

'''simple docstring'''






class      SCREAMING_SNAKE_CASE__      :




    def __init__( self      ):






          """simple docstring"""






          SCREAMING_SNAKE_CASE_				:      dict[int, list[int]]					=	{}
          # indexmap keys are an index and it's values are the number at that index
          SCREAMING_SNAKE_CASE_				:      dict[int, int]					=	{}




    def   __lowerCamelCase				( self    ,					lowercase__    ,					lowercase__      ):






          """simple docstring"""






          if isinstance(lowercase__    ,					(range, str)      ):
                SCREAMING_SNAKE_CASE_				:      Optional[Any]					=	list(lowercase__      )
          elif not isinstance(lowercase__    ,					lowercase__      ):
                raise TypeError(
                    "binary_search_delete() only accepts either a list, range or str"      )

          SCREAMING_SNAKE_CASE_				:      Any					=	0
          SCREAMING_SNAKE_CASE_				:      Optional[Any]					=	len(lowercase__      ) - 1

          while low <= high:
                SCREAMING_SNAKE_CASE_				:      List[str]					=	(low + high) // 2
                if array[mid] == item:
                      array.pop(lowercase__      )
                      return array
                elif array[mid] < item:
                      SCREAMING_SNAKE_CASE_				:      List[str]					=	mid + 1
                else:
                      SCREAMING_SNAKE_CASE_				:      List[str]					=	mid - 1
          raise ValueError(
              "Either the item is not in the array or the array was unsorted"      )




    def   __lowerCamelCase				( self    ,					lowercase__    ,					lowercase__      ):






          """simple docstring"""






          if isinstance(lowercase__    ,					(range, str)      ):
                SCREAMING_SNAKE_CASE_				:      Union[str, Any]					=	list(lowercase__      )
          elif not isinstance(lowercase__    ,					lowercase__      ):
                raise TypeError(
                    "binary_search_insert() only accepts either a list, range or str"      )

          SCREAMING_SNAKE_CASE_				:      Dict					=	0
          SCREAMING_SNAKE_CASE_				:      Union[str, Any]					=	len(lowercase__      ) - 1

          while low <= high:
                SCREAMING_SNAKE_CASE_				:      Union[str, Any]					=	(low + high) // 2
                if array[mid] == index:
                      # If the item already exists in the array,
                      # insert it after the existing item
                      array.insert(mid + 1    ,					lowercase__      )
                      return array
                elif array[mid] < index:
                      SCREAMING_SNAKE_CASE_				:      List[str]					=	mid + 1
                else:
                      SCREAMING_SNAKE_CASE_				:      Any					=	mid - 1

        # If the item doesn't exist in the array, insert it at the appropriate position
          array.insert(lowercase__    ,					lowercase__      )
          return array




    def   __lowerCamelCase				( self    ,					lowercase__    ,					lowercase__      ):






          """simple docstring"""






          if index in self.indexmap:
                SCREAMING_SNAKE_CASE_				:      Union[str, Any]					=	self.indexmap[index]
                if len(self.numbermap[n]      ) == 1:
                      del self.numbermap[n]
                else:
                      SCREAMING_SNAKE_CASE_				:      Any					=	self.binary_search_delete(self.numbermap[n]    ,					lowercase__      )

        # Set new index
          SCREAMING_SNAKE_CASE_				:      Dict					=	number

          # Number not seen before or empty so insert number value
          if number not in self.numbermap:
                SCREAMING_SNAKE_CASE_				:      Optional[Any]					=	[index]

          # Here we need to perform a binary search insertion in order to insert
          # The item in the correct place
          else:
                SCREAMING_SNAKE_CASE_				:      Union[str, Any]					=	self.binary_search_insert(
                    self.numbermap[number]    ,					lowercase__      )







    def   __lowerCamelCase				( self    ,					lowercase__      ):






          """simple docstring"""






          return self.numbermap.get(lowercase__    ,					[-1]      )[0]


if __name__ == "__main__":
      import doctest

      doctest.testmod()




'''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      (				SCREAMING_SNAKE_CASE_					:     int  ,  **SCREAMING_SNAKE_CASE_					:     int   )							->       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  ,  **SCREAMING_SNAKE_CASE_  ,  )





class      SCREAMING_SNAKE_CASE__      (    _UpperCAmelCase				):




    @staticmethod
    def   __lowerCamelCase				( lowercase__      ):






          """simple docstring"""






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




    def __init__( self    ,					lowercase__    ,					lowercase__    ,					lowercase__    ,					lowercase__    ,					lowercase__    ,					lowercase__    ,					lowercase__    ,					lowercase__    ,					lowercase__    ,					**lowercase__    ,					):






          """simple docstring"""






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







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

                SCREAMING_SNAKE_CASE_				:      List[Any]					=	Path(lowercase__      ).name + ".py"

                SCREAMING_SNAKE_CASE_				:      Optional[int]					=	os.path.join(lowercase__    ,					lowercase__      )
                if os.path.isfile(lowercase__      ):
                      SCREAMING_SNAKE_CASE_				:      Any					=	os.path.dirname(lowercase__      )
                elif os.path.isfile(lowercase__      ):
                      SCREAMING_SNAKE_CASE_				:      List[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
                SCREAMING_SNAKE_CASE_				:      Optional[int]					=	os.path.join(lowercase__    ,					config.DATASETDICT_INFOS_FILENAME      )
                copyfile(lowercase__    ,					lowercase__      )
                print(F"Dataset Infos file saved at {user_dataset_infos_path}"      )

