Python is quickly taking the crown for low-barrier to entry, slow, buggy code supported primarily by stackoverflow copy pastes from a never-ending supply of “data scientists”
Quickly seems like an overstatement; you've always been able to write low-barrier to entry, slow, buggy code. Is there a low-barrier language that doesn't end up with a lot of less-than-ideal code samples?
I support over a million lines of powershell. It's pretty hygienic, for the efforts of a hundred low-skill contributors.
The language has flaws. But the function parameters are an joy and incredibly powerful. The validation and type coercion is excellent. The functions are extremely composable.
Overall, it's the epitome of "pit of success".
The same team that has all this powershell also has about 50k lines of Python. The Python has the stench of swamp farts, so I don't think it's team skill that makes the powershell work so well.
Meh, Python really shines at I/O and gluing together C/C++/Fortran code. It's reasonably fast for most tasks, and if it isn't there are tools like Cython that make it pretty trivial to write Python code that achieves C-like execution speed (because it effectively compiles to C code).
I agree that Python is a great glue language (so are Perl and Python).
However, Python really doesn't shine when compared with other memory safe languages like Go, Rust, and Java.
Ultimately, Python is single-threaded by design. There are some hacks to get around this design contraint (multi-processing), but then you are adding an entire additional Python runtime to your system's memory for every "thread" you want to run. Even with asyncio, Python performs the worst when it comes to I/O.
I love Python, but it's important to understand that due to specific design considerations it is not and will likely never be a performant language.
If you can write code twice as fast then you'll write twice as many bugs.
Having been a C++ and python developer I see just as many footguns in both languages and have spent many many many hours dealing with slow, buggy code in either.
There's a lot of nice Python code out there, mostly written by disciplined and experienced systems people.
But I agree about the hordes of data scientists making copy and paste spaghetti. This is evidenced by companies deploying Jupyter notebooks in production, which essentially witnesses the fact that they've given up on getting data people to write quality production Python, and instead they treat their prototype spaghetti as sandboxed blackboxes that can be tested on inputs and deployed if they perform well enough.
I miss it. On the javascript side there was just jquery and a mountain of vanilla js that everyone could at least understand (and no npm dependency issues, ES6+ weirdness, etc) and on the PHP side, all built-in functions were in the global scope (easy to CTRL+F on a single page at a time when search endpoints were quite slow), there were (virtually) no web frameworks (at least I didn't use any until after 2009), and no package management to worry about unless you were doing something weird and/or wrangling with wordpress. As a tween and young teen I had plenty of small web design clients.. local businesses, photographers, etc., and I could build sites 100% from scratch starting from a photoshop mockup to custom PHP/HTML/CSS/JS, 100% no packages or other people's code. Packages have done a ton for us, for sure, but I truly miss those days and feel like we've lost something we'll never get back.
Back then it was actually quite possible to build an entire website or "app" as we call them now from first principles just banging your head against HTML/CSS/JS and whatever server side language you were using. Then the internet grew up, security issues became more prevalent, packages, other people's code, dependency hell, "futures", "promises", server state and client state management, shadow dom, reactivity, etc etc.