text: import argparse
  from argparse import RawTextHelpFormatter
  import os
  from datarobot_drum.drum.push import HELP_TEXT
  import sys
  
  from datarobot_drum.drum.description import version
  from datarobot_drum.drum.common import LOG_LEVELS, ArgumentsOptions, RunLanguage
  
  
  class CMRunnerArgsRegistry(object):
      SUBPARSER_DEST_KEYWORD = "subparser_name"
      NEW_SUBPARSER_DEST_KEYWORD = "new_mode"
      _parsers = {}
  
      @staticmethod
      def _tokenize_parser_prog(parser):
          # example:
          # - for score_parser prog is "drum score"
          # - for new_model_parser prog is "drum new model"
          return parser.prog.split(" ")
  
      @staticmethod
      def _reg_arg_version(*parsers):
          for parser in parsers:
              parser.add_argument(
                  "--version", action="version", version="%(prog)s {version}".format(version=version)
              )
  
      @staticmethod
      def _reg_arg_verbose(*parsers):
          for parser in parsers:
              parser.add_argument(
                  "--verbose", action="store_true", default=False, help="Show verbose output"
              )
  
      @staticmethod
      def _is_valid_file(arg):
          abs_path = os.path.abspath(arg)
          if not os.path.exists(arg):
              raise argparse.ArgumentTypeError("The file {} does not exist!".format(arg))
          else:
              return os.path.realpath(abs_path)
  
      @staticmethod
      def _is_valid_dir(arg):
          abs_path = os.path.abspath(arg)
          if not os.path.isdir(arg):
              raise argparse.ArgumentTypeError("The path {} is not a directory!".format(arg))
          else:
              return os.path.realpath(abs_path)
  
      @staticmethod
      def _is_valid_output_dir(arg):
          abs_path = os.path.abspath(arg)
          if not os.path.isdir(arg):
              raise argparse.ArgumentTypeError(
                  "The path {} is not a directory! For custom training models, "
                  "the output directory will consist of the artifacts usable "
                  "for making predictions. ".format(arg)
              )
          else:
              return os.path.realpath(abs_path)
  
      @staticmethod
      def _path_does_non_exist(arg):
          if os.path.exists(arg):
              raise argparse.ArgumentTypeError(
                  "The path {} already exists! Please provide a non existing path!".format(arg)
              )
          return os.path.abspath(arg)
  
      @staticmethod
      def _reg_arg_input(*parsers):
          for parser in parsers:
              parser.add_argument(
                  ArgumentsOptions.INPUT,
                  default=None,
                  required=True,
                  type=CMRunnerArgsRegistry._is_valid_file,
                  help="Path to an input dataset",
              )
  
      @staticmethod
      def _reg_arg_output(*parsers):
          for parser in parsers:
              prog_name_lst = CMRunnerArgsRegistry._tokenize_parser_prog(parser)
              if prog_name_lst[1] == ArgumentsOptions.SCORE:
                  help_message = "Path to a csv file to output predictions"
                  type_callback = os.path.abspath
              elif prog_name_lst[1] == ArgumentsOptions.FIT:
                  help_message = (
                      "DRUM will copy the contents of code_dir and create "
                      "the model artifact in the output folder"
                  )
                  type_callback = CMRunnerArgsRegistry._is_valid_output_dir
              else:
                  raise ValueError(
                      "{} argument should be used only by score and fit parsers!".format(
                          ArgumentsOptions.OUTPUT
                      )
                  )
              parser.add_argument(
                  ArgumentsOptions.OUTPUT, default=None, type=type_callback, help=help_message
              )
  
      @staticmethod
      def _reg_arg_target_feature_and_filename(*parsers):
          for parser in parsers:
              group = parser.add_mutually_exclusive_group(required=True)
              group.add_argument(
                  ArgumentsOptions.TARGET,
                  type=str,
                  required=False,
                  help="Which column to use as the target. Argument is mutually exclusive with {}".format(
                      ArgumentsOptions.TARGET_FILENAME
                  ),
              )
  
              group.add_argument(
                  ArgumentsOptions.TARGET_FILENAME,
                  type=CMRunnerArgsRegistry._is_valid_file,
                  required=False,
                  help="A file containing the target values. Argument is mutually exclusive with {}".format(
                      ArgumentsOptions.TARGET
                  ),
              )
  
