



"""simple docstring"""







import os
from argparse import ArgumentParser
from pathlib import Path
from shutil import copyfile
from typing import List

from datasets import config
from datasets.builder import DatasetBuilder
from datasets.commands import BaseDatasetsCLICommand
from datasets.download.download_config import DownloadConfig
from datasets.download.download_manager import DownloadMode
from datasets.load import dataset_module_factory, import_main_class
from datasets.utils.info_utils import VerificationMode

def 							UpperCamelCase_       (       lowerCAmelCase__ :							Tuple       ,  **lowerCAmelCase__ :							Any		)		->  Any:

  """simple docstring"""




  return RunBeamCommand(
      args.dataset       ,  args.name       ,  args.cache_dir       ,  args.beam_pipeline_options       ,  args.data_dir       ,  args.all_configs       ,  args.save_info or args.save_infos       ,  args.ignore_verifications       ,  args.force_redownload       ,  **lowerCAmelCase__       ,  )







class  UpperCamelCase__  (      lowercase_    ):




      """simple docstring"""




      @staticmethod
      def 	SCREAMING_SNAKE_CASE__					( SCREAMING_SNAKE_CASE_							: ArgumentParser			):
        lowerCAmelCase_  :							Optional[Any]								=					parser.add_parser('run_beam'       ,     help='Run a Beam dataset processing pipeline'			)
        run_beam_parser.add_argument('dataset'       ,     type=SCREAMING_SNAKE_CASE_       ,     help='Name of the dataset to download'			)
        run_beam_parser.add_argument('--name'       ,     type=SCREAMING_SNAKE_CASE_       ,     default=SCREAMING_SNAKE_CASE_       ,     help='Dataset config name'			)
        run_beam_parser.add_argument(
            '--cache_dir'       ,     type=SCREAMING_SNAKE_CASE_       ,     default=SCREAMING_SNAKE_CASE_       ,     help='Cache directory where the datasets are stored'       ,     )
        run_beam_parser.add_argument(
            '--beam_pipeline_options'       ,     type=SCREAMING_SNAKE_CASE_       ,     default=''       ,     help='Beam pipeline options, separated by commas. Example:: `--beam_pipeline_options=job_name=my-job,project=my-project`'       ,     )
        run_beam_parser.add_argument(
            '--data_dir'       ,     type=SCREAMING_SNAKE_CASE_       ,     default=SCREAMING_SNAKE_CASE_       ,     help='Can be used to specify a manual directory to get the files from'       ,     )
        run_beam_parser.add_argument('--all_configs'       ,     action='store_true'       ,     help='Test all dataset configurations'			)
        run_beam_parser.add_argument('--save_info'       ,     action='store_true'       ,     help='Save the dataset infos file'			)
        run_beam_parser.add_argument(
            '--ignore_verifications'       ,     action='store_true'       ,     help='Run the test without checksums and splits checks'			)
        run_beam_parser.add_argument('--force_redownload'       ,     action='store_true'       ,     help='Force dataset redownload'			)
        # aliases
        run_beam_parser.add_argument('--save_infos'       ,     action='store_true'       ,     help='alias for save_info'			)
        run_beam_parser.set_defaults(func=SCREAMING_SNAKE_CASE_			)



