code: def preprocessing_tolist(preprocess):
      """
      Transform preprocess into a list, if preprocess contains a dict, transform the dict into a list of dict.
  
      Parameters
      ----------
      preprocess : category_encoders, ColumnTransformer, list, dict, optional (default: None)
          The processing apply to the original data
  
      Returns
      -------
      List
          A list containing all preprocessing.
      """
      list_encoding = (
          preprocess if isinstance(preprocess, list) else [preprocess]
      )
      list_encoding = [
          [x] if isinstance(x, dict) else x for x in list_encoding
      ]
      return list_encoding
  
file_path: shapash/shapash/utils/transform.py
imports: from shapash.utils.columntransformer_backend import columntransformer, inv_transform_ct, supported_sklearn, transform_ct, get_col_mapping_ct
  from shapash.utils.category_encoder_backend import transform_ce, inv_transform_ce, supported_category_encoder, get_col_mapping_ce
  import re
  import numpy
  import pandas
label_desc: Use image node_id 3 for calling a global function with example usage: preprocessing_tolist(preprocess) and returns: list_encoding