text: import numpy as np
  from sklearn.compose import make_column_selector, make_column_transformer
  from sklearn.pipeline import make_pipeline
  from sklearn.preprocessing import RobustScaler, OneHotEncoder
  from sklearn.impute import SimpleImputer
  
  
  def basic_model_pipeline(
      model, num_scaler="robust", cat_encoder="ohe", imputer="simple"
  ):
      """From given sklearn style model make simple pipeline, along with suitable transformers
  
      Args:
          model (_type_): _description_
          num_scaler (str, optional): _description_. Defaults to 'robust'.
          cat_encoder (str, optional): _description_. Defaults to 'ohe'.
          imputer (str, optional): _description_. Defaults to 'simple'.
      """
  
      col_transformer = make_column_transformer(
          (RobustScaler(), make_column_selector(dtype_include=np.number)),
          (OneHotEncoder(), make_column_selector(dtype_exclude=np.number)),
      )
      pipeline = make_pipeline(SimpleImputer(), col_transformer, model)
      return pipeline
  