Understanding Python Slots

How about explicitly declaring class attributes or reducing memory footprint of class variables. Slots seems to be an answer.

slots (__slots__) a special class variable that is assigned a sequence of strings that are variable names used by instance.

Example:

class Car:
    __slots__ = ("brand_name", )

    def __init__(self):
        self.brand_name = "kia"


c = Car()
print(c.brand_name)

```
kia
```

The __slot__ declaration allows us to explicitly declare data members, which helps python to explicitly reserve space for them in memory and prevents the creation of __dict__ and __weakref__ attributes.

It also prevents the creation of any variables that aren’t declared in the __slots__ , doing so will result in AttributeError

c.price=1000

Traceback (most recent call last):
  File "C:\Users\cosmi\PycharmProjects\python-mastery\my_solutions\test.py", line 32, in <module>
    b.price = 1000
    ^^^^^^^
AttributeError: 'Car' object has no attribute 'price' and no __dict__ for setting new attributes

It also more efficient in terms of memory and speed.

Let’s compare the memory usage of a normal class and and __slot__ class.

class Car:
    """
    Regular classes use a __dict__ for attributes
    """
    def __init__(self):
        self.brand_name = "hyundai"


class ECar:
    __slots__ = ("brand_name", )  # this will prevent declaration of new slots

    def __init__(self):
        self.brand_name = "kia"


if __name__ == "__main__":
    import tracemalloc

    tracemalloc.start()

    a = Car()
    # a.price = 1000
    print("current memory: {} \n peak memory: {}".format(*tracemalloc.get_traced_memory()))

    tracemalloc.stop()

    del a

    tracemalloc.start(10)

    b = ECar()
    # b.price = 1000

    print("current memory: {} \n peak memory: {}".format(*tracemalloc.get_traced_memory()))

current memory: 400 
 peak memory: 400
current memory: 112 
 peak memory: 112

As we can see it’s uses almost 4x less memory, my example is sort of insignificant from real life perspective, but hope you got the idea.

Conclusion: __slots__ are simple efficient and safe approach to python’s default attribute access.