Optimizing Memory and Attribute Lookup in Python Classes with __slots__

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Published

2023-10-06

In Python, class attributes are usually stored in a dictionary called __dict__. This allows for dynamic addition of attributes but can be memory-inefficient. Python offers an alternative: the __slots__ attribute. By defining __slots__ in a class, you specify a fixed set of attributes, eliminating the need for a __dict__.

How it Works

  1. Default Storage: Normally, attributes are stored in a __dict__ dictionary for each instance.

    class Point:
    def __init__(self, x, y, z):
        self.x, self.y, self.z = x, y, z
p = Point(1, 2, 3)
print(p.__dict__)  # Output: {'x': 1, 'y': 2, 'z': 3}

  2. Using __slots__: To restrict attributes, define a __slots__ tuple in the class.

    class Point:
    __slots__ = ('x', 'y', 'z')
    def __init__(self, x, y, z):
        self.x, self.y, self.z = x, y, z
    • This prevents the addition of new attributes.
    • Eliminates the __dict__, thus saving memory.

Why Use __slots__

  • Memory Efficiency: Each instance uses a more efficient data structure instead of a dictionary.
  • Faster Attribute Lookup: Avoids the computational cost of dictionary key lookups.

Practical Example

In a program that processes a large file to create a million instances of a Point class, using __slots__ reduced memory usage from 271,660 bytes to 176,328 bytes.

When to Use

Use __slots__ when you have thousands of instances or require frequent attribute lookups. However, it restricts dynamic attribute addition, so use it judiciously.

References