class_docstr: The DataTypes setting assigns data types to measurement names
  
  Imported or extracted metadata might be textual or numeric and
  that interpretation should be up to the user. This setting lets
  the user pick the data type for their metadata.
docstr: Initializer
  
  text - description of the setting
  
  value - initial value (a json-encodable key/value dictionary)
  
  name_fn - a function that returns the current list of feature names
docstr_tok: ["Initializer","text","-","description","of","the","setting","value","-","initial","value","(","a","json-encodable","key\/value","dictionary",")","name_fn","-","a","function","that","returns","the","current","list","of","feature","names"]
code: def __init__(self, text, value="{}", name_fn=None, *args, **kwargs):
      """Initializer
  
      text - description of the setting
  
      value - initial value (a json-encodable key/value dictionary)
  
      name_fn - a function that returns the current list of feature names
      """
      super(DataTypes, self).__init__(text, value, *args, **kwargs)
  
      self.__name_fn = name_fn
  
imports: import json
  from ._setting import Setting
label_desc: Use image node_id 1 to create a new DataTypes object from inherited base classes: Setting with example: obj = DataTypes(text, value, name_fn)