🇨🇦 tunetardis

I can’t remember which comedian it was, but he said whenever he hears something like 4 out of 5 doctors recommend a particular medication, he wonders what that 5th doctor knows that the others don’t?

When I first started taking climatology back in the day, I thought it a bit paradoxical that profs kept going on about how global warming would lead to more extreme weather when, on a first principles basis at least, I would’ve thought it should lessen weather variability. Anthropogenic warming is an insulating effect, and that should tend to even out conditions across the planet, just as insulating your home should reduce drafts and what not.

I guess my problem was that I had it in my head that greater variability = more chance to hit extremes, and we were going the other way. But the way things are playing out, it’s less variability that is giving us what we view as aberrant weather. That heat dome that never leaves or that storm system that parks itself over your head for days on end. We get too much of one thing because the weather systems are actually becoming less chaotic and getting stuck in holding patterns for longer than is healthy.

As with most script languages, you can hit the ground running in a very procedural sort of way, as you don’t even have to define a main entry point. You just start coding.

But Python certainly has an object model. If I’m not mistaken, everything in Python is an object. Like even functions.

I suppose there are some aspects of the class implementation that feel a little tacked on? Like the way you need to manage the self reference manually where it may be implicitly handled for you in other languages. At least the way you call super() now is a lot less kludgy.

One thing I miss a bit in Python is method overloading. In a general sense, function overloading is not an OOP feature per se, but I find it useful in OOP, particularly with object initializers. You can sort of achieve it with @functools.singledispatch but it’s pretty janky. For initialization, I prefer keeping the __init__ method pretty rudimentary and writing factory functions to do more complex initializations. And with @dataclass, you can forego writing an __init__ altogether if you do it that way.