
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 				lowercase		(					SCREAMING_SNAKE_CASE__		):




							def __init__(				self   ,A__   ,A__   ,A__ = None   ,A__ = None   ,A__ = False   ,**A__   ,):
												super().__init__(features=A__   ,cache_dir=A__   ,keep_in_memory=A__   ,**A__)
												lowercase							=						Sql(
												    cache_dir=A__   ,features=A__   ,sql=A__   ,con=A__   ,**A__   ,)





							def  A__      (				self):
												lowercase							=						None
												lowercase							=						None
												lowercase							=						None
												lowercase							=						None

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

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







class 				lowercase		:




							def __init__(				self   ,A__   ,A__   ,A__   ,A__ = None   ,A__ = None   ,**A__   ,):
												if num_proc is not None and num_proc <= 0:
																	raise ValueError(f'num_proc {num_proc} must be an integer > 0.')

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




							def  A__      (				self):
												lowercase							=						self.to_sql_kwargs.pop('''sql'''   ,A__)
												lowercase							=						self.to_sql_kwargs.pop('''con'''   ,A__)
												lowercase							=						self.to_sql_kwargs.pop('''index'''   ,A__)

												lowercase							=						self._write(index=A__   ,**self.to_sql_kwargs)
												return written




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





							def  A__      (				self   ,A__   ,**A__):
												lowercase							=						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							=						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   ,A__   ,A__)]   ,)   ,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






from functools import lru_cache



@lru_cache
def        UpperCamelCase    (							lowerCAmelCase__		):
					'''simple docstring'''
					if num < 0:
										raise ValueError('''Number should not be negative.'''		)

					return 1 if num in (0, 1) else num * factorial(num - 1		)


if __name__ == "__main__":
							import doctest

							doctest.testmod()




