_list = [(1,2,3) for _ in range(10000000)]
>>> test_list[0] is test_list[-1]
True

So in your list of tuples, each index contains a reference the same object. There are not 10000000 tuples, there are 10000000 references to one tuple.

On the other hand, your list of namedtuple objects actually does create 10000000 unique objects.

A better apples-to-apples comparison would be to view the memory usage for

>>> test_list = [(i, i+1, i+2) for i in range(10000000)]

and:

>>> test_list_n = [point(x=i, y=i+1, z=i+2) for i in range(10000000)]

They have the same size:

>>> sys.getsizeof(test_list)
81528056

>>> sys.getsizeof(test_list_n)
81528056