      @staticmethod
      def _reg_arg_weights(*parsers):
          for parser in parsers:
              group = parser.add_mutually_exclusive_group(required=False)
              group.add_argument(
                  ArgumentsOptions.WEIGHTS,
                  type=str,
                  required=False,
                  default=None,
                  help="A column name of row weights in your training dataframe. "
                  "Argument is mutually exclusive with {}".format(ArgumentsOptions.WEIGHTS_CSV),
              )
              group.add_argument(
                  ArgumentsOptions.WEIGHTS_CSV,
                  type=CMRunnerArgsRegistry._is_valid_file,
                  required=False,
                  default=None,
                  help="A one column csv file to be parsed as row weights. "
                  "Argument is mutually exclusive with {}".format(ArgumentsOptions.WEIGHTS),
              )
  
      @staticmethod
      def _reg_arg_skip_predict(*parsers):
          for parser in parsers:
              parser.add_argument(
                  ArgumentsOptions.SKIP_PREDICT,
                  required=False,
                  default=False,
                  action="store_true",
                  help="By default we will attempt to predict using your model, but we give you the"
                  "option to turn this off",
              )
  
      @staticmethod
      def _reg_arg_pos_neg_labels(*parsers):
          def are_both_labels_present(arg):
              error_message = (
                  "\nError - for binary classification case, "
                  "both positive and negative class labels have to be provided. \n"
                  "See --help option for more information"
              )
              labels = [ArgumentsOptions.POSITIVE_CLASS_LABEL, ArgumentsOptions.NEGATIVE_CLASS_LABEL]
              if not all([x in sys.argv for x in labels]):
                  raise argparse.ArgumentTypeError(error_message)
              return arg
  
          for parser in parsers:
              fit_intuit_message = ""
              prog_name_lst = CMRunnerArgsRegistry._tokenize_parser_prog(parser)
              if prog_name_lst[1] == ArgumentsOptions.FIT:
                  fit_intuit_message = "If you do not provide these labels, but your dataset is classification, DRUM will choose the labels for you"
  
              parser.add_argument(
                  ArgumentsOptions.POSITIVE_CLASS_LABEL,
                  default=None,
                  type=are_both_labels_present,
                  help="Positive class label for a binary classification case. " + fit_intuit_message,
              )
              parser.add_argument(
                  ArgumentsOptions.NEGATIVE_CLASS_LABEL,
                  default=None,
                  type=are_both_labels_present,
                  help="Negative class label for a binary classification case. " + fit_intuit_message,
              )
  
      @staticmethod
      def _reg_arg_code_dir(*parsers):
          for parser in parsers:
              prog_name_lst = CMRunnerArgsRegistry._tokenize_parser_prog(parser)
              if prog_name_lst[1] == ArgumentsOptions.NEW:
                  help_message = "Directory to use for creating the new template"
                  type_callback = CMRunnerArgsRegistry._path_does_non_exist
              else:
                  help_message = "Custom model code dir"
                  type_callback = CMRunnerArgsRegistry._is_valid_dir
  
              parser.add_argument(
                  "-cd",
                  ArgumentsOptions.CODE_DIR,
                  default=None,
                  required=True,
                  type=type_callback,
                  help=help_message,
              )
  
      @staticmethod
      def _reg_arg_address(*parsers):
          for parser in parsers:
              parser.add_argument(
                  ArgumentsOptions.ADDRESS,
                  default=None,
                  required=True,
                  help="Prediction server address host[:port]. Default Flask port is: 5000",
              )
  
      @staticmethod
      def _reg_arg_logging_level(*parsers):
          for parser in parsers:
              parser.add_argument(
                  ArgumentsOptions.LOGGING_LEVEL,
                  required=False,
                  choices=list(LOG_LEVELS.keys()),
                  default="warning",
                  help="Logging level to use",
              )
  
      @staticmethod
      def _reg_arg_docker(*parsers):
          for parser in parsers:
              prog_name_lst = CMRunnerArgsRegistry._tokenize_parser_prog(parser)
              parser.add_argument(
                  ArgumentsOptions.DOCKER,
                  default=None,
                  required=False,
                  help="Docker image to use to run {} in the {} mode, "
                  "or a directory, containing a Dockerfile, "
                  "which can be built into a docker image. ".format(
                      ArgumentsOptions.MAIN_COMMAND, prog_name_lst[1]
                  ),
              )
  
