We would like to explore the potential of docker in our community.
This repository is there for a first attempt.
This repository is there a first attempt in this direction.
## Main use case
I have a Mac laptop and I would like to work locally on my Mac in a UNIX system.
Some of the reasons are
- work directly on lxplus can be slow (dependent on the node). The advantage of lxplus is that it mounts `afs`, `eos`, `cvmfs` and the HTCondor interface.
- work on SWAN can be slow and it does not mount `afs` - this can be problematic for the MAD-X mask.
- python C-compiled package can have difficulties to be maintained for Mac/Win, e.g., `cpymad` does not work properly on Mac
(I can install it on Mad and run small lattice, but when I try the larger ones, namely LHC, it fails).
I started to use a simple docker as a workaround (the same I used for CAS/JUAS courses), typically I use `jupyter lab` and my experience in term of performance and stability is very positive.
- I would like to mount `eos` and `afs` without suffering to much, and I would like that the possibility to share my setup not only via a set of wikis but also with press-one-button solution. With this spirit, one could prepare and share several `env`, e.g,. to track particles, to access NXCALS,...
For the moment, I am considering that you have already installed in your Mac (local host) `afs` - it is quite easy to do so, I tested the docker only on Catalina.
I have a Mac laptop and I would like to work locally on my Mac in a UNIX system for the following reasons:
- to work directly on lxplus can be slow (node dependent). The advantage of lxplus is that it mounts `afs`, `eos`, `cvmfs`... and the HTCondor interface.
- work on SWAN can be slow and it does not mount `afs` - this can be problematic for our MAD-X mask.
- python C-compiled package can have difficulties to be maintained for Mac/Win, e.g., `cpymad` does not work properly on Mac (I manage to install it on Mad and run small lattice, but when I try the larger ones, namely LHC, it fails). I started to use a simple docker as a workaround (the same I used for CAS/JUAS courses), typically I use `jupyter lab` and my experience in term of performance and stability is positive.
- I would like to mount `eos` and `afs` without suffering to much
- I would like that the possibility to share my setup not only via a set of wikis but also with a press-one-button solution. With this spirit, one could prepare and share several conda `env`, e.g,. to track particles, to access NXCALS,...
- one can also couple VSCode directly on the container.
For the moment, I am considering that you have already installed in your Mac (localhost) `afs` - it is quite easy to do so, I tested the docker only on Catalina.
You do not need to install `eos` on your Mac. This is installed inside the container (thanks to the help of Fabio Luchetti).
# To run the docker
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@@ -22,20 +20,26 @@ You do not need to install `eos` on your Mac. This is installed inside the conta
To lauch the docker sterbini/test
```bash
docker run -ti--cap-add SYS_ADMIN --device /dev/fuse gitlab-registry.cern.ch/abpcomputing/sandbox/be-abp-docker:$TAG
where you can find the $TAG you want at https://gitlab.cern.ch/abpcomputing/sandbox/be-abp-docker/container_registry/9443. Probably you want the latest tag.
where you can find the available $commit_tag at https://gitlab.cern.ch/abpcomputing/sandbox/be-abp-docker/container_registry/9443. Probably you want the latest tag.
**At the time of the writing (2021.04.16) the latest tag was fdc1d689.**
**At the time of the writing (2021.05.07) the latest tag was 288bbf2a.**
In case you want to mount a local folder, this has to be **shared** with Docker Docker (I did it with Docker Desktop on my Mac)
The volumes you mount are very important, since only the information you save there will survive after you exit the container.
When the container is starting will try to run the file `/home/jovyan/local_host_home/docker_start.sh`. You can customize it accordingly to your need. You find a template of the file in `/home/jovyan/docker_start.sh`. So please copy it on `/home/jovyan/local_host_home`.
You can run a jupyter notebook server with `jupy`.
