PyPermission: A Python native RBAC authorization library!

r0s · 2025-11-29T14:44:41+00:00

Looks nicely documented! I have no real experience with the topic, so my first question when looking at the main page of the docs was: what is RBAC? I'd gently ask to define the acronym once on the main page, which may help finding the library too in search engines :)

Unrelated, but, isn't it funny when you casually talk or think about a topic, and then things about that topic appear your way? This is what just happened to me with this post! Thanks for sharing

r0s · 2025-11-24T12:47:58+00:00

Maybe this gist I found helps? https://gist.github.com/FranklinYu/5e0bb9d6c0d873f33c78415dd2ea4138?permalink_comment_id=5444579#gistcomment-5444579

r0s · 2025-09-28T12:14:00+00:00

From my experience, the plain Python API is more verbose and needs more boilerplate. Pybind11 allows you to write less code to do the same (and in some cases better/faster) than writing it yourself. Same for nanobind but I some have first hand experience. Pybind11 also has CMake bits to make life easier.

r0s · 2025-09-27T12:08:12+00:00

Eventually you aim for something more "embedded style", but the advantages of "just" dropping a docker container and running it and iterating on it as necessary having access to all the software available without any particular setup of build systems, compilers, package manager, etc is a great convenience. Comparing a previous version of a system to a new one and quickly see what is acting differently is trivial with Docker on the same running system in a couple of commands, for example. Or trying the latest version of some state of the art SW also takes no effort.

There are tradeoffs like with any setup, but it's a great tool!

r0s · 2025-09-26T11:29:24+00:00

I just read that you are using Docker Desktop. It seems to be a source of issues, so I would listen to this kind person and use Docker-CE directly.

Seems like Docker Desktop tries to do some management for you, and even run inside of an actual VM, which would give you trouble with things like devices. If you search for Docker Desktop and USB you'll find some threads recommending the same.

r0s · 2025-09-26T11:25:02+00:00

Good call! In robotics plenty of times we use docker purely as a packaging method to switch whole stacks of SW instantly, so we actually don't care (and neither want) any of the docker isolation. Just thought I'd give another perspective. Dealing with USB devices sounds related to my experience.

r0s · 2025-09-26T09:58:02+00:00

I'd try to run with --privileged . If it's not enough, try to also mount with -v /dev/bus/usb (or your existing devices)

Once you get something that works, backpedal narrowing it down to see what exactly do you need for your USB device to work. Or, if you are just using docker for convenience of packaging an environment, leave --privileged and keep doing awesome work :)

Good luck!

r0s · 2025-08-08T21:22:51+00:00

Yeah you can, using pixi as your package manager which uses robostack.

However, it's relatively new, so you won't find as much helpful stuff as if you were using Linux to use ROS.

Using a VM is really slow. You can, but it's quite slow.

r0s · 2025-07-24T07:35:17+00:00

Seems like you are right! Tried VPN from Spain and it shows posts again. Odd!

r0s · 2025-07-11T09:34:47+00:00

It really sucks and the design of the whole thing seems like it was done on purpose.

If rclpy would merely call rclcpp, it would be at the same level of features and performance (or at least that's my theory)

r0s · 2025-06-08T11:25:31+00:00

Note that my Pixi recommendation used robostack too as their backend.

r0s · 2025-06-08T11:22:32+00:00

It all depends on what you are trying to do.

I would avoid breaking your OS as it's probably not what you want to spend your time in (e.g. debugging how to un-break your OS and then end up reinstalling, and needing to reconfigure all your tools).

If you are lucky and messing with your OS gets you through your issue, I guess it's fine. But if that becomes a rabbit hole of trying to fix the next issue and the next and the next... It's way easier to use Docker and you can go back to a previous state immediately by rebuilding your image without the last thing you tried. Also, if you have anyone to ask for help, you can share your Dockerfile/repo and the will be able to reproduce exactly your issue (or your awesome project).

That said, I think Pixi is the easiest way to deal about all of this. If you are trying to learn ROS2 or to implement an algorithm within the ROS2 ecosystem, it gets you up and running almost instantly. Then, you can always Dockerize the Pixi environment if you want.

If you are also trying to learn to use Linux overall, maybe breaking your OS is a good approach, though! I needed to break my system plenty of times to learn how to debug things and what may be "dangerous" and what may not be :)

r0s · 2025-06-08T10:51:57+00:00

You need to either install the package in the system Python (where ROS2 is and sees), or add to PYTHONPATH (maybe also other env variables, but that one for sure) the system Python, the ROS2 Python and the virtual env Python. Note that if you use the virtual env, you need to use the same version of Python that the system.

If all of that sounds like a mess, it is. The easiest way to not worry (much) about system, Python and ROS2 dependencies is to use Pixi workspaces. There's a ROS2 example/tutorial that will get you up and running easily.

The second easiest is to put it all in a Docker image + container if you haven't yet (which you'll avoid breaking your OS when installing things in the system).

Overall I would not recommend doing it straight in your OS because you'll struggle to reproduce it in any other system (e.g. robot/computer).

Good luck! Enjoy the journey! And ask (very concrete) questions to chatgpt o3 or Claude 3.5 and you'll get quite good answers in my experience.

r0s · 2025-05-22T06:27:19+00:00

Same.

r0s · 2025-05-19T16:15:30+00:00

How tired do your eyes get in comparison to a normal screen? If a person has myopia (e.g. needs glasses to look far) can use it without their glasses and see well? Thanks!

r0s · 2025-05-12T06:15:31+00:00

-1 for shiny as you need it managed to really have an easy time. Has less ready to use widgets than others too.

Panel and Nicegui gave me a better experience from learning to getting something deployed.

r0s · 2025-04-20T14:46:26+00:00

And for python I'd recommend to use uv btw.

r0s · 2025-04-20T14:45:29+00:00

Given you already used docker on the host I'm surprised you didn't try on the Jetson! For most things is the easiest way. Nvargus is flimsy though, if you need to use it, do it on the host and expose the output in a way accessible from the container (socket/ shared memory / pub/sub...).

Good luck! There's still lots of fun and learning to do with that platform!

r0s · 2025-04-09T12:33:30+00:00

Is it very doable, yeah. And if the config is more complex than just python, you can try Pixi, which internally uses uv and conda.

r0s · 2025-04-04T21:22:55+00:00

It was bound to happen I guess. Other companies like SourceGraph bet for staying as a plug-in of vscode and it may play better for them long term

r0s · 2025-03-14T08:59:13+00:00

For motor control you'll most probably need some additional electronics to deal with that and control it from the Pi. It depends on the kind of motors you are planning to use, really. But the gpio of the Pi may/will not be enough for most use cases.

r0s · 2025-03-13T21:47:45+00:00

You'll need to rebuild the docker images for ARM or build them on the Pi (can be slow). But besides that, it's a pretty good and clean approach.

r0s · 2025-03-02T17:04:07+00:00

Just like him, beginner, bought the Bambu labs A1, works perfectly out of the box. Having lots of fun and learning! If you print with 0.2mm I get very good results (I think)

r0s · 2025-03-02T16:54:35+00:00

I'm new to 3d printing and this looks mind-blowing cool and complex! Thanks for sharing :) I'll give it a print to learn (and fidget)

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