We're building the fast, deterministic and reproducible package manager Pixi for scientific and robotics workflows. Based on @condaforge & @robostack packages.
The Pixi team is at ROSCON in Toronto - come find the yellow backpacks if you want to chat! We keep spotting Pixi in so many cool robotics projects and it's making us proud. To get a glimpse of what we're working on, join the talk about the EU CRA this afternoon!
NVIDIA Isaac ROS 5.0 brings AI agents to robotics development. 🤖
Announced at #ROSCon, the release adds agentic workflows, Isaac Skills, ROS 2 Lyrical support, GPU-accelerated libraries and NVIDIA Jetson support from Orin Nano to Thor.
Open source and available now 📖 nvda.ws/3VahoaA
We made it easy to install Isaac ROS! The new `isaac-forge` repository contains many upstream NVIDIA Isaac ROS packages to make them installable with Pixi. You can test it today on your #NIVIDA#Jetson!
No docker needed!
github.com/wolfv/isaac-forge
Congratulations to the Mojo 1.0 release @Modular! So glad to have you in our community, and seeing @clattner_llvm on stage with `pixi` in the background was definitely a highlight for us.
pixi update --offline now resolves against only what you already have: the package cache and local file:// channels.
Air-gapped machines, planes, CI without egress.
Pixi now fully supports archspec, so you can create CPU-optimized environments and let Pixi handle the installation logic.
Read more about it in the blogpost we updated:
prefix.dev/blog/building_cpu…
Use pixi global to install any project from source now.
Pixi global supports the full package spec to configure the neccesary information to install it directly, without a pixi.toml.
Conda packages can have extras now.
Optional dependency groups you declare and then consume, via v3 repodata. Plus when conditions and variant flags.
This should also be available on conda-forge in the near future!
📖 : pixi.prefix.dev/latest/conce…
No more gpu and cpu environments, let pixi choose the right platform for you!
[system-requirements] is deprecated. Platforms now carry the requirements themselves.
CUDA and glibc constraints inline, and you can name a target what you actually call it.
Lastly, I'm a contributor to the `pixi-build-mojo` backend, which is what @prefix_dev can use to build Mojo projects: pixi.prefix.dev/latest/build…
And allows you to install dependencies directly from GitHub, which is really cool!