Python is not compiled and start & load pandas (which is comparable to the libraries loaded in the article) in ~0.4" on my computer, and that's a notoriously slow language.
If I were to use e.g. Rust with polars, load time would be virtually none. And when I have to process ~50k different datasets, I can't afford 0.85" per file, which would translate to ~11 hours of overhead.
> If I were to use e.g. Rust with polars, load time would be virtually none.
Because you're compiling...
And if you need to do the same in Julia, you should also pre-compile or some other method like https://github.com/dmolina/DaemonMode.jl (their demo shows loading a database, with subsequent loads after the first one taking roughly ~0.2% of the first)
No it's not, because I will not architecture my whole pipeline & program around Julia inability to start in maybe a second in a year or 1.7" now, I will just use another language.
When is 1.10 expected? Just wondering I did a quick google and it seems a lot of the 1.9 improvement were back ported from 1.10? Or is that really 2x on top of current 1.9?
1.10 feature freeze is going to be in the next few weeks. after that it will be a few months depending on how much is required to fix all the bugs that have probably been introduced. 1.9 mostly doesn't shorten loading times (although weak dependencies end up helping a bit). 1.10 has had a bunch of load time optimization which became a lot more obvious once 1.9 got rid of all the stupid stuff. the exact speedups are package dependent, but 2x is a good estimate. some packages get a lot more, some are about the same.
But 1.7 seconds at first startup isn't even enough time to articulate a serious thought, much less write any good code.
I struggle to believe it's a dent in anyones workflow.