Have a discussion with chatGPT about a program you would like to write, use this to assist the development.
Evidence this as the source of the program. There is your re-research. It's likely the implementation will differ substantially as well.
They might own the original program but it's unlikely they broad concept.
Well it's there, in one loooong print out. It's not as bad as I'm making it out to be, however, I went back to python unfortunately.
The crucial issue with Julia, no error messages.
So I use Julia for things that need to be fast (e.g. moving hdf5 to SQL and ffts) but I use python for everything else (except ggplot).
Simply, the lsp is far less useful. An object might have a dozen methods that act like verbs or some attributes that act as adjectives.
In Julia there is a huge number of functions, that work differently for different types and different combinations of types. So finding the documentation involves finding the right name for a function that does different things for different types, then scrolling down the docs for the the behaviour that corresponds to the specific combination of inputs.
I moved from R/Py to Julia for a while before moving back to Py (and a little bit of Rust).
I love how fast Julia is and the 1-index is fine for me, but I still prefer py for the oop.
Who cares if it's European sounding, it's still an interesting language that is relatively easy to learn, even for people from non-romance backgrounds.
I personally find multiple dispatch far more challenging to use than OOP. I'd reach for Torch over Flux any day.
Although, I really like that the majority of the Flux stack is Julia rather than a collection of Cpp.
I would recommend arkenfox over librewolf, that way you can use an up to date browser, with the same privacy and greater flexibility to enable features you may want (e.g. no letterbox etc).
Honestly, Switch to a basic Linux distro and use docker directly.
I ran TrueNAS for a while and it's just too complex and janky. I dropped back to void (for ZFS) and have a directory of compose files for radar/sonar, jellyfish, mediawiki, Lemmy etc.
Sqlite and duckdb are great, I don't know about shitty.
You don't get the visual feedback but the query language, reliability and python interface are all top notch.
Except every scientist and analyst. Stats, data sci and ML is done in R and Python, be it astro, health data or genomics.
If someone has been taught stats in spreadsheet software, they have have been taught wrong, period.
Also, programming is a very strong term. we're talking about stats in a scripting language, not software development in CPP.
If you want something more Unix like and less PowerShell (but absolutely not POSIX), checkout Elvish.
Jetpack compose in Kotlin, Flutter using Dart or Fyne are all pretty easy to get started with.
Yeah spotiflyer is great