Basically, leave Python for OS and application scripting tasks, and as BASIC replacement for those learning to program.
Python performance myths and fairy tales
21–30 of 221 posts
Re: Python performance myths and fairy tales
#22So we are paying 99% of the performance just for the 1% of cases where it's nice to code in. Why do people think it's a good trade-off?
Because many never used Smalltalk, Common Lisp, Self, Dylan,... so they think CPython is the only way there is, plus they already have their computer resources wasted by tons of Electron apps anyway, that they hardly question CPython's performance, or lack thereof.
Re: Python performance myths and fairy tales
#23So we are paying 99% of the performance just for the 1% of cases where it's nice to code in. Why do people think it's a good trade-off?
It isn't. There are many things Python isn't up to the task. However, it has been around forever, and some influential niche verticals like cyber security Python was as or more useful than native tooling, and works on multiple platforms.
Re: Python performance myths and fairy tales
#24Feel like Mojo is worth a shoutout in this context https://www.modular.com/mojo Solves the issue of having a superset of Python in syntax where "fn" instead of "def" functions are assumed static typed and compilable with Numba style optimisations.
Re: Python performance myths and fairy tales
#25Feel like Mojo is worth a shoutout in this context https://www.modular.com/mojo Solves the issue of having a superset of Python in syntax where "fn" instead of "def" functions are assumed static typed and compilable with Numba style optimisations.
Mojo NOT being open-source is a complete non-starter.
Re: Python performance myths and fairy tales
#26I didn't read with 100% focus, but this lwn account of the talk seemed to confirm those myths instead of debunking.
A more careful reading of the article is required.
The first myth is "Python is not slow" - it is debunked, it is slow.
The second myth is ""it's just a glue language / you just need to rewrite the hot parts in C/C++" - it is debunked, just rewriting stuff in C/Rust does not help.
The third myth is " Python is slow because it is interpreted" - it is debunked, it is not slow only because it is interpreted.
Re: Python performance myths and fairy tales
#27An earlier version of the talk is at https://www.youtube.com/watch?v=ir5ShHRi5lw (I could not find the EuroPython one).
Re: Python performance myths and fairy tales
#28It’s a good article on speed.
But honestly the thing that makes any of my programs slow is network calls. And there a nice async setup goes a long way. And then k8 for the scaling.
Re: Python performance myths and fairy tales
#29Feel like Mojo is worth a shoutout in this context https://www.modular.com/mojo Solves the issue of having a superset of Python in syntax where "fn" instead of "def" functions are assumed static typed and compilable with Numba style optimisations.
Mojo NOT being open-source is a complete non-starter.
Genuinely curious; while I understand why we would want a language to be open-source (there's plenty of good reasons), do you have anecdotes where the open-sourceness helped you solve a problem?
Re: Python performance myths and fairy tales
#30Antonio is a star. He's also a very talented artist.