Improving Python class efficiency with slots

If you're a Python developer, optimizing your code's memory usage and performance is crucial. One effective way is leveraging the __slots__ feature in your classes. This guide covers the advantages and a practical example.

What is __slots__?

Every object from a class has a dictionary that stores its attributes and values. It is flexible but can waste memory when you have many objects. __slots__ lets you declare which attributes a class can have, allocating a fixed amount of memory and skipping the per-instance dictionary.

A memory and performance change

By explicitly declaring attributes, __slots__ reduces overhead and speeds up attribute access. The result is a more efficient program.

Real-world application: the Point class

Without __slots__:

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

Profiling creation of a million points with memory_profiler:

Line #    Mem usage    Increment  Occurrences   Line Contents
=============================================================
 8    21.1 MiB    21.1 MiB           1   @profile()
 9    def create_points():
10   136.0 MiB   114.9 MiB     1000003   return [Point(1, 2, 3) for _ in range(1_000_000)]

With __slots__:

class SlottedPoint:
    __slots__ = ("x", "y", "z")
 
    def __init__(self, x, y, z):
        self.x = x
        self.y = y
        self.z = z

Profiling with __slots__:

Line #    Mem usage    Increment  Occurrences   Line Contents
=============================================================
 9    21.6 MiB    21.6 MiB           1   @profile()
10    def create_points():
11    90.5 MiB    68.9 MiB     1000003   return [Point(1, 2, 3) for _ in range(1_000_000)]

Using __slots__ lowered the required memory to ~47.3 MiB (an ~49% reduction). Note that __slots__ limits possible member variables: assigning new attributes beyond those declared raises AttributeError.

point = Point(1, 2, 3)
point.a = 4        # works
 
slotted_point = SlottedPoint(1, 2, 3)
slotted_point.a = 4  # AttributeError

Benefits of using __slots__

• Improved memory usage when you have many instances.
• Faster attribute access by skipping instance dictionaries.
• Enforced attribute names, reducing accidental clashes or typos.
• Clearer documentation of allowed attributes.

Conclusion

__slots__ is a practical tool to optimize memory and performance. Use it when you need many lightweight instances and want to balance readability with efficiency.