


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 		lowercase_(  SCREAMING_SNAKE_CASE_				,						**SCREAMING_SNAKE_CASE_     ):


  '''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				,						**SCREAMING_SNAKE_CASE_				,						)







class      UpperCAmelCase_ ( UpperCamelCase   ):

   '''simple docstring'''




   @staticmethod
   def _snake_case   (		__A			):






     """simple docstring"""





     lowerCamelCase			: 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						,    __A						,    __A						,    __A						,    __A						,    __A						,    __A						,    __A						,    __A						,    __A						,    **__A						,    ):






     """simple docstring"""





     lowerCamelCase			: int   =    dataset
     lowerCamelCase			: int   =    name
     lowerCamelCase			: int   =    cache_dir
     lowerCamelCase			: Any   =    beam_pipeline_options
     lowerCamelCase			: Optional[Any]   =    data_dir
     lowerCamelCase			: Optional[int]   =    all_configs
     lowerCamelCase			: Union[str, Any]   =    save_infos
     lowerCamelCase			: Union[str, Any]   =    ignore_verifications
     lowerCamelCase			: str   =    force_redownload
     lowerCamelCase			: int   =    config_kwargs






   def _snake_case   (		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			)
     lowerCamelCase   ,     lowerCamelCase			: Tuple   =    self._dataset, self._name
     lowerCamelCase			: Any   =    dataset_module_factory(__A			)
     lowerCamelCase			: Tuple   =    import_main_class(dataset_module.module_path			)
     lowerCamelCase			: List[DatasetBuilder]   =    []
     if self._beam_pipeline_options:
       lowerCamelCase			: Optional[Any]   =    beam.options.pipeline_options.PipelineOptions(
           flags=[F"""--{opt.strip()}""" for opt in self._beam_pipeline_options.split(","			) if opt]			)
     else:
       lowerCamelCase			: int   =    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:
       lowerCamelCase			: Any   =    os.path.join(builder_cls.get_imported_module_dir()						,    config.DATASETDICT_INFOS_FILENAME			)

       lowerCamelCase			: List[str]   =    Path(__A			).name + ".py"

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







def 		lowercase_(  SCREAMING_SNAKE_CASE_				,						SCREAMING_SNAKE_CASE_     ):


  '''simple docstring'''

  sequence.append(SCREAMING_SNAKE_CASE_     )

  lowerCamelCase			: str   =    0
  while sequence[index] != target:
    index += 1

  sequence.pop()

  if index == len(SCREAMING_SNAKE_CASE_     ):
    return None

  return index


if __name__ == "__main__":
   _snake_case					=					input('''Enter numbers separated by comma:\n''').strip()
   _snake_case					=					[int(item) for item in user_input.split(''',''')]

   _snake_case					=					input('''Enter a single number to be found in the list:\n''')
   _snake_case					=					int(target_input)
   _snake_case					=					sentinel_linear_search(sequence, target)
   if result is not None:
      print(f'''{target} found at positions: {result}''')
   else:
      print('''Not found''')



