I shudder to think what datascience code would look like if a language with a culture of monkeypatching/metaclassing had won. Clear code is nice, but not when the price is sweeping all of the details too deeply under the carpet.
Ever worked with numpy, scipy, pandas etc. in Python? It's ALL about what you call "sweeping the details under the carpet", or what is generally called abstraction. When abstraction is well "swept under the rug", eg. "you can use it without understanding it much" it's called non-leaky abstraction, and is the best kind of abstraction.
Sure, there's languages like Go that are all about NOT sweeping things under the rug. But that's a different niche.
Is there such thing?
(I agree that math abstractions are less leaky than others, of course)
Those are just external libraries written in C/fortran/etc. Not monkeypatching.
I don't applaud ruby dark voodoo tricks, but I think it's the same spirit.
i, unlike GP, do not get a smile on my face when i read ruby code full of implicit tricks. even when i understand some of them, it is still annoying.
why don't people just write clear, explicit, maintainable code instead of trying to be clever. i am sure method_missing could be implemented in python using various tricks but nobody, afaik, is doing that.
You could probably implement method_missing in Python using either __getattribute__ or __getattr__.
I think this is a small example of why nobody is doing so. It’s not just culture - Python’s object model is so complex that it would be hard to get right.
> why don't people just write clear, explicit, maintainable code instead of trying to be clever
But that’s boring. Seriously, it always amazes me how many programmers allow their decisions to be guided by what’s best for their personal enjoyment rather than what’s best for the project.
Exactly! Python is flexible too... using module import hooks and AST transformations you can even implement common-lisp-style-macros... but the language and model is so darn messy and special-case-y that it would blow up in your face if you tried to use it in a real world project :|
Whereas in Ruby you can whip up a nice clean DSL in no time, and people can actually understand how it's implemented and read it's source without being gurus. Whereas the number of Python programmers who properly understand metaclasses and AST wrangling and other stuff you'd need to do DSL-like stuff and have it work correctly can be counted on not that many fingers...