- easy_install, distutils and eggs were deprecated
- ensurepip and venv were introduced
- the whole wheel ecosystem flourished
- a new dependency resolver was introduced to python
But:
- a lot of noise has accumulated. Hence the procedure in the previous article, to avoid the traps from all that noise and go back to what usually works.
- we have a long way to go, but it's not something easily fixed (hence the conclusion of the current article explaining why it's going to take a long time to get better).
Hopefully, the direction of that long way is relegate python (and javascript!) to legacy languages.
Something, hopefully, will come out of webassembly. Otherwise, the last decade only saw the rise of two fundamentally flawed languages as the most popular ones.
Ruby losing to both was not a good thing. And I'm not even a Ruby programmer! I hated the language back in the Rails vs Java days. But it is impossible to deny that great software came out of Ruby.
Javascript and Python has produced no great software, just ponderous stacks of crappy code and poorly organized libraries. They are popular because they are used for throwaway web applications and throwaway scientific / non-programmer code, and it shows.
The fact that golang is what is producing new "good" software: a language that is intentionally bad, as opposed to python and javascript being worse because of cruft accumulation or Eich writing it a weekend, is also not a great sign but it's not the step backward that javascript and python are.
People writing in JS are usually techies who could/would migrate. People writing in Python are on a wide spectrum that goes from "one-step-above-matlab" to "know-it-all-c-wizard". You won't actually get all these people to move on any reasonable timeframe.
HN is biased because we tend to love tech and a lot of us know several languages, but Python is much more democratized. My friends in physics, biotech, mechanical engineering, basically everyone in STEM is using Python and to them it's a tool that took a lot of time to learn and they won't drop it all because dependencies are hard.
Besides, code at a large scale in any language is always messy. There are many ways to manage a growing codebase but if your only approach is relying a "good" language with static typing, verbose/explicit syntax, and a better built-in package manager, you are doomed to fail anyways.
Perhaps this is a case of correlation=/=causation? Python is more accessible so less adept programmers are more likely to use it.
