"""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							(       UpperCAmelCase_       :							str     ,				**UpperCAmelCase_       :							str    )				->     List[str]:

	'''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     ,				**UpperCAmelCase_     ,				)

class 						UpperCamelCase     (       lowercase		):



				@staticmethod
				def    _lowercase	(_A							: ArgumentParser)       ->      Any:
					__snake_case     :				Optional[int] 						=					parser.add_parser('run_beam'      ,    help='Run a Beam dataset processing pipeline')
					run_beam_parser.add_argument('dataset'      ,    type=_A      ,    help='Name of the dataset to download')
					run_beam_parser.add_argument('--name'      ,    type=_A      ,    default=_A      ,    help='Dataset config name')
					run_beam_parser.add_argument(
					    '--cache_dir'      ,    type=_A      ,    default=_A      ,    help='Cache directory where the datasets are stored'      ,    )
					run_beam_parser.add_argument(
					    '--beam_pipeline_options'      ,    type=_A      ,    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=_A      ,    default=_A      ,    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=_A)



				def __init__(self							: List[Any]      ,    _A							: str      ,    _A							: str      ,    _A							: str      ,    _A							: str      ,    _A							: str      ,    _A							: bool      ,    _A							: bool      ,    _A							: bool      ,    _A							: bool      ,    **_A							: List[Any]      ,    )       ->      List[Any]:
					__snake_case     :				Optional[Any] 						=					dataset
					__snake_case     :				List[Any] 						=					name
					__snake_case     :				Union[str, Any] 						=					cache_dir
					__snake_case     :				Any 						=					beam_pipeline_options
					__snake_case     :				str 						=					data_dir
					__snake_case     :				Union[str, Any] 						=					all_configs
					__snake_case     :				Dict 						=					save_infos
					__snake_case     :				List[str] 						=					ignore_verifications
					__snake_case     :				str 						=					force_redownload
					__snake_case     :				Any 						=					config_kwargs






				def    _lowercase	(self							: Optional[int])       ->      Dict:
					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)
					__snake_case						,							__snake_case     :				Union[str, Any] 						=					self._dataset, self._name
					__snake_case     :				List[str] 						=					dataset_module_factory(_A)
					__snake_case     :				Any 						=					import_main_class(dataset_module.module_path)
					__snake_case     :				List[DatasetBuilder] 						=					[]
					if self._beam_pipeline_options:
						__snake_case     :				str 						=					beam.options.pipeline_options.PipelineOptions(
						    flags=[f"--{opt.strip()}" for opt in self._beam_pipeline_options.split(',') if opt])
					else:
						__snake_case     :				Dict 						=					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=_A      ,    cache_dir=self._cache_dir      ,    base_path=dataset_module.builder_kwargs.get('base_path')      ,    ))
					else:
						builders.append(
						    builder_cls(
						        config_name=_A      ,    data_dir=self._data_dir      ,    beam_options=_A      ,    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=_A      ,    )
						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:
						__snake_case     :				Optional[Any] 						=					os.path.join(builder_cls.get_imported_module_dir()      ,    config.DATASETDICT_INFOS_FILENAME)

						__snake_case     :				Optional[Any] 						=					Path(_A).name + '.py'

						__snake_case     :				Any 						=					os.path.join(_A      ,    _A)
						if os.path.isfile(_A):
							__snake_case     :				Dict 						=					os.path.dirname(_A)
						elif os.path.isfile(_A):
							__snake_case     :				Optional[int] 						=					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
						__snake_case     :				Optional[Any] 						=					os.path.join(_A      ,    config.DATASETDICT_INFOS_FILENAME)
						copyfile(_A      ,    _A)
						print(f"Dataset Infos file saved at {user_dataset_infos_path}")






"""simple docstring"""







_a	:	Optional[Any]=					{
    "+": lambda x, y: x + y,
    "-": lambda x, y: x - y,
    "*": lambda x, y: x * y,
    "/": lambda x, y: x / y,
}
def     __UpperCAmelCase							(       UpperCAmelCase_       :							List[Any]    )				->     List[Any]:

	'''simple docstring'''





	return c.isdigit()
def     __UpperCAmelCase							(       UpperCAmelCase_       :							int    )				->     List[Any]:

	'''simple docstring'''





	__snake_case     :				Dict 						=					[]

	# iterate over the string in reverse order
	for c in expression.split()[::-1]:
		# push operand to stack
		if is_operand(UpperCAmelCase_    ):
			stack.append(int(UpperCAmelCase_    )    )

		else:
			# pop values from stack can calculate the result
			# push the result onto the stack again
			__snake_case     :				Optional[Any] 						=					stack.pop()
			__snake_case     :				int 						=					stack.pop()
			stack.append(calc[c](UpperCAmelCase_     ,				UpperCAmelCase_    )    )

	return stack.pop()


# Driver code
if __name__ == "__main__":
	_a	:	Union[str, Any]=					"+ 9 * 2 6"
	print(evaluate(test_expression))

	_a	:	List[Any]=					"/ * 10 2 + 4 1 "
	print(evaluate(test_expression))





