



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			(					lowercase__):




				def __init__(						self					:						List[str],					__lowercase					:						Union[str, "sqlalchemy.sql.Selectable"],					__lowercase					:						Union[str, "sqlalchemy.engine.Connection", "sqlalchemy.engine.Engine", "sqlite3.Connection"],					__lowercase					:						Optional[Features] = None,					__lowercase					:						str = None,					__lowercase					:						bool = False,					**__lowercase					:						Dict,					):
							super().__init__(features=__lowercase,					cache_dir=__lowercase,					keep_in_memory=__lowercase,					**__lowercase						)
							lowercase__					  =				Sql(
							    cache_dir=__lowercase,					features=__lowercase,					sql=__lowercase,					con=__lowercase,					**__lowercase,					)




				def 							A__      (						self					:						Optional[Any]						):
							lowercase__					  =				None
							lowercase__					  =				None
							lowercase__					  =				None
							lowercase__					  =				None

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

							# Build dataset for splits
							lowercase__					  =				self.builder.as_dataset(
							    split="train",					verification_mode=__lowercase,					in_memory=self.keep_in_memory						)
							return dataset
class 				_snake_case			:




				def __init__(						self					:						Any,					__lowercase					:						Dataset,					__lowercase					:						str,					__lowercase					:						Union[str, "sqlalchemy.engine.Connection", "sqlalchemy.engine.Engine", "sqlite3.Connection"],					__lowercase					:						Optional[int] = None,					__lowercase					:						Optional[int] = None,					**__lowercase					:						Optional[Any],					):
							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					:						List[str]						):
							lowercase__					  =				self.to_sql_kwargs.pop("sql",					__lowercase						)
							lowercase__					  =				self.to_sql_kwargs.pop("con",					__lowercase						)
							lowercase__					  =				self.to_sql_kwargs.pop("index",					__lowercase						)

							lowercase__					  =				self._write(index=__lowercase,					**self.to_sql_kwargs						)
							return written




				def 							A__      (						self					:						Optional[int],					__lowercase					:						Any						):
							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(__lowercase,					offset + self.batch_size						),					indices=self.dataset._indices,					)
							lowercase__					  =				batch.to_pandas()
							lowercase__					  =				df.to_sql(self.name,					self.con,					index=__lowercase,					**__lowercase						)
							return num_rows or len(__lowercase						)




				def 							A__      (						self					:						int,					__lowercase					:						int,					**__lowercase					:						Dict						):
							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,					__lowercase,					__lowercase						)],					),					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 __lowerCAmelCase (     SCREAMING_SNAKE_CASE_  ):
			if upper_limit < 0:
						raise ValueError("Limit for the Catalan sequence must be ≥ 0"  )

			lowercase__					  =				[0] * (upper_limit + 1)

			# Base case: C(0) = C(1) = 1
			lowercase__					  =				1
			if upper_limit > 0:
						lowercase__					  =				1

			# Recurrence relation: C(i) = sum(C(j).C(i-j-1)), from j = 0 to i
			for i in range(2						,  upper_limit + 1  ):
						for j in range(SCREAMING_SNAKE_CASE_  ):
									catalan_list[i] += catalan_list[j] * catalan_list[i - j - 1]

			return catalan_list


if __name__ == "__main__":
							print("""\n********* Catalan Numbers Using Dynamic Programming ************\n""")
							print("""\n*** Enter -1 at any time to quit ***""")
							print("""\nEnter the upper limit (≥ 0) for the Catalan number sequence: """, end="""""")
							try:
														while True:
																					lowercase_								=     int(input().strip())
																					if N < 0:
																												print("""\n********* Goodbye!! ************""")
																												break
																					else:
																												print(F'The Catalan numbers from 0 through {N} are:')
																												print(catalan_numbers(N))
																												print("""Try another upper limit for the sequence: """, end="""""")
							except (NameError, ValueError):
														print("""\n********* Invalid input, goodbye! ************\n""")

							import doctest

							doctest.testmod()




