kokikwbt/predictive-maintenance ? reverse-engineered prompt

Build me a small Python project that makes it easy to work with predictive maintenance datasets.

I want to be able to drop the datasets folder into my workspace, import the package, and then load each dataset with a simple call like datasets.ufd.load_data() or similar. It should also be able to generate a summary PDF for a dataset so I can quickly see the data before modeling. Please include support for the main predictive maintenance use cases like time series, anomaly detection, and remaining useful life style data, with a few dataset specific loaders already set up.

Keep it practical and easy to run in notebooks, since I’ll probably explore the data there first. If anything is unclear about a dataset format, look up the current docs online if you need to. I mainly want a clean, ready to use starting point for experimenting with these public maintenance datasets without having to wire everything together myself.