Python 3 Deep — Dive Part 4 Oop High Quality

Python 3: Deep Dive (Part 4 - OOP) course by Fred Baptiste is widely considered one of the highest-quality, most comprehensive resources for advanced Python developers on . It holds a near-perfect rating of

10. Performance considerations

• Attribute access: instance attribute lookup is fast but repeated attribute accesses in hot code paths can be optimized by local variable binding.
• slots can reduce memory usage and speed attribute access for large numbers of instances by avoiding per-instance dicts; trade-offs: less dynamic attribute assignment and awkward subclassing unless slots combined carefully.
• Avoid excessive use of dynamic features (heavy use of getattr, getattribute, or metaclasses) in performance-critical loops.
• For numeric/array-heavy workloads, delegate to specialized libraries (NumPy) rather than trying to optimize Python-level objects.

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class Point:
    def __init__(self, x, y):
        self.x = x
        self.y = y
# Each instance has a __dict__ (~72 bytes overhead + per attr)