      def __init__( self							: List[str]       ,     SCREAMING_SNAKE_CASE_							: str       ,     SCREAMING_SNAKE_CASE_							: str       ,     SCREAMING_SNAKE_CASE_							: str       ,     SCREAMING_SNAKE_CASE_							: str       ,     SCREAMING_SNAKE_CASE_							: str       ,     SCREAMING_SNAKE_CASE_							: bool       ,     SCREAMING_SNAKE_CASE_							: bool       ,     SCREAMING_SNAKE_CASE_							: bool       ,     SCREAMING_SNAKE_CASE_							: bool       ,     **SCREAMING_SNAKE_CASE_							: List[Any]       ,     ):
        lowerCAmelCase_  :							Optional[int]								=					dataset
        lowerCAmelCase_  :							str								=					name
        lowerCAmelCase_  :							Any								=					cache_dir
        lowerCAmelCase_  :							Tuple								=					beam_pipeline_options
        lowerCAmelCase_  :							Dict								=					data_dir
        lowerCAmelCase_  :							Optional[int]								=					all_configs
        lowerCAmelCase_  :							Union[str, Any]								=					save_infos
        lowerCAmelCase_  :							Tuple								=					ignore_verifications
        lowerCAmelCase_  :							List[str]								=					force_redownload
        lowerCAmelCase_  :							Dict								=					config_kwargs





      def 	SCREAMING_SNAKE_CASE__					( self							: List[Any]			):
        import apache_beam as beam

        if self._name is not None and self._all_configs:
          print('Both parameters `name` and `all_configs` can\'t be used at once.'			)
          exit(1			)
        lowerCAmelCase_		,lowerCAmelCase_  :							Dict								=					self._dataset, self._name
        lowerCAmelCase_  :							Tuple								=					dataset_module_factory(SCREAMING_SNAKE_CASE_			)
        lowerCAmelCase_  :							Any								=					import_main_class(dataset_module.module_path			)
        lowerCAmelCase_  :							List[DatasetBuilder]								=					[]
        if self._beam_pipeline_options:
          lowerCAmelCase_  :							Dict								=					beam.options.pipeline_options.PipelineOptions(
              flags=[F"--{opt.strip()}" for opt in self._beam_pipeline_options.split(','			) if opt]			)
        else:
          lowerCAmelCase_  :							int								=					None
        if self._all_configs and len(builder_cls.BUILDER_CONFIGS			) > 0:
          for builder_config in builder_cls.BUILDER_CONFIGS:
            builders.append(
                builder_cls(
                    config_name=builder_config.name       ,     data_dir=self._data_dir       ,     hash=dataset_module.hash       ,     beam_options=SCREAMING_SNAKE_CASE_       ,     cache_dir=self._cache_dir       ,     base_path=dataset_module.builder_kwargs.get('base_path'			)       ,     )			)
        else:
          builders.append(
              builder_cls(
                  config_name=SCREAMING_SNAKE_CASE_       ,     data_dir=self._data_dir       ,     beam_options=SCREAMING_SNAKE_CASE_       ,     cache_dir=self._cache_dir       ,     base_path=dataset_module.builder_kwargs.get('base_path'			)       ,     **self._config_kwargs       ,     )			)

        for builder in builders:
          builder.download_and_prepare(
              download_mode=DownloadMode.REUSE_CACHE_IF_EXISTS
              if not self._force_redownload
              else DownloadMode.FORCE_REDOWNLOAD       ,     download_config=DownloadConfig(cache_dir=config.DOWNLOADED_DATASETS_PATH			)       ,     verification_mode=VerificationMode.NO_CHECKS
              if self._ignore_verifications
              else VerificationMode.ALL_CHECKS       ,     try_from_hf_gcs=SCREAMING_SNAKE_CASE_       ,     )
          if self._save_infos:
            builder._save_infos()

        print('Apache beam run successful.'			)

        # If save_infos=True, the dataset infos file is created next to the loaded module file.
        # Let's move it to the original directory of the dataset script, to allow the user to
        # upload them on S3 at the same time afterwards.
        if self._save_infos:
          lowerCAmelCase_  :							str								=					os.path.join(builder_cls.get_imported_module_dir()       ,     config.DATASETDICT_INFOS_FILENAME			)

          lowerCAmelCase_  :							int								=					Path(SCREAMING_SNAKE_CASE_			).name + '.py'

          lowerCAmelCase_  :							List[str]								=					os.path.join(SCREAMING_SNAKE_CASE_       ,     SCREAMING_SNAKE_CASE_			)
          if os.path.isfile(SCREAMING_SNAKE_CASE_			):
            lowerCAmelCase_  :							Union[str, Any]								=					os.path.dirname(SCREAMING_SNAKE_CASE_			)
          elif os.path.isfile(SCREAMING_SNAKE_CASE_			):
            lowerCAmelCase_  :							List[Any]								=					path
          else:  # in case of a remote dataset
            print(F"Dataset Infos file saved at {dataset_infos_path}"			)
            exit(1			)

