For one thing it will run a lot of existing and proven Matlab code.

Another is that Octave and Matlab syntax is ambiguous about functions vs indexes (has pros and cons).

And don't get me wrong (I use jupyter and python a lot and really do like it) but numpy can get fundamentally weird in the way indexing maps to memory in ways that I don't remember happening back when I mostly used Octave.

And for the record Octave's version of the language is vastly superior to Matlab's. (Octave has chained indexing, broadcasting, etc. It could be that Matlab has finally copied those features but dunno. Every time I have to work in actual Matlab I want to rip my hair and teeth out due to lack of these basic trivial syntax features)

For me the major advantage of python is having access to other non-numerical things. It's so difficult to do anything not-numerics in Octave and Matlab or to use even basic data structures like lists and trees. Python is sort of a basic dynamic object language that with some functional programming idioms mixed in that makes some of the things that would otherwise make you scream for Lisp possible. That's worth the numpy annoyances. Otherwise I would probably be using julia.

This is the sort of superficial dismissal I was referring to.

"There are no safety issues because you can plead your case publically and incite a mob!" isn't exactly as trust-inspiring as you seem to believe.

No they allow admins to decide that. Users have no control. User activity is fully public and cannot be controlled for safety.

It would be similar hell in for example Matlab or C/C++ if install of external packages were made so easy.

Some systems that are designed more with the concept of maintenance challenges (Windows and others) make it possible to have different versions installed simultaneously.

The need for the whole venv thing fundamentally underscores the problem. How many versions of libc do you have installed simultaneously? (docker users pls don't respond)

Nothing really sticks out. It could also be something about how the automated checker provides input (maybe it expects to not press enter or something and it's stuck at input()... hard to say)

I personally would install ruff and run "ruff check yourfile.py" and then later "ruff check --select=ALL yourfile.py" and read about everything it complains about.

Google the error codes and find the description and discussion of each and why it is complaining, sometimes they're not a big deal, sometimes they are aha moments. Ruff has a page discussing each warning and error

https://docs.astral.sh/ruff/rules/

A few podcasts I listen to have switched to calling their bluesky handles out instead of their twitter handles in their outros. I'll probably install it and delete ex/twitter when I get an invite.

He also shrieked about bots, and now he parades his own around.

Just be aware that in the fediverse everyone sees what you up and down vote.

For the types of visualizations you're describing, the choice probably won't matter. I view matplotlib as "matlab flavor" and ggplot2 as "R flavor". For R-type work (a certain type of table-based stats) I just use R.

For matlab type work (image processing, simulations, etc) I now use matplotlib. This is mostly numpy/scipy things rather than... pandas things. Python is interesting because it has things that are beyond matplotlib (VTK, etc) and beyond matlab. Typically when you're prototyping in matlab you're assuming you will have to rewrite in a different system eventually, but with python you can move the prototype further down to more polished prototype easily.

I do a lot of image processing and am too familiar with matlab, so matplotlib generally came naturally for translating that prior knowledge. So really it depends on what sorts of things you are familiar with, languages you use, and would want to do in the future. I think with either choice you will eventually hit some wall of difficulty.

There are also more visualization and plot focused things (TeX family or PostScript and PDF) as well as the "processing" language.

I use R for... not-image-type analysis stats and generate plots in R using R's plotting. I mostly use python for matlab-type things and matplotlib seems more natural for that.

Julia is on my todo-list and I have heard good things about their plotting ecosystem but I have not looked into it.

Incidentally VTK is extremely well designed for the type of language it's based on and the problems its solving... but that's not really 2D plotting.

I don't like the idea. It seems like those fake websites that scrape stackoverflow and SEO to ruin Google search. Avoiding those sites are among the reasons people type "reddit" into searches. People want authentic interactions and I think mirroring reddit into Fediverse lacks authenticity and undermines its authenticity. Content here should be from people who are here.

If someone wants to assimilate content from reddit into something new and post it here that's good. That means the person is here and can be interacted with.

If someone wants to repost their own content here, that's also fine. They are here to interact with.

I just really think it's a bad idea to deliberately build a ghost town and think people will move in.

I'm left unsure whether DBMS is fun sex for dyslexics, or BSDM is a dyslexic database.

Basically it's what they have decided to disclose to law enforcement. So at best it tells you the baseline capabilities of law enforcement.