[Feature] Use of DeepCave API with data loaded in memory

[eddiebergman]

I'm trying to use the configurator footprint part of DeepCave and I have all the data in one big parquet file and a ConfigSpace object.

Just using the API, i.e. the code parts of DeepCave require Run which in addition require some convertor. All of these concepts rely on all my data being on disk for caching and hashing etc. This makes it very difficult to go from my loaded data to being able to use the plugins of DeepCave through python.

Admittedly this is likely not a common use case, but it still is one. Not sure how to rectify this other than to separate concerns about processing data from a run with the actual logic of hashing and viewing the filesystem.