Just for reference: the nail polish is supposed to create a random, near-impossible to replicate pattern using the metal flakes inside that get randomly distributed during application. You're supposed to take a picture of the blob after it has dried and keep that at home for comparison - the nail polish is not a miracle replacement for e. g. Loctite that will make it impossible to undo the screws.
I have no idea about the current state of AI tools, in particular I know absolutely nothing about the plethora of models people self-host and run.
Is this completely generative, or AI face swapped? What tools were used in the creation?
Just for reference, this is the character:
How anyone thought this would vibe with the intended audience is beyond me. No wait, it's actually not. It's just incredibly sad.
You don't know what you ask, traveler. My strongest potions would kill a dragon, let alone a man.
Interestingly, a short bit later in the video, the usage feels reversed: My potions are fit for a beast, let alone a man.
I mean, loops just became available, and I have seen two videos of this user in a time span of 30 minutes. Given that the videos have a certain production value (they're edited, there is music, proper lighting etc.) these videos were made by someone that was already doing this before loops and is now simply expanding their outreach to a new platform, so I would expect the content to be similar - whatever has worked for them previously, they're testing the waters without investing additional effort to adapt to a potentially different target audience.
Maybe loops will be different and the userbase will over time express a completely different taste in content, maybe not.
As I see it, I get to experience new forms of content, hopefully without the negative connotations that TikTok brought along, which I never got into.
Do I need to watch someone glue a condom to their shoes and surround their feet with fries for push a lame word pun to 11? Probably not. But I'm sure there will be different things, too.
And, of course: https://en.m.wikipedia.org/wiki/Pools_of_Darkness
I do in fact use unrefined, brown cane sugar, although I have not tried panela specifically.
The one I use pretty much looks like this:
It's an organic fair trade brand, but I'd have to look up where it is imported from.
As I said, I can't imagine making it with any other kind of sugar any more. Sorghum seems like an interesting idea, might have to experiment with that.
The key to amazing banana bread is to make it with soft, brown sugar. The stuff that is clumpy, glistening with moisture, reminiscent of molasses. It adds so much to the flavor. And actual nuts, of course.
Plots are typical composed, and when writing a paper (I insert them mostly into TeX publications) I do find the quality of the resulting plot is just so much more refined.
Seaborn is indeed closer and was definitely inspired by ggplot2 in some areas, but IMHO, it's still not 100% there visually. I'm very much a Python user and would love it to be, but when I'm, let's say, publishing a book, I'd always go back to ggplot2 - when preparing a paper for a lab class, seaborn is probably fine.
Or they have the same issue as me, their phone keyboard randomly inserting periods all the time. I manually remove them most of the time, but when I'm agitated, I sometimes can't be bothered.
This happens with several apps, e. g. https://www.reddit.com/r/Swiftkey/comments/wylng4/random_periods/
I didn't particularly want to link to reddit, but I wasn't able to quickly find e. g. an issue tracker.
You'll get used to it and it will only take a couple of minutes. And I honestly believe nothing comes close to ggplot2 in terms of quality, and I don't use R for anything else.
You were not kidding, this is seriously great. Completely new territory for me, but the excerpts won me over.
I did that on purpose, i. e. I wanted to confirm your thoughts about uv, drifted off into a general rant, remembered OP's original question and later realized it would have been better framed as a top level comment. In my defense, I was in an altered state of mind at the time.
pyenv and uv let you install and switch between multiple Python versions.
As for uv, those come from the Python build standalone project, if I remember correctly, pyenv also installs from there, but don't quote me on that.
I moved all our projects (and devs) from poetry to uv. Reasons were poetry's non standard pyproject.toml syntax and speed, plus some weird quirks, e. g. if poetry asks for input and is not run with the verbose flag, devs often don't notice and believe it is stuck (even though it's in the default project README).
Personally, I update uv on my local machine as soon as a new release is available so I can track any breaking changes. Couple of months in, I can say there were some hiccups in the beginning, but currently, it's smooth sailing, and the speed gain really affects productivity as well, mostly due to being able to not break away from a mental "flow" state while staring at updates, becoming suspicious something might be wrong. Don't get me wrong, apart from the custom syntax (poetry partially predates the pyproject PEP), poetry worked great for us for years, but uv feels nicer.
Recently, "uv build" was introduced, which simplified things. I wish there was an command to update the lock file while also updating the dependency specs in the project file. I ran some command today and by accident discovered that custom dependency groups (apart from e. g. "dev") have made it to uv, too.
"uv pip" does some things differently, in particular when resolving packages (it's possible to switch to pip's behavior now), but I do agree with the decisions, in particular the changes to prevent "dependency confusion" attacks.
As for the original question: Python really has a bit of a history of project management and build tools, I do feel however that the community and maintainers are finally getting somewhere.
cargo is a bit of an "unfair" comparison since its development happened much more aligned with Rust and its whole ecosystem and not as an afterthought by third party developers, but I agree: cargo is definitely a great benchmark how project and dependency management plus building should look like, along with rustup, it really makes the developer experience quite pleasant.
The need for virtual environments exists so that different projects can use different versions of dependencies and those dependencies can be installed in a project specific location vs a global, system location. Since Python is interpreted, these dependencies need to stick around for the lifetime of the program so they can be imported at runtime. poetry managed those in a separate folder in e. g. the user's cache directory, whereas uv for example stores the virtual environment in the project folder, which I strongly prefer.
cargo will download the matching dependencies (along with doing some caching) and link the correct version to the project, so a conceptual virtual environment doesn't need to exist for Rust. By default, rust links everything apart from the C runtime statically, so the dependencies are no longer neesed after the build - except you probably want to rebuild the project later, so there is some caching.
Finally, I'd also recommend to go and try setting up a project using astral's uv. It handles sane pyproject.toml files, will create/initialize new projects from a template, manages virtual environments and has CLI to build e. g. wheels or source distribution (you will need to specify which build backend to use. I use hatchling), but thats just a decision you make and express as one line in the project file. Note: hatchling is the build backend, hatch is pypa's project management, pretty much an alternative to poetry or uv.
uv will also install complete Python distributions (e. g. Python 3.12) if you need a different interpreter version for compatibility reasons
If you use workspaces in cargo, uv also does those.
uv init, uv add, uv lock --upgrade, uv sync, uv build and how uv handles tools you might want to install and run should really go a long way and probably provide an experience somewhat similar to cargo.
Didn't I just say that in the comment you replied to?
Also, ultraprocessed food is a fixed term that refers to
[...] foods [...] ready-to-eat or ready-to-heat industrial formulations made mainly with ingredients refined or extracted from foods and contain additives but little to no whole foods.
It's used as such in studies and reports.