Closed jzwart closed 4 years ago
Based on building the ~100 nml
files, it should take about 95 mins to generate all ~19,000 nml
files on one computer locally
@jzwart in the past we've ignored task remake files. It looks like Alison also does this in pipeline three using a similar combiner model. I think you'll want to add 1_nml_tasks_makefile.yml
to .gitignore
?
Agreed w/ Sam on the task makefiles, especially if they are this big. (I think it is fine to include small ones if it makes sense to).
Looks good to me, but wondering which scipiper version are you using? Is it the one w/ the task_combiners? or previous version?
I'm a little unclear if I'm using the combiner version of scipiper
. I updated this morning but with the master
branch. Looks like there is task_combiner
branch of scipiper, which I am not using
@limnoliver what are you using?
I am using the combiner branch for my work on the temperature prep pipeline...I think we should all use the same version, but I understand that the jump to the combiners version is not trivial (hence it is still hanging out on a branch).
If you are willing to make the jump, it will help us simplify some of the solutions and also help us from colliding w/ different versions on different parts of the pipeline.
I was using the latest version of the master branch. But yes, I think we should switch to the combiners branch since @jzwart is using that workflow as well.
Sounds good, I'll switch to the combiners branch
Sorry, I didn't see that this was still open until now. I am working on a similar pattern, but now that we have nhd HR, some of the functions won't work (e.g., populate_base_nml()
)
Resurrecting this pipeline for our lake temperature sprint.
nml
files for running GLM. I don't think it makes sense to create anind
file for these so am just creating these in a tmp dir, which will get rsync-ed to Yeti.