dunders | abusing Python 's double-underscore methods | Genomics library

This is what the __radd__ method is for - if your custom object is on the right side of the operator, and the left side of the operator can't handle it. Note that the left side of the operator will take precedence, if possible.

You can't create an instance of a class within its own body because the body needs to finish running before the class object can be created. The namespace the body of the class runs in becomes the class namespace.

To do what you want, you need to create the class first, then assign the class attributes afterwards. You can probably do this without putting anything specific about the attributes in the class at all:

What you're after is the concept called inheritance, a key part of object-oriented programming (see Wikipedia here.

When you define your class with class Image(object):, what that means is that Image is a subclass of object, which is a built-in type that does very little. Your functionality is added on to that more-or-less blank concept. But if instead you defined your class with class Image(np.array):, then Image would be a subclass of array, which means it would inherit all the default functionality of the array class. Essentially, any class method you want to leave as is you simply shouldn't redefine. If you don't write a __getitem__ function, it uses the one defined in array.

If you need to add additional functionality in any of those functions, you can still redefine them (called overriding) and then use super().__getitem__ (or whatever) to access the function defined in the inherited class. This often happens with __init__ for example.

For a more thorough explanation, take a look at the chapter on inheritance in Think Python.

Use the inspect module. From this source:

The dataclass decorator does not affect how attributes are stored or retrieved. Memory consumption and attribute access times will behave exactly as if the class was written without dataclass.

A class that uses __slots__ will have less memory consumption and slightly faster attribute access (because slot descriptors save a few dict lookups) than a similar class that does not use __slots__, regardless of whether either class uses dataclass. Here's a timing example, showing that dataclass doesn't affect attribute lookup times, while __slots__ does: