Feat/config engine

[viktorbeck98]

First version for the persistency and the configuration engine. The core of the configuration engine is integrated in the persistency. So far I implemented:

• A generic persistency class for event-based purposes that incorporates interchangable data structures that are defined at definition of the persistency object.
• Multiple data structures that can be injected into the persistency class based on the use case, such as:
  • EventDataFrame: best for developers to get an event-type-separated view of the data (based on pandas)
  • ChunkedEventDataFrame: similar as above but is fit for online processing (based on polars). Technically production-ready but since it stores all incoming data it is still RAM heavy. Howerver, in the future, for a storage component we could connect this to a database handling the storage.
  • EventVariableTracker: is also a data structure just as the two above but only stores series of persitency changes in the most efficient way (run-length encoding - RLE) and the set of unique values per variable. Persistency changes can thereby be seen as a feature extracted from the data. Detectors like the NewValueDetector, ComboDetector, EventSequenceDetector and possibly more can use this as the underlying structure.
• A RLU set implementation for handling outdated values (not yet integrated into persitency class)

Some todos:

• Integrate persitency class into the existing detectors (I am on it already)
• implement the functionality to remove outdated values from persistency

[ipmach]

looking good so far!

But we need to discuss about the notebooks, because I dont know if we want them in the main branch. They present multiple issues:

• Code traceability is pretty bad. As the files do not have human readable code. (it is written in Jupyter language).
• They are not tested in the main pipeline, so they have a higher risk of not working in the next versions.