code: def test_raises_error_when_transform_df_with_different_n_variables(
      df_datetime,
  ):
      transformer = DatetimeFeatures()
      transformer.fit(df_datetime)
      # different number of columns than the df used to fit
      with pytest.raises(ValueError):
          transformer.transform(df_datetime[vars_dt])
  
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 10 for calling a global function with example usage: test_raises_error_when_transform_df_with_different_n_variables(df_datetime) without return types