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Quick Python Tip: Use __slots__ to Reduce Class Memory Usage

#python #performance #tutorial #programming

Quick Python Tip: Use slots to Reduce Class Memory Usage

When working with large datasets or memory-intensive applications, optimizing memory usage is crucial. One often overlooked technique in Python is using the __slots__ attribute to reduce class memory usage.

Let's compare the memory usage of a regular class versus one using __slots__. We'll create two simple classes: RegularClass and SlottedClass.

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(f"RegularClass size: {sys.getsizeof(regular_obj)} bytes")
print(f"SlottedClass size: {sys.getsizeof(slotted_obj)} bytes")
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Running this code will show that SlottedClass uses significantly less memory than RegularClass. This is because __slots__ prevents the creation of a __dict__ attribute, which stores an object's attributes as key-value pairs, resulting in reduced memory usage.

Takeaway: Use __slots__ when you have classes with a fixed set of attributes to reduce memory usage and improve performance. This is especially useful when working with large datasets or applications where memory efficiency is critical.

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