
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__							(       __magic_name__						:     Optional[Any]							,  **__magic_name__						:     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							,  **__magic_name__							,  )


class 		__magic_name__   (						snake_case    ):





		@staticmethod
		def       _A							(							lowerCamelCase__    :	ArgumentParser				):
							lowerCAmelCase		:					Optional[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    :	Dict						,  lowerCamelCase__    :	str						,  lowerCamelCase__    :	str						,  lowerCamelCase__    :	str						,  lowerCamelCase__    :	str						,  lowerCamelCase__    :	str						,  lowerCamelCase__    :	bool						,  lowerCamelCase__    :	bool						,  lowerCamelCase__    :	bool						,  lowerCamelCase__    :	bool						,  **lowerCamelCase__    :	Dict						,  ):
							lowerCAmelCase		:					List[Any]  	=     dataset
							lowerCAmelCase		:					Optional[int]  	=     name
							lowerCAmelCase		:					List[Any]  	=     cache_dir
							lowerCAmelCase		:					Any  	=     beam_pipeline_options
							lowerCAmelCase		:					Dict  	=     data_dir
							lowerCAmelCase		:					Dict  	=     all_configs
							lowerCAmelCase		:					List[Any]  	=     save_infos
							lowerCAmelCase		:					Optional[Any]  	=     ignore_verifications
							lowerCAmelCase		:					Tuple  	=     force_redownload
							lowerCAmelCase		:					str  	=     config_kwargs





		def       _A							(							self    :	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		:					List[str]  	=     self._dataset, self._name
							lowerCAmelCase		:					Dict  	=     dataset_module_factory(lowerCamelCase__				)
							lowerCAmelCase		:					Optional[Any]  	=     import_main_class(dataset_module.module_path				)
							lowerCAmelCase		:					List[DatasetBuilder]  	=     []
							if self._beam_pipeline_options:
												lowerCAmelCase		:					Tuple  	=     beam.options.pipeline_options.PipelineOptions(
												    flags=[f'''--{opt.strip()}''' for opt in self._beam_pipeline_options.split(''','''				) if opt]				)
							else:
												lowerCAmelCase		:					Union[str, Any]  	=     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:
												lowerCAmelCase		:					Union[str, Any]  	=     os.path.join(builder_cls.get_imported_module_dir()						,  config.DATASETDICT_INFOS_FILENAME				)

												lowerCAmelCase		:					str  	=     Path(lowerCamelCase__				).name + '''.py'''

												lowerCAmelCase		:					Optional[Any]  	=     os.path.join(lowerCamelCase__						,  lowerCamelCase__				)
												if os.path.isfile(lowerCamelCase__				):
																	lowerCAmelCase		:					str  	=     os.path.dirname(lowerCamelCase__				)
												elif os.path.isfile(lowerCamelCase__				):
																	lowerCAmelCase		:					str  	=     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		:					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}'''				)


import json
import os
from dataclasses import dataclass

import numpy as np
import pyarrow as pa

import datasets
from utils import get_duration


__SCREAMING_SNAKE_CASE			:   List[Any]         =     10_00_00_00_00_00
__SCREAMING_SNAKE_CASE			:   Optional[Any]         =     1_00_00

__SCREAMING_SNAKE_CASE     ,				__SCREAMING_SNAKE_CASE			:   Any         =     os.path.split(__file__)
__SCREAMING_SNAKE_CASE			:   List[str]         =     os.path.join(RESULTS_BASEPATH, 'results', RESULTS_FILENAME.replace('.py', '.json'))
def     UpperCAmelCase__							(       __magic_name__						:     int							,  __magic_name__						:     int  ):


					'''simple docstring'''

					lowerCAmelCase		:					Optional[int]  	=     pa.Table.from_pydict({'''col''': [0] * chunk_size}  )
					lowerCAmelCase		:					int  	=     pa.concat_tables([table] * (num_examples // chunk_size)  )
					return datasets.Dataset(__magic_name__							,  fingerprint='''table_100B'''  )


@dataclass
class 		__magic_name__   :
		_lowerCAmelCase		=	42
		_lowerCAmelCase		=	42
		_lowerCAmelCase		=	42
		_lowerCAmelCase		=	42





		def       _A							(							self    :	Optional[int]				):
							lowerCAmelCase		:					Union[str, Any]  	=     np.random.default_rng(self.seed				)
							lowerCAmelCase		:					Tuple  	=     rng.integers(low=self.low						,  high=self.high						,  size=self.size				).tolist()





		def __iter__(							self    :	Dict				):
							return iter(self._sampled_values				)





		def __len__(							self    :	Tuple				):
							return self.size



@get_duration
def     UpperCAmelCase__							(       __magic_name__						:     datasets.Dataset  ):


					'''simple docstring'''

					lowerCAmelCase		:					Union[str, Any]  	=     dataset[0]
@get_duration
def     UpperCAmelCase__							(       __magic_name__						:     datasets.Dataset  ):


					'''simple docstring'''

					lowerCAmelCase		:					Any  	=     dataset[-1]
@get_duration
def     UpperCAmelCase__							(       __magic_name__						:     datasets.Dataset  ):


					'''simple docstring'''

					lowerCAmelCase		:					int  	=     dataset[range(len(__magic_name__  ) // 2							,  len(__magic_name__  ) // 2 + 10_24  )]
@get_duration
def     UpperCAmelCase__							(       __magic_name__						:     datasets.Dataset  ):


					'''simple docstring'''

					lowerCAmelCase		:					List[Any]  	=     dataset[RandIter(0							,  len(__magic_name__  )							,  10_24							,  seed=42  )]
def     UpperCAmelCase__							(       ):


					'''simple docstring'''

					lowerCAmelCase		:					Dict  	=     {'''num examples''': SPEED_TEST_N_EXAMPLES}
					lowerCAmelCase		:					Tuple  	=     (get_first_row, get_last_row, get_batch_of_aaaa_rows, get_batch_of_aaaa_random_rows)
					print('''generating dataset'''  )
					lowerCAmelCase		:					Dict  	=     generate_100B_dataset(num_examples=__magic_name__							,  chunk_size=__magic_name__  )
					print('''Functions'''  )
					for func in functions:
										print(func.__name__  )
										lowerCAmelCase		:					List[Any]  	=     func(__magic_name__  )

					with open(__magic_name__							,  '''wb'''  ) as f:
										f.write(json.dumps(__magic_name__  ).encode('''utf-8'''  )  )


if __name__ == "__main__":  # useful to run the profiler
		benchmark_table_100B()
