You can save it as a dataset and then fetch it during run time, or am i missing something?

Could I simply just reference the files by name and pass in a string such as ~/.clearml/my_file.json

After proving we can run our training, I would then advise we update our code base

This would be a short term solution as we build a proof of concept

ok, but if you were to run it from a different machine (or a different user!) it wouldn’t work

ok good to know

Sure. My git repo myProject.git does not have file.json checked into VCS. I'd like to add this file at experiment runtime or equivalent.

I assumed I would need to upload it and then reference it somehow?

do I have to fetch it via code? I was hoping to not modify my scripts

you would, but I’d advise against it, since that is not the intended way

ClearML downloads/caches datasets to ~/.clearml/ folder so yes, you need to modify your code.
dataset_folder = Dataset.get(project_name=, dataset_name=, version=).get_local_copy() file_json_path = os.path.join(dataset_folder, 'file.json')

I’m afaid I don’t think there is a way to go around this without modifying your code.

Can you please elaborate on what you mean?

so it caches to ~/.clearml/ any files that are under the same project name?

I wouldn't be able to pass in ~/.clearml/cache/storage_manager/datasets/ds_{ds_id}/my_file.json as an argument?

Or is there an easier way?

Is not direcly cached in the ~/.clearml folder. There are some directories inside (one for storage, one for pip, another for venvs, etc.

So in your case it would be stored in ~/.clearml/cache/storage_manager/datasets/ds_{ds_id}/my_file.json

Thanks!