- `*Model`s use the `methods.*.predict()` functions to predict demand
given an order time series generated by `timify.OrderHistory`
- `models.base.ForecastingModelABC` unifies how all `*Model`s work
and implements a caching strategy
- implement three `*Model`s for tactical forecasting, based on the
hets, varima, and rtarima models described in the first research paper
- add overall documentation for `urban_meal_delivery.forecasts` package
- move the fixtures in `tests.forecasts.timify.conftest` to
`tests.forecasts.conftest` and adjust the horizon of the test horizon
from two to three weeks
- move the module
- unify the corresponding tests in `tests.forecasts.methods` sub-package
- make all `predict()` and the `stl()` function round results
- streamline documentation
- the function queries the database and aggregates the ad-hoc orders
by pixel and time steps into a demand time series
- implement "heavy" integration tests for `aggregate_orders()`
- make `pandas` a package dependency
- streamline the `Config`
