That is, two instances of class D that do not specify a value for x when creating a class instance will share the same copy of x. Because dataclasses just use normal Python class creation they also share this behavior. There is no general way for Data Classes to detect this condition. Python Objects and Classes. Python is an object oriented programming language. Unlike procedure oriented programming, where the main emphasis is on functions, object oriented programming stresses on objects. An object is simply a collection of data (variables) and methods (functions) that act on those data.
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.
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__:
Instead of writing new data members' methods, one can inherit the members of an existing class. This existing class is called the base class or superclass, and the new class is called the derived class or sub-class. Let's learn to do all these things in Python. Python 2; Python 3.
Without__slots__:
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.
On a sidenote, you might want to give PyPy a try. It does all of theseoptimizations by default.
Slot Machine In Python
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