



def 	__a					(   lowerCAmelCase_       : list    )				->			Optional[int]:






      '''simple docstring'''



      UpperCAmelCase_=       len(lowerCamelCase_    )
      for i in range(1      ,lowerCamelCase_    ):
            UpperCAmelCase_=       collection[i]
            UpperCAmelCase_=       0
            UpperCAmelCase_=       i - 1

            while low <= high:
                  UpperCAmelCase_=       (low + high) // 2
                  if val < collection[mid]:
                        UpperCAmelCase_=       mid - 1
                  else:
                        UpperCAmelCase_=       mid + 1
            for j in range(lowerCamelCase_      ,lowerCamelCase_      ,-1    ):
                  UpperCAmelCase_=       collection[j - 1]
            UpperCAmelCase_=       val
      return collection


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









from typing import Optional

import pyspark

from .. import Features, NamedSplit
from ..download import DownloadMode
from ..packaged_modules.spark.spark import Spark
from .abc import AbstractDatasetReader






class 		lowercase						(			snake_case__):






	"""simple docstring"""


	def __init__(     self     :						int						,  __UpperCAmelCase     :						pyspark.sql.DataFrame						,  __UpperCAmelCase     :						Optional[NamedSplit] = None						,  __UpperCAmelCase     :						Optional[Features] = None						,  __UpperCAmelCase     :						bool = True						,  __UpperCAmelCase     :						str = None						,  __UpperCAmelCase     :						bool = False						,  __UpperCAmelCase     :						str = None						,  __UpperCAmelCase     :						bool = True						,  __UpperCAmelCase     :						str = "arrow"						,  **__UpperCAmelCase     :						str						,  )      ->			Dict:
							super().__init__(
							    split=__UpperCAmelCase						,  features=__UpperCAmelCase						,  cache_dir=__UpperCAmelCase						,  keep_in_memory=__UpperCAmelCase						,  streaming=__UpperCAmelCase						,  **__UpperCAmelCase						,  )
							UpperCAmelCase_=       load_from_cache_file
							UpperCAmelCase_=       file_format
							UpperCAmelCase_=       Spark(
							    df=__UpperCAmelCase						,  features=__UpperCAmelCase						,  cache_dir=__UpperCAmelCase						,  working_dir=__UpperCAmelCase						,  **__UpperCAmelCase						,  )




	def   _SCREAMING_SNAKE_CASE		(     self     :						Any					)      ->			Dict:
							if self.streaming:
													return self.builder.as_streaming_dataset(split=self.split					)
							UpperCAmelCase_=       None if self._load_from_cache_file else DownloadMode.FORCE_REDOWNLOAD
							self.builder.download_and_prepare(
							    download_mode=__UpperCAmelCase						,  file_format=self._file_format						,  )
							return self.builder.as_dataset(split=self.split					)




