

'''simple docstring'''

from .stack import Stack

def      __magic_name__							(			A				)      ->		bool:
	snake_case							=					Stack()
	snake_case							=					{'(': ')', '[': ']', '{': '}'}
	for bracket in parentheses:
		if bracket in bracket_pairs:
			stack.push(A				)
		elif bracket in (")", "]", "}"):
			if stack.is_empty() or bracket_pairs[stack.pop()] != bracket:
				return False
	return stack.is_empty()


if __name__ == "__main__":
						from doctest import testmod

						testmod()

						lowerCAmelCase_     =      ["((()))", "((())", "(()))"]
						print("Balanced parentheses demonstration:\n")
						for example in examples:
												lowerCAmelCase_     =      "" if balanced_parentheses(example) else "not "
												print(f"{example} is {not_str}balanced")









'''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 			__lowerCAmelCase			(__lowerCAmelCase   ,			**__lowerCAmelCase ):
		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 						lowerCAmelCase__      (      UpperCAmelCase__						):




			@staticmethod
			def 				lowerCAmelCase__     (		lowerCamelCase__	:  ArgumentParser			) ->Optional[Any]:



					'''simple docstring'''







					_UpperCAmelCase		:							Union[str, Any]             =   parser.add_parser("run_beam"						,	help="Run a Beam dataset processing pipeline"			)
					run_beam_parser.add_argument("dataset"						,	type=lowerCamelCase__						,	help="Name of the dataset to download"			)
					run_beam_parser.add_argument("--name"						,	type=lowerCamelCase__						,	default=lowerCamelCase__						,	help="Dataset config name"			)
					run_beam_parser.add_argument(
					    "--cache_dir"						,	type=lowerCamelCase__						,	default=lowerCamelCase__						,	help="Cache directory where the datasets are stored"						,	)
					run_beam_parser.add_argument(
					    "--beam_pipeline_options"						,	type=lowerCamelCase__						,	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=lowerCamelCase__						,	default=lowerCamelCase__						,	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=lowerCamelCase__			)




			def __init__(		self	:  str						,	lowerCamelCase__	:  str						,	lowerCamelCase__	:  str						,	lowerCamelCase__	:  str						,	lowerCamelCase__	:  str						,	lowerCamelCase__	:  str						,	lowerCamelCase__	:  bool						,	lowerCamelCase__	:  bool						,	lowerCamelCase__	:  bool						,	lowerCamelCase__	:  bool						,	**lowerCamelCase__	:  Optional[Any]						,	) ->Tuple:



					'''simple docstring'''







					_UpperCAmelCase		:							Any             =   dataset
					_UpperCAmelCase		:							str             =   name
					_UpperCAmelCase		:							int             =   cache_dir
					_UpperCAmelCase		:							Optional[int]             =   beam_pipeline_options
					_UpperCAmelCase		:							int             =   data_dir
					_UpperCAmelCase		:							Optional[int]             =   all_configs
					_UpperCAmelCase		:							Any             =   save_infos
					_UpperCAmelCase		:							Optional[Any]             =   ignore_verifications
					_UpperCAmelCase		:							Any             =   force_redownload
					_UpperCAmelCase		:							Tuple             =   config_kwargs






			def 				lowerCAmelCase__     (		self	:  Dict			) ->Union[str, Any]:



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

							_UpperCAmelCase		:							List[str]             =   Path(lowerCamelCase__			).name + ".py"

							_UpperCAmelCase		:							int             =   os.path.join(lowerCamelCase__						,	lowerCamelCase__			)
							if os.path.isfile(lowerCamelCase__			):
									_UpperCAmelCase		:							Any             =   os.path.dirname(lowerCamelCase__			)
							elif os.path.isfile(lowerCamelCase__			):
									_UpperCAmelCase		:							Tuple             =   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		:							Union[str, Any]             =   os.path.join(lowerCamelCase__						,	config.DATASETDICT_INFOS_FILENAME			)
							copyfile(lowerCamelCase__						,	lowerCamelCase__			)
							print(F"""Dataset Infos file saved at {user_dataset_infos_path}"""			)



