docs: lead installation guide with Docker/Apptainer over from-source#908
docs: lead installation guide with Docker/Apptainer over from-source#908sevmag wants to merge 1 commit into
Conversation
|
Feel free to add suggestions that change the wording or text now that we are already reworking this section @Aske-Rosted @christianlocatelli |
| which opens an image with a CPU-installation of GraphNeT 1.8.0 + PyTorch v2.6.0 + IceTray v1.13.0 installed and ready to use. You can replace the image path with the one you want to use from the DockerHub. | ||
|
|
||
|
|
||
| Installing From Source |
There was a problem hiding this comment.
Maybe here you could emphasize that this option is the recommended one for contributors.
"Installing From Source (for development, or if Docker/Apptainer isn't available)"
| =========== | ||
| Here we provide a quick start guide for getting you started with |graphnet|\ GraphNeT. | ||
|
|
||
| The easiest way to get started is with our pre-built Docker images — see `Docker & Apptainer Images`_ below. They ship GraphNeT, PyTorch and (optionally) IceTray ready to use, with both CPU and GPU variants, and can be run without sudo via Apptainer. If you instead need a writable install or an environment without a container runtime, see `Installing From Source`_. |
There was a problem hiding this comment.
I would adapt this section a bit. Instead of "easiest way to get started", I would suggest to instead use something like: "The most reliable way for GraphNeT Users to get a working environment...".
I would also already mention in that section, that the Docker option is not available for KM3NeT so far. Otherwise KM3NeT Users reading it from top to bottom could be a bit mislead. Could we add a one-line qualifier in the intro, e.g. "Docker images are currently available for IceTray-based experiments (IceCube & P-ONE); KM3NeT users should install from source for now"?
|
|
||
| The easiest way to get started is with our pre-built Docker images — see `Docker & Apptainer Images`_ below. They ship GraphNeT, PyTorch and (optionally) IceTray ready to use, with both CPU and GPU variants, and can be run without sudo via Apptainer. If you instead need a writable install or an environment without a container runtime, see `Installing From Source`_. | ||
|
|
||
| Docker & Apptainer Images |
There was a problem hiding this comment.
I don't know how familiar people in the community are with Docker/Apptainer. I personally never used containers before and would therefore have to look some things up before installing it.
In the Source installation section there is a link leading people to the Anaconda installation, so I thought it could be useful to provide at least a some links to the get started pages of Docker and Apptainer somewhere in this section. This is just a minor change but it leads ppl who are unfamiliar immediately to the most relevant pages.
Smth like:
(New to containers? See the get-started guides for Docker and Apptainer.)
christianlocatelli
left a comment
There was a problem hiding this comment.
Hi Severin, I left some comments on your PR. Let me know what you think :)
Closes #889.
Reorganises
docs/source/installation/install.rstso the recommended path — the pre-built Docker/Apptainer images — comes first, with from-source install framed as the option for writable/editable installs or systems without a container runtime. No technical content changes: just ordering and framing.What changed
Installing From Source_ for writable/editable installs.Motivation
HPC users often can't install from source on a bare cluster — e.g. RHEL/Rocky 8 nodes ship glibc 2.28, while
pyg_lib'slibpyg.soin the PyPI wheels requiresGLIBC_2.29, sopip install -e .[torch-XX]outside CVMFS/conda-forge tends to fail at import time. The pre-built images sidestep this entirely and are autobuilt per release for both CPU and GPU. Leading with them better matches what's actively maintained.🤖 Generated with Claude Code