code: 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 					__lowerCAmelCase			(  _A ,**_A					):
  
  
  
  							"""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 ,**_A ,)
  
  
  
  
  
  
  
  class _lowercase					(       _UpperCAmelCase						):
  
  
  
  
  
  							"""simple docstring"""
  
  
  
  
  							@staticmethod
  							def     _UpperCAmelCase       (    UpperCAmelCase  ):
  
  
  
  
  
  
  
  														'''simple docstring'''
  
  
  
  
  
  
  														_lowercase				=	parser.add_parser("""run_beam"""     ,   help="""Run a Beam dataset processing pipeline"""  )
  														run_beam_parser.add_argument("""dataset"""     ,   type=UpperCAmelCase     ,   help="""Name of the dataset to download"""  )
  														run_beam_parser.add_argument("""--name"""     ,   type=UpperCAmelCase     ,   default=UpperCAmelCase     ,   help="""Dataset config name"""  )
  														run_beam_parser.add_argument(
  														    """--cache_dir"""     ,   type=UpperCAmelCase     ,   default=UpperCAmelCase     ,   help="""Cache directory where the datasets are stored"""     ,   )
  														run_beam_parser.add_argument(
  														    """--beam_pipeline_options"""     ,   type=UpperCAmelCase     ,   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=UpperCAmelCase     ,   default=UpperCAmelCase     ,   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=UpperCAmelCase  )
  
  
  
  							def __init__(    self     ,   UpperCAmelCase     ,   UpperCAmelCase     ,   UpperCAmelCase     ,   UpperCAmelCase     ,   UpperCAmelCase     ,   UpperCAmelCase     ,   UpperCAmelCase     ,   UpperCAmelCase     ,   UpperCAmelCase     ,   **UpperCAmelCase     ,   ):
  
  
  
  
  
  
  
  														'''simple docstring'''
  
  
  
  
  
  
  														_lowercase				=	dataset
  														_lowercase				=	name
  														_lowercase				=	cache_dir
  														_lowercase				=	beam_pipeline_options
  														_lowercase				=	data_dir
  														_lowercase				=	all_configs
  														_lowercase				=	save_infos
  														_lowercase				=	ignore_verifications
  														_lowercase				=	force_redownload
  														_lowercase				=	config_kwargs
  
  
  
  							def     _UpperCAmelCase       (    self  ):
  
  
  
  
  
  
  
  														'''simple docstring'''
  
  
  
  
  
  
  														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  )
  														_lowercase				,       _lowercase				=	self._dataset, self._name
  														_lowercase				=	dataset_module_factory(UpperCAmelCase  )
  														_lowercase				=	import_main_class(dataset_module.module_path  )
  														_lowercase				=	[]
  														if self._beam_pipeline_options:
  																					_lowercase				=	beam.options.pipeline_options.PipelineOptions(
  																					    flags=[F'''--{opt.strip()}''' for opt in self._beam_pipeline_options.split(""","""  ) if opt]  )
  														else:
  																					_lowercase				=	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=UpperCAmelCase     ,   cache_dir=self._cache_dir     ,   base_path=dataset_module.builder_kwargs.get("""base_path"""  )     ,   )  )
  														else:
  																					builders.append(
  																					    builder_cls(
  																					        config_name=UpperCAmelCase     ,   data_dir=self._data_dir     ,   beam_options=UpperCAmelCase     ,   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=UpperCAmelCase     ,   )
  																					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:
  																					_lowercase				=	os.path.join(builder_cls.get_imported_module_dir()     ,   config.DATASETDICT_INFOS_FILENAME  )
  
  																					_lowercase				=	Path(UpperCAmelCase  ).name + """.py"""
  
  																					_lowercase				=	os.path.join(UpperCAmelCase     ,   UpperCAmelCase  )
  																					if os.path.isfile(UpperCAmelCase  ):
  																												_lowercase				=	os.path.dirname(UpperCAmelCase  )
  																					elif os.path.isfile(UpperCAmelCase  ):
  																												_lowercase				=	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
  																					_lowercase				=	os.path.join(UpperCAmelCase     ,   config.DATASETDICT_INFOS_FILENAME  )
  																					copyfile(UpperCAmelCase     ,   UpperCAmelCase  )
  																					print(F'''Dataset Infos file saved at {user_dataset_infos_path}'''  )
  
  
  
style_context: import math
  from timeit import timeit
  
  
  def 					__lowerCAmelCase			(  _A					):
  
  
  
  							"""simple docstring"""
  
  
  							_lowercase				=	0
  							_lowercase				=	abs(_A					)
  							while True:
  														_lowercase				=	n // 10
  														digits += 1
  														if n == 0:
  																					break
  							return digits
  
  
  def 					__lowerCAmelCase			(  _A					):
  
  
  
  							"""simple docstring"""
  
  
  							return 1 if n == 0 else math.floor(math.log(abs(_A					) ,10					) + 1					)
  
  
  def 					__lowerCAmelCase			(  _A					):
  
  
  
  							"""simple docstring"""
  
  
  							return len(str(abs(_A					)					)					)
  
  
  def 					__lowerCAmelCase			(  ):
  
  
  
  							"""simple docstring"""
  
  
  							from collections.abc import Callable
  
  							def benchmark_a_function(_A ,_A					) -> None:
  														_lowercase				=	f'''{func.__name__}({value})'''
  														_lowercase				=	timeit(f'''__main__.{call}''' ,setup="""import __main__"""					)
  														print(f'''{call}: {func(_A					)} -- {timing} seconds'''					)
  
  							for value in (262_144, 1_125_899_906_842_624, 1_267_650_600_228_229_401_496_703_205_376):
  														for func in (num_digits, num_digits_fast, num_digits_faster):
  																					benchmark_a_function(_A ,_A					)
  														print()
  
  
  if __name__ == "__main__":
  				import doctest
  
  				doctest.testmod()
  				benchmark()
  
  
  