PHP has always ben slow, its getting slightly faster, but still REALLY, REALLY slow for anything CPU heavy. This is why the ML crowd sticks with Python (numpy) thats incredibly fast.
PHP is still lacking, there is no unicode support, and for a web language this is really bad. Also, the way PHP functions, makes modern web (like websockets) use impossible, there is hacks around this but they all kind of suck.
Python is slower than most of the horses I bet on. That's pretty slow.
The important - CPU intensive parts - of numpy, pandas, pytorch, and all the other "fast python" libraries out there, are actually written in C.
Pure python should not be used for anything that requires good performance: it is programmer ergonomic, not CPU ergonomic. It is great that through the use of FFIs it has access to powerful libraries written in a language that isn't slow, but that does not make it as a language itself, fast.
Thats my point, pyton the is one of the slowest languages, and still have high quality, high perf libraries like numpy. PHP has no way to install deps that actually are written in asm/fortran or c.
PHP has decent FFI, nothing is stopping you from using the same libraries as you would with Python. Here's someone's quick hack as an example: https://github.com/dstogov/php-tensorflow
For an interpreted language PHP itself is ridiculously fast and the VM is rather small so you can use something else coughElixircough for parallellisation. I use it all the time for data wrangling stuff and database imports because it's robust, fast and PsySh is a pretty neat environment.
The array data structure is quite nice too. It's built on simple parts that are foundational to the VM itself, and very flexible, similar to lists in Lisp-like languages but without the seek lag when data grows due to the indexing.
It's very popular, as in a lot of businesses use it, it's just not fashionable.
I think it's a great tool to have. It had gradual typing before it was cool. You can type in like a page of code including the layout and render whatever in a PDO-supported database on a web page, served by the builtin web server, which is great for data exploration and things like SQL optimisation. At the moment I'm handling some data flows and conversions in a project with something like a terabyte of email and office documents that need to go into RDBMS, because there are some liberally licensed lightweight libraries (in contrast to the bulky stuff in Jakarta-land) and the performance is good enough to not be a bottleneck.
Edit: And when a library isn't good enough, I can usually trivially fix or extend it because it's in a familiar language and written by a simple minded person like myself.
There's a degree of clunkiness and incoherence in built-in API:s that might be off-putting at first but the included batteries and PsySH make for a quite decent tool anyway.
There were many many times I'd start writing a bash script, but then switch it to a PHP script. I've done this so many times that now I just start writing in PHP.
I'm pretty sure this is wrong. PHP has been faster than Python for a long time, but numpy is not written in Python, it's written in C. Just like PHP, coincidentally :)
In my experience, it’s actually very fast. That may be partly because of the way I write the code, though, and my backend code isn’t really too massive.
Big Oof. :( :( :(