
'''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 		_UpperCAmelCase			(					_lowerCamelCase  :    int					, **_lowerCamelCase  :    int						)      ->  str:
  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 					a_					(_UpperCAmelCase      ):




       @staticmethod
       def 							__UpperCamelCase    (       snake_case_					):
         _lowerCAmelCase    :					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				,				snake_case_				,				snake_case_				,				snake_case_				,				snake_case_				,				snake_case_				,				snake_case_				,				snake_case_				,				snake_case_				,				snake_case_				,				**snake_case_				,				):
         _lowerCAmelCase    :					Tuple							=   dataset
         _lowerCAmelCase    :					Dict							=   name
         _lowerCAmelCase    :					str							=   cache_dir
         _lowerCAmelCase    :					Optional[Any]							=   beam_pipeline_options
         _lowerCAmelCase    :					List[Any]							=   data_dir
         _lowerCAmelCase    :					Dict							=   all_configs
         _lowerCAmelCase    :					List[str]							=   save_infos
         _lowerCAmelCase    :					List[Any]							=   ignore_verifications
         _lowerCAmelCase    :					int							=   force_redownload
         _lowerCAmelCase    :					Tuple							=   config_kwargs







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

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

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



'''simple docstring'''

from __future__ import annotations


class 					a_					:




       def __init__(       self				,				snake_case_ = 0					):
         _lowerCAmelCase    :					Optional[Any]							=   value
         _lowerCAmelCase    :					Node | None							=   None
         _lowerCAmelCase    :					Node | None							=   None



def 		_UpperCAmelCase			(					_lowerCamelCase  :    Node | None					, _lowerCamelCase  :    Node | None						)      ->  Node | None:
  if treea is None:
    return treea
  if treea is None:
    return treea

  _lowerCAmelCase    :					Any							=   treea.value + treea.value
  _lowerCAmelCase    :					Tuple							=   merge_two_binary_trees(treea.left					, treea.left						)
  _lowerCAmelCase    :					List[str]							=   merge_two_binary_trees(treea.right					, treea.right						)
  return treea


def 		_UpperCAmelCase			(					_lowerCamelCase  :    Node | None						)      ->  None:
  if root:
    print(root.value						)
    print_preorder(root.left						)
    print_preorder(root.right						)


if __name__ == "__main__":
     UpperCamelCase_            =    Node(1)
     UpperCamelCase_            =    Node(2)
     UpperCamelCase_            =    Node(3)
     UpperCamelCase_            =    Node(4)

     UpperCamelCase_            =    Node(2)
     UpperCamelCase_            =    Node(4)
     UpperCamelCase_            =    Node(6)
     UpperCamelCase_            =    Node(9)
     UpperCamelCase_            =    Node(5)

     print("""Tree1 is: """)
     print_preorder(treea)
     print("""Tree2 is: """)
     print_preorder(treea)
     UpperCamelCase_            =    merge_two_binary_trees(treea, treea)
     print("""Merged Tree is: """)
     print_preorder(merged_tree)


