preprocessing.exog_builder.ExogBuilder

preprocessing.exog_builder.ExogBuilder(periods=None, country_code=None)

Builds a set of exogenous features for a given date range.

This builder combines temporal features (day of year, day of week, hour, etc.) with cyclical features encoded via RepeatingBasisFunctions and optional holiday indicators.

Attributes

Name	Type	Description
periods	List[Period]	List of periodic features to encode.
country_code	Optional[str]	Country code for holiday lookups.
holidays_list	Optional[`holidays`.`HolidayBase`]	List of holidays for the specified country.

Examples

>>> import pandas as pd
>>> from spotforecast2_safe.data.data import Period
>>> from spotforecast2_safe.preprocessing.exog_builder import ExogBuilder
>>> periods = [Period(name="hour", n_periods=24, column="hour", input_range=(0, 23))]
>>> builder = ExogBuilder(periods=periods, country_code="DE")
>>> start = pd.Timestamp("2025-01-01", tz="UTC")
>>> end = pd.Timestamp("2025-01-02", tz="UTC")
>>> exog = builder.build(start, end)
>>> exog.shape[1] > 0
True

Methods

Name	Description
build	Build the exogenous feature DataFrame for a date range.

build

preprocessing.exog_builder.ExogBuilder.build(start_date, end_date)

Build the exogenous feature DataFrame for a date range.

The generated DataFrame has an hourly frequency.

Parameters

Name	Type	Description	Default
start_date	pd.Timestamp	Start of the date range (inclusive).	required
end_date	pd.Timestamp	End of the date range (inclusive).	required

Returns

Name	Type	Description
	pd.DataFrame	pd.DataFrame: DataFrame containing exogenous features.

Raises

Name	Type	Description
	ValueError	If the date range is invalid.

Examples

>>> import pandas as pd
>>> from spotforecast2_safe.data.data import Period
>>> from spotforecast2_safe.preprocessing.exog_builder import ExogBuilder
>>> periods = [Period(name="hour", n_periods=24, column="hour", input_range=(0, 23))]
>>> builder = ExogBuilder(periods=periods, country_code="DE")
>>> start = pd.Timestamp("2025-01-01", tz="UTC")
>>> end = pd.Timestamp("2025-01-02", tz="UTC")
>>> exog = builder.build(start, end)
>>> exog.shape[1] > 0
True