

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			):
	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				,   **_SCREAMING_SNAKE_CASE				,   )




class   __UpperCamelCase			(    lowerCAmelCase__  ):




	@staticmethod
	def 					__A    (						lowerCAmelCase		:  int							):


		'''simple docstring'''







		UpperCAmelCase_				 =	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[str]						,		lowerCAmelCase		:  Optional[int]						,		lowerCAmelCase		:  Optional[Any]						,		lowerCAmelCase		:  List[str]						,		lowerCAmelCase		:  Any						,		lowerCAmelCase		:  Dict						,		lowerCAmelCase		:  Optional[Any]						,		lowerCAmelCase		:  Tuple						,		lowerCAmelCase		:  Any						,		lowerCAmelCase		:  Optional[Any]						,		**lowerCAmelCase		:  Union[str, Any]						,		):


		'''simple docstring'''







		UpperCAmelCase_				 =	dataset
		UpperCAmelCase_				 =	name
		UpperCAmelCase_				 =	cache_dir
		UpperCAmelCase_				 =	beam_pipeline_options
		UpperCAmelCase_				 =	data_dir
		UpperCAmelCase_				 =	all_configs
		UpperCAmelCase_				 =	save_infos
		UpperCAmelCase_				 =	ignore_verifications
		UpperCAmelCase_				 =	force_redownload
		UpperCAmelCase_				 =	config_kwargs




	def 					__A    (						self		:  Optional[int]							):


		'''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							)
		UpperCAmelCase_ ,      UpperCAmelCase_				 =	self._dataset, self._name
		UpperCAmelCase_				 =	dataset_module_factory(_A							)
		UpperCAmelCase_				 =	import_main_class(dataset_module.module_path							)
		UpperCAmelCase_				 =	[]
		if self._beam_pipeline_options:
			UpperCAmelCase_				 =	beam.options.pipeline_options.PipelineOptions(
			    flags=[F"--{opt.strip()}" for opt in self._beam_pipeline_options.split(","							) if opt]							)
		else:
			UpperCAmelCase_				 =	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:
			UpperCAmelCase_				 =	os.path.join(builder_cls.get_imported_module_dir()						,		config.DATASETDICT_INFOS_FILENAME							)

			UpperCAmelCase_				 =	Path(_A							).name + ".py"

			UpperCAmelCase_				 =	os.path.join(_A						,		_A							)
			if os.path.isfile(_A							):
				UpperCAmelCase_				 =	os.path.dirname(_A							)
			elif os.path.isfile(_A							):
				UpperCAmelCase_				 =	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
			UpperCAmelCase_				 =	os.path.join(_A						,		config.DATASETDICT_INFOS_FILENAME							)
			copyfile(_A						,		_A							)
			print(F"Dataset Infos file saved at {user_dataset_infos_path}"							)


from itertools import permutations


def     _UpperCAmelCase				(     ):





    """simple docstring"""


    SCREAMING_SNAKE_CASE_													=  list(map(''.join       ,      permutations('0123456789'				)				)				)
    return result[999_999]


if __name__ == "__main__":
       print(solution())


