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.
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.
https://www.php.net/manual/en/book.ffi.php is not enough for your needs?
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.
I’ll have to check this out.
Though not popular php can be a surprising decent scripting langauge.
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.
That is not why.
You stick to python because it's your common denominator. You all picked it up in school.
Python the most popular language around, and one of the slowest.
Python only seems fast because all the heavy duty number crunching libraries are actually written in C.
`pecl install Tensor`?
By far, for most apps, the biggest bottleneck is the database.
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.