docs: def rados_parse_df(self,
                         result):
          '''
          Parse the result from ansirunner module and save it as a json
          object
          '''
          parsed_results = []
          HEADING = r".*(pool name) *(category) *(KB) *(objects) *(clones)" + \
              " *(degraded) *(unfound) *(rd) *(rd KB) *(wr) *(wr KB)"
  
          HEADING_RE = re.compile(HEADING,
                                  re.IGNORECASE)
  
          dict_keys = ["pool_name", "category", "size_kb", "objects",
                       "clones", "degraded", "unfound", "rd", "rd_kb",
                       "wr", "wr_kb"]
  
          if result['contacted'].keys():
              for node in result['contacted'].keys():
                  df_result = {}
                  nodeobj = result['contacted'][node]
                  df_output = nodeobj['stdout']
                  for line in df_output.splitlines():
                      print "Line: ", line
                      # Skip the heading line.
                      reobj = HEADING_RE.match(line)
                      if not reobj:
                          row = line.split()
                          if len(row) != len(dict_keys):
                              print "line not match: ", line
                              continue
  
                          key_count = 0
                          for column in row:
                              df_result[dict_keys[key_count]] = column
                              key_count += 1
                          print "df_result: ", df_result
                          parsed_results.append(df_result)
  
                      nodeobj['parsed_results'] = parsed_results
  
          return result