code: def extract_profiles(self, pipeline_name, expose_data=True):
          
          compas_pipe = self.__profile_definition(pipeline_name)
          get_variable = compas_pipe.GEtUserVariable
          if os.path.isdir(self.path+'profiles') is not True:
              os.mkdir(self.path + 'profiles')
          target_dir = self.path + 'profiles'
          if expose_data is True:
              self.profiles[pipeline_name] = {}
          for key in PROFILE_KEYS:
              pipe = self.pipes[pipeline_name]
              pipe['data'][key] = get_variable(PROFILE_KEYS[key]).Variable()
              temp = {key: val for (key, val) in enumerate(pipe['data'][key])}
              try:
                  data = pd.DataFrame(temp, index=pipe['grid'])
              except ValueError:
                  data = pd.DataFrame(temp, index=pipe['non_st_grid'])
              data.columns = self.pipes[pipeline_name]['timesteps']
              data.to_csv('{}/{}-{}.csv'.format(target_dir, pipeline_name, key))
              if expose_data is True:
                  self.profiles[pipeline_name][key] = data
docs: Extract all the profiles of a specific pipeline and exposes the data
          in the namespace