Can you please elaborate on what you mean?

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

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')

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

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.

ok good to know

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

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

Thanks!

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

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

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

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

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

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

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

Or is there an easier way?

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