LOL yeah, while the principles listed in the Zen are good advices and practices, unfortunately most of them don't really depend on the language its self but
rather on whoever writes the code and their implementation choices.
Of those few that depend on the language too bad python violates pretty much all of them.
Starting with the very 1st and 2nd line, where significant white spaces (one of the worst idea ever in programming, if you ask me) make block limits implicit in the indentation rather than explicit int he code with clear delimitation marks (brackets, for instance), making in return most of the source code written in it look quite ugly, and as dyslexic I can add not very accessible. Let alone the horrible experience while iterating on a piece of code: 99% of the time you're briefly stopped by and error simply because in the iteration some lines got commented out and now the damn thing throws a fit for the indentation. Not really practical in my experience.
The reason why one language is more used then others at any given times it's way simpler and more bound to humans than the languages them self:
- fashion trendes
- laziness
- sloth
Most of the people out there writing code and "increasing numbers for any given language" have no real idea of why they started with one language rather then some other one, they never really dig deep enough to actually made an informed choice, and most will keep using a single programming language because they "don't feel the need to learn a new one", aka: I'm too lazy to ever go deep enough the only language I know, let alone learning a new one.
And it's the market's fault: we spent the last decade or more taunting how many bagilions programmers will be needed, how anyone can get a great life by simply learning a bit how to code, etc. None gave a fuck about quality, the only goal being cheapening and cheapening the Software Developer profession, until neural networks came about and indirectly revealed the truth: we haven't being rising SW developers/engineers/etc, most of them were just Code Typist copying out of stack overflow. If something like copilot or chatGPT can substitute them, it means there wasn't much value there in the 1st place.
In 2007, Jeff Atwood made the quote that was popularly referred to as Atwood's Law: “Any application that can be written in JavaScript, will eventually be written in JavaScript.”, and that's NOT a good thing, it's just the epitome of the state of the industry.
In python's case it's luck was google: python (like go, for instance) is a convenient language for system automations, let's say a more sane versions of what perl was mostly used for in the past (if you notice, lots of python Zen's ideas are attempts to fix perl's insanity).
Google has lots of system engineering going on, lots of people using (and abusing) python, and a single repo where everything ends up into, and when they started making neural networks with them, python got fashion for making neural networks. Anyone and their dog wanting to try out some kind of machine learning (10+ years ago) would find a tutorial in python, and tensorflow sealed the deal.
Yes, numpy and pandas did have quite a bit of weight into luring the Math Community into using python, but there's nothing inherent in python that makes them possible, they could have being made in any other language. For instance haskel and lisp are way more approachable from a math stand point, they're just not in fashion any more
The reason why one language is more used then others at any given times it's way simpler and more bound to humans than the languages them self: - fashion trendes - laziness - sloth
Most of the people out there writing code and "increasing numbers for any given language" have no real idea of why they started with one language rather then some other one, they never really dig deep enough to actually made an informed choice, and most will keep using a single programming language because they "don't feel the need to learn a new one", aka: I'm too lazy to ever go deep enough the only language I know, let alone learning a new one. And it's the market's fault: we spent the last decade or more taunting how many bagilions programmers will be needed, how anyone can get a great life by simply learning a bit how to code, etc. None gave a fuck about quality, the only goal being cheapening and cheapening the Software Developer profession, until neural networks came about and indirectly revealed the truth: we haven't being rising SW developers/engineers/etc, most of them were just Code Typist copying out of stack overflow. If something like copilot or chatGPT can substitute them, it means there wasn't much value there in the 1st place. In 2007, Jeff Atwood made the quote that was popularly referred to as Atwood's Law: “Any application that can be written in JavaScript, will eventually be written in JavaScript.”, and that's NOT a good thing, it's just the epitome of the state of the industry.
In python's case it's luck was google: python (like go, for instance) is a convenient language for system automations, let's say a more sane versions of what perl was mostly used for in the past (if you notice, lots of python Zen's ideas are attempts to fix perl's insanity). Google has lots of system engineering going on, lots of people using (and abusing) python, and a single repo where everything ends up into, and when they started making neural networks with them, python got fashion for making neural networks. Anyone and their dog wanting to try out some kind of machine learning (10+ years ago) would find a tutorial in python, and tensorflow sealed the deal.
Yes, numpy and pandas did have quite a bit of weight into luring the Math Community into using python, but there's nothing inherent in python that makes them possible, they could have being made in any other language. For instance haskel and lisp are way more approachable from a math stand point, they're just not in fashion any more