Python Slots Vs Data Class
An inner class or nested class is a defined entirely within the body of another class. If an object is created using a class, the object inside the root class can be used. A class can have more than one inner classes, but in general inner classes are avoided. Related Course: Python Programming Bootcamp: Go from zero to hero. Inner class example. The strategy for handling multi-class classification can be set via the “multiclass” argument and can be set to “ovr” for the one-vs-rest strategy. The complete example of fitting a logistic regression model for multi-class classification using the built-in one-vs-rest strategy is listed below. Python has been an object-oriented language since the time it existed. Due to this, creating and using classes and objects are downright easy. This chapter helps you become an expert in using Python's object-oriented programming support. If you do not have any previous experience with object. As noted already in the answers, data classes from dataclasses cannot generate slots for the simple reason that slots must be defined before a class is created. In fact, the PEP for data classes explicitly mentions this: At least for the initial release, slots will not be supported. slots needs to be added at class creation time.
In Python every class can have instance attributes. By default Pythonuses a dict to store an object’s instance attributes. This is reallyhelpful as it allows setting arbitrary new attributes at runtime.
Python Slots Vs Data Classification
However, for small classes with known attributes it might be abottleneck. The dict wastes a lot of RAM. Python can’t just allocatea static amount of memory at object creation to store all theattributes. Therefore it sucks a lot of RAM if you create a lot ofobjects (I am talking in thousands and millions). Still there is a wayto circumvent this issue. It involves the usage of __slots__ totell Python not to use a dict, and only allocate space for a fixed setof attributes. Here is an example with and without __slots__:
Without__slots__:
Python Slots Vs Data Classifications
With__slots__:
The second piece of code will reduce the burden on your RAM. Some peoplehave seen almost 40 to 50% reduction in RAM usage by using thistechnique.
Python Slots Vs Data Classic
On a sidenote, you might want to give PyPy a try. It does all of theseoptimizations by default.
Python Slots Vs Data Classes
Below you can see an example showing exact memory usage with and without __slots__ done in IPython thanks to https://github.com/ianozsvald/ipython_memory_usage