code: def check_preprocessing(preprocessing=None):
      """
      Check that all transformation of the preprocessing are supported.
  
      Parameters
      ----------
      preprocessing: category_encoders, ColumnTransformer, list, dict, optional (default: None)
          The processing apply to the original data
      """
      if preprocessing is not None:
          list_preprocessing = preprocessing_tolist(preprocessing)
          use_ct, use_ce = check_transformers(list_preprocessing)
          return use_ct, use_ce
  
imports: import copy
  import numpy
  import pandas
  from shapash.utils.category_encoder_backend import no_dummies_category_encoder, supported_category_encoder, dummies_category_encoder
  from shapash.utils.columntransformer_backend import no_dummies_sklearn, supported_sklearn
  from shapash.utils.model import extract_features_model
  from shapash.utils.model_synoptic import dict_model_feature
  from shapash.utils.transform import preprocessing_tolist, check_transformers
  from shapash.utils.columntransformer_backend import columntransformer, get_feature_names, get_list_features_names
label_desc: Use image node_id 1 for calling a global function with example usage: check_preprocessing(preprocessing) and returns: use_ct,  use_ce