      @staticmethod
      def _reg_arg_threaded(*parsers):
          for parser in parsers:
              parser.add_argument(
                  ArgumentsOptions.THREADED,
                  action="store_true",
                  default=False,
                  help="Run prediction server in threaded mode",
              )
  
      @staticmethod
      def _reg_arg_show_perf(*parsers):
          for parser in parsers:
              parser.add_argument(
                  "--show-perf", action="store_true", default=False, help="Show performance stats"
              )
  
      @staticmethod
      def _reg_arg_in_perf_mode_internal(*parsers):
          for parser in parsers:
              parser.add_argument(
                  "--in-perf-mode-internal",
                  action="store_true",
                  default=False,
                  help="Provide indication that {} is called as part of a performance test run ".format(
                      ArgumentsOptions.MAIN_COMMAND
                  ),
              )
  
      @staticmethod
      def _reg_arg_samples(*parsers):
          for parser in parsers:
              parser.add_argument("-s", "--samples", type=int, default=None, help="Number of samples")
  
      @staticmethod
      def _reg_arg_iterations(*parsers):
          for parser in parsers:
              parser.add_argument(
                  "-i", "--iterations", type=int, default=None, help="Number of iterations"
              )
  
      @staticmethod
      def _reg_arg_timeout(*parsers):
          for parser in parsers:
              parser.add_argument(
                  ArgumentsOptions.TIMEOUT, type=int, default=180, help="Test case timeout"
              )
  
      @staticmethod
      def _reg_arg_in_server(*parsers):
          for parser in parsers:
              parser.add_argument(
                  "--in-server",
                  action="store_true",
                  default=False,
                  help="Show performance inside server",
              )
  
      @staticmethod
      def _reg_arg_url(*parsers):
          for parser in parsers:
              parser.add_argument(
                  "--url", default=None, help="Run performance against the given prediction server"
              )
  
      @staticmethod
      def _reg_arg_language(*parsers):
          for parser in parsers:
              langs = [e.value for e in RunLanguage]
              prog_name_lst = CMRunnerArgsRegistry._tokenize_parser_prog(parser)
              if prog_name_lst[1] == ArgumentsOptions.NEW:
                  langs.remove(RunLanguage.JAVA.value)
                  required_val = True
              else:
                  required_val = False
  
              parser.add_argument(
                  ArgumentsOptions.LANGUAGE,
                  choices=langs,
                  default=None,
                  required=required_val,
                  help="Language to use for the new model/env template to create",
              )
  
      @staticmethod
      def _reg_arg_num_rows(*parsers):
          for parser in parsers:
              parser.add_argument(
                  ArgumentsOptions.NUM_ROWS,
                  default="ALL",
                  help="Number of rows to use for testing the fit functionality. "
                  "Set to ALL to use all rows. Default is 100",
              )
  
      @staticmethod
      def _reg_arg_with_error_server(*parsers):
          for parser in parsers:
              parser.add_argument(
                  "--with-error-server",
                  action="store_true",
                  default=False,
                  help="Start server even if pipeline initialization fails.",
              )
  
      @staticmethod
      def _reg_arg_show_stacktrace(*parsers):
          for parser in parsers:
              parser.add_argument(
                  "--show-stacktrace",
                  action="store_true",
                  default=False,
                  help="Show stacktrace when error happens.",
              )
  
      @staticmethod
      def get_arg_parser():
          parser = argparse.ArgumentParser(description="Run user model")
          CMRunnerArgsRegistry._parsers[ArgumentsOptions.MAIN_COMMAND] = parser
          CMRunnerArgsRegistry._reg_arg_version(parser)
          subparsers = parser.add_subparsers(
              dest=CMRunnerArgsRegistry.SUBPARSER_DEST_KEYWORD, help="Commands"
          )
  
