Say I'm doing what you describe, operating on the same data with different functions, if written properly couldn't a program do this even without a class structure to it? 🤔

Yeah thats kinda where the first object oriented programming came from. In C (which doesn’t have classes) you define a struct (an arrangement of data in memory, kinda like a named tuple in Python), and then you write functions to manipulate those structs.

For example, multiplying two complex vectors might look like:

ComplexVectorMultiply(myVectorA, myVectorB, &myOutputVector, length);

Programmers decided it would be a lot more readable if you could write code that looked like:

myOutputVector = myVectorA.multiply(myVectorB);

Or even just;

myOutputVector = myVectorA * myVectorB;

(This last iteration is an example of “operator overloading”).

So yes, you can work entirely without classes, and that’s kinda how classes work under the hood. Fundamentally object oriented programming is just an organizational tool to help you write more readable and more concise code.

I use classes to group data together. E.g.

@dataclass.dataclass
class Measurement:
    temperature: int
    voltage: numpy.ndarray
    current: numpy.ndarray
    another_parameter: bool
    
    def resistance(self) -> float:
        ...

measurements = parse_measurements()
measurements = [m for m in measurements if m.another_parameter]
plt.plot(
    [m.temperature for m in measurements], 
    [m.resistance() for m in measurements]
)

This is much nicer to handle than three different lists of temperature, voltage and current. And then a fourth list of resistances. And another list for another_parameter. Especially if you have more parameters to each measurement and need to group measurements by these parameters.