



import multiprocessing
from typing import TYPE_CHECKING, Optional, Union

from .. import Dataset, Features, config
from ..formatting import query_table
from ..packaged_modules.sql.sql import Sql
from ..utils import logging
from .abc import AbstractDatasetInputStream


if TYPE_CHECKING:
				import sqlitea

				import sqlalchemy

class  snake_case__(_UpperCamelCase     ):

					"""simple docstring"""






					def __init__(				self   :      Optional[int] ,  SCREAMING_SNAKE_CASE   :      Dict ,  SCREAMING_SNAKE_CASE   :      List[str] ,  SCREAMING_SNAKE_CASE   :      List[Any] = None ,  SCREAMING_SNAKE_CASE   :      Union[str, Any] = None ,  SCREAMING_SNAKE_CASE   :      Tuple = False ,  **SCREAMING_SNAKE_CASE   :      Optional[Any] ,  ):
									super().__init__(features=__lowerCAmelCase ,  cache_dir=__lowerCAmelCase ,  keep_in_memory=__lowerCAmelCase ,  **__lowerCAmelCase	)
									lowercase__	:       List[str]						=	Sql(
									    cache_dir=__lowerCAmelCase ,  features=__lowerCAmelCase ,  sql=__lowerCAmelCase ,  con=__lowerCAmelCase ,  **__lowerCAmelCase ,  )







					def 					snake_case	(				self   :      List[Any]	):
									lowercase__	:       Dict						=	None
									lowercase__	:       Any						=	None
									lowercase__	:       List[Any]						=	None
									lowercase__	:       Optional[Any]						=	None

									self.builder.download_and_prepare(
									    download_config=__lowerCAmelCase ,  download_mode=__lowerCAmelCase ,  verification_mode=__lowerCAmelCase ,  base_path=__lowerCAmelCase ,  )

									# Build dataset for splits
									lowercase__	:       Optional[int]						=	self.builder.as_dataset(
									    split="train" ,  verification_mode=__lowerCAmelCase ,  in_memory=self.keep_in_memory	)
									return dataset






class  snake_case__:

					"""simple docstring"""






					def __init__(				self   :      Optional[Any] ,  SCREAMING_SNAKE_CASE   :      Any ,  SCREAMING_SNAKE_CASE   :      Tuple ,  SCREAMING_SNAKE_CASE   :      Dict ,  SCREAMING_SNAKE_CASE   :      Dict = None ,  SCREAMING_SNAKE_CASE   :      Any = None ,  **SCREAMING_SNAKE_CASE   :      List[str] ,  ):



									if num_proc is not None and num_proc <= 0:
													raise ValueError(f"""num_proc {num_proc} must be an integer > 0."""	)

									lowercase__	:       List[str]						=	dataset
									lowercase__	:       List[str]						=	name
									lowercase__	:       Dict						=	con
									lowercase__	:       Optional[Any]						=	batch_size if batch_size else config.DEFAULT_MAX_BATCH_SIZE
									lowercase__	:       Any						=	num_proc
									lowercase__	:       Dict						=	to_sql_kwargs







					def 					snake_case	(				self   :      Union[str, Any]	):
									lowercase__	:       Union[str, Any]						=	self.to_sql_kwargs.pop("sql" ,  __lowerCAmelCase	)
									lowercase__	:       List[str]						=	self.to_sql_kwargs.pop("con" ,  __lowerCAmelCase	)
									lowercase__	:       int						=	self.to_sql_kwargs.pop("index" ,  __lowerCAmelCase	)

									lowercase__	:       Optional[Any]						=	self._write(index=__lowerCAmelCase ,  **self.to_sql_kwargs	)
									return written







					def 					snake_case	(				self   :      Tuple ,  SCREAMING_SNAKE_CASE   :      Tuple	):
									lowercase__				,				lowercase__				,				lowercase__	:       Optional[int]						=	args
									lowercase__	:       List[Any]						=	{**to_sql_kwargs, "if_exists": "append"} if offset > 0 else to_sql_kwargs
									lowercase__	:       List[Any]						=	query_table(
									    table=self.dataset.data ,  key=slice(__lowerCAmelCase ,  offset + self.batch_size	) ,  indices=self.dataset._indices ,  )
									lowercase__	:       int						=	batch.to_pandas()
									lowercase__	:       int						=	df.to_sql(self.name ,  self.con ,  index=__lowerCAmelCase ,  **__lowerCAmelCase	)
									return num_rows or len(__lowerCAmelCase	)







					def 					snake_case	(				self   :      Tuple ,  SCREAMING_SNAKE_CASE   :      Optional[int] ,  **SCREAMING_SNAKE_CASE   :      Optional[Any]	):
									lowercase__	:       Optional[int]						=	0

									if self.num_proc is None or self.num_proc == 1:
													for offset in logging.tqdm(
													    range(0 ,  len(self.dataset	) ,  self.batch_size	) ,  unit="ba" ,  disable=not logging.is_progress_bar_enabled() ,  desc="Creating SQL from Arrow format" ,  ):
																	written += self._batch_sql((offset, index, to_sql_kwargs)	)
									else:
													lowercase__				,				lowercase__	:       Optional[Any]						=	len(self.dataset	), self.batch_size
													with multiprocessing.Pool(self.num_proc	) as pool:
																	for num_rows in logging.tqdm(
																	    pool.imap(
																	        self._batch_sql ,  [(offset, index, to_sql_kwargs) for offset in range(0 ,  __lowerCAmelCase ,  __lowerCAmelCase	)] ,  ) ,  total=(num_rows // batch_size) + 1 if num_rows % batch_size else num_rows // batch_size ,  unit="ba" ,  disable=not logging.is_progress_bar_enabled() ,  desc="Creating SQL from Arrow format" ,  ):
																					written += num_rows

									return written





"""simple docstring"""






import math


def      UpperCAmelCase__			(							lowerCAmelCase__	:int						)					->       bool:
      '''simple docstring'''


      lowercase								=      math.loga(math.sqrt(4 * positive_integer + 1						) / 2 + 1 / 2						)

      return exponent == int(lowerCAmelCase__						)


def      UpperCAmelCase__			(							lowerCAmelCase__	:float = 1 / 1_2_3_4_5						)					->       int:
      '''simple docstring'''


      lowercase								=      0
      lowercase								=      0

      lowercase								=      3
      while True:
            lowercase								=      (integer**2 - 1) / 4
            # if candidate is an integer, then there is a partition for k
            if partition_candidate == int(lowerCAmelCase__						):
                  lowercase								=      int(lowerCAmelCase__						)
                  total_partitions += 1
                  if check_partition_perfect(lowerCAmelCase__						):
                        perfect_partitions += 1
            if perfect_partitions > 0:
                  if perfect_partitions / total_partitions < max_proportion:
                        return int(lowerCAmelCase__						)
            integer += 1


if __name__ == "__main__":
       print(F"""{solution() = }""")



