在Python中，__slots__通過限制實例屬性並優(yōu)化內(nèi)存使用來提升性能。它阻止動態(tài)字典__dict__的創(chuàng)建，改用更緊湊的內(nèi)存結(jié)構(gòu)存儲屬性，減少大量實例的內(nèi)存開銷，並加快屬性訪問速度，適用於需創(chuàng)建大量對象、屬性已知且需封裝的場景。但其限制包括無法動態(tài)添加屬性（除非顯式包含__dict__）、多重繼承複雜化及調(diào)試困難，因此應(yīng)在關(guān)注性能和內(nèi)存效率時使用。

In Python, the __slots__ attribute allows you to explicitly declare which instance variables a class is allowed to have. This does more than just restrict what attributes can be added—it also optimizes memory usage and improves performance, especially when creating many instances of a class.

Reducing Memory Overhead

By default, each Python object has a dynamic dictionary ( __dict__ ) that stores its attributes. While this makes Python flexible, it comes with memory overhead—especially when you're creating thousands or millions of instances.

When you define __slots__ , Python doesn't create a __dict__ for each instance. Instead, it uses a more compact internal structure to store the attributes, often as pointers to fixed positions in memory.

For example:

 class Point:
    __slots__ = ('x', 'y')

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

Each Point instance no longer carries around a full dictionary. If you're creating millions of points (like in simulations or graphics applications), this can significantly reduce memory usage.

Improving Access Speed

Accessing attributes defined in __slots__ is generally faster than accessing those stored in a __dict__ . That's because slot-based access skips the hash table lookup that dictionaries require. It becomes noticeable when you're doing heavy computations or tight loops involving many object accesses.

Here are a few scenarios where using __slots__ makes sense:

• You're creating a large number of objects.
• You know all the attributes upfront and don't need dynamic assignment.
• You want to enforce encapsulation by preventing accidental addition of new attributes.

Caveats and Limitations

Using __slots__ isn't always the best choice. There are some trade-offs:

• Once you define __slots__ , you can't dynamically add new attributes to instances unless you explicitly include '__dict__' in the slots list.
• Multiple inheritance can get tricky if parent classes also use __slots__ .
• Debugging or monkey-patching becomes harder since you can't easily attach temporary attributes.

So while __slots__ helps optimize memory and speed, it's not something you should apply everywhere automatically.

Basically, it's useful when you care about performance and memory efficiency in object-heavy code—but otherwise, it's safe to skip unless you're optimizing for scale.

And that's how __slots__ works under the hood.

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