




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     __lowerCAmelCase (       lowerCAmelCase__ ):

			"""simple docstring"""







			def __init__(      self			,						lowerCamelCase__			,						lowerCamelCase__			,						lowerCamelCase__ = None			,						lowerCamelCase__ = None			,						lowerCamelCase__ = False			,						**lowerCamelCase__			,						)    ->      List[Any]:



							'''simple docstring'''
							super().__init__(features=UpperCamelCase__			,						cache_dir=UpperCamelCase__			,						keep_in_memory=UpperCamelCase__			,						**UpperCamelCase__							)
							__lowerCamelCase		       =    Sql(
							    cache_dir=UpperCamelCase__			,						features=UpperCamelCase__			,						sql=UpperCamelCase__			,						con=UpperCamelCase__			,						**UpperCamelCase__			,						)






			def       lowercase_    (      self							)    ->      List[Any]:



							'''simple docstring'''
							__lowerCamelCase		       =    None
							__lowerCamelCase		       =    None
							__lowerCamelCase		       =    None
							__lowerCamelCase		       =    None

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

							# Build dataset for splits
							__lowerCamelCase		       =    self.builder.as_dataset(
							    split='train'			,						verification_mode=UpperCamelCase__			,						in_memory=self.keep_in_memory							)
							return dataset







class     __lowerCAmelCase :

			"""simple docstring"""







			def __init__(      self			,						lowerCamelCase__			,						lowerCamelCase__			,						lowerCamelCase__			,						lowerCamelCase__ = None			,						lowerCamelCase__ = None			,						**lowerCamelCase__			,						)    ->      Any:



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

							__lowerCamelCase		       =    dataset
							__lowerCamelCase		       =    name
							__lowerCamelCase		       =    con
							__lowerCamelCase		       =    batch_size if batch_size else config.DEFAULT_MAX_BATCH_SIZE
							__lowerCamelCase		       =    num_proc
							__lowerCamelCase		       =    to_sql_kwargs


			def       lowercase_    (      self							)    ->      int:



							'''simple docstring'''
							__lowerCamelCase		       =    self.to_sql_kwargs.pop('sql'			,						UpperCamelCase__							)
							__lowerCamelCase		       =    self.to_sql_kwargs.pop('con'			,						UpperCamelCase__							)
							__lowerCamelCase		       =    self.to_sql_kwargs.pop('index'			,						UpperCamelCase__							)

							__lowerCamelCase		       =    self._write(index=UpperCamelCase__			,						**self.to_sql_kwargs							)
							return written


			def       lowercase_    (      self			,						lowerCamelCase__							)    ->      str:



							'''simple docstring'''
							__lowerCamelCase		       =    args
							__lowerCamelCase		       =    {**to_sql_kwargs, "if_exists": "append"} if offset > 0 else to_sql_kwargs
							__lowerCamelCase		       =    query_table(
							    table=self.dataset.data			,						key=slice(UpperCamelCase__			,						offset + self.batch_size							)			,						indices=self.dataset._indices			,						)
							__lowerCamelCase		       =    batch.to_pandas()
							__lowerCamelCase		       =    df.to_sql(self.name			,						self.con			,						index=UpperCamelCase__			,						**UpperCamelCase__							)
							return num_rows or len(UpperCamelCase__							)






			def       lowercase_    (      self			,						lowerCamelCase__			,						**lowerCamelCase__							)    ->      int:



							'''simple docstring'''
							__lowerCamelCase		       =    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:
											__lowerCamelCase		       =    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			,						UpperCamelCase__			,						UpperCamelCase__							)]			,						)			,						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








def      A      (      _SCREAMING_SNAKE_CASE ,_SCREAMING_SNAKE_CASE    )	-> Any:
       # "extended trapezoidal rule"
       # int(f) = dx/2 * (f1 + 2f2 + ... + fn)
       lowerCamelCase   :      str			 =					(boundary[1] - boundary[0]) / steps
       lowerCamelCase   :      List[str]			 =					boundary[0]
       lowerCamelCase   :      Union[str, Any]			 =					boundary[1]
       lowerCamelCase   :      int			 =					make_points(_SCREAMING_SNAKE_CASE ,_SCREAMING_SNAKE_CASE ,_SCREAMING_SNAKE_CASE    )
       lowerCamelCase   :      List[str]			 =					0.0
       y += (h / 2.0) * f(_SCREAMING_SNAKE_CASE    )
       for i in x_i:
              # print(i)
              y += h * f(_SCREAMING_SNAKE_CASE    )
       y += (h / 2.0) * f(_SCREAMING_SNAKE_CASE    )
       return y

def      A      (      _SCREAMING_SNAKE_CASE ,_SCREAMING_SNAKE_CASE ,_SCREAMING_SNAKE_CASE    )	-> int:
       lowerCamelCase   :      int			 =					a + h
       while x < (b - h):
              yield x
              lowerCamelCase   :      List[str]			 =					x + h

def      A      (      _SCREAMING_SNAKE_CASE    )	-> Optional[Any]:  # enter your function here
       lowerCamelCase   :      str			 =					(x - 0) * (x - 0)
       return y

def      A      (      )	-> int:
       lowerCamelCase   :      int			 =					0.0  # Lower bound of integration
       lowerCamelCase   :      int			 =					1.0  # Upper bound of integration
       lowerCamelCase   :      Dict			 =					10.0  # define number of steps or resolution
       lowerCamelCase   :      int			 =					[a, b]  # define boundary of integration
       lowerCamelCase   :      str			 =					method_a(_SCREAMING_SNAKE_CASE ,_SCREAMING_SNAKE_CASE    )
       print(f'''y = {y}'''    )


if __name__ == "__main__":
       main()






