code: def test_raises_error_when_variables_not_datetime(df_datetime):
      # asking for not datetime variable(s)
      with pytest.raises(TypeError):
          DatetimeFeatures(variables=["Age"]).fit(df_datetime)
      with pytest.raises(TypeError):
          DatetimeFeatures(variables=["Name", "Age", "date_obj1"]).fit(
              df_datetime
          )
      with pytest.raises(TypeError):
          DatetimeFeatures(variables="index").fit(df_datetime)
      # passing a df that contains no datetime variables
      with pytest.raises(ValueError):
          DatetimeFeatures().fit(df_datetime[["Name", "Age"]])
  
imports: import numpy
  import pandas
  import pytest
  from sklearn.exceptions import NotFittedError
  from sklearn.pipeline import Pipeline
  from feature_engine.datetime import DatetimeFeatures
  from feature_engine.datetime._datetime_constants import FEATURES_DEFAULT, FEATURES_SUFFIXES, FEATURES_SUPPORTED
label_desc: Use image node_id 6 for calling a global function with example usage: test_raises_error_when_variables_not_datetime(df_datetime) without return types