          # Move datasetinfo back to the user
          lowerCAmelCase_  :							Optional[int]								=					os.path.join(SCREAMING_SNAKE_CASE_       ,     config.DATASETDICT_INFOS_FILENAME			)
          copyfile(SCREAMING_SNAKE_CASE_       ,     SCREAMING_SNAKE_CASE_			)
          print(F"Dataset Infos file saved at {user_dataset_infos_path}"			)










"""simple docstring"""







import unittest
from timeit import timeit

def 							UpperCamelCase_       (       lowerCAmelCase__ :							int       ,  lowerCAmelCase__ :							int		)		->  int:

  """simple docstring"""




  lowerCAmelCase_  :							Any								=					first_num if first_num >= second_num else second_num
  lowerCAmelCase_  :							Union[str, Any]								=					max_num
  while (common_mult % first_num > 0) or (common_mult % second_num > 0):
    common_mult += max_num
  return common_mult

def 							UpperCamelCase_       (       lowerCAmelCase__ :							int       ,  lowerCAmelCase__ :							int		)		->  int:

  """simple docstring"""




  return b if a == 0 else greatest_common_divisor(b % a       ,  lowerCAmelCase__		)

def 							UpperCamelCase_       (       lowerCAmelCase__ :							int       ,  lowerCAmelCase__ :							int		)		->  int:

  """simple docstring"""




  return first_num // greatest_common_divisor(lowerCAmelCase__       ,  lowerCAmelCase__		) * second_num

def 							UpperCamelCase_       (       )		->  Dict:

  """simple docstring"""




  lowerCAmelCase_  :							str								=					(
      'from __main__ import least_common_multiple_slow, least_common_multiple_fast'
  )
  print(
      'least_common_multiple_slow():'       ,  timeit('least_common_multiple_slow(1000, 999)'       ,  setup=lowerCAmelCase__		)       ,  )
  print(
      'least_common_multiple_fast():'       ,  timeit('least_common_multiple_fast(1000, 999)'       ,  setup=lowerCAmelCase__		)       ,  )







class  UpperCamelCase__  (      unittest.TestCase    ):




      """simple docstring"""




      _SCREAMING_SNAKE_CASE    							=	(
          (10, 20),
          (13, 15),
          (4, 31),
          (10, 42),
          (43, 34),
          (5, 12),
          (12, 25),
          (10, 25),
          (6, 9),
      )
      _SCREAMING_SNAKE_CASE    							=	(20, 195, 124, 210, 1462, 60, 300, 50, 18)



      def 	SCREAMING_SNAKE_CASE__					( self							: List[str]			):
        for i, (first_num, second_num) in enumerate(self.test_inputs			):
          lowerCAmelCase_  :							Union[str, Any]								=					least_common_multiple_slow(SCREAMING_SNAKE_CASE_       ,     SCREAMING_SNAKE_CASE_			)
          lowerCAmelCase_  :							Any								=					least_common_multiple_fast(SCREAMING_SNAKE_CASE_       ,     SCREAMING_SNAKE_CASE_			)
          with self.subTest(i=SCREAMING_SNAKE_CASE_			):
            self.assertEqual(SCREAMING_SNAKE_CASE_       ,     self.expected_results[i]			)
            self.assertEqual(SCREAMING_SNAKE_CASE_       ,     self.expected_results[i]			)


if __name__ == "__main__":
     benchmark()
     unittest.main()





