Check out my top level comment in this thread for a (hopefully clear) example. Sometimes you can rephrase a time series problem into boring classical regression.

It can make the implementation and maintainability of a codebase better (IMHO), without sacrificing predictive power.

Create features for day of week, day of year, month of year, lagged values of y, lagged values of y for each period (eg: 1, 2, 3 weeks and years ago etc). You then predict forward 1 time step at a time.