old_contents: from hashlib import md5
  
  from .datasource import Datasource
  from .pandas_datasource import PandasDatasource
  from .sqlalchemy_datasource import SqlAlchemyDatasource
  from .sparkdf_datasource import SparkDFDatasource
  from ..util import load_class
  
  
  def anonymize_datasource_class_name(class_name, module_name):
      try:
          class_ = load_class(class_name=class_name, module_name=module_name)
  
          # Get a baseline:
          anonymized_class_info = dict()
          if issubclass(class_, Datasource):
              anonymized_class_info["parent_class"] = "Datasource"
          else:
              anonymized_class_info["parent_class"] = "__not_datasource__"
              anonymized_class_info["custom_class"] = md5(class_name).hexdigest()
  
          if issubclass(class_, PandasDatasource):
              anonymized_class_info["parent_class"] = "PandasDatasource"
              if not class_ == PandasDatasource:
                  anonymized_class_info["custom_class"] = md5(class_name).hexdigest()
          elif issubclass(class_, SqlAlchemyDatasource):
              anonymized_class_info["parent_class"] = "SqlAlchemyDatasource"
              if not class_ == SqlAlchemyDatasource:
                  anonymized_class_info["custom_class"] = md5(class_name).hexdigest()
          elif issubclass(class_, SparkDFDatasource):
              anonymized_class_info["parent_class"] = "SqlAlchemyDatasource"
              if not class_ == SparkDFDatasource:
                  anonymized_class_info["custom_class"] = md5(class_name).hexdigest()
          return anonymized_class_info
      except AttributeError:
          return {"parent_class": "__unrecognized__", "custom_class": md5(class_name).hexdigest()}
  
new_contents: from hashlib import md5
  
  from .datasource import Datasource
  from .pandas_datasource import PandasDatasource
  from .sqlalchemy_datasource import SqlAlchemyDatasource
  from .sparkdf_datasource import SparkDFDatasource
  from ..util import load_class
  
  
  def anonymize_datasource_class_name(class_name, module_name):
      try:
          class_ = load_class(class_name=class_name, module_name=module_name)
  
          # Get a baseline:
          anonymized_class_info = dict()
          if issubclass(class_, Datasource):
              anonymized_class_info["parent_class"] = "Datasource"
          else:
              anonymized_class_info["parent_class"] = "__not_datasource__"
              anonymized_class_info["custom_class"] = md5(class_name).hexdigest()
  
          if issubclass(class_, PandasDatasource):
              anonymized_class_info["parent_class"] = "PandasDatasource"
              if not class_ == PandasDatasource:
                  anonymized_class_info["custom_class"] = md5(class_name).hexdigest()
          elif issubclass(class_, SqlAlchemyDatasource):
              anonymized_class_info["parent_class"] = "SqlAlchemyDatasource"
              if not class_ == SqlAlchemyDatasource:
                  anonymized_class_info["custom_class"] = md5(class_name).hexdigest()
          elif issubclass(class_, SparkDFDatasource):
              anonymized_class_info["parent_class"] = "SparkDFDatasource"
              if not class_ == SparkDFDatasource:
                  anonymized_class_info["custom_class"] = md5(class_name).hexdigest()
          return anonymized_class_info
      except AttributeError:
          return {"parent_class": "__unrecognized__", "custom_class": md5(class_name).hexdigest()}
  
subject: Fix anonymize_datasource_name