Quick Python Tip: Use __slots__ to Reduce Class Memory Usage (2026)

Quick Python Tip: Use slots to Reduce Class Memory Usage

When working with large datasets or memory-constrained environments, optimizing class memory usage can be crucial. One often overlooked technique is utilizing the __slots__ attribute in Python classes. By declaring __slots__, you can significantly reduce the memory footprint of your objects.

Let's compare the memory usage of a regular class versus one using __slots__:

import sys

class RegularClass:
    def __init__(self, x, y):
        self.x = x
        self.y = y

class SlottedClass:
    __slots__ = ('x', 'y')
    def __init__(self, x, y):
        self.x = x
        self.y = y

regular_obj = RegularClass(1, 2)
slotted_obj = SlottedClass(1, 2)

print(sys.getsizeof(regular_obj))  # Output: 56 (varies by Python version)
print(sys.getsizeof(slotted_obj))  # Output: 40 (varies by Python version)

As shown, using __slots__ reduces the memory usage of the SlottedClass object by approximately 28% compared to the RegularClass object.

Takeaway: By leveraging __slots__ in your Python classes, you can minimize memory usage and improve performance, especially when dealing with large numbers of objects. Remember to use __slots__ when you have a fixed set of attributes and don't need dynamic attribute assignment.

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