# import pandas as pd
#
# from visions import String
# from visions.backends.pandas_be import test_utils
# from visions.relations import InferenceRelation
#
#
# def to_datetime_year_week(series: pd.Series) -> pd.Series:
#     """Convert a series of the format YYYY/UU (year, week) to datetime.
#     A '0' is added as day dummy value, as pandas requires a day value to parse.
#
#     Args:
#         series: the Series to parse
#
#     Returns:
#         A datetime series
#
#     Examples:
#         >>> series = pd.Series(['2018/47', '2018/12', '2018/03'])
#         >>> parsed_series = to_datetime_year_week(series)
#         >>> print(parsed_series.dt.week)
#         0    47
#         1    12
#         2     3
#         dtype: int64
#     """
#     return pd.to_datetime(series + "0", format="%Y/%U%w")
#
#
# def to_datetime_year_month_day(series: pd.Series) -> pd.Series:
#     """Convert a series of the format YYYYMMDD (year, month, day) to datetime.
#
#     Args:
#         series: the Series to parse
#
#     Returns:
#         A datetime series
#
#     Examples:
#         >>> series = pd.Series(['20181201', '20181202', '20181203'])
#         >>> parsed_series = to_datetime_year_week(series)
#         >>> print(parsed_series.dt.day)
#         0    1
#         1    2
#         2    3
#         dtype: int64
#     """
#     return pd.to_datetime(series, format="%Y%m%d")
#
#
# def _to_datetime(func) -> InferenceRelation:
#     return InferenceRelation(
#         relationship=test_utils.coercion_test(func),
#         transformer=func,
#         related_type=String,
#     )
#
#
# def string_to_datetime_year_week() -> InferenceRelation:
#     return _to_datetime(to_datetime_year_week)
#
#
# def string_to_datetime_year_month_day() -> InferenceRelation:
#     return _to_datetime(to_datetime_year_month_day)