The default behavior of the object superclass is to create a dict for an object's attributes. This provides fast resolution of names. It means that an object can have attributes added and changed very freely. Because a hash is used to locate the attribute by name, the internal dict object can consume quite a bit of memory.

We can modify the behavior of the object superclass by providing a list of specific attribute names when we create a class. When we assign these names to the specially named __slots__ variable, these will be the only available attributes. A dict is not created, and memory use is reduced considerably.

If we're working with very large datasets, we might need to use a class that looks like this:

class SmallSample:
    counter= 0
    __slots__ = ["sequence", "measure"]
    def __init__(self, measure):
        SmallSample.counter += 1
        self.sequence = SmallSample.counter
        self.measure = measure

This class uses the __slots__ attribute...