I've had someone in a team implement feature engineering using tsfresh. It lead to a malignantly under-performing, complicated heap of spaghetti that was a nightmare to get into production. Weird API, slow code, little added value over simple features found in a day of manual exploration.

Person doing the implementation wasn't a rock star coder so we couldn't fix the performance and complexity issues in time; it was left it out of the releas. Maybe with more expertise, tsfresh can add value. The experience was pretty off-putting for me, all in all. Maybe others have different experiences?

I've tried it a number of times, and had a similar experience. The whole stack is orders of magnitudes slower to compute compared to "simple" features (i.e. rolling averages), without showing real predictive improvements.

Thanks for the elaboration. Good to know someone had a similar experience.

Actually, I had a similar off-putting experience with tsfresh. I just thought it was due to me not understanding how to use it properly. The API is indeed pretty weird.