          batch_parser = subparsers.add_parser(
              ArgumentsOptions.SCORE, help="Run predictions in batch mode"
          )
          fit_parser = subparsers.add_parser(ArgumentsOptions.FIT, help="Fit your model to your data")
          parser_perf_test = subparsers.add_parser(
              ArgumentsOptions.PERF_TEST, help="Run performance tests"
          )
          validation_parser = subparsers.add_parser(
              ArgumentsOptions.VALIDATION, help="Run validation checks"
          )
          server_parser = subparsers.add_parser(
              ArgumentsOptions.SERVER, help="Run predictions in server"
          )
          new_parser = subparsers.add_parser(
              ArgumentsOptions.NEW,
              description="Create new model/env template",
              help="Create new model/env template",
          )
          new_subparsers = new_parser.add_subparsers(
              dest=CMRunnerArgsRegistry.NEW_SUBPARSER_DEST_KEYWORD, help="Commands"
          )
          CMRunnerArgsRegistry._parsers[ArgumentsOptions.NEW] = new_parser
  
          new_model_parser = new_subparsers.add_parser(
              ArgumentsOptions.NEW_MODEL, help="Create a new modeling code directory template"
          )
          push_parser = subparsers.add_parser(
              ArgumentsOptions.PUSH,
              help="Add your modeling code into DataRobot",
              description=HELP_TEXT,
              formatter_class=RawTextHelpFormatter,
          )
  
          # Note following args are not supported for perf-test, thus set as default
          parser_perf_test.set_defaults(logging_level="warning", verbose=False)
          validation_parser.set_defaults(logging_level="warning", verbose=False)
  
          CMRunnerArgsRegistry._reg_arg_code_dir(
              batch_parser,
              parser_perf_test,
              server_parser,
              fit_parser,
              new_model_parser,
              validation_parser,
              push_parser,
          )
          CMRunnerArgsRegistry._reg_arg_verbose(
              batch_parser, server_parser, fit_parser, new_parser, new_model_parser, push_parser
          )
          CMRunnerArgsRegistry._reg_arg_input(
              batch_parser, parser_perf_test, fit_parser, validation_parser
          )
          CMRunnerArgsRegistry._reg_arg_pos_neg_labels(
              batch_parser, parser_perf_test, server_parser, fit_parser, validation_parser
          )
          CMRunnerArgsRegistry._reg_arg_logging_level(
              batch_parser, server_parser, fit_parser, new_parser, new_model_parser, push_parser
          )
          CMRunnerArgsRegistry._reg_arg_docker(
              batch_parser,
              parser_perf_test,
              server_parser,
              fit_parser,
              validation_parser,
              push_parser,
          )
          CMRunnerArgsRegistry._reg_arg_output(batch_parser, fit_parser)
          CMRunnerArgsRegistry._reg_arg_show_perf(batch_parser, server_parser)
  
          CMRunnerArgsRegistry._reg_arg_target_feature_and_filename(fit_parser)
          CMRunnerArgsRegistry._reg_arg_weights(fit_parser)
          CMRunnerArgsRegistry._reg_arg_skip_predict(fit_parser)
          CMRunnerArgsRegistry._reg_arg_num_rows(fit_parser)
  
          CMRunnerArgsRegistry._reg_arg_samples(parser_perf_test)
          CMRunnerArgsRegistry._reg_arg_iterations(parser_perf_test)
          CMRunnerArgsRegistry._reg_arg_timeout(parser_perf_test)
          CMRunnerArgsRegistry._reg_arg_in_server(parser_perf_test)
          CMRunnerArgsRegistry._reg_arg_url(parser_perf_test)
  
          CMRunnerArgsRegistry._reg_arg_address(server_parser)
          CMRunnerArgsRegistry._reg_arg_threaded(server_parser)
          CMRunnerArgsRegistry._reg_arg_in_perf_mode_internal(server_parser)
          CMRunnerArgsRegistry._reg_arg_with_error_server(server_parser)
  
          CMRunnerArgsRegistry._reg_arg_language(
              new_model_parser, server_parser, batch_parser, parser_perf_test, validation_parser
          )
  
          CMRunnerArgsRegistry._reg_arg_show_stacktrace(
              batch_parser,
              parser_perf_test,
              server_parser,
              fit_parser,
              validation_parser,
              new_model_parser,
          )
  
          return parser
  
      @staticmethod
      def verify_options(options):
          if not options.subparser_name:
              CMRunnerArgsRegistry._parsers[ArgumentsOptions.MAIN_COMMAND].print_help()
              exit(1)
          elif options.subparser_name == ArgumentsOptions.NEW:
              if not options.new_mode:
                  CMRunnerArgsRegistry._parsers[ArgumentsOptions.NEW].print_help()
                  exit(1)
  