I was not aware of the links you shared pointing out the inconsistencies. I wonder how the authors themselves respond about these reddit posts (if at all?). Thank you for sharing!
Despite that, it does have some implementations that made it stick out for me across all other languages, such as the fit / transform / predict API spread across the library, and the useage of joblib as back-end for speedup - this allows their models to be easily scaleable on clusters with the use of Dask.
I still have confidence that their most used functions (e.g. RandomForest) and models are still correctly implemented and provide great value in that regard.