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: Get a dictionary of the data type for every name
  
  Using the name function, if present, create a dictionary of name
  to data type (DT_TEXT / INTEGER / FLOAT / NONE)
docstr_tok: ["Get","a","dictionary","of","the","data","type","for","every","name","Using","the","name","function",",","if","present",",","create","a","dictionary","of","name","to","data","type","(","DT_TEXT","\/","INTEGER","\/","FLOAT","\/","NONE",")"]
code: def get_data_types(self):
      """Get a dictionary of the data type for every name
  
      Using the name function, if present, create a dictionary of name
      to data type (DT_TEXT / INTEGER / FLOAT / NONE)
      """
      result = json.loads(self.value_text)
      if self.__name_fn is not None:
          for name in self.__name_fn():
              if name not in result:
                  result[name] = self.DT_TEXT
      return result
  
imports: import json
  from ._setting import Setting
label_desc: Use image node_id 2 for calling the DataTypes obj's underlying member method code with example usage: obj.get_data_types() and returns: result